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Predictive Value of Max’s Giant Associated Protein Mutation in Outcomes of Lung Adenocarcinoma Patients Treated With Immune Checkpoint Inhibitors

ABSTRACT: Treatment with immune checkpoint inhibitors (ICIs) has considerably improved prognosis in multiple cancers. However, regardless of PD-L1 expression and TMB, better predictive biomarkers are required to identify ICI-responsive patients. We analyzed a pan-cancer cohort as the discovery cohort to identify the role of Max’s giant associated protein (MGA) mutation in the outcome of ICI treatment in different types of cancers. A pooled lung adenocarcinoma (LUAD) cohort was considered as the validation cohort. Another two LUAD cohorts who received conventional treatment were included for prognostic analysis and mechanism exploration. In the discovery cohort, MGA mutation was a favorable survival biomarker for patients with LUAD than in those with other types of cancers. MGA mutation was positively correlated with the TMB score. The results of the validation cohort were consistent with those of the discovery cohort. Patients with MGA mutation in the TMB-low subgroup had longer survival. Two LUAD cohorts who received standard treatment showed that the MGA mutation was not a prognostic biomarker for standard treatment. Mechanically, we found that the co-mutant genes did not affect the prognostic role of MGA mutation. Gene-set enrichment analysis revealed that genes belonging to the immunodeficiency pathway were enriched in the MGA wild-type group in LUAD. Moreover, activated NK cells were more enriched in the MGA mutant LUAD group. In conclusion, our results demonstrated that MGA mutation was an independent predictive biomarker for ICI therapy. These results may provide a novel insight into identifying potential patients with LUAD for ICI therapy.

SUBMITTER: Qu Y

PROVIDER: S-EPMC8558674 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundA critical and challenging process in immunotherapy is to identify cancer patients who could benefit from immune checkpoint inhibitors (ICIs). Exploration of predictive biomarkers could help to maximize the clinical benefits. Eph receptors have been shown to play essential roles in tumor immunity. However, the association between EPH gene mutation and ICI response is lacking.MethodsClinical data and whole-exome sequencing (WES) data from published studies were collected and consolidated as a discovery cohort to analyze the association between EPH gene mutation and efficacy of ICI therapy. Another independent cohort from Memorial Sloan Kettering Cancer Center (MSKCC) was adopted to validate our findings. The Cancer Genome Atlas (TCGA) cohort was used to perform anti-tumor immunity and pathway enrichment analysis.ResultsAmong fourteen EPH genes, EPHA7-mutant (EPHA7-MUT) was enriched in patients responding to ICI therapy (FDR adjusted P < 0.05). In the discovery cohort (n = 386), significant differences were detected between EPHA7-MUT and EPHA7-wildtype (EPHA7-WT) patients regarding objective response rate (ORR, 52.6% vs 29.1%, FDR adjusted P = 0.0357) and durable clinical benefit (DCB, 70.3% vs 42.7%, FDR adjusted P = 0.0200). In the validation cohort (n = 1144), significant overall survival advantage was observed in EPHA7-MUT patients (HR = 0.62 [95% confidence interval, 0.39 to 0.97], multivariable adjusted P = 0.0367), which was independent of tumor mutational burden (TMB) and copy number alteration (CNA). Notably, EPHA7-MUT patients without ICI therapy had significantly worse overall survival in TCGA cohort (HR = 1.33 [95% confidence interval, 1.06 to 1.67], multivariable adjusted P = 0.0139). Further gene set enrichment analysis revealed enhanced anti-tumor immunity in EPHA7-MUT tumor.ConclusionsEPHA7-MUT successfully predicted better clinical outcomes in ICI-treated patients across multiple cancer types, indicating that EPHA7-MUT could serve as a potential predictive biomarker for immune checkpoint inhibitors.

Project description:BackgroundCD73 induces the dephosphorylation of adenosine monophosphate converting it to adenosine, enabling malignancies to escape from immune surveillance. Although CD73 overexpression has been reported to be a poor prognostic factor in several malignancies including non-small cell lung cancer (NSCLC), its predictive relevance in NSCLC patients receiving immune checkpoint inhibitors is unknown. The present research was conducted to investigate the prognostic significance of CD73 expression in NSCLC patients receiving immune checkpoint inhibitors (ICIs).MethodsWe screened 91 patients with advanced or recurrent NSCLC who received immune checkpoint inhibitors. CD73 expression was evaluated immunohistochemically using tissue specimens obtained just before treatment with ICIs.ResultsAnalysis of progression-free survival (PFS) and overall survival (OS) in relation to several levels of CD73 expression (1%, 10%, 30%, and 50%) showed that both tended to be more favorable as expression of CD73 increased. PFS and OS were longer for patients in whom at least 50% of the tumor cells expressed CD73 than for those in whom <50% of the tumor cells did so. In patients who were positive for EGFR mutation, immune checkpoint inhibitors were significantly more effective in those with high CD73 expression, whereas CD73 expression did not significantly affect the efficacy in patients with EGFR mutation-negative NSCLC. Furthermore, CD73 expression was predictive factor for the PFS independent of PD-L1 expression in patients with EGFR mutation.ConclusionsHigh CD73 expression may predict a favorable response to ICIs in NSCLC patients, especially those harboring EGFR mutations.Key pointsSignificant findings of the study: In patients who were positive for EGFR mutation, immune checkpoint inhibitors (ICIs) were significantly more effective in those with high CD73 expression, whereas CD73 expression did not significantly affect the efficacy in patients with EGFR mutation-negative NSCLC.What this study addsHigh CD73 expression may predict a favorable response to immune checkpoint inhibitors in NSCLC patients, especially those harboring EGFR mutations.

