Improving breast cancer survival analysis through competition-based multidimensional modeling.

Breast cancer is the most common malignancy in women and is responsible for hundreds of thousands of deaths annually. As with most cancers, it is a heterogeneous disease and different breast cancer subtypes are treated differently. Understanding the difference in prognosis for breast cancer based on its molecular and phenotypic features is one avenue for improving treatment by matching the proper treatment with molecular subtypes of the disease. In this work, we employed a competition-based approach to modeling breast cancer prognosis using large datasets containing genomic and clinical information and an online real-time leaderboard program used to speed feedback to the modeling team and to encourage each modeler to work towards achieving a higher ranked submission. We find that machine learning methods combined with molecular features selected based on expert prior knowledge can improve survival predictions compared to current best-in-class methodologies and that ensemble models trained across multiple user submissions systematically outperform individual models within the ensemble. We also find that model scores are highly consistent across multiple independent evaluations. This study serves as the pilot phase of a much larger competition open to the whole research community, with the goal of understanding general strategies for model optimization using clinical and molecular profiling data and providing an objective, transparent system for assessing prognostic models.

Copynumber: Efficient algorithms for single- and multi-track copy number segmentation.

BACKGROUND: Cancer progression is associated with genomic instability and an accumulation of gains and losses of DNA. The growing variety of tools for measuring genomic copy numbers, including various types of array-CGH, SNP arrays and high-throughput sequencing, calls for a coherent framework offering unified and consistent handling of single- and multi-track segmentation problems. In addition, there is a demand for highly computationally efficient segmentation algorithms, due to the emergence of very high density scans of copy number. RESULTS: A comprehensive Bioconductor package for copy number analysis is presented. The package offers a unified framework for single sample, multi-sample and multi-track segmentation and is based on statistically sound penalized least squares principles. Conditional on the number of breakpoints, the estimates are optimal in the least squares sense. A novel and computationally highly efficient algorithm is proposed that utilizes vector-based operations in R. Three case studies are presented. CONCLUSIONS: The R package copynumber is a software suite for segmentation of single- and multi-track copy number data using algorithms based on coherent least squares principles.

The Longitudinal Transcriptional Response to Neoadjuvant Chemotherapy with and without Bevacizumab in Breast Cancer.

Purpose: Chemotherapy-induced alterations to gene expression are due to transcriptional reprogramming of tumor cells or subclonal adaptations to treatment. The effect on whole-transcriptome mRNA expression was investigated in a randomized phase II clinical trial to assess the effect of neoadjuvant chemotherapy with the addition of bevacizumab.Experimental Design: Tumor biopsies and whole-transcriptome mRNA profiles were obtained at three fixed time points with 66 patients in each arm. Altogether, 358 specimens from 132 patients were available, representing the transcriptional state before treatment start, at 12 weeks and after treatment (25 weeks). Pathologic complete response (pCR) in breast and axillary nodes was the primary endpoint.Results: pCR was observed in 15 patients (23%) receiving bevacizumab and chemotherapy and 8 patients (12%) receiving only chemotherapy. In the estrogen receptor-positive patients, 11 of 54 (20%) treated with bevacizumab and chemotherapy achieved pCR, while only 3 of 57 (5%) treated with chemotherapy reached pCR. In patients with estrogen receptor-positive tumors treated with combination therapy, an elevated immune activity was associated with good response. Proliferation was reduced after treatment in both treatment arms and most pronounced in the combination therapy arm, where the reduction in proliferation accelerated during treatment. Transcriptional alterations during therapy were subtype specific, and the effect of adding bevacizumab was most evident for luminal-B tumors.Conclusions: Clinical response and gene expression response differed between patients receiving combination therapy and chemotherapy alone. The results may guide identification of patients likely to benefit from antiangiogenic therapy. Clin Cancer Res; 23(16); 4662-70. ©2017 AACR.

The Sub-Cellular Localization of WRAP53 Has Prognostic Impact in Breast Cancer.

WRAP53 protein controls intracellular trafficking of DNA repair proteins, the telomerase enzyme, and splicing factors. Functional loss of the protein has been linked to carcinogenesis, premature aging and neurodegeneration. The aim of this study was to investigate the prognostic significance of WRAP53 protein expression in breast cancer. A tissue microarray was constructed from primary breast tumors and immunostained by a polyclonal WRAP53 antibody to assess the protein expression pattern. Two different patient cohorts with long term follow-up were studied; a test- and a validation set of 154 and 668 breast tumor samples respectively. Breast cancer patients with tumor cells lacking the expression of WRAP53 in the nucleus had a significantly poorer outcome compared to patients with tumor cells expressing this protein in the nuclei (HR = 1.95, 95%CI = 1.09-3.51, p = 0.025). Nuclear localization of WRAP53 was further shown to be an independent marker of prognosis in multivariate analysis (HR = 2.57, 95%CI = 1.27-5.19, p = 0.008), and also significantly associated with better outcome in patients with TP53 mutation. Here we show that the sub-cellular localization of the WRAP53 protein has a significant impact on breast cancer survival, and thus has a potential as a clinical marker in diagnostics and treatment.

