The genomic landscape of carcinomas with mucinous differentiation

AbstractMucinous carcinomas can arise in any organ with epithelial cells that produce mucus. While mucinous tumors from different organs are histologically similar, it remains to be elucidated whether they share molecular alterations. Here we analyzed a total of 902 patients across six cancer types by comparing mucinous and non-mucinous samples, integrating text mining of pathology reports, gene expression, methylation, mutational and copy-number profiling. We found that, in addition to genes involved in mucin processing and secretion, MUC2 up-regulation is a multi-cancer biomarker of mucinous histology and is regulated by DNA methylation in colorectal, breast and stomach cancer. The majority of carcinomas with mucinous differentiation had fewer DNA copy-number alterations than non-mucinous tumors. The tumor mutational burden was lower in breast and lung with mucinous differentiation compared to their non-mucinous counterparts. We found several differences in the frequency of oncogenic gene and pathway alterations between mucinous and non-mucinous carcinomas, including a lower frequency of p53 pathway alterations in colorectal and lung cancer, and a lower frequency of PI-3-Kinase/Akt pathway alterations in breast and stomach cancer with mucinous differentiation. This study shows that carcinomas with mucinous differentiation originating from different organs share transcriptomic and genomic similarities. These results might pave the way for a more biologically relevant taxonomy for these rare cancers.

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Comprehensive patient-level classification and quantification of driver events in TCGA PanCanAtlas cohorts

PLoS Genetics ◽

10.1371/journal.pgen.1009996 ◽

2022 ◽

Vol 18 (1) ◽

pp. e1009996

Author(s):

Alexey D. Vyatkin ◽

Danila V. Otnyukov ◽

Sergey V. Leonov ◽

Aleksey V. Belikov

Keyword(s):

Copy Number ◽

Human Cancer ◽

Single Nucleotide ◽

Cancer Driver ◽

Molecular Alterations ◽

Patient Level ◽

Tumour Suppressors ◽

Chromosome Arm ◽

Cancer Mutations ◽

Cancer Types

There is a growing need to develop novel therapeutics for targeted treatment of cancer. The prerequisite to success is the knowledge about which types of molecular alterations are predominantly driving tumorigenesis. To shed light onto this subject, we have utilized the largest database of human cancer mutations–TCGA PanCanAtlas, multiple established algorithms for cancer driver prediction (2020plus, CHASMplus, CompositeDriver, dNdScv, DriverNet, HotMAPS, OncodriveCLUSTL, OncodriveFML) and developed four novel computational pipelines: SNADRIF (Single Nucleotide Alteration DRIver Finder), GECNAV (Gene Expression-based Copy Number Alteration Validator), ANDRIF (ANeuploidy DRIver Finder) and PALDRIC (PAtient-Level DRIver Classifier). A unified workflow integrating all these pipelines, algorithms and datasets at cohort and patient levels was created. We have found that there are on average 12 driver events per tumour, of which 0.6 are single nucleotide alterations (SNAs) in oncogenes, 1.5 are amplifications of oncogenes, 1.2 are SNAs in tumour suppressors, 2.1 are deletions of tumour suppressors, 1.5 are driver chromosome losses, 1 is a driver chromosome gain, 2 are driver chromosome arm losses, and 1.5 are driver chromosome arm gains. The average number of driver events per tumour increases with age (from 7 to 15) and cancer stage (from 10 to 15) and varies strongly between cancer types (from 1 to 24). Patients with 1 and 7 driver events per tumour are the most frequent, and there are very few patients with more than 40 events. In tumours having only one driver event, this event is most often an SNA in an oncogene. However, with increasing number of driver events per tumour, the contribution of SNAs decreases, whereas the contribution of copy-number alterations and aneuploidy events increases.

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Sex-dependent differences in DNA copy number alterations in hepatocellular carcinoma

Academic Journal of Second Military Medical University ◽

10.3724/sp.j.1008.2012.00005 ◽

2012 ◽

Vol 32 (1) ◽

pp. 5-9 ◽

Cited By ~ 1

Author(s):

Bing-ji WEN ◽

Wen-ming CONG ◽

Ai-zhong WANG ◽

Song-qin HE ◽

Hong-mei JIANG ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Copy Number ◽

Copy Number Alterations ◽

Dna Copy Number ◽

Dna Copy Number Alterations

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Chromosomal copy number heterogeneity predicts survival rates across cancers

Nature Communications ◽

10.1038/s41467-021-23384-6 ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Erik van Dijk ◽

Tom van den Bosch ◽

Kristiaan J. Lenos ◽

Khalid El Makrini ◽

Lisanne E. Nijman ◽

...

