EcTMB: a robust method to estimate and classify tumor mutational burden.
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ABSTRACT:
SUBMITTER: Yao L
PROVIDER: S-EPMC7080796 | biostudies-literature | 2020 Mar
REPOSITORIES: biostudies-literature
Publications
ecTMB: a robust method to estimate and classify tumor mutational burden.
Yao Lijing L Fu Yao Y Mohiyuddin Marghoob M Lam Hugo Y K HYK
Scientific reports 20200318 1
Tumor Mutational Burden (TMB) is a measure of the abundance of somatic mutations in a tumor, which has been shown to be an emerging biomarker for both anti-PD-(L)1 treatment and prognosis; however, multiple challenges still hinder the adoption of TMB as a biomarker. The key challenges are the inconsistency of tumor mutational burden measurement among assays and the lack of a meaningful threshold for TMB classification. Here we describe a new method, ecTMB (Estimation and Classification of TMB), ...[more]
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Project description:The clinical applicability of the whole-exome sequencing (WES) in estimating tumor mutational burden (TMB) is currently limited by high cost, time-consuming and tissue availability. And given to the differences in the mutational landscapes among different types of cancer, we aimed to develop a cancer-specific signature to estimate TMB for right-sided colon cancer patients (RCC). Using WES data of 315 RCC patients, we identified the exons in which the number of mutational sites of the coding DNA sequences associated with TMB through linear regression analysis. Then, among these exons, we extracted a signature composed by 102 exons (~0.13 Mbp) through a heuristic selection procedure. The TMB estimated by the signature was highly correlated with those calculated by WES in the discovery dataset (R2=0.9869) and three independent validation datasets (R2=0.9351, R2=0.8063 and R2=0.9527, respectively). And the performance of the signature was superior to a colorectal-specific TMB estimation model contained 22 genes (~0.24 Mbp). Moreover, between TMB-high and TMB-low RCC patients, there were significantly differences in the frequencies of microsatellite instability status, CpG island methylator phenotype, BRAF, KRAS and POLE/POLD1 mutation status (p<0.01). However, the performances of the signature in other types of cancer were dramatically degraded (left-sided colon cancer, R2=0.7849 and 0.9407, respectively; rectum, R2=0.5955 and R2=0.965, respectively; breast cancer, R2=0.8444; lung cancer, R2=0.5963), suggesting that it was necessary to develop cancer-specific TMB estimated signatures to estimate precisely the TMB in different types of cancer. In summary, we developed an exon signature that can accurately estimate TMB in RCC patients, and the cost and time required for the assessment of TMB can be considerably decreased, making it more suitable for blood and/or biopsy samples.
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Project description:Immunotherapy has become one of the most promising therapy methods for cancer, but only a small number of patients are responsive to it, indicating that more effective biomarkers are urgently needed. This study developed a pathway analysis method, named PathwayTMB, to identify genomic mutation pathways that serve as potential biomarkers for predicting the clinical outcome of immunotherapy. PathwayTMB first calculates the patient-specific pathway-based tumor mutational burden (PTMB) to reflect the cumulative extent of mutations for each pathway. It then screens mutated survival benefit-related pathways to construct an immune-related prognostic signature based on PTMB (IPSP). In a melanoma training set, IPSP-high patients presented a longer overall survival and a higher response rate than IPSP-low patients. Moreover, the IPSP showed a superior predictive effect compared with TMB. In addition, the prognostic and predictive value of the IPSP was consistently validated in two independent validation sets. Finally, in a multi-cancer dataset, PathwayTMB also exhibited good performance. Our results indicate that PathwayTMB could identify the mutation pathways for predicting immunotherapeutic survival, and their combination may serve as a potential predictive biomarker for immune checkpoint inhibitor therapy.
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Project description:The treatment of patients with a variety of solid tumors has benefitted from immune checkpoint inhibition targeting the anti-programmed cell death-1 (PD-1)/programmed cell death ligand-1 (PD-L1) axis. The US Food and Drug Administration (FDA) granted accelerated approval of PD-1 inhibitor pembrolizumab for the treatment of adult and pediatric patients with TMB-high (TMB-H), solid tumors that have progressed following prior treatment and who have no other treatment options, including the extension to tumors of the Central Nervous System (CNS). In general, pan-cancer approvals are viewed positively to empower patients and clinicians. There are subsets (eg, BRAF, NTRK) for which this pathway for approval is appropriate. However, the pan-cancer FDA approval of pembrolizumab raises several concerns regarding the generalizability of the evidence to other tumor types, including managing patients with gliomas and other CNS tumors. The cut off for TMB-H is not well defined. There are intrinsic immunological differences between gliomas and other cancers types, including the immunosuppressive glioma microenvironment, the tumor's effects on systemic immune function, and the transformation of the T cell populations to an exhausted phenotype in glioma. Here we address the caveats with pan-cancer approvals concerning gliomas, complexities of the unique CNS immune environment, and discuss potential predictive biomarkers, including TMB, and explain why the recent approval should be applied with caution in CNS tumors.
