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Table shows the pathway deregulated in OUH and TCGA cohort.

Despite advances in diagnostics, less than 5% of patients with periampullary tumors experience an overall survival of five years or more. Periampullary tumors are neoplasms that arise in the vicinity of the ampulla of Vater, an enlargement of liver and pancreas ducts where they join and enter the small intestine. In this study, we analyzed copy number aberrations using Affymetrix SNP 6.0 arrays in 60 periampullary adenocarcinomas from Oslo University Hospital to identify genome-wide copy number aberrations, putative driver genes, deregulated pathways, and potential prognostic markers. Results were validated in a separate cohort derived from The Cancer Genome Atlas Consortium (n = 127). In contrast to many other solid tumors, periampullary adenocarcinomas exhibited more frequent genomic deletions than gains. Genes in the frequently codeleted region 17p13 and 18q21/22 were associated with cell cycle, apoptosis, and p53 and Wnt signaling. By integrating genomics and transcriptomics data from the same patients, we identified CCNE1 and ERBB2 as candidate driver genes. Morphologic subtypes of periampullary adenocarcinomas (i.e., pancreatobiliary or intestinal) harbor many common genomic aberrations. However, gain of 13q and 3q, and deletions of 5q were found specific to the intestinal subtype. Our study also implicated the use of the PAM50 classifier in identifying a subgroup of patients with a high proliferation rate, which had impaired survival. Furthermore, gain of 18p11 (18p11.21-23, 18p11.31-32) and 19q13 (19q13.2, 19q13.31-32) and subsequent overexpression of the genes in these loci were associated with impaired survival. Our work identifies potential prognostic markers for periampullary tumors, the genetic characterization of which has lagged. Cancer Res; 76(17); 5092–102. ©2016 AACR.

Summary results for all SNPs at the 4q24 locus associated with breast cancer risk at P

Background: A recent association study identified a common variant (rs9790517) at 4q24 to be associated with breast cancer risk. Independent association signals and potential functional variants in this locus have not been explored.Methods: We conducted a fine-mapping analysis in 55,540 breast cancer cases and 51,168 controls from the Breast Cancer Association Consortium.Results: Conditional analyses identified two independent association signals among women of European ancestry, represented by rs9790517 [conditional P = 2.51 × 10−4; OR, 1.04; 95% confidence interval (CI), 1.02–1.07] and rs77928427 (P = 1.86 × 10−4; OR, 1.04; 95% CI, 1.02–1.07). Functional annotation using data from the Encyclopedia of DNA Elements (ENCODE) project revealed two putative functional variants, rs62331150 and rs73838678 in linkage disequilibrium (LD) with rs9790517 (r2 ≥ 0.90) residing in the active promoter or enhancer, respectively, of the nearest gene, TET2. Both variants are located in DNase I hypersensitivity and transcription factor–binding sites. Using data from both The Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC), we showed that rs62331150 was associated with level of expression of TET2 in breast normal and tumor tissue.Conclusion: Our study identified two independent association signals at 4q24 in relation to breast cancer risk and suggested that observed association in this locus may be mediated through the regulation of TET2.Impact: Fine-mapping study with large sample size warranted for identification of independent loci for breast cancer risk. Cancer Epidemiol Biomarkers Prev; 24(11); 1680–91. ©2015 AACR.

Table S1: Genes significantly differentially expressed in samples with pathological complete response compared to those without in the Combination arm. Table S2: DAVID analysis of 720 differentially expressed genes in tumors that achieved pathological complete reponse compared to those that did not, in the combination arm. Table S3 : Genes significantly differentially expressed in samples with pathological complete response compared to those without in the Chemotherapy arm. Table S4: DAVID analysis of 1243 differentially expressed genes in tumors that achieved pathological complete reponse compared to those that did not, in the chemotherapy arm. Table S5 : List of genes with significant lower expression in week 12 samples treated with combination therapy compared to those treated with chemotherapy Table S6: DAVID analysis of 42 differentially expressed genes in week-12 tumors in the combination arm compared to chemotherapy arm. Table S7 : Differentially expressed genes between week-0 and week-12 in Basal-like tumors treated with combination therapy Table S8 : Differentially expressed genes between week-0 and week-12 Luminal B tumors treated with combination therapy Table S9 : Differentially expressed genes between week-0 and week-12 Luminal A tumors treated with combination therapy Table S10: Differentially expressed genes between week-0 and week-12 Basal-like tumors treated with chemotherapy Table S11 : Differentially expressed genes between week-0 and week-12 Luminal B tumors treated with chemotherapy Table S12 : Differentially expressed genes between week-0 and week-12 Luminal A tumors treated with chemotherapy Table S13: Pathways significantly altered between Chemotherapy and Combination therapy arms from week-0 to week-12 LuminalB samples Table S14: Pathways significantly altered between anthracycline and taxane treatment in the Luminal A samples in chemotherapy arm

The table shows the genes, chromosomal location and frequency of deletion and amplification of genes in OUH (PAs (n=54), cell lines (n=3) and IPMN (n=3) and TCGA data sets (n=127).

This file contains the legends of supplementary figures and tables.

1a) Amplification and deletion of cytobands in OUH cohort. 1b) Amplification and deletion of cytobands in TCGA cohort. The rows represent the cytobands while the columns represent the samples. The color bars on y-axis represent the chromosomes. The red color in the heatmap represents the amplification, green color represent the deletion while black represent the normal state.

The minor allele frequency is in blue and purple is the total copy number.

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.

Supplementary figures as referred to in the manuscript

Table shows the correlation score (r) between allele frequency and gene expression in OUH and TCGA cohort

The minor allele frequency is in blue and purple is the total copy number.

The x-axis represents the genomic position and is divided into 22 facets for 22 chromosomes. The y-axis represents the frequency of chromosomal gain and losses for five subtypes based on site of origin. The number of samples in each subtypes are PDAC: 28, bile duct: 4, ampulla P: 6, ampulla I: 7, duodenum: 9.

4A) Scatter plot shows the correlation between GII and ploidy of the tumors in OUH cohort. 4B) Scatter plot shows the correlation between GII and ploidy of the tumors in TCGA cohort. The x-axis represent the genome instability index while the y-axis represent the ploidy of the tumors

Epithelial-to-mesenchymal transition (EMT) contributes to tumor cell survival, immune evasion, migration, invasion, and therapy resistance. Across human cancer, tumors that are high grade, poorly differentiated, and have undergone EMT carry a worse prognosis with a higher likelihood of metastasis. AXL, a receptor tyrosine kinase, drives EMT and is implicated in tumor progression, metastasis, and therapy resistance in multiple cancer types including pancreatic cancer and breast cancer. TANK-binding kinase 1 (TBK1) is central to AXL-driven EMT yet, the mechanism of how TBK1 induces EMT remains unclear. Here, we report that AXL activation stimulates TBK1 binding and phosphorylation of AKT3. TBK1 activation of AKT3 drives binding and phosphorylation of slug/snail resulting in protection from proteasomal degradation and translocation of the complex into the nucleus. We show that nuclear translocation of AKT3 is required for AXL-driven EMT and metastasis. Congruently, nuclear AKT3 expression correlates with worse outcome in aggressive breast cancer. To advance AKT3 as a therapeutic target, an AKT3-isoform selective allosteric small molecule inhibitor, BGB214, was developed. BGB214 inhibits AKT3 nuclear translocation, EMT-TF stability, AKT3-mediated invasion of breast cancer cells and reduces tumor initiation in vivo. Our results suggest that AKT3 nuclear activity is an important feature of AXL-driven epithelial plasticity and that selective AKT3 inhibition represents a novel therapeutic avenue for treating aggressive cancer.SignificanceNuclear AKT3 activity is an important feature of AXL-TBK1 driven EMT and metastasis, thus selective AKT3 targeting represents a novel approach to treat aggressive cancer.

Cancer transcriptomes are shaped by genetic and epigenetic features, such as DNA methylation and copy number aberrations. Knowledge of the relationships between gene expression and such features is fundamental to understanding the basis of tumor phenotypes. Here, we present a pan-cancer atlas of transcriptional dependence on DNA methylation and copy number aberrations (PANORAMA). Our analyses suggest that copy number alterations are a central driver of inter-tumor heterogeneity, while the majority of expression-methylation associations found in cancer are a reflection of cell-of-origin and normal cell admixture. The atlas is made available through an online tool at https://pancancer.app.