Keyword(s):

Copy Number ◽

Cancer Survival ◽

Survival Rates ◽

Cancer Prognosis ◽

Disease Outcomes ◽

Distinct Disease ◽

Cancer Types ◽

Chromosomal Copy Number ◽

Chromosomal Copy ◽

Pan Cancer

AbstractSurvival rates of cancer patients vary widely within and between malignancies. While genetic aberrations are at the root of all cancers, individual genomic features cannot explain these distinct disease outcomes. In contrast, intra-tumour heterogeneity (ITH) has the potential to elucidate pan-cancer survival rates and the biology that drives cancer prognosis. Unfortunately, a comprehensive and effective framework to measure ITH across cancers is missing. Here, we introduce a scalable measure of chromosomal copy number heterogeneity (CNH) that predicts patient survival across cancers. We show that the level of ITH can be derived from a single-sample copy number profile. Using gene-expression data and live cell imaging we demonstrate that ongoing chromosomal instability underlies the observed heterogeneity. Analysing 11,534 primary cancer samples from 37 different malignancies, we find that copy number heterogeneity can be accurately deduced and predicts cancer survival across tissues of origin and stages of disease. Our results provide a unifying molecular explanation for the different survival rates observed between cancer types.

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From Benign Inflammatory Dermatosis to Cutaneous Lymphoma. DNA Copy Number Imbalances in Mycosis Fungoides versus Large Plaque Parapsoriasis

Medicina ◽

10.3390/medicina57050502 ◽

2021 ◽

Vol 57 (5) ◽

pp. 502

Author(s):

Georgiana Gug ◽

Caius Solovan

Keyword(s):

Mycosis Fungoides ◽

Copy Number ◽

Snp Array ◽

Chromosome 1 ◽

Copy Number Alterations ◽

Dna Copy Number ◽

Large Plaque ◽

Inflammatory Dermatosis ◽

Fresh Frozen ◽

Dna Copy Number Alterations

Background and Objectives: Mycosis fungoides (MF) and large plaque parapsoriasis (LPP) evolution provide intriguing data and are the cause of numerous debates. The diagnosis of MF and LPP is associated with confusion and imprecise definition. Copy number alterations (CNAs) may play an essential role in the genesis of cancer out of genes expression dysregulation. Objectives: Due to the heterogeneity of MF and LPP and the scarcity of the cases, there are an exceedingly small number of studies that have identified molecular changes in these pathologies. We aim to identify and compare DNA copy number alterations and gene expression changes between MF and LPP to highlight the similarities and the differences between these pathologies. Materials and Methods: The patients were prospectively selected from University Clinic of Dermatology and Venereology Timișoara, Romania. From fresh frozen skin biopsies, we extracted DNA using single nucleotide polymorphism (SNP) data. The use of SNP array for copy number profiling is a promising approach for genome-wide analysis. Results: After reviewing each group, we observed that the histograms generated for chromosome 1–22 were remarkably similar and had a lot of CNAs in common, but also significant differences were seen. Conclusions: This study took a step forward in finding out the differences and similarities between MF and LPP, for a more specific and implicitly correct approach of the case. The similarity between these two pathologies in terms of CNAs is striking, emphasizing once again the difficulty of approaching and differentiating them.

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Human-interpretable image features derived from densely mapped cancer pathology slides predict diverse molecular phenotypes

Nature Communications ◽

10.1038/s41467-021-21896-9 ◽

2021 ◽

Vol 12 (1) ◽

Cited By ~ 1

Author(s):

James A. Diao ◽

Jason K. Wang ◽

Wan Fung Chui ◽

Victoria Mountain ◽

Sai Chowdary Gullapally ◽

...

Keyword(s):

Tumor Microenvironment ◽

Image Features ◽

Tissue Type ◽

Type Model ◽

Biologically Relevant ◽

Cancer Pathology ◽

Substantial Progress ◽

Cancer Types ◽

Molecular Phenotypes ◽

Immune Checkpoint Proteins

AbstractComputational methods have made substantial progress in improving the accuracy and throughput of pathology workflows for diagnostic, prognostic, and genomic prediction. Still, lack of interpretability remains a significant barrier to clinical integration. We present an approach for predicting clinically-relevant molecular phenotypes from whole-slide histopathology images using human-interpretable image features (HIFs). Our method leverages >1.6 million annotations from board-certified pathologists across >5700 samples to train deep learning models for cell and tissue classification that can exhaustively map whole-slide images at two and four micron-resolution. Cell- and tissue-type model outputs are combined into 607 HIFs that quantify specific and biologically-relevant characteristics across five cancer types. We demonstrate that these HIFs correlate with well-known markers of the tumor microenvironment and can predict diverse molecular signatures (AUROC 0.601–0.864), including expression of four immune checkpoint proteins and homologous recombination deficiency, with performance comparable to ‘black-box’ methods. Our HIF-based approach provides a comprehensive, quantitative, and interpretable window into the composition and spatial architecture of the tumor microenvironment.

