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Gowthami J, Gururaj N, Mahalakshmi V, Sathya R, Sabarinath TR, Doss DM. Genetic predisposition and prediction protocol for epithelial neoplasms in disease-free individuals: A systematic review. J Oral Maxillofac Pathol 2020; 24:293-307. [PMID: 33456239 PMCID: PMC7802851 DOI: 10.4103/jomfp.jomfp_348_19] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2019] [Revised: 03/23/2020] [Accepted: 04/24/2020] [Indexed: 01/13/2023] Open
Abstract
Background Epithelial neoplasm is an important global health-care problem, with high morbidity and mortality rates. Early diagnosis and appropriate treatment are essential for increased life survival. Prediction of occurrence of malignancy in a disease-free individual by any means will be a great breakthrough for healthy living. Aims and Objectives The aims and objectives were to predict the genetic predisposition and propose a prediction protocol for epithelial malignancy of various systems in our body, in a disease-free individual. Methods We have searched databases both manually and electronically, published in English language in Cochrane group, Google search, MEDLINE and PubMed from 2000 to 2019. We have included all the published, peer-reviewed, narrative reviews; randomized controlled trials; case-control studies; and cohort studies and excluded the abstract-only articles and duplicates. Specific words such as "etiological factors," "pathology and mutations," "signs and symptoms," "genetics and IHC marker," and "treatment outcome" were used for the search. A total of 1032 citations were taken, and only 141 citations met the inclusion criteria and were analyzed. Results After analyzing various articles, the etiological factors, clinical signs and symptoms, genes and the pathology involved and the commonly used blood and tissue markers were analyzed. A basic investigation strategy using immunohistochemistry markers was established. Conclusion The set of proposed biomarkers should be studied in future to predict genetic predisposition in disease-free individuals.
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Affiliation(s)
- J Gowthami
- Department of Oral and Maxillofacial Pathology and Microbiology, CSI College of Dental Sciences and Research, Madurai, Tamil Nadu, India
| | - N Gururaj
- Department of Oral and Maxillofacial Pathology and Microbiology, CSI College of Dental Sciences and Research, Madurai, Tamil Nadu, India
| | - V Mahalakshmi
- Department of Oral and Maxillofacial Pathology and Microbiology, CSI College of Dental Sciences and Research, Madurai, Tamil Nadu, India
| | - R Sathya
- Department of Oral and Maxillofacial Pathology and Microbiology, CSI College of Dental Sciences and Research, Madurai, Tamil Nadu, India
| | - T R Sabarinath
- Department of Oral and Maxillofacial Pathology and Microbiology, CSI College of Dental Sciences and Research, Madurai, Tamil Nadu, India
| | - Daffney Mano Doss
- Department of Oral and Maxillofacial Pathology and Microbiology, CSI College of Dental Sciences and Research, Madurai, Tamil Nadu, India
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Montaudon E, Nikitorowicz-Buniak J, Sourd L, Morisset L, El Botty R, Huguet L, Dahmani A, Painsec P, Nemati F, Vacher S, Chemlali W, Masliah-Planchon J, Château-Joubert S, Rega C, Leal MF, Simigdala N, Pancholi S, Ribas R, Nicolas A, Meseure D, Vincent-Salomon A, Reyes C, Rapinat A, Gentien D, Larcher T, Bohec M, Baulande S, Bernard V, Decaudin D, Coussy F, Le Romancer M, Dutertre G, Tariq Z, Cottu P, Driouch K, Bièche I, Martin LA, Marangoni E. PLK1 inhibition exhibits strong anti-tumoral activity in CCND1-driven breast cancer metastases with acquired palbociclib resistance. Nat Commun 2020; 11:4053. [PMID: 32792481 PMCID: PMC7426966 DOI: 10.1038/s41467-020-17697-1] [Citation(s) in RCA: 76] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2019] [Accepted: 07/16/2020] [Indexed: 02/08/2023] Open
Abstract
A significant proportion of patients with oestrogen receptor (ER) positive breast cancers (BC) develop resistance to endocrine treatments (ET) and relapse with metastatic disease. Here we perform whole exome sequencing and gene expression analysis of matched primary breast tumours and bone metastasis-derived patient-derived xenografts (PDX). Transcriptomic analyses reveal enrichment of the G2/M checkpoint and up-regulation of Polo-like kinase 1 (PLK1) in PDX. PLK1 inhibition results in tumour shrinkage in highly proliferating CCND1-driven PDX, including different RB-positive PDX with acquired palbociclib resistance. Mechanistic studies in endocrine resistant cell lines, suggest an ER-independent function of PLK1 in regulating cell proliferation. Finally, in two independent clinical cohorts of ER positive BC, we find a strong association between high expression of PLK1 and a shorter metastases-free survival and poor response to anastrozole. In conclusion, our findings support clinical development of PLK1 inhibitors in patients with advanced CCND1-driven BC, including patients progressing on palbociclib treatment.
