Beyond finding druggable targets and tumor mutational burden: to measure heterogeneity by ctDNA.
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ABSTRACT:
SUBMITTER: Liu Z
PROVIDER: S-EPMC7327335 | biostudies-literature | 2020 Jun
REPOSITORIES: biostudies-literature
Publications
Beyond finding druggable targets and tumor mutational burden: to measure heterogeneity by ctDNA.
Liu Zhichao Z He Jianxing J Liang Wenhua W
Annals of translational medicine 20200601 11
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Project description:BackgroundThe tumor mutational burden (TMB) is a genomic biomarker associated with the benefits from immune checkpoint inhibitors (ICIs) cancer therapy. An elevated blood TMB (bTMB) in circulating tumor DNA (ctDNA) represents a compelling non-invasive diagnostic approach; however, the validity and utility of this emerging biomarker across cancer types have not been examined.Patient and methodsThe blood and tissue TMB was measured in a large pan-tumor clinical cohort and the MONSTAR-SCREEN observational study (UMIN000036749) using the FoundationOne Liquid CDx and FoundationOne CDx assays. A subset of the MONSTAR-SCREEN cohort was used to evaluate the association between the bTMB and the efficacy of ICIs therapy.ResultsThe majority of cancer types showed similar prevalence of TMB≥10 mutations/megabase and bTMB≥10. There was high concordance between bTMB and TMB in blood and tissue biopsy from the same patient when the plasma tumor fraction (TF) was at least 1% (Spearman's coefficient 0.74 and > 80% sensitivity to detect TMB-high). High microsatellite instability (MSI-H) was detected by ctDNA with 79% sensitivity when TF was at least 1%, but only 6% sensitivity when TF was <1%. Among patients with bTMB≥14 and elevated TF≥10% treated with ICIs, there was a trend toward a longer progression-free survival and overall survival compared with patients with bTMB<14 and elevated TF≥10% (HR, 0.62 [95%CI, 0.39-0.98]; p = 0.04 and HR, 0.60 [95%CI, 0.34-1.1]; p = 0.05).ConclusionsOur findings suggest that an elevated bTMB is correlated with elevated TMB and represents a pragmatic biomarker for assessing ICIs benefits. The utility of this biomarker is likely to be associated with high TF levels, informing future prospective investigations.
| S-EPMC11863975 | biostudies-literature
Project description:BackgroundHigh tumor mutational burden (TMB) is one of the widely researched predictive biomarkers of immune checkpoint inhibitors and has been shown to be closely related with response to immunotherapy in multiple cancer types. However, for patients who have failed conventional therapy and are about to undergo immunotherapy, there is no consensus recommendation on the timing of tumor sampling for TMB analysis, and the effects of different therapies on TMB have not been clarified. This retrospective observational study aimed to investigate the heterogeneity of TMB and genomic mutation under the treatment pressure.Patients and methodsWe retrospectively collected the available genomic and therapeutic information from 8051 samples across 15 tumor types (>50 samples/tumor) found in 30 published studies and investigated the distribution and heterogeneity of TMB under treatment across diverse cohorts.ResultsThis integrated analysis has shown anticancer treatments increased TMB. Significant effects of treatment on TMB were more frequently observed in tumor types with lower treatment-naïve TMB, including breast, prostate, and pediatric cancers. For different cancer therapies, chemotherapy was prone to be correlated with an increased TMB in most cancer types. Meanwhile, the fraction of the TMB-high category of breast, prostate, and bladder cancers and glioma increased significantly after chemotherapy. Several actionable genes including ERS1 and NF1 in breast cancer, as well as some prognostic markers including TERT in bladder cancer and IDH1 in glioma, were significantly changed in post-chemotherapy tumors compared to treatment-naïve tumors.ConclusionOur study reveals the heterogeneity of TMB under treatment across diverse cancer types and provides evidences that chemotherapy was associated with increases in TMB as well as the fraction of TMB-high category, suggesting that resampling tumor tissues for calculating post-chemotherapy TMB could be a better option for predicting the response to immunotherapy, especially for tumors with initially low TMB.
