Metastatic Melanoma

1. Disease Information (definition and current understanding)

Definition/overview. Melanoma is a malignant neoplasm arising from melanocytes; metastatic melanoma refers to melanoma that has disseminated beyond the primary site/regional basin to distant organs (stage IV in common staging usage), or clinically “advanced/unresectable” disease requiring systemic therapy (wang2025advancesinimmunotherapy pages 1-2, datzmann2021implementationandeffectiveness pages 2-3). Metastatic disease commonly involves lung, liver, brain, lymph nodes, and bone (wang2025advancesinimmunotherapy pages 1-2). Historically, metastatic melanoma had extremely poor survival prior to modern systemic therapies (poletto2023predictivefactorsin pages 1-2, shah2024immunecheckpointinhibitors pages 1-2).

Key concept: treatment eras. Multiple 2023–2024 sources emphasize a treatment‑era shift: before immune checkpoint inhibitors (ICIs) and modern targeted therapy, median overall survival (OS) was ~6 months; contemporary regimens can yield multi‑year median OS and long‑term survival in a substantial fraction of patients (poletto2023predictivefactorsin pages 1-2, jalil2024exploringresistanceto pages 1-3).

Direct abstract quotes supporting key concepts (examples). - From a 2024 ICI‑focused review: “However, over 50% of patients experience limited or no response to ICI therapy. Resistance to ICIs is influenced by a complex interplay of tumour intrinsic and extrinsic factors.” (Hossain et al., 2024; https://doi.org/10.3390/ijms251810120) (hossain2024immunecheckpointinhibitor pages 1-2) - From a 2024 resistance review: metastatic melanoma survival “below 5%” historically, shifting to “over 50%” 5‑year survival in the modern era, with ~50% not responding or relapsing (Jalil et al., 2024; https://doi.org/10.20517/cdr.2024.54) (jalil2024exploringresistanceto pages 1-3)

2. Etiology

2.1 Disease causal factors (mechanistic and environmental)

UV radiation as dominant environmental carcinogen. Contemporary epidemiologic reviews identify ultraviolet radiation exposure as the key risk factor for cutaneous malignant melanoma, with additional contributions from phenotype and behavioral exposure patterns (sunburns, indoor tanning) (pinto2024globaltrendsin pages 7-11). Mechanistically, UV can generate DNA damage (e.g., thymine dimers), while melanin is protective via UV absorption and free‑radical scavenging (wang2025recentglobalpatterns pages 1-2).

2.2 Risk factors (genetic and environmental)

Environmental/host risk factors (population literature). Risk factors highlighted in 2024 global trend and 2024 US mortality analyses include: UV exposure (strongest), fair skin phenotype and sun sensitivity, high nevus count/dysplastic nevi, family/personal history, immunosuppression, and indoor tanning (pinto2024globaltrendsin pages 7-11, didier2024patternsandtrends pages 1-2). Ozone depletion and geography influence UV exposure and melanoma burden (pinto2024globaltrendsin pages 7-11).

Genetic susceptibility / molecular predisposition (tumor drivers). Metastatic melanoma biology is strongly shaped by somatic driver alterations that activate the MAPK pathway. Reviews cite BRAFV600 mutations in ~40–50% of cutaneous melanomas, enabling BRAF/MEK targeted therapy (fernandez2023newapproachesto pages 1-3, jalil2024exploringresistanceto pages 1-3).

2.3 Protective factors

Protective pigmentation context. Higher melanin levels reduce UV penetration and associated damage; lower melanin in lighter-skinned individuals increases melanoma risk (wang2025recentglobalpatterns pages 1-2). (Specific quantified effect sizes for sunscreen or behavioral interventions were not retrieved in current tool evidence.)

2.4 Gene–environment interactions

The retrieved evidence supports a conceptual model in which UV exposure induces DNA damage and mutational/neoantigen landscapes that influence immune recognition and response to immunotherapy (high mutational burden is repeatedly discussed as a predictor of ICI response), linking environmental carcinogenesis to immunotherapy sensitivity (kato2026drugtherapyfor pages 3-4, roccuzzo2024prognosticbiomarkersin pages 3-4). (Specific GxE loci/effect sizes were not retrieved in current tool evidence.)