Summary The receptor tyrosine kinase AXL is associated with epithelial plasticity in several solid tumors including breast cancer and AXL-targeting agents are currently in clinical trials. We hypothesized that AXL is a driver of stemness traits in cancer by co-option of a regulatory function normally reserved for stem cells. AXL-expressing cells in human mammary epithelial ducts co-expressed markers associated with multipotency, and AXL inhibition abolished colony formation and self-maintenance activities while promoting terminal differentiation in vitro. Axl-null mice did not exhibit a strong developmental phenotype, but enrichment of Axl+ cells was required for mouse mammary gland reconstitution upon transplantation, and Axl-null mice had reduced incidence of Wnt1-driven mammary tumors. An AXL-dependent gene signature is a feature of transcriptomes in basal breast cancers and reduced patient survival irrespective of subtype. Our interpretation is that AXL regulates access to epithelial plasticity programs in MaSCs and, when co-opted, maintains acquired stemness in breast cancer cells., Graphical Abstract, Highlights • AXL + mammary epithelial cells have multipotent activity conserved in women and mice • AXL allows accesses to epithelial-to-mesenchymal transition genes and prevents differentiation into luminal cells • Deletion of Axl reduced incidence of Wnt1-driven tumors in mice • Provides a rationale explaining the advantage to cancer cells that co-opt AXL signaling, Cell Biology; Stem Cells Research; Cancer

The long non-coding RNA NEAT1 locus is transcribed into two overlapping isoforms, NEAT1_1 and NEAT1_2, of which the latter is essential for the assembly of nuclear paraspeckles. NEAT1 is abnormally expressed in a wide variety of human cancers. Emerging evidence suggests that the two isoforms have distinct functions in gene expression regulation, and recently it was shown that NEAT1_2, but not NEAT1_1, expression predicts poor clinical outcome in cancer. Here, we report that NEAT1_2 expression correlates with HER2-positive breast cancers and high-grade disease. We provide evidence that NEAT1_1 and NEAT1_2 have distinct expression pattern among different intrinsic breast cancer subtypes. Finally, we show that NEAT1_2 expression and paraspeckle formation increase upon lactation in humans, confirming what has previously been demonstrated in mice. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

Source at https://doi.org/10.1002/1878-0261.12319. The tumor microenvironment (TME) may influence both cancer progression and therapeutic response. In breast cancer, particularly in the aggressive triple‐negative/basal‐like subgroup, patient outcome is strongly associated with the tumor's inflammatory profile. Tumor‐associated macrophages (TAMs) are among the most abundant immune cells in the TME, shown to be linked to poor prognosis and therapeutic resistance. In this study, we investigated the effect of the metastasis‐ and inflammation‐associated microenvironmental factor S100A4 on breast cancer cells (BCCs) of different subtypes and explored their further interactions with myeloid cells. We demonstrated that extracellular S100A4 activates BCCs, particularly the basal‐like subtype, to elevate secretion of pro‐inflammatory cytokines. The secreted factors promoted conversion of monocytes to TAM‐like cells that exhibited protumorigenic activities: stimulated epithelial–mesenchymal transition, proliferation, chemoresistance, and motility in cancer cells. In conclusion, we have shown that extracellular S100A4 instigates a tumor‐supportive microenvironment, involving a network of cytokines and TAM‐like cells, which was particularly characteristic for basal‐like BCCs and potentiated their aggressive properties. The S100A4–BCC–TAM interaction cascade could be an important contributor to the aggressive behavior of this subtype and should be further explored for therapeutic targeting.

Homozygous deletions are rare in cancers and often target tumour suppressor genes. Here, we build a compendium of 2218 primary tumours across 12 human cancer types and systematically screen for homozygous deletions, aiming to identify rare tumour suppressors. Our analysis defines 96 genomic regions recurrently targeted by homozygous deletions. These recurrent homozygous deletions occur either over tumour suppressors or over fragile sites, regions of increased genomic instability. We construct a statistical model that separates fragile sites from regions showing signatures of positive selection for homozygous deletions and identify candidate tumour suppressors within those regions. We find 16 established tumour suppressors and propose 27 candidate tumour suppressors. Several of these genes (including MGMT, RAD17, and USP44) show prior evidence of a tumour suppressive function. Other candidate tumour suppressors, such as MAFTRR, KIAA1551, and IGF2BP2, are novel. Our study demonstrates how rare tumour suppressors can be identified through copy number meta-analysis., Homozygous deletions are rare in cancers and often target tumour suppressor genes. Here, the authors conduct pan-cancer analyses and apply statistical modelling to identify 27 candidate tumour suppressors, including MAFTRR, KIAA1551, and IGF2BP2.

Background Chemotherapeutic agents such as anthracyclines and taxanes are commonly used in the neoadjuvant setting. Bevacizumab is an antibody which binds to vascular endothelial growth factor A (VEGFA) and inhibits its receptor interaction, thus obstructing the formation of new blood vessels. Methods A phase II randomized clinical trial of 123 patients with Her2-negative breast cancer was conducted, with patients treated with neoadjuvant chemotherapy (fluorouracil (5FU)/epirubicin/cyclophosphamide (FEC) and taxane), with or without bevacizumab. Serial biopsies were obtained at time of diagnosis, after 12 weeks of treatment with FEC ± bevacizumab, and after 25 weeks of treatment with taxane ± bevacizumab. A time course study was designed to investigate the genomic landscape at the three time points when tumor DNA alterations, tumor percentage, genomic instability, and tumor clonality were assessed. Substantial differences were observed with some tumors changing mainly between diagnosis and at 12 weeks, others between 12 and 25 weeks, and still others changing in both time periods. Results In both treatment arms, good responders (GR) and non-responders (NR) displayed significant difference in genomic instability index (GII) at time of diagnosis. In the combination arm, copy number alterations at 25 loci at the time of diagnosis were significantly different between the GR and NR. An inverse aberration pattern was also observed between the two extreme response groups at 6p22-p12 for patients in the combination arm. Signs of subclonal reduction were observed, with some aberrations disappearing and others being retained during treatment. Increase in subclonal amplification was observed at 6p21.1, a locus which contains the VEGFA gene for the protein which are targeted by the study drug bevacizumab. Of the 13 pre-treatment samples that had a gain at VEGFA, 12 were responders. Significant decrease of frequency of subclones carrying gains at 17q21.32-q22 was observed at 12 weeks, with the peak occurring at TMEM100, an ALK1 receptor signaling-dependent gene essential for vasculogenesis. This implies that cells bearing amplifications of VEGFA and TMEM100 are particularly sensitive to this treatment regime. Conclusions Taken together, these results suggest that heterogeneity and subclonal architecture influence the response to targeted treatment in combination with chemotherapy, with possible implications for clinical decision-making and monitoring of treatment efficacy. Trial registration NCT00773695 . Registered 15 October 2008

Previous genome-wide association studies among women of European ancestry identified two independent breast cancer susceptibility loci represented by single nucleotide polymorphisms (SNPs) rs13281615 and rs11780156 at 8q24. A fine-mapping study across 2.06 Mb (chr8:127,561,724-129,624,067, hg19) in 55,540 breast cancer cases and 51,168 controls within the Breast Cancer Association Consortium was conducted. Three additional independent association signals in women of European ancestry, represented by rs35961416 (OR = 0.95, 95% CI = 0.93-0.97, conditional p = 5.8 × 10(-6) ), rs7815245 (OR = 0.94, 95% CI = 0.91-0.96, conditional p = 1.1 × 10(-6) ) and rs2033101 (OR = 1.05, 95% CI = 1.02-1.07, conditional p = 1.1 × 10(-4) ) were found. Integrative analysis using functional genomic data from the Roadmap Epigenomics, the Encyclopedia of DNA Elements project, the Cancer Genome Atlas and other public resources implied that SNPs rs7815245 in Signal 3, and rs1121948 in Signal 5 (in linkage disequilibrium with rs11780156, r(2) = 0.77), were putatively functional variants for two of the five independent association signals. The results highlighted multiple 8q24 variants associated with breast cancer susceptibility in women of European ancestry.

GWAS have identified a breast cancer susceptibility locus on 2q35. Here we report the fine mapping of this locus using data from 101,943 subjects from 50 case-control studies. We genotype 276 SNPs using the ‘iCOGS’ genotyping array and impute genotypes for a further 1,284 using 1000 Genomes Project data. All but two, strongly correlated SNPs (rs4442975 G/T and rs6721996 G/A) are excluded as candidate causal variants at odds against >100:1. The best functional candidate, rs4442975, is associated with oestrogen receptor positive (ER+) disease with an odds ratio (OR) in Europeans of 0.85 (95% confidence interval=0.84−0.87; P=1.7 × 10−43) per t-allele. This SNP flanks a transcriptional enhancer that physically interacts with the promoter of IGFBP5 (encoding insulin-like growth factor-binding protein 5) and displays allele-specific gene expression, FOXA1 binding and chromatin looping. Evidence suggests that the g-allele confers increased breast cancer susceptibility through relative downregulation of IGFBP5, a gene with known roles in breast cell biology., Previous studies identified an association between the 2q35 locus and breast cancer. Here, the authors show that a SNP at 2q35, rs4442975, is associated with oestrogen receptor positive disease and suggest that this effect is mediated through the downregulation of a known breast cancer gene, IGFBP5.

