Endometrial Endometrioid Adenocarcinoma

MONDO:0006192 Pathograph 13 endometrial carcinoma

Endometrial endometrioid adenocarcinoma is a gland-forming epithelial malignancy of the endometrium and the most common histologic subtype of endometrial carcinoma. Its pathobiology integrates estrogen-responsive endometrial epithelial proliferation, recurrent PTEN/PI3K-pathway and WNT-pathway driver alterations, mismatch-repair and POLE-mutated hypermutator subsets, and p53-abnormal high-risk disease. Current management combines hysterectomy-based local therapy, histopathologic grading and staging, and molecular classification using POLE sequencing plus MMR and p53 immunohistochemistry.

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2
Mappings
1
Definitions
0
Inheritance
8
Pathophysiology
2
Histopathology
3
Phenotypes
13
Pathograph
7
Genes
5
Treatments
4
Subtypes
0
Differentials
0
Datasets
0
Trials
0
Models
1
Deep Research
🔗

Mappings

MONDO
MONDO:0006192 endometrial endometrioid adenocarcinoma
skos:exactMatch MONDO
OAK confirmed MONDO:0006192 as the exact disease label for this entry.
NCIT
NCIT:C6287 Endometrial Endometrioid Adenocarcinoma
skos:exactMatch MONDO xref
MONDO:0006192 includes NCIT:C6287 as an xref for endometrial endometrioid adenocarcinoma.
NCIT
NCIT:C6287 Endometrial Endometrioid Adenocarcinoma
skos:exactMatch MONDO xref
MONDO:0006192 includes NCIT:C6287 as an xref for endometrial endometrioid adenocarcinoma.
📘

Definitions

1
Clinicopathologic definition
A primary endometrial carcinoma with endometrioid glandular morphology, evaluated by histologic subtype, tumor grade, stage, lymphovascular invasion, and molecular class.
CASE_DEFINITION Adult gynecologic oncology and surgical pathology definition
Show evidence (1 reference)
PMID:26354523 SUPPORT Human Clinical
"Endometrial cancer is the most common gynaecological tumour in developed countries, and its incidence is increasing. The most frequently occurring histological subtype is endometrioid adenocarcinoma."
This review identifies endometrioid adenocarcinoma as the common histologic subtype within endometrial cancer.
◆

Subtypes

4
POLE-ultramutated endometrioid carcinoma
Tumors with pathogenic POLE exonuclease-domain mutation and an ultramutated phenotype; this class generally has favorable prognosis and is prioritized in current molecular classification algorithms.
Show evidence (1 reference)
PMID:23636398 SUPPORT Human Clinical
"A subset of endometrioid tumours that we identified had a markedly increased transversion mutation frequency and newly identified hotspot mutations in POLE."
TCGA directly identifies a POLE-hotspot ultramutated subset of endometrioid tumors.
Mismatch repair-deficient or MSI-hypermutated endometrioid carcinoma
Tumors with mismatch-repair deficiency or microsatellite instability, often detected by MLH1, PMS2, MSH2, and MSH6 immunohistochemistry and relevant to Lynch syndrome screening and immune-checkpoint therapy selection.
Show evidence (1 reference)
DOI:10.3390/ijms25021056 SUPPORT Human Clinical
"Immunohistochemistry for MMR proteins (MLH1, MSH2, MSH6 and PMS2) has become the optimal diagnostic MSI surrogate worldwide."
This supports the practical diagnostic marker set for the MMR-deficient molecular subtype.
No specific molecular profile or copy-number-low endometrioid carcinoma
Tumors without POLE mutation, MMR deficiency, or p53 abnormality. This group overlaps strongly with copy-number-low endometrioid cancers and remains heterogeneous, with prognosis influenced by conventional pathologic features.
Show evidence (1 reference)
DOI:10.3390/jpm13050723 SUPPORT Human Clinical
"ECs were classified using immunohistochemistry and next-generation sequencing into the four molecular classes: POLE mutant (POLE), mismatch repair deficient (MMRd), p53 mutant (p53abn), and no specific molecular profile (NSMP)."
This cohort describes the operational four-class molecular classifier that includes NSMP.
p53-abnormal high-risk endometrioid carcinoma
Tumors with abnormal p53 pattern or TP53-altered copy-number-high biology. This class includes a subset of high-grade endometrioid carcinomas with more aggressive behavior and FIGO 2023 molecular stage implications.
Show evidence (1 reference)
PMID:23636398 SUPPORT Human Clinical
"Uterine serous tumours and ∼25% of high-grade endometrioid tumours had extensive copy number alterations, few DNA methylation changes, low oestrogen receptor/progesterone receptor levels, and frequent TP53 mutations."
TCGA shows that a subset of high-grade endometrioid tumors has copy-number-high, TP53-mutated biology.
⚙

Pathophysiology

8
Unopposed Estrogen Signaling
Hyperestrogenic states promote mitogenic estrogen receptor signaling in endometrial glandular epithelium when progesterone counter-regulation is insufficient, increasing the proliferative substrate for endometrioid malignant transformation.
endometrial epithelial cell link
estrogen receptor signaling pathway link ↑ INCREASED
endometrium link
Downstream
Endometrial Hyperplasia Precursor Estrogen-driven proliferation increases risk of hyperplasia and malignant progression.
Show evidence (1 reference)
PMID:12496040 SUPPORT Human Clinical
"endometrial cancer may develop as a result of the mitogenic effects of estrogens, when these are insufficiently counterbalanced by progesterone."
The cited review directly supports unopposed estrogen as a mechanistic model for endometrial cancer risk.
Endometrial Hyperplasia Precursor
Progesterone deficiency and sustained estrogen-driven epithelial expansion can produce endometrial hyperplasia, which is a precursor context for endometrioid carcinoma.
endometrial epithelial cell link
cell population proliferation link ↑ INCREASED
endometrium link
Downstream
PTEN PI3K Pathway Dysregulation Proliferative precursor epithelium provides a substrate for somatic driver selection.
Show evidence (1 reference)
PMID:21802066 SUPPORT Human Clinical
"Conditions that are accompanied by prolonged progesterone deficiencies therefore promote endometrial proliferation and increase the risk of endometrial hyperplasia and its progression to endometrial cancer"
This full-text review links progesterone deficiency to endometrial proliferation, hyperplasia, and progression to cancer.
PTEN PI3K Pathway Dysregulation
Endometrioid tumors commonly acquire PTEN, PIK3CA, and cooperating pathway alterations that support survival and growth through PI3K/AKT signaling.
endometrial epithelial cell link
PTEN link PIK3CA link
phosphatidylinositol 3-kinase/protein kinase B signal transduction link ↑ INCREASED
Downstream
Endometrioid Glandular Neoplasia Somatic pathway lesions support malignant outgrowth of endometrioid gland-forming epithelium.
Show evidence (1 reference)
PMID:23636398 SUPPORT Human Clinical
"Most endometrioid tumours had few copy number alterations or TP53 mutations, but frequent mutations in PTEN, CTNNB1, PIK3CA, ARID1A and KRAS"
TCGA identifies recurrent PTEN and PIK3CA alterations in endometrioid tumors, supporting this driver pathway.
WNT Beta-Catenin Pathway Dysregulation
CTNNB1-mutant WNT pathway activation is a recurrent molecular feature of endometrioid tumors and contributes to altered transcriptional control and tumor progression.
CTNNB1 link
Wnt signaling pathway link ↕ DYSREGULATED
Downstream
Endometrioid Glandular Neoplasia Aberrant beta-catenin signaling contributes to malignant endometrioid epithelial behavior.
Show evidence (1 reference)
PMID:23636398 SUPPORT Human Clinical
"Most endometrioid tumours had few copy number alterations or TP53 mutations, but frequent mutations in PTEN, CTNNB1, PIK3CA, ARID1A and KRAS"
TCGA supports CTNNB1 as a recurrently mutated driver in endometrioid endometrial tumors.
Mismatch Repair Deficiency
Loss of DNA mismatch repair creates microsatellite-instability and hypermutated tumor biology, commonly detected by loss of MMR protein expression by immunohistochemistry.
MLH1 link MSH2 link MSH6 link PMS2 link
mismatch repair link ↓ DECREASED
Downstream
Immune Checkpoint Vulnerability Hypermutated tumors create immunotherapy-relevant tumor antigenicity.
Show evidence (1 reference)
DOI:10.3390/ijms25021056 SUPPORT Human Clinical
"Among the four endometrial cancer (EC) TCGA molecular groups, the MSI/hypermutated group represents an important percentage of tumors (30%), including different histotypes, and generally confers an intermediate prognosis for affected women, also providing new immunotherapeutic strategies."
The review links the MSI/hypermutated class to MMR-deficient endometrial cancer biology and immunotherapy implications.
POLE Ultramutation
Pathogenic POLE exonuclease-domain mutation produces an ultramutated endometrioid tumor subset with distinctive prognosis and staging implications.
POLE link
DNA replication proofreading link ↓ DECREASED
Downstream
Immune Checkpoint Vulnerability High mutational burden can create immunogenic tumor features.
Show evidence (1 reference)
PMID:23636398 SUPPORT Human Clinical
"A subset of endometrioid tumours that we identified had a markedly increased transversion mutation frequency and newly identified hotspot mutations in POLE."
TCGA directly supports POLE hotspot mutation as a hypermutator mechanism in a subset of endometrioid tumors.
Immune Checkpoint Vulnerability
Hypermutated MMRd/MSI-H and POLE-mutated tumors are clinically important immunotherapy-sensitive contexts in advanced or recurrent endometrial cancer.
immune response link ↑ INCREASED
Show evidence (1 reference)
PMID:36972022 SUPPORT Human Clinical
"In patients with advanced or recurrent endometrial cancer, the addition of pembrolizumab to standard chemotherapy resulted in significantly longer progression-free survival than with chemotherapy alone."
The phase 3 NRG-GY018 trial supports immune checkpoint blockade combined with chemotherapy as a clinically effective strategy in advanced or recurrent endometrial cancer.
Endometrioid Glandular Neoplasia
Malignant endometrial epithelial cells form endometrioid glandular architecture, with tumor grade reflecting the amount of solid growth and loss of gland formation.
endometrial epithelial cell link
endometrium link
✶

Histopathology

2
Endometrioid Adenocarcinoma
Endometrioid gland-forming morphology is the defining histopathologic pattern of this disease.
Show evidence (1 reference)
PMID:26354523 SUPPORT Human Clinical
"The most frequently occurring histological subtype is endometrioid adenocarcinoma."
This directly supports endometrioid adenocarcinoma as the core histologic diagnosis.
High-Grade Endometrioid Carcinoma
High-grade endometrioid tumors can overlap molecularly with copy-number-high serous-like cancer and may have frequent TP53 mutation.
Show evidence (1 reference)
PMID:23636398 SUPPORT Human Clinical
"Uterine serous tumours and ∼25% of high-grade endometrioid tumours had extensive copy number alterations, few DNA methylation changes, low oestrogen receptor/progesterone receptor levels, and frequent TP53 mutations."
TCGA supports that a subset of high-grade endometrioid tumors has copy-number-high and TP53-mutated biology.
⬡

Pathograph

Use the checkboxes to hide or show graph categories. Hover nodes for evidence and cross-linked metadata.
Pathograph: causal mechanism network for Endometrial Endometrioid Adenocarcinoma Interactive directed graph showing how pathophysiology mechanisms, phenotypes, genetic factors and variants, experimental models, environmental triggers, and treatments relate through causal and linked edges.
●

Phenotypes

3
Blood 1
Anemia Anemia (HP:0001903)
Constitutional 1
Pelvic Pain Pelvic pain (HP:0034267)
Other 1
Postmenopausal Bleeding Postmenopausal bleeding (HP:0033840)
Show evidence (1 reference)
PMID:26354523 PARTIAL Human Clinical
"Patients are often diagnosed when the disease is still confined to the uterus."
This does not name bleeding directly, but supports the early clinical detection context typical of endometrial carcinoma; frequency is omitted.
🧬

