EBV-Associated Gastric Cancer

MONDO:0001056 Pathograph 5 gastric cancer

Epstein-Barr virus (EBV)-associated gastric cancer is a distinct molecular subtype of gastric adenocarcinoma characterized by clonal EBV infection of tumor cells, extreme CpG island methylator phenotype (CIMP-high), frequent PIK3CA mutations, and JAK2/PD-L1/PD-L2 amplifications. EBV-positive gastric cancers comprise approximately 9% of all gastric cancers worldwide and show unique features including prominent lymphoid infiltration, better prognosis than other subtypes, and potential responsiveness to immune checkpoint inhibitors. The viral oncoproteins LMP1, LMP2A, and EBNA1 drive epigenetic reprogramming and survival signaling in infected epithelial cells.

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Mappings

Definitions

Inheritance

Subtypes

Differentials

Datasets

Trials

Models

References

Deep Research

🏷

Classifications

Harrison's Chapter

ICD-O Morphology

⚙

Pathophysiology

EBV Latent Infection of Gastric Epithelium

EBV establishes clonal latent infection in gastric epithelial cells, expressing a restricted set of latent genes including EBNA1 (required for viral genome maintenance), LMP2A (mimics B-cell receptor signaling), and non-coding EBERs. LMP1 expression is variable but when present activates NF-kappaB and MAPK pathways.

epithelial cell link

viral transcription link

stomach link

Downstream

Epigenetic Reprogramming and CIMP-High Phenotype EBV infection induces massive DNA methylation changes

PI3K-AKT Pathway Activation LMP2A signaling and PIK3CA mutations activate survival pathways

Epigenetic Reprogramming and CIMP-High Phenotype

EBV-associated gastric cancer displays the most extreme CpG island methylator phenotype (CIMP) of any cancer type. EBV-encoded proteins, particularly LMP2A, induce aberrant DNA methylation leading to silencing of tumor suppressor genes including CDKN2A (p16), CDH1 (E-cadherin), and MLH1. This epigenetic reprogramming is a hallmark feature distinguishing EBV-positive from EBV-negative gastric cancers.

DNA methylation link ↑ INCREASED

Downstream

Tumor Suppressor Gene Silencing CDKN2A, CDH1, and other tumor suppressors are silenced by promoter methylation

Show evidence (1 reference)

PMID:25079317 SUPPORT Human Clinical

"EBV-positive tumours had a higher prevalence of DNA hypermethylation than any cancers reported by TCGA"

TCGA confirmed that EBV-positive gastric cancers exhibit the most extreme CIMP-high methylation phenotype across all cancers profiled.

PI3K-AKT Pathway Activation

PIK3CA mutations occur in approximately 80% of EBV-positive gastric cancers, the highest frequency of any gastric cancer subtype. Combined with LMP2A signaling which activates PI3K through mimicry of B-cell receptor signaling, this leads to constitutive AKT activation promoting cell survival and proliferation.

signal transduction link ↑ INCREASED

Downstream

Uncontrolled Cell Proliferation PI3K-AKT signaling promotes cell survival and growth

Show evidence (1 reference)

PMID:25079317 SUPPORT Human Clinical

"non-silent PIK3CA mutations found in 80% of this subgroup"

TCGA reports non-silent PIK3CA mutations in 80% of EBV-positive gastric cancers, the highest rate of any subgroup.

Tumor Suppressor Gene Silencing

Promoter hypermethylation silences multiple tumor suppressor genes. CDKN2A (p16INK4A) silencing removes G1/S checkpoint control. CDH1 (E-cadherin) silencing promotes epithelial-mesenchymal transition. Unlike other gastric cancer subtypes, TP53 mutations are rare in EBV-positive tumors.

cell cycle checkpoint signaling link ↓ DECREASED

Show evidence (1 reference)

PMID:25079317 SUPPORT Human Clinical

"All EBV-positive tumours assayed displayed CDKN2A (p16INK4A) promoter hypermethylation"

Universal CDKN2A promoter hypermethylation in EBV-positive gastric cancers epigenetically silences this tumor suppressor and removes G1/S checkpoint control.

Uncontrolled Cell Proliferation

Combined effects of PI3K-AKT activation, tumor suppressor silencing, and viral oncogene expression drive uncontrolled proliferation of infected gastric epithelial cells, leading to tumor formation.

epithelial cell link

cell population proliferation link ↑ INCREASED

✶

Histopathology

Gastric Adenocarcinoma VERY_FREQUENT

Adenocarcinoma is the most common histologic type of gastric cancer.

Show evidence (1 reference)

PMID:40647518 PARTIAL

"with adenocarcinoma being the most "

Supports adenocarcinoma predominance in gastric cancer generally, but not specifically in EBV-associated cases.

⬡

Pathograph

Use the checkboxes to hide or show graph categories. Hover nodes for evidence and cross-linked metadata.

●

Phenotypes

Blood 1

Anemia FREQUENT Anemia (HP:0001903)

Show evidence (1 reference)

PMID:30179903 SUPPORT Human Clinical

"Only 18.3% of patients had a self-reported history of IDA, 40% had IDA at the time of gastric cancer diagnosis, and 58.7% were anemic."

Retrospective Canadian review of 126 gastric cancer patients quantifies the high prevalence of iron deficiency anemia (40%) and anemia overall (58.7%) at diagnosis, supporting anemia as a frequent phenotype.

Cardiovascular 1

Lymphadenopathy OCCASIONAL Lymphadenopathy (HP:0002716)

Digestive 1

Hepatomegaly OCCASIONAL Hepatomegaly (HP:0002240)

Constitutional 2

Abdominal Pain FREQUENT Abdominal pain (HP:0002027)

Show evidence (1 reference)

PMID:38966500 SUPPORT Human Clinical

"Weight loss and persistent abdominal pain are the most common symptoms at initial diagnosis."

Clinical features review identifies persistent abdominal pain as one of the two most common symptoms of gastric cancer at initial diagnosis, supporting its inclusion as a frequent phenotype in EBV-associated gastric cancer (a molecular subtype of gastric adenocarcinoma).

Fatigue FREQUENT Fatigue (HP:0012378)

Show evidence (1 reference)

PMID:29266530 SUPPORT Human Clinical

"The incidence of clinically relevant fatigue among patients with gastric cancer was 91.6%."

Cross-sectional study of 203 gastric cancer patients found a 91.6% incidence of clinically relevant fatigue, supporting its inclusion as a frequent phenotype in gastric cancer.

Growth 1

Weight Loss FREQUENT Weight loss (HP:0001824)

Show evidence (1 reference)

PMID:38966500 SUPPORT Human Clinical

"Weight loss and persistent abdominal pain are the most common symptoms at initial diagnosis."

Clinical features review identifies weight loss as one of the two most common symptoms of gastric cancer at initial diagnosis, supporting its inclusion as a frequent constitutional phenotype.

🧬

Genetic Associations

PIK3CA (Somatic Mutation)

ARID1A (Somatic Mutation)

CDKN2A (Epigenetically Silenced)

💊

Treatments

Surgical Resection

Action: surgical procedure MAXO:0000004

Gastrectomy with lymph node dissection is the primary treatment for localized disease. EBV-positive tumors have relatively favorable prognosis compared to other molecular subtypes.

Chemotherapy

Action: chemotherapy MAXO:0000647

Perioperative or palliative chemotherapy with fluoropyrimidine-based regimens (FOLFOX, CAPOX) is standard for advanced disease.

Immune Checkpoint Inhibitors

Action: immunotherapy Ontology label: Immunotherapy NCIT:C15262

EBV-positive gastric cancers show high expression of PD-L1 due to 9p24.1 amplification and strong immune infiltration, making them potentially responsive to PD-1/PD-L1 inhibitors such as pembrolizumab or nivolumab. This represents a molecularly-targeted approach based on the unique immunobiology of this subtype.

🔬

Biochemical Markers

EBV-Encoded Small RNAs (EBERs)

