Dataset Information

Predictive value of tumor mutation burden (TMB) with targeted next-generation sequencing in immunocheckpoint inhibitors for non-small cell lung cancer (NSCLC).

ABSTRACT: Background: To evaluate the clinical predictive value of tumor mutation burden (TMB) for immune checkpoint inhibitor (ICI) therapy in patients with non-small cell lung cancer (NSCLC). Method: As of 15 February 2020, PubMed, PMC and EMBASE databases as well as the American society of clinical oncology (ASCO) and European society of medical oncology (ESMO) databases were searched. The Mantel-Haenszel or inverse variance weighted fixed-effects model (I² ? 50%) or random-effects model (I² > 50%) were used to evaluate OR and its 95% CI of objective response rate (ORR) and disease control rate (DCR) , as well as HR and its 95% CI of progression-free survival (PFS) and overall survival (OS). In addition, we did publication bias, heterogeneity analysis, sensitivity analysis and subgroup analysis. And quality of the studies included and the level of evidence for outcome measures were evaluated. Results: 14 studies involving 2872 patients were included. The ORR (OR 3.52, 95%CI 2.32-5.35, p < 0.00001), DCR (OR 3.26, 95%CI 1.91-5.55, p < 0.0001), PFS (HR 0.81, 95%CI 0.74-0.89, p < 0.00001) and OS (HR 0.83, 95%CI 0.74-0.94, p = 0.002) of ICI therapy in the high TMB group were all superior to those in the low TMB group. Conclusions: TMB is a promising biomarker, which can predict the efficacy of ICI therapy in advanced NSCLC patients, included ORR, DCR, PFS and OS.

SUBMITTER: Ma X

PROVIDER: S-EPMC7738995 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Predictive value of tumor mutation burden (TMB) with targeted next-generation sequencing in immunocheckpoint inhibitors for non-small cell lung cancer (NSCLC).

Ma Xiaoting X Zhang Yujian Y Wang Shan S Yu Jing J

Journal of Cancer 20210101 2

Background: To evaluate the clinical predictive value of tumor mutation burden (TMB) for immune checkpoint inhibitor (ICI) therapy in patients with non-small cell lung cancer (NSCLC). Method: As of 15 February 2020, PubMed, PMC and EMBASE databases as well as the American society of clinical oncology (ASCO) and European society of medical oncology (ESMO) databases were searched. The Mantel-Haenszel or inverse variance weighted fixed-effects model (I2 ≤ 50%) or random-eff ...[more]

PMID: 33391454

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Project description:First-generation, reversible epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs), erlotinib and gefitinib, represented an important addition to the treatment armamentarium for non-small-cell lung cancer (NSCLC) patients with activating EGFR mutations. However, all patients inevitably develop acquired resistance to these agents, primarily due to secondary EGFR mutations, molecular aberrations affecting other signaling pathways, or transformation to small-cell histology. It was hypothesized that development of second-generation TKIs with broader inhibitory profiles could confer longer-lasting clinical activity and overcome acquired resistance to first-generation inhibitors. Here, we review the development of afatinib, an irreversible ErbB family blocker that potently inhibits signaling of all homodimers and heterodimers formed by the EGFR, human epidermal growth factor receptor (HER)-2, HER3, and HER4 receptors. In two phase III trials in patients with EGFR mutation-positive NSCLC, first-line afatinib significantly improved progression-free survival (PFS) and health-related quality of life versus standard-of-care chemotherapy. Moreover, in preplanned sub-analyses, afatinib significantly improved overall survival in patients harboring EGFR Del19 mutations. Afatinib has also demonstrated clinical activity in NSCLC patients who had progressed on erlotinib/gefitinib, particularly when combined with cetuximab, and offers 'treatment beyond progression' benefit when combined with paclitaxel versus chemotherapy alone. Furthermore, a recent phase III study demonstrated that PFS was significantly improved with afatinib versus erlotinib for the second-line treatment of patients with squamous cell carcinoma of the lung. The activity of afatinib in both first-line and relapsed/refractory settings may reflect its ability to irreversibly inhibit all ErbB family members. Afatinib has a well-defined safety profile with characteristic gastrointestinal (diarrhea, stomatitis) and cutaneous (rash/acne) adverse events.

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.

Dataset Information

Predictive value of tumor mutation burden (TMB) with targeted next-generation sequencing in immunocheckpoint inhibitors for non-small cell lung cancer (NSCLC).

Publications

Predictive value of tumor mutation burden (TMB) with targeted next-generation sequencing in immunocheckpoint inhibitors for non-small cell lung cancer (NSCLC).

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