3. Phenotypes (clinical presentation and metastatic patterns)

3.1 Core metastatic phenotypes and clinical manifestations

Metastatic dissemination sites. Advanced melanoma commonly metastasizes to lung, liver, brain, lymph nodes, and bone (wang2025advancesinimmunotherapy pages 1-2). Brain metastases are frequent; one real‑world community series observed brain metastases in 27.4% (20/73) during first‑line ipilimumab+nivolumab management, and the paper reiterates historical estimates of very high lifetime risk in metastatic melanoma (ong2025timingofbrain pages 1-2, ong2025timingofbrain pages 4-5).

Treatment-related phenotypes (immune-related toxicities). Combination ICI improves efficacy but increases high‑grade toxicity, a recurring expert theme in 2023–2024 reviews (hossain2024immunecheckpointinhibitor pages 1-2). In a Danish real‑world cohort of asymptomatic melanoma brain metastases treated with ipilimumab+nivolumab, 35.4% discontinued due to grade 3–4 adverse events (kattenhøj2024efficacyofipilimumab pages 4-6).

3.2 Phenotype ontology suggestions (HPO)

Because phenotype frequency tables were not retrieved from dedicated phenotype resources (HPO/Orphanet/OMIM) in the tool context, the following HPO term suggestions are plausible mappings for knowledge‑base structuring (not asserted as comprehensive): - Brain metastasis: Metastatic neoplasm (HP:0030972) + site qualifiers; consider custom mapping to “brain metastasis” if available in HPO extensions. - Liver metastasis: Metastatic neoplasm (HP:0030972) with liver localization. - Elevated LDH: Increased circulating lactate dehydrogenase concentration (HPO term exists in many HPO builds; exact ID not retrieved here). - Cutaneous/subcutaneous metastases: Subcutaneous nodule (HP:0012126) (as an approximation).

(For a production knowledge base, direct HPO lookups are recommended; not possible in this run due to tool limitations.)

4. Genetic / Molecular Information

4.1 Key causal/driver genes (somatic; actionable in practice)

MAPK pathway driver alterations. Reviews consistently emphasize MAPK pathway activation as central. Key genes/targets implicated in metastatic melanoma and therapy selection include BRAF, MAP2K1/2 (MEK1/2), and NRAS; immune checkpoint targets include PDCD1 (PD‑1) and CTLA4 (OpenTargets Search: metastatic melanoma, fernandez2023newapproachesto pages 1-3). BRAF alterations are the most established predictive biomarker for targeted therapy selection (fernandez2023newapproachesto pages 1-3).

4.2 Pathogenic variants / variant classes (summary)

• BRAF V600 (e.g., V600E/K) activating substitutions: common actionable somatic driver; supports BRAF inhibitor + MEK inhibitor combinations (fernandez2023newapproachesto pages 1-3, fateeva2024currentstateof pages 5-6).
• NF1 loss / PTEN inactivation: associated with pathway rewiring and resistance mechanisms (MAPK reactivation, PI3K–AKT activation), discussed as contributors to therapy resistance (kolathur2024molecularsusceptibilityand pages 13-15).

(Allele frequencies in population databases and ClinVar/ACMG germline classifications were not retrieved in current evidence. For metastatic melanoma, most clinical decision-making is based on somatic tumor profiling.)

4.3 Biomarkers (tumor and circulating)

Tumor mutational burden (TMB), PD‑L1, and IFN‑γ signatures. A 2024 biomarker review highlights TMB, PD‑L1 expression, and IFN‑γ signature as promising correlates of improved response in melanoma trials (roccuzzo2024prognosticbiomarkersin pages 3-4). Another 2023 review frames biomarkers across host/immune/tumor categories and emphasizes LDH/CRP/ctDNA plus inflammatory signatures (poletto2023predictivefactorsin pages 1-2).

Circulating tumor DNA (ctDNA). A meta‑analysis including 1,063 melanoma patients treated with ICIs (literature through Aug 15, 2024) found detectable ctDNA was associated with substantially worse outcomes: - Pretreatment detectable ctDNA: OS HR 3.19; PFS HR 2.08. - On‑treatment detectable ctDNA: OS HR 4.57; PFS HR 3.79. (liu2025theprognosticvalue pages 1-2)

5. Mechanism / Pathophysiology

5.1 Causal chains (from initiating factors to metastatic disease)

1) UV exposure / DNA damage → mutational accumulation → oncogenic signaling activation (MAPK pathway via BRAF/NRAS/NF1 alterations) → melanocyte transformation and tumor progression (wang2025recentglobalpatterns pages 1-2, fernandez2023newapproachesto pages 1-3). 2) Tumor evolution and microenvironmental shaping → immune escape (PD‑1/PD‑L1 axis, CTLA‑4 mediated suppression, myeloid-driven immunosuppression) → metastatic progression and therapeutic resistance (song2024currentknowledgeabout pages 1-3, zielinska2025mechanismsofresistance pages 8-9).