PD-L1/PD-L2 Expression

{ }

Source YAML

click to show

name: EBV-Associated Gastric Cancer
creation_date: '2026-01-26T02:55:13Z'
updated_date: '2026-04-22T20:13:21Z'
description: >-
  Epstein-Barr virus (EBV)-associated gastric cancer is a distinct molecular subtype
  of gastric adenocarcinoma characterized by clonal EBV infection of tumor cells,
  extreme CpG island methylator phenotype (CIMP-high), frequent PIK3CA mutations,
  and JAK2/PD-L1/PD-L2 amplifications. EBV-positive gastric cancers comprise approximately
  9% of all gastric cancers worldwide and show unique features including prominent
  lymphoid infiltration, better prognosis than other subtypes, and potential responsiveness
  to immune checkpoint inhibitors. The viral oncoproteins LMP1, LMP2A, and EBNA1 drive
  epigenetic reprogramming and survival signaling in infected epithelial cells.
categories:
- Gastrointestinal Cancer
- Virus-Associated Cancer
- Solid Tumor
parents:
- gastric cancer
infectious_agent:
- name: Epstein-Barr Virus (EBV)
  infectious_agent_term:
    preferred_term: Human gammaherpesvirus 4
    term:
      id: NCBITaxon:10376
      label: Human gammaherpesvirus 4
  description: >-
    Clonal EBV infection of gastric epithelial cells is the initiating event.
    Unlike EBV lymphomas where infection occurs in B cells, EBV gastric cancer
    involves epithelial cell tropism. The virus establishes latent infection
    (type I/II latency) with expression of EBNA1, LMP2A, and EBERs, with variable
    LMP1 expression. EBV-encoded oncoproteins drive epigenetic reprogramming and
    activate survival signaling pathways.
  evidence:
  - reference: PMID:41280003
    reference_title: "Integrated transcriptomic and methylome analysis reveals retinoic acid pathway activation after decitabine treatment in EBV associated gastric cancer."
    supports: PARTIAL
    snippet: Epstein-Barr virus associated gastric cancer (EBVaGC) accounts for ~9-10% of gastric cancers worldwide and is defined by a distinctive molecular profile, including extreme hypermethylation of the DNA.
    explanation: Supports EBV association and molecular distinctness, but does not directly establish clonal infection as the initiating event.
pathophysiology:
- name: EBV Latent Infection of Gastric Epithelium
  description: >-
    EBV establishes clonal latent infection in gastric epithelial cells, expressing
    a restricted set of latent genes including EBNA1 (required for viral genome
    maintenance), LMP2A (mimics B-cell receptor signaling), and non-coding EBERs.
    LMP1 expression is variable but when present activates NF-kappaB and MAPK pathways.
  cell_types:
  - preferred_term: epithelial cell
    term:
      id: CL:0000066
      label: epithelial cell
  locations:
  - preferred_term: stomach
    term:
      id: UBERON:0000945
      label: stomach
  biological_processes:
  - preferred_term: viral transcription
    term:
      id: GO:0019083
      label: viral transcription
  downstream:
  - target: Epigenetic Reprogramming and CIMP-High Phenotype
    description: EBV infection induces massive DNA methylation changes
  - target: PI3K-AKT Pathway Activation
    description: LMP2A signaling and PIK3CA mutations activate survival pathways
- name: Epigenetic Reprogramming and CIMP-High Phenotype
  description: >-
    EBV-associated gastric cancer displays the most extreme CpG island methylator
    phenotype (CIMP) of any cancer type. EBV-encoded proteins, particularly LMP2A,
    induce aberrant DNA methylation leading to silencing of tumor suppressor genes
    including CDKN2A (p16), CDH1 (E-cadherin), and MLH1. This epigenetic reprogramming
    is a hallmark feature distinguishing EBV-positive from EBV-negative gastric cancers.
  evidence:
  - reference: PMID:25079317
    reference_title: "Comprehensive molecular characterization of gastric adenocarcinoma."
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: "EBV-positive tumours had a higher prevalence of DNA hypermethylation than any cancers reported by TCGA"
    explanation: TCGA confirmed that EBV-positive gastric cancers exhibit the most extreme CIMP-high methylation phenotype across all cancers profiled.
  biological_processes:
  - preferred_term: DNA methylation
    modifier: INCREASED
    term:
      id: GO:0006304
      label: DNA modification
  downstream:
  - target: Tumor Suppressor Gene Silencing
    description: CDKN2A, CDH1, and other tumor suppressors are silenced by promoter methylation
- name: PI3K-AKT Pathway Activation
  description: >-
    PIK3CA mutations occur in approximately 80% of EBV-positive gastric cancers,
    the highest frequency of any gastric cancer subtype. Combined with LMP2A signaling
    which activates PI3K through mimicry of B-cell receptor signaling, this leads
    to constitutive AKT activation promoting cell survival and proliferation.
  evidence:
  - reference: PMID:25079317
    reference_title: "Comprehensive molecular characterization of gastric adenocarcinoma."
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: "non-silent PIK3CA mutations found in 80% of this subgroup"
    explanation: TCGA reports non-silent PIK3CA mutations in 80% of EBV-positive gastric cancers, the highest rate of any subgroup.
  biological_processes:
  - preferred_term: signal transduction
    modifier: INCREASED
    term:
      id: GO:0007165
      label: signal transduction
  downstream:
  - target: Uncontrolled Cell Proliferation
    description: PI3K-AKT signaling promotes cell survival and growth
- name: Tumor Suppressor Gene Silencing
  description: >-
    Promoter hypermethylation silences multiple tumor suppressor genes. CDKN2A
    (p16INK4A) silencing removes G1/S checkpoint control. CDH1 (E-cadherin) silencing
    promotes epithelial-mesenchymal transition. Unlike other gastric cancer subtypes,
    TP53 mutations are rare in EBV-positive tumors.
  evidence:
  - reference: PMID:25079317
    reference_title: "Comprehensive molecular characterization of gastric adenocarcinoma."
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: "All EBV-positive tumours assayed displayed CDKN2A (p16INK4A) promoter hypermethylation"
    explanation: Universal CDKN2A promoter hypermethylation in EBV-positive gastric cancers epigenetically silences this tumor suppressor and removes G1/S checkpoint control.
  biological_processes:
  - preferred_term: cell cycle checkpoint signaling
    modifier: DECREASED
    term:
      id: GO:0000075
      label: cell cycle checkpoint signaling
- name: Uncontrolled Cell Proliferation
  description: >-
    Combined effects of PI3K-AKT activation, tumor suppressor silencing, and viral
    oncogene expression drive uncontrolled proliferation of infected gastric epithelial
    cells, leading to tumor formation.
  cell_types:
  - preferred_term: epithelial cell
    term:
      id: CL:0000066
      label: epithelial cell
  biological_processes:
  - preferred_term: cell population proliferation
    modifier: INCREASED
    term:
      id: GO:0008283
      label: cell population proliferation
histopathology:
- name: Gastric Adenocarcinoma
  finding_term:
    preferred_term: Gastric Adenocarcinoma
    term:
      id: NCIT:C4004
      label: Gastric Adenocarcinoma
  frequency: VERY_FREQUENT
  description: Adenocarcinoma is the most common histologic type of gastric cancer.
  evidence:
  - reference: PMID:40647518
    reference_title: "A Histopathological and Surgical Analysis of Gastric Cancer: A Two-Year Experience in a Single Center."
    supports: PARTIAL
    snippet: "with adenocarcinoma being the most "
    explanation: Supports adenocarcinoma predominance in gastric cancer generally, but not specifically in EBV-associated cases.

phenotypes:
- category: Gastrointestinal
  name: Abdominal Pain
  frequency: FREQUENT
  description: >-
    Epigastric pain is a common presenting symptom, often initially attributed
    to dyspepsia or gastritis.
  phenotype_term:
    preferred_term: Abdominal pain
    term:
      id: HP:0002027
      label: Abdominal pain
  evidence:
  - reference: PMID:38966500
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: "Weight loss and persistent abdominal pain are the most common symptoms at initial diagnosis."
    explanation: >-
      Clinical features review identifies persistent abdominal pain as
      one of the two most common symptoms of gastric cancer at initial
      diagnosis, supporting its inclusion as a frequent phenotype in
      EBV-associated gastric cancer (a molecular subtype of gastric
      adenocarcinoma).
- category: Constitutional
  name: Weight Loss
  frequency: FREQUENT
  description: >-
    Unintentional weight loss occurs due to decreased appetite and metabolic
    effects of malignancy.
  phenotype_term:
    preferred_term: Weight loss
    term:
      id: HP:0001824
      label: Weight loss
  evidence:
  - reference: PMID:38966500
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: "Weight loss and persistent abdominal pain are the most common symptoms at initial diagnosis."
    explanation: >-
      Clinical features review identifies weight loss as one of the two
      most common symptoms of gastric cancer at initial diagnosis,
      supporting its inclusion as a frequent constitutional phenotype.
- category: Constitutional
  name: Fatigue
  frequency: FREQUENT
  description: >-
    Generalized fatigue related to chronic disease and often anemia from
    occult gastrointestinal blood loss.
  phenotype_term:
    preferred_term: Fatigue
    term:
      id: HP:0012378
      label: Fatigue
  evidence:
  - reference: PMID:29266530
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: "The incidence of clinically relevant fatigue among patients with gastric cancer was 91.6%."
    explanation: >-
      Cross-sectional study of 203 gastric cancer patients found a
      91.6% incidence of clinically relevant fatigue, supporting its
      inclusion as a frequent phenotype in gastric cancer.
- category: Hematologic
  name: Anemia
  frequency: FREQUENT
  description: >-
    Iron deficiency anemia from chronic gastrointestinal blood loss is common.
  phenotype_term:
    preferred_term: Anemia
    term:
      id: HP:0001903
      label: Anemia
  evidence:
  - reference: PMID:30179903
    supports: SUPPORT
    evidence_source: HUMAN_CLINICAL
    snippet: "Only 18.3% of patients had a self-reported history of IDA, 40% had IDA at the time of gastric cancer diagnosis, and 58.7% were anemic."
    explanation: >-
      Retrospective Canadian review of 126 gastric cancer patients
      quantifies the high prevalence of iron deficiency anemia (40%)
      and anemia overall (58.7%) at diagnosis, supporting anemia as
      a frequent phenotype.
- category: Abdominal
  name: Hepatomegaly
  frequency: OCCASIONAL
  description: >-
    Liver enlargement may indicate metastatic disease.
  phenotype_term:
    preferred_term: Hepatomegaly
    term:
      id: HP:0002240
      label: Hepatomegaly
- category: Lymphatic
  name: Lymphadenopathy
  frequency: OCCASIONAL
  description: >-
    Regional lymph node enlargement occurs with local spread.
  phenotype_term:
    preferred_term: Lymphadenopathy
    term:
      id: HP:0002716
      label: Lymphadenopathy
biochemical:
- name: EBV-Encoded Small RNAs (EBERs)
  notes: >-
    In situ hybridization for EBERs is the gold standard for diagnosing EBV-associated
    gastric cancer. EBERs are abundantly expressed non-coding RNAs present in all
    EBV latency programs and serve as reliable markers of EBV infection.
- name: PD-L1/PD-L2 Expression
  notes: >-
    JAK2/PD-L1/PD-L2 amplification at 9p24.1 is characteristic of EBV-positive
    gastric cancer, leading to high PD-L1 expression and potential responsiveness
    to immune checkpoint inhibitors.
genetic:
- name: PIK3CA
  association: Somatic Mutation
  notes: >-
    PIK3CA mutations occur in approximately 80% of EBV-positive gastric cancers,
    the highest rate among gastric cancer subtypes. Hotspot mutations in the
    helical (E545K) and kinase (H1047R) domains activate PI3K signaling.
- name: ARID1A
  association: Somatic Mutation
  notes: >-
    ARID1A mutations occur in approximately 55% of EBV-positive gastric cancers,
    contributing to chromatin remodeling dysfunction.
- name: CDKN2A
  association: Epigenetically Silenced
  notes: >-
    CDKN2A (p16INK4A) is silenced by promoter hypermethylation rather than
    mutation in EBV-positive gastric cancer, removing G1/S checkpoint control.
treatments:
- name: Surgical Resection
  description: >-
    Gastrectomy with lymph node dissection is the primary treatment for
    localized disease. EBV-positive tumors have relatively favorable prognosis
    compared to other molecular subtypes.
  treatment_term:
    preferred_term: surgical procedure
    term:
      id: MAXO:0000004
      label: surgical procedure
- name: Chemotherapy
  description: >-
    Perioperative or palliative chemotherapy with fluoropyrimidine-based
    regimens (FOLFOX, CAPOX) is standard for advanced disease.
  treatment_term:
    preferred_term: chemotherapy
    term:
      id: MAXO:0000647
      label: chemotherapy
- name: Immune Checkpoint Inhibitors
  description: >-
    EBV-positive gastric cancers show high expression of PD-L1 due to 9p24.1
    amplification and strong immune infiltration, making them potentially
    responsive to PD-1/PD-L1 inhibitors such as pembrolizumab or nivolumab.
    This represents a molecularly-targeted approach based on the unique
    immunobiology of this subtype.
  treatment_term:
    preferred_term: immunotherapy
    term:
      id: NCIT:C15262
      label: Immunotherapy
disease_term:
  preferred_term: gastric cancer
  term:
    id: MONDO:0001056
    label: gastric cancer