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Affiliation(s)
- Elodie Montaudon
- Translational Research Department, Institut Curie, 26 Rue d'Ulm, 75005, Paris, France
| | | | - Laura Sourd
- Translational Research Department, Institut Curie, 26 Rue d'Ulm, 75005, Paris, France
| | - Ludivine Morisset
- Translational Research Department, Institut Curie, 26 Rue d'Ulm, 75005, Paris, France
| | - Rania El Botty
- Translational Research Department, Institut Curie, 26 Rue d'Ulm, 75005, Paris, France
| | - Léa Huguet
- Translational Research Department, Institut Curie, 26 Rue d'Ulm, 75005, Paris, France
| | - Ahmed Dahmani
- Translational Research Department, Institut Curie, 26 Rue d'Ulm, 75005, Paris, France
| | - Pierre Painsec
- Translational Research Department, Institut Curie, 26 Rue d'Ulm, 75005, Paris, France
| | - Fariba Nemati
- Translational Research Department, Institut Curie, 26 Rue d'Ulm, 75005, Paris, France
| | - Sophie Vacher
- Department of Genetics, Institut Curie, Paris, France
| | | | | | | | - Camilla Rega
- Institute of Cancer Research, 123 Old Brompton Road, SW7 3RP, London, UK
| | | | - Nikiana Simigdala
- Institute of Cancer Research, 123 Old Brompton Road, SW7 3RP, London, UK
| | - Sunil Pancholi
- Institute of Cancer Research, 123 Old Brompton Road, SW7 3RP, London, UK
| | - Ricardo Ribas
- Institute of Cancer Research, 123 Old Brompton Road, SW7 3RP, London, UK
| | - André Nicolas
- Department of Pathology, Institut Curie, Paris, France
| | | | | | - Cécile Reyes
- Translational Research Department, Institut Curie, 26 Rue d'Ulm, 75005, Paris, France
| | - Audrey Rapinat
- Translational Research Department, Institut Curie, 26 Rue d'Ulm, 75005, Paris, France
| | - David Gentien
- Translational Research Department, Institut Curie, 26 Rue d'Ulm, 75005, Paris, France
| | - Thibaut Larcher
- INRA, APEX-PAnTher, Oniris, Rue De La Géraudière Cedex 3, 44322, Nantes, France
| | - Mylène Bohec
- Genomics of Excellence (ICGex) Platform, Institut Curie Research Center, Paris, France
| | - Sylvain Baulande
- Genomics of Excellence (ICGex) Platform, Institut Curie Research Center, Paris, France
| | | | - Didier Decaudin
- Translational Research Department, Institut Curie, 26 Rue d'Ulm, 75005, Paris, France
- Department of Medical Oncology, Institut Curie, Paris, France
| | - Florence Coussy
- Translational Research Department, Institut Curie, 26 Rue d'Ulm, 75005, Paris, France
- Department of Medical Oncology, Institut Curie, Paris, France
| | - Muriel Le Romancer
- Inserm U1052, Centre de Recherche en Cancérologie de Lyon, 28 Rue Laennec, 69000, Lyon, France
| | | | - Zakia Tariq
- Department of Genetics, Institut Curie, Paris, France
| | - Paul Cottu
- Department of Medical Oncology, Institut Curie, Paris, France
| | | | - Ivan Bièche
- Department of Genetics, Institut Curie, Paris, France
| | - Lesley-Ann Martin
- Institute of Cancer Research, 123 Old Brompton Road, SW7 3RP, London, UK
| | - Elisabetta Marangoni
- Translational Research Department, Institut Curie, 26 Rue d'Ulm, 75005, Paris, France.
