scholarly journals CNApp: quantification of genomic copy number alterations in cancer and integrative analysis to unravel clinical implications

2018 ◽  
Author(s):  
Sebastià Franch-Expósito ◽  
Laia Bassaganyas ◽  
Maria Vila-Casadesús ◽  
Eva Hernández-Illán ◽  
Roger Esteban-Fabró ◽  
...  
Keyword(s):  
Machine Learning ◽  
Copy Number ◽  
Human Tumor ◽  
Clinical Implications ◽  
Copy Number Alterations ◽  
Cancer Dataset ◽  
Genomic Imbalances ◽  
Unique Framework ◽  
Tumor Types ◽  
User Friendly

ABSTRACTSomatic copy number alterations (CNAs) are a hallmark of cancer. Although CNA profiles have been established for most human tumor types, their precise role in tumorigenesis as well as their clinical and therapeutic relevance remain largely unclear. Thus, computational and statistical approaches are required to thoroughly define the interplay between CNAs and tumor phenotypes. Here we developed CNApp, a user-friendly web tool that offers sample- and cohort-level computational analyses, allowing a comprehensive and integrative exploration of CNAs with clinical and molecular variables. By using purity-corrected segmented data from multiple genomic platforms, CNApp generates genome-wide profiles, computes CNA scores for broad, focal and global CNA burdens, and uses machine learning-based predictions to classify samples. We applied CNApp to a pan-cancer dataset of 10,635 genomes from TCGA showing that CNA patterns classify cancer types according to their tissue-of-origin, and that broad and focal CNA scores positively correlate in samples with low amounts of whole-chromosome and chromosomal arm-level imbalances. Moreover, using the hepatocellular carcinoma cohort from the TCGA repository, we demonstrate the reliability of the tool in identifying recurrent CNAs, confirming previous results. Finally, we establish machine learning-based models to predict colon cancer molecular subtypes and microsatellite instability based on broad CNA scores and specific genomic imbalances. In summary, CNApp facilitates data-driven research and provides a unique framework for the first time to comprehensively assess CNAs and perform integrative analyses that enable the identification of relevant clinical implications. CNApp is hosted at http://cnapp.bsc.es.

scholarly journals CNApp, a tool for the quantification of copy number alterations and integrative analysis revealing clinical implications

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Sebastià Franch-Expósito ◽  
Laia Bassaganyas ◽  
Maria Vila-Casadesús ◽  
Eva Hernández-Illán ◽  
Roger Esteban-Fabró ◽  
...  
Keyword(s):  
Copy Number ◽  
Clinical Implications ◽  
Cancer Type ◽  
Copy Number Alterations ◽  
Cancer Dataset ◽  
Web Based ◽  
Genomic Imbalances ◽  
Genome Wide ◽  
Cancer Types ◽  
Unique Framework

Somatic copy number alterations (CNAs) are a hallmark of cancer, but their role in tumorigenesis and clinical relevance remain largely unclear. Here, we developed CNApp, a web-based tool that allows a comprehensive exploration of CNAs by using purity-corrected segmented data from multiple genomic platforms. CNApp generates genome-wide profiles, computes CNA scores for broad, focal and global CNA burdens, and uses machine learning-based predictions to classify samples. We applied CNApp to the TCGA pan-cancer dataset of 10,635 genomes showing that CNAs classify cancer types according to their tissue-of-origin, and that each cancer type shows specific ranges of broad and focal CNA scores. Moreover, CNApp reproduces recurrent CNAs in hepatocellular carcinoma and predicts colon cancer molecular subtypes and microsatellite instability based on broad CNA scores and discrete genomic imbalances. In summary, CNApp facilitates CNA-driven research by providing a unique framework to identify relevant clinical implications. CNApp is hosted at https://tools.idibaps.org/CNApp/.

Disclosure of Copy Number Alterations in AML with Normal Karyotype Using Matrix-Based Comparative Genomic Hybridization.

Blood ◽  
2005 ◽  
Vol 106 (11) ◽  
pp. 759-759
Author(s):  
Frank G. Rucker ◽  
Lars Bullinger ◽  
Hans A. Kestler ◽  
Peter Lichter ◽  
Konstanze Dohner ◽  
...  
Keyword(s):  
Molecular Markers ◽  
High Resolution ◽  
Comparative Genomic Hybridization ◽  
Copy Number ◽  
Normal Karyotype ◽  
Comparative Genomic ◽  
Copy Number Alterations ◽  
Genomic Hybridization ◽  
Genomic Imbalances ◽  
Genome Wide

