scholarly journals Canine tumor mutational burden is correlated with TP53 mutation across tumor types and breeds

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Burair A. Alsaihati ◽  
Kun-Lin Ho ◽  
Joshua Watson ◽  
Yuan Feng ◽  
Tianfang Wang ◽  
...  
Keyword(s):  
Mammary Tumor ◽  
Tumor Type ◽  
Sequencing Data ◽  
Major Pathway ◽  
Oral Melanoma ◽  
Mutational Burden ◽  
Whole Exome ◽  
Tumor Mutational Burden ◽  
Tumor Types ◽  
Canine Tumor

AbstractSpontaneous canine cancers are valuable but relatively understudied and underutilized models. To enhance their usage, we reanalyze whole exome and genome sequencing data published for 684 cases of >7 common tumor types and >35 breeds, with rigorous quality control and breed validation. Our results indicate that canine tumor alteration landscape is tumor type-dependent, but likely breed-independent. Each tumor type harbors major pathway alterations also found in its human counterpart (e.g., PI3K in mammary tumor and p53 in osteosarcoma). Mammary tumor and glioma have lower tumor mutational burden (TMB) (median < 0.5 mutations per Mb), whereas oral melanoma, osteosarcoma and hemangiosarcoma have higher TMB (median ≥ 1 mutations per Mb). Across tumor types and breeds, TMB is associated with mutation of TP53 but not PIK3CA, the most mutated genes. Golden Retrievers harbor a TMB-associated and osteosarcoma-enriched mutation signature. Here, we provide a snapshot of canine mutations across major tumor types and breeds.

Pan-Cancer assessment of tumor mutational burden using a comprehensive genomic profiling assay.

2018 ◽  
Vol 36 (5_suppl) ◽  
pp. 157-157 ◽  
Author(s):  
Donna Nichol ◽  
Siân Jones ◽  
Samuel V. Angiouli ◽  
Laurel Keefer ◽  
Monica Nesselbush ◽  
...  
Keyword(s):  
Microsatellite Instability ◽  
Exome Sequencing ◽  
Whole Exome Sequencing ◽  
Dynamic Range ◽  
Predictive Biomarkers ◽  
Clinical Biomarkers ◽  
Mutational Burden ◽  
Whole Exome ◽  
Tumor Mutational Burden ◽  
Tumor Types

157 Background: Checkpoint inhibitors (CPIs) have been approved for frontline or subsequent therapies in several indications over the last few years. While patient response can be remarkably durable, many patients do not benefit. Current clinical biomarkers of response to CPIs include microsatellite instability (MSI) and PD-L1 expression. While a proportion of many solid tumors display microsatellite instability, the prevalence is often very low. Similarly, while clinically informative, PD-L1 expression alone is not sufficient to predict therapeutic outcomes with high accuracy. The lack of predictive biomarkers for response highlights the need for improved biomarkers with greater prevalence across tumor types to predict response to CPIs. Multiple clinical studies have revealed that high tumor mutational burden (TMB) is associated with improved clinical response. Methods: Here, we describe the development of a method that can be used to accurately infer mutational burden from a discrete set of targeted regions of interest across the exome. Initially, we performed an assessment of the accuracy across multiple bioinformatics methods for identification of individual sequence mutations (SBS/indels) using orthogonally validated data together with publicly available TCGA whole-exome sequencing data. The targeted regions were then isolated from these datasets to demonstrate analytical performance across several different solid tumor types. Finally, we evaluated independent non-small cell lung cancer (NSCLC) and colorectal carcinoma (CRC) cohorts to demonstrate the analytical accuracy of the assay and bioinformatics approach for determination of mutational burden when compared to whole exome sequencing. Results: In summary, high concordance was observed across a large dynamic range of mutations per megabase of coding sequence. Conclusions: Our data indicate that the assay can be used to accurately determine mutational burden in a range of tumor types, across a spectra of potential mutational burden cut-offs using automated, complex mutation identification algorithms.