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Project description:Accurate estimation of systemic tumor load from the blood of cancer patients has enormous potential. One avenue is to measure the presence of cell-free circulating tumor DNA in plasma. Various approaches have been investigated, predominantly covering hotspot mutations or customized, patient-specific assays. Therefore, we investigated the utility of using exome sequencing to monitor circulating tumor DNA levels through the detection of single nucleotide variants in plasma. Two technologies, claiming to offer efficient library preparation from nanogram levels of DNA, were evaluated. This allowed us to estimate the proportion of starting molecules measurable by sequence capture (<5%). As cell-free DNA is highly fragmented, we designed and provide software for efficient identification of PCR duplicates in single-end libraries with a varying size distribution. On average, this improved sequence coverage by 38% in comparison to standard tools. By exploiting the redundant information in PCR-duplicates the background noise was reduced to ?1/35,000. By applying our optimized analysis pipeline to a simulation analysis, we determined the current sensitivity limit to ?1/2400, starting with 30 ng of cell-free DNA. Subsequently, circulating tumor DNA levels were assessed in seven breast- and one prostate cancer patient. One patient carried detectable levels of circulating tumor DNA, as verified by break-point specific PCR. These results demonstrate exome sequencing on cell-free DNA to be a powerful tool for disease monitoring of metastatic cancers. To enable a broad implementation in the diagnostic settings, the efficiency limitations of sequence capture and the inherent noise levels of the Illumina sequencing technology must be further improved.
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Project description:BackgroundOsteosarcoma (OTS) is aggressive bone malignancy without well-recognized prognosis biomarker. Tumor mutational burden (TMB) has been proved as effective biomarker in predicting clinical outcomes in several cancer types. However, its prognostic value in OTS remains unknown. In this study, we aim to evaluate the implication of TMB in OTS patients.MethodsTo depict the landscape of somatic mutations in OTS, we performed Whole-Exome Sequencing (WES) on 31 OTS tissue samples and corresponding White Blood Cells (WBCs) as matched control. TMB was calculated as the total number of somatic alterations in coding regions normalized to the per sequenced genomic megabase (~30.4Mb in WES). The prognostic values of TMB were evaluated by Kaplan-Meier methods and Cox regression models.ResultsThe median age was 16.0 years at diagnosis, and 54.8% of patients were male. The most common genetic alterations were mainly involved in cell cycle and DNA damage response and repair, including H3F3A, TP53, MYC, and CDKN2A/B. The median progression-free survival (PFS) was 775.5 days in TMB-High (defined as third quartile of TMB value, <2.565) versus 351 days in TMB-Low (<2.565). All patients with TMB-High are PFS-Long (>400 days), while 36.4% of all patients with TMB-Low were PFS-Long (P=0.003). TMB were significantly greater in PFS-Long than in PFS-Short (<400 days) (P=0.002). Moreover, the median overall survival (OS) was 1,307 days in TMB-High versus 672.5 days in TMB-Low. Furthermore, TMB-High group had significantly improved PFS (P=0.04) and OS (P=0.03).ConclusionsTMB-High can be used as prognostic marker for OTS. Our findings demonstrate that TMB may be helpful in combination with traditionally clinicopathologic risk factors to optimize risk stratification and guide treatment decisions.
| S-EPMC8059407 | biostudies-literature
Project description:Whether tumor mutational burden (TMB) is related to improved survival outcomes or the promotion of immunotherapy in various malignant tumors remains controversial, and we lack a comprehensive understanding of TMB across cancers. Based on the data obtained from The Cancer Genome Atlas (TCGA), we conducted a multiomics analysis of TMB across 21 cancer types to identify characteristics related to TMB and determine the mechanism as it relates to prognosis, gene expression, gene mutation and signaling pathways. In our study, TMB was found to have a significant relationship with prognosis for 21 tumors, and the relationship was different in different tumors. TMB may also be related to different outcomes for patients with different tumor subtypes. TMB was confirmed to be correlated with clinical information, such as age and sex. Mutations in GATA3 and MAP3K1 in beast invasive carcinoma (BRCA), TCF7L2 in colon adenocarcinoma (COAD), NFE2L2 in esophageal carcinoma (ESCA), CIC and IDH1 in brain lower grade glioma (LGG), CDH1 in stomach adenocarcinoma (STAD), and TP53 in uterine corpus endometrial carcinoma (UCEC) were demonstrated to be correlated with lower TMB. Moreover, we identified differentially expressed genes (DEGs) and differentially methylated regions (DMRs) according to different TMB levels in 21 cancers. We also investigated the correlation between enrichment of signaling pathways, immune cell infiltration and TMB. In conclusion, we identified multiomic characteristics related to the TMB in 21 tumors, providing support for a comprehensive understanding of the role of TMB in different tumors.
| S-EPMC8531462 | biostudies-literature