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Buechler SA, Stephens MT, Hummon AB, Ludwig K, Cannon E, Carter TC, Resnick J, Gökmen-Polar Y, Badve SS. ColoType: a forty gene signature for consensus molecular subtyping of colorectal cancer tumors using whole-genome assay or targeted RNA-sequencing. Sci Rep 2020; 10:12123. [PMID: 32694712 PMCID: PMC7374173 DOI: 10.1038/s41598-020-69083-y] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2020] [Accepted: 07/03/2020] [Indexed: 01/02/2023] Open
Abstract
Colorectal cancer (CRC) tumors can be partitioned into four biologically distinct consensus molecular subtypes (CMS1-4) using gene expression. Evidence is accumulating that tumors in different subtypes are likely to respond differently to treatments. However, to date, there is no clinical diagnostic test for CMS subtyping. In this study, we used novel methodology in a multi-cohort training domain (n = 1,214) to develop the ColoType scores and classifier to predict CMS1-4 based on expression of 40 genes. In three validation cohorts (n = 1,744, in total) representing three distinct gene-expression measurement technologies, ColoType predicted gold-standard CMS subtypes with accuracies 0.90, 0.91, 0.88, respectively. To accommodate for potential intratumoral heterogeneity and tumors of mixed subtypes, ColoType was designed to report continuous scores measuring the prevalence of each of CMS1-4 in a tumor, in addition to specifying the most prevalent subtype. For analysis of clinical specimens, ColoType was also implemented with targeted RNA-sequencing (Illumina AmpliSeq). In a series of formalin-fixed, paraffin-embedded CRC samples (n = 49), ColoType by targeted RNA-sequencing agreed with subtypes predicted by two independent methods with accuracies 0.92, 0.82, respectively. With further validation, ColoType by targeted RNA-sequencing, may enable clinical application of CMS subtyping with widely-available and cost-effective technology.
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Affiliation(s)
- Steven A Buechler
- Department of Applied and Computational Mathematics and Statistics, Harper Cancer Research Institute, University of Notre Dame, 102B Crowley Hall, Notre Dame, IN, 46556, USA.
| | - Melissa T Stephens
- Genomics and Bioinformatics Core Facility, University of Notre Dame, Notre Dame, IN, USA
| | - Amanda B Hummon
- Department of Chemistry and Biochemistry, Comprehensive Cancer Center, The Ohio State University, Columbus, OH, USA
| | - Katelyn Ludwig
- Functional Genetics Section, Genetics Branch, Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA
| | - Emily Cannon
- Department of Applied and Computational Mathematics and Statistics, Harper Cancer Research Institute, University of Notre Dame, 102B Crowley Hall, Notre Dame, IN, 46556, USA
| | - Tonia C Carter
- Center for Precision Medicine Research, Marshfield Clinic, Marshfield, WI, USA
| | - Jeffrey Resnick
- Department of Pathology, Marshfield Clinic, Marshfield, WI, USA
| | - Yesim Gökmen-Polar
- Department of Pathology and Laboratory Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Sunil S Badve
- Department of Pathology and Laboratory Medicine, Indiana University School of Medicine, Indianapolis, IN, USA.,Indiana University Melvin and Bren Simon Cancer Center, Indianapolis, IN, USA
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4
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Identification of a prognostic LncRNA signature for ER-positive, ER-negative and triple-negative breast cancers. Breast Cancer Res Treat 2020; 183:95-105. [PMID: 32601968 DOI: 10.1007/s10549-020-05770-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2019] [Accepted: 06/23/2020] [Indexed: 12/20/2022]
Abstract
PURPOSE The development of multi-gene signatures has led to improvements in identification of breast cancer patients at high risk of recurrence. The prognostic power of commercially available gene signatures is mostly restricted to estrogen receptor (ER)-positive breast cancer. On the contrary, immune-related gene signatures predict prognosis only in ER-negative breast cancer. This study aimed to develop a better prognostic signature for breast cancer. METHODS The expressions of long non-coding RNA (lncRNA) genes from 30 independent microarray datasets with a total of 4813 samples were analyzed. A prognostic lncRNA signature was developed based on likelihood-ratio Cox regression analysis. Survival analysis was used to compare the prognostic efficiencies of our signature and 10 previously reported prognostic gene signatures. RESULTS Cox regression analysis on 30 independent datasets showed that the 6-lncRNA signature identified in this study performed as well as five commercially available signatures in recurrence prediction for ER-positive breast cancer. In ER-negative breast cancer, this lncRNA signature was as prognostic as three immune-related gene signatures. Moreover, our lncRNA signature also demonstrated a good capacity to predict recurrence risk for triple-negative breast cancer. Function analysis showed that several lncRNAs in this signature were probably involved in cell proliferation and immune processes. CONCLUSIONS A six-LncRNA signature was identified that is prognostic for ER-positive, ER-negative, and triple-negative breast cancers and thus deserves further validation in prospective studies.
