Integrative analyses identify modulators of response to neoadjuvant aromatase inhibitors in patients with early breast cancer

Introduction Aromatase inhibitors (AIs) are a vital component of estrogen receptor positive (ER+) breast cancer treatment. De novo and acquired resistance, however, is common. The aims of this study were to relate patterns of copy number aberrations to molecular and proliferative response to AIs, to study differences in the patterns of copy number aberrations between breast cancer samples pre- and post-AI neoadjuvant therapy, and to identify putative biomarkers for resistance to neoadjuvant AI therapy using an integrative analysis approach. Methods Samples from 84 patients derived from two neoadjuvant AI therapy trials were subjected to copy number profiling by microarray-based comparative genomic hybridisation (aCGH, n = 84), gene expression profiling (n = 47), matched pre- and post-AI aCGH (n = 19 pairs) and Ki67-based AI-response analysis (n = 39). Results Integrative analysis of these datasets identified a set of nine genes that, when amplified, were associated with a poor response to AIs, and were significantly overexpressed when amplified, including CHKA, LRP5 and SAPS3. Functional validation in vitro, using cell lines with and without amplification of these genes (SUM44, MDA-MB134-VI, T47D and MCF7) and a model of acquired AI-resistance (MCF7-LTED) identified CHKA as a gene that when amplified modulates estrogen receptor (ER)-driven proliferation, ER/estrogen response element (ERE) transactivation, expression of ER-regulated genes and phosphorylation of V-AKT murine thymoma viral oncogene homolog 1 (AKT1). Conclusions These data provide a rationale for investigation of the role of CHKA in further models of de novo and acquired resistance to AIs, and provide proof of concept that integrative genomic analyses can identify biologically relevant modulators of AI response

Low-Multiplicity Burst Search At The Sudbury Neutrino Observatory

Results are reported from a search for low-multiplicity neutrino bursts in the Sudbury Neutrino Observatory. Such bursts could indicate the detection of a nearby core-collapse supernova explosion. The data were taken from Phase I (1999 November-2001 May), when the detector was filled with heavy water, and Phase II (2001 July-2003 August), when NaCl was added to the target. The search was a blind analysis in which the potential backgrounds were estimated and analysis cuts were developed to eliminate such backgrounds with 90% confidence before the data were examined. The search maintained a greater than 50% detection probability for standard supernovae occurring at a distance of up to 60 kpc for Phase I and up to 70 kpc for Phase II. No low-multiplicity bursts were observed during the data-taking period.Natural Sciences and Engineering Research Council, CanadaIndustry Canada, CanadaNational Research Council, CanadaNorthern Ontario Heritage Fund, CanadaAtomic Energy of Canada, Ltd., CanadaOntario Power Generation, CanadaHigh Performance Computing Virtual Laboratory, CanadaCanada Foundation for Innovation, CanadaCanada Research Chairs, CanadaDepartment of Energy, USNational Energy Research Scientific Computing Center, USAlfred P. Sloan Foundation, USScience and Technology Facilities Council, UKFundacao para a Ciencia e a Technologia, PortugalAstronom

Intra-tumor genetic heterogeneity and alternative driver genetic alterations in breast cancers with heterogeneous HER2 gene amplification

Background HER2 is overexpressed and amplified in approximately 15% of invasive breast cancers, and is the molecular target and predictive marker of response to anti-HER2 agents. In a subset of these cases, heterogeneous distribution of HER2 gene amplification can be found, which creates clinically challenging scenarios. Currently, breast cancers with HER2 amplification/overexpression in just over 10% of cancer cells are considered HER2-positive for clinical purposes; however, it is unclear as to whether the HER2-negative components of such tumors would be driven by distinct genetic alterations. Here we sought to characterize the pathologic and genetic features of the HER2-positive and HER2-negative components of breast cancers with heterogeneous HER2 gene amplification and to define the repertoire of potential driver genetic alterations in the HER2-negative components of these cases.Results We separately analyzed the HER2-negative and HER2-positive components of 12 HER2 heterogeneous breast cancers using gene copy number profiling and massively parallel sequencing, and identified potential driver genetic alterations restricted to the HER2-negative cells in each case. In vitro experiments provided functional evidence to suggest that BRF2 and DSN1 overexpression/amplification, and the HER2 I767M mutation may be alterations that compensate for the lack of HER2 amplification in the HER2-negative components of HER2 heterogeneous breast cancers.Conclusions Our results indicate that even driver genetic alterations, such as HER2 gene amplification, can be heterogeneously distributed within a cancer, and that the HER2-negative components are likely driven by genetic alterations not present in the HER2-positive components, including BRF2 and DSN1 amplification and HER2 somatic mutations