| S-EPMC11292426 | biostudies-literature
Project description:The tumor mutational burden (TMB) has been reported as a predictive marker of the response to immune checkpoint inhibition (ICI) therapy in previous melanoma clinical trials. However, the TMB alone is not sufficient to accurately predict immunotherapy benefit. Additional biomarkers are needed for better stratification of immunotherapy-sensitive patients. In the present study, mutation data and survival information of patients with melanoma were collected from several immunotherapy studies, and tumor heterogeneity was estimated using mutant-allele tumor heterogeneity (MATH). The benefit score was defined as the ratio between the TMB and tumor heterogeneity, and optimal critical values were selected to group patients and evaluate their response to ICI treatment. The benefit score significantly improved the performance of stratifying the overall survival of patients compared with the TMB alone as a predictor in two independent cohorts (p = 0.0068 vs. p = 0.1 and p = 0.045 vs. p = 0.13), in which patients were treated with Ipilimumab and Nivolumab, respectively. In another cohort of patients with melanoma receiving mixed ICI treatment, the benefit score was also positively associated with higher overall survival (p = 0.022) and outperformed the TMB alone, with a significance of p = 0.089. The benefit score showed a positive correlation with clonal TMB, a reported immunotherapy marker, and exceeded it in immunotherapy response prediction. Besides, a high benefit score was found to be associated with higher proportions of natural killer cells, lower proportions of M2 macrophages and elevated CD8 T cells, all of which favor ICI therapy. In summary, tumor heterogeneity combined with the TMB showed superior efficacy in predicting the response to ICI therapy. This might further help to delineate the mechanisms of immunotherapy in patients with melanoma.
| S-EPMC7661856 | biostudies-literature
Project description:Harnessing the immune system by checkpoint blockade has greatly expanded the therapeutic options for advanced cancer. Since the efficacy of immunotherapies is influenced by the molecular make-up of the tumor and its crosstalk with the immune system, comprehensive analysis of genetic and immunologic tumor characteristics is essential to gain insight into mechanisms of therapy response and resistance. We investigated the association of immune cell contexture and tumor genetics including tumor mutational burden (TMB), copy number alteration (CNA) load, mutant allele heterogeneity (MATH) and specific mutational signatures (MutSigs) using TCGA data of 5722 tumor samples from 21 cancer types. Among all genetic variables, MutSigs associated with DNA repair deficiency and AID/APOBEC gene activity showed the strongest positive correlations with immune parameters. For smoking-related and UV-light-exposure associated MutSigs a few positive correlations were identified, while MutSig 1 (clock-like process) correlated non-significantly or negatively with the major immune parameters in most cancer types. High TMB was associated with high immune cell infiltrates in some but not all cancer types, in contrast, high CNA load and high MATH were mostly associated with low immune cell infiltrates. While a bi- or multimodal distribution of TMB was observed in colorectal, stomach and endometrial cancer where its levels were associated with POLE/POLD1 mutations and MSI status, TMB was unimodal distributed in the most other cancer types including NSCLC and melanoma. In summary, this study uncovered specific genetic-immunology associations in major cancer types and suggests that mutational signatures should be further investigated as interesting candidates for response prediction beyond TMB.