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5
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Buechler SA, Gray KP, Gökmen-Polar Y, Willis S, Thürlimann B, Kammler R, Viale G, Leyland-Jones B, Badve SS, Regan MM. Independent Validation of EarlyR Gene Signature in BIG 1-98: A Randomized, Double-Blind, Phase III Trial Comparing Letrozole and Tamoxifen as Adjuvant Endocrine Therapy for Postmenopausal Women With Hormone Receptor-Positive, Early Breast Cancer. JNCI Cancer Spectr 2019; 3:pkz051. [PMID: 32337480 PMCID: PMC7049990 DOI: 10.1093/jncics/pkz051] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2018] [Revised: 05/11/2019] [Accepted: 07/22/2019] [Indexed: 11/12/2022] Open
Abstract
Background EarlyR gene signature in estrogen receptor–positive (ER+) breast cancer is computed from the expression values of ESPL1, SPAG5, MKI67, PLK1, and PGR. EarlyR has been validated in multiple cohorts profiled using microarrays. This study sought to verify the prognostic features of EarlyR in a case-cohort sample from BIG 1–98, a randomized clinical trial of ER+ postmenopausal breast cancer patients treated with adjuvant endocrine therapy (letrozole or tamoxifen). Methods Expression of EarlyR gene signature was estimated by Illumina cDNA-mediated Annealing, Selection, and Ligation assay of RNA from formalin-fixed, paraffin-embedded primary breast cancer tissues in a case-cohort subset of ER+ women (N = 1174; 216 cases of recurrence within 8 years) from BIG 1–98. EarlyR score and prespecified risk strata (≤25 = low, 26–75 = intermediate, >75 = high) were “blindly” computed. Analysis endpoints included distant recurrence–free interval and breast cancer–free interval at 8 years after randomization. Hazard ratios (HRs) and test statistics were estimated with weighted analysis methods. Results The distribution of the EarlyR risk groups was 67% low, 19% intermediate, and 14% high risk in this ER+ cohort. EarlyR was prognostic for distant recurrence–free interval; EarlyR high-risk patients had statistically increased risk of distant recurrence within 8 years (HR = 1.73, 95% confidence interval = 1.14 to 2.64) compared with EarlyR low-risk patients. EarlyR was also prognostic of breast cancer–free interval (HR = 1.74, 95% confidence interval = 1.21 to 2.62). Conclusions This study confirmed the prognostic significance of EarlyR using RNA from formalin-fixed, paraffin-embedded tissues from a case-cohort sample of BIG 1–98. EarlyR identifies a set of high-risk patients with relatively poor prognosis who may be considered for additional treatment. Further studies will focus on analyzing the predictive value of EarlyR signature.
