Canine tumor mutation rate is positively correlated with TP53 mutation across cancer types and breeds

2020 ◽  
Author(s):  
Burair A. Alsaihati ◽  
Kun-Lin Ho ◽  
Joshua Watson ◽  
Yuan Feng ◽  
Tianfang Wang ◽  
...  
Keyword(s):  
Mutation Rate ◽  
Mammary Cancer ◽  
Mutation Rates ◽  
Cancer Type ◽  
Sequencing Data ◽  
Major Pathway ◽  
Molecular Features ◽  
Oral Melanoma ◽  
Whole Exome Sequencing Data ◽  
Cancer Types

AbstractSpontaneous canine cancers are a valuable but relatively understudied and underutilized model in cancer research. To enhance their usage, we reanalyzed whole exome sequencing data published for 601 dogs with mammary cancer, osteosarcoma, oral melanoma, lymphoma, glioma or hemangiosarcoma from over 35 breeds, after rigorous quality control, including breed validation. Each cancer type harbors distinct molecular features, with major pathway alterations matching its human counterpart (e.g., PI3K for mammary cancer and p53 for osteosarcoma). On average, mammary cancer and glioma have lower mutation rates (median <0.5 mutation per Mb), whereas oral melanoma, osteosarcoma and hemangiosarcoma have higher mutation rates (median ≥1 mutation per Mb). Across cancer types and across breeds, the mutation rate is strongly associated with TP53 mutation, but not with PIK3CA mutation. The mutation rate is also associated with a mutation signature enriched in osteosarcoma of Golden Retrievers, independent of TP53 mutation. Finally, compared to other breeds examined, DNA repair genes appear to be less conserved in Golden Retriever which is predisposed to numerous cancers.

scholarly journals Integrated molecular characterisation of endometrioid ovarian carcinoma identifies opportunities for stratification

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Robert L. Hollis ◽  
Barbara Stanley ◽  
John P. Thomson ◽  
Michael Churchman ◽  
Ian Croy ◽  
...  
Keyword(s):  
High Risk ◽  
Ovarian Carcinoma ◽  
Expression Patterns ◽  
Parp Inhibitors ◽  
Receptor Expression ◽  
Cancer Type ◽  
Sequencing Data ◽  
Molecular Features ◽  
Endometrioid Ovarian Carcinoma ◽  
Molecular Landscape

AbstractEndometrioid ovarian carcinoma (EnOC) is an under-investigated ovarian cancer type. Recent studies have described disease subtypes defined by genomics and hormone receptor expression patterns; here, we determine the relationship between these subtyping layers to define the molecular landscape of EnOC with high granularity and identify therapeutic vulnerabilities in high-risk cases. Whole exome sequencing data were integrated with progesterone and oestrogen receptor (PR and ER) expression-defined subtypes in 90 EnOC cases following robust pathological assessment, revealing dominant clinical and molecular features in the resulting integrated subtypes. We demonstrate significant correlation between subtyping approaches: PR-high (PR + /ER + , PR + /ER−) cases were predominantly CTNNB1-mutant (73.2% vs 18.4%, P < 0.001), while PR-low (PR−/ER + , PR−/ER−) cases displayed higher TP53 mutation frequency (38.8% vs 7.3%, P = 0.001), greater genomic complexity (P = 0.007) and more frequent copy number alterations (P = 0.001). PR-high EnOC patients experience favourable disease-specific survival independent of clinicopathological and genomic features (HR = 0.16, 95% CI 0.04–0.71). TP53 mutation further delineates the outcome of patients with PR-low tumours (HR = 2.56, 95% CI 1.14–5.75). A simple, routinely applicable, classification algorithm utilising immunohistochemistry for PR and p53 recapitulated these subtypes and their survival profiles. The genomic profile of high-risk EnOC subtypes suggests that inhibitors of the MAPK and PI3K-AKT pathways, alongside PARP inhibitors, represent promising candidate agents for improving patient survival. Patients with PR-low TP53-mutant EnOC have the greatest unmet clinical need, while PR-high tumours—which are typically CTNNB1-mutant and TP53 wild-type—experience excellent survival and may represent candidates for trials investigating de-escalation of adjuvant chemotherapy to agents such as endocrine therapy.

