Comprehensive analysis of advanced-stage solid tumors from TCGA reveal widespread variation of genomics evidence levels across cancer types.

e13547 Background: Improved scalability and affordability of next generation sequencing (NGS) has pivoted cancer care toward genomics-driven treatment decisions. Particularly in advanced-stage or refractory cancer, clinical insights gleaned from NGS have become an integral option as these patients have typically exhausted all lines of available therapy. As precision oncology evolves, NGS is expected to have a differential impact based on the cancer type. In this study, a comprehensive NGS panel was used to determine the strength of clinical evidence in various advanced stage tumor samples from The Cancer Genome Atlas (TCGA). Methods: A hybrid capture panel, Oncofoco, was developed to evaluate SNVs, INDELs, CNVs and TMB in 366 genes. The panel’s utility was validated by interrogating a broader cohort of 2847 TCGA samples (advanced tumors with T3 or T4; or N > = 1; or M > = 1). Watsonä for Genomics, an artificial intelligence offering, was used for variant interpretation and annotation of the 366 genes. A clinical evidence classification system that evaluated the strength of biomarker/drug response associations was used for annotation with level 1/R1 strongest and level 4 weakest from clinical literature, FDA drug labels and guidelines (PMID:28890946). Results: The highest level of evidence for the top nine frequently occurring advanced stage cancers in TCGA is shown in Table. Conclusions: Thyroid cancer and cutaneous melanoma have emerged as the cancer types with the most level 1 evidence (FDA approved drugs) owing to BRAF V600E mutations. Kidney and prostate cancers show no cases with level 1 evidence and also had the largest fraction of unactionable tumors. Over half of colorectal cancer cases had level R1 resistance evidence attributed to KRAS and NRAS mutations. The clinical utility of NGS in late-stage refractory cancer varies widely by tumor type. The presence of level 3 and level 4 evidence in all cancer types bodes well for the development of new targeted drugs. [Table: see text]

Download Full-text

ASF1B Promotes Oncogenesis in Lung Adenocarcinoma and Other Cancer Types

Frontiers in Oncology ◽

10.3389/fonc.2021.731547 ◽

2021 ◽

Vol 11 ◽

Author(s):

Wencheng Zhang ◽

Zhouyong Gao ◽

Mingxiu Guan ◽

Ning Liu ◽

Fanjie Meng ◽

...

Keyword(s):

Lung Adenocarcinoma ◽

Immune Cell ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Tumor Promoter ◽

Regulatory Subunit ◽

Cell Cycle Distribution ◽

Cancer Type ◽

Dependent Manner ◽

Cancer Types

Anti-silencing function 1B histone chaperone (ASF1B) is known to be an important modulator of oncogenic processes, yet its role in lung adenocarcinoma (LUAD) remains to be defined. In this study, an integrated assessment of The Cancer Genome Atlas (TCGA) and genotype-tissue expression (GTEx) datasets revealed the overexpression of ASF1B in all analyzed cancer types other than LAML. Genetic, epigenetic, microsatellite instability (MSI), and tumor mutational burden (TMB) analysis showed that ASF1B was regulated by single or multiple factors. Kaplan-Meier survival curves suggested that elevated ASF1B expression was associated with better or worse survival in a cancer type-dependent manner. The CIBERSORT algorithm was used to evaluate immune microenvironment composition, and distinct correlations between ASF1B expression and immune cell infiltration were evident when comparing tumor and normal tissue samples. Gene set enrichment analysis (GSEA) indicated that ASF1B was associated with proliferation- and immunity-related pathways. Knocking down ASF1B impaired the proliferation, affected cell cycle distribution, and induced cell apoptosis in LUAD cell lines. In contrast, ASF1B overexpression had no impact on the malignant characteristics of LUAD cells. At the mechanistic level, ASF1B served as an indirect regulator of DNA Polymerase Epsilon 3, Accessory Subunit (POLE3), CDC28 protein kinase regulatory subunit 1(CKS1B), Dihydrofolate reductase (DHFR), as established through proteomic profiling and Immunoprecipitation-Mass Spectrometry (IP-MS) analyses. Overall, these data suggested that ASF1B serves as a tumor promoter and potential target for cancer therapy and provided us with clues to better understand the importance of ASF1B in many types of cancer.

