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. 2022 Jan 11:9:770811.
doi: 10.3389/fcell.2021.770811. eCollection 2021.

CAMSAP1 Mutation Correlates With Improved Prognosis in Small Cell Lung Cancer Patients Treated With Platinum-Based Chemotherapy

Yonglin Yi  1 , Zhengang Qiu  2 , Zifu Yao  1   3 , Anqi Lin  1 , Yimin Qin  1 , Ruizhan Sha  1 , Ting Wei  1 , Yanru Wang  1 , Quan Cheng  4 , Jian Zhang  1 , Peng Luo  1 , Weitao Shen  1
Affiliations

CAMSAP1 Mutation Correlates With Improved Prognosis in Small Cell Lung Cancer Patients Treated With Platinum-Based Chemotherapy

Yonglin Yi et al. Front Cell Dev Biol. .

Abstract

Platinum-based chemotherapy is the first-line treatment for small cell lung cancer (SCLC). However, due to patients developing a resistance to the drug, most experience relapse and their cancer can become untreatable. A large number of recent studies have found that platinum drug sensitivity of various cancers is affected by specific gene mutations, and so with this study, we attempted to find an effective genetic biomarker in SCLC patients that indicates their sensitivity to platinum-based drugs. To do this, we first analyzed whole exome sequencing (WES) and clinical data from two cohorts to find gene mutations related to the prognosis and to the platinum drug sensitivity of SCLC patients. The cohorts used were the Zhujiang cohort (N = 138) and the cohort reported by George et al. (N = 101). We then carried out gene set variation analysis (GSVA) and gene set enrichment analysis (GSEA) to investigate possible molecular mechanisms through which these gene mutations affect patient prognosis and platinum drug sensitivity. We found that for SCLC patients, CAMSAP1 mutation can activate anti-tumor immunity, mediate tumor cell apoptosis, inhibit epithelial-mesenchymal transition (EMT), improve prognosis, and improve platinum drug sensitivity, suggesting that CAMSAP1 mutation may be a potential biomarker indicating platinum drug sensitivity and patient prognosis in SCLC.

Keywords: CAMSAP1; biomarker; drug sensitivity; platinum-based chemotherapy; small cell lung cancer.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

FIGURE 1
FIGURE 1
Bioinformatics analysis process. SCLC, small-cell lung cancer; GSVA, gene set variation analysis; GSEA, gene set enrichment analysis; cMAP, connectivity map.
FIGURE 2
FIGURE 2
Cox proportional risk regression analysis identifying survival-related genes. (A) The forest plots show the univariate cox analysis results of 51 common OS-related gene mutations in the Zhujiang and reported cohorts (B) Venn diagram showing the overlap of OS-related genes with mutation frequency >5% in the Zhujiang and reported cohorts. (C) Multivariate cox analysis results of gene mutations, clinical factors and OS in the Zhujiang and reported cohorts. (D) Kaplan-Meier survival analysis results of OS comparing the CAMSAP1-MT group (red) and the CAMSAP1-WT group (blue) in the Zhujiang and reported cohorts. OS, overall survival; HR, hazard ratio; CL, confidence interval.
FIGURE 3
FIGURE 3
Genetic characteristics of SCLC patients. (A) Panoramic views of the 20 most frequently mutated genes in the Zhujiang and reported cohorts. Genes are sorted by mutation frequency. CAMSAP1 status, sex, OS, PFS, mutation type and mutation frequency are marked. ***: p < 0.001; **: p < 0.01; *: p < 0.05. (B) Lollipop plot showing the distribution of CAMSAP1 mutation in the Zhujiang and reported cohorts.
FIGURE 4
FIGURE 4
Oncogene mutations in SCLC patients. (A) Panoramic views of the 20 most frequently mutated oncogenes in the Zhujiang and reported cohorts. Genes are sorted by mutation frequency. CAMSAP1 status, sex, OS, PFS, mutation type and mutation frequency are marked. ***: p < 0.001; **: p < 0.01; *: p < 0.05. (B) Co-occurrence and mutual exclusivity among the 20 most frequently mutated oncogenes in the Zhujiang and reported cohorts. (C) Co-occurrence and mutual exclusivity among the 20 most frequently mutated genes in the Zhujiang and reported cohorts.
FIGURE 5
FIGURE 5
Transcriptome functional characteristics of the CAMSAP1-MT and the CAMSAP1-WT groups. (A) The difference in GSVA scores between the CAMSAP1-MT and CAMSAP1-WT groups in the Zhujiang cohort. (B) The difference in GSVA scores between the CAMSAP1-MT and CAMSAP1-WT groups in the reported cohort. (C) GSEA results of platinum drug sensitivity and prognosis related pathways, including anti-tumor immune pathway, platinum-mediated apoptosis pathway and cell activity pathway. The results above reflect the Zhujiang cohort, and the results below reflect the reported cohort. Yellow represents mutual exclusivity and green represents co-occurrence. *: p < 0.01.
FIGURE 6
FIGURE 6
Potential CAMSAP1 targeted drugs. (A) Heatmap showing the enrichment scores of each compound obtained by cMAP analysis in the Zhujiang and reported cohorts. Red indicates an enrichment score >0 and blue indicates an enrichment score <0. (B) Heatmap showing the MoA of each compound. The histogram on the right shows the number of compounds in each MoA. The histogram on the top shows the number of MoA of each compound. MoA: Mode-of-action.
FIGURE 7
FIGURE 7
Possible mechanism underlying the improved platinum drug sensitivity and prognosis of CAMSAP1-MT SCLC patients.
See this image and copyright information in PMC

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