5.2 Major pathways and processes

MAPK pathway (RAS–RAF–MEK–ERK). Central melanoma growth and survival pathway; BRAF mutations enable targeted inhibitors. Acquired resistance often involves MAPK reactivation (fateeva2024currentstateof pages 5-6).

PI3K–AKT pathway bypass and crosstalk. Resistance and survival can be supported by PI3K–AKT signaling; NF1/PTEN alterations are discussed as enabling this bypass and contributing to targeted therapy resistance (kolathur2024molecularsusceptibilityand pages 13-15, kato2026drugtherapyfor pages 3-4).

Immune evasion and TME suppression. Resistance to anti‑PD‑1 can be mediated by suppressive TME cell types (Tregs, TAMs, MDSCs), suppressive cytokines (IL‑10, TGF‑β), nutrient depletion (arginine/tryptophan), hypoxia/acidity, and IDO‑mediated tryptophan catabolism (zielinska2025mechanismsofresistance pages 8-9). Microbiome influences anti‑PD‑1 response, with some taxa associated with enhanced dendritic cell activity (zielinska2025mechanismsofresistance pages 8-9).

Visual evidence (treatment landscape and resistance). Fateeva et al. (2024) provide a schematic overview of FDA‑approved advanced melanoma therapies (ICIs and targeted BRAF/MEK agents) and a separate figure outlining targeted‑therapy resistance mechanisms including MAPK reactivation/bypass (fateeva2024currentstateof media 7006da46, fateeva2024currentstateof media e15bcd35).

5.3 Ontology suggestions

• GO biological process (examples): MAPK cascade; regulation of T cell activation; antigen processing and presentation; interferon‑gamma signaling; leukocyte chemotaxis; epithelial–mesenchymal transition-like programs / dedifferentiation (the latter is discussed conceptually in resistance literature but not quantified in extracted evidence).
• CL cell types (examples): CD8+ T cell; regulatory T cell; tumor-associated macrophage; myeloid-derived suppressor cell; dendritic cell.

6. Anatomical Structures Affected

Organ-level metastatic targets. Lung, liver, brain, lymph nodes, bone are repeatedly cited common metastatic destinations (wang2025advancesinimmunotherapy pages 1-2). Brain metastasis is clinically prominent and a major determinant of management strategy (kattenhøj2024efficacyofipilimumab pages 1-2).

UBERON suggestions (examples; IDs not retrieved here): skin; lymph node; brain; liver; lung; bone.

7. Temporal Development (onset and progression)

Staging concept. Real-world cohort definitions tie distant metastatic codes (C78/C79) to UICC/AJCC stage IV, and locoregional metastases (C77) to stage III in study classification (datzmann2021implementationandeffectiveness pages 2-3). Clinically, metastatic melanoma may present synchronously with initial diagnosis or metachronously (subsequent metastasis), as operationalized in registry analyses (datzmann2021implementationandeffectiveness pages 2-3).

Brain metastasis timing. In a community cohort on first‑line ipilimumab+nivolumab, delayed brain metastases were uncommon (6/59) and occurred within 15 months, with poor outcomes (ong2025timingofbrain pages 1-2).

8. Inheritance and Population (epidemiology)

8.1 Global burden statistics (recent)

• GLOBOCAN 2022: 331,722 new melanoma cases and ~58,667 deaths globally; incidence highest in Oceania/North America/Europe (wang2025recentglobalpatterns pages 1-2).
• GBD 2021 melanoma prevalence trend: global cutaneous malignant melanoma prevalence 833,215 (2021), a 161.3% increase since 1990; ASPR 25.37/100,000; ASMR 0.73/100,000; DALYs 1,678,836 (liu2024globalregionaland pages 1-2).

8.2 US mortality trends (population disparities)

US CDC WONDER analysis (1999–2020): 184,416 melanoma deaths; age‑adjusted mortality declined from 2.7 to 2.0 per 100,000, with higher mortality in men and older adults; rural populations had higher mortality than urban/suburban (didier2024patternsandtrends pages 1-2).

9. Diagnostics

Standard-of-care diagnosis (high-level). The tool evidence set in this run did not include dedicated pathology/imaging guideline documents; therefore, detailed diagnostic criteria, histopathologic and immunohistochemical panels, and radiology protocols are not exhaustively enumerated here.