Common variants in 94 loci have been associated with breast cancer including 15 loci with genome-wide significant associations (P, B.C.A.C. was funded through a European Community Seventh Framework Programme under grant agreement no 223175 (HEALTH-F2-2009-223175; COGS); Cancer Research UK (C1287/A10118, C1287/A10710, C12292/A11174, C1281/A12014, C5047/A8384, C5047/A15007, C5047/A10692); the National Institutes of Health Specialized Program of Research Excellence (SPORE) in Breast Cancer (CA116201), R01 grants (CA128978, CA176785, CA192393), and Post-Cancer GWAS initiative (1U19 CA148537, 1U19 CA148065 and 1U19 CA148112 - the GAME-ON initiative); the Canadian Institutes of Health Research (CIHR) for the CIHR Team in Familial Risks of Breast Cancer, the Breast Cancer Res. Foundation, and the Ovarian Cancer Research Fund. CIMBA genotyping was supported by National Institutes of Health grant (CA128978); the Department of Defence (W81XWH-10-1-0341); and the Breast Cancer Res. Foundation. CIMBA data management and data analysis were supported by Cancer Research UK grants C12292/A11174 and C1287/A10118. This study made use of data generated by the Wellcome Trust Case Control consortium. Functional studies were supported by the Florida Breast Cancer Foundation. A full description of funding and acknowledgments is provided in Supplementary Note 1.

BACKGROUND:The study of the intrinsic molecular subtypes of breast cancer has revealed differences among them in terms of prognosis and response to chemotherapy and endocrine therapy. However, the ability of intrinsic subtypes to predict benefit from adjuvant radiotherapy has only been examined in few studies.METHODS:Gene expression-based intrinsic subtyping was performed in 228 breast tumors collected from two independent post-mastectomy clinical trials (British Columbia and the Danish Breast Cancer Cooperative Group 82b trials), where pre-menopausal patients with node-positive disease were randomized to adjuvant radiotherapy or not. All patients received adjuvant chemotherapy and a subgroup of patients underwent ovarian ablation. Tumors were classified into intrinsic subtypes: Luminal A, Luminal B, HER2-enriched, Basal-like and Normal-like using the research-based PAM50 classifier.RESULTS:In the British Columbia study, patients treated with radiation had an overall significant lower incidence of locoregional recurrence compared to the controls. For Luminal A tumors the risk of loco-regional recurrence was low and was further lowered by adjuvant radiation. These findings were validated in the DBCG 82b study. The individual data from the two cohorts were merged, the hazard ratio (HR) for loco-regional recurrence associated with giving radiation was 0.34 (0.19 to 0.61) overall and 0.12 (0.03 to 0.52) for Luminal A tumors.CONCLUSIONS:In both postmastectomy trials, patients with Luminal A tumors turned out to have a significant lower incidence of loco-regional recurrence when randomized to adjuvant radiotherapy, leaving no indication to omit postmastectomy adjuvant radiation in pre-menopausal high-risk patients with Luminal A tumors. It was not possible to evaluate the effect of radiotherapy among the other subtypes because of limited sample sizes. BACKGROUND: The study of the intrinsic molecular subtypes of breast cancer has revealed differences among them in terms of prognosis and response to chemotherapy and endocrine therapy. However, the ability of intrinsic subtypes to predict benefit from adjuvant radiotherapy has only been examined in few studies.METHODS: Gene expression-based intrinsic subtyping was performed in 228 breast tumors collected from two independent post-mastectomy clinical trials (British Columbia and the Danish Breast Cancer Cooperative Group 82b trials), where pre-menopausal patients with node-positive disease were randomized to adjuvant radiotherapy or not. All patients received adjuvant chemotherapy and a subgroup of patients underwent ovarian ablation. Tumors were classified into intrinsic subtypes: Luminal A, Luminal B, HER2-enriched, Basal-like and Normal-like using the research-based PAM50 classifier.RESULTS: In the British Columbia study, patients treated with radiation had an overall significant lower incidence of locoregional recurrence compared to the controls. For Luminal A tumors the risk of loco-regional recurrence was low and was further lowered by adjuvant radiation. These findings were validated in the DBCG 82b study. The individual data from the two cohorts were merged, the hazard ratio (HR) for loco-regional recurrence associated with giving radiation was 0.34 (0.19 to 0.61) overall and 0.12 (0.03 to 0.52) for Luminal A tumors.CONCLUSIONS: In both postmastectomy trials, patients with Luminal A tumors turned out to have a significant lower incidence of loco-regional recurrence when randomized to adjuvant radiotherapy, leaving no indication to omit postmastectomy adjuvant radiation in pre-menopausal high-risk patients with Luminal A tumors. It was not possible to evaluate the effect of radiotherapy among the other subtypes because of limited sample sizes.

Homozygous deletions are rare in cancers and often target tumour suppressor genes. Here, we build a compendium of 2218 primary tumours across 12 human cancer types and systematically screen for homozygous deletions, aiming to identify rare tumour suppressors. Our analysis defines 96 genomic regions recurrently targeted by homozygous deletions. These recurrent homozygous deletions occur either over tumour suppressors or over fragile sites, regions of increased genomic instability. We construct a statistical model that separates fragile sites from regions showing signatures of positive selection for homozygous deletions and identify candidate tumour suppressors within those regions. We find 16 established tumour suppressors and propose 27 candidate tumour suppressors. Several of these genes (including MGMT, RAD17, and USP44) show prior evidence of a tumour suppressive function. Other candidate tumour suppressors, such as MAFTRR, KIAA1551, and IGF2BP2, are novel. Our study demonstrates how rare tumour suppressors can be identified through copy number meta-analysis.

Genome-wide association studies have identified SNPs near ZNF365 at 10q21.2 that are associated with both breast cancer risk and mammographic density. To identify the most likely causal SNPs, we fine mapped the association signal by genotyping 428 SNPs across the region in 89,050 European and 12,893 Asian case and control subjects from the Breast Cancer Association Consortium. We identified four independent sets of correlated, highly trait-associated variants (iCHAVs), three of which were located within ZNF365. The most strongly risk-associated SNP, rs10995201 in iCHAV1, showed clear evidence of association with both estrogen receptor (ER)-positive (OR = 0.85 [0.82-0.88]) and ER-negative (OR = 0.87 [0.82-0.91]) disease, and was also the SNP most strongly associated with percent mammographic density. iCHAV2 (lead SNP, chr10: 64,258,684:D) and iCHAV3 (lead SNP, rs7922449) were also associated with ER-positive (OR = 0.93 [0.91-0.95] and OR = 1.06 [1.03-1.09]) and ER-negative (OR = 0.95 [0.91-0.98] and OR = 1.08 [1.04-1.13]) disease. There was weaker evidence for iCHAV4, located 5' of ADO, associated only with ER-positive breast cancer (OR = 0.93 [0.90-0.96]). We found 12, 17, 18, and 2 candidate causal SNPs for breast cancer in iCHAVs 1-4, respectively. Chromosome conformation capture analysis showed that iCHAV2 interacts with the ZNF365 and NRBF2 (more than 600 kb away) promoters in normal and cancerous breast epithelial cells. Luciferase assays did not identify SNPs that affect transactivation of ZNF365, but identified a protective haplotype in iCHAV2, associated with silencing of the NRBF2 promoter, implicating this gene in the etiology of breast cancer.