Tumor mutation burden analysis in a 5,660 cancer patient cohort reveals cancer type-specific mechanisms for high mutation burden.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. 2589-2589
Author(s):  
Xiaodong Jiao ◽  
Xiaochun Zhang ◽  
Baodong Qin ◽  
Dong Liu ◽  
Liang Liu ◽  
...  
Keyword(s):  
Effective Means ◽  
Lung Squamous Cell Carcinoma ◽  
Biological Pathways ◽  
Formalin Fixed Paraffin Embed ◽  
Cancer Type ◽  
Biological Mechanisms ◽  
Tumor Mutation Burden ◽  
Molecular Features ◽  
Mutation Burden ◽  
Cancer Types

2589 Background: Tumor mutation burden (TMB), calculated by whole-exome sequencing (WES) or large NGS panels, has an important association with immunotherapy responses. Elucidating the underlying biological mechanisms of high TMB might help develop more precise and effective means for TMB and immunotherapy response prediction. Meanwhile, the landscape of TMB across different cancer types and its association with other molecular features have not been well investigated in large cohorts in China. Methods: Cancer patients whose fresh tissue (n = 1556), formalin-fixed, paraffin-embed (FFPE) specimen (n = 1794), and pleural fluid (n = 84) were profiled using 295- or 520-gene NGS panel. The association of the TMB status with a series of molecular features and biological pathways was interrogated using bootstrapping. Results: TMB, measured by 295- or 520-cancer-related gene panels, were correlated with WES TMB based on in silico simulation in the TCGA cohort. We compared the TMB landscape across 11 cancer type groups and found the highest average TMB in lung squamous cell carcinoma, whereas the lowest TMB was established in sarcoma. High microsatellite instability, DNA damage response deficiency, and homologous recombination repair deficiency indicated significantly higher TMB. The independent predictive power for TMB of twenty-six biological pathways was tested in 10 cancer groups. FoxO signaling pathway most commonly correlated with low-TMB; significant association was identified in four cancer groups. In contrast, no pathway was significantly correlated with high-TMB in more than two cancer groups. Overall, we discovered that the underlying pathways which may be the main drivers of TMB status varied greatly and sometimes had an opposite association with TMB across different cancer types. Moreover, we developed a 14- and 22-gene signature for TMB prediction for LUAD and LUSC, respectively, with only 10 genes shared by both signatures, indicating a histology-specific mechanism for driving high-TMB in lung cancer. Conclusions: The findings extended the knowledge of the underlying biological mechanisms for high TMB and might be helpful for developing more precise and accessible TMB assessment panels and algorithms in more cancer types.

Rate of incidental germline findings detected by tumor-normal matched sequencing in cancer types lacking hereditary cancer testing guidelines.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 10582-10582
Author(s):  
Timothy A. Yap ◽  
Arya Ashok ◽  
Jessica Stoll ◽  
Anna Ewa Schwarzbach ◽  
Kimberly L. Blackwell ◽  
...  
Keyword(s):  
Bile Duct ◽  
Hereditary Cancer ◽  
Next Generation Sequencing Data ◽  
Cancer Type ◽  
Cancer Genes ◽  
Sequencing Data ◽  
Single Nucleotide Variants ◽  
Germline Variants ◽  
Cancer Types ◽  
Germline Testing