Real-world implementation signal (testing/monitoring). Danish national practice for melanoma brain metastases in a registry cohort used MRI for intracranial response and PET/CT for systemic disease at ~12-week intervals during early follow-up, consistent with high-intensity monitoring in advanced melanoma care (kattenhøj2024efficacyofipilimumab pages 4-6).

Biomarker testing. BRAF mutation status is described as a key predictive biomarker for therapy selection; TMB is described as controversial; ctDNA is emerging as prognostic/monitoring biomarker with meta-analytic hazard ratios (fernandez2023newapproachesto pages 1-3, liu2025theprognosticvalue pages 1-2).

10. Outcome / Prognosis

10.1 Survival improvement with modern systemic therapy

A 2023 review summarizes historical and modern outcomes: - Pre‑modern era: metastatic melanoma median OS ~6 months (poletto2023predictivefactorsin pages 1-2). - Anti‑PD‑1 monotherapy: ORR 42–45%; median OS ~3 years (poletto2023predictivefactorsin pages 1-2). - Nivolumab + ipilimumab: ORR 58%; median OS 72.1 months (poletto2023predictivefactorsin pages 1-2). A 2024 resistance review cites CheckMate‑067 long‑term data: median OS 72.1 months and 6.5‑year survival 56% (jalil2024exploringresistanceto pages 1-3).

10.2 Prognostic biomarkers (recent quantitative examples)

LDH risk stratification. A 2024 biomarker review reports dramatic stratification by LDH: LDH <2×ULN associated with 1‑year PFS 68% and OS 90%, whereas LDH ≥2×ULN shows 1‑year PFS 8% and OS 40% (roccuzzo2024prognosticbiomarkersin pages 3-4).

ctDNA hazard ratios. Detectable ctDNA is associated with markedly worse OS and PFS both pre‑treatment and during ICI therapy (liu2025theprognosticvalue pages 1-2).

11. Treatment (current applications, real-world implementation, and recent developments)

11.1 Current standard systemic modalities

Immune checkpoint inhibitors (ICIs). ICIs target CTLA‑4 and PD‑1/PD‑L1 (and newer targets such as LAG‑3) to restore anti-tumor T cell activity (shah2024immunecheckpointinhibitors pages 1-2, hossain2024immunecheckpointinhibitor pages 1-2). Combination strategies improve efficacy but can increase toxicity (hossain2024immunecheckpointinhibitor pages 1-2).

Targeted therapy for BRAF‑mutant melanoma. BRAF inhibitors plus MEK inhibitors improve response and survival versus earlier approaches but are limited by resistance (often within months) and toxicity (fateeva2024currentstateof pages 5-6).

Visual summary of therapy classes. Fateeva et al. (2024) figure depicts FDA-approved advanced melanoma therapies across ICI classes and BRAF/MEK targeted agents (fateeva2024currentstateof media 7006da46).

11.2 Brain metastases management (real-world and trial data)

Real-world outcomes with ipilimumab+nivolumab in asymptomatic melanoma brain metastases. Danish registry cohort (n=79) first‑line ipilimumab+nivolumab: ORR 46.9%, CR 16.5%, 6‑month PFS 53.5%, median PFS 6.5 months, median OS not reached at 5 years (kattenhøj2024efficacyofipilimumab pages 1-2).

Trial benchmark and emerging combinations. A 2024 Neuro-Oncology Advances abstract cites CheckMate 204 intracranial response 54% with ipilimumab+nivolumab and grade 3/4 TRAEs 55%, and early phase II data for nivolumab+relatlimab in brain metastases (intracranial response 43% in first 8 patients; grade 3 TRAEs 12%) (phillips2024imun05phaseii pages 1-1).

11.3 Emerging/ongoing clinical trials (real-world implementation readiness)

ClinicalTrials.gov records provide structured evidence for near-term implementations: - RELATIVITY-047 (NCT03470922): relatlimab+nivolumab vs nivolumab, Phase 2/3; primary endpoint PFS by blinded review; includes biomarker tissue requirements; excludes active brain metastases (NCT03470922 chunk 1). - RELATIVITY-127 (NCT05625399): SC vs IV nivolumab+relatlimab FDC, Phase 3; primary endpoints pharmacokinetics with key clinical endpoints including ORR/PFS/OS and QoL (FACT‑MS) (NCT05625399 chunk 1). - TILVANCE-301 / IOV-MEL-301 (NCT05727904): autologous TIL therapy lifileucel + pembrolizumab vs pembrolizumab, Phase 3; primary endpoints ORR and PFS; includes optional crossover to lifileucel upon progression (NCT05727904 chunk 1).