The NeoAva study is a phase II clinical trial of patients with HER2 negative primary tumors of ≥25 mm treated with neoadjuvant chemotherapy (4 x FEC100 + 12 weeks of taxane-based therapy) and randomized (1:1) to receive bevacizumab or no bevacizumab. Mammography, ultrasound and MR imaging were used for response evaluation, in addition to final pathology assessment. Tumor response were evaluable in 131 patients; of which 66 received bevacizumab in addition to chemotherapy. Tumor material was obtained at screening, 12 weeks into treatment and at surgical removal of tumors at 25 weeks. mRNA expression profiling was performed on Agilent 8x60K platform and the tumors were classified into LuminalA, LuminalB, Her2-enriched, Basal and Normal-like subtypes using the PAM50 classifier. Ratio of the tumor size at final pathology assessment, and at inclusion (by radiology assessment) was calculated to obtain a continuous scale of response reflecting the percentage of tumor shrinkage in response to therapy. Genomic Grade Index (GGI scores) based on expression profiles of 97 genes (including cell-cycle and proliferation genes) were calculated. There were no significant differences in the tumor size, lymph node, hormone receptor status or PAM50 subtypes between the treatment arms. pCR in breast and axilla were obtained in 14 (21.1%) patients in the chemo+bev arm, and in 7 (10.6%) patients in the chemo-only arm. Tumors that obtained pCR were in higher number ER negative and TP53 mutated and exhibited Basal-like phenotype. The overall pCR rates were higher in the ER negative tumors compared to ER positive tumors {39.1% (9 of 23) vs 11.1% (12 of 108)}. However, addition of bevacizumab seemed to improve pCR in the ER positive patient group (9 vs 3) and not in ER negative patient group (5 vs 4). On evaluating the continuous response variable, ER status, TP53 mutation status and PAM50 subtypes were significantly associated to response (p < 0.001). GGI scores were highly correlated to response (p< 0.001), i. e tumors with higher GGI scores showed better response. Importantly, when the chemo+bev and the chemo-only arms were evaluated separately, although similar trend of associations was observed in both arms, the associations were found to be enhanced in the chemo+bev arm. Next, we evaluated a shift in PAM50 subtypes across the timepoints. A shift towards a better prognosis group, i.e Luminal A or Normal-like profile was observed in response to therapy. Distribution of Luminal A and Normal-like tumors at week 25, (and not at screening or week 12) was significantly different in the chemo+bev vs chemo-only group (p = 0.026, Fisher’s exact test). GGI scores regressed across timepoints reflecting the loss of aggressive and proliferating component of the tumors in response to therapy. GGI scores in the chemo+bev group became significantly lower (p < 0.01) already at week 12. This suggests that the removal of the proliferating component of the tumors by chemotherapy is accelerated and improved by addition of bevacizumab. These results, with potentially important clinical relevance will be further investigated with respect to subtypes and the molecular changes induced by antiangiogenic therapy. Citation Format: Olav Engebraaten, Laxmi Silwal-Pandit, Marit Krohn, Elen K Møller, Silje Nord, Thomas Fleischer, Hedda von der Lippe Gythfelt, Elin Borgen, Øystein Garred, Anne Fangberget, Marit Muri Holmen, Ellen Schlichting, Helle Skjerven, Steinar Lundgren, Vessela N Kristensen, Ole Christian Lingjaerde, Erik Wist, Bjørn Naume, Anne-Lise Børresen-Dale. Molecular response in breast cancer treated with neoadjuvant chemotherapy with and without bevacizumab: Results from NeoAva - a randomized phase II study [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P4-11-14.

Genome-wide association studies (GWAS) and large-scale replication studies have identified common variants in 79 loci associated with breast cancer, explaining ∼14% of the familial risk of the disease. To identify new susceptibility loci, we performed a meta-analysis of 11 GWAS, comprising 15,748 breast cancer cases and 18,084 controls together with 46,785 cases and 42,892 controls from 41 studies genotyped on a 211,155-marker custom array (iCOGS). Analyses were restricted to women of European ancestry. We generated genotypes for more than 11 million SNPs by imputation using the 1000 Genomes Project reference panel, and we identified 15 new loci associated with breast cancer at P < 5 × 10(-8). Combining association analysis with ChIP-seq chromatin binding data in mammary cell lines and ChIA-PET chromatin interaction data from ENCODE, we identified likely target genes in two regions: SETBP1 at 18q12.3 and RNF115 and PDZK1 at 1q21.1. One association appears to be driven by an amino acid substitution encoded in EXO1. ispartof: Nature Genetics vol:47 issue:4 pages:373-80 ispartof: location:United States status: published

