Validation of multi-gene biomarkers for clinical outcomes is one of the most important issues for cancer prognosis. An important source of information for virtual validation is the high number of available cancer datasets. Nevertheless, assessing the prognostic performance of a gene expression signature along datasets is a difficult task for Biologists and Physicians and also time-consuming for Statisticians and Bioinformaticians. Therefore, to facilitate performance comparisons and validations of survival biomarkers for cancer outcomes, we developed SurvExpress, a cancer-wide gene expression database with clinical outcomes and a web-based tool that provides survival analysis and risk assessment of cancer datasets. The main input of SurvExpress is only the biomarker gene list. We generated a cancer database collecting more than 20,000 samples and 130 datasets with censored clinical information covering tumors over 20 tissues. We implemented a web interface to perform biomarker validation and comparisons in this database, where a multivariate survival analysis can be accomplished in about one minute. We show the utility and simplicity of SurvExpress in two biomarker applications for breast and lung cancer. Compared to other tools, SurvExpress is the largest, most versatile, and quickest free tool available. SurvExpress web can be accessed in http://bioinformatica.mty.itesm.mx/SurvExpress (a tutorial is included). The website was implemented in JSP, JavaScript, MySQL, and R.

Circadian rhythms are essential for temporal (~24 h) regulation of molecular processes in diverse species. Dysregulation of circadian gene expression has been implicated in the pathogenesis of various disorders, including hypertension, diabetes, depression, and cancer. Recently, microRNAs (miRNAs) have been identified as critical modulators of gene expression post-transcriptionally, and perhaps involved in circadian clock architecture or their output functions. The aim of the present study is to explore the temporal expression of miRNAs among entrained breast cell lines. For this purpose, we evaluated the temporal (28 h) expression of 2006 miRNAs in MCF-10A, MCF-7, and MDA-MB-231 cells using microarrays after serum shock entrainment. We noted hundreds of miRNAs that exhibit rhythmic fluctuations in each breast cell line, and some of them across two or three cell lines. Afterwards, we validated the rhythmic profiles exhibited by miR-141-5p, miR-1225-5p, miR-17-5p, miR-222-5p, miR-769-3p, and miR-548ay-3p in the above cell lines, as well as in ZR-7530 and HCC-1954 using RT-qPCR. Our results show that serum shock entrainment in breast cells lines induces rhythmic fluctuations of distinct sets of miRNAs, which have the potential to be related to endogenous circadian clock, but extensive investigation is required to elucidate that connection.

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BACKGROUND: Diverse molecular mechanisms are being reported in human breast cancer (BC), which can affect the biochemical functions throughout malignant cells development. The microRNAs (miRNAs) are an emerging class of modulators of gene expression with relevant roles in several biological processes, as oncogenic, tumor-suppressive, and metastatic-influencing in BC cells. Recently, a few reports have implied the possible pattern of expression (time oscillation) of miRNAs in time that may be related to molecular changes in mammalian cells. These findings suggest a biological connection among normal and cancer cells, and rhythmic regulation of some miRNAs, but such connection has not yet been studied. In this study, we aimed to identify and compare the rhythmic expression of miRNAs in human breast epithelial normal and cancer cell lines. METHODS: We used cell culture to explore three cell lines, one breast epithelial normal (MCF10A) and two cancer (MCF-7 and MDA-MB-231) cell lines under standard growth conditions in vitro. The cells were synchronized by serum shock (50% horse serum for 2 h), and we collected sample cells (triplicate) for intervals of 4 hours during 48 hours. Collected cells at 12h to 40h (8 time-points) were genome-wide analyzed of miRNA expression using high-throughput Agilent Human miRNA microarray of 2006 human miRNAs. Analysis for identification of rhythmic miRNAs was developed by cosine analysis in R software. RESULTS: We observed diverse oscillation patterns (minimum 6 patterns, i.e. cosine or sine oscillation) of miRNAs in cell lines. Each cell line shows approximately 85 miRNAs with rhythmic oscillation. These also showed distinct phases between cell lines, which could suggest as part of molecular changes in breast normal and cancer cell lines. CONCLUSIONS: Our results suggest that miRNAs may present rhythmic oscillation in the regulation of molecular changes of human breast normal and cancer cells. Citation Format: Chacolla RJ, Trevino VM, Scott SP, Moreno JE. Rhythmic time oscillations of microRNAs in human breast epithelial normal and cancer cell lines. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P2-03-07.

BACKGROUND: Breast cancer (BC) is a heterogeneous disease with diverse biological-molecular characteristics and clinical behaviors. Traditionally, prediction of recurrence in patients recently diagnosed is a big challenge for oncologists. In the last decade, advances in gene expression profiling technologies have improved the genetic knowledge of breast cancer by reporting several prognostic gene-signatures. However, there is still a need for covering the molecular heterogeneity of this cancer. Integration of public microarray data could be used to identify better and robust predictive gene-signatures. The aim of this study was to investigate prognostic genes that might function as biomarkers to differentiate among all heterogeneous BC patients, into those with high, medium or low recurrence risk. METHODS: We collected nine public datasets, 1574 BC patients with median follow-up time of 10 years. The data were split into train-test, 50% each. Train was subject to univariate and multivariate analysis to generate a signature, which was validated in the test data. Seven genes were identified with high accuracy for recurrence prediction. This signature was validated in 40 formalin-fixed paraffin-embedded (FFPE) Mexican BC tissues with clinical follow up of 3 to 13 years by quantitative RT-PCR assays. RESULTS: We identified a 7-gene signature which showed an accuracy prediction measured by concordance index of 65.62% and Log-rank test p-value: 1 x 10-15. The validation of the gene-signature level expression in 40 FFPE samples in Kaplan Meier analysis showed prediction significance by concordance index of 65.25% and Log-Rank p-value: 0.0005. CONCLUSIONS: This 7-gene signature may provide a powerful tool to guide the adequate treatment protocols in early-diagnosed breast cancer patients. Citation Format: Chacolla RJ, Trevino VM, Scott SP, Guzman EA, Cardona S. Robust 7-gene signature for recurrence prognosis of breast cancer validated in formalin-fixed paraffin-embedded samples. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P4-09-04.