Download Full-text

Putatively cancer-specific exon–exon junctions are shared across patients and present in developmental and other non-cancer cells

NAR Cancer ◽

10.1093/narcan/zcaa001 ◽

2020 ◽

Vol 2 (1) ◽

Cited By ~ 1

Author(s):

Julianne K David ◽

Sean K Maden ◽

Benjamin R Weeder ◽

Reid F Thompson ◽

Abhinav Nellore

Keyword(s):

Rna Splicing ◽

Tissue Expression ◽

The Body ◽

The Cancer Genome Atlas ◽

Cancer Type ◽

Rna Seq ◽

Normal Tissues ◽

Cancer Types ◽

Exon Junctions ◽

Cancer Tissues

Abstract This study probes the distribution of putatively cancer-specific junctions across a broad set of publicly available non-cancer human RNA sequencing (RNA-seq) datasets. We compared cancer and non-cancer RNA-seq data from The Cancer Genome Atlas (TCGA), the Genotype-Tissue Expression (GTEx) Project and the Sequence Read Archive. We found that (i) averaging across cancer types, 80.6% of exon–exon junctions thought to be cancer-specific based on comparison with tissue-matched samples (σ = 13.0%) are in fact present in other adult non-cancer tissues throughout the body; (ii) 30.8% of junctions not present in any GTEx or TCGA normal tissues are shared by multiple samples within at least one cancer type cohort, and 87.4% of these distinguish between different cancer types; and (iii) many of these junctions not found in GTEx or TCGA normal tissues (15.4% on average, σ = 2.4%) are also found in embryological and other developmentally associated cells. These findings refine the meaning of RNA splicing event novelty, particularly with respect to the human neoepitope repertoire. Ultimately, cancer-specific exon–exon junctions may have a substantial causal relationship with the biology of disease.

Download Full-text

From Genetic Alterations to Tumor Microenvironment: The Ariadne’s String in Pancreatic Cancer

Cells ◽

10.3390/cells9020309 ◽

2020 ◽

Vol 9 (2) ◽

pp. 309 ◽

Cited By ~ 3

Author(s):

Chiara Bazzichetto ◽

Fabiana Conciatori ◽

Claudio Luchini ◽

Francesca Simionato ◽

Raffaela Santoro ◽

...

Keyword(s):

Pancreatic Cancer ◽

Tumor Microenvironment ◽

Current Knowledge ◽

Myeloid Cells ◽

Genetic Alterations ◽

Molecular Characteristics ◽

Precision Oncology ◽

Cancer Type ◽

Tumor Type ◽

Driver Genes

The threatening notoriety of pancreatic cancer mainly arises from its negligible early diagnosis, highly aggressive progression, failure of conventional therapeutic options and consequent very poor prognosis. The most important driver genes of pancreatic cancer are the oncogene KRAS and the tumor suppressors TP53, CDKN2A, and SMAD4. Although the presence of few drivers, several signaling pathways are involved in the oncogenesis of this cancer type, some of them with promising targets for precision oncology. Pancreatic cancer is recognized as one of immunosuppressive phenotype cancer: it is characterized by a fibrotic-desmoplastic stroma, in which there is an intensive cross-talk between several cellular (e.g., fibroblasts, myeloid cells, lymphocytes, endothelial, and myeloid cells) and acellular (collagen, fibronectin, and soluble factors) components. In this review; we aim to describe the current knowledge of the genetic/biological landscape of pancreatic cancer and the composition of its tumor microenvironment; in order to better direct in the intrinsic labyrinth of this complex tumor type. Indeed; disentangling the genetic and molecular characteristics of cancer cells and the environment in which they evolve may represent the crucial step towards more effective therapeutic strategies

Download Full-text

Cancer Type-Dependent Correlations betweenTP53Mutations and Antitumor Immunity

10.1101/692715 ◽

2019 ◽

Author(s):

Lin Li ◽

Mengyuan Li ◽

Xiaosheng Wang

Keyword(s):