11.4 Treatment ontology suggestions (MAXO; examples)

• Immune checkpoint inhibitor therapy; anti‑PD‑1 therapy; anti‑CTLA‑4 therapy; anti‑LAG‑3 therapy; BRAF inhibitor therapy; MEK inhibitor therapy; adoptive T cell therapy / tumor‑infiltrating lymphocyte therapy; stereotactic radiosurgery (for brain metastases) (therapy modalities discussed across sources) (fateeva2024currentstateof media 7006da46, NCT05727904 chunk 1).

12. Prevention

Primary prevention. Global trend analyses emphasize UV exposure as the primary modifiable risk factor and connect prevention (sun protection) and early detection to mortality declines in high-income regions (e.g., Australia) (pinto2024globaltrendsin pages 1-2, pinto2024globaltrendsin pages 7-11).

Secondary prevention/early detection. The global trends review highlights early diagnosis (including dermoscopy and ABCD rule awareness) as contributors to improved outcomes and mortality reductions (pinto2024globaltrendsin pages 7-11).

(Quantified effect sizes for specific screening programs or sunscreen interventions were not retrieved in the current tool evidence.)

13. Other Species / Natural Disease

Canine melanoma as a comparative model. Integrated comparative genomic analysis of canine malignant melanoma identifies recurrent somatic alterations (e.g., truncating PTPRJ mutations ~19%; RAS mutations ~24%; TP53 mutations ~19%; MDM2 amplifications ~24%), with noted differences such as absent BRAF mutations and low UV mutational signatures, supporting comparative modeling for BRAF‑wild-type/sun‑shielded melanoma subtypes (Hendricks et al., 2018; https://doi.org/10.1371/journal.pgen.1007589) (pqac-000000?? not retrieved in evidence extraction in this run; paper text present but not gathered into evidence snippets).

Because full evidence snippets were not extracted for this section in the current run, cross‑species claims should be treated as incomplete.

14. Model Organisms and Experimental Models

The current tool evidence set did not include dedicated model-organism or cell-line methodological reviews for metastatic melanoma; thus only high-level, commonly used systems are listed as non‑exhaustive: genetically engineered mouse models (BRAF/NRAS-driven), xenografts/PDX, syngeneic mouse melanoma lines, and TIL/immune co-culture systems. For a knowledge base, these should be populated using model‑system databases (MGI/IMSR/Cellosaurus) and primary experimental papers.

Consolidated quantitative reference table

Table: This table compiles high-yield quantitative findings for metastatic melanoma across epidemiology, therapy outcomes, biomarker prognostics, and major ongoing clinical trials. It is useful as a compact reference for evidence-backed burden estimates and current treatment landscape metrics.

Expert synthesis / analysis (authoritative themes)

1) Durable survival is now achievable, especially with combination ICI regimens, but primary/acquired resistance remains common (~50%) (poletto2023predictivefactorsin pages 1-2, jalil2024exploringresistanceto pages 1-3, hossain2024immunecheckpointinhibitor pages 1-2). 2) Mechanisms of resistance are multi-layered, spanning tumor intrinsic (antigen presentation defects, IFN‑γ pathway changes, MAPK/PI3K signaling) and extrinsic TME factors (Tregs/TAMs/MDSCs, hypoxia/acidity, metabolic suppression), and may be influenced by the gut microbiome (kato2026drugtherapyfor pages 3-4, zielinska2025mechanismsofresistance pages 8-9). 3) Real-world data support translation of trial efficacy to selected populations (e.g., asymptomatic melanoma brain metastases treated with ipilimumab+nivolumab in a nationwide Danish registry) (kattenhøj2024efficacyofipilimumab pages 1-2). 4) Biomarkers with practical clinical traction include LDH and ctDNA, with strong prognostic separation and meta-analytic hazard ratios, while TMB/PD‑L1/IFN‑γ signatures are promising but require standardization and context-aware interpretation (roccuzzo2024prognosticbiomarkersin pages 3-4, liu2025theprognosticvalue pages 1-2).

Notes on evidence gaps in this run

• Dedicated retrieval of MONDO ID, MeSH ID, ICD‑11 code(s), structured HPO phenotype frequency tables, and diagnostic/pathology guideline documents was not successful with the current tool calls; therefore, these elements are intentionally not asserted beyond what was directly evidenced (OpenTargets Search: metastatic melanoma, datzmann2021implementationandeffectiveness pages 2-3).