PURPOSE: Cis-acting regulatory SNPs resulting in differential allelic expression (DAE) may, in part, explain the underlying phenotypic variation associated with many complex diseases. To investigate whether common variants associated with DAE were involved in breast cancer susceptibility among BRCA1 and BRCA2 mutation carriers, a list of 175 genes was developed based of their involvement in cancer-related pathways. METHODS: Using data from a genome-wide map of SNPs associated with allelic expression, we assessed the association of ~320 SNPs located in the vicinity of these genes with breast and ovarian cancer risks in 15,252 BRCA1 and 8211 BRCA2 mutation carriers ascertained from 54 studies participating in the Consortium of Investigators of Modifiers of BRCA1/2. RESULTS: We identified a region on 11q22.3 that is significantly associated with breast cancer risk in BRCA1 mutation carriers (most significant SNP rs228595 p = 7 × 10-6). This association was absent in BRCA2 carriers (p = 0.57). The 11q22.3 region notably encompasses genes such as ACAT1, NPAT, and ATM. Expression quantitative trait loci associations were observed in both normal breast and tumors across this region, namely for ACAT1, ATM, and other genes. In silico analysis revealed some overlap between top risk-associated SNPs and relevant biological features in mammary cell data, which suggests potential functional significance. CONCLUSION: We identified 11q22.3 as a new modifier locus in BRCA1 carriers. Replication in larger studies using estrogen receptor (ER)-negative or triple-negative (i.e., ER-, progesterone receptor-, and HER2-negative) cases could therefore be helpful to confirm the association of this locus with breast cancer risk. Funding for the iCOGS infrastructure came from the European Community's Seventh Framework Programme under Grant Agreement No. 223175 (HEALTH-F2-2009-223175) (COGS), Cancer Research UK (C1287/A10118, C1287/A 10710, C12292/A11174, C1281/A12014, C5047/A8384, C5047/A15007, C5047/A10692, C8197/A16565), the National Institutes of Health (CA128978) and Post-cancer GWAS Initiative (1U19 CA148537, 1U19 CA148065, and 1U19 CA148112: the GAME-ON Initiative), the Department of Defence (W81XWH-10-1-0341), the Canadian Institutes of Health Research (CIHR) for the CIHR Team in Familial Risks of Breast Cancer, Komen Foundation for the Cure, the Breast Cancer Research Foundation, and the Ovarian Cancer Research Fund. BCFR: this work was supported by Grant UM1 CA164920 from the National Cancer Institute. BFBOCC was supported by Lithuania (BFBOCC-LT): Research Council of Lithuania Grant SEN-18/2015. BIDMC was supported by the Breast Cancer Research Foundation. BRCA-gene mutations and breast cancer in South African women (BMBSA) was supported by Grants from the Cancer Association of South Africa (CANSA) to Elizabeth J. van Rensburg. BRICOH: SLN was partially supported by the Morris and Horowitz Families Endowed Professorship. CNIO: this work was partially supported by Spanish Association Against Cancer (AECC08), RTICC 06/0020/1060, FISPI08/1120, Mutua Madrilena Foundation (FMMA), and SAF2010-20493. COH-CCGCRN: patients were recruited for this study from the City of Hope Clinical Cancer Genomics Community Research Network, supported in part by Award Number RC4CA153828 (PI: J. Weitzel) from the National Cancer Institute and the Office of the Director, National Institutes of Health. CONSIT Team: Associazione Italiana Ricerca sul Cancro (AIRC) to P. Peterlongo (IG 2012 Id. 12821) and P. Radice (IG 2014 Id. 15547). Funds from Italian citizens who allocated the 5 9 1000 share of their tax payment in support of the Fondazione IRCCS Istituto Nazionale Tumori, according to Italian laws (INT-Institutional Strategic Projects '5x1000') to S. Manoukian. FiorGen Foundation for Pharmacogenomics to L. Papi. CORE: the CIMBA Data Management and Data Analysis were supported by Cancer Research: UK Grants C12292/A20861, C12292/A11174. ACA is a Cancer Research-UK Senior Cancer Research Fellow. GCT is an NHMRC Senior Principal Research Fellow. J. Lecarpentier has been financially supported by the Fondation ARC (FONDATION ARC, 9 rue Guy Moquet 94803 Villejuif: France), Grant Number SAE20131200623. This work was supported by the Canadian Institutes of Health Research for the "CIHR Team in Familial Risks of Breast Cancer" Program: Grant No. CRN-87521 and the Ministry of Economic Development, Innovation and Export Trade: Grant No. PSR-SIIRI-701. The PERSPECTIVE Project was supported by the Government of Canada through Genome Canada and the Canadian Institutes of Health Research, the Ministere de l'Economie, Innovation et Exportation du Quebec through Genome Quebec, and The Quebec Breast Cancer Foundation. This work was also supported by the Ministere de l'Economie, Innovation et Exportation du Quebec: Grant No. PSR-SIIRI-701. DEMOKRITOS: this research has been co-financed by the European Union (European Social Fund: ESF) and Greek National Funds through the Operational Program "Education and Lifelong Learning" of the National Strategic Reference Framework (NSRF): Research Funding Program of the General Secretariat for Research and Technology: SYN11_10_19 NBCA. Investing in Knowledge Society through the European Social Fund. The DKFZ Study was supported by the DKFZ. EMBRACE was supported by Cancer Research UK Grants C1287/A10118 and C1287/A11990. D. Gareth Evans and Fiona Lalloo were supported by an NIHR Grant to the Biomedical Research Centre, Manchester. The Investigators at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust were supported by an NIHR Grant to the Biomedical Research Centre at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust. Ros Eeles and Elizabeth Bancroft were supported by Cancer Research UK Grant C5047/A8385. Ros Eeles was also supported by NIHR support to the Biomedical Research Centre at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust. FCCC: the authors acknowledge the support from The University of Kansas Cancer Center (P30 CA168524) and the Kansas Bioscience Authority Eminent Scholar Program. A.K.G. was funded by 5U01CA113916, R01CA140323, and by the Chancellors Distinguished Chair in Biomedical Sciences Professorship. The German Consortium of Hereditary Breast and Ovarian Cancer (GC-HBOC) was supported by the German Cancer Aid (Grant No. 110837, Rita K. Schmutzler). This work was supported by the European Regional Development Fund and Free State of Saxony, Germany (LIFE: Leipzig Research Centre for Civilization Diseases, Project Numbers 713-241202, 713-241202, 14505/2470, 14575/2470). GEMO: the study was supported by the Ligue Nationale Contre le Cancer; the Association "Le cancer du sein, parlons-en!" Award; the Canadian Institutes of Health Research for the "CIHR Team in Familial Risks of Breast Cancer" Program and the French National Institute of Cancer (INCa). GEORGETOWN: CI received support from the Non-therapeutic Subject Registry Shared Resource at Georgetown University (NIH/NCI Grant P30-CA051008), the Fisher Center for Hereditary Cancer and Clinical GenomicsResearch, and Swing Fore the Cure. G-FAST: Bruce Poppe is a Senior Clinical Investigator of FWO. Mattias Van Heetvelde obtained funding from IWT. HCSC was supported by a Grant RD12/0036/0006 and 15/00059 from ISCIII (Spain), partially supported by European Regional Development FEDER Funds. The HEBCS was financially supported by the Helsinki University Hospital Research Fund, Academy of Finland (266528), the Finnish Cancer Society and the Sigrid Juselius Foundation. HEBON Study was supported by the Dutch Cancer Society Grants NKI1998-1854, NKI2004-3088, and NKI2007-3756, the Netherlands Organization of Scientific Research Grant NWO 91109024, the Pink Ribbon Grants 110005 and 2014-187.WO76, the BBMRI Grant NWO 184.021.007/CP46, and the Transcan Grant JTC 2012 Cancer 12-054. HEBON thanks the Registration Teams of Dutch Cancer Registry (IKNL; S. Siesling, J. Verloop) and the Dutch Pathology database (PALGA; L. Overbeek) for their help in part of the data collection. HRBCP was supported by the Hong Kong Sanatorium and Hospital, Dr. Ellen Li Charitable Foundation, The Kerry Group Kuok Foundation, National Institute of Health 1R 03CA130065, and North California Cancer Center. Hungarian Breast and Ovarian Cancer Study (HUNBOCS) was supported by Hungarian Research Grants KTIA-OTKA CK-80745 and OTKA K-112228. ICO: Contract Grant Sponsor: Asociacion Espanola Contra el Cancer, Spanish Health Research Fund; Carlos III Health Institute; Catalan Health Institute and Autonomous Government of Catalonia. Contract Grant Numbers: ISCIIIRETIC RD06/0020/1051, RD12/0036/008, PI10/01422, PI10/00748, PI13/00285, PIE13/00022, 2009SGR290, and 2014SGR364. The IHCC was supported by Grant PBZ_KBN_122/P05/2004. The ILUH Group was supported by the Icelandic Association "Walking for Breast Cancer Research" and by the Landspitali University Hospital Research Fund. INHERIT: this work was supported by the Canadian Institutes of Health Research for the "CIHR Team in Familial Risks of Breast Cancer" Program: Grant No. CRN-87521 and the Ministry of Economic Development, Innovation and Export Trade: Grant No. PSR-SIIRI-701. The PERSPECTIVE Project was supported by the Government of Canada through Genome Canada and the Canadian Institutes of Health Research (Grant GPH-129344), the Ministere de l'Economie, Science et Innovation du Quebec through Genome Quebec, and the Quebec Breast Cancer Foundation. IOVHBOCS was supported by Ministero della Salute and "5x1000" Istituto Oncologico Veneto Grant. IPOBCS: this study was in part supported by Liga Portuguesa Contra o Cancro. kConFab was supported by a Grant from the National Breast Cancer Foundation, and previously by the National Health and Medical Research Council (NHMRC), the Queensland Cancer Fund, the Cancer Councils of New South Wales, Victoria, Tasmania, and South Australia, and the Cancer Foundation of Western Australia. KOHBRA was supported by a Grant from the National R&D Program for Cancer Control, Ministry for Health, Welfare and Family Affairs, Republic of Korea (1020350). MAYO was supported by NIH Grants CA116167, CA192393, and CA176785, an NCI Specialized Program of Research Excellence (SPORE) in Breast Cancer (CA116201), and a Grant from the Breast Cancer Research Foundation. MCGILL: Jewish General Hospital Weekend to End Breast Cancer, Quebec Ministry of Economic Development, Innovation and Export Trade. MODSQUAD was supported by MH CZ: DRO (MMCI, 00209805) and by the European Regional Development Fund and the State Budget of the Czech Republic (RECAMO, CZ.1.05/2.1.00/03.0101) to LF, and by Charles University in Prague Project UNCE204024 (MZ). MSKCC was supported by Grants from the Breast Cancer Research Foundation, the Robert and Kate Niehaus Clinical Cancer Genetics Initiative, and the Andrew Sabin Research Fund. NAROD: 1R01 CA149429-01. NCI: the research of Drs. MH Greene and PL Mai was supported by the Intramural Research Program of the US National Cancer Institute, NIH, and by Support Services Contracts NO2-CP-11019-50 and N02-CP-65504 with Westat, Inc., Rockville, MD. NICCC was supported by Clalit Health Services in Israel. Some of its activities were supported by the Israel Cancer Association and the Breast Cancer Research Foundation (BCRF), NY. NNPIO: this work has been supported by the Russian Federation for Basic Research (Grants 15-04-01744 and 16-54-00055). NRG Oncology: this study was supported by NRG Oncology Operations Grant Number U10 CA180868 as well as NRG SDMC Grant U10 CA180822, Gynecologic Oncology Group (GOG) Administrative Office and the GOG Tissue Bank (CA 27469), and the GOG Statistical and Data Center (CA 37517). Drs. Greene, Mai, and Savage were supported by Funding from the Intramural Research Program, NCI. OSUCCG was supported by the Ohio State University Comprehensive Cancer Center. PBCS: this work was supported by the Italian Association of Cancer Research (AIRC) [IG 2013 N.14477] and Tuscany Institute for Tumors (ITT) Grant 2014-2015-2016. SEABASS: Ministry of Science, Technology and Innovation, Ministry of Higher Education (UM.C/HlR/MOHE/06), and Cancer Research Initiatives Foundation. The SMC Team was in part sponsored by a Grant from the Israeli Cancer Association to the Israeli Consortium of Hereditary Breast Cancer. SWE-BRCA Collaborators were supported by the Swedish Cancer Society. UCHICAGO was supported by NCI Specialized Program of Research Excellence (SPORE) in Breast Cancer (CA125183), R01 CA142996, 1U01CA161032, and by the Ralph and Marion Falk Medical Research Trust, the Entertainment Industry Fund National Women's Cancer Research Alliance, and the Breast Cancer Research Foundation. OIO is an ACS Clinical Research Professor. UCLA: Jonsson Comprehensive Cancer Center Foundation; Breast Cancer Research Foundation. UCSF: UCSF Cancer Risk Program and Helen Diller Family Comprehensive Cancer Center. UKFOCR was supported by a Project Grant from CRUK to Paul Pharoah. UPENN: National Institutes of Health (NIH) (R01-CA102776 and R01-CA083855; Breast Cancer Research Foundation; Susan G. Komen Foundation for the Cure, Basser Research Center for BRCA. VFCTG: Victorian Cancer Agency, Cancer Australia, National Breast Cancer Foundation. WCP: Dr. Karlan was funded by the American Cancer Society Early Detection Professorship (SIOP-06-258-01-COUN) and the National Center for Advancing Translational Sciences (NCATS), Grant UL1TR000124. Sí

