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Published on: July 25, 2020
Molecular profiling of Asian patients with advanced melanoma receiving check-point inhibitor treatment
1Department of Medicine, Division of Hematology-Oncology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea; Department of Internal Medicine, Chungbuk National University Hospital, Chungbuk National University College of Medicine, Cheongju, Korea.
Objective:
Melanoma is major medical challenge and being able to monitor treatment response is critical. This study aimed to use molecular profiling of Asian patients with advanced melanoma who were receiving treatment with check-point inhibitors (CPIs) to identify novel biomarkers of tumor response.
Methods:
Next-generation sequencing (NGS) was performed using tumor specimens collected from 178 Asian patients with metastatic melanoma receiving CPIs. The NGS data and clinical-pathological factors were analyzed for potential genetic biomarkers of tumor response to CPI treatment.
Results:
The most common melanoma subtype was acral melanoma (40%), followed by cutaneous melanoma (32%), mucosal melanoma (26%), and others (2%). For calculation of treatment efficacy, 164 of the patients could be evaluated. The overall response rate was 45.7%, of which 41 cases exhibited complete responses (25.0%) and 34 showed partial responses (20.7%). There were no significant differences in tumor responses based on melanoma subtype (P = 0.295). Genetically, NRAS mutations, TP53 mutations, and NF2 deletions were significantly associated with resistance to CPIs (P < 0.05). In contrast, MYC and RPS6KB1 amplifications were associated with responsiveness to CPIs (P < 0.05). Median progression-free survival (PFS) for patients treated with CPIs was 5.9 months (95% CI, 3.8-8.05 months). Univariate analysis identified TP53 and BRAF mutations, NF2 deletions, and BIRC2 amplifications as poor prognostic factors for PFS (P < 0.05).
Conclusions:
This study determined the integrated genomic profiles of Asian patients with metastatic melanoma receiving CPIs and identified candidate biomarkers that reflected treatment outcomes.
Insights
Molecular profiling of Asian melanoma patients treated with checkpoint inhibitors (CPIs) identified genetic biomarkers for treatment response. Specific gene mutations and amplifications correlated with resistance or responsiveness to CPI therapy, aiding in outcome prediction.
Area of Science:
- Oncology
- Genomics
- Cancer Research
Background:
- Melanoma presents a significant challenge in cancer treatment.
- Monitoring patient response to therapy, especially with immune checkpoint inhibitors (CPIs), is critical for effective management.
- Identifying predictive biomarkers can optimize treatment strategies for advanced melanoma.
Purpose of the Study:
- To investigate the molecular profiles of Asian patients with advanced melanoma undergoing CPI treatment.
- To identify novel genomic biomarkers associated with tumor response to CPIs in this population.
- To correlate genetic alterations with clinical outcomes, including response rates and progression-free survival.
Main Methods:
- Next-generation sequencing (NGS) was performed on tumor specimens from 178 Asian patients with metastatic melanoma receiving CPIs.
- Clinical-pathological data were analyzed alongside NGS results.
- Statistical analyses were conducted to identify significant associations between genetic factors and treatment response.
Main Results:
- Acral melanoma was the most frequent subtype (40%).
- The overall response rate to CPIs was 45.7%.
- NRAS mutations, TP53 mutations, and NF2 deletions were linked to CPI resistance (P < 0.05).
- MYC and RPS6KB1 amplifications were associated with CPI responsiveness (P < 0.05).
- TP53 mutations, BRAF mutations, NF2 deletions, and BIRC2 amplifications were poor prognostic factors for progression-free survival (PFS).
Conclusions:
- Integrated genomic profiling of Asian patients receiving CPIs provides insights into treatment response.
- Candidate biomarkers, including specific gene mutations and amplifications, have been identified.
- These findings can potentially guide personalized treatment strategies for advanced melanoma.