References

1. (OpenTargets Search: metastatic melanoma): Open Targets Query (metastatic melanoma, 43 results). Buniello, A. et al. (2025). Open Targets Platform: facilitating therapeutic hypotheses building in drug discovery. Nucleic Acids Research.

2. (datzmann2021implementationandeffectiveness pages 2-3): T Datzmann, J Schmitt, S Fuhrmann, and M Roessler. Implementation and effectiveness of novel therapeutic substances for advanced malignant melanoma in saxony, germany, 2010–2020—cohort study …. Unknown journal, 2021.

3. (kattenhøj2024efficacyofipilimumab pages 1-2): Karoline Dreyer Kattenhøj, Christine Louise Møberg, Louise Mahncke Guldbrandt, Rasmus Blechingberg Friis, Christophe Kamungu Mapendano, Søren Kjær Petersen, Christina Halgaard Bruvik Ruhlmann, Inge Marie Svane, Marco Donia, Eva Ellebaek, and Henrik Schmidt. Efficacy of ipilimumab and nivolumab in patients with melanoma and brain metastases—a danish real-world cohort. Cancers, 16:2559, Jul 2024. URL: https://doi.org/10.3390/cancers16142559, doi:10.3390/cancers16142559. This article has 6 citations.

4. (jalil2024exploringresistanceto pages 1-3): Anum Jalil, Melissa M Donate, and Jane Mattei. Exploring resistance to immune checkpoint inhibitors and targeted therapies in melanoma. Cancer Drug Resistance, Oct 2024. URL: https://doi.org/10.20517/cdr.2024.54, doi:10.20517/cdr.2024.54. This article has 17 citations.

5. (liu2024globalregionaland pages 1-2): Chengling Liu, Xingchen Liu, Li Hu, Xin Li, Haiming Xin, and Sailin Zhu. Global, regional, and national burden of cutaneous malignant melanoma from 1990 to 2021 and prediction to 2045. Frontiers in Oncology, Dec 2024. URL: https://doi.org/10.3389/fonc.2024.1512942, doi:10.3389/fonc.2024.1512942. This article has 25 citations.

6. (NCT05727904 chunk 1): Study to Investigate Lifileucel Regimen Plus Pembrolizumab Compared With Pembrolizumab Alone in Participants With Untreated Advanced Melanoma.. Iovance Biotherapeutics, Inc.. 2023. ClinicalTrials.gov Identifier: NCT05727904

7. (wang2025advancesinimmunotherapy pages 1-2): Xue Wang, Shanshan Ma, Shuting Zhu, Liucun Zhu, and Wenna Guo. Advances in immunotherapy and targeted therapy of malignant melanoma. Biomedicines, 13:225, Jan 2025. URL: https://doi.org/10.3390/biomedicines13010225, doi:10.3390/biomedicines13010225. This article has 23 citations.

8. (poletto2023predictivefactorsin pages 1-2): Stefano Poletto, Luca Paruzzo, Alessandro Nepote, Daniela Caravelli, Dario Sangiolo, and Fabrizio Carnevale-Schianca. Predictive factors in metastatic melanoma treated with immune checkpoint inhibitors: from clinical practice to future perspective. Cancers, 16:101, Dec 2023. URL: https://doi.org/10.3390/cancers16010101, doi:10.3390/cancers16010101. This article has 16 citations.

9. (shah2024immunecheckpointinhibitors pages 1-2): Vedant Shah, Viraj Panchal, Abhi Shah, Bhavya Vyas, Siddharth Agrawal, and Sanket Bharadwaj. Immune checkpoint inhibitors in metastatic melanoma therapy (review). Medicine International, Feb 2024. URL: https://doi.org/10.3892/mi.2024.137, doi:10.3892/mi.2024.137. This article has 41 citations.

10. (hossain2024immunecheckpointinhibitor pages 1-2): Sultana Mehbuba Hossain, Kevin Ly, Yih Jian Sung, Antony Braithwaite, and Kunyu Li. Immune checkpoint inhibitor therapy for metastatic melanoma: what should we focus on to improve the clinical outcomes? International Journal of Molecular Sciences, 25:10120, Sep 2024. URL: https://doi.org/10.3390/ijms251810120, doi:10.3390/ijms251810120. This article has 11 citations.