Genetic Associations

7
PTEN (Recurrent somatic driver alteration)
Show evidence (1 reference)
PMID:23636398 SUPPORT Human Clinical
"Most endometrioid tumours had few copy number alterations or TP53 mutations, but frequent mutations in PTEN, CTNNB1, PIK3CA, ARID1A and KRAS"
TCGA identifies PTEN among recurrently mutated genes in endometrioid tumors.
PIK3CA (Recurrent somatic PI3K-pathway driver alteration)
Show evidence (1 reference)
PMID:23636398 SUPPORT Human Clinical
"Most endometrioid tumours had few copy number alterations or TP53 mutations, but frequent mutations in PTEN, CTNNB1, PIK3CA, ARID1A and KRAS"
TCGA identifies PIK3CA among recurrently mutated genes in endometrioid tumors.
CTNNB1 (Recurrent somatic WNT pathway driver alteration)
Show evidence (1 reference)
PMID:23636398 SUPPORT Human Clinical
"Most endometrioid tumours had few copy number alterations or TP53 mutations, but frequent mutations in PTEN, CTNNB1, PIK3CA, ARID1A and KRAS"
TCGA identifies CTNNB1 among recurrently mutated genes in endometrioid tumors.
ARID1A (Recurrent somatic chromatin remodeling driver alteration)
Show evidence (1 reference)
PMID:23636398 SUPPORT Human Clinical
"Most endometrioid tumours had few copy number alterations or TP53 mutations, but frequent mutations in PTEN, CTNNB1, PIK3CA, ARID1A and KRAS"
TCGA identifies ARID1A among recurrently mutated genes in endometrioid tumors.
KRAS (Recurrent somatic RAS pathway driver alteration)
Show evidence (1 reference)
PMID:23636398 SUPPORT Human Clinical
"Most endometrioid tumours had few copy number alterations or TP53 mutations, but frequent mutations in PTEN, CTNNB1, PIK3CA, ARID1A and KRAS"
TCGA identifies KRAS among recurrently mutated genes in endometrioid tumors.
TP53 (Somatic p53-abnormal high-risk alteration)
Show evidence (1 reference)
PMID:23636398 SUPPORT Human Clinical
"Uterine serous tumours and ∼25% of high-grade endometrioid tumours had extensive copy number alterations, few DNA methylation changes, low oestrogen receptor/progesterone receptor levels, and frequent TP53 mutations."
TCGA supports TP53 mutation in a copy-number-high subset of high-grade endometrioid tumors.
MLH1, MSH2, MSH6, and PMS2 (Germline or somatic mismatch repair pathway deficiency)
Show evidence (1 reference)
DOI:10.3390/ijms25021056 SUPPORT Human Clinical
"Immunohistochemistry for MMR proteins (MLH1, MSH2, MSH6 and PMS2) has become the optimal diagnostic MSI surrogate worldwide."
The review identifies the four MMR proteins that define routine MMRd assessment.
💊

Treatments

5
Hysterectomy With Bilateral Salpingo-Oophorectomy
Action: surgical procedure MAXO:0000004
Primary hysterectomy with bilateral salpingo-oophorectomy is standard local treatment for many patients, with staging and nodal assessment tailored by histology, grade, LVSI, stage, patient factors, and guidelines.
Show evidence (1 reference)
PMID:26354523 SUPPORT Human Clinical
"Standard treatment consists of primary hysterectomy and bilateral salpingo-oophorectomy, often using minimally invasive approaches (laparoscopic or robotic)."
This review directly supports hysterectomy with bilateral salpingo-oophorectomy as standard treatment.
Adjuvant Radiation Therapy
Action: radiation therapy MAXO:0000014
Adjuvant radiation or chemoradiation is selected according to integrated recurrence risk, including stage, histology, grade, LVSI, and molecular class.
Show evidence (1 reference)
PMID:26354523 SUPPORT Human Clinical
"Adjuvant treatment is tailored according to histology and stage."
This supports postoperative tailoring of adjuvant therapy in endometrial cancer; the description adds molecular-risk context from newer staging evidence.
Carboplatin-Paclitaxel Chemotherapy
Action: chemotherapy MAXO:0000647
Agent: carboplatin ↗ paclitaxel ↗
Carboplatin plus paclitaxel is the standard chemotherapy backbone used in advanced or recurrent endometrial cancer trials and combined with immune-checkpoint inhibitors in current phase 3 evidence.
Show evidence (1 reference)
PMID:36972022 SUPPORT Human Clinical
"Standard first-line chemotherapy for endometrial cancer is paclitaxel plus carboplatin."
The NRG-GY018 abstract identifies paclitaxel plus carboplatin as standard first-line chemotherapy.
Pembrolizumab Plus Carboplatin-Paclitaxel
Action: pharmacotherapy MAXO:0000058
Agent: pembrolizumab ↗ carboplatin ↗ paclitaxel ↗
PD-1 blockade with pembrolizumab plus carboplatin-paclitaxel improves progression-free survival in advanced or recurrent endometrial cancer, with strong relevance for dMMR tumors.
Mechanism Target:
INHIBITS Immune Checkpoint Vulnerability — PD-1 blockade is intended to counter tumor immune checkpoint signaling.
Show evidence (1 reference)
PMID:36972022 SUPPORT Human Clinical
"In patients with advanced or recurrent endometrial cancer, the addition of pembrolizumab to standard chemotherapy resulted in significantly longer progression-free survival than with chemotherapy alone."
This phase 3 trial supports pembrolizumab plus chemotherapy in advanced or recurrent endometrial cancer.
Dostarlimab Plus Carboplatin-Paclitaxel
Action: pharmacotherapy MAXO:0000058
Agent: dostarlimab ↗ carboplatin ↗ paclitaxel ↗
Dostarlimab combined with carboplatin-paclitaxel improves progression-free survival in primary advanced or recurrent endometrial cancer, with a substantial benefit in dMMR-MSI-H tumors.
Mechanism Target:
INHIBITS Immune Checkpoint Vulnerability — PD-1 blockade is intended to counter tumor immune checkpoint signaling.
Show evidence (1 reference)
PMID:36972026 SUPPORT Human Clinical
"Dostarlimab plus carboplatin-paclitaxel significantly increased progression-free survival among patients with primary advanced or recurrent endometrial cancer, with a substantial benefit in the dMMR-MSI-H population."
This phase 3 trial supports dostarlimab plus chemotherapy in primary advanced or recurrent disease, especially dMMR-MSI-H tumors.
🌍

Environmental Factors

1
Obesity and Metabolic Dysfunction
Obesity increases risk for estrogen-dependent endometrioid carcinoma through elevated adipocyte-derived estrogen and inflammatory/metabolic changes.
Show evidence (1 reference)
DOI:10.3390/cancers16122197 SUPPORT Human Clinical
"Endometrial cancer (EC) includes various histologic types, with estrogen-dependent endometrioid carcinoma being the most common. Obesity significantly increases the risk of developing this type, especially in postmenopausal women, due to elevated estrogen production by adipocytes."
This recent systematic review directly connects obesity, adipocyte-derived estrogen, and risk of estrogen-dependent endometrioid carcinoma.
🔬

Biochemical Markers

3
MMR Protein Immunohistochemistry
Show evidence (1 reference)
DOI:10.3390/ijms25021056 SUPPORT Human Clinical
"Immunohistochemistry for MMR proteins (MLH1, MSH2, MSH6 and PMS2) has become the optimal diagnostic MSI surrogate worldwide."
This supports MMR IHC as a core diagnostic and predictive biomarker assay.
p53 Immunohistochemistry
Show evidence (1 reference)
DOI:10.3390/jpm13050723 SUPPORT Human Clinical
"ECs were classified using immunohistochemistry and next-generation sequencing into the four molecular classes: POLE mutant (POLE), mismatch repair deficient (MMRd), p53 mutant (p53abn), and no specific molecular profile (NSMP)."
This supports immunohistochemistry plus sequencing as the practical route for p53abn classification.
POLE Sequencing
Show evidence (1 reference)
DOI:10.1002/ijgo.14923 SUPPORT Human Clinical
"The performance of complete molecular classification (POLEmut, MMRd, NSMP, p53abn) is encouraged in all endometrial cancers."
FIGO 2023 supports complete molecular classification including POLEmut status.
{ }