Project description:Background: Despite an increasing understanding about tumor mutation burden (TMB) in cancer immunity and cancer immunotherapy, the comprehensive cognition between TMB and efficiency of immune checkpoint inhibitors (ICIs) is still lacking. A systematic review and meta-analysis was conducted to evaluate the predictive value of TMB on efficacy of ICIs. Methods: Systematic literature search was conducted on PubMed, EMBASE, Web of Science and Cochrane Library up to June 16, 2019. Pooled odds ratio (OR) of objective response rate (ORR), hazard ratio (HR) of progression-free survival (PFS) and overall survival (OS) were estimated by inverse variance weighted fixed-effects model (I 2 ≤ 50%) or DerSimonian-Laird random-effects model (I 2 > 50%). In addition, heterogeneity analysis, sensitivity analysis, publication bias and subgroup analysis were conducted. Moreover, fractional polynomial regression was conducted to investigate the dose-response relationship between TMB cutoffs and efficacy of ICIs. Furthermore, we assessed ORR by TMB and programmed cell death ligand 1 (PD-L1) expression after layering each other in studies which the two could be both acquired. Results: Three thousand six hundred fifty-seven records were retrieved through database searching, and 29 studies with 4,431 patients were finally included in the meta-analysis. TMB high group had significantly improved ORR (pooled OR 3.31, 95% CI 2.61, 4.19, P < 0.001), PFS (pooled HR 0.59, 95% CI 0.49, 0.71, P < 0.001) and OS (pooled HR 0.68, 95% CI 0.53, 0.89, P = 0.004). Sensitivity analyses illustrated the results were stable, and publication bias was identified in ORR. Subgroup analyses showed the predictive value of TMB was significant in non-small-cell lung cancer (except for the OS) and melanoma. In addition, heterogeneity was substantial in targeted next generation sequencing group but tiny in whole exome sequencing group. Furthermore, TMB and PD-L1 expression were capable to predict improved ORR of ICIs after stratification of each other, with tiny heterogeneity. Conclusions: High tumor mutation burden predicted improved efficacy of immune checkpoint inhibitors in cancers, and targeted next generation sequencing for estimating tumor mutation burden in clinic should be standardized to eliminate heterogeneity in the future. Moreover, tumor mutation burden and programmed cell death ligand 1 expression were independent factors on predicting efficacy of immune checkpoint inhibitors.

Project description:Immune checkpoint inhibitors (ICIs) therapy elicits admirable anti-tumor responses across many types of cancer. Growing evidence point to a link to Mediator complex subunit 12 (MED12) and DNA damage repair (DDR) and TGF-β signing, while the clinical data on the association of MED12 and ICIs response are lacking. In this study, clinical and whole-exome sequencing (WES) data from published studies were merged as a WES cohort to explore the association between MED12 mutation (MED12-Mut) and ICIs efficiency across cancers. Then, Memorial Sloan Kettering Cancer Center (MSKCC) cohort was used for validating our findings. The Cancer Genome Atlas (TCGA) cohort was used to perform anti-tumor immunity and prognosis analysis. In the WES cohort (n = 474), significant differences were detected between MED12-Mut and MED12-wildtype (MED12-Wt) patients regarding durable clinical benefit (DCB, 80.00% vs. 53.67%, P = 0.022). In addition, significantly prolonged PFS was observed in MED12-Mut patients (mPFS: not reached, NR vs. 5.87 months, HR: 0.38, 95% CI 0.17-0.85, log-rank P = 0.015), After taking into account age, gender, metastasis, treatment and TMB status, the result of multivariable Cox proportional hazards regression showed significantly better PFS (HR:0.40, 95% CI 0.18-0.92; P = 0.031). In the MSKCC cohort (n = 1513), overall survival advantage was achieved in MED12-Mut patients (mOS: 41 vs. 19 months, HR:0.54, 95%CI 0.34-0.85; log-rank P = 0.007), after taking into account same factors in WES cohort, this link still existed (HR: 0.60, 95% CI: 0.38-0.96, P = 0.033), Notably, TMB was also found significantly higher in MED12-Mut patients in both WES and MSKCC cohort. Further tumor-infiltrating lymphocytes and DDR-related gene analysis revealed anti-tumor immunity in MED12-Mut patients. Totally, MED12-Mut successfully predicted better clinical outcomes in ICIs-treated pan-cancer cohort, indicating that MED12-Mut could serve as a potential predictive biomarker for immune checkpoint inhibitors in pan-cancer.

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Predictive Value of Max’s Giant Associated Protein Mutation in Outcomes of Lung Adenocarcinoma Patients Treated With Immune Checkpoint Inhibitors

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