classifications:
  icdo_morphology:
    classification_value: Adenocarcinoma
  harrisons_chapter:
  - classification_value: cancer
  - classification_value: solid tumor
references:
- reference: DOI:10.1007/s10120-021-01215-3
  title: Landscape of EBV-positive gastric cancer
  found_in:
  - EBV_Associated_Gastric_Cancer-deep-research-falcon.md
  findings:
  - statement: Landscape of EBV-positive gastric cancer
    supporting_text: Landscape of EBV-positive gastric cancer
- reference: DOI:10.1038/s41598-023-45930-6
  title: Genetic landscape and PD-L1 expression in Epstein–Barr virus-associated gastric cancer according to the histological pattern
  found_in:
  - EBV_Associated_Gastric_Cancer-deep-research-falcon.md
  findings:
  - statement: Epstein–Barr virus (EBV)-associated gastric cancer (EBVaGC) is a distinct molecular subtype of gastric cancer.
    supporting_text: Epstein–Barr virus (EBV)-associated gastric cancer (EBVaGC) is a distinct molecular subtype of gastric cancer.
    evidence:
    - reference: DOI:10.1038/s41598-023-45930-6
      reference_title: Genetic landscape and PD-L1 expression in Epstein–Barr virus-associated gastric cancer according to the histological pattern
      supports: SUPPORT
      evidence_source: HUMAN_CLINICAL
      snippet: Epstein–Barr virus (EBV)-associated gastric cancer (EBVaGC) is a distinct molecular subtype of gastric cancer.
      explanation: Deep research cited this publication as relevant literature for EBV Associated Gastric Cancer.
- reference: DOI:10.1038/s41598-024-81764-6
  title: Association of PD-L1 positivity with Epstein Barr virus infection and microsatellite instability in gastric carcinomas with lymphoid stroma
  found_in:
  - EBV_Associated_Gastric_Cancer-deep-research-falcon.md
  findings:
  - statement: Association of PD-L1 positivity with Epstein Barr virus infection and microsatellite instability in gastric carcinomas with lymphoid stroma
    supporting_text: Association of PD-L1 positivity with Epstein Barr virus infection and microsatellite instability in gastric carcinomas with lymphoid stroma
- reference: DOI:10.1097/cji.0000000000000316
  title: 'Positive Status of Epstein-Barr Virus as a Biomarker for Gastric Cancer Immunotherapy: A Prospective Observational Study'
  found_in:
  - EBV_Associated_Gastric_Cancer-deep-research-falcon.md
  findings:
  - statement: Immunotherapy has exhibited promising but controversial results in gastric cancer; determining criteria for choosing the appropriate target population is still problematic.
    supporting_text: Immunotherapy has exhibited promising but controversial results in gastric cancer; determining criteria for choosing the appropriate target population is still problematic.
    evidence:
    - reference: DOI:10.1097/cji.0000000000000316
      reference_title: 'Positive Status of Epstein-Barr Virus as a Biomarker for Gastric Cancer Immunotherapy: A Prospective Observational Study'
      supports: SUPPORT
      evidence_source: HUMAN_CLINICAL
      snippet: Immunotherapy has exhibited promising but controversial results in gastric cancer; determining criteria for choosing the appropriate target population is still problematic.
      explanation: Deep research cited this publication as relevant literature for EBV Associated Gastric Cancer.
- reference: DOI:10.1136/jitc-2021-004080
  title: Efficacy and predictive biomarkers of immunotherapy in Epstein-Barr virus-associated gastric cancer
  found_in:
  - EBV_Associated_Gastric_Cancer-deep-research-falcon.md
  findings:
  - statement: Epstein-Barr virus (EBV)-associated gastric cancer (GC) (EBVaGC) is a distinct molecular subtype of GC with a favorable prognosis.
    supporting_text: Epstein-Barr virus (EBV)-associated gastric cancer (GC) (EBVaGC) is a distinct molecular subtype of GC with a favorable prognosis.
    evidence:
    - reference: DOI:10.1136/jitc-2021-004080
      reference_title: Efficacy and predictive biomarkers of immunotherapy in Epstein-Barr virus-associated gastric cancer
      supports: SUPPORT
      evidence_source: OTHER
      snippet: Epstein-Barr virus (EBV)-associated gastric cancer (GC) (EBVaGC) is a distinct molecular subtype of GC with a favorable prognosis.
      explanation: Deep research cited this publication as relevant literature for EBV Associated Gastric Cancer.
- reference: DOI:10.1136/jitc-2024-010201
  title: 'Immune microenvironment of Epstein-Barr virus (EBV)-negative compared to EBV-associated gastric cancers: implications for immunotherapy'
  found_in:
  - EBV_Associated_Gastric_Cancer-deep-research-falcon.md
  findings:
  - statement: Gastric carcinomas (GC) are aggressive malignancies, and only ~15% of patients respond to anti-programmed cell death (ligand) 1 (PD-(L)1) monotherapy.
    supporting_text: Gastric carcinomas (GC) are aggressive malignancies, and only ~15% of patients respond to anti-programmed cell death (ligand) 1 (PD-(L)1) monotherapy.
    evidence:
    - reference: DOI:10.1136/jitc-2024-010201
      reference_title: 'Immune microenvironment of Epstein-Barr virus (EBV)-negative compared to EBV-associated gastric cancers: implications for immunotherapy'
      supports: SUPPORT
      evidence_source: HUMAN_CLINICAL
      snippet: Gastric carcinomas (GC) are aggressive malignancies, and only ~15% of patients respond to anti-programmed cell death (ligand) 1 (PD-(L)1) monotherapy.
      explanation: Deep research cited this publication as relevant literature for EBV Associated Gastric Cancer.
- reference: DOI:10.1186/s13027-023-00489-9
  title: 'Assessing Epstein–Barr virus in gastric cancer: clinicopathological features and prognostic implications'
  found_in:
  - EBV_Associated_Gastric_Cancer-deep-research-falcon.md
  findings:
  - statement: Epstein–Barr virus (EBV)-associated gastric cancer (EBVaGC) was a unique molecular subtype of gastric cancer (GC).
    supporting_text: Epstein–Barr virus (EBV)-associated gastric cancer (EBVaGC) was a unique molecular subtype of gastric cancer (GC).
    evidence:
    - reference: DOI:10.1186/s13027-023-00489-9
      reference_title: 'Assessing Epstein–Barr virus in gastric cancer: clinicopathological features and prognostic implications'
      supports: SUPPORT
      evidence_source: HUMAN_CLINICAL
      snippet: Epstein–Barr virus (EBV)-associated gastric cancer (EBVaGC) was a unique molecular subtype of gastric cancer (GC).
      explanation: Deep research cited this publication as relevant literature for EBV Associated Gastric Cancer.
- reference: DOI:10.21037/jgo-24-345
  title: Development of a streamlined NGS-based TCGA classification scheme for gastric cancer and its implications for personalized therapy
  found_in:
  - EBV_Associated_Gastric_Cancer-deep-research-falcon.md
  findings:
  - statement: Development of a streamlined NGS-based TCGA classification scheme for gastric cancer and its implications for personalized therapy
    supporting_text: Development of a streamlined NGS-based TCGA classification scheme for gastric cancer and its implications for personalized therapy
- reference: DOI:10.3389/fimmu.2024.1358511
  title: The viral etiology of EBV-associated gastric cancers contributes to their unique pathology, clinical outcomes, treatment responses and immune landscape
  found_in:
  - EBV_Associated_Gastric_Cancer-deep-research-falcon.md
  findings:
  - statement: Epstein-Barr virus (EBV) is a pathogen known to cause a number of malignancies, often taking years for them to develop after primary infection.
    supporting_text: Epstein-Barr virus (EBV) is a pathogen known to cause a number of malignancies, often taking years for them to develop after primary infection.
    evidence:
    - reference: DOI:10.3389/fimmu.2024.1358511
      reference_title: The viral etiology of EBV-associated gastric cancers contributes to their unique pathology, clinical outcomes, treatment responses and immune landscape
      supports: SUPPORT
      evidence_source: OTHER
      snippet: Epstein-Barr virus (EBV) is a pathogen known to cause a number of malignancies, often taking years for them to develop after primary infection.
      explanation: Deep research cited this publication as relevant literature for EBV Associated Gastric Cancer.
- reference: DOI:10.3390/cancers16112000
  title: 'Epstein–Barr Virus and Clinico-Endoscopic Characteristics of Gastric Remnant Cancers Compared to Proximal Non-Remnant Cancers: A Population-Based Study'
  found_in:
  - EBV_Associated_Gastric_Cancer-deep-research-falcon.md
  findings:
  - statement: Epstein–Barr virus (EBV) is associated with 5–10% of gastric cancers and is recognized as a distinct molecular subtype.
    supporting_text: Epstein–Barr virus (EBV) is associated with 5–10% of gastric cancers and is recognized as a distinct molecular subtype.
    evidence:
    - reference: DOI:10.3390/cancers16112000
      reference_title: 'Epstein–Barr Virus and Clinico-Endoscopic Characteristics of Gastric Remnant Cancers Compared to Proximal Non-Remnant Cancers: A Population-Based Study'
      supports: SUPPORT
      evidence_source: HUMAN_CLINICAL
      snippet: Epstein–Barr virus (EBV) is associated with 5–10% of gastric cancers and is recognized as a distinct molecular subtype.
      explanation: Deep research cited this publication as relevant literature for EBV Associated Gastric Cancer.
- reference: DOI:10.3390/medicina59050834
  title: 'Prognostic Implication of EBV Infection in Gastric Carcinomas: A Systematic Review and Meta-Analysis'
  found_in:
  - EBV_Associated_Gastric_Cancer-deep-research-falcon.md
  findings:
  - statement: and This study aims to elucidate the prognostic implications of Epstein–Barr virus (EBV) infection in gastric carcinomas (GCs) through a systematic review and meta-analysis.
    supporting_text: and This study aims to elucidate the prognostic implications of Epstein–Barr virus (EBV) infection in gastric carcinomas (GCs) through a systematic review and meta-analysis.
    evidence:
    - reference: DOI:10.3390/medicina59050834
      reference_title: 'Prognostic Implication of EBV Infection in Gastric Carcinomas: A Systematic Review and Meta-Analysis'
      supports: SUPPORT
      evidence_source: OTHER
      snippet: and This study aims to elucidate the prognostic implications of Epstein–Barr virus (EBV) infection in gastric carcinomas (GCs) through a systematic review and meta-analysis.
      explanation: Deep research cited this publication as relevant literature for EBV Associated Gastric Cancer.
- reference: DOI:10.3390/pathogens13090728
  title: 'Unlocking the Potential: Epstein-Barr Virus (EBV) in Gastric Cancer and Future Treatment Prospects, a Literature Review'
  found_in:
  - EBV_Associated_Gastric_Cancer-deep-research-falcon.md
  findings:
  - statement: Gastric cancer (GC) is a complex disease with various etiologies.
    supporting_text: Gastric cancer (GC) is a complex disease with various etiologies.
    evidence:
    - reference: DOI:10.3390/pathogens13090728
      reference_title: 'Unlocking the Potential: Epstein-Barr Virus (EBV) in Gastric Cancer and Future Treatment Prospects, a Literature Review'
      supports: SUPPORT
      evidence_source: HUMAN_CLINICAL
      snippet: Gastric cancer (GC) is a complex disease with various etiologies.
      explanation: Deep research cited this publication as relevant literature for EBV Associated Gastric Cancer.

📚

References & Deep Research

References

DOI:10.1007/s10120-021-01215-3

Landscape of EBV-positive gastric cancer

1 finding

Landscape of EBV-positive gastric cancer

"Landscape of EBV-positive gastric cancer"

DOI:10.1038/s41598-023-45930-6

Genetic landscape and PD-L1 expression in Epstein–Barr virus-associated gastric cancer according to the histological pattern

1 finding

Epstein–Barr virus (EBV)-associated gastric cancer (EBVaGC) is a distinct molecular subtype of gastric cancer.

"Epstein–Barr virus (EBV)-associated gastric cancer (EBVaGC) is a distinct molecular subtype of gastric cancer."

Show evidence (1 reference)

DOI:10.1038/s41598-023-45930-6 SUPPORT Human Clinical

"Epstein–Barr virus (EBV)-associated gastric cancer (EBVaGC) is a distinct molecular subtype of gastric cancer."

Deep research cited this publication as relevant literature for EBV Associated Gastric Cancer.

DOI:10.1038/s41598-024-81764-6

Association of PD-L1 positivity with Epstein Barr virus infection and microsatellite instability in gastric carcinomas with lymphoid stroma

1 finding

Association of PD-L1 positivity with Epstein Barr virus infection and microsatellite instability in gastric carcinomas with lymphoid stroma

"Association of PD-L1 positivity with Epstein Barr virus infection and microsatellite instability in gastric carcinomas with lymphoid stroma"

DOI:10.1097/cji.0000000000000316

Positive Status of Epstein-Barr Virus as a Biomarker for Gastric Cancer Immunotherapy: A Prospective Observational Study

1 finding

Immunotherapy has exhibited promising but controversial results in gastric cancer; determining criteria for choosing the appropriate target population is still problematic.

"Immunotherapy has exhibited promising but controversial results in gastric cancer; determining criteria for choosing the appropriate target population is still problematic."

Show evidence (1 reference)

DOI:10.1097/cji.0000000000000316 SUPPORT Human Clinical

"Immunotherapy has exhibited promising but controversial results in gastric cancer; determining criteria for choosing the appropriate target population is still problematic."

Deep research cited this publication as relevant literature for EBV Associated Gastric Cancer.

DOI:10.1136/jitc-2021-004080

Efficacy and predictive biomarkers of immunotherapy in Epstein-Barr virus-associated gastric cancer

1 finding

Epstein-Barr virus (EBV)-associated gastric cancer (GC) (EBVaGC) is a distinct molecular subtype of GC with a favorable prognosis.

"Epstein-Barr virus (EBV)-associated gastric cancer (GC) (EBVaGC) is a distinct molecular subtype of GC with a favorable prognosis."

Show evidence (1 reference)

DOI:10.1136/jitc-2021-004080 SUPPORT Other

"Epstein-Barr virus (EBV)-associated gastric cancer (GC) (EBVaGC) is a distinct molecular subtype of GC with a favorable prognosis."

Deep research cited this publication as relevant literature for EBV Associated Gastric Cancer.

DOI:10.1136/jitc-2024-010201

Immune microenvironment of Epstein-Barr virus (EBV)-negative compared to EBV-associated gastric cancers: implications for immunotherapy

1 finding

Gastric carcinomas (GC) are aggressive malignancies, and only ~15% of patients respond to anti-programmed cell death (ligand) 1 (PD-(L)1) monotherapy.

"Gastric carcinomas (GC) are aggressive malignancies, and only ~15% of patients respond to anti-programmed cell death (ligand) 1 (PD-(L)1) monotherapy."

Show evidence (1 reference)

DOI:10.1136/jitc-2024-010201 SUPPORT Human Clinical

"Gastric carcinomas (GC) are aggressive malignancies, and only ~15% of patients respond to anti-programmed cell death (ligand) 1 (PD-(L)1) monotherapy."

Deep research cited this publication as relevant literature for EBV Associated Gastric Cancer.

DOI:10.1186/s13027-023-00489-9

Assessing Epstein–Barr virus in gastric cancer: clinicopathological features and prognostic implications

1 finding

Epstein–Barr virus (EBV)-associated gastric cancer (EBVaGC) was a unique molecular subtype of gastric cancer (GC).

"Epstein–Barr virus (EBV)-associated gastric cancer (EBVaGC) was a unique molecular subtype of gastric cancer (GC)."

Show evidence (1 reference)

DOI:10.1186/s13027-023-00489-9 SUPPORT Human Clinical

"Epstein–Barr virus (EBV)-associated gastric cancer (EBVaGC) was a unique molecular subtype of gastric cancer (GC)."

Deep research cited this publication as relevant literature for EBV Associated Gastric Cancer.

DOI:10.21037/jgo-24-345

Development of a streamlined NGS-based TCGA classification scheme for gastric cancer and its implications for personalized therapy

1 finding

Development of a streamlined NGS-based TCGA classification scheme for gastric cancer and its implications for personalized therapy

"Development of a streamlined NGS-based TCGA classification scheme for gastric cancer and its implications for personalized therapy"

DOI:10.3389/fimmu.2024.1358511

The viral etiology of EBV-associated gastric cancers contributes to their unique pathology, clinical outcomes, treatment responses and immune landscape

1 finding

Epstein-Barr virus (EBV) is a pathogen known to cause a number of malignancies, often taking years for them to develop after primary infection.

"Epstein-Barr virus (EBV) is a pathogen known to cause a number of malignancies, often taking years for them to develop after primary infection."

Show evidence (1 reference)

DOI:10.3389/fimmu.2024.1358511 SUPPORT Other

"Epstein-Barr virus (EBV) is a pathogen known to cause a number of malignancies, often taking years for them to develop after primary infection."

Deep research cited this publication as relevant literature for EBV Associated Gastric Cancer.

DOI:10.3390/cancers16112000

Epstein–Barr Virus and Clinico-Endoscopic Characteristics of Gastric Remnant Cancers Compared to Proximal Non-Remnant Cancers: A Population-Based Study

1 finding

Epstein–Barr virus (EBV) is associated with 5–10% of gastric cancers and is recognized as a distinct molecular subtype.

"Epstein–Barr virus (EBV) is associated with 5–10% of gastric cancers and is recognized as a distinct molecular subtype."

Show evidence (1 reference)

DOI:10.3390/cancers16112000 SUPPORT Human Clinical

"Epstein–Barr virus (EBV) is associated with 5–10% of gastric cancers and is recognized as a distinct molecular subtype."

Deep research cited this publication as relevant literature for EBV Associated Gastric Cancer.

DOI:10.3390/medicina59050834

Prognostic Implication of EBV Infection in Gastric Carcinomas: A Systematic Review and Meta-Analysis

1 finding

and This study aims to elucidate the prognostic implications of Epstein–Barr virus (EBV) infection in gastric carcinomas (GCs) through a systematic review and meta-analysis.

"and This study aims to elucidate the prognostic implications of Epstein–Barr virus (EBV) infection in gastric carcinomas (GCs) through a systematic review and meta-analysis."

Show evidence (1 reference)

DOI:10.3390/medicina59050834 SUPPORT Other

"and This study aims to elucidate the prognostic implications of Epstein–Barr virus (EBV) infection in gastric carcinomas (GCs) through a systematic review and meta-analysis."

Deep research cited this publication as relevant literature for EBV Associated Gastric Cancer.

DOI:10.3390/pathogens13090728

Unlocking the Potential: Epstein-Barr Virus (EBV) in Gastric Cancer and Future Treatment Prospects, a Literature Review

1 finding

Gastric cancer (GC) is a complex disease with various etiologies.

"Gastric cancer (GC) is a complex disease with various etiologies."

Show evidence (1 reference)

DOI:10.3390/pathogens13090728 SUPPORT Human Clinical

"Gastric cancer (GC) is a complex disease with various etiologies."

Deep research cited this publication as relevant literature for EBV Associated Gastric Cancer.

Deep Research

Falcon ▸

Disease Characteristics Research Template

Edison Scientific Literature 31 citations 2026-04-05T14:38:50.590465

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: EBV-Associated Gastric Cancer
MONDO ID: (if available)
Category:

Research Objectives

Please provide a comprehensive research report on EBV-Associated Gastric Cancer 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

EBV-Associated Gastric Cancer (EBVaGC) — Disease Characteristics Research Report (2023–2024 prioritized)

Target Disease

Disease name: Epstein–Barr virus (EBV)-associated gastric cancer (EBVaGC) / EBV-positive gastric carcinoma
Category: Infection-associated epithelial malignancy; molecular subtype of gastric adenocarcinoma
MONDO ID: Not identified from the retrieved evidence in this run (additional ontology lookup required).

1. Disease information

Overview (what is the disease?)

EBV-associated gastric cancer (EBVaGC) is a molecularly and clinicopathologically distinct subset of gastric cancer defined by the presence of EBV infection within the malignant epithelial (tumor) cells, typically demonstrated by in situ hybridization for EBV-encoded small RNAs (EBER) (saito2021landscapeofebvpositive pages 1-2, li2023assessingepstein–barrvirus pages 1-2). It is recognized as one of the major molecular subtypes in The Cancer Genome Atlas (TCGA) gastric cancer classification (saito2021landscapeofebvpositive pages 1-2, lee2024associationofpdl1 pages 1-2).

Synonyms / alternative names

EBV-positive gastric cancer (EBV(+) GC) (saito2021landscapeofebvpositive pages 1-2)
EBV-associated gastric carcinoma (EBVaGC) (bai2022efficacyandpredictive pages 1-2)
Gastric carcinoma with lymphoid stroma (GCLS) / carcinoma with lymphoid stroma (CLS) when presenting with prominent lymphoid infiltration (park2023geneticlandscapeand pages 1-2, lee2024associationofpdl1 pages 1-2)
Lymphoepithelioma-like carcinoma (LELC) pattern in stomach (often overlaps with GCLS conceptually) (corallo2024unlockingthepotential pages 6-8, saito2021landscapeofebvpositive pages 1-2)

Key identifiers (status)

ICD/MeSH/OMIM/Orphanet/MONDO: Not reliably extractable from the retrieved primary/full-text evidence in this run; this report therefore focuses on primary literature definitions and diagnostic criteria.

Evidence provenance

The information in this report is derived from aggregated disease-level primary literature (cohort studies, meta-analyses, and mechanistic studies), plus a small number of prospective/observational immunotherapy cohorts and clinical trial registry entries (xie2020positivestatusof pages 1-2, bai2022efficacyandpredictive pages 1-2, pyo2023prognosticimplicationof pages 1-2).

2. Etiology

Primary causal factor

EBVaGC is causally linked to EBV infection of gastric epithelial cells with maintenance of EBV genomes/latency-associated gene expression in tumor cells; EBVaGC is considered an “infection-associated” cancer subtype with distinct molecular/immune features (salnikov2024theviraletiology pages 1-2).

Risk factors

Infectious: EBV infection in tumor cells is the defining etiologic factor; EBV positivity is observed in ~5–10% of gastric cancers in many series (mcmiller2024immunemicroenvironmentof pages 1-2).
Anatomic/clinical context: EBV positivity appears enriched in gastric remnant cancers (post-distal gastrectomy), with EBV positivity reported as 18.7% in remnant cancers vs 6.0% in proximal non-remnant controls in a Norwegian population-based study (Bringeland et al. 2024; DOI: 10.3390/cancers16112000; retrieved in this run but not yet evidence-extracted beyond summary in artifact) (artifact-00).

Protective factors

A meta-analysis suggests EBV-positive status is associated with better overall survival compared to EBV-negative gastric cancer (HR < 1), which is prognostic rather than strictly protective against disease occurrence (pyo2023prognosticimplicationof pages 1-2).

Gene–environment / microbe–environment interactions

Direct gene–environment interaction statistics were not extractable from the retrieved texts. However, EBV-associated tumors show characteristic host epigenetic reprogramming (hypermethylation) and immune pathway activation, consistent with pathogen-driven remodeling of host gene regulation (corallo2024unlockingthepotential pages 3-5, salnikov2024theviraletiology pages 1-2).

3. Phenotypes (clinical and pathological presentation)

Clinicopathologic phenotype (human)

Commonly reported features include: - Male predominance (e.g., 72.2% male in one 2023 cohort; and EBVaGC more common in males in a 420-patient cohort) (li2023assessingepstein–barrvirus pages 1-2, park2023geneticlandscapeand pages 1-2). - Tumor location: preferential involvement of upper-to-middle stomach (saito2021landscapeofebvpositive pages 1-2, park2023geneticlandscapeand pages 1-2). - Histology: frequent association with gastric carcinoma with lymphoid stroma (GCLS) characterized by dense intra/peritumoral lymphocytic infiltration (park2023geneticlandscapeand pages 1-2, lee2024associationofpdl1 pages 1-2). - Stage associations: one cohort found association with early T stage and early TNM stage (li2023assessingepstein–barrvirus pages 1-2).

Suggested HPO terms (examples; mapping-level suggestions)

Because EBVaGC is a cancer subtype, phenotypes overlap with gastric cancer generally; the literature extracted here emphasized histology and immune infiltration. - Gastric adenocarcinoma: HP:0006753 (Malignant neoplasm of stomach; verify exact HPO term naming in curation pipeline) - Gastrointestinal bleeding (particularly in remnant cancers): HP:0002239 (artifact-00; Bringeland 2024 study context) - Weight loss/anorexia (common in GC but not quantified here): HP:0001824 (Weight loss), HP:0004396 (Anorexia) - Lymphocyte-rich tumor stroma (not a standard HPO clinical term; better captured via pathology ontologies)

Frequency data

EBV positivity in GCLS: 85% (181/214) in one large 2024 cohort (lee2024associationofpdl1 pages 1-2).

4. Genetic / molecular information

“Causal genes”

EBVaGC is not a Mendelian disorder and does not have a single causal germline gene. Its defining cause is EBV infection in tumor cells, with recurrent somatic alterations.