scholarly journals Analysis of tumor mutational burden: correlation of five large gene panels with whole exome sequencing

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Carina Heydt ◽  
Jan Rehker ◽  
Roberto Pappesch ◽  
Theresa Buhl ◽  
Markus Ball ◽  
...  
Keyword(s):  
Exome Sequencing ◽  
Whole Exome Sequencing ◽  
Large Gene ◽  
Mutational Burden ◽  
Whole Exome ◽  
Tumor Mutational Burden ◽  
Gene Panels

scholarly journals Clinical advantage of targeted sequencing for unbiased tumor mutational burden estimation in samples with low tumor purity

2020 ◽  
Vol 8 (2) ◽  
pp. e001199
Author(s):  
Tae Hee Hong ◽  
Hongui Cha ◽  
Joon Ho Shim ◽  
Boram Lee ◽  
Jongsuk Chung ◽  
...  
Keyword(s):  
Exome Sequencing ◽  
Whole Exome Sequencing ◽  
Predictive Ability ◽  
Progression Free Survival ◽  
Superior Performance ◽  
Enhanced Sensitivity ◽  
Mutational Burden ◽  
Tumor Purity ◽  
Whole Exome ◽  
Tumor Mutational Burden

BackgroundTumor mutational burden (TMB) measurement is limited by low tumor purity of samples, which can influence prediction of the immunotherapy response, particularly when using whole-exome sequencing-based TMB (wTMB). This issue could be overcome by targeted panel sequencing-based TMB (pTMB) with higher depth of coverage, which remains unexplored.MethodsWe comprehensively reanalyzed four public datasets of immune checkpoint inhibitor (ICI)-treated cohorts (adopting pTMB or wTMB) to test each biomarker’s predictive ability for low purity samples (cut-off: 30%). For validation, paired genomic profiling with the same tumor specimens was performed to directly compare wTMB and pTMB in patients with breast cancer (paired-BRCA, n=165) and ICI-treated patients with advanced non-small-cell lung cancer (paired-NSCLC, n=156).ResultsLow tumor purity was common (range 30%–45%) in real-world samples from ICI-treated patients. In the survival analyzes of public cohorts, wTMB could not predict the clinical benefit of immunotherapy when tumor purity was low (log-rank p=0.874), whereas pTMB could effectively stratify the survival outcome (log-rank p=0.020). In the paired-BRCA and paired-NSCLC cohorts, pTMB was less affected by tumor purity, with significantly more somatic variants identified at low allele frequency (p<0.001). We found that wTMB was significantly underestimated in low purity samples with a large proportion of clonal variants undetected by whole-exome sequencing. Interestingly, pTMB more accurately predicted progression-free survival (PFS) after immunotherapy than wTMB owing to its superior performance in the low tumor purity subgroup (p=0.054 vs p=0.358). Multivariate analysis revealed pTMB (p=0.016), but not wTMB (p=0.32), as an independent predictor of PFS even in low-purity samples. The net reclassification index using pTMB was 21.7% in the low-purity subgroup (p=0.016).ConclusionsOur data suggest that TMB characterization with targeted deep sequencing might have potential strength in predicting ICI responsiveness due to its enhanced sensitivity for hard-to-detect variants at low-allele fraction. Therefore, pTMB could act as an invaluable biomarker in the setting of both clinical trials and practice outside of trials based on its reliable performance in mitigating the purity-related bias.