| S-EPMC6279340 | biostudies-literature
Project description:BackgroundGerm cell tumors (GCT) might undergo transformation into a somatic-type malignancy (STM), resulting in a cell fate switch to tumors usually found in somatic tissues, such as rhabdomyosarcomas or adenocarcinomas. STM is associated with a poor prognosis, but the molecular and epigenetic mechanisms triggering STM are still enigmatic, the tissue-of-origin is under debate and biomarkers are lacking.MethodsTo address these questions, we characterized a unique cohort of STM tissues on mutational, epigenetic and protein level using modern and high-throughput methods like TSO assays, 850k DNA methylation arrays and mass spectrometry.Results and conclusionsFor the first time, we show that based on DNA methylation and proteome data carcinoma-related STM more closely resemble yolk-sac tumors, while sarcoma-related STM resemble teratoma. STM harbor mutations in FGF signaling factors (FGF6/23, FGFR1/4) highlighting the corresponding pathway as a therapeutic target. Furthermore, STM utilize signaling pathways, like AKT, FGF, MAPK, and WNT to mediate molecular functions coping with oxidative stress, toxin transport, DNA helicase activity, apoptosis and the cell cycle. Collectively, these data might explain the high therapy resistance of STM. Finally, we identified putative novel biomarkers secreted by STM, like EFEMP1, MIF, and DNA methylation at specific CpG dinucleotides.
| S-EPMC10645790 | biostudies-literature
Project description:The role of tumor mutational burden (TMB) in shaping tumor immunity is a key question that has not been addressable using genetically engineered mouse models (GEMMs) of lung cancer. To induce TMB in lung GEMMs, we expressed an ultra-mutator variant of DNA polymerase-E (POLE)P286R in lung epithelial cells. Introduction of PoleP286R allele into KrasG12D and KrasG12D; p53L/L (KP) models significantly increase their TMB. Immunogenicity and sensitivity to immune checkpoint blockade (ICB) induced by Pole is partially dependent on p53. Corroborating these observations, survival of NSCLC patients whose tumors have TP53truncating mutations is shorter than those with TP53WT with immunotherapy. Immune resistance is in part through reduced antigen presentation and in part due to mutational heterogeneity. Total STING protein levels are elevated in Pole mutated KP tumors creating a vulnerability. A stable polyvalent STING agonist or p53 induction increases sensitivity to immunotherapy offering therapeutic options in these polyclonal tumors.
| S-EPMC10693909 | biostudies-literature
Project description:ObjectiveTo identify and validate causal protein targets that may serve as potential therapeutic interventions for both the onset and progression of Parkinson's disease (PD) through integrative proteomic and genetic analyses.MethodWe utilized large-scale plasma and brain protein quantitative trait loci (pQTL) datasets from the deCODE Health study and the Religious Orders Study/Rush Memory and Aging Project (ROS/MAP), respectively. Proteome-wide association studies (PWAS) were conducted using the OTTERS framework for plasma proteins and the FUSION tool for brain proteins, examining associations with PD onset and three progression phenotypes: composite, motor, and cognitive. Significant protein associations (FDR-corrected p < 0.05) from PWAS were further validated using summary-based Mendelian randomization (SMR), colocalization analyses, and reverse Mendelian randomization (MR) to establish causality. Phenome-wide Mendelian randomization (PheW-MR) was performed to assess potential side effects across 679 disease traits when targeting these proteins to reduce PD-related phenotype risk by 20%. Additionally, we conducted cellular distribution-based clustering using gene expression data from the Allen Brain Atlas (ABA) to explore the distribution of key proteins across brain regions, constructed protein-protein interaction (PPI) networks via the STRING database to explore interactions among proteins, and evaluated the druggability of identified targets using the DrugBank database to identify opportunities for drug repurposing.ResultOur analyses identified 25 candidate proteins associated with PD phenotypes, including 16 plasma proteins linked to PD progression (10 cognitive, 4 motor, and 3 composite) and 9 plasma proteins associated with PD onset. Notably, GPNMB was implicated in both plasma and brain tissues for PD onset. PheW-MR revealed predominantly beneficial side effects for the identified targets, with 83.7% of associations indicating positive outcomes and 16.3% indicating adverse effects. Cellular clustering categorized candidate targets into three distinct expression profiles across brain cell types using ABA. PPI network analysis highlighted one key interaction cluster among the proteins for PD cognitive progression and PD onset. Druggability assessment revealed 15 out of 25 proteins had repurposing opportunities for PD treatment.ConclusionWe have identified 25 causal protein targets associated with the onset and progression of PD, providing new insights into the research and development of treatment strategies for PD.
