Survival analysis in breast cancer using proteomic data from four independent datasets

Abstract

Breast cancer clinical treatment selection is based on the immunohistochemical determination of four proteins: ESR1, PGR, HER2, and MKI67. Our aim was to correlate immunohistochemical results to proteome-level technologies in measuring the expression of these markers. We also aimed to integrate available proteome-level breast cancer datasets to identify and validate new prognostic biomarker candidates.We identified protein studies involving breast cancer patient cohorts with published survival and proteomic information. Immunohistochemistry and proteomic technologies were compared using the Mann-Whitney test. Receiver operating characteristics (ROC) curves were generated to validate discriminative power. Cox regression and Kaplan-Meier survival analysiss were calculated to assess prognostic power. The false discovery rate was computed to correct for multiple hypothesis testing.The complete database contains protein expression data and survival information from four independent cohorts for 1,229 breast cancer patients. In all four studies combined, a total of 7,342 unique proteins were identified, and 1,417 of these were identified in at least three datasets. ESR1, PGR, HER2 protein expression levels determined by RPPA or LC-MS/MS methods showed a significant correlation with the levels determined by immunohistochemistry (p<0.0001). PGR and ESR1 levels showed a moderate correlation (correlation coefficient=0.17, p=0.0399). A panel of candidate proteins, including apoptosis-related proteins (BCL2,), adhesion markers (CDH1, CLDN3, CLDN7) and basal markers (cytokeratins), were validated as prognostic biomarkers. We expanded our established web tool to validate survival-associated biomarkers to include the proteomic datasets analyzed in this study (https://kmplot.com/analysis/).Large proteomic studies now provide sufficient data enabling the validation and ranking of new protein biomarkers.

USP5 promotes breast cancer cell proliferation and metastasis by stabilizing HIF2α

“…Thus, USP5 is highly expressed in breast tumors and contributes to HIF2α abundance. Moreover, analysis by Kaplan−Meier plotter (https://kmplot.com/analysis) (Ősz et al, 2021), an online survival analysis tool, showed that the high levels of USP5 protein led to the poor clinical overall survival of patients with breast cancer. These results indicate that the protein levels of USP5 are positively correlated with HIF2α protein levels in breast cancer and are associated with poor clinical outcomes in patients with breast cancer.…”

Immune checkpoint blockade reprograms systemic immune landscape and tumor microenvironment in obesity-associated breast cancer

“…One gene downregulated by anti-PD-1 in obese tumors was laminin subunit beta-2 ( Lamb2 ) ( Figure S3C ). In line with downregulation of Lamb2 with anti-PD-1 in obese murine tumors, low LAMB2 protein expression was associated with greater overall survival in estrogen receptor (ER)-negative (ER−) tumors ( Ősz et al, 2020 ). In ER− tumors, median survival was 29 months in high expressers versus more than 3-fold longer at 100 months in low LAMB2 protein expressers ( Figure 3C , HR = 2.57, and log rank p = 0.65, n = 54 patients).…”

“…Hence, we explored associations with obesity-mediated factors that could influence antitumor immunosurveillance to identify putative biomarkers of anti-PD-1 efficacy, namely, the gut microbiome. Obesity affects the gut microbiome (Pierre et al, 2016;Aron-Wisnewsky et al, 2021;Newman et al, 2021). Microbiota, including bacteria and fungi, are increasingly tied to response to ICB or chemotherapy through unknown mechanisms, but recent work suggests mechanisms including microbially derived metabolite signaling on immune cells (Mager et al, 2020;Sipe et al, 2020;Simpson et al, 2021;Langan et al, 2018;Gopalakrishnan et al, 2018;Frankel et al, 2017;Vé tizou et al, 2015;Matson et al, 2018;Routy et al, 2018;Iida et al, 2013;Viaud et al, 2013;Sepich-Poore et al, 2021;Sivan et al, 2015).…”

Expression and Clinical Significance of Origin Recognition Complex Family in Breast Cancer

“…The sources for the databases were GEO, EGA, and TCGA. It is a meta-analysis based discovery and validation of survival biomarkers 35 . We assessed the association between ORCs and overall survival(OS) in BC patients via Kaplan-Meier Plotter.…”