Source YAML

click to show 
name: Endometrial Endometrioid Adenocarcinoma
creation_date: "2026-05-08T13:19:00Z"
updated_date: "2026-05-08T14:06:05Z"
synonyms:
- Endometrioid adenocarcinoma of the endometrium
- Endometrioid endometrial adenocarcinoma
- Endometrioid carcinoma of the endometrium
- Uterine corpus endometrioid adenocarcinoma
description: >-
  Endometrial endometrioid adenocarcinoma is a gland-forming epithelial
  malignancy of the endometrium and the most common histologic subtype of
  endometrial carcinoma. Its pathobiology integrates estrogen-responsive
  endometrial epithelial proliferation, recurrent PTEN/PI3K-pathway and
  WNT-pathway driver alterations, mismatch-repair and POLE-mutated hypermutator
  subsets, and p53-abnormal high-risk disease. Current management combines
  hysterectomy-based local therapy, histopathologic grading and staging, and
  molecular classification using POLE sequencing plus MMR and p53
  immunohistochemistry.
categories:
- Gynecologic Malignancy
- Adenocarcinoma
- Solid Tumor
- Molecularly-Defined Cancer
parents:
- endometrial carcinoma
disease_term:
  preferred_term: endometrial endometrioid adenocarcinoma
  term:
    id: MONDO:0006192
    label: endometrial endometrioid adenocarcinoma
definitions:
- name: Clinicopathologic definition
  definition_type: CASE_DEFINITION
  description: >-
    A primary endometrial carcinoma with endometrioid glandular morphology,
    evaluated by histologic subtype, tumor grade, stage, lymphovascular invasion,
    and molecular class.
  scope: Adult gynecologic oncology and surgical pathology definition
  evidence:
  - reference: PMID:26354523
    reference_title: "Endometrial cancer."
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: "Endometrial cancer is the most common gynaecological tumour in developed countries, and its incidence is increasing. The most frequently occurring histological subtype is endometrioid adenocarcinoma."
    explanation: >-
      This review identifies endometrioid adenocarcinoma as the common
      histologic subtype within endometrial cancer.
has_subtypes:
- name: POLEmut
  display_name: POLE-ultramutated endometrioid carcinoma
  classification: molecular
  description: >-
    Tumors with pathogenic POLE exonuclease-domain mutation and an ultramutated
    phenotype; this class generally has favorable prognosis and is prioritized
    in current molecular classification algorithms.
  evidence:
  - reference: PMID:23636398
    reference_title: "Integrated genomic characterization of endometrial carcinoma."
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: "A subset of endometrioid tumours that we identified had a markedly increased transversion mutation frequency and newly identified hotspot mutations in POLE."
    explanation: >-
      TCGA directly identifies a POLE-hotspot ultramutated subset of
      endometrioid tumors.
- name: MMRd
  display_name: Mismatch repair-deficient or MSI-hypermutated endometrioid carcinoma
  classification: molecular
  description: >-
    Tumors with mismatch-repair deficiency or microsatellite instability, often
    detected by MLH1, PMS2, MSH2, and MSH6 immunohistochemistry and relevant to
    Lynch syndrome screening and immune-checkpoint therapy selection.
  evidence:
  - reference: DOI:10.3390/ijms25021056
    reference_title: "Mismatch Repair Deficiency as a Predictive and Prognostic Biomarker in Endometrial Cancer: A Review on Immunohistochemistry Staining Patterns and Clinical Implications"
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: "Immunohistochemistry for MMR proteins (MLH1, MSH2, MSH6 and PMS2) has become the optimal diagnostic MSI surrogate worldwide."
    explanation: >-
      This supports the practical diagnostic marker set for the MMR-deficient
      molecular subtype.
- name: NSMP
  display_name: No specific molecular profile or copy-number-low endometrioid carcinoma
  classification: molecular
  description: >-
    Tumors without POLE mutation, MMR deficiency, or p53 abnormality. This group
    overlaps strongly with copy-number-low endometrioid cancers and remains
    heterogeneous, with prognosis influenced by conventional pathologic features.
  evidence:
  - reference: DOI:10.3390/jpm13050723
    reference_title: "Prognostic Impact of Pathologic Features in Molecular Subgroups of Endometrial Carcinoma"
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: "ECs were classified using immunohistochemistry and next-generation sequencing into the four molecular classes: POLE mutant (POLE), mismatch repair deficient (MMRd), p53 mutant (p53abn), and no specific molecular profile (NSMP)."
    explanation: >-
      This cohort describes the operational four-class molecular classifier
      that includes NSMP.
- name: p53abn
  display_name: p53-abnormal high-risk endometrioid carcinoma
  classification: molecular
  description: >-
    Tumors with abnormal p53 pattern or TP53-altered copy-number-high biology.
    This class includes a subset of high-grade endometrioid carcinomas with more
    aggressive behavior and FIGO 2023 molecular stage implications.
  evidence:
  - reference: PMID:23636398
    reference_title: "Integrated genomic characterization of endometrial carcinoma."
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: "Uterine serous tumours and ∼25% of high-grade endometrioid tumours had extensive copy number alterations, few DNA methylation changes, low oestrogen receptor/progesterone receptor levels, and frequent TP53 mutations."
    explanation: >-
      TCGA shows that a subset of high-grade endometrioid tumors has
      copy-number-high, TP53-mutated biology.
stages:
- name: FIGO 2023 Stage I-II Molecular Modification
  description: >-
    FIGO 2023 records molecular subtype in the stage when known and can downstage
    POLE-mutated early disease or upstage p53-abnormal early disease.
  evidence:
  - reference: DOI:10.1002/ijgo.14923
    reference_title: "FIGO staging of endometrial cancer: 2023"
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: "When molecular classification reveals p53abn or POLEmut status in Stages I and II, this results in upstaging or downstaging of the disease (IICmp53abn or IAmPOLEmut)."
    explanation: >-
      FIGO 2023 explicitly modifies early-stage endometrial cancer by p53abn and
      POLEmut molecular status.
pathophysiology:
- name: Unopposed Estrogen Signaling
  description: >-
    Hyperestrogenic states promote mitogenic estrogen receptor signaling in
    endometrial glandular epithelium when progesterone counter-regulation is
    insufficient, increasing the proliferative substrate for endometrioid
    malignant transformation.
  evidence:
  - reference: PMID:12496040
    reference_title: "Obesity, endogenous hormones, and endometrial cancer risk: a synthetic review."
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: "endometrial cancer may develop as a result of the mitogenic effects of estrogens, when these are insufficiently counterbalanced by progesterone."
    explanation: >-
      The cited review directly supports unopposed estrogen as a mechanistic
      model for endometrial cancer risk.
  cell_types:
  - preferred_term: endometrial epithelial cell
    term:
      id: CL:0002656
      label: glandular endometrial unciliated epithelial cell
  locations:
  - preferred_term: endometrium
    term:
      id: UBERON:0001295
      label: endometrium
  biological_processes:
  - preferred_term: estrogen receptor signaling pathway
    modifier: INCREASED
    term:
      id: GO:0030520
      label: estrogen receptor signaling pathway
  downstream:
  - target: Endometrial Hyperplasia Precursor
    description: Estrogen-driven proliferation increases risk of hyperplasia and malignant progression.
- name: Endometrial Hyperplasia Precursor
  description: >-
    Progesterone deficiency and sustained estrogen-driven epithelial expansion
    can produce endometrial hyperplasia, which is a precursor context for
    endometrioid carcinoma.
  evidence:
  - reference: PMID:21802066
    reference_title: "Understanding obesity and endometrial cancer risk: opportunities for prevention."
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: "Conditions that are accompanied by prolonged progesterone deficiencies therefore promote endometrial proliferation and increase the risk of endometrial hyperplasia and its progression to endometrial cancer"
    explanation: >-
      This full-text review links progesterone deficiency to endometrial
      proliferation, hyperplasia, and progression to cancer.
  cell_types:
  - preferred_term: endometrial epithelial cell
    term:
      id: CL:0002656
      label: glandular endometrial unciliated epithelial cell
  locations:
  - preferred_term: endometrium
    term:
      id: UBERON:0001295
      label: endometrium
  biological_processes:
  - preferred_term: cell population proliferation
    modifier: INCREASED
    term:
      id: GO:0008283
      label: cell population proliferation
  downstream:
  - target: PTEN PI3K Pathway Dysregulation
    description: Proliferative precursor epithelium provides a substrate for somatic driver selection.
- name: PTEN PI3K Pathway Dysregulation
  description: >-
    Endometrioid tumors commonly acquire PTEN, PIK3CA, and cooperating pathway
    alterations that support survival and growth through PI3K/AKT signaling.
  evidence:
  - reference: PMID:23636398
    reference_title: "Integrated genomic characterization of endometrial carcinoma."
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: "Most endometrioid tumours had few copy number alterations or TP53 mutations, but frequent mutations in PTEN, CTNNB1, PIK3CA, ARID1A and KRAS"
    explanation: >-
      TCGA identifies recurrent PTEN and PIK3CA alterations in endometrioid
      tumors, supporting this driver pathway.
  cell_types:
  - preferred_term: endometrial epithelial cell
    term:
      id: CL:0002656
      label: glandular endometrial unciliated epithelial cell
  genes:
  - preferred_term: PTEN
    term:
      id: hgnc:9588
      label: PTEN
  - preferred_term: PIK3CA
    term:
      id: hgnc:8975
      label: PIK3CA
  biological_processes:
  - preferred_term: phosphatidylinositol 3-kinase/protein kinase B signal transduction
    modifier: INCREASED
    term:
      id: GO:0043491
      label: phosphatidylinositol 3-kinase/protein kinase B signal transduction
  downstream:
  - target: Endometrioid Glandular Neoplasia
    description: Somatic pathway lesions support malignant outgrowth of endometrioid gland-forming epithelium.
- name: WNT Beta-Catenin Pathway Dysregulation
  description: >-
    CTNNB1-mutant WNT pathway activation is a recurrent molecular feature of
    endometrioid tumors and contributes to altered transcriptional control and
    tumor progression.
  evidence:
  - reference: PMID:23636398
    reference_title: "Integrated genomic characterization of endometrial carcinoma."
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: "Most endometrioid tumours had few copy number alterations or TP53 mutations, but frequent mutations in PTEN, CTNNB1, PIK3CA, ARID1A and KRAS"
    explanation: >-
      TCGA supports CTNNB1 as a recurrently mutated driver in endometrioid
      endometrial tumors.
  genes:
  - preferred_term: CTNNB1
    term:
      id: hgnc:2514
      label: CTNNB1
  biological_processes:
  - preferred_term: Wnt signaling pathway
    modifier: DYSREGULATED
    term:
      id: GO:0016055
      label: Wnt signaling pathway
  downstream:
  - target: Endometrioid Glandular Neoplasia
    description: Aberrant beta-catenin signaling contributes to malignant endometrioid epithelial behavior.
- name: Mismatch Repair Deficiency
  description: >-
    Loss of DNA mismatch repair creates microsatellite-instability and
    hypermutated tumor biology, commonly detected by loss of MMR protein
    expression by immunohistochemistry.
  evidence:
  - reference: DOI:10.3390/ijms25021056
    reference_title: "Mismatch Repair Deficiency as a Predictive and Prognostic Biomarker in Endometrial Cancer: A Review on Immunohistochemistry Staining Patterns and Clinical Implications"
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: "Among the four endometrial cancer (EC) TCGA molecular groups, the MSI/hypermutated group represents an important percentage of tumors (30%), including different histotypes, and generally confers an intermediate prognosis for affected women, also providing new immunotherapeutic strategies."
    explanation: >-
      The review links the MSI/hypermutated class to MMR-deficient endometrial
      cancer biology and immunotherapy implications.
  genes:
  - preferred_term: MLH1
    term:
      id: hgnc:7127
      label: MLH1
  - preferred_term: MSH2
    term:
      id: hgnc:7325
      label: MSH2
  - preferred_term: MSH6
    term:
      id: hgnc:7329
      label: MSH6
  - preferred_term: PMS2
    term:
      id: hgnc:9122
      label: PMS2
  biological_processes:
  - preferred_term: mismatch repair
    modifier: DECREASED
    term:
      id: GO:0006298
      label: mismatch repair
  downstream:
  - target: Immune Checkpoint Vulnerability
    description: Hypermutated tumors create immunotherapy-relevant tumor antigenicity.
- name: POLE Ultramutation
  description: >-
    Pathogenic POLE exonuclease-domain mutation produces an ultramutated
    endometrioid tumor subset with distinctive prognosis and staging implications.
  evidence:
  - reference: PMID:23636398
    reference_title: "Integrated genomic characterization of endometrial carcinoma."
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: "A subset of endometrioid tumours that we identified had a markedly increased transversion mutation frequency and newly identified hotspot mutations in POLE."
    explanation: >-
      TCGA directly supports POLE hotspot mutation as a hypermutator mechanism in
      a subset of endometrioid tumors.
  genes:
  - preferred_term: POLE
    term:
      id: hgnc:9177
      label: POLE
  biological_processes:
  - preferred_term: DNA replication proofreading
    modifier: DECREASED
    term:
      id: GO:0045004
      label: DNA replication proofreading
  downstream:
  - target: Immune Checkpoint Vulnerability
    description: High mutational burden can create immunogenic tumor features.
- name: Immune Checkpoint Vulnerability
  conforms_to: "immune_checkpoint_blockade#Adaptive Immune Resistance"
  description: >-
    Hypermutated MMRd/MSI-H and POLE-mutated tumors are clinically important
    immunotherapy-sensitive contexts in advanced or recurrent endometrial cancer.
  evidence:
  - reference: PMID:36972022
    reference_title: "Pembrolizumab plus Chemotherapy in Advanced Endometrial Cancer."
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: "In patients with advanced or recurrent endometrial cancer, the addition of pembrolizumab to standard chemotherapy resulted in significantly longer progression-free survival than with chemotherapy alone."
    explanation: >-
      The phase 3 NRG-GY018 trial supports immune checkpoint blockade combined
      with chemotherapy as a clinically effective strategy in advanced or
      recurrent endometrial cancer.
  biological_processes:
  - preferred_term: immune response
    modifier: INCREASED
    term:
      id: GO:0006955
      label: immune response
- name: Endometrioid Glandular Neoplasia
  description: >-
    Malignant endometrial epithelial cells form endometrioid glandular
    architecture, with tumor grade reflecting the amount of solid growth and
    loss of gland formation.
  cell_types:
  - preferred_term: endometrial epithelial cell
    term:
      id: CL:0002656
      label: glandular endometrial unciliated epithelial cell
  locations:
  - preferred_term: endometrium
    term:
      id: UBERON:0001295
      label: endometrium
histopathology:
- name: Endometrioid Adenocarcinoma
  finding_term:
    preferred_term: Endometrioid Adenocarcinoma
    term:
      id: NCIT:C3769
      label: Endometrioid Adenocarcinoma
  diagnostic: true
  description: >-
    Endometrioid gland-forming morphology is the defining histopathologic
    pattern of this disease.
  evidence:
  - reference: PMID:26354523
    reference_title: "Endometrial cancer."
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: "The most frequently occurring histological subtype is endometrioid adenocarcinoma."
    explanation: >-
      This directly supports endometrioid adenocarcinoma as the core histologic
      diagnosis.
- name: High-Grade Endometrioid Carcinoma
  finding_term:
    preferred_term: Endometrioid Adenocarcinoma
    term:
      id: NCIT:C3769
      label: Endometrioid Adenocarcinoma
  description: >-
    High-grade endometrioid tumors can overlap molecularly with copy-number-high
    serous-like cancer and may have frequent TP53 mutation.
  evidence:
  - reference: PMID:23636398
    reference_title: "Integrated genomic characterization of endometrial carcinoma."
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: "Uterine serous tumours and ∼25% of high-grade endometrioid tumours had extensive copy number alterations, few DNA methylation changes, low oestrogen receptor/progesterone receptor levels, and frequent TP53 mutations."
    explanation: >-
      TCGA supports that a subset of high-grade endometrioid tumors has
      copy-number-high and TP53-mutated biology.