| S-EPMC11862824 | biostudies-literature
Project description:Parkinson's disease is a neurodegenerative movement disorder that currently has no disease-modifying treatment, partly owing to inefficiencies in drug target identification and validation. We use Mendelian randomization to investigate over 3,000 genes that encode druggable proteins and predict their efficacy as drug targets for Parkinson's disease. We use expression and protein quantitative trait loci to mimic exposure to medications, and we examine the causal effect on Parkinson's disease risk (in two large cohorts), age at onset and progression. We propose 23 drug-targeting mechanisms for Parkinson's disease, including four possible drug repurposing opportunities and two drugs which may increase Parkinson's disease risk. Of these, we put forward six drug targets with the strongest Mendelian randomization evidence. There is remarkably little overlap between our drug targets to reduce Parkinson's disease risk versus progression, suggesting different molecular mechanisms. Drugs with genetic support are considerably more likely to succeed in clinical trials, and we provide compelling genetic evidence and an analysis pipeline to prioritise Parkinson's disease drug development.
| S-EPMC8688480 | biostudies-literature
Project description:Although hepatoblastoma is the most common pediatric liver cancer, its genetic heterogeneity and therapeutic targets are not well elucidated. Therefore, we conducted a multiomics analysis, including mutatome, DNA methylome, and transcriptome analyses, of 59 hepatoblastoma samples. Based on DNA methylation patterns, hepatoblastoma was classified into three clusters exhibiting remarkable correlation with clinical, histological, and genetic features. Cluster F was largely composed of cases with fetal histology and good outcomes, whereas clusters E1 and E2 corresponded primarily to embryonal/combined histology and poor outcomes. E1 and E2, albeit distinguishable by different patient age distributions, were genetically characterized by hypermethylation of the HNF4A/CEBPA-binding regions, fetal liver-like expression patterns, upregulation of the cell cycle pathway, and overexpression of NQO1 and ODC1. Inhibition of NQO1 and ODC1 in hepatoblastoma cells induced chemosensitization and growth suppression, respectively. Our results provide a comprehensive description of the molecular basis of hepatoblastoma and rational therapeutic strategies for high-risk cases.
| S-EPMC7341754 | biostudies-literature
Project description:Characterization of tumors utilizing next-generation sequencing methods, including assessment of the number of somatic mutations (tumor mutational burden [TMB]), is currently at the forefront of the field of personalized medicine. Recent clinical studies have associated high TMB with improved patient response rates and survival benefit from immune checkpoint inhibitors; hence, TMB is emerging as a biomarker of response for these immunotherapy agents. However, variability in current methods for TMB estimation and reporting is evident, demonstrating a need for standardization and harmonization of TMB assessment methodology across assays and centers. Two uniquely placed organizations, Friends of Cancer Research (Friends) and the Quality Assurance Initiative Pathology (QuIP), have collaborated to coordinate efforts for international multistakeholder initiatives to address this need. Friends and QuIP, who have partnered with several academic centers, pharmaceutical organizations, and diagnostic companies, have adopted complementary, multidisciplinary approaches toward the goal of proposing evidence-based recommendations for achieving consistent TMB estimation and reporting in clinical samples across assays and centers. Many factors influence TMB assessment, including preanalytical factors, choice of assay, and methods of reporting. Preliminary analyses highlight the importance of targeted gene panel size and composition, and bioinformatic parameters for reliable TMB estimation. Herein, Friends and QuIP propose recommendations toward consistent TMB estimation and reporting methods in clinical samples across assays and centers. These recommendations should be followed to minimize variability in TMB estimation and reporting, which will ensure reliable and reproducible identification of patients who are likely to benefit from immune checkpoint inhibitors.
| S-EPMC6618007 | biostudies-literature