Journal article

LobSig is a multigene predictor of outcome in invasive lobular carcinoma

Amy E McCart Reed, Samir Lal, Jamie R Kutasovic, Leesa Wockner, Alan Robertson, Xavier M de Luca, Priyakshi Kalita-de Croft, Andrew J Dalley, Craig P Coorey, Luyu Kuo, Kaltin Ferguson, Colleen Niland, Gregory Miller, Julie Johnson, Lynne E Reid, Renique Males, Jodi M Saunus, Georgia Chenevix-Trench, Lachlan Coin, Sunil R Lakhani Show all

NPJ BREAST CANCER | NATURE PUBLISHING GROUP | Published : 2019

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 ×..

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University of Melbourne Researchers

Grants

Awarded by Cancer Council Queensland


Awarded by ARC LIEF


Funding Acknowledgements

We would like to acknowledge the Brisbane Breast Bank, for coordinating sample collection, archiving, and data management, as well as all the patients who donated tissue for this study. We acknowledge the support of Metro North Hospital and Health Services in the collection of the Clinical Subject Data and Clinical Subject Materials. Additional tissues and samples were received from the Australia Breast Cancer Tissue Bank, which has been generously supported by the National Health and Medical Research Council of Australia, The Cancer Institute NSW and the National Breast Cancer Foundation, Australia. These tissues and samples are made available to researchers on a non-exclusive basis. Peter Simpson was the recipient of a fellowship from the National Breast Cancer Foundation, Australia. This work was funded in part by grants from the Wesley Research Institute, Cancer Council Queensland (APP631585) and the NHMRC. This study made use of data generated by the Molecular Taxonomy of Breast Cancer International Consortium; funding for the METABRIC project was provided by Cancer Research UK and the British Columbia Cancer Agency Branch. Metacore was developed with support from ARC LIEF grant LE120100071. We would like to thank Anne Bernard from QFAB for statistical advice and Drs. Katia Nones, Nic Waddell, Fares Al-Ejeh, Ana Cristina Vargas for their input.