Abstract 3404: Landscape and genomic correlates of ctDNA-based tumor mutational burden across six solid tumor types

2019 ◽  
Author(s):  
Katie Quinn ◽  
Elena Helman ◽  
Tracy Nance ◽  
Jennifer Yen ◽  
John Latham ◽  
...  
Keyword(s):  
Solid Tumor ◽  
Mutational Burden ◽  
Tumor Mutational Burden ◽  
Tumor Types

Adenocarcinoma (ACB), urothelial carcinoma (UCB) and squamous cell carcinoma (SCCB) of the bladder: A Comprehensive Genomic Profiling (CGP) Study.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. 4533-4533 ◽  
Author(s):  
Joseph Jacob ◽  
Gennady Bratslavsky ◽  
Oleg Shapiro ◽  
Nick Liu ◽  
Elizabeth Kate Ferry ◽  
...  
Keyword(s):  
High Status ◽  
Genomic Profiling ◽  
Dna Repair Genes ◽  
Genomic Profile ◽  
Hybrid Capture ◽  
Mutational Burden ◽  
Comprehensive Genomic Profiling ◽  
Tumor Mutational Burden ◽  
Tumor Types ◽  
Repair Genes

4533 Background: We performed a CGP to compare the genomic alterations (GA) in ABC, UBC and SCCB. Methods: 143 cases of ACB, 2,142 cases of UCB and 83 cases of SCCB were subjected to CGP using a hybrid-capture based assay. Tumor mutational burden (TMB) was determined on 1.1 Mbp of sequenced DNA and microsatellite instability (MSI) was determined on 114 loci. PD-L1 expression was determined by IHC. Results: ABC patients were younger and more often female than UBC and SCCB (P < 0.0001). UBC and SCCB had a higher GA/tumor than ABC (P = 0.01). Un-targetable GA were similar in all 3 groups involving TP53 and KRAS. APC GA were more frequent in ABC whereas TERT, CDKN2A/B and DNA-repair genes ( ARID1A and KDM6A) more frequently altered in UBC and SCCB. Targetable MTOR pathway GA ( PIK3CA, TSC1, PTEN) were more frequent in UBC and SCCB as were targetable kinase alterations ( FGFR3 and ERBB2). The UBC and SCCB had a significantly higher TMB than ABC (P < 0.0001) including mean TMB and TMB > 20 mut/Mb (P < 0.0001). CD274 (PD-L1) was amplified more frequently in SCCB than ACB or UBC (P < 0.0001). MSI high status was very uncommon in all tumor types. Conclusions: Deep sequencing reveals that ABC features a widely different genomic profile from UBC and SCCB. UBC has the highest frequencies of targetable kinase GA and high TMB. SCCB has the highest frequencies of IO efficacy predicting biomarkers including mean TMB and PD-L1 amp. Nonetheless, ABC does feature potential kinase targets such as FGFR3 and ERBB2. [Table: see text]

Notch family gene mutations associate with high tumor mutational burden in diverse cancers.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e14616-e14616
Author(s):  
Da Jiang ◽  
Zhaojian Niu ◽  
Jianli Zhang ◽  
Yanlei Wang ◽  
Liang Shang ◽  
...  
Keyword(s):  
Notch Pathway ◽  
Underlying Mechanism ◽  
Base Substitution ◽  
Tumor Type ◽  
Cancer Genes ◽  
Multiple Cancer ◽  
Mutational Burden ◽  
Tumor Mutational Burden ◽  
Family Gene ◽  
Mutation Type