Abstract Clonal chromosome abnormalities represent one of the most important prognostic factors in adult acute myeloid leukemia (AML), and cytogenetic data are used for risk-adapted treatment strategies. By conventional cytogenetic analysis, approximately 50% of patients lack clonal chromosome aberrations, and normal cytogenetics are associated with an intermediate clinical outcome. This clinically heterogeneous group seems to be in part characterized by molecular markers, such as MLL, FLT3, CEBPA, and NPM1 mutations. In order to identify novel candidate regions of genomic imbalances, we applied comparative genomic hybridization to microarrays (matrix-CGH). Using this high-resolution genome-wide screening approach we analyzed 49 normal karyotype AML cases characterized for the most common clinically relevant molecular markers (MLL-PTD n=13, FLT3-ITD n=7, FLT3-ITD/NPM1+ n=4, MLL-PTD/FLT3-ITD n=3, CEBPA+ n=12, CEBPA+/FLT3-ITD n=1; CEBPA+/NPM1+ n=1; no molecular markers n=8) with a microarray platform consisting of 2799 different BAC or PAC clones. A set of 1500 of these clones covers the whole human genome with a physical distance of approximately 2 Mb. The remaining 1299 clones either contiguously span genomic regions known to be frequently involved in hematologic malignancies (e.g., 1p, 2p, 3q, 7q, 9p, 11q, 12q, 13q, 17p, 18q) (n=600) or contain oncogenes or tumor suppressor genes (n=699). In addition to known copy number polymorphisms in 5q11, 7q22, 7q35, 14q32, and 15q11, the CLuster Along Chromosomes method (CLAC; http://www-stat.stanford.edu/~wp57/CGH-Miner) disclosed copy number alterations (CNAs) in terms of gains in 1p, 11q, 12q, and 17p. CNAs in terms of losses were identified in 9p, 11q, 12p, 12q, and 13q. Two-class supervised analyses using the significance analysis of microarrays (SAM) method identified for the MLL-PTD cases a gain of a single clone harboring the MLL gene. While the significance of these findings, which are currently validated using fluorescence in-situ hybridization (FISH), still remains to be determined, our preliminary results already demonstrate the power and reliablity of this microarray-based technique allowing genome-wide screens of genomic imbalances as the MLL aberration was detected in all cases known to have a MLL-PTD. Furthermore, ongoing correlation of high-resolution genomic profiling with global gene expression studies will help to disclose pathways underlying normal karyotype AML, thereby leading to new insights of leukemogenesis.

scholarly journals A machine learning model for ranking candidate HLA class I neoantigens based on known neoepitopes from multiple human tumor types

Nature Cancer ◽  
2021 ◽  
Author(s):  
Jared J. Gartner ◽  
Maria R. Parkhurst ◽  
Alena Gros ◽  
Eric Tran ◽  
Mohammad S. Jafferji ◽  
...  
Keyword(s):  
Machine Learning ◽  
Human Tumor ◽  
Hla Class I ◽  
Learning Model ◽  
Class I ◽  
Machine Learning Model ◽  
Tumor Types

scholarly journals Mutant allele specific imbalance in oncogenes with copy number alterations: Occurrence, mechanisms, and potential clinical implications

2017 ◽  
Vol 384 ◽  
pp. 86-93 ◽  
Author(s):  
Chih-Chieh Yu ◽  
Wanglong Qiu ◽  
Caroline S. Juang ◽  
Mahesh M. Mansukhani ◽  
Balazs Halmos ◽  
...  
Keyword(s):  
Copy Number ◽  
Mutant Allele ◽  
Clinical Implications ◽  
Copy Number Alterations ◽  
Allele Specific

scholarly journals Functional Exploration of Copy Number Alterations in a Drosophila Model of Triple Negative Breast Cancer

2020 ◽  
Author(s):  
Jennifer E. L. Diaz ◽  
Vanessa Barcessat ◽  
Christian Bahamon ◽  
Ross L. Cagan
Keyword(s):  
Breast Cancer ◽  
Copy Number ◽  
Triple Negative ◽  
Standard Of Care ◽  
Chemotherapeutic Drug ◽  
Copy Number Alterations ◽  
Drosophila Model ◽  
Genetic Complexity ◽  
Disproportionate Number ◽  
Tumor Types

AbstractAccounting for 10-20% of breast cancer cases, TNBC is associated with a disproportionate number of breast cancer deaths. Despite recent progress, many patients fail to respond to current targeted therapies. Responses to chemotherapy are variable, and the tumor characteristics that determine response are poorly understood. One challenge in studying TNBC is its genomic profile: outside of TP53 loss, most cases are characterized by copy number alterations (CNAs), making modeling the disease in whole animals challenging. We analyzed 186 previously identified CNA regions in breast cancer to rank genes within each region by likelihood of acting as a tumor driver. We characterized a Drosophila p53-Myc model of TNBC, demonstrating aspects of transformation. We then used this model to assess highly ranked genes, identifying 48 as functional drivers. To demonstrate the utility of this functional database, we combined six of these drivers with p53-Myc to generate six 3-hit genotypes. These 3-hit models showed increased aspects of transformation as well as resistance to the standard-of-care chemotherapeutic drug fluorouracil. Our work provides a functional database of CNA-associated TNBC drivers, and uses this database to support the model that increased genetic complexity leads to increased therapeutic resistance. Further, we provide a template for an integrated computational/whole animal approach to identify functional drivers of transformation and drug resistance within CNAs for other tumor types.