11. (pinto2024globaltrendsin pages 7-11): Giuseppe De Pinto, Silvia Mignozzi, Carlo La Vecchia, Fabio Levi, Eva Negri, and Claudia Santucci. Global trends in cutaneous malignant melanoma incidence and mortality. Melanoma Research, 34:265-275, Feb 2024. URL: https://doi.org/10.1097/cmr.0000000000000959, doi:10.1097/cmr.0000000000000959. This article has 65 citations and is from a peer-reviewed journal.

12. (wang2025recentglobalpatterns pages 1-2): Mingyue Wang, Xinghua Gao, and Li Zhang. Recent global patterns in skin cancer incidence, mortality, and prevalence. Chinese Medical Journal, 138:185-192, Dec 2025. URL: https://doi.org/10.1097/cm9.0000000000003416, doi:10.1097/cm9.0000000000003416. This article has 131 citations and is from a peer-reviewed journal.

13. (didier2024patternsandtrends pages 1-2): Alexander J. Didier, Swamroop V. Nandwani, Dean Watkins, Alan M. Fahoury, Andrew Campbell, Daniel J. Craig, Divya Vijendra, and Nancy Parquet. Patterns and trends in melanoma mortality in the united states, 1999–2020. BMC Cancer, Jul 2024. URL: https://doi.org/10.1186/s12885-024-12426-z, doi:10.1186/s12885-024-12426-z. This article has 38 citations and is from a peer-reviewed journal.

14. (fernandez2023newapproachesto pages 1-3): Manuel Felipe Fernandez, Jacob Choi, and Jeffrey Sosman. New approaches to targeted therapy in melanoma. Cancers, 15:3224, Jun 2023. URL: https://doi.org/10.3390/cancers15123224, doi:10.3390/cancers15123224. This article has 48 citations.

15. (kato2026drugtherapyfor pages 3-4): Hiroshi Kato. Drug therapy for melanoma: current updates and future prospects. Cancers, 18:382, Jan 2026. URL: https://doi.org/10.3390/cancers18030382, doi:10.3390/cancers18030382. This article has 1 citations.

16. (roccuzzo2024prognosticbiomarkersin pages 3-4): Gabriele Roccuzzo, Cristina Sarda, Valentina Pala, Simone Ribero, and Pietro Quaglino. Prognostic biomarkers in melanoma: a 2023 update from clinical trials in different therapeutic scenarios. Expert Review of Molecular Diagnostics, 24:379-392, May 2024. URL: https://doi.org/10.1080/14737159.2024.2347484, doi:10.1080/14737159.2024.2347484. This article has 12 citations and is from a peer-reviewed journal.

17. (ong2025timingofbrain pages 1-2): Claire Victoria Ong and Wolfram Samlowski. Timing of brain metastases in relation to outcome during first-line ipilimumab plus nivolumab therapy for metastatic melanoma in a community oncology practice. Journal of Neuro-Oncology, 172:645-653, Feb 2025. URL: https://doi.org/10.1007/s11060-025-04951-z, doi:10.1007/s11060-025-04951-z. This article has 1 citations and is from a peer-reviewed journal.

18. (ong2025timingofbrain pages 4-5): Claire Victoria Ong and Wolfram Samlowski. Timing of brain metastases in relation to outcome during first-line ipilimumab plus nivolumab therapy for metastatic melanoma in a community oncology practice. Journal of Neuro-Oncology, 172:645-653, Feb 2025. URL: https://doi.org/10.1007/s11060-025-04951-z, doi:10.1007/s11060-025-04951-z. This article has 1 citations and is from a peer-reviewed journal.

19. (kattenhøj2024efficacyofipilimumab pages 4-6): Karoline Dreyer Kattenhøj, Christine Louise Møberg, Louise Mahncke Guldbrandt, Rasmus Blechingberg Friis, Christophe Kamungu Mapendano, Søren Kjær Petersen, Christina Halgaard Bruvik Ruhlmann, Inge Marie Svane, Marco Donia, Eva Ellebaek, and Henrik Schmidt. Efficacy of ipilimumab and nivolumab in patients with melanoma and brain metastases—a danish real-world cohort. Cancers, 16:2559, Jul 2024. URL: https://doi.org/10.3390/cancers16142559, doi:10.3390/cancers16142559. This article has 6 citations.

20. (fateeva2024currentstateof pages 5-6): Anna Fateeva, Kevinn Eddy, and Suzie Chen. Current state of melanoma therapy and next steps: battling therapeutic resistance. Cancers, 16:1571, Apr 2024. URL: https://doi.org/10.3390/cancers16081571, doi:10.3390/cancers16081571. This article has 53 citations.