The 5p12 breast cancer susceptibility locus affects MRPS30 expression in estrogen-receptor positive tumors.

Genome-wide association studies have identified numerous loci linked to breast cancer susceptibility, but the mechanism by which variations at these loci influence susceptibility is usually unknown. Some variants are only associated with particular clinical subtypes of breast cancer. Understanding how and why these variants influence subtype-specific cancer risk contributes to our understanding of cancer etiology. We conducted a genome-wide expression Quantitative Trait Locus (eQTL) study in a discovery set of 287 breast tumors and 97 normal mammary tissue samples and a replication set of 235 breast tumors. We found that the risk-associated allele of rs7716600 in the 5p12 estrogen receptor-positive (ER-positive) susceptibility locus was associated with elevated expression of the nearby gene MRPS30 exclusively in ER-positive tumors. We replicated this finding in 235 independent tumors. Further, we showed the rs7716600 risk genotype was associated with decreased MRPS30 promoter methylation exclusively in ER-positive breast tumors. In vitro studies in MCF-7 cells carrying the protective genotype showed that estrogen stimulation decreased MRPS30 promoter chromatin availability and mRNA levels. In contrast, in 600MPE cells carrying the risk genotype, estrogen increased MRPS30 expression and did not affect promoter availability. Our data suggest the 5p12 risk allele affects MRPS30 expression in estrogen-responsive tumor cells after tumor initiation by a mechanism affecting chromatin availability. These studies emphasize that the genetic architecture of breast cancer is context-specific, and integrated analysis of gene expression and chromatin remodeling in normal and tumor tissues will be required to explain the mechanisms of risk alleles.

JARID1B is a luminal lineage-driving oncogene in breast cancer.

Recurrent mutations in histone-modifying enzymes imply key roles in tumorigenesis, yet their functional relevance is largely unknown. Here, we show that JARID1B, encoding a histone H3 lysine 4 (H3K4) demethylase, is frequently amplified and overexpressed in luminal breast tumors and a somatic mutation in a basal-like breast cancer results in the gain of unique chromatin binding and luminal expression and splicing patterns. Downregulation of JARID1B in luminal cells induces basal genes expression and growth arrest, which is rescued by TGFß pathway inhibitors. Integrated JARID1B chromatin binding, H3K4 methylation, and expression profiles suggest a key function for JARID1B in luminal cell-specific expression programs. High luminal JARID1B activity is associated with poor outcome in patients with hormone receptor-positive breast tumors.

The HER2 amplicon includes several genes required for the growth and survival of HER2 positive breast cancer cells.

About 20% of breast cancers are characterized by amplification and overexpression of the HER2 oncogene. Although significant progress has been achieved for treating such patients with HER2 inhibitor trastuzumab, more than half of the patients respond poorly or become resistant to the treatment. Since the HER2 amplicon at 17q12 contains multiple genes, we have systematically explored the role of the HER2 co-amplified genes in breast cancer cell growth and their relation to trastuzumab resistance. We integrated aCGH data of the HER2 amplicon from 71 HER2 positive breast tumors and 10 cell lines with systematic functional RNA interference analysis of 23 core amplicon genes with several phenotypic endpoints in a panel of trastuzumab responding and non-responding HER2 positive breast cancer cells. Silencing of HER2 caused a greater growth arrest and apoptosis in the responding compared to the non-responding cell lines, indicating that the resistant cells are inherently less dependent on the HER2 pathway. Several other genes in the amplicon also showed a more pronounced effect when silenced; indicating that expression of HER2 co-amplified genes may be needed to sustain the growth of breast cancer cells. Importantly, co-silencing of STARD3, GRB7, PSMD3 and PERLD1 together with HER2 led to an additive inhibition of cell viability as well as induced apoptosis. These studies indicate that breast cancer cells may become addicted to the amplification of several genes that reside in the HER2 amplicon. The simultaneous targeting of these genes may increase the efficacy of the anti-HER2 therapies and possibly also counteract trastuzumab resistance. The observed additive effects seem to culminate to both apoptosis and cell proliferation pathways indicating that these pathways may be interesting targets for combinatorial treatment of HER2+ breast cancers.