Searches For High-Frequency Variations In The B-8 Solar Neutrino Flux At The Sudbury Neutrino Observatory

We have performed three searches for high-frequency signals in the solar neutrino flux measured by the Sudbury Neutrino Observatory, motivated by the possibility that solar g-mode oscillations could affect the production or propagation of solar B-8 neutrinos. The first search looked for any significant peak in the frequency range 1-144 day(-1), with a sensitivity to sinusoidal signals with amplitudes of 12% or greater. The second search focused on regions in which g-mode signals have been claimed by experiments aboard the Solar and Heliospheric Observatory satellite, and was sensitive to signals with amplitudes of 10% or greater. The third search looked for extra power across the entire frequency band. No statistically significant signal was detected in any of the three searches.Natural Sciences and Engineering Research Council, CanadaIndustry Canada, CanadaNational Research Council, CanadaNorthern Ontario Heritage Fund, CanadaAtomic Energy of Canada, Ltd., CanadaOntario Power Generation, CanadaHigh Performance Computing Virtual Laboratory, CanadaCanada Foundation for InnovationDept. of Energy, USNational Energy Research Scientific Computing Center, USScience and Technologies Facilities Council, UKAstronom

Characterization of the genomic features and expressed fusion genes in micropapillary carcinomas of the breast

Micropapillary carcinoma ( MPC ) is a rare histological special type of breast cancer, characterized by an aggressive clinical behaviour and a pattern of copy number aberrations ( CNAs ) distinct from that of grade‐ and oestrogen receptor ( ER )‐matched invasive carcinomas of no special type ( IC‐NSTs ). The aims of this study were to determine whether MPCs are underpinned by a recurrent fusion gene(s) or mutations in 273 genes recurrently mutated in breast cancer. Sixteen MPCs were subjected to microarray‐based comparative genomic hybridization ( aCGH ) analysis and Sequenom OncoCarta mutation analysis. Eight and five MPCs were subjected to targeted capture and RNA sequencing, respectively. aCGH analysis confirmed our previous observations about the repertoire of CNAs of MPCs . Sequencing analysis revealed a spectrum of mutations similar to those of luminal B IC‐NSTs , and recurrent mutations affecting mitogen‐activated protein kinase family genes and NBPF10 . RNA ‐sequencing analysis identified 17 high‐confidence fusion genes, eight of which were validated and two of which were in‐frame. No recurrent fusions were identified in an independent series of MPCs and IC‐NSTs . Forced expression of in‐frame fusion genes ( SLC2A1–FAF1 and BCAS4–AURKA ) resulted in increased viability of breast cancer cells. In addition, genomic disruption of CDK12 caused by out‐of‐frame rearrangements was found in one MPC and in 13% of HER2 ‐positive breast cancers, identified through a re‐analysis of publicly available massively parallel sequencing data. In vitro analyses revealed that CDK12 gene disruption results in sensitivity to PARP inhibition, and forced expression of wild‐type CDK12 in a CDK12 ‐null cell line model resulted in relative resistance to PARP inhibition. Our findings demonstrate that MPCs are neither defined by highly recurrent mutations in the 273 genes tested, nor underpinned by a recurrent fusion gene. Although seemingly private genetic events, some of the fusion transcripts found in MPCs may play a role in maintenance of a malignant phenotype and potentially offer therapeutic opportunities. © 2014 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/106752/1/path4325.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/106752/2/path4325-sup-0001-AppendixS1.pd

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment