1
|
Palaniappan A, Muthamilselvan S, Sarathi A. COADREADx: A comprehensive algorithmic dissection of colorectal cancer unravels salient biomarkers and actionable insights into its discrete progression. PeerJ 2024; 12:e18347. [PMID: 39484215 PMCID: PMC11526798 DOI: 10.7717/peerj.18347] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2024] [Accepted: 09/27/2024] [Indexed: 11/03/2024] Open
Abstract
Background Colorectal cancer is a common condition with an uncommon burden of disease, heterogeneity in manifestation, and no definitive treatment in the advanced stages. Renewed efforts to unravel the genetic drivers of colorectal cancer progression are paramount. Early-stage detection contributes to the success of cancer therapy and increases the likelihood of a favorable prognosis. Here, we have executed a comprehensive computational workflow aimed at uncovering the discrete stagewise genomic drivers of colorectal cancer progression. Methods Using the TCGA COADREAD expression data and clinical metadata, we constructed stage-specific linear models as well as contrast models to identify stage-salient differentially expressed genes. Stage-salient differentially expressed genes with a significant monotone trend of expression across the stages were identified as progression-significant biomarkers. The stage-salient genes were benchmarked using normals-augmented dataset, and cross-referenced with existing knowledge. The candidate biomarkers were used to construct the feature space for learning an optimal model for the digital screening of early-stage colorectal cancers. The candidate biomarkers were also examined for constructing a prognostic model based on survival analysis. Results Among the biomarkers identified are: CRLF1, CALB2, STAC2, UCHL1, KCNG1 (stage-I salient), KLHL34, LPHN3, GREM2, ADCY5, PLAC2, DMRT3 (stage-II salient), PIGR, HABP2, SLC26A9 (stage-III salient), GABRD, DKK1, DLX3, CST6, HOTAIR (stage-IV salient), and CDH3, KRT80, AADACL2, OTOP2, FAM135B, HSP90AB1 (top linear model genes). In particular the study yielded 31 genes that are progression-significant such as ESM1, DKK1, SPDYC, IGFBP1, BIRC7, NKD1, CXCL13, VGLL1, PLAC1, SPERT, UPK2, and interestingly three members of the LY6G6 family. Significant monotonic linear model genes included HIGD1A, ACADS, PEX26, and SPIB. A feature space of just seven biomarkers, namely ESM1, DHRS7C, OTOP3, AADACL2, LPHN3, GABRD, and LPAR1, was sufficient to optimize a RandomForest model that achieved > 98% balanced accuracy (and performant recall) of cancer vs. normal on external validation. Design of an optimal multivariate model based on survival analysis yielded a prognostic panel of three stage-IV salient genes, namely HOTAIR, GABRD, and DKK1. Based on the above sparse signatures, we have developed COADREADx, a web-server for potentially assisting colorectal cancer screening and patient risk stratification. COADREADx provides uncertainty measures for its predictions and needs clinical validation. It has been deployed for experimental non-commercial use at: https://apalanialab.shinyapps.io/coadreadx/.
Collapse
Affiliation(s)
- Ashok Palaniappan
- Systems Computational Biology Lab, Department of Bioinformatics, School of Chemical and Biotechnology, SASTRA Deemed University, Thanjavur, Tamil Nadu, India
| | - Sangeetha Muthamilselvan
- Systems Computational Biology Lab, Department of Bioinformatics, School of Chemical and Biotechnology, SASTRA Deemed University, Thanjavur, Tamil Nadu, India
| | - Arjun Sarathi
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| |
Collapse
|
2
|
Mastromatteo S, Chen A, Gong J, Lin F, Thiruvahindrapuram B, Sung WW, Whitney J, Wang Z, Patel RV, Keenan K, Halevy A, Panjwani N, Avolio J, Wang C, Côté-Maurais G, Bégin S, Adam D, Brochiero E, Bjornson C, Chilvers M, Price A, Parkins M, van Wylick R, Mateos-Corral D, Hughes D, Smith MJ, Morrison N, Tullis E, Stephenson AL, Wilcox P, Quon BS, Leung WM, Solomon M, Sun L, Ratjen F, Strug LJ. High-quality read-based phasing of cystic fibrosis cohort informs genetic understanding of disease modification. HGG ADVANCES 2023; 4:100156. [PMID: 36386424 PMCID: PMC9647008 DOI: 10.1016/j.xhgg.2022.100156] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Accepted: 10/13/2022] [Indexed: 11/06/2022] Open
Abstract
Phasing of heterozygous alleles is critical for interpretation of cis-effects of disease-relevant variation. We sequenced 477 individuals with cystic fibrosis (CF) using linked-read sequencing, which display an average phase block N50 of 4.39 Mb. We use these samples to construct a graph representation of CFTR haplotypes, demonstrating its utility for understanding complex CF alleles. These are visualized in a Web app, CFTbaRcodes, that enables interactive exploration of CFTR haplotypes present in this cohort. We perform fine-mapping and phasing of the chr7q35 trypsinogen locus associated with CF meconium ileus, an intestinal obstruction at birth associated with more severe CF outcomes and pancreatic disease. A 20-kb deletion polymorphism and a PRSS2 missense variant p.Thr8Ile (rs62473563) are shown to independently contribute to meconium ileus risk (p = 0.0028, p = 0.011, respectively) and are PRSS2 pancreas eQTLs (p = 9.5 × 10−7 and p = 1.4 × 10−4, respectively), suggesting the mechanism by which these polymorphisms contribute to CF. The phase information from linked reads provides a putative causal explanation for variation at a CF-relevant locus, which also has implications for the genetic basis of non-CF pancreatitis, to which this locus has been reported to contribute.
Collapse
|
3
|
Abstract
BACKGROUND Few previous published papers reported copy number variations of genes could affect the predisposition of Graves' disease (GD). Herein, the aim of this study was to explore the association between copy number variations (CNV) profile and GD. METHODS The preliminary copy number microarray used to screen copy number variant genes was performed in 6 GD patients. Five CNV candidate genes (CFH, CFHR1, KIAA0125, UGT2B15, and UGT2B17) were then validated in an independent set of samples (50 GD patients and 50 matched healthy ones) by the Accucopy assay method. The CNV of the other 2 genes TRY6 and CCL3L1 was investigated in 144 GD patients and 144 healthy volunteers by the definitive genotyping technique using the Taqman quantitative polymerase-chain-reaction (Taqman qPCR). TRY6 gene-associated single nucleotide polymorphism (SNP), rs13230029, was genotyped by the PCR-ligase detection reaction (LDR) in 675 GD patients and 898 healthy controls. RESULTS There were no correlation of the gene copy number (GCN) of CFH, CFHR1, KIAA0125, UGT2B15, and UGT2B17 with GD. In comparison with that of controls, the GCN distribution of TRY6 and CCL3L1 in GD patients did not show significantly differ (P > 0.05). Furthermore, TRY6-related polymorphism (rs13230029) showed no difference between GD patients and controls. No correlation was found between CNV or SNP genotype and clinical phenotypes. Generally, there were no link of the copy numbers of several genes, including CFH, CFHR1, KIAA0125, UGT2B15, UGT2B17, TRY6, and CCL3L1 to GD. CONCLUSION Our results clearly indicated that the copy number variations of multiple genes, namely CFH, CFHR1, KIAA0125, UGT2B15, UGT2B17, TRY6, and CCL3L1, were not associated with the development of GD.
Collapse
|
5
|
Kurian AW, Hare EE, Mills MA, Kingham KE, McPherson L, Whittemore AS, McGuire V, Ladabaum U, Kobayashi Y, Lincoln SE, Cargill M, Ford JM. Clinical evaluation of a multiple-gene sequencing panel for hereditary cancer risk assessment. J Clin Oncol 2014; 32:2001-9. [PMID: 24733792 PMCID: PMC4067941 DOI: 10.1200/jco.2013.53.6607] [Citation(s) in RCA: 382] [Impact Index Per Article: 34.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
PURPOSE Multiple-gene sequencing is entering practice, but its clinical value is unknown. We evaluated the performance of a customized germline-DNA sequencing panel for cancer-risk assessment in a representative clinical sample. METHODS Patients referred for clinical BRCA1/2 testing from 2002 to 2012 were invited to donate a research blood sample. Samples were frozen at -80° C, and DNA was extracted from them after 1 to 10 years. The entire coding region, exon-intron boundaries, and all known pathogenic variants in other regions were sequenced for 42 genes that had cancer risk associations. Potentially actionable results were disclosed to participants. RESULTS In total, 198 women participated in the study: 174 had breast cancer and 57 carried germline BRCA1/2 mutations. BRCA1/2 analysis was fully concordant with prior testing. Sixteen pathogenic variants were identified in ATM, BLM, CDH1, CDKN2A, MUTYH, MLH1, NBN, PRSS1, and SLX4 among 141 women without BRCA1/2 mutations. Fourteen participants carried 15 pathogenic variants, warranting a possible change in care; they were invited for targeted screening recommendations, enabling early detection and removal of a tubular adenoma by colonoscopy. Participants carried an average of 2.1 variants of uncertain significance among 42 genes. CONCLUSION Among women testing negative for BRCA1/2 mutations, multiple-gene sequencing identified 16 potentially pathogenic mutations in other genes (11.4%; 95% CI, 7.0% to 17.7%), of which 15 (10.6%; 95% CI, 6.5% to 16.9%) prompted consideration of a change in care, enabling early detection of a precancerous colon polyp. Additional studies are required to quantify the penetrance of identified mutations and determine clinical utility. However, these results suggest that multiple-gene sequencing may benefit appropriately selected patients.
