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Oncogenic alterations reveal key strategies for precision oncology in melanoma treatment

Wei Sun1,2, Fang Zhao3, Tu Hu1,2

  • 1Department of Musculoskeletal Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.

Annals of Translational Medicine
|December 22, 2022
PubMed
Abstract

Insights

Next-generation sequencing (NGS) in melanoma patients identified EGFR mutations as predictors of progression-free survival with immunotherapy. Combined genetic and clinical analysis revealed specific mutations linked to lower survival rates.

Area of Science:

  • Oncology
  • Genomics
  • Precision Medicine

Background:

  • Molecular profiling using next-generation sequencing (NGS) is increasingly used in solid tumors like melanoma to find drug targets.
  • The link between molecular alterations and clinical outcomes in melanoma remains incompletely understood.

Purpose of the Study:

  • To investigate the association between molecular alterations identified by NGS and clinical outcomes in melanoma patients.
  • To explore the utility of a predictive model for treatment side effects.
  • To identify specific genetic markers associated with survival and response to immunotherapy.

Main Methods:

  • Analyzed genetic alterations in 108 malignant melanoma patients using the OncoCare panel (559 genes).
  • Collected sequencing data and clinical outcomes for 95 patients.
  • Developed a predictive model for side effects using clinical data and somatic variants.

Main Results:

  • An epidermal growth factor receptor (EGFR) mutation predicted progression-free survival (PFS) in patients receiving immunotherapy (log-rank P=0.01).
  • Tumor mutation burden (TMB) was not significantly associated with PFS (log-rank P=0.87).
  • Patients with combined DNA POLD1/ALOX12B or POLD1/PTPRT mutations showed significantly lower survival rates.

Conclusions:

  • NGS clinical panels offer benefits for melanoma treatment stratification.
  • Findings support the development of personalized therapeutic strategies for melanoma based on molecular profiling.
Keywords:
Melanomagenetic alterationsmachine learningnext-generation sequencing panels (NGS panels)prognostic predictors

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