Key recurrent somatic alterations (current understanding)

Across genomic profiling and reviews, EBVaGC is characterized by: - PIK3CA and ARID1A recurrent mutations, and relatively fewer TP53 mutations (saito2021landscapeofebvpositive pages 1-2, guo2024developmentofa pages 1-2). - 9p24.1 amplifications including JAK2, CD274 (PD-L1), and PDCD1LG2 (PD-L2), contributing to immune evasion (corallo2024unlockingthepotential pages 3-5, mcmiller2024immunemicroenvironmentof pages 1-2). - Extensive DNA hypermethylation (including CDKN2A promoter hypermethylation noted in TCGA summaries; MLH1 promoter hypermethylation is not a typical feature in EBV subtype as summarized in one review) (corallo2024unlockingthepotential pages 3-5).

One 2024 review summarized reported frequencies from prior genomic studies: PIK3CA 80%, ARID1A 55%, BCOR 23%, and JAK2/CD274/PDCD1LG2 amplifications 15% (corallo2024unlockingthepotential pages 3-5).

Epigenetic information

EBVaGC is notable for DNA hypermethylation compared to other gastric cancer subtypes (corallo2024unlockingthepotential pages 3-5).

5. Mechanism / pathophysiology

Core mechanistic themes

EBVaGC’s pathophysiology is shaped by combined viral oncogenic programs, host epigenetic remodeling, and immune microenvironment remodeling.

Causal chain (conceptual): 1) EBV infects gastric epithelial cells and establishes a latency program in tumor cells (definition-level) → 2) EBV products and host responses drive epigenetic reprogramming (hypermethylation) and select for particular somatic alterations (e.g., PIK3CA/ARID1A) → 3) Tumors develop an “immune-hot” yet immunoregulatory environment, often with strong lymphocyte infiltration and immune checkpoint activation/amplification (PD-L1/PD-L2; JAK2) → 4) This immune contexture can be associated with higher responsiveness to checkpoint blockade in some cohorts, but responses are heterogeneous (corallo2024unlockingthepotential pages 6-8, bai2022efficacyandpredictive pages 1-2, mcmiller2024immunemicroenvironmentof pages 1-2).

Immune microenvironment (2024 primary study)

A 2024 JITC study comparing EBV+ vs EBV− primary gastric cancers reported: - EBVaGC background prevalence “~5–10% of GCs,” and EBV+ tumors often harbor PD-L1/PD-L2 amplifications with robust CD8+ infiltrates (mcmiller2024immunemicroenvironmentof pages 1-2). - In a treatment-naïve set (11 EBV+, 14 EBV−), CD8+ T-cell densities were higher in EBV+ tumors (p=0.044) (mcmiller2024immunemicroenvironmentof pages 1-2). - PD-L1+ tumor cells were observed in 3/25 tumors (all EBV+) (mcmiller2024immunemicroenvironmentof pages 1-2). - EBV− tumors overexpressed inflammatory/immunosuppressive pathways including COX-2/PGE2 (PTGS2/COX-2 up 32-fold, p=0.005) (mcmiller2024immunemicroenvironmentof pages 1-2).

Recent developments (2023–2024)

Single-cell immunology in EBV(+) GC under therapy: A 2023 study used longitudinal scRNA-seq/scTCR/BCR-seq in EBV(+) GC treated with immunochemotherapy and reported a baseline intratumoral ISG-15+ CD8+ T-cell population associated with immunotherapy responsiveness, and suggested potential benefit of anti-LAG-3 in refractory EBV(+) GC (bai2022efficacyandpredictive pages 1-2).
Operationalizing TCGA subtyping in practice: A 2024 NGS-based TCGA-surrogate classification study reported EBV subtype prevalence 5.2% in a real-world cohort and found 100% disease control rate for ICI therapy in EBV and MSI subtypes in a small validation cohort (guo2024developmentofa pages 1-2).

Suggested GO terms (mechanism-level; mapping suggestions)

GO:0006955 immune response
GO:0002682 regulation of immune system process
GO:0006325 chromatin organization (epigenetic remodeling)
GO:0006306 DNA methylation
GO:0008283 cell population proliferation

Suggested CL terms (cell types)

CD8+ T cell (CL:0000625)
Macrophage (CL:0000235); M2-like macrophage signatures noted for immunosuppressive environments (mcmiller2024immunemicroenvironmentof pages 1-2)
Gastric epithelial cell (use appropriate CL term for gastric mucosal epithelial lineage in curation)

6. Epidemiology, population, and prognosis

Prevalence / proportion among gastric cancers

Estimates vary by region and detection methods. - Meta-analysis (2023): EBV infection in 10.4% of gastric carcinomas (95% CI 8.2%–13.1%) (pyo2023prognosticimplicationof pages 1-2). - TCGA-surrogate NGS cohort (2024): EBV subtype 5.2% (guo2024developmentofa pages 1-2). - Individual cohorts can range widely (e.g., 12.62% in one 420-patient cohort) (li2023assessingepstein–barrvirus pages 1-2).

Prognosis (statistics)

A 2023 systematic review/meta-analysis (57 studies; 22,943 patients) found EBV positivity associated with improved overall survival: HR 0.890 (95% CI 0.816–0.970) (pyo2023prognosticimplicationof pages 1-2). In diffuse-type Lauren classification, EBV positivity was associated with stronger favorable prognosis (HR 0.400, 95% CI 0.300–0.534) (pyo2023prognosticimplicationof pages 1-2).

7. Diagnostics

Core diagnostic definition

EBER in situ hybridization (EBER-ISH) is repeatedly described as the reference method for defining EBV-positive tumor status. - In a clinical cohort paper: “EBV-encoded RNA (EBER) in situ hybridization method was used to evaluate the EBV status in GC” (li2023assessingepstein–barrvirus pages 1-2). - A 2022 immunotherapy biomarker study states EBER-ISH is “regarded as the gold standard” but has limitations for multiplex biomarker assessment (bai2022efficacyandpredictive pages 1-2).

Biomarkers used alongside EBV status

PD-L1 IHC (CPS): EBV+ GCLS shows high PD-L1 positivity; CPS ≥1/≥5/≥10 were 81.8%, 70.2%, 55.3% in EBV+ GCLS (lee2024associationofpdl1 pages 1-2).
MSI/MMR status: EBV+ GCLS rarely MSI-high (0.6%), while EBV− GCLS often MSI-high (54.5%) (lee2024associationofpdl1 pages 1-2).

Omics-based diagnostics / recent development

An NGS-based EBV detection algorithm (validated against EBER-ISH) achieved sensitivity 95.7% and specificity 100%, and enabled simultaneous evaluation of clinically relevant biomarkers (TMB, MSI, HER2, fusions) (bai2022efficacyandpredictive pages 1-2).

Differential diagnosis

Differential considerations include MSI-high gastric cancers (which can also have prominent immune infiltration and PD-L1 positivity) and other histologic subtypes; in lymphoid-stroma–rich tumors, MSI-H is a key alternate subtype (lee2024associationofpdl1 pages 1-2).

8. Treatment and real-world implementation

Standard-of-care context

EBVaGC is treated within standard gastric cancer algorithms (surgery/endoscopic resection for early disease; chemotherapy ± targeted therapy; immunotherapy in selected advanced settings). EBV positivity is increasingly used as a biomarker relevant to immunotherapy selection/stratification (bai2022efficacyandpredictive pages 1-2, mcmiller2024immunemicroenvironmentof pages 1-2).

Immunotherapy (checkpoint blockade) — response statistics

Evidence suggests EBVaGC can show high response rates to ICI in some cohorts, but responses vary. - In an EBV+/pMMR cohort receiving immunotherapy, ORR 54.5% (12/22) was reported (bai2022efficacyandpredictive pages 1-2). - A prospective observational cohort of 9 stage-IV EBVaGC treated with ICIs reported: “Three patients … showed partial response, 5 stable disease” and the “longest duration of response was 18 months” (xie2020positivestatusof pages 1-2). - A 2024 review summarized heterogeneous reports with ORRs “from 0 to 100%,” including a small pembrolizumab series reported as ORR 100% (n=6; PFS 8.5 months) and a small camrelizumab series with ORR 0% (n=6; DCR 67%; PFS 2.2 months; OS 6.8 months) (corallo2024unlockingthepotential pages 6-8).

Translational/precision treatment implications

EBV subtype tumors frequently have PD-L1/PD-L2 amplification and inflamed immune phenotype, which supports immunotherapy candidacy (mcmiller2024immunemicroenvironmentof pages 1-2).
Practical molecular subtyping by NGS may support immunotherapy selection: in one validation cohort, ICI disease control rate was 100% in MSI and EBV subtypes (guo2024developmentofa pages 1-2).

Clinical trials (real-world implementations; ClinicalTrials.gov)

Trials explicitly incorporating EBV status in gastric cancer include: - NCT05970627 (Phase 2): perioperative chemotherapy + toripalimab for EBV-associated locally advanced gastric/EGJ adenocarcinoma (NOT_YET_RECRUITING) (trial retrieved in this run). - NCT03257163 (Phase 2): pembrolizumab + capecitabine + radiation in mismatch-repair deficient and EBV-positive gastric cancer (ACTIVE_NOT_RECRUITING) (trial retrieved in this run). - NCT05535569 (Phase Ib/II): nivolumab + paclitaxel in EBV-related/MSI-H/PD-L1+ advanced gastric cancer (COMPLETED) (trial retrieved in this run).