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Wedding of Molecular Alterations and Immune Checkpoint Blockade: Genomics as a Matchmaker

JNCI Journal of the National Cancer Institute ◽

10.1093/jnci/djab067 ◽

2021 ◽

Author(s):

Elena Fountzilas ◽

Razelle Kurzrock ◽

Henry Hiep Vo ◽

Apostolia-Maria Tsimberidou

Keyword(s):

Molecular Mechanisms ◽

Cell Receptor ◽

Immune Checkpoint Blockade ◽

Checkpoint Blockade ◽

Beta Catenin ◽

Molecular Alterations ◽

Receptor Repertoire ◽

Repair Deficiency ◽

Tumor Mutational Burden

Abstract The development of checkpoint blockade immunotherapy has transformed the medical oncology armamentarium. But, despite its favorable impact on clinical outcomes, immunotherapy benefits only a subset of patients, and a substantial proportion of these individuals eventually manifest resistance. Serious immune-related adverse events and hyper-progression have also been reported. It is therefore essential to understand the molecular mechanisms and identify the drivers of therapeutic response and resistance. In this review, we provide an overview of the current and emerging clinically relevant genomic biomarkers implicated in checkpoint blockade outcome. U.S. Food and Drug Administration–approved molecular biomarkers of immunotherapy response include mismatch repair deficiency/microsatellite instability and tumor mutational burden ≥10 mutations/megabase. Investigational genomic-associated biomarkers for immunotherapy response include alterations of the following genes/associated pathways: chromatin remodeling (ARID1A, PBRM1, SMARCA4, SMARCB1, BAP1), major histocompatibility complex, specific (e.g., ultraviolet, APOBEC) mutational signatures, T-cell receptor repertoire, PDL1, POLE/POLD1, and neo-antigens produced by the mutanome; those potentially associated with resistance include β2-microglobulin, EGFR, Keap1, JAK1/JAK2/interferon-gamma signaling, MDM2, PTEN, STK11, and Wnt/Beta-catenin pathway alterations. Prospective clinical trials are needed to assess the role of a composite of these biomarkers in order to optimize the implementation of precision immunotherapy in patient care.

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Analysis of DNA Copy Number Alterations in Ovarian Serous Tumors Identifies New Molecular Genetic Changes in Low-Grade and High-Grade Carcinomas

Cancer Research ◽

10.1158/0008-5472.can-08-3913 ◽

2009 ◽

Vol 69 (9) ◽

pp. 4036-4042 ◽

Cited By ~ 118

Author(s):

Kuan-Ting Kuo ◽

Bin Guan ◽

Yuanjian Feng ◽

Tsui-Lien Mao ◽

Xu Chen ◽

...

Keyword(s):

Copy Number ◽

Molecular Genetic ◽

Low Grade ◽

High Grade ◽

Copy Number Alterations ◽

Dna Copy Number ◽

Genetic Changes ◽

Dna Copy Number Alterations ◽

Serous Tumors

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Unique Genomic Landscape of High-Grade Neuroendocrine Cervical Carcinoma: Implications for Rethinking Current Treatment Paradigms

JCO Precision Oncology ◽

10.1200/po.19.00248 ◽

2020 ◽

pp. 972-987

Author(s):

Ramez N. Eskander ◽

Julia Elvin ◽

Laurie Gay ◽

Jeffrey S. Ross ◽

Vincent A. Miller ◽

...

Keyword(s):

Treatment Strategies ◽

Current Treatment ◽

High Grade ◽

Novel Treatment ◽

Sample Average ◽

Genomic Landscape ◽

Comprehensive Genomic Profiling ◽

Tumor Mutational Burden ◽

Sample Range ◽

Novel Treatment Strategies

PURPOSE High-grade neuroendocrine cervical cancer (HGNECC) is an uncommon malignancy with limited therapeutic options; treatment is patterned after the histologically similar small-cell lung cancer (SCLC). To better understand HGNECC biology, we report its genomic landscape. PATIENTS AND METHODS Ninety-seven patients with HGNECC underwent comprehensive genomic profiling (182-315 genes). These results were subsequently compared with a cohort of 1,800 SCLCs. RESULTS The median age of patients with HGNECC was 40.5 years; 83 patients (85.6%) harbored high-risk human papillomavirus (HPV). Overall, 294 genomic alterations (GAs) were identified (median, 2 GAs/sample; average, 3.0 GAs/sample, range, 0-25 GAs/sample) in 109 distinct genes. The most frequently altered genes were PIK3CA (19.6% of cohort), MYC (15.5%), TP53 (15.5%), and PTEN (14.4%). RB1 GAs occurred in 4% versus 32% of HPV-positive versus HPV-negative tumors ( P < .0001). GAs in HGNECC involved the following pathways: PI3K/AKT/mTOR (41.2%); RAS/MEK (11.3%); homologous recombination (9.3%); and ERBB (7.2%). Two tumors (2.1%) had high tumor mutational burden (TMB; both with MSH2 alterations); 16 (16.5%) had intermediate TMB. Seventy-one patients (73%) had ≥ 1 alteration that was theoretically druggable. Comparing HGNECC with SCLC, significant differences in TMB, microsatellite instability, HPV-positive status, and in PIK3CA, MYC, PTEN, TP53, ARID1A, and RB1 alteration rates were found. CONCLUSION This large cohort of patients with HGNECC demonstrated a genomic landscape distinct from SCLC, calling into question the biologic and therapeutic relevance of the histologic similarities between the entities. Furthermore, 73% of HGNECC tumors had potentially actionable alterations, suggesting novel treatment strategies for this aggressive malignancy.

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