Dataset Information

Smoking status combined with tumor mutational burden as a prognosis predictor for combination immune checkpoint inhibitor therapy in non-small cell lung cancer.

ABSTRACT:

Background

This study aimed to explore the prognostic value of tumor mutational burden (TMB) combined with smoking status in advanced non-small cell lung cancer (NSCLC) patients who received immune checkpoint inhibitor therapy (anti PD-1/PD-L1 therapy) combined with chemotherapy or anti-angiogenesis therapy.

Methods

We conducted a retrospective analysis of NSCLC patients who underwent next-generation sequencing test (either 295-gene panel NGS or 1021-gene panel NGS) from September 2017 to November 2020. The relationship between TMB and smoking status was investigated. Kaplan-Meier survival analysis was used to compare progression-free survival (PFS) of the NSCLC patients who received combination immunotherapy grouped by TMB value and smoking status.

Results

We enrolled 323 cases and 388 cases of NSCLC patients in the 295-gene panel cohort and 1021-gene panel cohort, respectively. Positive correlation between TMB and smoking status was found in lung adenocarcinoma, but not in lung squamous cell carcinoma. Participants with both high TMB and smoking status who received immune checkpoint therapy combined with chemotherapy or anti-angiogenesis therapy had longer PFS than other participants (p < 0.05).

Conclusions

The combination of TMB with smoking status might be a potential predictor for the efficacy of combination immunotherapy in advanced NSCLC.

SUBMITTER: Sun LY

PROVIDER: S-EPMC8495280 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature

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Publications

Smoking status combined with tumor mutational burden as a prognosis predictor for combination immune checkpoint inhibitor therapy in non-small cell lung cancer.

Sun Li-Yue LY Cen Wen-Jian WJ Tang Wen-Ting WT Long Ya-Kang YK Yang Xin-Hua XH Ji Xiao-Meng XM Yang Jiao-Jiao JJ Zhang Ren-Jing RJ Wang Fang F Shao Jian-Yong JY Du Zi-Ming ZM

Cancer medicine 20210901 19

<h4>Background</h4>This study aimed to explore the prognostic value of tumor mutational burden (TMB) combined with smoking status in advanced non-small cell lung cancer (NSCLC) patients who received immune checkpoint inhibitor therapy (anti PD-1/PD-L1 therapy) combined with chemotherapy or anti-angiogenesis therapy.<h4>Methods</h4>We conducted a retrospective analysis of NSCLC patients who underwent next-generation sequencing test (either 295-gene panel NGS or 1021-gene panel NGS) from September ...[more]

PMID: 34469045

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Project description:BackgroundThe ryanodine receptors (RYRs) have been implicated in many muscular, cardiac and neurological diseases. However, there are almost no studies so far focusing on RYR genetic alterations and its roles in cancer, especially in non-small cell lung cancer (NSCLC).MethodsThe whole-exome sequencing (WES) data, demographic and clinical data of 1,052 NSCLC patients was downloaded from The Cancer Genome Atlas (TCGA) database and analyzed using the corresponding packages of the R software. Mutational profile was established and its correlation with tumor mutational burden (TMB), prognosis, age and smoking status was analyzed and compared.ResultsRYR mutations were found in 502 NSCLC patients, in which mutations of RYR1, RYR2 and RYR3 were found in 17.3% (182/1,052), 40.0% (421/1,052) and 21.3% (224/1,052) of patients, respectively. Random distribution of mutations without hotspot mutations were observed with all three RYR isoforms. Significant co-mutations were found between RYR1 and RYR3, while mutual exclusive mutations were found between RYR1 and RYR2, and between RYR2 and RYR3. Significant correlation was found between cumulative number of mutations and cumulative TMB for all three RYR isoforms, and patients with RYR mutations exhibited significantly higher TMB than those without RYR mutations. Significant correlation was also found between mutational status and age in RYR2 and RYR3, and between mutational status and smoking history grading in all three isoforms, and between mutational status and number of pack years in RYR3. More interestingly, significant stratification of patient survival was revealed by RYR2 mutational status, which was found to be one of the independent risk factors for patient prognosis in multivariate Cox analysis.ConclusionsThe mutational profile of RYR in NSCLC has been characterized for the first time. Strong correlation was found between RYR mutational status and TMB, age and smoking status. RYR2 mutational status was an independent risk factor for NSCLC patient prognosis.

Project description:BACKGROUND:To achieve optimal outcomes, an individual approach is needed in the treatment and care of patients. The potential value of tumor mutational burden (TMB) status and/or programmed cell death ligand 1 (PD-L1) expression as biomarkers to predict which patients are most likely to respond to checkpoint inhibitors has been explored in many studies. The goal of this targeted literature review is to identify data available for TMB status and/or PD-L1 expression that predict response to checkpoint inhibitors and/or anti-cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) antibodies. METHODS:Targeted literature searches were performed using electronic medical databases (MEDLINE, Embase, and BIOSIS) and internet searches of specified sites. Bibliographies of key systematic literature reviews and meta-analyses also were reviewed for studies of interest. RESULTS:The review identified 27 studies of non-small cell lung cancer (NSCLC), 40 studies of melanoma, 10 studies of urothelial cancer, and 5 studies of renal cell cancer indications. Studies also were identified in other cancer types, e.g., colorectal, breast, gastric, and Merkel cell cancer and squamous-cell carcinoma of the head and neck. Twelve trials, including six in NSCLC and four in melanoma, evaluated TMB as a predictor of outcomes. A TMB of ≥10 mutations per megabase was shown to be an effective biomarker in the CheckMate 227 study. PD-L1 expression was included in the majority of identified studies and was found to predict response in in melanoma and in all types of NSCLC. Prediction of response was not a prespecified analysis in some studies; others had small sample sizes and wide confidence intervals. A clear predictive trend for PD-L1 expression was not identified in renal, breast, gastric, or Merkel cell cancer. CONCLUSION:Based on data contained in this review, assessment of TMB status and PD-L1 expression may help enhance the prediction of response to checkpoint inhibition in some tumors, such as NSCLC and melanoma. In this rapidly growing area of research, further exploratory biomarkers are being investigated including tumor-infiltrating lymphocytes, immune profiling (e.g., effector T cells or regulatory T cells), epigenetic signatures, T-cell receptor repertoire, proteomics, microbiome, and metabolomics.

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Dataset Information

Smoking status combined with tumor mutational burden as a prognosis predictor for combination immune checkpoint inhibitor therapy in non-small cell lung cancer.

Background

Methods

Results

Conclusions

Publications

Smoking status combined with tumor mutational burden as a prognosis predictor for combination immune checkpoint inhibitor therapy in non-small cell lung cancer.

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