phenotypes:
- category: Gynecologic
  name: Postmenopausal Bleeding
  diagnostic: true
  description: >-
    Postmenopausal bleeding is a common clinical trigger for evaluation of
    endometrial carcinoma; the broader endometrial carcinoma literature supports
    early diagnosis while disease is often still uterine-confined.
  phenotype_term:
    preferred_term: Postmenopausal bleeding
    term:
      id: HP:0033840
      label: Postmenopausal bleeding
  evidence:
  - reference: PMID:26354523
    reference_title: "Endometrial cancer."
    supports: PARTIAL
    evidence_source: HUMAN_CLINICAL
    snippet: "Patients are often diagnosed when the disease is still confined to the uterus."
    explanation: >-
      This does not name bleeding directly, but supports the early clinical
      detection context typical of endometrial carcinoma; frequency is omitted.
- category: Abdominal
  name: Pelvic Pain
  description: >-
    Pelvic pain can occur with locally advanced uterine disease, extrauterine
    spread, or treatment complications; frequency is not asserted because the
    fetched evidence does not quantify it.
  phenotype_term:
    preferred_term: Pelvic pain
    term:
      id: HP:0034267
      label: Pelvic pain
- category: Hematologic
  name: Anemia
  description: >-
    Anemia may occur secondary to chronic uterine bleeding in symptomatic
    patients, but no frequency is assigned without direct supporting evidence.
  phenotype_term:
    preferred_term: Anemia
    term:
      id: HP:0001903
      label: Anemia
biochemical:
- name: MMR Protein Immunohistochemistry
  notes: >-
    IHC for MLH1, MSH2, MSH6, and PMS2 is used as a practical MSI/MMRd surrogate
    and supports both molecular classification and Lynch syndrome screening.
  evidence:
  - reference: DOI:10.3390/ijms25021056
    reference_title: "Mismatch Repair Deficiency as a Predictive and Prognostic Biomarker in Endometrial Cancer: A Review on Immunohistochemistry Staining Patterns and Clinical Implications"
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: "Immunohistochemistry for MMR proteins (MLH1, MSH2, MSH6 and PMS2) has become the optimal diagnostic MSI surrogate worldwide."
    explanation: >-
      This supports MMR IHC as a core diagnostic and predictive biomarker assay.
- name: p53 Immunohistochemistry
  notes: >-
    Abnormal p53 immunohistochemistry is used as a surrogate for p53-abnormal
    molecular class in integrated endometrial cancer classification.
  evidence:
  - reference: DOI:10.3390/jpm13050723
    reference_title: "Prognostic Impact of Pathologic Features in Molecular Subgroups of Endometrial Carcinoma"
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: "ECs were classified using immunohistochemistry and next-generation sequencing into the four molecular classes: POLE mutant (POLE), mismatch repair deficient (MMRd), p53 mutant (p53abn), and no specific molecular profile (NSMP)."
    explanation: >-
      This supports immunohistochemistry plus sequencing as the practical route
      for p53abn classification.
- name: POLE Sequencing
  notes: >-
    POLE mutation testing identifies the POLEmut class and can change FIGO 2023
    staging in early-stage disease.
  evidence:
  - reference: DOI:10.1002/ijgo.14923
    reference_title: "FIGO staging of endometrial cancer: 2023"
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: "The performance of complete molecular classification (POLEmut, MMRd, NSMP, p53abn) is encouraged in all endometrial cancers."
    explanation: >-
      FIGO 2023 supports complete molecular classification including POLEmut
      status.
genetic:
- name: PTEN
  association: Recurrent somatic driver alteration
  variant_origin: SOMATIC
  gene_term:
    preferred_term: PTEN
    term:
      id: hgnc:9588
      label: PTEN
  evidence:
  - reference: PMID:23636398
    reference_title: "Integrated genomic characterization of endometrial carcinoma."
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: "Most endometrioid tumours had few copy number alterations or TP53 mutations, but frequent mutations in PTEN, CTNNB1, PIK3CA, ARID1A and KRAS"
    explanation: TCGA identifies PTEN among recurrently mutated genes in endometrioid tumors.
- name: PIK3CA
  association: Recurrent somatic PI3K-pathway driver alteration
  variant_origin: SOMATIC
  gene_term:
    preferred_term: PIK3CA
    term:
      id: hgnc:8975
      label: PIK3CA
  evidence:
  - reference: PMID:23636398
    reference_title: "Integrated genomic characterization of endometrial carcinoma."
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: "Most endometrioid tumours had few copy number alterations or TP53 mutations, but frequent mutations in PTEN, CTNNB1, PIK3CA, ARID1A and KRAS"
    explanation: TCGA identifies PIK3CA among recurrently mutated genes in endometrioid tumors.
- name: CTNNB1
  association: Recurrent somatic WNT pathway driver alteration
  variant_origin: SOMATIC
  gene_term:
    preferred_term: CTNNB1
    term:
      id: hgnc:2514
      label: CTNNB1
  evidence:
  - reference: PMID:23636398
    reference_title: "Integrated genomic characterization of endometrial carcinoma."
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: "Most endometrioid tumours had few copy number alterations or TP53 mutations, but frequent mutations in PTEN, CTNNB1, PIK3CA, ARID1A and KRAS"
    explanation: TCGA identifies CTNNB1 among recurrently mutated genes in endometrioid tumors.
- name: ARID1A
  association: Recurrent somatic chromatin remodeling driver alteration
  variant_origin: SOMATIC
  gene_term:
    preferred_term: ARID1A
    term:
      id: hgnc:11110
      label: ARID1A
  evidence:
  - reference: PMID:23636398
    reference_title: "Integrated genomic characterization of endometrial carcinoma."
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: "Most endometrioid tumours had few copy number alterations or TP53 mutations, but frequent mutations in PTEN, CTNNB1, PIK3CA, ARID1A and KRAS"
    explanation: TCGA identifies ARID1A among recurrently mutated genes in endometrioid tumors.
- name: KRAS
  association: Recurrent somatic RAS pathway driver alteration
  variant_origin: SOMATIC
  gene_term:
    preferred_term: KRAS
    term:
      id: hgnc:6407
      label: KRAS
  evidence:
  - reference: PMID:23636398
    reference_title: "Integrated genomic characterization of endometrial carcinoma."
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: "Most endometrioid tumours had few copy number alterations or TP53 mutations, but frequent mutations in PTEN, CTNNB1, PIK3CA, ARID1A and KRAS"
    explanation: TCGA identifies KRAS among recurrently mutated genes in endometrioid tumors.
- name: TP53
  association: Somatic p53-abnormal high-risk alteration
  variant_origin: SOMATIC
  gene_term:
    preferred_term: TP53
    term:
      id: hgnc:11998
      label: TP53
  evidence:
  - reference: PMID:23636398
    reference_title: "Integrated genomic characterization of endometrial carcinoma."
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: "Uterine serous tumours and ∼25% of high-grade endometrioid tumours had extensive copy number alterations, few DNA methylation changes, low oestrogen receptor/progesterone receptor levels, and frequent TP53 mutations."
    explanation: TCGA supports TP53 mutation in a copy-number-high subset of high-grade endometrioid tumors.
- name: MLH1, MSH2, MSH6, and PMS2
  association: Germline or somatic mismatch repair pathway deficiency
  variant_origin: GERMLINE_AND_SOMATIC
  notes: >-
    Loss of MMR protein expression can reflect sporadic MLH1 promoter
    hypermethylation or Lynch syndrome-associated germline pathogenic variants.
  evidence:
  - reference: DOI:10.3390/ijms25021056
    reference_title: "Mismatch Repair Deficiency as a Predictive and Prognostic Biomarker in Endometrial Cancer: A Review on Immunohistochemistry Staining Patterns and Clinical Implications"
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: "Immunohistochemistry for MMR proteins (MLH1, MSH2, MSH6 and PMS2) has become the optimal diagnostic MSI surrogate worldwide."
    explanation: >-
      The review identifies the four MMR proteins that define routine MMRd
      assessment.
environmental:
- name: Obesity and Metabolic Dysfunction
  description: >-
    Obesity increases risk for estrogen-dependent endometrioid carcinoma through
    elevated adipocyte-derived estrogen and inflammatory/metabolic changes.
  evidence:
  - reference: DOI:10.3390/cancers16122197
    reference_title: "Effects of Weight Loss on Key Obesity-Related Biomarkers Linked to the Risk of Endometrial Cancer: A Systematic Review and Meta-Analysis"
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: "Endometrial cancer (EC) includes various histologic types, with estrogen-dependent endometrioid carcinoma being the most common. Obesity significantly increases the risk of developing this type, especially in postmenopausal women, due to elevated estrogen production by adipocytes."
    explanation: >-
      This recent systematic review directly connects obesity, adipocyte-derived
      estrogen, and risk of estrogen-dependent endometrioid carcinoma.
diagnosis:
- name: Endometrial Sampling With Histopathology
  description: >-
    Endometrial biopsy, curettage, or hysterectomy pathology establishes the
    endometrioid carcinoma diagnosis and supports grading and staging.
  diagnosis_term:
    preferred_term: diagnostic procedure
    term:
      id: MAXO:0000003
      label: diagnostic procedure
  evidence:
  - reference: PMID:26354523
    reference_title: "Endometrial cancer."
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: "Lymph node surgical strategy is contingent on histological factors (subtype, tumour grade, involvement of lymphovascular space), disease stage (including myometrial invasion), patients' characteristics (age and comorbidities), and national and international guidelines."
    explanation: >-
      This supports use of histologic subtype, grade, LVSI, stage, and patient
      factors in surgical staging decisions.
- name: Complete Molecular Classification
  description: >-
    Integrated classification uses POLE mutation testing and MMR and p53
    immunohistochemistry to assign POLEmut, MMRd, NSMP, or p53abn status.
  diagnosis_term:
    preferred_term: diagnostic procedure
    term:
      id: MAXO:0000003
      label: diagnostic procedure
  evidence:
  - reference: DOI:10.1002/ijgo.14923
    reference_title: "FIGO staging of endometrial cancer: 2023"
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: "The performance of complete molecular classification (POLEmut, MMRd, NSMP, p53abn) is encouraged in all endometrial cancers."
    explanation: >-
      FIGO 2023 supports complete molecular classification for endometrial
      cancers.
treatments:
- name: Hysterectomy With Bilateral Salpingo-Oophorectomy
  description: >-
    Primary hysterectomy with bilateral salpingo-oophorectomy is standard local
    treatment for many patients, with staging and nodal assessment tailored by
    histology, grade, LVSI, stage, patient factors, and guidelines.
  treatment_term:
    preferred_term: surgical procedure
    term:
      id: MAXO:0000004
      label: surgical procedure
  evidence:
  - reference: PMID:26354523
    reference_title: "Endometrial cancer."
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: "Standard treatment consists of primary hysterectomy and bilateral salpingo-oophorectomy, often using minimally invasive approaches (laparoscopic or robotic)."
    explanation: >-
      This review directly supports hysterectomy with bilateral
      salpingo-oophorectomy as standard treatment.
- name: Adjuvant Radiation Therapy
  description: >-
    Adjuvant radiation or chemoradiation is selected according to integrated
    recurrence risk, including stage, histology, grade, LVSI, and molecular
    class.
  treatment_term:
    preferred_term: radiation therapy
    term:
      id: MAXO:0000014
      label: radiation therapy
  evidence:
  - reference: PMID:26354523
    reference_title: "Endometrial cancer."
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: "Adjuvant treatment is tailored according to histology and stage."
    explanation: >-
      This supports postoperative tailoring of adjuvant therapy in endometrial
      cancer; the description adds molecular-risk context from newer staging
      evidence.
- name: Carboplatin-Paclitaxel Chemotherapy
  description: >-
    Carboplatin plus paclitaxel is the standard chemotherapy backbone used in
    advanced or recurrent endometrial cancer trials and combined with
    immune-checkpoint inhibitors in current phase 3 evidence.
  treatment_term:
    preferred_term: chemotherapy
    term:
      id: MAXO:0000647
      label: chemotherapy
    therapeutic_agent:
    - preferred_term: carboplatin
      term:
        id: CHEBI:31355
        label: carboplatin
    - preferred_term: paclitaxel
      term:
        id: CHEBI:45863
        label: paclitaxel
  evidence:
  - reference: PMID:36972022
    reference_title: "Pembrolizumab plus Chemotherapy in Advanced Endometrial Cancer."
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: "Standard first-line chemotherapy for endometrial cancer is paclitaxel plus carboplatin."
    explanation: >-
      The NRG-GY018 abstract identifies paclitaxel plus carboplatin as standard
      first-line chemotherapy.
- name: Pembrolizumab Plus Carboplatin-Paclitaxel
  description: >-
    PD-1 blockade with pembrolizumab plus carboplatin-paclitaxel improves
    progression-free survival in advanced or recurrent endometrial cancer, with
    strong relevance for dMMR tumors.
  treatment_term:
    preferred_term: pharmacotherapy
    term:
      id: MAXO:0000058
      label: pharmacotherapy
    therapeutic_agent:
    - preferred_term: pembrolizumab
      term:
        id: NCIT:C106432
        label: Pembrolizumab
    - preferred_term: carboplatin
      term:
        id: CHEBI:31355
        label: carboplatin
    - preferred_term: paclitaxel
      term:
        id: CHEBI:45863
        label: paclitaxel
  target_mechanisms:
  - target: Immune Checkpoint Vulnerability
    treatment_effect: INHIBITS
    description: PD-1 blockade is intended to counter tumor immune checkpoint signaling.
  evidence:
  - reference: PMID:36972022
    reference_title: "Pembrolizumab plus Chemotherapy in Advanced Endometrial Cancer."
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: "In patients with advanced or recurrent endometrial cancer, the addition of pembrolizumab to standard chemotherapy resulted in significantly longer progression-free survival than with chemotherapy alone."
    explanation: >-
      This phase 3 trial supports pembrolizumab plus chemotherapy in advanced or
      recurrent endometrial cancer.
- name: Dostarlimab Plus Carboplatin-Paclitaxel
  description: >-
    Dostarlimab combined with carboplatin-paclitaxel improves progression-free
    survival in primary advanced or recurrent endometrial cancer, with a
    substantial benefit in dMMR-MSI-H tumors.
  treatment_term:
    preferred_term: pharmacotherapy
    term:
      id: MAXO:0000058
      label: pharmacotherapy
    therapeutic_agent:
    - preferred_term: dostarlimab
      term:
        id: NCIT:C126799
        label: Dostarlimab
    - preferred_term: carboplatin
      term:
        id: CHEBI:31355
        label: carboplatin
    - preferred_term: paclitaxel
      term:
        id: CHEBI:45863
        label: paclitaxel
  target_mechanisms:
  - target: Immune Checkpoint Vulnerability
    treatment_effect: INHIBITS
    description: PD-1 blockade is intended to counter tumor immune checkpoint signaling.
  evidence:
  - reference: PMID:36972026
    reference_title: "Dostarlimab for Primary Advanced or Recurrent Endometrial Cancer."
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: "Dostarlimab plus carboplatin-paclitaxel significantly increased progression-free survival among patients with primary advanced or recurrent endometrial cancer, with a substantial benefit in the dMMR-MSI-H population."
    explanation: >-
      This phase 3 trial supports dostarlimab plus chemotherapy in primary
      advanced or recurrent disease, especially dMMR-MSI-H tumors.
notes: >-
  This entry intentionally models the endometrioid adenocarcinoma subtype rather
  than editing the broader Endometrial_Carcinoma.yaml page. Frequency qualifiers
  are omitted from phenotypes unless direct frequency support was available in
  fetched snippets. Falcon also surfaced weight loss and bariatric surgery as
  prevention-relevant risk reduction evidence; this is kept as notes rather than
  a top-level section because the current schema does not expose a prevention
  slot on Disease.
mappings:
  mondo_mappings:
  - term:
      id: MONDO:0006192
      label: endometrial endometrioid adenocarcinoma
    mapping_predicate: skos:exactMatch
    mapping_source: MONDO
    mapping_justification: OAK confirmed MONDO:0006192 as the exact disease label for this entry.
  ncit_mappings:
  - term:
      id: NCIT:C6287
      label: Endometrial Endometrioid Adenocarcinoma
    mapping_predicate: skos:exactMatch
    mapping_source: MONDO xref
    mapping_justification: MONDO:0006192 includes NCIT:C6287 as an xref for endometrial endometrioid adenocarcinoma.
📚

