4.6 Article

Whole-Exome Sequencing Uncovers Specific Genetic Variation Difference Based on Different Modes of Drug Resistance in Small Cell Lung Cancer

Journal

FRONTIERS IN ONCOLOGY
Volume 12, Issue -, Pages -

Publisher

FRONTIERS MEDIA SA
DOI: 10.3389/fonc.2022.891938

Keywords

small cell lung cancer; whole-exome sequencing; somatic mutational signature; recurrence; therapeutic strategy

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Funding

  1. special funds for Taishan Scholars Project [tsqn201812149]

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This study analyzed whole-exome sequencing data to explore the differences in mutational characteristics, gene expression, and chromosomal instability between chemorefractory and chemosensitive small cell lung cancer (SCLC) patients. A classifier was developed to predict treatment response and recurrence risk, providing a reference basis for personalized treatment plans for Chinese SCLC patients.
The poor survival rate of small cell lung cancer (SCLC) is mainly related to the condition that patients with SCLC often have good responses to first-line chemotherapy initially, but later on, most of these patients relapse rapidly due to resistance to further treatment. In this study, we attempted to analyze whole-exome sequencing data based on the largest sample size to date, to develop a classifier to predict whether a patient will be chemorefractory or chemosensitive and to explicate the risk of recurrence that affects the prognosis of patients. We showed the different characteristics of somatic mutational signatures, somatic mutation genes, and distinct genome instability between chemorefractory and chemosensitive SCLC patients. Amplified mutations in the chemosensitive group inhibited the regulation of the cell cycle process, transcription factor binding, and B-cell differentiation. Analysis of deletion mutation also suggested that detection of the chromosomal-level variation might influence our treatment decisions. Higher PD-L1 expressions (based on TPS methods) were mostly present among chemosensitive patients (p = 0.026), while there were no differences in PD-L1 expressions (based on CPS methods) and CD8(+) TILs between the two groups. According to the model determined by logistic regression, each sample was endowed with a predictive probability value (PV). The samples were divided into a high-risk group (>0.55) and a low-risk group (<= 0.55), and the survival analysis showed obvious differences between the two groups. This study provides a reference basis to translate this knowledge into practice, such as formulating personalized treatment plans, which may benefit Chinese patients with SCLC.

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