Abstract 4928: Relationship between protein biomarkers of potential chemotherapy response and microsatellite status, tumor mutational burden, and PD-L1 expression in patients with cancer

2019 ◽  
Author(s):  
Mina Nikanjam ◽  
David Arguello ◽  
Zoran Gatalica ◽  
Donald A. Barkauskas ◽  
Razelle Kurzrock
Keyword(s):  
Chemotherapy Response ◽  
Protein Biomarkers ◽  
Patients With Cancer ◽  
Mutational Burden ◽  
Tumor Mutational Burden

scholarly journals Relationship between protein biomarkers of chemotherapy response and microsatellite status, tumor mutational burden and PD‐L1 expression in cancer patients

2020 ◽  
Vol 146 (11) ◽  
pp. 3087-3097 ◽  
Author(s):  
Mina Nikanjam ◽  
David Arguello ◽  
Zoran Gatalica ◽  
Jeff Swensen ◽  
Donald A. Barkauskas ◽  
...  
Keyword(s):  
Cancer Patients ◽  
Chemotherapy Response ◽  
Protein Biomarkers ◽  
Mutational Burden ◽  
Tumor Mutational Burden

scholarly journals Tumor mutational burden is not predictive of cytotoxic chemotherapy response

2020 ◽  
Vol 9 (1) ◽  
pp. 1781997
Author(s):  
Mina Nikanjam ◽  
Paul Riviere ◽  
Aaron Goodman ◽  
Donald A. Barkauskas ◽  
Garrett Frampton ◽  
...  
Keyword(s):  
Cytotoxic Chemotherapy ◽  
Chemotherapy Response ◽  
Mutational Burden ◽  
Tumor Mutational Burden

scholarly journals Bioinformatic Methods and Bridging of Assay Results for Reliable Tumor Mutational Burden Assessment in Non-Small Cell Lung Cancer

2019 ◽  
Author(s):  
Han Chang ◽  
Ariella Sasson ◽  
Sujaya Srinivasan ◽  
Ryan Golhar ◽  
Danielle M. Greenawalt ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Clinical Trial ◽  
Small Cell Lung Cancer ◽  
Small Cell ◽  
Missense Mutations ◽  
Small Cell Lung ◽  
Patients With Cancer ◽  
Mutational Burden ◽  
Tumor Mutational Burden ◽  
Highly Correlated

AbstractIntroductionTumor mutational burden (TMB) has emerged as a clinically relevant biomarker that may be associated with immune checkpoint inhibitor efficacy. Standardization of TMB measurement is essential for implementing diagnostic tools to guide treatment.ObjectiveHere we describe the in-depth evaluation of bioinformatic TMB analysis by whole exome sequencing (WES) in formalin-fixed, paraffin-embedded samples from a phase 3 clinical trial.MethodsIn the CheckMate 026 clinical trial, TMB was retrospectively assessed in 312 patients with non-small cell lung cancer (58% of the intent-to-treat population) who received first-line nivolumab treatment or standard-of-care chemotherapy. We examined the sensitivity of TMB assessment to bioinformatic filtering methods and assessed concordance between TMB data derived by WES and the FoundationOne®CDx assay.ResultsTMB scores comprising synonymous, indel, frameshift, and nonsense mutations (all mutations) were 3.1-fold higher than data including missense mutations only, but values were highly correlated (Spearman’s r = 0.99). Scores from CheckMate 026 samples including missense mutations only were similar to those generated from data in The Cancer Genome Atlas, but those including all mutations were generally higher. Using databases for germline subtraction (instead of matched controls) showed a trend for race-dependent increases in TMB scores. WES and FoundationOne CDx outputs were highly correlated (Spearman’s r = 0.90).ConclusionsParameter variation can impact TMB calculations, highlighting the need for standardization. Encouragingly, differences between assays could be accounted for by empirical calibration, suggesting that reliable TMB assessment across assays, platforms, and centers is achievable.Key PointsTumor mutational burden (TMB) is a clinically relevant biomarker for efficacy of immunotherapy in patients with cancerVariations in TMB assessment parameters can shift the final TMB value. Harmonization and standardization are important to the successful clinical implementation of TMB testingTMB values assessed by different methods are highly correlated. Harmonization of TMB testing in patients with cancer is therefore achievable

scholarly journals NCMP-17. MISMATCH REPAIR MUTATIONS AND THE CENTRAL NERVOUS SYSTEM: A CASE SERIES OF GERMLINE MUTATIONS AND CNS MALIGNANCY