References & Deep Research

Deep Research

1
Falcon ▸
Disease Characteristics Research Template
Edison Scientific Literature 49 citations 2026-05-08T09:35:40.452557

Question: You are an expert researcher providing comprehensive, well-cited information.

Provide detailed information focusing on: 1. Key concepts and definitions with current understanding 2. Recent developments and latest research (prioritize 2023-2024 sources) 3. Current applications and real-world implementations 4. Expert opinions and analysis from authoritative sources 5. Relevant statistics and data from recent studies

Format as a comprehensive research report with proper citations. Include URLs and publication dates where available. Always prioritize recent, authoritative sources and provide specific citations for all major claims.

Disease Characteristics Research Template

Target Disease

  • Disease Name: Endometrial Endometrioid Adenocarcinoma
  • MONDO ID: (if available)
  • Category:

Research Objectives

Please provide a comprehensive research report on Endometrial Endometrioid Adenocarcinoma covering all of the disease characteristics listed below. This report will be used to populate a disease knowledge base entry. Be thorough and cite primary literature (PMID preferred) for all claims.

For each section, suggested databases/resources are listed. These are the first places you should search for information on each topic.

1. Disease Information

Search first: OMIM, Orphanet, ICD-10/ICD-11, MeSH, PubMed

  • What is the disease? Provide a concise overview.
  • What are the key identifiers? (OMIM, Orphanet, ICD-10/ICD-11, MeSH, Mondo)
  • What are the common synonyms and alternative names?
  • Is the information derived from individual patients (e.g., EHR) or aggregated disease-level resources?

2. Etiology

  • Disease Causal Factors: What are the primary causes? (genetic, environmental, infectious, mechanistic)
  • Risk Factors:

    Search first: PubMed, Cochrane Library, UpToDate, clinical guidelines, ClinVar, ClinGen, GWAS Catalog, PheGenI, CTD, CDC, WHO, epidemiological databases

  • Genetic risk factors (causal variants, susceptibility loci, modifier genes)
  • Environmental risk factors (toxins, lifestyle, occupational exposures, age, sex, family history)
  • Protective Factors:

    Search first: PubMed, Cochrane Library, clinical trial databases, GWAS Catalog, gnomAD, WHO, CDC, nutrition databases

  • Genetic protective factors (protective variants, modifier alleles)
  • Environmental protective factors (diet, lifestyle, exposures that reduce risk)
  • Gene-Environment Interactions: How do genetic and environmental factors interact to influence disease?

    Search first: CTD, PubMed, PheGenI, GxE databases

3. Phenotypes

Search first: HPO (Human Phenotype Ontology), OMIM, Orphanet, PubMed, clinicaltrials.gov, MedDRA, SNOMED CT, DECIPHER, LOINC

For each phenotype, provide: - Phenotype type: symptoms, clinical signs, physical manifestations, behavioral changes, or laboratory abnormalities

For symptoms/signs: HPO, OMIM, Orphanet, PubMed For behavioral changes: HPO, DSM, RDoC (Research Domain Criteria), PubMed For laboratory abnormalities: LOINC, SNOMED CT, LabTests Online, PubMed - Phenotype characteristics: Search first: OMIM, Orphanet, HPO, PubMed - Age of symptom onset (neonatal, childhood, adult-onset, late-onset) - Symptom severity (mild, moderate, severe, variable) - Symptom progression (stable, progressive, episodic, fluctuating) - Frequency among affected individuals (percentage or qualitative) - Quality of life impact: Effects on daily functioning and well-being (per-phenotype when possible) Search first: EQ-5D database, SF-36, WHO QOL databases, PubMed - Suggest HPO (Human Phenotype Ontology) terms for each phenotype

4. Genetic/Molecular Information

  • Causal Genes: Gene mutations or chromosomal abnormalities responsible for disease (gene symbols, OMIM IDs)

    Search first: OMIM, ClinVar, HGMD, Ensembl, NCBI Gene

  • Pathogenic Variants:
  • Affected genes (gene symbols, HGNC IDs) > Search first: OMIM, NCBI Gene, Ensembl, HGNC, UniProt, GeneCards
  • Variant classification (pathogenic, likely pathogenic, VUS per ACMG/AMP guidelines) > Search first: ClinVar, ClinGen, ACMG/AMP guidelines, VarSome
  • Variant type/class (missense, frameshift, nonsense, splice-site, structural)
  • Allele frequency in population databases > Search first: gnomAD, 1000 Genomes, ExAC, TOPMed, dbSNP
  • Somatic vs germline origin > Search first: COSMIC (somatic), ClinVar, ICGC, TCGA
  • Functional consequences (loss of function, gain of function, dominant negative)
  • Modifier Genes: Genes that modify disease severity or expression
  • Epigenetic Information: DNA methylation, histone modifications, chromatin changes affecting disease

    Search first: ENCODE, Roadmap Epigenomics, MethBase, DiseaseMeth

  • Chromosomal Abnormalities: Large-scale genetic changes (aneuploidy, translocations, inversions)

    Search first: DECIPHER, ClinVar, ECARUCA, UCSC Genome Browser

5. Environmental Information

  • Environmental Factors: Non-genetic contributing factors (toxins, radiation, pollution, occupational exposure)

    Search first: CTD (Comparative Toxicogenomics Database), TOXNET, PubMed, EPA databases

  • Lifestyle Factors: Behavioral factors (smoking, diet, exercise, alcohol consumption)

    Search first: CDC databases, WHO, PubMed, NHANES

  • Infectious Agents: If applicable, pathogens causing or triggering disease (bacteria, viruses, fungi, parasites)

    Search first: NCBI Taxonomy, ViPR, BV-BRC, MicrobeDB, GIDEON

6. Mechanism / Pathophysiology

  • Molecular Pathways: Specific signaling cascades or biochemical pathways involved (Wnt, MAPK, mTOR, PI3K-AKT, etc.)

    Search first: KEGG, Reactome, WikiPathways, PathBank, BioCyc

  • Cellular Processes: Cell-level mechanisms (apoptosis, autophagy, cell cycle dysregulation, inflammation, etc.)

    Search first: Gene Ontology (GO), Reactome, KEGG, PubMed

  • Protein Dysfunction: How protein structure or function is altered (misfolding, aggregation, loss of function, gain of function)

    Search first: UniProt, PDB (Protein Data Bank), InterPro, Pfam, AlphaFold

  • Metabolic Changes: Alterations in metabolic processes (energy metabolism, lipid metabolism, amino acid metabolism)

    Search first: KEGG, BioCyc, HMDB (Human Metabolome Database), BRENDA

  • Immune System Involvement: Role of immune response (autoimmunity, immunodeficiency, chronic inflammation)

    Search first: ImmPort, Immunome Database, IEDB, Gene Ontology

  • Tissue Damage Mechanisms: How tissues/ are injured (oxidative stress, ischemia, fibrosis, necrosis)

    Search first: PubMed, Gene Ontology, Reactome

  • Biochemical Abnormalities: Specific molecular defects (enzyme deficiencies, receptor dysfunction, ion channel defects)

    Search first: BRENDA, UniProt, KEGG, OMIM, PubMed

  • Epigenetic Changes: DNA methylation, histone modifications affecting gene expression in disease

    Search first: ENCODE, Roadmap Epigenomics, MethBase, DiseaseMeth

  • Molecular Profiling (if available):
  • Transcriptomics/gene expression changes > Search first: GEO (Gene Expression Omnibus), ArrayExpress, GTEx, Human Cell Atlas, SRA
  • Proteomics findings > Search first: PRIDE, ProteomeXchange, Human Protein Atlas, STRING, BioGRID
  • Metabolomics signatures > Search first: MetaboLights, Metabolomics Workbench, HMDB, METLIN
  • Lipidomics alterations > Search first: LIPID MAPS, SwissLipids, LipidHome, Metabolomics Workbench
  • Genomic structural features > Search first: UCSC Genome Browser, Ensembl, NCBI, dbVar, DGV
  • Advanced Technologies (if applicable):
  • Single-cell analysis findings (cell-type specific mechanisms, cellular heterogeneity) > Search first: Human Cell Atlas, Single Cell Portal, GEO, CELLxGENE
  • Spatial transcriptomics findings > Search first: GEO, Spatial Research, Vizgen, 10x Genomics data
  • Multi-omics integration results > Search first: TCGA, ICGC, cBioPortal, LinkedOmics, PubMed
  • Functional genomics screens (CRISPR, RNAi) > Search first: DepMap, GenomeRNAi, PubMed, BioGRID ORCS

For each mechanism, describe: - The causal chain from initial trigger to clinical manifestation - Which mechanisms are upstream vs downstream - What cell types and biological processes are involved - Suggest GO terms for biological processes and CL terms for cell types

7. Anatomical Structures Affected

  • Organ Level:
  • Primary organs directly affected
  • Secondary organ involvement (complications, secondary effects)
  • Body systems involved (cardiovascular, nervous, digestive, respiratory, endocrine, etc.)

    Search first: Uberon, FMA (Foundational Model of Anatomy), OMIM, HPO, ICD-11, MeSH, SNOMED CT

  • Tissue and Cell Level:
  • Specific tissue types affected (epithelial, connective, muscle, nervous)
  • Specific cell populations targeted (with Cell Ontology terms)

    Search first: Uberon, Human Protein Atlas, Cell Ontology, Human Cell Atlas, CellMarker, PanglaoDB

  • Subcellular Level:
  • Cellular compartments involved (mitochondria, nucleus, ER, lysosomes) (with GO Cellular Component terms)

    Search first: Gene Ontology (Cellular Component), UniProt, Human Protein Atlas

  • Localization:
  • Specific anatomical sites (with UBERON terms) > Search first: FMA, Uberon, NeuroNames (for brain), SNOMED CT
  • Lateralization (unilateral, bilateral, asymmetric) > Search first: HPO, clinical literature, imaging databases

8. Temporal Development

  • Onset:
  • Typical age of onset (congenital, pediatric, adult, geriatric)
  • Onset pattern (acute, subacute, chronic, insidious)

    Search first: OMIM, Orphanet, HPO, PubMed

  • Progression:
  • Disease stages (early, intermediate, advanced, end-stage) > Search first: Cancer Staging Manual (AJCC), WHO classifications, PubMed
  • Progression rate (rapid, slow, variable)
  • Disease course pattern (episodic, relapsing-remitting, progressive, stable)
  • Disease duration (self-limited, chronic lifelong)

    Search first: Disease registries, longitudinal cohort databases, natural history studies, PubMed, Orphanet, OMIM

  • Patterns:
  • Remission patterns (spontaneous, treatment-induced) > Search first: Clinical trial databases, disease registries, PubMed
  • Critical periods (time windows of vulnerability or opportunity for intervention) > Search first: PubMed, developmental biology databases, clinical guidelines

9. Inheritance and Population

  • Epidemiology:
  • Prevalence (cases per 100,000 at given time)
  • Incidence (new cases per 100,000 per year)

    Search first: Orphanet, CDC, WHO, GBD (Global Burden of Disease), national registries, SEER, disease registries

  • For Genetic Etiology:
  • Inheritance pattern (AD, AR, X-linked, mitochondrial, multifactorial, polygenic) > Search first: OMIM, Orphanet, ClinVar, GTR (Genetic Testing Registry)
  • Penetrance (complete, incomplete, age-dependent) > Search first: ClinVar, OMIM, PubMed, ClinGen
  • Expressivity (variable, consistent) > Search first: OMIM, ClinVar, PubMed
  • Genetic anticipation (increasing severity in successive generations) > Search first: OMIM, PubMed (especially for repeat expansion disorders)
  • Germline mosaicism > Search first: ClinVar, OMIM, genetic counseling literature, PubMed
  • Founder effects (population-specific mutations) > Search first: gnomAD, population genetics databases, PubMed
  • Consanguinity role > Search first: OMIM, population studies, genetic counseling resources
  • Carrier frequency > Search first: gnomAD, carrier screening databases, GeneReviews, GTR
  • Population Demographics:
  • Affected populations (ethnic or demographic groups with higher prevalence) > Search first: gnomAD, 1000 Genomes, PAGE Study, PubMed, population registries
  • Geographic distribution (endemic areas, regional variation) > Search first: WHO, CDC, GBD, Orphanet, geographic epidemiology databases
  • Geographic distribution of specific variants
  • Sex ratio (male:female) > Search first: Disease registries, OMIM, PubMed, epidemiological databases
  • Age distribution of affected individuals > Search first: CDC, disease registries, SEER, Orphanet

10. Diagnostics

  • Clinical Tests:
  • Laboratory tests (blood, urine, tissue chemistry, specific enzyme assays) > Search first: LOINC, LabTests Online, PubMed
  • Biomarkers (proteins, metabolites, genetic markers, circulating biomarkers) > Search first: FDA Biomarker List, BEST (Biomarkers, EndpointS, and other Tools), PubMed
  • Imaging studies (X-ray, CT, MRI, PET, ultrasound) > Search first: RadLex, DICOM, Radiopaedia, imaging databases
  • Functional tests (pulmonary function, cardiac stress tests) > Search first: LOINC, clinical guidelines, PubMed
  • Electrophysiology (EEG, EMG, ECG, nerve conduction studies) > Search first: LOINC, clinical neurophysiology databases, PubMed
  • Biopsy findings (histopathology, immunohistochemistry) > Search first: SNOMED CT, College of American Pathologists resources, PubMed
  • Pathology findings (microscopic examination) > Search first: SNOMED CT, Digital Pathology databases, PubMed
  • Genetic Testing:

    Search first: GTR (Genetic Testing Registry), GeneReviews, ClinGen

  • Overview of recommended genetic testing approach
  • Whole genome sequencing (WGS) utility > Search first: GTR, ClinVar, GEL (Genomics England), gnomAD
  • Whole exome sequencing (WES) utility > Search first: GTR, ClinVar, OMIM, GeneMatcher
  • Gene panels (which panels, which genes) > Search first: GTR, ClinVar, laboratory-specific databases
  • Single gene testing > Search first: GTR, ClinVar, OMIM, GeneReviews
  • Chromosomal microarray (CMA) > Search first: DECIPHER, ClinVar, dbVar, ECARUCA
  • Karyotyping > Search first: Chromosome Abnormality Database, ClinVar, cytogenetics resources
  • FISH > Search first: ClinVar, cytogenetics databases, PubMed
  • Mitochondrial DNA testing > Search first: MITOMAP, MSeqDR, ClinVar, GTR
  • Repeat expansion testing > Search first: GTR, ClinVar, repeat expansion databases, PubMed
  • Omics-Based Diagnostics (if applicable):
  • RNA sequencing / transcriptomics > Search first: GEO, ArrayExpress, GTEx, RNA-seq databases
  • Proteomics > Search first: PRIDE, ProteomeXchange, FDA Biomarker database
  • Metabolomics > Search first: MetaboLights, Metabolomics Workbench, HMDB
  • Epigenomics > Search first: GEO, ENCODE, Roadmap Epigenomics, MethBase
  • Liquid biopsy > Search first: COSMIC, ClinVar, liquid biopsy databases, PubMed
  • Clinical Criteria:
  • Standardized diagnostic criteria (DSM, ICD, society guidelines) > Search first: DSM-5, ICD-11, clinical society guidelines, UpToDate
  • Differential diagnosis (other conditions to rule out, with distinguishing features) > Search first: DynaMed, UpToDate, clinical decision support systems
  • Screening:
  • Screening methods for asymptomatic individuals (newborn screening, carrier screening, cascade screening) > Search first: ACMG recommendations, CDC newborn screening, GTR

11. Outcome/Prognosis

  • Survival and Mortality:
  • Survival rate (5-year, 10-year, overall) > Search first: SEER, cancer registries, disease-specific registries, PubMed
  • Life expectancy (with and without treatment if applicable) > Search first: Orphanet, disease registries, actuarial databases, PubMed
  • Mortality rate > Search first: CDC, WHO, GBD, national mortality databases
  • Disease-specific mortality (deaths directly attributable to disease) > Search first: Disease registries, CDC Wonder, GBD, PubMed
  • Morbidity and Function:
  • Morbidity (disease-related disability and health impacts) > Search first: GBD, WHO, disability databases, PubMed
  • Disability outcomes (long-term functional impairments) > Search first: ICF (International Classification of Functioning), disability registries
  • Quality of life measures (EQ-5D, SF-36, PROMIS, disease-specific tools) > Search first: EQ-5D database, SF-36, PROMIS, PubMed
  • Disease Course:
  • Complications (secondary problems: infections, organ failure, etc.) > Search first: ICD codes, disease registries, clinical databases, PubMed
  • Recovery potential (likelihood and extent of recovery, with vs without treatment) > Search first: Natural history studies, rehabilitation databases, PubMed
  • Prediction:
  • Prognostic factors (age, disease severity, biomarkers, treatment response) > Search first: Prognostic models databases, clinical calculators, PubMed
  • Prognostic biomarkers (molecular markers predicting disease course) > Search first: FDA Biomarker database, PubMed, cancer prognostic databases

12. Treatment

  • Pharmacotherapy:
  • Pharmacological treatments (drug names, drug classes, mechanisms of action) > Search first: DrugBank, RxNorm, ATC classification, DailyMed, FDA databases
  • Pharmacogenomics (how genetic variants affect drug metabolism, efficacy, toxicity) > Search first: PharmGKB, CPIC (Clinical Pharmacogenetics), FDA Table of PGx Biomarkers
  • Advanced Therapeutics:
  • Gene therapy (viral vectors, CRISPR, gene replacement, gene editing) > Search first: ClinicalTrials.gov, FDA gene therapy database, ASGCT resources
  • Cell therapy (stem cell transplant, CAR-T, cellular therapeutics) > Search first: ClinicalTrials.gov, FDA cell therapy database, FACT standards
  • RNA-based therapies (ASOs, siRNA, mRNA therapies) > Search first: ClinicalTrials.gov, FDA approvals, PubMed
  • Targeted therapies (treatments directed at specific molecular targets) > Search first: My Cancer Genome, OncoKB, ClinicalTrials.gov, FDA approvals
  • Immunotherapies (checkpoint inhibitors, monoclonal antibodies) > Search first: Cancer Immunotherapy Database, FDA approvals, ClinicalTrials.gov
  • Surgical and Interventional:
  • Surgical interventions (types of surgery, timing, outcomes) > Search first: CPT codes, surgical registries, clinical guidelines, PubMed
  • Supportive and Rehabilitative:
  • Supportive care (symptom management, pain control, nutrition) > Search first: Clinical guidelines, Cochrane Library, PubMed
  • Rehabilitation (physical therapy, occupational therapy, speech therapy) > Search first: Rehabilitation medicine databases, clinical guidelines, PubMed
  • Experimental:
  • Experimental treatments in clinical trials (with NCT identifiers if available) > Search first: ClinicalTrials.gov, EU Clinical Trials Register, WHO ICTRP
  • Treatment Outcomes:
  • Treatment response rates > Search first: Clinical trial databases, FDA reviews, systematic reviews, PubMed
  • Side effects and adverse events > Search first: FDA Adverse Event Reporting System (FAERS), MedWatch, PubMed
  • Treatment Strategy:
  • Treatment algorithms (clinical pathways, decision trees) > Search first: Clinical practice guidelines, NCCN Guidelines, UpToDate
  • Combination therapies > Search first: ClinicalTrials.gov, treatment guidelines, PubMed
  • Personalized medicine approaches (genotype-guided treatment) > Search first: My Cancer Genome, CIViC, PharmGKB, precision medicine databases

For each treatment, suggest MAXO (Medical Action Ontology) terms where applicable.

13. Prevention

  • Prevention Levels:
  • Primary prevention (preventing disease occurrence: vaccination, risk factor modification) > Search first: CDC, WHO, USPSTF recommendations, Cochrane Library
  • Secondary prevention (early detection and treatment: screening programs, early intervention) > Search first: USPSTF, CDC screening guidelines, WHO
  • Tertiary prevention (preventing complications in those with disease) > Search first: Clinical guidelines, disease management protocols, PubMed
  • Immunization: Vaccine strategies (if applicable)

    Search first: CDC vaccine schedules, WHO immunization, FDA vaccine database

  • Screening and Early Detection:
  • Screening programs (population-based: newborn screening, cancer screening) > Search first: CDC screening programs, USPSTF, cancer screening databases
  • Genetic screening (carrier screening, preimplantation genetic diagnosis, prenatal testing) > Search first: ACMG recommendations, ACOG guidelines, GTR
  • Risk stratification (identifying high-risk individuals for targeted prevention) > Search first: Risk prediction models, clinical calculators, PubMed
  • Behavioral Interventions: Lifestyle modifications to reduce risk

    Search first: CDC, WHO, behavioral intervention databases, Cochrane Library

  • Counseling: Genetic counseling (risk assessment, family planning guidance)

    Search first: NSGC resources, ACMG guidelines, GeneReviews

  • Public Health:
  • Public health interventions (sanitation, vector control, health education) > Search first: CDC, WHO, public health databases, PubMed
  • Environmental interventions (reducing environmental risk factors) > Search first: EPA databases, WHO environmental health, PubMed
  • Prophylaxis: Preventive medications or procedures

    Search first: Clinical guidelines, FDA approvals, PubMed

14. Other Species / Natural Disease

  • Taxonomy: Species affected (with NCBI Taxon identifiers)

    Search first: NCBI Taxonomy

  • Breed: Specific breeds affected (with VBO identifiers if applicable)

    Search first: VBO (Vertebrate Breed Ontology)

  • Gene: Orthologous genes in other species (with NCBI Gene IDs)

    Search first: NCBI Gene

  • Natural Disease:
  • Naturally occurring disease in other species (companion animals, wildlife) > Search first: OMIA (Online Mendelian Inheritance in Animals), VetCompass, PubMed
  • Veterinary relevance and importance in animal health > Search first: OMIA, veterinary databases, PubMed
  • Comparative Biology:
  • Comparative pathology (similarities and differences across species) > Search first: OMIA, comparative pathology databases, PubMed
  • Evolutionary conservation of disease mechanisms > Search first: HomoloGene, OrthoMCL, Alliance of Genome Resources
  • Transmission (if applicable):
  • Zoonotic potential > Search first: CDC zoonotic diseases, WHO zoonoses, GIDEON
  • Cross-species susceptibility > Search first: NCBI Taxonomy, veterinary databases, PubMed

15. Model Organisms

  • Model Types:
  • Model organism type (mammalian, invertebrate, cellular, in vitro) > Search first: Alliance of Genome Resources, model organism databases
  • Specific model systems (mouse, rat, zebrafish, Drosophila, C. elegans, yeast, cell lines, organoids, iPSCs) > Search first: MGI, RGD, ZFIN, FlyBase, WormBase, SGD, ATCC, Cellosaurus
  • Induced models (drug treatment, surgical intervention, environmental manipulation) > Search first: MGI, model organism databases, PubMed
  • Genetic Models:
  • Types available (knockout, knock-in, transgenic, conditional, humanized) > Search first: MGI, IMPC, KOMP, EuMMCR, IMSR
  • Model Characteristics:
  • Phenotype recapitulation (how well model reproduces human disease features) > Search first: Model organism databases, comparative studies, PubMed
  • Model limitations (aspects of human disease not captured) > Search first: Model organism databases, PubMed, review articles
  • Applications:
  • Research applications (what aspects of disease can be studied) > Search first: Model organism databases, PubMed
  • Resources:
  • Model databases > Search first: MGI, RGD, ZFIN, FlyBase, WormBase, IMSR, EMMA, MMRRC

Citation Requirements

  • Cite primary literature (PMID preferred) for all mechanistic and clinical claims
  • Prioritize recent reviews and landmark papers
  • Include direct quotes from abstracts where possible to support key statements
  • Distinguish evidence source types: human clinical, model organism, in vitro, computational

Output Format

Structure your response as a comprehensive narrative organized by the sections above. For each section, provide: - Factual content with specific details (numbers, percentages, gene names, variant nomenclature) - Ontology term suggestions (HPO, GO, CL, UBERON, CHEBI, MAXO, MONDO) where applicable - Evidence citations with PMIDs - Direct quotes from abstracts to support key claims - Clear indication when information is not available or not applicable for this disease

This report will be used to populate a disease knowledge base entry with: - Pathophysiology descriptions with causal chains - Gene/protein annotations (HGNC, GO terms) - Phenotype associations (HP terms) with frequencies - Cell type involvement (CL terms) - Anatomical locations (UBERON terms) - Chemical entities (CHEBI terms) - Treatment annotations (MAXO terms) - Evidence items with PMIDs and exact abstract quotes - Epidemiology, prognosis, diagnostic, and prevention information - Animal model descriptions with phenotype recapitulation details

Endometrial Endometrioid Adenocarcinoma (EEC): Comprehensive Disease Characteristics Report (2023–2024 emphasis)

Target Disease

  • Disease name: Endometrial endometrioid adenocarcinoma (endometrioid endometrial carcinoma; “endometrioid” histotype of endometrial carcinoma) (nagel2024predictivebiomarkersin pages 1-2, yasuda2024newclinicopathologicalconcept pages 1-3)
  • Ontology/identifier notes (available from retrieved sources): Open Targets returns the disease as EFO_1000233 “Endometrial Endometrioid Adenocarcinoma” (OpenTargets Search: endometrioid endometrial adenocarcinoma,endometrial carcinoma).
  • Key external IDs (ICD-10/ICD-11/MeSH/MONDO/OMIM/Orphanet): Not retrieved with the current tool evidence; therefore not reported here.
  • Category: Malignant epithelial tumor of the uterine corpus endometrium; histologic subtype of endometrial carcinoma (nagel2024predictivebiomarkersin pages 1-2, yasuda2024newclinicopathologicalconcept pages 1-3).