BACKGROUND:Breast cancer is a heterogeneous disease at the clinical and molecular level. In this study we integrate classifications extracted from five different molecular levels in order to identify integrated subtypes.METHODS:Tumor tissue from 425 patients with primary breast cancer from the Oslo2 study was cut and blended, and divided into fractions for DNA, RNA and protein isolation and metabolomics, allowing the acquisition of representative and comparable molecular data. Patients were stratified into groups based on their tumor characteristics from five different molecular levels, using various clustering methods. Finally, all previously identified and newly determined subgroups were combined in a multilevel classification using a "cluster-of-clusters" approach with consensus clustering.RESULTS:Based on DNA copy number data, tumors were categorized into three groups according to the complex arm aberration index. mRNA expression profiles divided tumors into five molecular subgroups according to PAM50 subtyping, and clustering based on microRNA expression revealed four subgroups. Reverse-phase protein array data divided tumors into five subgroups. Hierarchical clustering of tumor metabolic profiles revealed three clusters. Combining DNA copy number and mRNA expression classified tumors into seven clusters based on pathway activity levels, and tumors were classified into ten subtypes using integrative clustering. The final consensus clustering that incorporated all aforementioned subtypes revealed six major groups. Five corresponded well with the mRNA subtypes, while a sixth group resulted from a split of the luminal A subtype; these tumors belonged to distinct microRNA clusters. Gain-of-function studies using MCF-7 cells showed that microRNAs differentially expressed between the luminal A clusters were important for cancer cell survival. These microRNAs were used to validate the split in luminal A tumors in four independent breast cancer cohorts. In two cohorts the microRNAs divided tumors into subgroups with significantly different outcomes, and in another a trend was observed.CONCLUSIONS:The six integrated subtypes identified confirm the heterogeneity of breast cancer and show that finer subdivisions of subtypes are evident. Increasing knowledge of the heterogeneity of the luminal A subtype may add pivotal information to guide therapeutic choices, evidently bringing us closer to improved treatment for this largest subgroup of breast cancer. BACKGROUND: Breast cancer is a heterogeneous disease at the clinical and molecular level. In this study we integrate classifications extracted from five different molecular levels in order to identify integrated subtypes.METHODS: Tumor tissue from 425 patients with primary breast cancer from the Oslo2 study was cut and blended, and divided into fractions for DNA, RNA and protein isolation and metabolomics, allowing the acquisition of representative and comparable molecular data. Patients were stratified into groups based on their tumor characteristics from five different molecular levels, using various clustering methods. Finally, all previously identified and newly determined subgroups were combined in a multilevel classification using a "cluster-of-clusters" approach with consensus clustering.RESULTS: Based on DNA copy number data, tumors were categorized into three groups according to the complex arm aberration index. mRNA expression profiles divided tumors into five molecular subgroups according to PAM50 subtyping, and clustering based on microRNA expression revealed four subgroups. Reverse-phase protein array data divided tumors into five subgroups. Hierarchical clustering of tumor metabolic profiles revealed three clusters. Combining DNA copy number and mRNA expression classified tumors into seven clusters based on pathway activity levels, and tumors were classified into ten subtypes using integrative clustering. The final consensus clustering that incorporated all aforementioned subtypes revealed six major groups. Five corresponded well with the mRNA subtypes, while a sixth group resulted from a split of the luminal A subtype; these tumors belonged to distinct microRNA clusters. Gain-of-function studies using MCF-7 cells showed that microRNAs differentially expressed between the luminal A clusters were important for cancer cell survival. These microRNAs were used to validate the split in luminal A tumors in four independent breast cancer cohorts. In two cohorts the microRNAs divided tumors into subgroups with significantly different outcomes, and in another a trend was observed.CONCLUSIONS: The six integrated subtypes identified confirm the heterogeneity of breast cancer and show that finer subdivisions of subtypes are evident. Increasing knowledge of the heterogeneity of the luminal A subtype may add pivotal information to guide therapeutic choices, evidently bringing us closer to improved treatment for this largest subgroup of breast cancer.

