AI Article Synopsis

  • The study investigates how whole-exome sequencing and circulating free DNA (cfDNA) can help predict therapy response in metastatic melanoma patients during treatment.
  • Non-responders showed more genetic variations and mutations in key melanoma genes compared to responders, especially in those with the V600 mutation.
  • The study also found that factors like tumor mutational burden (TMB), loss of heterozygosity (LOH), and tumor ploidy were linked to therapy resistance, suggesting that genomic testing can provide insights into treatment outcomes.

Article Abstract

Although several studies have explored the molecular landscape of metastatic melanoma, the genetic determinants of therapy resistance are still largely unknown. Here, we aimed to determine the contribution of whole-exome sequencing and circulating free DNA (cfDNA) analysis in predicting response to therapy in a consecutive real-world cohort of 36 patients, undergoing fresh tissue biopsy and followed during treatment. Although the underpowered sample size limited statistical analysis, samples from non-responders had higher copy number variations and mutations in melanoma driver genes compared to responders in the V600+ subset. In the V600- subset, Tumor Mutational Burden (TMB) was twice that in responders vs. non-responders. Genomic layout revealed commonly known and novel potential intrinsic/acquired resistance driver gene variants. Among these, , , mutations, and / amplification/deletion were present in 42% and 67% of patients, respectively. Both Loss of Heterozygosity (LOH) load and tumor ploidy were inversely associated with TMB. In immunotherapy-treated patients, samples from responders showed higher TMB and lower LOH and were more frequently diploid compared to non-responders. Secondary germline testing and cfDNA analysis proved their efficacy in finding germline predisposing variants carriers (8.3%) and following dynamic changes during treatment as a surrogate of tissue biopsy, respectively.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10002464PMC
http://dx.doi.org/10.3390/ijms24054302DOI Listing

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