scholarly journals Author response: CNApp, a tool for the quantification of copy number alterations and integrative analysis revealing clinical implications

2020 ◽  
Author(s):  
Sebastià Franch-Expósito ◽  
Laia Bassaganyas ◽  
Maria Vila-Casadesús ◽  
Eva Hernández-Illán ◽  
Roger Esteban-Fabró ◽  
...  
Keyword(s):  
Copy Number ◽  
Integrative Analysis ◽  
Author Response ◽  
Clinical Implications ◽  
Copy Number Alterations

Ultrastructure of two neoplasms in culture compared with original biopsies

1984 ◽  
Vol 42 ◽  
pp. 50-51
Author(s):  
Joseph M. Harb ◽  
James T. Casper ◽  
Vlcki Piaskowski
Keyword(s):  
Electron Microscopy ◽  
Tissue Culture ◽  
Biopsy Specimen ◽  
Cultured Cells ◽  
Light And Electron Microscopy ◽  
Human Tumor ◽  
Soft Agar ◽  
Human Tumor Cells ◽  
Morphological Distinction ◽  
Tumor Types

The application of tissue culture and the newer methodologies of direct cloning and colony formation of human tumor cells in soft agar hold promise as valuable modalities for a variety of diagnostic studies, which include morphological distinction between tumor types by electron microscopy (EM). We present here two cases in which cells in culture expressed distinct morphological features not apparent in the original biopsy specimen. Evaluation of the original biopsies by light and electron microscopy indicated both neoplasms to be undifferentiated sarcomas. Colonies of cells propagated in soft agar displayed features of rhabdomyoblasts in one case, and cultured cells of the second biopsy expressed features of Ewing's sarcoma.

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

2012 ◽  
Vol 32 (1) ◽  
pp. 5-9 ◽  
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

scholarly journals EPCO-29. EPIGENOMICS OF THE GLIOMA LONGITUDINAL ANALYSIS (GLASS) CONSORTIUM

2020 ◽  
Vol 22 (Supplement_2) ◽  
pp. ii75-ii75
Author(s):  
Thais Sabedot ◽  
Michael Wells ◽  
Indrani Datta ◽  
Tathiane Malta ◽  
Ana Valeria Castro ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Longitudinal Analysis ◽  
Copy Number ◽  
Large Scale ◽  
Molecular Classification ◽  
Tumor Burden ◽  
Copy Number Alterations ◽  
Unsupervised Analysis ◽  
Diffuse Gliomas ◽  
New Biomarkers

Abstract Adult diffuse gliomas are central nervous system (CNS) tumors that arise from the malignant transformation of glial cells. Nearly all gliomas will recur despite standard treatment however, current histopathological grading fails to predict which of them will relapse and/or progress. The Glioma Longitudinal AnalySiS (GLASS) consortium is a large-scale collaboration that aims to investigate the molecular profiling of matched primary and recurrent glioma samples from multiple institutions in order to better understand the dynamic evolution of these tumors. At this time, the cohort comprises 946 samples across 11 institutions and among those, 864 have DNA methylation data available. The current molecular classification based on 7 subtypes published by TCGA in 2016 was applied to the dataset. Among the IDH wildtype tumors, 33% (16/49) of the patients showed a change of subtype upon recurrence, whereas most of them (9/16) were Classic-like at the primary stage but changed to either Mesenchymal-like or PA-like at the recurrent level. Among the IDH mutant tumors, 15% (22/142) showed a change of subtype at recurrent stage, in which 16 out of 22 progressed from G-CIMP-high to G-CIMP-low. Although some tumors progressed to a different subtype upon recurrence, an unsupervised analysis showed that the samples tend to cluster by patient instead of by subtype. By estimating the copy number alterations of these tumors using DNA methylation, the overall copy number profile of the recurrent samples remains similar to their primary counterpart. From this initial analysis using epigenomic data, we were able to characterize some aspects of glioma evolution and how the DNA methylation is associated with the progression of these tumors to different subtypes. These findings corroborate the importance of epigenetics in gliomas and can potentially lead to the identification of new biomarkers that can reflect tumor burden and predict its development.

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