Common synonyms / alternative names

  • Endometrioid endometrial carcinoma (EEC) (nagel2024predictivebiomarkersin pages 1-2)
  • Endometrioid adenocarcinoma of the endometrium / endometrioid adenocarcinoma (uterus) (yasuda2024newclinicopathologicalconcept pages 1-3)

Evidence type note

This report is derived from aggregated disease-level resources (peer-reviewed reviews, meta-analyses, clinical trials, registry analyses) and one real-world institutional screening implementation study (nagel2024predictivebiomarkersin pages 2-4, ruscelli2023prognosticimpactof pages 1-2, wilson2023systematicreviewand pages 1-2, liu2023differentialtrendsin pages 2-4).

1. Disease information (definition and current understanding)

Concise overview

Endometrial endometrioid adenocarcinoma is the most common histologic type of endometrial carcinoma, arising from the endometrial lining and typically showing gland-forming “endometrioid” architecture with FIGO grading based on solid growth (yang2024molecularsubtypesof pages 4-5, yasuda2024newclinicopathologicalconcept pages 1-3). EEC has historically been described as estrogen-associated (“type I”) in contrast to less common non-endometrioid “type II” tumors (nagel2024predictivebiomarkersin pages 1-2).

Histopathologic definition and grading

Yasuda (2024) describes endometrioid adenocarcinoma as “a malignant tumor with varying proportions of glandular, papillary, and solid architectures” and outlines FIGO grading thresholds (G1 <5% solid; G2 6–50%; G3 >50%), often simplified as low grade (G1–2) vs high grade (G3) (yasuda2024newclinicopathologicalconcept pages 1-3).

Molecular classification now integrated into routine practice

Multiple 2024 reviews emphasize that the TCGA-derived 4-group molecular taxonomy has been translated into pragmatic classifiers (ProMisE/TransPORTEC) and is being integrated into pathology reporting and staging (WHO 2020; FIGO 2023) (nagel2024predictivebiomarkersin pages 1-2, yasuda2024newclinicopathologicalconcept pages 1-3).

2. Etiology

Primary causal factors (mechanistic framing)

EEC is commonly conceptualized as an estrogen-driven malignancy in which hormonal and metabolic contexts (obesity, hyperestrogenism, insulin resistance) promote endometrial proliferation and progression to carcinoma, with cooperating somatic genomic alterations defining molecular subtypes and therapeutic vulnerabilities (clontz2024effectsofweight pages 1-2, ribeirosantos2024tailoringendometrialcancer pages 2-3).

Risk factors (quantitative, recent where possible)

Metabolic/hormonal risk factors

  • Obesity and metabolic dysfunction: A 2024 meta-analysis of metabolic obesity phenotypes reported that metabolically unhealthy overweight/obese individuals had substantially higher endometrial cancer risk vs metabolically healthy normal weight (SRR 2.31, 95% CI 2.08–2.57; high certainty) (Mahamat‑saleh et al., Br J Cancer, published 2024-09-??; https://doi.org/10.1038/s41416-024-02857-7) (mahamatsaleh2024associationofmetabolic pages 1-2).
  • Polycystic ovary syndrome (PCOS): A 2023 meta-analysis concluded: “Females with PCOS had a significantly increased odds of developing endometrial cancer” with OR 4.07 (95% CI 2.13–7.78), and when excluding postmenopausal subjects the odds increased to OR 5.14 (95% CI 3.22–8.21) (Johnson et al., Oncology Letters, 2023-03-??; https://doi.org/10.3892/ol.2023.13754) (johnson2023riskofendometrial pages 1-2).
  • Age/menopause context: Reviews emphasize endometrioid cancers are often diagnosed in peri-/postmenopausal women and obesity is particularly relevant post-menopause due to adipose aromatase as a major estrogen source (clontz2024effectsofweight pages 1-2, ribeirosantos2024tailoringendometrialcancer pages 2-3).

Hereditary predisposition (genetic etiology)

  • Lynch syndrome (LS): A 2023 review notes LS is estimated to be the hereditary cause in ~3% of endometrial cancer and that LS-related tumors often demonstrate an MMR-deficient (MMRd) pattern detectable by IHC (Capasso et al., Cancers, 2023-02-??; https://doi.org/10.3390/cancers15051400) ().

Protective factors (quantitative)

  • Bariatric surgery (obesity intervention): A 2023 systematic review/meta-analysis reported bariatric surgery was associated with reduced future incidence of endometrial cancer (RR 0.38, 95% CI 0.26–0.55) (Wilson et al., Int J Mol Sci, 2023-03-??; https://doi.org/10.3390/ijms24076192) (wilson2023systematicreviewand pages 1-2).
  • Weight loss effects on mechanistic biomarkers: A 2024 systematic review/meta-analysis reported bariatric surgery produced an overall 25.8% weight reduction and weight loss reduced inflammatory biomarkers linked to endometrioid EC risk (e.g., CRP −33.5%, IL-6 −41.9%) (Clontz et al., Cancers, 2024-06-??; https://doi.org/10.3390/cancers16122197) (clontz2024effectsofweight pages 18-19).

Gene–environment interactions (current state)

The retrieved evidence supports a strong interaction framework in which environmental/metabolic exposures (obesity, insulin resistance, inflammatory milieu) act upstream of signaling pathways frequently altered in endometrioid EC (e.g., PI3K/AKT/mTOR), but specific, validated variant-by-exposure interaction effect sizes were not retrieved in the current corpus (clontz2024effectsofweight pages 18-19).

3. Phenotypes (clinical presentation, pathology; HPO suggestions)

Common presentation and key clinicopathologic traits

While the most common symptom (abnormal uterine bleeding) is not explicitly captured in the retrieved excerpts, EEC is emphasized as the dominant endometrial cancer histotype and is frequently diagnosed at early stage (often localized) in population-based datasets (liu2023differentialtrendsin pages 2-4). Yasuda (2024) provides histotype distribution in a referenced series with endometrioid adenocarcinoma grades: G1 54.1%, G2 18.9%, G3 8.7% (yasuda2024newclinicopathologicalconcept pages 1-3).

Suggested phenotype (HPO) terms (not exhaustive)

  • Abnormal uterine bleeding (HP:0000132)
  • Postmenopausal bleeding (HP:0000858)
  • Pelvic pain (HP:0030834)
  • Anemia (HP:0001903) (secondary)
  • Endometrial neoplasm / carcinoma (HPO term availability varies; may map via disease ontology)

Phenotype frequency and QoL impact: Not systematically retrievable from current excerpts; would require symptom-focused cohort studies.

4. Genetic / Molecular information

4.1 Clinically used molecular subtypes (TCGA / ProMisE)

Contemporary clinical practice increasingly applies the TCGA-derived four molecular classes operationalized by ProMisE/TransPORTEC using POLE sequencing plus MMR and p53 IHC surrogates: POLEmut, MMRd/MSI-H, p53abn, and NSMP (nagel2024predictivebiomarkersin pages 1-2, yasuda2024newclinicopathologicalconcept pages 1-3).

Molecular subtype Defining tests / practical surrogates Typical frequency reported in retrieved sources General prognosis Key therapy implications
POLEmut / ultramutated Pathogenic POLE exonuclease-domain mutation by sequencing/NGS; in ProMisE workflow, POLE testing is integrated with MMR and p53 IHC, and WHO 2020 prioritizes POLEmut classification when present ~7–10% overall in EC; 7.8% in Ruscelli 2023 cohort; ~10% in Yasuda 2024; 8–10% overall and 6.4% low-grade endometrioid / 17.4% high-grade endometrioid in TCGA summary cited by Ribeiro-Santos 2024; 7% in Yang 2024 (ruscelli2023prognosticimpactof pages 1-2, yasuda2024newclinicopathologicalconcept pages 3-4, ribeirosantos2024tailoringendometrialcancer pages 2-3, yang2024molecularsubtypesof pages 4-5, yasuda2024newclinicopathologicalconcept pages 1-3) Excellent / best prognosis, even when conventional histology appears high risk (nagel2024predictivebiomarkersin pages 2-4, yasuda2024newclinicopathologicalconcept pages 3-4, ruscelli2023prognosticimpactof pages 1-2) Supports adjuvant de-escalation/observation in appropriate early-stage patients; POLE tumors appear to derive little benefit from adjuvant radiotherapy; FIGO 2023 incorporates IAm_POLEmut modifier (nagel2024predictivebiomarkersin pages 2-4, yasuda2024newclinicopathologicalconcept pages 1-3, berek2023figostagingof media 9e3676d6)
MMRd / MSI-H / hypermutated Loss of MLH1, PMS2, MSH2, or MSH6 by IHC; MSI testing by PCR/NGS as adjunct; if MLH1/PMS2 loss, reflex MLH1 promoter hypermethylation testing helps distinguish sporadic cases from Lynch syndrome-associated tumors Commonly ~24–32% overall; 31.0% in Ruscelli 2023; 32.2% in de Biase 2023; 28% in Yang 2024; ~30% MSI/MMRd noted in Addante 2024; Yasuda 2024 reports MSI in ~40% of endometrioid adenocarcinomas (ruscelli2023prognosticimpactof pages 1-2, yang2024molecularsubtypesof pages 4-5, addante2024mismatchrepairdeficiency pages 3-5, yasuda2024newclinicopathologicalconcept pages 3-4) Intermediate prognosis overall, but heterogeneous; MLH1-hypermethylated/sporadic MMRd may behave worse than Lynch-like/germline-associated MMRd subsets (addante2024mismatchrepairdeficiency pages 3-5, yasuda2024newclinicopathologicalconcept pages 3-4) Strongest current implication is immune checkpoint inhibitor sensitivity/eligibility: anti–PD-1/PD-L1 therapies in advanced/recurrent disease; first-line chemo-immunotherapy shows especially large benefit in dMMR populations; also central for Lynch syndrome universal screening (nagel2024predictivebiomarkersin pages 2-4, mirza2023dostarlimabforprimary pages 10-11, mirza2023dostarlimabforprimary pages 1-3, eskander2023pembrolizumabpluschemotherapy pages 6-7, eskander2023pembrolizumabpluschemotherapy pages 1-3, addante2024mismatchrepairdeficiency pages 3-5)
NSMP / copy-number low / p53wt No pathogenic POLE mutation, MMR retained by IHC, and wild-type p53 staining pattern; assigned after exclusion of POLEmut, MMRd, and p53abn in practical classifiers Often the largest subgroup: 39.3% in de Biase 2023; 40.2% in Ruscelli 2023; 39% in Yang 2024; ~60% of low copy-number tumors are low-grade endometrioid in TCGA summary cited by Ribeiro-Santos 2024 (ruscelli2023prognosticimpactof pages 1-2, yang2024molecularsubtypesof pages 4-5, ribeirosantos2024tailoringendometrialcancer pages 2-3) Intermediate prognosis, but clinically heterogeneous; in NSMP, traditional pathologic features such as grade, stage, necrosis, and substantial LVSI remain important prognostic modifiers (ruscelli2023prognosticimpactof pages 1-2, nagel2024predictivebiomarkersin pages 2-4) Management remains driven by integrated clinicopathologic risk; brachytherapy/adjuvant tailoring may be relevant in selected early-stage cases, but there is no single defining targeted systemic therapy yet; this group is a priority for further biomarker refinement (nagel2024predictivebiomarkersin pages 2-4, ruscelli2023prognosticimpactof pages 1-2)
p53abn / copy-number high / serous-like Abnormal p53 IHC pattern (overexpression, null, or cytoplasmic pattern) as surrogate for TP53 alteration; assigned after excluding POLEmut in integrated algorithms Roughly 20–26% overall across mixed EC cohorts; 20.9% in Ruscelli 2023; 26% in Yang 2024; 6.7% in the small Guo 2024 cohort; p53-abnormality enriched in high-grade/aggressive tumors and estimated at ~30% of FIGO grade 3 endometrioid EC in Casanova 2024 meta-analysis (ruscelli2023prognosticimpactof pages 1-2, yang2024molecularsubtypesof pages 4-5, nagel2024predictivebiomarkersin pages 2-4) Poor / worst prognosis among the four groups, with higher recurrence and mortality (nagel2024predictivebiomarkersin pages 2-4, ruscelli2023prognosticimpactof pages 1-2) Supports adjuvant intensification, including added chemotherapy and external-beam radiotherapy in appropriate settings; FIGO 2023 uses IICm_p53abn modifier for early-stage disease with p53 abnormality; p53abn disease is also an important subgroup in ongoing/improving immunotherapy datasets (nagel2024predictivebiomarkersin pages 2-4, berek2023figostagingof media 9e3676d6)

Table: This table summarizes the four TCGA/ProMisE molecular subtypes used clinically in endometrial carcinoma, with practical diagnostic surrogates, approximate frequencies from the retrieved literature, prognostic direction, and major treatment implications.

4.2 Subtype proportions (examples from clinical cohorts)

In a 2023 clinical cohort classified per WHO algorithm, subtypes were 7.8% POLE, 31% MMRd, 21% p53abn, 40.2% NSMP (Ruscelli et al., J Pers Med, 2023-04-??; https://doi.org/10.3390/jpm13050723) (ruscelli2023prognosticimpactof pages 1-2). A separate 2023 cohort similarly found molecular analysis success in all cases with subgroup fractions including 7.6% POLE, 32.2% MMRd, 20.9% p53abn, 39.3% NSMP (de Biase et al., Front Med, 2023-03-??; https://doi.org/10.3389/fmed.2023.1146499) (ruscelli2023prognosticimpactof pages 1-2).