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Affiliation(s)
- Steven A Buechler
- University of Notre Dame, Notre Dame, IN.,Harper Cancer Research Institute, Notre Dame, IN
| | - Kathryn P Gray
- IBCSG Statistical Center Department of Biostatistics and Computational Biology, Dana Farber Cancer Institute, Boston, MA.,Harvard T.H. Chan School of Public Health, Boston, MA
| | - Yesim Gökmen-Polar
- Department of Pathology and Laboratory Medicine, Indiana University School of Medicine, Indianapolis, IN
| | - Scooter Willis
- Avera Cancer Institute, Department of Molecular and Experimental Medicine, Sioux Falls, SD
| | - Beat Thürlimann
- Breast Center, Kantonsspital, St. Gallen, Switzerland.,Swiss Group for Clinical Cancer Research SAKK, Berne, Switzerland
| | - Rosita Kammler
- International Breast Cancer Study Group Coordinating Center Pathology Office, Bern, Switzerland
| | - Giuseppe Viale
- University of Milan, IEO European Institute of Oncology IRCCS, Milan, Italy
| | - Brian Leyland-Jones
- Avera Cancer Institute, Department of Molecular and Experimental Medicine, Sioux Falls, SD
| | - Sunil S Badve
- Department of Pathology and Laboratory Medicine, Indiana University School of Medicine, Indianapolis, IN.,Indiana University Melvin and Bren Simon Cancer Center, Indianapolis, IN
| | - Meredith M Regan
- IBCSG Statistical Center Department of Biostatistics and Computational Biology, Dana Farber Cancer Institute, Boston, MA.,Harvard Medical School, Boston, MA
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6
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McCart Reed AE, Lal S, Kutasovic JR, Wockner L, Robertson A, de Luca XM, Kalita-de Croft P, Dalley AJ, Coorey CP, Kuo L, Ferguson K, Niland C, Miller G, Johnson J, Reid LE, Males R, Saunus JM, Chenevix-Trench G, Coin L, Lakhani SR, Simpson PT. LobSig is a multigene predictor of outcome in invasive lobular carcinoma. NPJ Breast Cancer 2019; 5:18. [PMID: 31263747 PMCID: PMC6597578 DOI: 10.1038/s41523-019-0113-y] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2019] [Accepted: 05/22/2019] [Indexed: 12/12/2022] Open
Abstract
Invasive lobular carcinoma (ILC) is the most common special type of breast cancer, and is characterized by functional loss of E-cadherin, resulting in cellular adhesion defects. ILC typically present as estrogen receptor positive, grade 2 breast cancers, with a good short-term prognosis. Several large-scale molecular profiling studies have now dissected the unique genomics of ILC. We have undertaken an integrative analysis of gene expression and DNA copy number to identify novel drivers and prognostic biomarkers, using in-house (n = 25), METABRIC (n = 125) and TCGA (n = 146) samples. Using in silico integrative analyses, a 194-gene set was derived that is highly prognostic in ILC (P = 1.20 × 10-5)-we named this metagene 'LobSig'. Assessing a 10-year follow-up period, LobSig outperformed the Nottingham Prognostic Index, PAM50 risk-of-recurrence (Prosigna), OncotypeDx, and Genomic Grade Index (MapQuantDx) in a stepwise, multivariate Cox proportional hazards model, particularly in grade 2 ILC cases (χ 2, P = 9.0 × 10-6), which are difficult to prognosticate clinically. Importantly, LobSig status predicted outcome with 94.6% accuracy amongst cases classified as 'moderate-risk' according to Nottingham Prognostic Index in the METABRIC cohort. Network analysis identified few candidate pathways, though genesets related to proliferation were identified, and a LobSig-high phenotype was associated with the TCGA proliferative subtype (χ 2, P < 8.86 × 10-4). ILC with a poor outcome as predicted by LobSig were enriched with mutations in ERBB2, ERBB3, TP53, AKT1 and ROS1. LobSig has the potential to be a clinically relevant prognostic signature and warrants further development.