There are significant inter-individual differences in the levels of gene expression. Through modulation of gene expression, cis-acting variants represent an important source of phenotypic variation. Consequently, cis-regulatory SNPs associated with differential allelic expression are functional candidates for further investigation as disease-causing variants. To investigate whether common variants associated with differential allelic expression were involved in breast cancer susceptibility, a list of genes was established on the basis of their involvement in cancer related pathways and/or mechanisms. Thereafter, using data from a genome-wide map of allelic expression associated SNPs, 313 genetic variants were selected and their association with breast cancer risk was then evaluated in 46,451 breast cancer cases and 42,599 controls of European ancestry ascertained from 41 studies participating in the Breast Cancer Association Consortium. The associations were evaluated with overall breast cancer risk and with estrogen receptor negative and positive disease. One novel breast cancer susceptibility locus on 4q21 (rs11099601) was identified (OR = 1.05, P = 5.6x10-6). rs11099601 lies in a 135 kb linkage disequilibrium block containing several genes, including, HELQ, encoding the protein HEL308 a DNA dependant ATPase and DNA Helicase involved in DNA repair, MRPS18C encoding the Mitochondrial Ribosomal Protein S18C and FAM175A (ABRAXAS), encoding a BRCA1 BRCT domain-interacting protein involved in DNA damage response and double-strand break (DSB) repair. Expression QTL analysis in breast cancer tissue showed rs11099601 to be associated with HELQ (P = 8.28x10-14), MRPS18C (P = 1.94x10-27) and FAM175A (P = 3.83x10-3), explaining about 20%, 14% and 1%, respectively of the variance inexpression of these genes in breast carcinomas. This work was supported by the Canadian Institutes of Health Research for the "CIHR Team in Familial Risks of Breast Cancer" program - grant # CRN-87521, the Ministry of Economy Innovation and Exportations-grant # PSR-SIIRI-701 and by the Government of Canada through Genome Canada and the Canadian Institutes of Health Research, and the Ministere de l'Economie, de la Science et de l'Innovation du Quebec through Genome Quebec and The Quebec Breast Cancer Foundation for the PERSPECTIVE project. Jacques Simard is Chairholder of the Canada Research Chair in Oncogenetics. Silje Nord is financed by a carrier grant from the Norwegian Regional Health authorities (Grant number 2014061). BCAC is funded by Cancer Research UK [C1287/A10118, C1287/A12014] and by the European Community's Seventh Framework Programme under grant agreement number 223175 (grant number HEALTH-F2-2009-223175) (COGS). Funding for the iCOGS infrastructure came from: the European Community's Seventh Framework Programme under grant agreement no 223175 (HEALTH-F2-2009-223175) (COGS), Cancer Research UK (C1287/A10118, C1287/A 10710, C12292/A11174, C1281/A12014, C5047/A8384, C5047/A15007, C5047/A10692, C8197/A16565), the National Institutes of Health (CA128978) and Post-Cancer GWAS initiative (1U19 CA148537, 1U19 CA148065 and 1U19 CA148112 - the GAME-ON initiative), the Department of Defence (W81XWH-10-1-0341), the Canadian Institutes of Health Research (CIHR) for the CIHR Team in Familial Risks of Breast Cancer, Komen Foundation for the Cure, the Breast Cancer Research Foundation, and the Ovarian Cancer Research Fund. The Australian Breast Cancer Family Study (ABCFS) was supported by grant UM1 CA164920 from the National Cancer Institute (USA). The content of this manuscript does not necessarily reflect the views or policies of the National Cancer Institute or any of the collaborating centers in the Breast Cancer Family Registry (BCFR), nor does mention of trade names, commercial products, or organizations imply endorsement by the USA Government or the BCFR. The ABCFS was also supported by the National Health and Medical Research Council of Australia, the New South Wales Cancer Council, the Victorian Health Promotion Foundation (Australia) and the Victorian Breast Cancer Research Consortium. J.L.H. is a National Health and Medical Research Council (NHMRC) Senior Principal Research Fellow. M.C.S. is a NHMRC Senior Research Fellow. The ABCS study was supported by the Dutch Cancer Society [grants NKI 2007-3839; 2009 4363]; BBMRI-NL, which is a Research Infrastructure financed by the Dutch government (NWO 184.021.007); and the Dutch National Genomics Initiative. The work of the BBCC was partly funded by ELAN-Fond of the University Hospital of Erlangen. The BBCS is funded by Cancer Research UK and Breast Cancer Now and acknowledges NHS funding to the NIHR Biomedical Research Centre, and the National Cancer Research Network (NCRN). ES is supported by NIHR Comprehensive Biomedical Research Centre, Guy's & St. Thomas' NHS Foundation Trust in partnership with King's College London, United Kingdom. IT is supported by the Oxford Biomedical Research Center. The BSUCH study was supported by the Dietmar-Hopp Foundation, the Helmholtz Society and the German Cancer Research Center (DKFZ). The CECILE study was funded by Fondation de France, Institut National du Cancer (INCa), Ligue Nationale contre le Cancer, Ligue contre le Cancer Grand Ouest, Agence Nationale de Securite Sanitaire (ANSES), Agence Nationale de la Recherche (ANR). The CGPS was supported by the Chief Physician Johan Boserup and Lise Boserup Fund, the Danish Medical Research Council and Herlev Hospital. The CNIO-BCS was supported by the Instituto de Salud Carlos III, the Red Tematica de Investigacion Cooperativa en Cancer and grants from the Asociacion Espanola Contra el Cancer and the Fondo de Investigacion Sanitario (PI11/00923 and PI12/00070). The CTS was initially supported by the California Breast Cancer Act of 1993 and the California Breast Cancer Research Fund (contract 97-10500) and is currently funded through the National Institutes of Health (R01 CA77398). Collection of cancer incidence data was supported by the California Department of Public Health as part of the statewide cancer reporting program mandated by California Health and Safety Code Section 103885. HAC receives support from the Lon V Smith Foundation (LVS39420). The ESTHER study was supportd by a grant from the Baden Wurttemberg Ministry of Science, Research and Arts. Additional cases were recruited in the context of the VERDI study, which was supported by a grant from the German Cancer Aid (Deutsche Krebshilfe). The GENICA was funded by the Federal Ministry of Education and Research (BMBF) Germany grants 01KW9975/5, 01KW9976/8, 01KW9977/0 and 01KW0114, the Robert Bosch Foundation, Stuttgart, Deutsches Krebsforschungszentrum (DKFZ), Heidelberg, the Institute for Prevention and Occupational Medicine of the German Social Accident Insurance, Institute of the Ruhr University Bochum (IPA), Bochum, as well as the Department of Internal Medicine, Evangelische Kliniken Bonn gGmbH, Johanniter Krankenhaus, Bonn, Germany. The HEBCS was financilly supported by the Helsinki University Central Hospital Research Fund, Academy of Finland (266528), the Finnish Cancer Society, The Nordic Cancer Union and the Sigrid Juselius Foundation. The HMBCS was supported by a grant from the Friends of Hannover Medical School and by the Rudolf Bartling Foundation. Financial support for KARBAC was provided through the regional agreement on medical training and clinical research (ALF) between Stockholm County Council and Karolinska Institutet, the Swedish Cancer Society, The Gustav V Jubilee foundation and and Bert von Kantzows foundation. The KBCP was financially supported by the special Government Funding (EVO) of Kuopio University Hospital grants, Cancer Fund of North Savo, the Finnish Cancer Organizations, and by the strategic funding of the University of Eastern Finland. kConFab is supported by a grant from the National Breast Cancer Foundation, and previously by the National Health and Medical Research Council (NHMRC), the Queensland Cancer Fund, the Cancer Councils of New South Wales, Victoria, Tasmania and South Australia, and the Cancer Foundation of Western Australia. Financial support for the AOCS was provided by the United States Army Medical Research and Materiel Command [DAMD17-01-1-0729], Cancer Council Victoria, Queensland Cancer Fund, Cancer Council New South Wales, Cancer Council South Australia, The Cancer Foundation of Western Australia, Cancer Council Tasmania and the National Health and Medical Research Council of Australia (NHMRC; 400413, 400281, 199600). G.C.T. and P.W. are supported by the NHMRC. RB was a Cancer Institute NSW Clinical Research Fellow. LMBC is supported by the 'Stichting tegen Kanker' (232-2008 and 196-2010). Diether Lambrechts is supported by the FWO and the KULPFV/10/016-SymBioSysII. The MARIE study was supported by the Deutsche Krebshilfe e.V. [70-2892-BR I, 106332, 108253, 108419], the Hamburg Cancer Society, the German Cancer Research Center (DKFZ) and the Federal Ministry of Education and Research (BMBF) Germany [01KH0402]. MBCSG (Milan Breast Cancer Study Group) is supported by grants from the Italian Association for Cancer Research (AIRC) and by funds from the Italian citizens who allocated the 5/1000 share of their tax payment in support of the Fondazione IRCCS Istituto Nazionale Tumori, according to Italian laws (INT-Institutional strategic projects "5x1000"). The MCBCS was supported by the NIH grants CA192393, CA116167, CA176785 an NIH Specialized Program of Research Excellence (SPORE) in Breast Cancer [CA116201], and the Breast Cancer Research Foundation and a generous gift from the David F. and Margaret T. Grohne Family Foundation. MCCS cohort recruitment was funded by VicHealth and Cancer Council Victoria. The MCCS was further supported by Australian NHMRC grants 209057, 251553 and 504711 and by infrastructure provided by Cancer Council Victoria. Cases and their vital status were ascertained through the Victorian Cancer Registry (VCR) and the Australian Institute of Health and Welfare (AIHW), including the National Death Index and the Australian Cancer Database. The MEC was support by NIH grants CA63464, CA54281, CA098758 and CA132839. The work of MTLGEBCS was supported by the Quebec Breast Cancer Foundation, the Canadian Institutes of Health Research for the "CIHR Team in Familial Risks of Breast Cancer" program - grant # CRN-87521 and the Ministry of Economic Development, Innovation and Export Trade - grant # PSR-SIIRI-701. The NBCS has been supported by the Research Council of Norway grant 193387/V50 (to A-L Borresen-Dale and V.N. Kristensen) and grant 193387/H10 (to A-L Borresen-Dale and V.N. Kristensen), South Eastern Norway Health Authority (grant 39346 to A-L Borresen-Dale and 27208 to V.N. Kristensen) and the Norwegian Cancer Society (to A-L Borresen-Dale and 419616 - 71248 - PR-2006-0282 to V.N. Kristensen). It has received funding from the K.G. Jebsen Centre for Breast Cancer Research (2012-2015). The OBCS was supported by research grants from the Finnish Cancer Foundation, the Academy of Finland (grant number 250083, 122715 and Center of Excellence grant number 251314), the Finnish Cancer Foundation, the Sigrid Juselius Foundation, the University of Oulu, the University of Oulu Support Foundation and the special Governmental EVO funds for Oulu University Hospital-based research activities. The Ontario Familial Breast Cancer Registry (OFBCR) was supported by grant UM1 CA164920 from the National Cancer Institute (USA). The content of this manuscript does not necessarily reflect the views or policies of the National Cancer Institute or any of the collaborating centers in the Breast Cancer Family Registry (BCFR), nor does mention of trade names, commercial products, or organizations imply endorsement by the USA Government or the BCFR. The ORIGO study was supported by the Dutch Cancer Society (RUL 1997-1505) and the Biobanking and Biomolecular Resources Research Infrastructure (BBMRI-NL CP16). The PBCS was funded by Intramural Research Funds of the National Cancer Institute, Department of Health and Human Services, USA. The pKARMA study was supported by Marit and Hans Rausings Initiative against Breast Cancer. The RBCS was funded by the Dutch Cancer Society (DDHK 2004-3124, DDHK 2009-4318). The SASBAC study was supported by funding from the Agency for Science, Technology and Research of Singapore (A*STAR), the US National Institute of Health (NIH) and the Susan G. Komen Breast Cancer Foundation. The SBCS was supported by Yorkshire Cancer Research S295, S299, S305PA and Sheffield Experimental Cancer Medicine Centre. SEARCH is funded by a programme grant from Cancer Research UK [C490/A10124] and supported by the UK National Institute for Health Research Biomedical Research Centre at the University of Cambridge. SEBCS was supported by the BRL (Basic Research Laboratory) program through the National Research Foundation of Korea funded by the Ministry of Education, Science and Technology (2012-0000347). SGBCC is funded by the NUS start-up Grant, National University Cancer Institute Singapore (NCIS) Centre Grant and the NMRC Clinician Scientist Award. Additional controls were recruited by the Singapore Consortium of Cohort Studies-Multi-ethnic cohort (SCCS-MEC), which was funded by the Biomedical Research Council, grant number: 05/1/21/19/425. SKKDKFZS is supported by the DKFZ. The SZBCS was supported by Grant PBZ_KBN_122/P05/2004. The TNBCC was supported by: a Specialized Program of Research Excellence (SPORE) in Breast Cancer (CA116201), a grant from the Breast Cancer Research Foundation, a generous gift from the David F. and Margaret T. Grohne Family Foundation. The UKBGS is funded by Breast Cancer Now and the Institute of Cancer Research (ICR), London. ICR acknowledges NHS funding to the NIHR Biomedical Research Centre. Sí