Suggested MAXO terms (treatment action ontology; mapping suggestions)

Immune checkpoint inhibitor therapy (e.g., anti-PD-1): MAXO term for immune checkpoint inhibitor therapy (exact ID to be selected during ontology curation)
Gastric cancer surgical resection / gastrectomy
Endoscopic submucosal dissection (for select early lesions)
Radiotherapy / chemoradiation

9. Model organisms and experimental models

Mechanistic and translational models

Direct model-system inventories (specific EBV+ gastric cancer organoids, cell lines, or mouse models) were not comprehensively extractable from the retrieved evidence set. However, EBV-associated gastric cancer is frequently studied using EBV-positive gastric cancer cell lines and xenografts in mechanistic viral-miRNA studies; for example, EBV-encoded miR-BART11-3p was shown to modulate the DUSP6–MAPK axis and promote proliferation/metastasis-related phenotypes in vitro and in vivo (xenograft context) (paper retrieved but not evidence-extracted in this run).

10. Summary table artifact

Key quantitative facts from recent literature are consolidated below.

Feature	Quantitative value(s)	Study/Population	PMID (if available; otherwise DOI)	Publication date	URL
EBVaGC prevalence, global estimate	2%–20%; average 8.9%	Review summarizing global prevalence; EBVaGC across gastric cancers (park2023geneticlandscapeand pages 1-2)	DOI: 10.1038/s41598-023-45930-6	2023-11	https://doi.org/10.1038/s41598-023-45930-6
EBVaGC prevalence, single-center cohort	53/420 = 12.62%	Li et al.; gastric cancer cohort evaluated by EBER ISH (li2023assessingepstein–barrvirus pages 1-2)	DOI: 10.1186/s13027-023-00489-9	2023-02	https://doi.org/10.1186/s13027-023-00489-9
EBV prevalence in gastric carcinomas, meta-analysis	10.4% (95% CI 8.2%–13.1%)	57 studies; 22,943 patients (pyo2023prognosticimplicationof pages 1-2)	DOI: 10.3390/medicina59050834	2023-04	https://doi.org/10.3390/medicina59050834
EBV subtype prevalence by NGS-TCGA surrogate	5.2%	3DMed cohort, n=765 gastric cancers (guo2024developmentofa pages 1-2)	DOI: 10.21037/jgo-24-345	2024-10	https://doi.org/10.21037/jgo-24-345
EBV prevalence in gastric remnant vs proximal non-remnant controls	18.7% vs 6.0%	Population-based Central Norway study; gastric remnant cancer vs controls	DOI: 10.3390/cancers16112000	2024-05	https://doi.org/10.3390/cancers16112000
EBVaGC prevalence, broad current estimate	~5%–10% of gastric cancers	McMiller et al.; background statement for immune microenvironment study (mcmiller2024immunemicroenvironmentof pages 1-2)	DOI: 10.1136/jitc-2024-010201	2024-11	https://doi.org/10.1136/jitc-2024-010201
NGS-based EBV detection performance vs EBER-ISH	Sensitivity 95.7% (22/23); specificity 100% (53/53)	Bai et al.; training/validation cohorts for NGS EBV detection (bai2022efficacyandpredictive pages 1-2)	DOI: 10.1136/jitc-2021-004080	2022-03	https://doi.org/10.1136/jitc-2021-004080
Immunotherapy response in EBV+/pMMR advanced GC	ORR 54.5% (12/22)	Bai et al.; EBV+/pMMR patients receiving immunotherapy (bai2022efficacyandpredictive pages 1-2)	DOI: 10.1136/jitc-2021-004080	2022-03	https://doi.org/10.1136/jitc-2021-004080
Prospective ICI outcomes in stage IV EBVaGC	3 PR; 5 SD; 1 non-measurable lesion with decreased ascites/tumor markers; longest response 18 months	Xie et al.; 9 stage-IV EBVaGC patients treated with ICIs (xie2020positivestatusof pages 1-2)	DOI: 10.1097/CJI.0000000000000316	2020-03	https://doi.org/10.1097/CJI.0000000000000316
Pembrolizumab in small EBVaGC cohort (reported in review)	ORR 100% (n=6); PFS 8.5 months	Kim et al. 2018, as summarized in Corallo 2024 review (corallo2024unlockingthepotential pages 6-8)	DOI: 10.3390/pathogens13090728	2024-08	https://doi.org/10.3390/pathogens13090728
Camrelizumab in small EBVaGC cohort (reported in review)	ORR 0% (n=6); DCR 67%; PFS 2.2 months; OS 6.8 months	Phase 2 result summarized in Corallo 2024 review (corallo2024unlockingthepotential pages 6-8)	DOI: 10.3390/pathogens13090728	2024-08	https://doi.org/10.3390/pathogens13090728
ICI disease control by molecular subtype	DCR 100% in MSI and EBV cases; 62.9% in GS; 12.5% in CIN	Korean validation cohort, n=55 (guo2024developmentofa pages 1-2)	DOI: 10.21037/jgo-24-345	2024-10	https://doi.org/10.21037/jgo-24-345
PD-L1 in EBV+ GCLS	CPS ≥1: 81.8%; CPS ≥5: 70.2%; CPS ≥10: 55.3%	Lee & Oh; 181 EBV+ GCLS among 214 GCLS cases (lee2024associationofpdl1 pages 1-2)	DOI: 10.1038/s41598-024-81764-6	2024-12	https://doi.org/10.1038/s41598-024-81764-6
MSI-H in GCLS by EBV status	0.6% in EBV+ GCLS vs 54.5% in EBV− GCLS	Lee & Oh; GCLS cohort (lee2024associationofpdl1 pages 1-2)	DOI: 10.1038/s41598-024-81764-6	2024-12	https://doi.org/10.1038/s41598-024-81764-6
HER2 amplification in GCLS by EBV status	~3.9% in EBV+ GCLS vs ~3.0% in EBV− GCLS; 13% in EBV− GAC controls	Lee & Oh; GCLS vs GAC (lee2024associationofpdl1 pages 1-2)	DOI: 10.1038/s41598-024-81764-6	2024-12	https://doi.org/10.1038/s41598-024-81764-6
CD8+ T-cell infiltration in EBV+ vs EBV− GC	Higher CD8+ density in EBV+ tumors; p=0.044	McMiller et al.; 25 treatment-naïve specimens (11 EBV+, 14 EBV−) (mcmiller2024immunemicroenvironmentof pages 1-2)	DOI: 10.1136/jitc-2024-010201	2024-11	https://doi.org/10.1136/jitc-2024-010201
PD-L1+ tumor cells in immune microenvironment study	3/25 tumors; all 3 were EBV+	McMiller et al.; 25 treatment-naïve gastric cancers (mcmiller2024immunemicroenvironmentof pages 1-2)	DOI: 10.1136/jitc-2024-010201	2024-11	https://doi.org/10.1136/jitc-2024-010201
COX-2/PGE2 pathway enrichment in EBV− tumors	PTGS2/COX-2 up 32-fold (p=0.005); PTGER1 up 21-fold (p=0.015)	McMiller et al.; EBV− vs EBV+ immune microenvironment comparison (mcmiller2024immunemicroenvironmentof pages 1-2)	DOI: 10.1136/jitc-2024-010201	2024-11	https://doi.org/10.1136/jitc-2024-010201
Prognostic effect of EBV positivity	OS HR 0.890 (95% CI 0.816–0.970)	Pyo et al. meta-analysis; 57 studies, 22,943 patients (pyo2023prognosticimplicationof pages 1-2)	DOI: 10.3390/medicina59050834	2023-04	https://doi.org/10.3390/medicina59050834
Prognostic effect in diffuse-type Lauren classification	HR 0.400 (95% CI 0.300–0.534)	Pyo et al. subgroup analysis (pyo2023prognosticimplicationof pages 1-2)	DOI: 10.3390/medicina59050834	2023-04	https://doi.org/10.3390/medicina59050834
Recurrent molecular features of EBV subtype	Recurrent ARID1A and PIK3CA mutations; fewer TP53 mutations	Guo et al. NGS-based subtype classification (guo2024developmentofa pages 1-2)	DOI: 10.21037/jgo-24-345	2024-10	https://doi.org/10.21037/jgo-24-345
Frequent EBVaGC molecular alterations summarized in review	PIK3CA 80%; ARID1A 55%; BCOR 23%; JAK2/CD274/PDCD1LG2 amplifications 15%	Corallo 2024 review summarizing prior genomic studies (corallo2024unlockingthepotential pages 3-5)	DOI: 10.3390/pathogens13090728	2024-08	https://doi.org/10.3390/pathogens13090728

Table: This table consolidates key quantitative findings for EBV-associated gastric cancer across prevalence, molecular features, biomarkers, immune microenvironment, prognosis, and immunotherapy response. It is useful as a quick-reference evidence summary for knowledge base curation and clinical/research interpretation.

11. Expert opinion / authoritative synthesis (2024 reviews)

A 2024 Frontiers in Immunology review emphasizes that EBVaGC is “immunologically, molecularly and pathologically distinct” and describes an overall “immune-hot” phenotype with improved prognosis relative to EBV-negative gastric cancers (salnikov2024theviraletiology pages 1-2). A 2024 Pathogens review highlights EBV status as a potential predictive biomarker for response to chemotherapy and immune checkpoint inhibitors, while emphasizing heterogeneity and the need for prospective validation (corallo2024unlockingthepotential pages 6-8).

Data gaps and limitations (important for knowledge base curation)

Ontology identifiers (MONDO/MeSH/ICD) were not obtainable from the retrieved full-text evidence in this run; dedicated ontology/database queries are needed.
Several key statements in recent reviews summarize TCGA-era findings; where possible, this report relied on cohort studies/meta-analyses for quantitative estimates (pyo2023prognosticimplicationof pages 1-2, guo2024developmentofa pages 1-2, mcmiller2024immunemicroenvironmentof pages 1-2).
Immunotherapy response estimates remain largely based on small cohorts and heterogeneous designs; even recent syntheses report ORRs ranging from 0–100% across small series (corallo2024unlockingthepotential pages 6-8, bai2022efficacyandpredictive pages 1-2).

References

(saito2021landscapeofebvpositive pages 1-2): Motonobu Saito and Koji Kono. Landscape of ebv-positive gastric cancer. Gastric Cancer, 24:983-989, Jul 2021. URL: https://doi.org/10.1007/s10120-021-01215-3, doi:10.1007/s10120-021-01215-3. This article has 92 citations and is from a domain leading peer-reviewed journal.
(li2023assessingepstein–barrvirus pages 1-2): Guanghua Li, Zhihao Zhou, Zhixiong Wang, and Zhao Wang. Assessing epstein–barr virus in gastric cancer: clinicopathological features and prognostic implications. Infectious Agents and Cancer, Feb 2023. URL: https://doi.org/10.1186/s13027-023-00489-9, doi:10.1186/s13027-023-00489-9. This article has 12 citations and is from a peer-reviewed journal.
(lee2024associationofpdl1 pages 1-2): Sun Mi Lee and Hyunjoo Oh. Association of pd-l1 positivity with epstein barr virus infection and microsatellite instability in gastric carcinomas with lymphoid stroma. Scientific Reports, Dec 2024. URL: https://doi.org/10.1038/s41598-024-81764-6, doi:10.1038/s41598-024-81764-6. This article has 5 citations and is from a peer-reviewed journal.
(bai2022efficacyandpredictive pages 1-2): Yuezong Bai, Tong Xie, Zhenghang Wang, Shuang Tong, Xiaochen Zhao, Feilong Zhao, Jinping Cai, Xiaofan Wei, Zhi Peng, and Lin Shen. Efficacy and predictive biomarkers of immunotherapy in epstein-barr virus-associated gastric cancer. Journal for Immunotherapy of Cancer, 10:e004080, Mar 2022. URL: https://doi.org/10.1136/jitc-2021-004080, doi:10.1136/jitc-2021-004080. This article has 114 citations and is from a domain leading peer-reviewed journal.
(park2023geneticlandscapeand pages 1-2): Ji Hyun Park, Hee Jin Cho, Jeonghwa Seo, Ki Bum Park, Yong Hwan Kwon, Han Ik Bae, An Na Seo, and Moonsik Kim. Genetic landscape and pd-l1 expression in epstein–barr virus-associated gastric cancer according to the histological pattern. Scientific Reports, Nov 2023. URL: https://doi.org/10.1038/s41598-023-45930-6, doi:10.1038/s41598-023-45930-6. This article has 6 citations and is from a peer-reviewed journal.
(corallo2024unlockingthepotential pages 6-8): Salvatore Corallo, Angioletta Lasagna, Beatrice Filippi, Domiziana Alaimo, Anna Tortorella, Francesco Serra, Alessandro Vanoli, and Paolo Pedrazzoli. Unlocking the potential: epstein-barr virus (ebv) in gastric cancer and future treatment prospects, a literature review. Pathogens, 13:728, Aug 2024. URL: https://doi.org/10.3390/pathogens13090728, doi:10.3390/pathogens13090728. This article has 18 citations.
(xie2020positivestatusof pages 1-2): Tong Xie, Yiqiang Liu, Zhening Zhang, Xiaotian Zhang, Jifang Gong, Changsong Qi, Jian Li, Lin Shen, and Zhi Peng. Positive status of epstein-barr virus as a biomarker for gastric cancer immunotherapy: a prospective observational study. Journal of Immunotherapy (Hagerstown, Md. : 1997), 43:139-144, Mar 2020. URL: https://doi.org/10.1097/cji.0000000000000316, doi:10.1097/cji.0000000000000316. This article has 107 citations.
(pyo2023prognosticimplicationof pages 1-2): Jung-Soo Pyo, Nae-Yu Kim, and Dong-Wook Kang. Prognostic implication of ebv infection in gastric carcinomas: a systematic review and meta-analysis. Medicina, 59:834, Apr 2023. URL: https://doi.org/10.3390/medicina59050834, doi:10.3390/medicina59050834. This article has 4 citations.
(salnikov2024theviraletiology pages 1-2): Mikhail Yuryevich Salnikov, Katelyn M. MacNeil, and J. Mymryk. The viral etiology of ebv-associated gastric cancers contributes to their unique pathology, clinical outcomes, treatment responses and immune landscape. Frontiers in Immunology, Mar 2024. URL: https://doi.org/10.3389/fimmu.2024.1358511, doi:10.3389/fimmu.2024.1358511. This article has 31 citations and is from a peer-reviewed journal.
(mcmiller2024immunemicroenvironmentof pages 1-2): Tracee L McMiller, Sepideh Besharati, Mark Yarchoan, Qingfeng Zhu, Keziban Ünsal-Kaçmaz, Ke Xu, Junghwa Lee, Feriyl Bhaijee, Logan L Engle, Janis M Taube, Alan E Berger, Robert A Anders, and Suzanne L Topalian. Immune microenvironment of epstein-barr virus (ebv)-negative compared to ebv-associated gastric cancers: implications for immunotherapy. Journal for Immunotherapy of Cancer, 12:e010201, Nov 2024. URL: https://doi.org/10.1136/jitc-2024-010201, doi:10.1136/jitc-2024-010201. This article has 7 citations and is from a domain leading peer-reviewed journal.
(corallo2024unlockingthepotential pages 3-5): Salvatore Corallo, Angioletta Lasagna, Beatrice Filippi, Domiziana Alaimo, Anna Tortorella, Francesco Serra, Alessandro Vanoli, and Paolo Pedrazzoli. Unlocking the potential: epstein-barr virus (ebv) in gastric cancer and future treatment prospects, a literature review. Pathogens, 13:728, Aug 2024. URL: https://doi.org/10.3390/pathogens13090728, doi:10.3390/pathogens13090728. This article has 18 citations.
(guo2024developmentofa pages 1-2): Pengda Guo, Yang Yang, Lu Wang, Yu Zhang, Bei Zhang, Jinping Cai, Fabrício Freire de Melo, Matthew R. Strickland, Min Huang, and Biao Liu. Development of a streamlined ngs-based tcga classification scheme for gastric cancer and its implications for personalized therapy. Journal of Gastrointestinal Oncology, 15:2053-2066, Oct 2024. URL: https://doi.org/10.21037/jgo-24-345, doi:10.21037/jgo-24-345. This article has 4 citations and is from a peer-reviewed journal.

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OpenScientist Report

Classifications

Pathophysiology

Histopathology

Pathograph

Phenotypes

Genetic Associations

Treatments

Biochemical Markers

Source YAML

References & Deep Research

References

Deep Research

Disease Characteristics Research Template

Target Disease

Research Objectives

1. Disease Information

2. Etiology

3. Phenotypes

4. Genetic/Molecular Information

5. Environmental Information

6. Mechanism / Pathophysiology

7. Anatomical Structures Affected

8. Temporal Development

9. Inheritance and Population

10. Diagnostics

11. Outcome/Prognosis

12. Treatment

13. Prevention

14. Other Species / Natural Disease

15. Model Organisms

Citation Requirements

Output Format

EBV-Associated Gastric Cancer (EBVaGC) — Disease Characteristics Research Report (2023–2024 prioritized)

Target Disease

1. Disease information

Overview (what is the disease?)

Synonyms / alternative names

Key identifiers (status)

Evidence provenance

2. Etiology

Primary causal factor

Risk factors

Protective factors

Gene–environment / microbe–environment interactions

3. Phenotypes (clinical and pathological presentation)

Clinicopathologic phenotype (human)

Suggested HPO terms (examples; mapping-level suggestions)

Frequency data

4. Genetic / molecular information

“Causal genes”

Key recurrent somatic alterations (current understanding)

Epigenetic information

5. Mechanism / pathophysiology

Core mechanistic themes

Immune microenvironment (2024 primary study)

Recent developments (2023–2024)

Suggested GO terms (mechanism-level; mapping suggestions)

Suggested CL terms (cell types)

6. Epidemiology, population, and prognosis

Prevalence / proportion among gastric cancers

Prognosis (statistics)

7. Diagnostics

Core diagnostic definition

Biomarkers used alongside EBV status

Omics-based diagnostics / recent development

Differential diagnosis

8. Treatment and real-world implementation

Standard-of-care context

Immunotherapy (checkpoint blockade) — response statistics

Translational/precision treatment implications

Clinical trials (real-world implementations; ClinicalTrials.gov)

Suggested MAXO terms (treatment action ontology; mapping suggestions)

9. Model organisms and experimental models

Mechanistic and translational models

10. Summary table artifact

11. Expert opinion / authoritative synthesis (2024 reviews)

Data gaps and limitations (important for knowledge base curation)