10582 Background: Up to 10% of all cancers are associated with hereditary cancer syndromes; however, guidelines for germline testing are currently limited to patients and families with specific cancer types (ovarian, breast, prostate, pancreatic, etc.). Although germline alterations have been shown in genes associated with cancers such as bile-duct, head & neck, brain, bladder, esophageal, and lung cancers, genetic testing is not routinely offered (PMID: 28873162). In such cancers, a guidelines-based approach may fail to detect cancer risk variants found by tumor-normal (T/N) matched sequencing. Here, we report the prevalence of incidental germline findings in patients with the aforementioned 6 cancer types and highlight frequently mutated genes by cancer type. Methods: We retrospectively analyzed next-generation sequencing data from de-identified records of 19,630 patients tested using Tempus|xT T/N matched assay. Incidental germline findings (i.e., single nucleotide variants and small insertions/deletions) detected in 50 hereditary cancer genes were determined for: bile duct (n = 466), head & neck (n = 673), esophageal (n = 395), brain (n = 1,391), bladder (n = 810), and lung (n = 5,544), where n = total patients. For comparison, we also included 4 cancer types that frequently undergo germline testing: ovarian (n = 2,042), breast (n = 3,542), prostate (n = 2,146), and pancreatic (n = 2,621). Results: We detected incidental pathogenic/likely pathogenic germline variants (P/LPV) in 6.5% (601/9,279) of patients diagnosed with the 6 selected cancer types lacking hereditary cancer testing guidelines. The highest prevalence of P/LPV was identified in patients with bladder (8%), brain (6.9%), and lung (6.5%) cancers. Frequently mutated genes (Table) include ATM (n = 62), BRCA2 (n = 60), BRCA1 (n = 33), APC (n = 27), and CHEK2 (n = 21). Of note, the Ashkenazi Jewish variant (p.I1307K) was the most frequent mutation in APC. For cancer types where patients frequently undergo germline testing, the rates of incidental germline findings in descending order were ovarian (15%), breast (12%), prostate (9.4%), and pancreatic (8.5%) cancers. Conclusions: In addition to enhanced variant calling, T/N matched sequencing may identify germline variants missed by a guidelines-based approach to testing. The identification of such germline findings may have clinical implications for the patient, as well as at-risk family members, thereby resulting in the opportunity for genetic counseling and risk-stratified intervention.[Table: see text]

scholarly journals Individualized ctDNA Fingerprints to Monitor Treatment Response and Recurrence in Multiple Cancer Types

2019 ◽  
Author(s):  
Jiaping Li ◽  
Wei Jiang ◽  
Jinwang Wei ◽  
Jianwei Zhang ◽  
Linbo Cai ◽  
...  
Keyword(s):  
Exome Sequencing ◽  
Treatment Response ◽  
Whole Exome Sequencing ◽  
Therapeutic Response ◽  
Sequencing Data ◽  
Multiple Cancer ◽  
Exome Sequencing Data ◽  
Whole Exome ◽  
Whole Exome Sequencing Data ◽  
Cancer Types

AbstractCirculating tumor DNA (ctDNA) panels hold high promise of accurately predicting the therapeutic response of tumors while being minimally invasive and cost-efficient. However, their use has been limited to a small number of tumor types and patients. Here, we developed individualized ctDNA fingerprints suitable for most patients with multiple cancer types. The panels were designed based on individual whole-exome sequencing data in 521 Chinese patients and targeting high clonal population clusters of somatic mutations. Together, these patients represent 12 types of cancers and seven different treatments. The customized ctDNA panels have a median somatic mutation number of 19, most of which are patient-specific rather than cancer hotspot mutations; 66.8% of the patients were ctDNA-positive. We further evaluated the ctDNA content fraction (CCF) of the mutations, and analyzed the association between the change of ctDNA concentration and therapeutic response. We followed up 106 patients for clinical evaluation, demonstrating a significant correlation of changes in ctDNA with clinical outcomes, with a consistency rate of 93.4%. In particular, the median CCF increased by 204.6% in patients with progressive disease, decreased by 82.5% in patients with remission, and was relatively stable in patients with stable disease. Overall, 85% of the patients with a ctDNA-positive status experienced metastasis or relapse long before imaging detection, except for two patients who developed recurrence and metastasis almost simultaneously. The average lead time between the first ctDNA-positive finding and radiological diagnosis was 76 days in three patients that changed from a ctDNA-negative to -positive status. Our individualized ctDNA analysis can effectively monitor the treatment response, metastasis, and recurrence in multiple cancer types in patients with multiple treatment options, therefore offering great clinical applicability for improving personalized treatment in cancer.One Sentence SummaryctDNA fingerprint panels were customized to predict the treatment response for multiple cancer types from individual whole-exome sequencing data.

scholarly journals A Comprehensive Survey of Genomic Alterations in Gastric Cancer Reveals Recurrent Neoantigens as Potential Therapeutic Targets

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Chao Chen ◽  
Qiming Zhou ◽  
Riping Wu ◽  
Bo Li ◽  
Qiang Chen ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Somatic Mutations ◽  
Sequencing Data ◽  
Cell Based Therapy ◽  
Public Resource ◽  
Whole Exome ◽  
Genomic Landscape ◽  
Whole Exome Sequencing Data ◽  
Comprehensive Survey ◽  
Cancer Types