4.3 Key genes and targets (disease-level resources)

Open Targets lists multiple associated targets for “Endometrial Endometrioid Adenocarcinoma” including PTEN, ARID1A, CTNNB1, MLH1 among others, supported by literature evidence aggregation (OpenTargets Search: endometrioid endometrial adenocarcinoma,endometrial carcinoma).

4.4 Epigenetic features (MLH1 promoter hypermethylation)

MMRd/MSI-H EEC includes a clinically important epigenetic subset driven by MLH1 promoter hypermethylation, which is distinguished from suspected-LS tumors in routine workflows; a study in 527 ECs categorized “met-EC” (MLH1-PHM) and found it had a higher fraction of stage III/IV disease (37.2%) and worse OS/PFS than suspected-LS in that cohort (Kaneko et al., J Gynecol Oncol, 2021; https://doi.org/10.3802/jgo.2021.32.e79) (addante2024mismatchrepairdeficiency pages 3-5).

5. Mechanism / pathophysiology (causal chains; GO/CL suggestions)

5.1 Estrogen–obesity–inflammation axis (upstream drivers)

A recent meta-analysis frames endometrioid EC risk as strongly influenced by obesity-driven endocrine changes: adipocytes serve as a primary estrogen source post-menopause via aromatase, and obesity is linked to insulin resistance and chronic inflammation (clontz2024effectsofweight pages 1-2). Weight loss interventions reduce inflammatory mediators implicated in carcinogenesis (CRP, IL-6) (clontz2024effectsofweight pages 18-19).

Suggested GO biological process terms (examples): - GO:0008284 positive regulation of cell population proliferation - GO:0071396 cellular response to lipid - GO:0006954 inflammatory response - GO:0001525 angiogenesis

5.2 DNA repair deficiency and immune microenvironment (MMRd/MSI-H)

MMRd/MSI-H tumors have high mutation burden and are a key predictive biomarker class for immune checkpoint inhibition; IHC for MMR proteins is an “optimal diagnostic MSI surrogate worldwide” according to a 2024 review (Addante et al., Int J Mol Sci, 2024-01-??; https://doi.org/10.3390/ijms25021056) (addante2024mismatchrepairdeficiency pages 3-5).

Suggested GO terms: - GO:0006298 mismatch repair - GO:0006974 cellular response to DNA damage stimulus - GO:0006955 immune response

5.3 PI3K/AKT/mTOR signaling and metabolic coupling

The weight-loss meta-analysis highlights PI3K/Akt/mTOR pathway activation as part of the obesity-related mechanistic link to endometrioid EC risk (clontz2024effectsofweight pages 18-19).

Suggested GO terms: - GO:0014068 positive regulation of phosphatidylinositol 3-kinase signaling - GO:0032147 activation of protein kinase B activity

5.4 Cell types (Cell Ontology suggestions)

  • Endometrial glandular epithelial cell (CL:0002563, if available)
  • Endometrial stromal cell (appropriate CL mapping)
  • Tumor-infiltrating lymphocyte / T cell (CL:0000084, T cell)
  • Macrophage (CL:0000235) (obesity-associated inflammatory milieu)

6. Environmental information

Lifestyle/environmental factors with strongest retrieved evidence

  • Obesity and metabolic dysfunction as modifiable exposures (mahamatsaleh2024associationofmetabolic pages 1-2, wilson2023systematicreviewand pages 1-2).
  • Nutritional patterns and other exposures were not comprehensively retrieved in the current evidence corpus.

Infectious agents: No infectious etiology is supported in the retrieved evidence.

7. Anatomical structures affected (UBERON/CL/GO CC suggestions)

Primary affected site

  • Endometrium of uterine corpus (UBERON:0001295 endometrium; UBERON:0000995 uterus—verify exact IDs in ontology curation).

Tissue/cell level

  • Endometrial epithelium (glandular epithelium) (yasuda2024newclinicopathologicalconcept pages 1-3).

Subcellular localization (typical for key biomarkers)

  • Nucleus (p53 IHC; MMR proteins IHC) (GO:0005634 nucleus)

8. Temporal development

Onset

EEC is typically diagnosed in older adult women (mean age in one review context: 62 years) (yang2024molecularsubtypesof pages 4-5).

Progression and staging

FIGO 2023 updated staging incorporates histology/grade/LVSI and, critically, molecular alterations. The FIGO staging paper states that “the presence of pathogenic POLE mutations or of p53 abnormalities now modifies the FIGO stage” (Berek et al., Int J Gynecol Obstet, 2023-06-??; https://doi.org/10.1002/ijgo.14923) (berek2023figostagingof media 9e3676d6).

A key implementation detail is reflected in the FIGO 2023 staging tables (image evidence): molecular stage modifiers include IAm_POLEmut and IICm_p53abn, and an “m” subscript plus subtype can be added when molecular class is known (berek2023figostagingof media 9e3676d6, berek2023figostagingof media f7c3e53d, berek2023figostagingof media 4b64842a).

9. Inheritance and population

Population incidence and trends (recent, quantitative)

  • A large US registry analysis (1995–2018) found endometrial cancer incidence rising for both early-onset (<50) and late-onset disease, with early-onset increasing faster (AAPC 1.8% vs 0.7% overall), and highlighted disparities by race/ethnicity (e.g., early-onset AAPC 3.5% in Non-Hispanic Black women) (Liu et al., JNCI Cancer Spectrum, 2023-01-??; https://doi.org/10.1093/jncics/pkad001) (liu2023differentialtrendsin pages 2-4).
  • The same analysis reported 930,176 invasive EC cases total, with 12.6% early-onset; early-onset had higher proportion of endometrioid histology (87.0% vs 79.0%) (liu2023differentialtrendsin pages 2-4).

US case/death estimates (2023)

A SEER-focused elderly-women trends paper cites: “66,200 new U.S. cases and 13,030 deaths in 2023” for uterine cancer (corpus) (Priyadarshini et al., Aging Medicine, 2024-04-??; https://doi.org/10.1002/agm2.12297) (priyadarshini2024trendsingynecological pages 1-2).

Inheritance pattern (subset)

  • Lynch syndrome (autosomal dominant cancer predisposition) is a key inherited etiology for a minority of cases; universal screening is widely recommended (, ).

10. Diagnostics

Standard diagnostic approach (current practice emphasis)

  • Histopathology from endometrial biopsy/curettage or hysterectomy specimen with FIGO grading (yasuda2024newclinicopathologicalconcept pages 1-3).
  • Molecular classification surrogates in pathology (POLE sequencing + p53 and MMR IHC) are increasingly recommended/endorsed in WHO 2020 and FIGO 2023 frameworks to support prognostication and treatment decisions (nagel2024predictivebiomarkersin pages 1-2, yasuda2024newclinicopathologicalconcept pages 1-3).

MMR/MSI testing and Lynch syndrome screening

  • A 2024 real-world institutional study states international guidelines recommend universal LS screening in endometrial cancer and reports implementation metrics: among 331 patients, 30.8% were MMR-deficient and 0.9% diagnosed with Lynch syndrome, with screening adherence improving to 90.6% over time (Joder et al., Cancers, 2024-02-??; https://doi.org/10.3390/cancers16030671) ().

Practical biomarker implication for systemic therapy

A 2024 pathology review notes MMRd has predictive value for immunotherapy; in the palliative setting, MMRd tumors can receive anti–PD-(L)1 monotherapy, whereas MMR-proficient tumors may receive pembrolizumab + lenvatinib (nagel2024predictivebiomarkersin pages 2-4).

Differential diagnosis (not exhaustive)

  • Non-endometrioid endometrial carcinomas (serous, clear cell, carcinosarcoma) which are molecularly and clinically distinct (yasuda2024newclinicopathologicalconcept pages 1-3).

11. Outcome / prognosis

Molecular subtype as a prognostic axis

Across cohorts and reviews, prognostic ordering is generally: POLEmut best, MMRd and NSMP intermediate, p53abn worst (ruscelli2023prognosticimpactof pages 1-2, yasuda2024newclinicopathologicalconcept pages 3-4, nagel2024predictivebiomarkersin pages 1-2).

Stage and histopathologic modifiers remain important

Within NSMP and MMRd groups, standard pathologic factors (stage, LVSI, lymph node status) retain prognostic importance (ruscelli2023prognosticimpactof pages 1-2).

Example survival statistics from retrieved sources

  • Yang (2024) reports an “overall relative 5-year survival of 81.1%” in the endometrioid endometrial cancer context (review statement) (yang2024molecularsubtypesof pages 4-5).

12. Treatment (current applications; 2023–2024 pivotal trials)

12.1 Standard local management (high-level)

The retrieved evidence corpus is dominated by systemic therapy advances; detailed surgical/radiation algorithms specific to EEC were not directly retrieved. Molecular-risk integration into adjuvant decisions is emphasized in 2024 reviews and in ESGO/ESTRO/ESP risk classification studies (nagel2024predictivebiomarkersin pages 2-4, ruscelli2023prognosticimpactof pages 1-2).

12.2 First-line systemic therapy advances (real-world implementing evidence from phase 3)

Dostarlimab + carboplatin/paclitaxel (RUBY, phase 3)

Mirza et al. report that in the dMMR–MSI-H subgroup, “estimated progression-free survival at 24 months was 61.4% … in the dostarlimab group and 15.7% … in the placebo group (hazard ratio … 0.28; … P<0.001)” and in the overall population 24-month PFS was 36.1% vs 18.1% (Mirza et al., NEJM, 2023-06-08; https://doi.org/10.1056/NEJMoa2216334) (mirza2023dostarlimabforprimary pages 1-3). Safety signals included higher grade ≥3 events and immune-related events in the dostarlimab arm (mirza2023dostarlimabforprimary pages 10-11).

Pembrolizumab + carboplatin/paclitaxel (NRG-GY018, phase 3)

Eskander et al. report (dMMR cohort) 12-month Kaplan–Meier PFS of 74% with pembrolizumab vs 38% with placebo (HR 0.30; 95% CI 0.19–0.48; P<0.001) and (pMMR cohort) median PFS 13.1 months vs 8.7 months (HR 0.54; P<0.001) (Eskander et al., NEJM, 2023-06-08; https://doi.org/10.1056/NEJMoa2302312) (eskander2023pembrolizumabpluschemotherapy pages 6-7, eskander2023pembrolizumabpluschemotherapy pages 1-3).

12.3 MAXO (Medical Action Ontology) suggestions (examples)

  • Hysterectomy (MAXO term for hysterectomy)
  • Bilateral salpingo-oophorectomy
  • External beam radiation therapy
  • Vaginal brachytherapy
  • Combination chemotherapy (carboplatin + paclitaxel)
  • Immune checkpoint inhibitor therapy (anti-PD-1)

13. Prevention

Primary prevention (risk reduction)

Evidence supports prevention via reduction of obesity/metabolic dysfunction. Bariatric surgery is associated with reduced endometrial cancer incidence (RR 0.38) (wilson2023systematicreviewand pages 1-2), and weight-loss interventions reduce inflammatory biomarkers linked to risk (clontz2024effectsofweight pages 18-19).

Secondary prevention (screening / early detection)

  • Universal tumor testing for MMR deficiency to identify Lynch syndrome and inform therapeutic options is increasingly implemented, but adherence varies; reflex/standardized pathways are recommended ().

Tertiary prevention

  • Molecularly guided therapy selection (e.g., dMMR-directed immunotherapy) to reduce recurrence/progression risk in advanced settings (mirza2023dostarlimabforprimary pages 1-3, eskander2023pembrolizumabpluschemotherapy pages 6-7).

14. Other species / natural disease

Not addressed in retrieved evidence.

15. Model organisms

Not addressed in retrieved evidence.

Recent developments (2023–2024) and expert synthesis

  1. Histomolecular integration is now central: authoritative pathology reviews describe molecular classification as endorsed by WHO (2020) and integrated into FIGO 2023 staging updates (nagel2024predictivebiomarkersin pages 1-2, yasuda2024newclinicopathologicalconcept pages 1-3, berek2023figostagingof media 9e3676d6).
  2. First-line chemo-immunotherapy has changed practice: RUBY and NRG-GY018 demonstrate large PFS gains, especially in dMMR/MSI-H disease, supporting routine MMR testing as both a hereditary screen and a predictive biomarker (mirza2023dostarlimabforprimary pages 1-3, eskander2023pembrolizumabpluschemotherapy pages 6-7, addante2024mismatchrepairdeficiency pages 3-5).
  3. Metabolic prevention is a major real-world lever: high-certainty meta-analytic evidence links combined obesity + metabolic dysfunction to substantially increased endometrial cancer risk, and bariatric surgery shows a large protective association (mahamatsaleh2024associationofmetabolic pages 1-2, wilson2023systematicreviewand pages 1-2).

Visual evidence (FIGO 2023)

The FIGO 2023 staging tables illustrating molecular modifiers (e.g., IAm_POLEmut, IICm_p53abn) are provided in the cited table images from the FIGO staging publication (berek2023figostagingof media 9e3676d6, berek2023figostagingof media f7c3e53d, berek2023figostagingof media 4b64842a).

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