21. (kolathur2024molecularsusceptibilityand pages 13-15): Kiran Kumar Kolathur, Radhakanta Nag, Prathvi V Shenoy, Yagya Malik, Sai Manasa Varanasi, Ramcharan Singh Angom, and Debabrata Mukhopadhyay. Molecular susceptibility and treatment challenges in melanoma. Cells, 13:1383, Aug 2024. URL: https://doi.org/10.3390/cells13161383, doi:10.3390/cells13161383. This article has 11 citations.

22. (liu2025theprognosticvalue pages 1-2): Lei Liu, Shufu Hou, Aiping Zhu, Bing Yan, Linchuan Li, and Dandan Song. The prognostic value of circulating tumor dna in malignant melanoma patients treated with immune checkpoint inhibitors: a systematic review and meta-analysis. Frontiers in Immunology, Jan 2025. URL: https://doi.org/10.3389/fimmu.2024.1520441, doi:10.3389/fimmu.2024.1520441. This article has 9 citations and is from a peer-reviewed journal.

23. (song2024currentknowledgeabout pages 1-3): Lanni Song, Yixin Yang, and Xuechen Tian. Current knowledge about immunotherapy resistance for melanoma and potential predictive and prognostic biomarkers. Cancer Drug Resistance, May 2024. URL: https://doi.org/10.20517/cdr.2023.150, doi:10.20517/cdr.2023.150. This article has 5 citations.

24. (zielinska2025mechanismsofresistance pages 8-9): Magdalena K. Zielińska, Magdalena Ciążyńska, Dorota Sulejczak, Piotr Rutkowski, and Anna M. Czarnecka. Mechanisms of resistance to anti-pd-1 immunotherapy in melanoma and strategies to overcome it. Biomolecules, 15:269, Feb 2025. URL: https://doi.org/10.3390/biom15020269, doi:10.3390/biom15020269. This article has 28 citations.

25. (fateeva2024currentstateof media 7006da46): Anna Fateeva, Kevinn Eddy, and Suzie Chen. Current state of melanoma therapy and next steps: battling therapeutic resistance. Cancers, 16:1571, Apr 2024. URL: https://doi.org/10.3390/cancers16081571, doi:10.3390/cancers16081571. This article has 53 citations.

26. (fateeva2024currentstateof media e15bcd35): Anna Fateeva, Kevinn Eddy, and Suzie Chen. Current state of melanoma therapy and next steps: battling therapeutic resistance. Cancers, 16:1571, Apr 2024. URL: https://doi.org/10.3390/cancers16081571, doi:10.3390/cancers16081571. This article has 53 citations.

27. (phillips2024imun05phaseii pages 1-1): Suzanne Phillips, Elizabeth Burton, Isabella Claudia Glitza Oliva, Jennifer McQuade, Rodabe Amaria, Adi Diab, Michael Wong, Caroline Chung, Denái Milton, Jared Malke, Julie Simon, Jeffrey Wefel, Jing Li, Michael Davies, and Hussein Tawbi. Imun-05 phase ii study of nivolumab (nivo) in combination with relatlimab (rela) in patients with active melanoma brain metastases (mbm). Neuro-Oncology Advances, 6:i14-i15, Aug 2024. URL: https://doi.org/10.1093/noajnl/vdae090.044, doi:10.1093/noajnl/vdae090.044. This article has 1 citations and is from a peer-reviewed journal.

28. (NCT03470922 chunk 1): A Study of Relatlimab Plus Nivolumab Versus Nivolumab Alone in Participants With Advanced Melanoma. Bristol-Myers Squibb. 2018. ClinicalTrials.gov Identifier: NCT03470922

29. (NCT05625399 chunk 1): A Study of Subcutaneous Nivolumab + Relatlimab Fixed-dose Combination (FDC) in Previously Untreated Metastatic or Unresectable Melanoma. Bristol-Myers Squibb. 2023. ClinicalTrials.gov Identifier: NCT05625399

30. (pinto2024globaltrendsin pages 1-2): Giuseppe De Pinto, Silvia Mignozzi, Carlo La Vecchia, Fabio Levi, Eva Negri, and Claudia Santucci. Global trends in cutaneous malignant melanoma incidence and mortality. Melanoma Research, 34:265-275, Feb 2024. URL: https://doi.org/10.1097/cmr.0000000000000959, doi:10.1097/cmr.0000000000000959. This article has 65 citations and is from a peer-reviewed journal.