Collapse
Affiliation(s)
- Allison W Kurian
- Allison W. Kurian, Meredith A. Mills, Kerry E. Kingham, Lisa McPherson, Alice S. Whittemore, Valerie McGuire, Uri Ladabaum, James M. Ford, Stanford University School of Medicine, Stanford; Emily E. Hare, Yuya Kobayashi, Stephen E. Lincoln, Michele Cargill, InVitae, San Francisco, CA
| | - Emily E Hare
- Allison W. Kurian, Meredith A. Mills, Kerry E. Kingham, Lisa McPherson, Alice S. Whittemore, Valerie McGuire, Uri Ladabaum, James M. Ford, Stanford University School of Medicine, Stanford; Emily E. Hare, Yuya Kobayashi, Stephen E. Lincoln, Michele Cargill, InVitae, San Francisco, CA
| | - Meredith A Mills
- Allison W. Kurian, Meredith A. Mills, Kerry E. Kingham, Lisa McPherson, Alice S. Whittemore, Valerie McGuire, Uri Ladabaum, James M. Ford, Stanford University School of Medicine, Stanford; Emily E. Hare, Yuya Kobayashi, Stephen E. Lincoln, Michele Cargill, InVitae, San Francisco, CA
| | - Kerry E Kingham
- Allison W. Kurian, Meredith A. Mills, Kerry E. Kingham, Lisa McPherson, Alice S. Whittemore, Valerie McGuire, Uri Ladabaum, James M. Ford, Stanford University School of Medicine, Stanford; Emily E. Hare, Yuya Kobayashi, Stephen E. Lincoln, Michele Cargill, InVitae, San Francisco, CA
| | - Lisa McPherson
- Allison W. Kurian, Meredith A. Mills, Kerry E. Kingham, Lisa McPherson, Alice S. Whittemore, Valerie McGuire, Uri Ladabaum, James M. Ford, Stanford University School of Medicine, Stanford; Emily E. Hare, Yuya Kobayashi, Stephen E. Lincoln, Michele Cargill, InVitae, San Francisco, CA
| | - Alice S Whittemore
- Allison W. Kurian, Meredith A. Mills, Kerry E. Kingham, Lisa McPherson, Alice S. Whittemore, Valerie McGuire, Uri Ladabaum, James M. Ford, Stanford University School of Medicine, Stanford; Emily E. Hare, Yuya Kobayashi, Stephen E. Lincoln, Michele Cargill, InVitae, San Francisco, CA
| | - Valerie McGuire
- Allison W. Kurian, Meredith A. Mills, Kerry E. Kingham, Lisa McPherson, Alice S. Whittemore, Valerie McGuire, Uri Ladabaum, James M. Ford, Stanford University School of Medicine, Stanford; Emily E. Hare, Yuya Kobayashi, Stephen E. Lincoln, Michele Cargill, InVitae, San Francisco, CA
| | - Uri Ladabaum
- Allison W. Kurian, Meredith A. Mills, Kerry E. Kingham, Lisa McPherson, Alice S. Whittemore, Valerie McGuire, Uri Ladabaum, James M. Ford, Stanford University School of Medicine, Stanford; Emily E. Hare, Yuya Kobayashi, Stephen E. Lincoln, Michele Cargill, InVitae, San Francisco, CA
| | - Yuya Kobayashi
- Allison W. Kurian, Meredith A. Mills, Kerry E. Kingham, Lisa McPherson, Alice S. Whittemore, Valerie McGuire, Uri Ladabaum, James M. Ford, Stanford University School of Medicine, Stanford; Emily E. Hare, Yuya Kobayashi, Stephen E. Lincoln, Michele Cargill, InVitae, San Francisco, CA
| | - Stephen E Lincoln
- Allison W. Kurian, Meredith A. Mills, Kerry E. Kingham, Lisa McPherson, Alice S. Whittemore, Valerie McGuire, Uri Ladabaum, James M. Ford, Stanford University School of Medicine, Stanford; Emily E. Hare, Yuya Kobayashi, Stephen E. Lincoln, Michele Cargill, InVitae, San Francisco, CA
| | - Michele Cargill
- Allison W. Kurian, Meredith A. Mills, Kerry E. Kingham, Lisa McPherson, Alice S. Whittemore, Valerie McGuire, Uri Ladabaum, James M. Ford, Stanford University School of Medicine, Stanford; Emily E. Hare, Yuya Kobayashi, Stephen E. Lincoln, Michele Cargill, InVitae, San Francisco, CA
| | - James M Ford
- Allison W. Kurian, Meredith A. Mills, Kerry E. Kingham, Lisa McPherson, Alice S. Whittemore, Valerie McGuire, Uri Ladabaum, James M. Ford, Stanford University School of Medicine, Stanford; Emily E. Hare, Yuya Kobayashi, Stephen E. Lincoln, Michele Cargill, InVitae, San Francisco, CA.
| |
Collapse
|