The data access committee for Multimodal Genomic Features Predict Outcome of Immune Checkpoint Blockade in Non-small Cell Lung Cancer
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PROVIDER: EGAC00001001331 | EGA |
REPOSITORIES: EGA
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Project description:Despite progress in immunotherapy, identifying patients that respond has remained a challenge. Through analysis of whole-exome and targeted sequence data from 5,449 tumors, we found a significant correlation between tumor mutation burden (TMB) and tumor purity, suggesting that low tumor purity tumors are likely to have inaccurate TMB estimates. We developed a new method to estimate a corrected TMB (cTMB) that was adjusted for tumor purity and more accurately predicted outcome to immune checkpoint blockade (ICB). To identify improved predictive markers together with cTMB, we performed whole-exome sequencing for 104 lung tumors treated with ICB. Through comprehensive analyses of sequence and structural alterations, we discovered a significant enrichment in activating mutations in receptor tyrosine kinase (RTK) genes in nonresponding tumors in three immunotherapy treated cohorts. An integrated multivariable model incorporating cTMB, RTK mutations, smoking-related mutational signature and human leukocyte antigen status provided an improved predictor of response to immunotherapy that was independently validated.
| S-EPMC7514475 | biostudies-literature
Project description:Despite progress in immunotherapy, identifying patients that respond has remained a challenge. Through analysis of whole-exome and targeted sequence data from 5,449 tumors, we found a significant correlation between tumor mutation burden (TMB) and tumor purity, suggesting that low tumor purity tumors are likely to have inaccurate TMB estimates. We developed a new method to estimate a corrected TMB (cTMB) that was adjusted for tumor purity and more accurately predicted outcome to immune checkpoint blockade (ICB). To identify improved predictive markers together with cTMB, we performed whole-exome sequencing for 104 lung tumors treated with ICB. Through comprehensive analyses of sequence and structural alterations, we discovered a significant enrichment in activating mutations in receptor tyrosine kinase (RTK) genes in non-responding tumors in three immunotherapy-treated cohorts. An integrated multivariable model incorporating cTMB, RTK mutations, smoking-related mutational signature, and HLA status provided an improved predictor of response to immunotherapy that was independently validated.
| EGAS00001003892 | EGA
Project description:Multimodal Genomic Features Predict Outcome of Immune Checkpoint Blockade in Non-small Cell Lung Cancer
| PRJNA592578 | ENA
Project description:Multimodal Genomic Features Predict Outcome of Immune Checkpoint Blockade in Non-small Cell Lung Cancer
| PRJNA592579 | ENA
Project description:Immune checkpoint blockade (ICB) therapy has provided clinical benefits for patients with advanced non-small-cell lung cancer (NSCLC), but the majority still do not respond. Although a few biomarkers of ICB treatment response have been developed, the predictive power of these biomarkers showed substantial variation across datasets. Therefore, predicting response to ICB therapy remains a challenge. Here, we provided a concise combinatorial strategy for predicting ICB therapy response and constructed the ICB treatment signature (ITS) in lung cancer. The prediction performance of ITS has been validated in an independent ICB treatment cohort of NSCLC, where patients with higher ITS score were significantly associated with longer progression-free survival and better response. And ITS score was more powerful than traditional biomarkers, such as TMB and PD-L1, in predicting the ICB treatment response in NSCLC. In addition, ITS scores still had predictive effects in other cancer data sets, showing strong scalability and robustness. Further research showed that a high ITS score represented comprehensive immune activation characteristics including activated immune cell infiltration, increased mutation load, and TCR diversity. In conclusion, our practice suggested that the combination of biomarkers will lead to a better prediction of ICB treatment prognosis, and the ITS score will provide NSCLC patients with better ICB treatment decisions.
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Project description:BackgroundPredictive biomarkers of immune checkpoint inhibitor (ICI) efficacy are currently lacking for non-small cell lung cancer (NSCLC). Here, we describe the results from the Anti-PD-1 Response Prediction DREAM Challenge, a crowdsourced initiative that enabled the assessment of predictive models by using data from two randomized controlled clinical trials (RCTs) of ICIs in first-line metastatic NSCLC.MethodsParticipants developed and trained models using public resources. These were evaluated with data from the CheckMate 026 trial (NCT02041533), according to the model-to-data paradigm to maintain patient confidentiality. The generalizability of the models with the best predictive performance was assessed using data from the CheckMate 227 trial (NCT02477826). Both trials were phase III RCTs with a chemotherapy control arm, which supported the differentiation between predictive and prognostic models. Isolated model containers were evaluated using a bespoke strategy that considered the challenges of handling transcriptome data from clinical trials.ResultsA total of 59 teams participated, with 417 models submitted. Multiple predictive models, as opposed to a prognostic model, were generated for predicting overall survival, progression-free survival, and progressive disease status with ICIs. Variables within the models submitted by participants included tumor mutational burden (TMB), programmed death ligand 1 (PD-L1) expression, and gene-expression-based signatures. The best-performing models showed improved predictive power over reference variables, including TMB or PD-L1.ConclusionsThis DREAM Challenge is the first successful attempt to use protected phase III clinical data for a crowdsourced effort towards generating predictive models for ICI clinical outcomes and could serve as a blueprint for similar efforts in other tumor types and disease states, setting a benchmark for future studies aiming to identify biomarkers predictive of ICI efficacy.Trial registrationCheckMate 026; NCT02041533, registered January 22, 2014. CheckMate 227; NCT02477826, registered June 23, 2015.
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Project description:Peripheral-immune-checkpoint blockade (P-ICB) with mAbs to PD-1 (nivolumab and pembrolizumab) or PD-L1 (atezolizumab, durvalumab, avelumab) alone or combination with chemotherapy represents a novel active treatment for mNSCLC patients. However, this therapy can be associated to immune-related adverse events (irAEs) and high cost. Therefore, finding reliable biomarkers of response and irAEs is strongly encouraged to accurately select patients who may potentially benefit from the immuno-oncological treatment. This is a retrospective multi-institutional analysis performed on ninety-five mNSCLC patients who received real-world salvage therapy with nivolumab or atezolizumab between December 2015 and April 2020. The outcome of these patients in term of PFS and OS was evaluated in comparison with different serum levels of C-reactive protein (CRP), Erythrocyte Sedimention Rate (ESR) and Procalcitonin (PCT) by performing Kaplan-Meier and Log-rank test and multivariate analysis. We found that high baseline levels of CRP, ESR, and PCT were strongly predictive of poor outcome (P <0.05) with the worse prognosis detected in those patients with a baseline levels of both ESR and PCT over the pre-established cut off (median OS recorded in patients with no marker over the cut off vs. those with just one marker over the cut off vs. those with both markers over the cut off: 40 ± 59 vs. 15.5 ± 5.5 vs. 5.5 ± 1.6 months, respectively; P <0.0001). Our results suggest the predictive value of systemic inflammation and suggest a potential role of PCT in predicting a poor outcome in mNSCLC receiving PD-1/PD-L1 blocking mAbs. This finding also suggests a potential role of subclinical bacterial infections in defining the response to PD-1/PD-L1 blocking mAbs that deserves further and more specific investigations.
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Project description:Patients with oncogene-driven lung cancer have limited therapeutic options after progressing on their targeted tyrosine kinase inhibitor (TKI) therapy. Given the growing role of immune checkpoint inhibitor (ICI) therapy in the treatment of lung cancer, oncogene-driven cancer has warranted further evaluation regarding ICI therapy. However, initial ICI studies have suggested that ICI monotherapy is not only lacking in efficacy, but that it may be less tolerable in oncogene-driven non-small-cell lung cancer (NSCLC). We performed a detailed review of the literature using Pubmed, and present the current and impactful findings here. Studies evaluating the use of concurrent ICI therapy and TKI therapy have also suggested increased toxicity and lack of increased activity in these patients. Larger studies have suggested that the sequence of ICI therapy and TKI, such as utilizing ICI therapy after TKI as opposed to before TKI, may play a role in reducing toxicity (hepatotoxicity, pneumonitis); however, these studies are limited in number. Novel methods of patient selection, including low tumor mutational burden, inflamed phenotyping, and high CD8 + tumor infiltrating lymphocytes, may aid in determining ideal patients to give ICI therapy. Novel therapeutic combinations including the addition of anti-VEGF (vascular endothelial growth factor) therapy or radiotherapy show promising findings for these patients. Given the growing unmet need for therapeutic options in patients with oncogene-driven NSCLC who have failed TKI therapy, further research is warranted.
| S-EPMC8579493 | biostudies-literature
Project description:Immune checkpoint blockade has shown anti-tumour activity and improved survival in advanced non-small cell lung cancer (NSCLC). A number of anti-PD-1/PD-L1 and CTLA-4 monoclonal antibody agents have been evaluated in metastatic non-small cell lung cancer. Nivolumab, pembrolizumab and atezolizumab are currently approved for use in clinical practice due to demonstrated improvement in response rate, overall survival (OS) and quality of life (QoL) over standard chemotherapy. We present a series of cases that highlight the clinical challenges that these novel agents present. A review of rare immune-related adverse events (AEs), optimal treatment duration and patient selection will be presented. This series will also address real-life clinical scenarios such as treatment re-challenge and management of immune-related AEs.
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Project description:Despite the initial successes of immunotherapy, there is an urgent clinical need for molecular assays that identify patients more likely to respond. Here, we report that ultrasensitive measures of circulating tumor DNA (ctDNA) and T-cell expansion can be used to assess responses to immune checkpoint blockade in metastatic lung cancer patients (N = 24). Patients with clinical response to therapy had a complete reduction in ctDNA levels after initiation of therapy, whereas nonresponders had no significant changes or an increase in ctDNA levels. Patients with initial response followed by acquired resistance to therapy had an initial drop followed by recrudescence in ctDNA levels. Patients without a molecular response had shorter progression-free and overall survival compared with molecular responders [5.2 vs. 14.5 and 8.4 vs. 18.7 months; HR 5.36; 95% confidence interval (CI), 1.57-18.35; P = 0.007 and HR 6.91; 95% CI, 1.37-34.97; P = 0.02, respectively], which was detected on average 8.7 weeks earlier and was more predictive of clinical benefit than CT imaging. Expansion of T cells, measured through increases of T-cell receptor productive frequencies, mirrored ctDNA reduction in response to therapy. We validated this approach in an independent cohort of patients with early-stage non-small cell lung cancer (N = 14), where the therapeutic effect was measured by pathologic assessment of residual tumor after anti-PD1 therapy. Consistent with our initial findings, early ctDNA dynamics predicted pathologic response to immune checkpoint blockade. These analyses provide an approach for rapid determination of therapeutic outcomes for patients treated with immune checkpoint inhibitors and have important implications for the development of personalized immune targeted strategies.Significance: Rapid and sensitive detection of circulating tumor DNA dynamic changes and T-cell expansion can be used to guide immune targeted therapy for patients with lung cancer.See related commentary by Zou and Meyerson, p. 1038.
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