MicroRNAs (miRNAs) are endogenous non-coding RNAs, which play an essential role in the regulation of gene expression during carcinogenesis. The role of miRNAs in breast cancer has been thoroughly investigated, and although many miRNAs are identified as cancer related, little is known about their involvement in benign tumors. In this study, we investigated miRNA expression profiles in the two most common types of human benign tumors (fibroadenoma/fibroadenomatosis) and in malignant breast tumors and explored their role as oncomirs and tumor suppressor miRNAs. Here, we identified 33 miRNAs with similar deregulated expression in both benign and malignant tumors compared with the expression levels of those in normal tissue, including breast cancer-related miRNAs such as let-7, miR-21 and miR-155. Additionally, messenger RNA (mRNA) expression profiles were obtained for some of the same samples. Using integrated mRNA/miRNA expression analysis, we observed that overexpression of certain miRNAs co-occurred with a significant downregulation of their candidate target mRNAs in both benign and malignant tumors. In support of these findings, in vitro functional screening of the downregulated miRNAs in non-malignant and breast cancer cell lines identified several possible tumor suppressor miRNAs, including miR-193b, miR-193a-3p, miR-126, miR-134, miR-132, miR-486-5p, miR-886-3p, miR-195 and miR-497, showing reduced growth when re-expressed in cancer cells. The finding of deregulated expression of oncomirs and tumor suppressor miRNAs in benign breast tumors is intriguing, indicating that they may play a role in proliferation. A role of cancer-related miRNAs in the early phases of carcinogenesis and malignant transformation can, therefore, not be ruled out.

BACKGROUND: Individual differences in breast size are a conspicuous feature of variation in human females and have been associated with fecundity and advantage in selection of mates. To identify common variants that are associated with breast size, we conducted a large-scale genotyping association meta-analysis in 7169 women of European descent across three independent sample collections with digital or screen film mammograms. METHODS: The samples consisted of the Swedish KARMA, LIBRO-1 and SASBAC studies genotyped on iCOGS, a custom illumina iSelect genotyping array comprising of 211 155 single nucleotide polymorphisms (SNPs) designed for replication and fine mapping of common and rare variants with relevance to breast, ovary and prostate cancer. Breast size of each subject was ascertained by measuring total breast area (mm(2)) on a mammogram. RESULTS: We confirm genome-wide significant associations at 8p11.23 (rs10086016, p=1.3×10(-14)) and report a new locus at 22q13 (rs5995871, p=3.2×10(-8)). The latter region contains the MKL1 gene, which has been shown to impact endogenous oestrogen receptor α transcriptional activity and is recruited on oestradiol sensitive genes. We also replicated previous genome-wide association study findings for breast size at four other loci. CONCLUSIONS: A new locus at 22q13 may be associated with female breast size. KARMA and LIBRO-1 were supported by Märit and Hans Rausings Initiative Against Breast Cancer. SASBAC was supported by funding from the Agency for Science, Technology and Research of Singapore (A*STAR), the US National Institute of Health (NIH) and the Susan G. Komen Breast Cancer Foundation. All three studies are genotyped as part of the Collaborative Oncological Gene-environment Study (COGS), which is supported by the European Community's Seventh Framework Programme under grant agreement 223175 (HEALTH-F2-2009-223175) (COGS). Genotyping of the iCOGS array was funded by the European Union (HEALTH-F2-2009-223175), Cancer Research UK (C1287/A10710), the Canadian Institutes of Health Research (CIHR) for the CIHR Team in Familial Risks of Breast Cancer program and the Ministry of Economic Development, Innovation and Export Trade of Quebec (grant PSR-SIIRI-701). BCAC is funded by Cancer Research UK (C1287/A10118 and C1287/A12014). Combining the GWAS data was supported in part by the US National Institutes of Health (NIH) Cancer Post-Cancer GWAS initiative grant 1 U19 CA 148065-01 (DRIVE, part of the GAME-ON initiative). KC was financed by the Swedish Cancer Society (5128-B07-01PAF). KH was supported by the Swedish Research Council (523-2006-972) and the Swedish E Science Research Centre. This work was also supported, in part, by the Intramural Research Program of the U.S. National Cancer Institute, Department of Health and Human Services, USA. We wish to thank Aki Tuuliainen, Kimberley Sio Kim Chua, Sander Canisius, Grethe I.G. Alnæs, Torben Luders and Lodewyk Wessels for their help in data collection and analysis Sí

Article, Background Multiple recent genome-wide association studies (GWAS) have identified a single nucleotide polymorphism (SNP), rs10771399, at 12p11 that is associated with breast cancer risk. Method We performed a fine-scale mapping study of a 700 kb region including 441 genotyped and more than 1300 imputed genetic variants in 48,155 cases and 43,612 controls of European descent, 6269 cases and 6624 controls of East Asian descent and 1116 cases and 932 controls of African descent in the Breast Cancer Association Consortium (BCAC; http://bcac.ccge.medschl.cam.ac.uk/), and in 15,252 BRCA1 mutation carriers in the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA). Stepwise regression analyses were performed to identify independent association signals. Data from the Encyclopedia of DNA Elements project (ENCODE) and the Cancer Genome Atlas (TCGA) were used for functional annotation. Results Analysis of data from European descendants found evidence for four independent association signals at 12p11, represented by rs7297051 (odds ratio (OR) = 1.09, 95 % confidence interval (CI) = 1.06–1.12; P = 3 × 10-9), rs805510 (OR = 1.08, 95 % CI = 1.04–1.12, P = 2 × 10-5), and rs1871152 (OR = 1.04, 95 % CI = 1.02–1.06; P = 2 × 10-4) identified in the general populations, and rs113824616 (P = 7 × 10-5) identified in the meta-analysis of BCAC ER-negative cases and BRCA1 mutation carriers. SNPs rs7297051, rs805510 and rs113824616 were also associated with breast cancer risk at P, published version, peerReviewed

Store deler av den norske befolkningen rammes av en psykisk lidelse i løpet av livet. Angstlidelser og depressive lidelser er to av de vanligste gruppene psykiske lidelser. I løpet av livet vil rundt en av fire rammes av en angstlidelse, og en av fem av depresjon. Et stort antall mennesker med angst og depresjoner som hemmer fungering i hverdagen genererer samfunnsøkonomiske kostnader på flere områder. I samfunnet i dag ser vi at etterspørselen etter sykdomsforebyggende tiltak er mye større enn det faktiske tilbudet. Dette er med på å opprettholde de samfunnsøkonomiske kostnadene vi ser i dag også på lengre sikt. Angst og depresjoner er en av de største årsakene til arbeidsfravær, sykemelding og uførhet i Norge (Berge, 2016). I denne oppgaven forsøker vi å framstille de samfunnsøkonomiske kostnadene knyttet til arbeidsavviket sykdommene framkaller. Fokuset i oppgaven er å gi et bilde på hva de arbeidsrelaterte samfunnsøkonomiske kostnadene er på årsbasis, vi har beregnet dette i 2015 verdi. Problemsstillingen vi søker å svare på i denne oppgaven er hvor mye koster det for samfunnet at deler av den norske arbeidsstyrken lider av angst og depresjoner. Vi ser på kostnadsstrømmen knyttet til beholdningen av arbeidsstyrken som står helt eller delvis utenfor arbeidslivet, grunnet angst og depresjoner. Beregningene tar utgangspunkt i gjennomgått litteratur om sykdomsomfanget. For å kunne si noe mer om langtidseffektene vil vi avslutte oppgaven med en scenarioanalyse. Analysen vil systematisere tidligere kostnadsberegninger og ta utgangspunkt i variablene kjønn og alder. Scenarioanalysen vil i motsetning til beregningene av kostnadene for et år, se på hvor store kostnader et enkeltindivid kan genere på lengre sikt om personen faller helt eller delvis ut av yrkeslivet. Både kostnadsstrømmen knyttet til beholdningen av syke og scenarioanalysen er ment for å tydeliggjøre behovet for eventuelle tiltak rettet mot forebyggingen av de psykiske lidelsene. Analysen i seg selv forteller lite om hvordan ressurser i helsevesenet bør fordeles, men tydeliggjør behovet for kostnadsreduserende tiltak på problemområdet. Oppgaven er først og fremst ment å være oppmerksomhetsvekkende.