Immunotherapy directed against cancer-specific neoantigens derived from non-silent mutants is a promising individualized strategy for cancer treatment. Neoantigens shared across patients could be used as a public resource for developing T cell-based therapy. To identify potential public neoantigens for therapy in gastric cancer (GC), 74 GC patients were enrolled in this study. Combined with the TCGA cohort and other published studies, whole exome sequencing data from 942 GC patients were used to detect somatic mutations and predict neoantigens shared by GC patients. The mutations pattern between our study and the TCGA cohort is comparable, and C > T is the most common substitution. The number of neoantigens was significantly higher in older patients (age ≥60) compared to younger patients (age <60), both in this study and the TCGA cohort. Recurrent neoantigens were found in eight genes (TP53, PIK3CA, PGM5, ERBB3, C6, TRIM49C, OR4C16, and KRAS) in this study. The neoantigen-associated mutations PIK3CA (p.H1047R) and TP53 (p.R175H) are common across several cancer types, indicating their potential usage. Overall, our study illustrates a comprehensive genomic landscape of GC and provides the recurrent neoantigens to facilitate further immunotherapy.

scholarly journals Contextual Classifications of Cancer Driver Genes

2019 ◽  
Author(s):  
Pramod Chandrashekar ◽  
Navid Ahmadinejad ◽  
Junwen Wang ◽  
Aleksandar Sekulic ◽  
Jan B. Egan ◽  
...  
Keyword(s):  
Computational Method ◽  
Cancer Type ◽  
Sequencing Data ◽  
Multiple Cancer ◽  
Driver Genes ◽  
Cancer Driver ◽  
Link Type ◽  
Mutational Hotspots ◽  
Cancer Types ◽  
Cancer Driver Genes

ABSTRACTFunctions of cancer driver genes depend on cellular contexts that vary substantially across tissues and organs. Distinguishing oncogenes (OGs) and tumor suppressor genes (TSGs) for each cancer type is critical to identifying clinically actionable targets. However, current resources for context-aware classifications of cancer drivers are limited. In this study, we show that the direction and magnitude of somatic selection of missense and truncating mutations of a gene are suggestive of its contextual activities. By integrating these features with ratiometric and conservation measures, we developed a computational method to categorize OGs and TSGs using exome sequencing data. This new method, named genes under selection in tumors (GUST) shows an overall accuracy of 0.94 when tested on manually curated benchmarks. Application of GUST to 10,172 tumor exomes of 33 cancer types identified 98 OGs and 179 TSGs, >70% of which promote tumorigenesis in only one cancer type. In broad-spectrum drivers shared across multiple cancer types, we found heterogeneous mutational hotspots modifying distinct functional domains, implicating the synchrony of convergent and divergent disease mechanisms. We further discovered two novel OGs and 28 novel TSGs with high confidence. The GUST program is available at https://github.com/liliulab/gust. A database with pre-computed classifications is available at https://liliulab.shinyapps.io/gust

scholarly journals Characterizing genetic intra-tumor heterogeneity across 2,658 human cancer genomes

2018 ◽  
Author(s):  
Stefan C. Dentro ◽  
Ignaty Leshchiner ◽  
Kerstin Haase ◽  
Maxime Tarabichi ◽  
Jeff Wintersinger ◽  
...  
Keyword(s):  
Tumor Heterogeneity ◽  
Human Cancer ◽  
Driver Mutations ◽  
Whole Genome Sequencing Data ◽  
Tumor Evolution ◽  
Driver Gene ◽  
Cancer Type ◽  
Whole Genome ◽  
Sequencing Data ◽  
Cancer Types

SUMMARYIntra-tumor heterogeneity (ITH) is a mechanism of therapeutic resistance and therefore an important clinical challenge. However, the extent, origin and drivers of ITH across cancer types are poorly understood. To address this question, we extensively characterize ITH across whole-genome sequences of 2,658 cancer samples, spanning 38 cancer types. Nearly all informative samples (95.1%) contain evidence of distinct subclonal expansions, with frequent branching relationships between subclones. We observe positive selection of subclonal driver mutations across most cancer types, and identify cancer type specific subclonal patterns of driver gene mutations, fusions, structural variants and copy-number alterations, as well as dynamic changes in mutational processes between subclonal expansions. Our results underline the importance of ITH and its drivers in tumor evolution, and provide an unprecedented pan-cancer resource of comprehensively annotated subclonal events from whole-genome sequencing data.

