ROCplot.org: Validating predictive biomarkers of chemotherapy/hormonal therapy/anti-HER2 therapy using transcriptomic data of 3,104 breast cancer patients.

Systemic therapy of breast cancer can include chemotherapy, hormonal therapy and targeted therapy. Prognostic biomarkers are able to predict survival and predictive biomarkers are able to predict therapy response. In this report, we describe the initial release of the first available online tool able to identify gene expression-based predictive biomarkers using transcriptomic data of a large set of breast cancer patients. Published gene expression data of 36 publicly available datasets were integrated with treatment data into a unified database. Response to therapy was determined using either author-reported pathological complete response data (n = 1,775) or relapse-free survival status at 5 years (n = 1,329). Treatment data includes chemotherapy (n = 2,108), endocrine therapy (n = 971) and anti-human epidermal growth factor receptor 2 (HER2) therapy (n = 267). The transcriptomic database includes 20,089 unique genes and 54,675 probe sets. Gene expression and therapy response are compared using receiver operating characteristics and Mann-Whitney tests. We demonstrate the utility of the pipeline by cross-validating 23 paclitaxel resistance-associated genes in different molecular subtypes of breast cancer. An additional set of established biomarkers including TP53 for chemotherapy in Luminal breast cancer (p = 1.01E-19, AUC = 0.769), HER2 for trastuzumab therapy (p = 8.4E-04, AUC = 0.629) and PGR for hormonal therapy (p = 8.6E-05, AUC = 0.7), are also endorsed. The tool is designed to validate and rank new predictive biomarker candidates in real time. By analyzing the selected genes in a large set of independent patients, one can select the most robust candidates and quickly eliminate those that are most likely to fail in a clinical setting. The analysis tool is accessible at www.rocplot.org.

Demographic shift disproportionately increases cancer burden in an aging nation: current and expected incidence and mortality in Hungary up to 2030.

BACKGROUND: Population aging is a common demographic pattern in developed countries, and aging increases the risk of cancer. The disproportionately high cancer burden, as a consequence, is especially pronounced in Central and Eastern European countries, including Hungary. METHODS: We summarized current and projected future cancer incidences and mortalities utilizing data from the last two decades. Predictions are based on cancer incidence and mortality collected between 1996 and 2015 in Hungary. In addition to the crude rates, data were age standardized to the European standard population (ESP) of 2013, ESP of 1976, and local census of 2011. RESULTS: The lifetime probability of developing cancer and cancer-related mortality has already reached 56.9% and 27.6% in men, respectively, and 51.9% and 21.7% in women. Between 2016 and 2030, the total population is expected to shrink by 6%, while the number of 60-year olds and above will grow by 18%. This will lead to a 35% increase in cancer incidence and 30% increase in cancer death among 65-85-year olds. Joinpoint regression identified the period 2007-2015 as starting point for this coming increase in new cases. In women, lung and breast cancer will increase yearly by 1.9% and 1.7%, respectively, between 2016 and 2030, while in men, the prostate and colorectal cancer rates will increase yearly by 3.6% and 2.1%. CONCLUSION: In the aging population of Hungary, cancer incidence will increase considerably over previous projections. Although a large portion of the most rapidly rising cancers are avoidable by implementing public health programs, a substantial portion remains inevitably incurable.