Antitumor Immunity ◽

Colon Adenocarcinoma ◽

Joint Effect ◽

The Cancer Genome Atlas ◽

Cancer Type ◽

Mutation Burden ◽

Cancer Genome Atlas ◽

Negative Role ◽

Stomach Adenocarcinoma ◽

Cancer Types

AbstractMany studies have shown thatTP53mutations play a negative role in antitumor immunity. However, a few studies reported thatTP53mutations could promote antitumor immunity. To explain these contradictory findings, we analyzed five cancer cohorts from The Cancer Genome Atlas (TCGA) project. We found thatTP53-mutated cancers had significantly higher levels of antitumor immune signatures thanTP53-wildtype cancers in breast invasive carcinoma (BRCA) and lung adenocarcinoma (LUAD). In contrast,TP53-mutated cancers had significantly lower antitumor immune signature levels thanTP53-wildtype cancers in stomach adenocarcinoma (STAD), colon adenocarcinoma (COAD), and head and neck squamous cell carcinoma (HNSC). Moreover,TP53-mutated cancers likely had higher tumor mutation burden (TMB) and tumor aneuploidy level (TAL) thanTP53-wildtype cancers. However, the TMB differences were more marked betweenTP53-mutated andTP53-wildtype cancers than the TAL differences in BRCA and LUAD, and the TAL differences were more significant in STAD and COAD. Furthermore, we showed that TMB and TAL had a positive and a negative correlation with antitumor immunity and that TMB affected antitumor immunity more greatly than TAL did in BRCA and LUAD while TAL affected antitumor immunity more strongly than TMB in STAD and HNSC. These findings indicate that the distinct correlations betweenTP53mutations and antitumor immunity in different cancer types are a consequence of the joint effect of the altered TMB and TAL caused byTP53mutations on tumor immunity. Our data suggest that theTP53mutation status could be a useful biomarker for cancer immunotherapy response depending on cancer types.

Download Full-text

Pan-cancer analysis reveals complex tumor-specific alternative polyadenylation

10.1101/160960 ◽

2017 ◽

Author(s):

Zhuyi Xue ◽

René L Warren ◽

Ewan A Gibb ◽

Daniel MacMillan ◽

Johnathan Wong ◽

...

Keyword(s):

Alternative Polyadenylation ◽

Length Change ◽

The Cancer Genome Atlas ◽

Cancer Type ◽

Rna Seq ◽

Multiple Cancer ◽

Tissue Samples ◽

Cancer Genome Atlas ◽

Specific Alternative ◽

Cancer Types

AbstractAlternative polyadenylation (APA) of 3’ untranslated regions (3’ UTRs) has been implicated in cancer development. Earlier reports on APA in cancer primarily focused on 3’ UTR length modifications, and the conventional wisdom is that tumor cells preferentially express transcripts with shorter 3’ UTRs. Here, we analyzed the APA patterns of 114 genes, a select list of oncogenes and tumor suppressors, in 9,939 tumor and 729 normal tissue samples across 33 cancer types using RNA-Seq data from The Cancer Genome Atlas, and we found that the APA regulation machinery is much more complicated than what was previously thought. We report 77 cases (gene-cancer type pairs) of differential 3’ UTR cleavage patterns between normal and tumor tissues, involving 33 genes in 13 cancer types. For 15 genes, the tumor-specific cleavage patterns are recurrent across multiple cancer types. While the cleavage patterns in certain genes indicate apparent trends of 3’ UTR shortening in tumor samples, over half of the 77 cases imply 3’ UTR length change trends in cancer that are more complex than simple shortening or lengthening. This work extends the current understanding of APA regulation in cancer, and demonstrates how large volumes of RNA-seq data generated for characterizing cancer cohorts can be mined to investigate this process.

Download Full-text

Costs and outcomes associated with febrile neutropenia-related hospitalizations across patients with varying cancer types: A retrospective analysis

Journal of Clinical Oncology ◽

10.1200/jco.2009.27.15_suppl.e20560 ◽

2009 ◽

Vol 27 (15_suppl) ◽

pp. e20560-e20560

Author(s):

M. B. Schilling ◽

C. Parks ◽

R. G. Deeter

Keyword(s):

Febrile Neutropenia ◽

Healthcare Cost ◽

Opportunistic Infections ◽

Metastatic Breast ◽

Clinical Impact ◽

Cancer Type ◽

Tumor Type ◽

Healthcare Database ◽

Hospitalization Costs ◽

Cancer Types

e20560 Background: Neutropenia, the major dose-limiting toxicity of chemotherapy, is a frequent, often serious, and sometimes fatal complication of myelosuppressive chemotherapy. Its economic and clinical impact is often under-appreciated, and thus this study evaluates the contribution of febrile neutropenia (FN) by tumor type as related to healthcare cost and mortality. Methods: FN patients in this study were identified as having cancer (ICD-9-CM: 140.xx - 208.xx), neutropenia (288.0x) and either opportunistic infections (110 total codes) or fever of unknown origin (780.6) who were hospitalized between 1/05 and 6/08 in a retrospective cohort study from the Aspen US healthcare database (∼11 million pts, >342 inpatient facilities, and >300 million charge-detail records). Unadjusted mean healthcare cost of hospitalization, length of hospital stay (LOS), and mortality rates were calculated, stratifying by cancer type (breast, metastatic breast, and lung cancers, non-Hodgkin lymphoma (NHL), or other hematologic tumors). Results: Among 598 hospitalized patients (mean age 63 years; 53% female) with cancer experiencing FN, the mean cost of hospitalization, LOS and mortality varied significantly by tumor type ( Table ). Conclusions: FN hospitalizations are costly and may be associated with significant mortality. Considerable variations exist across cancer types for hospitalization costs, LOS and mortality. The tumor type is important in assessing the economic and clinical impact of FN hospitalizations. [Table: see text] [Table: see text]