2020 ◽  
Vol 22 (Supplement_2) ◽  
pp. ii126-ii126
Author(s):  
Amber Ruiz ◽  
Jerome Graber
Keyword(s):  
Treatment Response ◽  
Mismatch Repair ◽  
Case Series ◽  
Germline Mutations ◽  
Molecular Characteristics ◽  
Loss Of Function ◽  
Dna Mismatch ◽  
Mutational Burden ◽  
Increased Risk ◽  
Tumor Mutational Burden

Abstract Our understanding of genetic predispositions for malignancy is continually evolving. One family of germline mutations well described in the literature is that of the DNA mismatch repair mechanism (MMR). Lynch syndrome (LS) is due to a loss of function mutation of several MMR genes- MSH2, MLH1, MSH6, and PMS2. Germline MMR mutations lead to microsatellite instability and loss of genomic integrity resulting in an increased risk for various cancers (colorectal, genitourinary, etc). LS may be as common as 1 in 400 people and some MMR mutations have been associated with gliomas. There is a paucity of information regarding frequency of glioma subtypes as well as tumor genetic and molecular characteristics which have important clinical implications. We describe a case series of 6 individuals with germline MMR mutations and brain tumors. Those with MSH2 and PMS2 mutations (n=3) developed glioblastomas at a mean age at diagnosis of 48 years. These tumors expressed MGMT hyper-methylation and high tumor mutational burden. Only one had IDH-1 mutation. Those with MLH1 mutations (n=3), did not develop gliomas. This raises the question of differential glioma subtype development based on MMR gene. It also highlights the possibility of Lynch-associated gliomas having more favorable treatment response due to MGMT methylation and potential response to immunotherapy based on high tumor mutational burden. Though the sample size is small, there appears to be a preponderance of women compared to men (5:1 respectively). Larger studies are needed to verify CNS involvement in germline MMR mutations. In doing so, we hope to identify factors that may influence clinical management and lead to a better understanding of treatment response and disease prognosis.

Comprehensive exploration of tumor mutational burden and immune infiltration in diffuse glioma

2021 ◽  
Vol 96 ◽  
pp. 107610
Author(s):  
Kai Kang ◽  
Fucun Xie ◽  
Yijun Wu ◽  
Zhile Wang ◽  
Li Wang ◽  
...  
Keyword(s):  
Diffuse Glioma ◽  
Immune Infiltration ◽  
Mutational Burden ◽  
Tumor Mutational Burden

scholarly journals Tumor mutational burden assessment in non-small-cell lung cancer samples: results from the TMB2 harmonization project comparing three NGS panels

2021 ◽  
Vol 9 (5) ◽  
pp. e001904
Author(s):  
Javier Ramos-Paradas ◽  
Susana Hernández-Prieto ◽  
David Lora ◽  
Elena Sanchez ◽  
Aranzazu Rosado ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Predictive Value ◽  
Predictive Biomarker ◽  
Small Cell ◽  
Small Cell Lung ◽  
Mutational Burden ◽  
Reproducibility Study ◽  
Tumor Mutational Burden

BackgroundTumor mutational burden (TMB) is a recently proposed predictive biomarker for immunotherapy in solid tumors, including non-small cell lung cancer (NSCLC). Available assays for TMB determination differ in horizontal coverage, gene content and algorithms, leading to discrepancies in results, impacting patient selection. A harmonization study of TMB assessment with available assays in a cohort of patients with NSCLC is urgently needed.MethodsWe evaluated the TMB assessment obtained with two marketed next generation sequencing panels: TruSight Oncology 500 (TSO500) and Oncomine Tumor Mutation Load (OTML) versus a reference assay (Foundation One, FO) in 96 NSCLC samples. Additionally, we studied the level of agreement among the three methods with respect to PD-L1 expression in tumors, checked the level of different immune infiltrates versus TMB, and performed an inter-laboratory reproducibility study. Finally, adjusted cut-off values were determined.ResultsBoth panels showed strong agreement with FO, with concordance correlation coefficients (CCC) of 0.933 (95% CI 0.908 to 0.959) for TSO500 and 0.881 (95% CI 0.840 to 0.922) for OTML. The corresponding CCCs were 0.951 (TSO500-FO) and 0.919 (OTML-FO) in tumors with <1% of cells expressing PD-L1 (PD-L1<1%; N=55), and 0.861 (TSO500-FO) and 0.722 (OTML-FO) in tumors with PD-L1≥1% (N=41). Inter-laboratory reproducibility analyses showed higher reproducibility with TSO500. No significant differences were found in terms of immune infiltration versus TMB. Adjusted cut-off values corresponding to 10 muts/Mb with FO needed to be lowered to 7.847 muts/Mb (TSO500) and 8.380 muts/Mb (OTML) to ensure a sensitivity >88%. With these cut-offs, the positive predictive value was 78.57% (95% CI 67.82 to 89.32) and the negative predictive value was 87.50% (95% CI 77.25 to 97.75) for TSO500, while for OTML they were 73.33% (95% CI 62.14 to 84.52) and 86.11% (95% CI 74.81 to 97.41), respectively.ConclusionsBoth panels exhibited robust analytical performances for TMB assessment, with stronger concordances in patients with negative PD-L1 expression. TSO500 showed a higher inter-laboratory reproducibility. The cut-offs for each assay were lowered to optimal overlap with FO.

scholarly journals Identification and validation of a miRNA-related expression signature for tumor mutational burden in colorectal cancer

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Lijun Xu ◽  
Qing Zheng
Keyword(s):  
Colorectal Cancer ◽  
Immune Response ◽  
Validation Cohort ◽  
Expression Profiles ◽  
Functional Enrichment ◽  
Immune Checkpoints ◽  
Positive Correlation ◽  
Expression Signature ◽  
Mutational Burden ◽  
Tumor Mutational Burden

Abstract Background Tumor mutational burden (TMB) is a promising predictor, which could stratify colorectal cancer (CRC) patients based on the response to immune checkpoint inhibitors (ICIs). MicroRNAs (miRNAs) act as the key regulators of anti-cancer immune response. However, the relationship between TMB and miRNA expression profiles is not elucidated in CRC. Methods Differentially expressed miRNAs (DE miRNAs) between the TMBhigh group and the TMBlow group were identified for the CRC cohort of the TCGA database. In the training cohort, a miRNA-related expression signature for predicting TMB level was developed by the least absolute shrinkage and selection operator (LASSO) method and tested with reference to its discrimination, calibration, and decision curve analysis (DCA) in the validation cohort. Functional enrichment analysis of these TMB-related miRNAs was performed. The correlation between this miRNA-related expression signature and three immune checkpoints was analyzed. Results Twenty-one out of 43 DE miRNAs were identified as TMB-related miRNAs, which were used to develop a miRNA-related expression signature. This TMB-related miRNA signature demonstrated great discrimination (AUCtest set = 0.970), satisfactory calibration (P > 0.05), and clinical utility in the validation cohort. Functional enrichment results revealed that these TMB-related miRNAs were mainly involved in biological processes associated with immune response and signaling pathways related with cancer. This miRNA-related expression signature showed a median positive correlation with PD-L1 (R = 0.47, P < 0.05) and CTLA4 (R = 0.39, P < 0.05) and a low positive correlation with PD-1 (R = 0.16, P < 0.05). Conclusion This study presents a miRNA-related expression signature which could stratify CRC patients with different TMB levels.

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