scholarly journals Race-Specific Genetic Profiles of Homologous Recombination Deficiency in Multiple Cancers

2021 ◽  
Vol 11 (12) ◽  
pp. 1287
Author(s):  
Yi-Wen Hsiao ◽  
Tzu-Pin Lu
Keyword(s):  
African American ◽  
Homologous Recombination ◽  
Clinical Importance ◽  
Cancer Prognosis ◽  
Cancer Type ◽  
Sequencing Data ◽  
Homologous Recombination Deficiency ◽  
Cancer Types ◽  
American Black ◽  
Black Populations

Homologous recombination deficiency (HRD) has been used to predict both cancer prognosis and the response to DNA-damaging therapies in many cancer types. HRD has diverse manifestations in different cancers and even in different populations. Many screening strategies have been designed for detecting the sensitivity of a patient’s HRD status to targeted therapies. However, these approaches suffer from low sensitivity, and are not specific to each cancer type and population group. Therefore, identifying race-specific and targetable HRD-related genes is of clinical importance. Here, we conducted analyses using genomic sequencing data that was generated by the Pan-Cancer Atlas. Collapsing non-synonymous variants with functional damage to HRD-related genes, we analyzed the association between these genes and race within cancer types using the optimal sequencing kernel association test (SKAT-O). We have identified race-specific mutational patterns of curated HRD-related genes across cancers. Overall, more significant mutation sites were found in ATM, BRCA2, POLE, and TOP2B in both the ‘White’ and ‘Asian’ populations, whereas PTEN, EGFG, and RIF1 mutations were observed in both the ‘White’ and ‘African American/Black’ populations. Furthermore, supported by pathogenic tendency databases and previous reports, in the ‘African American/Black’ population, several associations, including BLM with breast invasive carcinoma, ERCC5 with ovarian serous cystadenocarcinoma, as well as PTEN with stomach adenocarcinoma, were newly described here. Although several HRD-related genes are common across cancers, many of them were found to be specific to race. Further studies, using a larger cohort of diverse populations, are necessary to identify HRD-related genes that are specific to race, for guiding gene testing methods.

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.

scholarly journals Pan-cancer analyses of human nuclear receptors reveal transcriptome diversity and prognostic value across cancer types

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Toshima Z. Parris
Keyword(s):  
Human Cancer ◽  
The Cancer Genome Atlas ◽  
Transcriptional Networks ◽  
Cancer Type ◽  
Sequencing Data ◽  
Pairwise Correlation ◽  
Organ Systems ◽  
Cancer Types ◽  
Disease Stratification ◽  
Pan Cancer

AbstractThe human nuclear receptor (NR) superfamily comprises 48 ligand-dependent transcription factors that play regulatory roles in physiology and pathophysiology. In cancer, NRs have long served as predictors of disease stratification, treatment response, and clinical outcome. The Cancer Genome Atlas (TCGA) Pan-Cancer project provides a wealth of genetic data for a large number of human cancer types. Here, we examined NR transcriptional activity in 8,526 patient samples from 33 TCGA ‘Pan-Cancer’ diseases and 11 ‘Pan-Cancer’ organ systems using RNA sequencing data. The web-based Kaplan-Meier (KM) plotter tool was then used to evaluate the prognostic potential of NR gene expression in 21/33 cancer types. Although, most NRs were significantly underexpressed in cancer, NR expression (moderate to high expression levels) was predominantly restricted (46%) to specific tissues, particularly cancers representing gynecologic, urologic, and gastrointestinal ‘Pan-Cancer’ organ systems. Intriguingly, a relationship emerged between recurrent positive pairwise correlation of Class IV NRs in most cancers. NR expression was also revealed to play a profound effect on patient overall survival rates, with ≥5 prognostic NRs identified per cancer type. Taken together, these findings highlighted the complexity of NR transcriptional networks in cancer and identified novel therapeutic targets for specific cancer types.

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