Download Full-text

NGS testing patterns in advanced non-small cell lung cancer (aNSCLC) and metastatic breast cancer (mBC): OneOncology (OO) sites compared to Flatiron Health Nationwide (NAT).

Journal of Clinical Oncology ◽

10.1200/jco.2020.39.28_suppl.288 ◽

2021 ◽

Vol 39 (28_suppl) ◽

pp. 288-288

Author(s):

Ari M. Vanderwalde ◽

Esprit Ma ◽

Elaine Yu ◽

Tania Szado ◽

Richard Price ◽

...

Keyword(s):

Advanced Disease ◽

Metastatic Breast ◽

Precision Oncology ◽

Cancer Type ◽

Tumor Type ◽

Future Studies ◽

Testing Rate ◽

Testing Patterns ◽

Test Result ◽

Over Time

288 Background: Personalized treatment (tx) decisions can be improved through diagnostic tests with NGS by detecting different actionable mutations. OO, a research-focused network of community practices, has a network-wide precision oncology initiative and has advocated for NGS testing in advanced cancers since 2019. This study evaluated NGS testing patterns in aNSCLC and mBC populations descriptively in OO community sites and Flatiron Health NAT. Methods: This study used the Flatiron Health EHR derived de-identified database from [1] four OO sites, and [2] NAT. Patients (pts) diagnosed (Dx) with aNSCLC (stage ≥ IIIb) or mBC from 1/1/2015 to 5/31/2020, aged ≥ 18 years, had ≥ 1 visit ≤ 90 days (d) of advanced or metastatic Dx, and had ≥ 1 biomarker test were included. NAT NGS was confirmed via abstraction from patient records. Descriptive analyses were conducted to assess NGS testing patterns and pts characteristics by tumor type. Results: Of biomarker tested pts at OO vs. NAT (community:academic: 90%:10% aNSCLC; 93%:7% mBC), 2,029 of 3,152 (64%) OO vs. 13,681 of 29,572 (46%) NAT in aNSCLC and 514 of 1,282 (40%) OO vs. 2,458 of 12,175 (20%) NAT in mBC received NGS ± other tests. Testing rate of all 5 aNSCLC biomarkers (ALK, BRAF, EGFR, ROS-1, and KRAS) was higher with NGS vs. other tests for OO (87% vs. 6%) and NAT (87% vs. 11%). In mBC, a higher testing rate of BRCA with NGS vs. other tests (OO: 68% vs. 26%, NAT: 71% vs. 28%) and similar testing rate on HER2 (OO: 98% vs. 98%, NAT: 100% vs. 99%). Median time from Dx to NGS test result at OO vs. NAT was 33 d vs. 32 d in aNSCLC and 70 d vs. 188 d in mBC. NGS testing rates increased over time, with higher rates at OO vs. NAT [Table]. Pts with NGS vs. other tests were slightly younger in aNSCLC (OO: 68 y vs. 70 y, p = 0.001; NAT: 69 y vs. 70 yr, p < 0.001) and mBC (OO: 61 y vs. 67 y, p < 0.001; NAT: 61 y vs. 66 y, p < 0.001), and slightly more commercially insured in aNSCLC (OO: 48% vs. 45%, p = 0.3; NAT: 37% vs. 33%, p < 0.001) and mBC (OO: 54% vs. 48% OO, p = 0.053; NAT: 42 % vs. 36 %, p < 0.001). Conclusions: The adoption of NGS differed by cancer type and NGS testing rates have increased over time in aNSCLC and mBC. While some pts may have received testing outside of the Flatiron network, OO had a higher NGS uptake than NAT, and had a shorter time to testing in mBC that was possibly related to a network wide strategy recommending testing at Dx of advanced disease. Future studies on tx pattern after NGS testing are warranted to improve the actionability of NGS to foster personalized tx. [Table: see text]

Download Full-text

Quantitative Analysis of Differential Expression of HOX Genes in Multiple Cancers

Cancers ◽

10.3390/cancers12061572 ◽

2020 ◽

Vol 12 (6) ◽

pp. 1572

Author(s):

