@article { , title = {A novel prognostic two-gene signature for triple negative breast cancer}, abstract = {The absence of a robust risk stratification tool for triple negative breast cancer (TNBC) underlies imprecise and non-selective treatment of these patients with cytotoxic chemotherapy. This study aimed to interrogate transcriptomes of TNBC resected samples using next generation sequencing to identify novel biomarkers associated with disease outcomes. A subset of cases (n=112) from a large, well-characterized cohort of primary TNBC (n=333) were subjected to RNA-sequencing. Reads were aligned to the human reference genome (GRCH38.83) using the STAR aligner and gene expression quantified using HTSEQ. We identified genes associated with distant metastasis-free survival and breast cancer-specific survival by applying supervised artificial neural network analysis with gene selection to the RNA-sequencing data. The prognostic ability of these genes was validated using the Breast Cancer Gene-Expression Miner v4. 0 and Genotype 2 outcome datasets. Multivariate Cox regression analysis identified a prognostic gene signature that was independently associated with poor prognosis. Finally, we corroborated our results from the two-gene prognostic signature by their protein expression using immunohistochemistry. Artificial neural network identified two gene panels that strongly predicted distant metastasis-free survival and breast cancer-specific survival. Univariate Cox regression analysis of 21 genes common to both panels revealed that the expression level of eight genes was independently associated with poor prognosis (p}, doi = {10.1038/s41379-020-0563-7}, eissn = {1530-0285}, issn = {0893-3952}, journal = {Modern Pathology}, pages = {2208–2220}, publicationstatus = {Published}, publisher = {Nature Publishing Group}, url = {https://nottingham-repository.worktribe.com/output/4325602}, volume = {33}, keyword = {Nottingham Breast Cancer Research Centre, triple negative breast cancer, TNBC, prognostic gene signature, ANN, ACSM4, SPDYC, NGS}, year = {2020}, author = {Alsaleem, Mansour A and Ball, Graham and Toss, Michael S and Raafat, Sara and Aleskandarany, Mohammed and Joseph, Chitra and Ogden, Angela and Bhattarai, Shristi and Rida, Padmashree C G and Khani, Francesca and Davis, Melissa and Elemento, Olivier and Aneja, Ritu and Ellis, Ian O and Green, Andrew and Mongan, Nigel P. and Rakha, Emad} }