e14616 Background: The Notch pathway has an important role in tumorigenesis in many types of cancer. Clinical trials with Notch inhibitors are ongoing. Recently, Notch pathway has been reported to be part of tumor immunity and patients with NOTCH1 mutations (mut) showed better outcome to PD-1 inhibitors, however, the underlying mechanism is unknown. Methods: Next generation sequencing (NGS) panel of 450 cancer genes was performed on FFPE tissue and matched blood samples from 1341 solid tumors, including hepatocellular carcinoma (HCC, n = 644), esophageal carcinoma (EC, n = 255), breast cancer (BC, n = 175), small cell lung cancer (SCLC, n = 141), head and neck cancer (HNC, n = 77). Notch family gene (NOTCH1/2/3/4) muts were analyzed. Genomic alterations including single base substitution, short and long insertions/deletion, copy number variation, gene fusion and rearrangement were assessed. Tumor mutational burden (TMB) was calculated in all patients by NGS algorithms. TMB high (TMB-H) was defined as TMB values ≥75% tumors in each tumor type. Results: For all patients, Notch family gene mut (substitution/indel/truncation) were found in 27% EC, 19% SCLC, 12% HNC, 6% BC and 5% HCC. The median TMB was 6.1 muts/Mb. In general, tumors with Notch family gene mut had significantly higher median TMB in pan-cancer cohort when compared with tumors without Notch family gene mut (9.2 vs. 6.1 muts/Mb, p < 0.001). Specifically, tumors with NOTCH1 mut had higher TMB in HCC (8.5 vs 5.5, p = 0.034), in BC (23.2 vs. 4.6, p = 0.006) and in SCLC (14.0 vs. 9.4, p = 0.002), while NOTCH2 mutant tumors presented higher TMB in HCC (18.5 vs. 5.5, p = 0.026), in EC (14.7 vs. 6.9, p = 0.001) and in SCLC (13.2 vs. 4.6, p = 0.026). We found 65% of NOTCH1 mut were located in epidermal growth factor (EGF)-like repeats domain. Classes of the NOTCH1 mutation type were substitution/indel (non-frameshift) (58%) and truncation (42%), while NOTCH2 mut were 88% and 12%. In TMB-H tumors, substitution/indel is the predominant mutation type of Notch family gene (NOTCH1 61%, NOTCH2 100%). Conclusions: Tumors with Notch family gene mut presented higher TMB in multiple cancer types, indicating a potential strategy for targeted and immunotherapy in NOTCH mutant cancers.

Tumor mutational burden reference materials for assay standardization.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e14746-e14746
Author(s):  
Matt Butler ◽  
Yves Konigshofer ◽  
Omoshile Clement ◽  
Li Liu ◽  
Chen Zhao ◽  
...  
Keyword(s):  
Cell Line ◽  
Cell Lines ◽  
Reference Materials ◽  
Large Scale ◽  
Ground Truth ◽  
Consensus Method ◽  
Mutational Burden ◽  
Whole Exome ◽  
Tumor Mutational Burden ◽  
Genomic Aberrations

e14746 Background: Next Generation Sequencing based assays are designed to detect genomic aberrations in a limited number of target regions. However, there is a need for accurate measurement of tumor mutational burden (TMB) as low as 4 to as high as 50. As TMB assessment is added to various targeted panels, consistent results between panels are required to advance the broad use of this biomarker. Properly designed reference materials aid measurement standardization and are required to demonstrate assay concordance. We developed reference materials that vary in TMB score, tumor content 5-50% and are prepared in FFPE format. Methods: Seven lung and two breast tumor cell lines as well as matched “normal” lymphoblastoid cell lines were expanded in cell culture. Genomic DNA (gDNA) from each cell line was extracted. Tumor/normal mixes were made by mixing DNA and by embedding cells in FFPE blocks. Whole exome sequencing (WES) results were obtained using Agilent SureSelectXT for library construction and an Illumina Novaseq for sequencing. The Friends of Cancer Research TMB consensus method for analyzing WES data was used to filter variants and calculate TMB scores. Results: The cell lines were grown at large scale to produce extractable gDNA. 100% gDNA tumor, 30% gDNA tumor mixes and 30% FFPE cell line mixes were prepared. Preliminary results show that a clinically-relevant range of TMB values ranging from 4 to 35 mutations per million bases. The several thousand mutations that were observed across the lines were found in a variety of genes, which may explain why TMB in targeted panels is influenced by the specific target regions. Also, the initial results show that 30% cell line mixes showed similar TMB results to 100% gDNA. Conclusions: Our approach with wide ranging TMB values as tumor normal mixes is flexible and can be used to test different tumors and assays. For this study we established WES as the ground truth measurement for comparison to other assay formats and obtained comparison data from other panels. This approach also allows laboratories to test additional variables including formalin fixation, sample extraction, gene panel size, target regions, sequencing depth, filtering and limits of detection.

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