Orit Adato ◽

Yaron Orenstein ◽

Juri Kopolovic ◽

Tamar Juven-Gershon ◽

Ron Unger

Keyword(s):

Gene Expression ◽

Quantitative Analysis ◽

Differential Expression ◽

Survival Data ◽

Hox Genes ◽

Expression Patterns ◽

The Cancer Genome Atlas ◽

Tumor Type ◽

Hox Gene ◽

Cancer Types

Transcription factors encoded by Homeobox (HOX) genes play numerous key functions during early embryonic development and differentiation. Multiple reports have shown that mis-regulation of HOX gene expression plays key roles in the development of cancers. Their expression levels in cancers tend to differ based on tissue and tumor type. Here, we performed a comprehensive analysis comparing HOX gene expression in different cancer types, obtained from The Cancer Genome Atlas (TCGA), with matched healthy tissues, obtained from Genotype-Tissue Expression (GTEx). We identified and quantified differential expression patterns that confirmed previously identified expression changes and highlighted new differential expression signatures. We discovered differential expression patterns that are in line with patient survival data. This comprehensive and quantitative analysis provides a global picture of HOX genes’ differential expression patterns in different cancer types.

Download Full-text

Integrative Analysis of Cancer Omics Data for Prognosis Modeling

Genes ◽

10.3390/genes10080604 ◽

2019 ◽

Vol 10 (8) ◽

pp. 604 ◽

Cited By ~ 2

Author(s):

Wang ◽

Wu ◽

Keyword(s):

Integrative Analysis ◽

The Cancer Genome Atlas ◽

Cancer Prognosis ◽

Sufficient Information ◽

Cancer Type ◽

Multiple Cancer ◽

Cancer Genome Atlas ◽

Cancer Types ◽

Information Borrowing ◽

Penalization Technique

Prognosis modeling plays an important role in cancer studies. With the development of omics profiling, extensive research has been conducted to search for prognostic markers for various cancer types. However, many of the existing studies share a common limitation by only focusing on a single cancer type and suffering from a lack of sufficient information. With potential molecular similarity across cancer types, one cancer type may contain information useful for the analysis of other types. The integration of multiple cancer types may facilitate information borrowing so as to more comprehensively and more accurately describe prognosis. In this study, we conduct marginal and joint integrative analysis of multiple cancer types, effectively introducing integration in the discovery process. For accommodating high dimensionality and identifying relevant markers, we adopt the advanced penalization technique which has a solid statistical ground. Gene expression data on nine cancer types from The Cancer Genome Atlas (TCGA) are analyzed, leading to biologically sensible findings that are different from the alternatives. Overall, this study provides a novel venue for cancer prognosis modeling by integrating multiple cancer types.

Download Full-text

Identifying cancer type specific oncogenes and tumor suppressors using limited size data

Journal of Bioinformatics and Computational Biology ◽

10.1142/s0219720016500311 ◽

2016 ◽

Vol 14 (06) ◽

pp. 1650031 ◽

Cited By ~ 4

Author(s):

Ana B. Pavel ◽

Cristian I. Vasile

Keyword(s):

Tumor Suppressors ◽

Molecular Mechanisms ◽

Lung Squamous Cell Carcinoma ◽

The Cancer Genome Atlas ◽

Driver Mutations ◽

Cancer Type ◽

Multiple Cancer ◽

Driver Genes ◽

Cancer Subtypes ◽

Cancer Types

Cancer is a complex and heterogeneous genetic disease. Different mutations and dysregulated molecular mechanisms alter the pathways that lead to cell proliferation. In this paper, we explore a method which classifies genes into oncogenes (ONGs) and tumor suppressors. We optimize this method to identify specific (ONGs) and tumor suppressors for breast cancer, lung adenocarcinoma (LUAD), lung squamous cell carcinoma (LUSC) and colon adenocarcinoma (COAD), using data from the cancer genome atlas (TCGA). A set of genes were previously classified as ONGs and tumor suppressors across multiple cancer types (Science 2013). Each gene was assigned an ONG score and a tumor suppressor score based on the frequency of its driver mutations across all variants from the catalogue of somatic mutations in cancer (COSMIC). We evaluate and optimize this approach within different cancer types from TCGA. We are able to determine known driver genes for each of the four cancer types. After establishing the baseline parameters for each cancer type, we identify new driver genes for each cancer type, and the molecular pathways that are highly affected by them. Our methodology is general and can be applied to different cancer subtypes to identify specific driver genes and improve personalized therapy.

Download Full-text