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Affiliation(s)
- Amy E. McCart Reed
- UQ Centre for Clinical Research, Faculty of Medicine, The University of Queensland, Herston, QLD 4029 Australia
| | - Samir Lal
- UQ Centre for Clinical Research, Faculty of Medicine, The University of Queensland, Herston, QLD 4029 Australia
- Present Address: Pfizer Oncology Research, San Diego, CA 92121 USA
| | - Jamie R. Kutasovic
- UQ Centre for Clinical Research, Faculty of Medicine, The University of Queensland, Herston, QLD 4029 Australia
| | - Leesa Wockner
- QIMR Berghofer Medical Research Institute, Herston, Brisbane, QLD 4006 Australia
| | - Alan Robertson
- Institute for Molecular Bioscience, The University of Queensland, St Lucia, Brisbane, QLD 4072 Australia
| | - Xavier M. de Luca
- UQ Centre for Clinical Research, Faculty of Medicine, The University of Queensland, Herston, QLD 4029 Australia
| | - Priyakshi Kalita-de Croft
- UQ Centre for Clinical Research, Faculty of Medicine, The University of Queensland, Herston, QLD 4029 Australia
| | - Andrew J. Dalley
- UQ Centre for Clinical Research, Faculty of Medicine, The University of Queensland, Herston, QLD 4029 Australia
| | - Craig P. Coorey
- UQ Centre for Clinical Research, Faculty of Medicine, The University of Queensland, Herston, QLD 4029 Australia
| | - Luyu Kuo
- UQ Centre for Clinical Research, Faculty of Medicine, The University of Queensland, Herston, QLD 4029 Australia
| | - Kaltin Ferguson
- UQ Centre for Clinical Research, Faculty of Medicine, The University of Queensland, Herston, QLD 4029 Australia
| | - Colleen Niland
- UQ Centre for Clinical Research, Faculty of Medicine, The University of Queensland, Herston, QLD 4029 Australia
| | - Gregory Miller
- UQ Centre for Clinical Research, Faculty of Medicine, The University of Queensland, Herston, QLD 4029 Australia
- Pathology Queensland, The Royal Brisbane & Women’s Hospital, Herston, QLD 4029 Australia
| | - Julie Johnson
- UQ Centre for Clinical Research, Faculty of Medicine, The University of Queensland, Herston, QLD 4029 Australia
| | - Lynne E. Reid
- UQ Centre for Clinical Research, Faculty of Medicine, The University of Queensland, Herston, QLD 4029 Australia
| | - Renique Males
- UQ Centre for Clinical Research, Faculty of Medicine, The University of Queensland, Herston, QLD 4029 Australia
| | - Jodi M. Saunus
- UQ Centre for Clinical Research, Faculty of Medicine, The University of Queensland, Herston, QLD 4029 Australia
| | | | - Lachlan Coin
- Institute for Molecular Bioscience, The University of Queensland, St Lucia, Brisbane, QLD 4072 Australia
| | - Sunil R. Lakhani
- UQ Centre for Clinical Research, Faculty of Medicine, The University of Queensland, Herston, QLD 4029 Australia
- Pathology Queensland, The Royal Brisbane & Women’s Hospital, Herston, QLD 4029 Australia
| | - Peter T. Simpson
- UQ Centre for Clinical Research, Faculty of Medicine, The University of Queensland, Herston, QLD 4029 Australia
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7
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Cannon E, Buechler S. Colon Cancer Tumor Location Defined by Gene Expression May Disagree With Anatomic Tumor Location. Clin Colorectal Cancer 2019; 18:149-158. [PMID: 30853326 DOI: 10.1016/j.clcc.2019.02.002] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2018] [Revised: 01/22/2019] [Accepted: 02/04/2019] [Indexed: 12/23/2022]
Abstract
BACKGROUND Cancers of the right colon have been shown to differ from left-side colon cancers in prognosis, response to epithelial growth factor receptor inhibitors, microsatellite instability and BRAF mutation status, and other molecular characteristics. Clinical application of these differences will benefit from a deeper understanding of how tumor location defines and is defined by gene expression. MATERIALS AND METHODS This study was carried out using Affymetrix microarray datasets (Cohort A: training set, n = 352; validation set, n = 519) and samples from The Cancer Genome Atlas Colon Adenocarcinoma database (Cohort B: n = 408), in which tumor location was reported. Gene expression patterns characteristic of tumor side were identified in a manner unbiased by statistical classification method. RESULTS In the Cohort A validation set, the anatomic locations of 75% of tumors agree with the locations predicted by gene expression (so-called genomic location), whereas 8% of tumors had genomic locations discordant with their anatomic locations, and 17% of tumors had ambiguous genomic locations. Genomic location was a better predictor of microsatellite instability, CpG island methylator phenotype status, and BRAF mutation status than anatomic location. Tumors with ambiguous genomic location were significantly (P = 1.3 × 10-7) more likely to have the mesenchymal consensus molecular subtype (40%) than those with a specific genomic location (18%). A genomic signature to predict genomic location was defined. CONCLUSION Tumor location is increasingly considered in deciding treatment of a colon tumor. We showed that genomic location was superior to anatomic location as a predictor of molecular characteristics, suggesting that it may be a more accurate predictor of response.
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Affiliation(s)
- Emily Cannon
- Department of Applied and Computational Mathematics and Statistics, University of Notre Dame, Notre Dame, IN
| | - Steven Buechler
- Department of Applied and Computational Mathematics and Statistics, University of Notre Dame, Notre Dame, IN.
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