Targeting within ER positive early breast cancer: patient selection for current therapies and novel therapeutic approaches in a heterogeneous group

Over 1 million women a year are diagnosed with Breast Cancer. The majority, approximately 70% express the oestrogen receptor (ER). ER positive breast cancer has historically been perceived as a ‘good cancer’, although many woman with ER+ breast cancer still succumb to their disease and globally breast cancer is the leading cause of female cancer deaths. The advent of gene expression profiling and the definition of the molecular instrinsic subtypes has defined at least two subtypes of ER positive breast cancers (luminal A and luminal B) that differ markedly in terms of biological behaviour, response to adjuvant therapies and most importantly patient outcome. The focus of this research is ER+ breast cancer and targeting patient therapy in this heterogeneous group. This work attempts to translate our understanding of the biology of the ER and cell signalling interactions to aid the correct identification of patients for both current therapy and more novel therapeutic approaches. Following a hypothesis generating pilot study examining whether the level of ER influences response to endocrine therapy, 557 formalin fixed paraffin embedded (FFPE) breast cancer specimens retrieved at time of definitive surgery from early breast cancer patients with available accurate 15 years follow up data were analysed to measure ER, Progesterone receptor (PgR), HER2 and Ki67 expression using immunohistochemistry. Tumour expression of ER, PgR and the combined endocrine receptor (CER), which considers the expression level of both hormone receptors and hypothesised to more accurately quantify endocrine responsiveness by acting as a surrogate marker of a functioning ER signalling pathway, were analysed. The results suggest that in this cohort of ER+ endocrine treated patients CER is a better predictor of endocrine response than either the ER of PgR independently. The CER was thereafter utilised as a surrogate marker of oestrogen receptor signalling pathway to develop a scoring system which included HER2 IHC expression and tumour histological grade, as surrogate markers of the 3 key pathways (ER signalling, HER2 signalling and proliferation). These were chosen as previous studies comparing various gene prognostic profiles indicate commonality in sampling groups of the genes representing their activation. The scoring system, named the Clinical Outcome Score (COS) was developed to represent a pragmatic equivalent of gene prognostic profiles utilising currently routinely measured tumour markers. We hypothesised that COS as an indicator of tumour biology may aid identification of risk in the very challenging group, ER+/HER2 negative patients with intermediate grade and low disease burden, and may help guide adjuvant therapy decisions particularly the indication for chemotherapy . In this exploratory analysis, the distribution of COS scores (2-10) followed a linear response with a notable separation between low scores (2-4) and high scores (5-10). Importantly, when analysed in combination with tumour burden, low COS may help identify patients with nearly 100% long term survival, however in all analysis high COS was associated with a highly significant poorer outcome in terms of early recurrence, late recurrence and 15 year breast cancer specific survival. This group of high risk ER+ breast cancer patients represent a real challenge (and concern) in the treatment of early breast cancer, as there is increasing evidence that ER+ tumours are relatively chemo-in senstive and the response to chemotherapy agents is limited. As a secondary analysis, within our cohort of ER+/ HER2- endocrine treated patients we retrospectively analysed the benefit of chemotherapy in patients with low and high COS scores and the results indicate lack of benefit in the cohort of patients diagnosed 1995-1998. Investigating novel therapeutic targets focusing on the subtypes of breast cancer, and tumour biology involved in endocrine resistance is now beginning to take precedence in breast cancer research. Two potential new therapeutic targets in ER+ breast cancer were studied. The first is the sodium iodide symporter, NIS, a transmembrane glycoprotein which has been exploited for the safe delivery of radio-iodide in the treatment of thyroid cancers for many years. NIS is expressed in many breast cancers, however most breast cancers expressing NIS lack functional uptake as demonstrated by scintography studies and in vivo animal work. In vitro results suggest that the ER is important in NIS regulation and function. In addition MAPK and PI3K-Akt signalling pathways may have a role in NIS regulation- both these pathways are often activated in ER+ breast cancer and known to have extensive crosstalk with the ER. Utilising ER+ and ER negative breast cancer cell lines we examined NIS function following gene delivery with a human NIS (hNIS) transfected plasmid and assessed function and expression of NIS following ER knockdown by siRNA. Our results suggest that the ER phenotype is important but not necessarily the ER per say. We examined NIS expression in a mixed ER+ and ER- cohort (n=50) of patient tumour samples using real time RT-PCR, and report high levels of NIS mRNA expression was limited to ER+ breast tumours. Prompting analysis of NIS expression, cellular location and correlations with cell signalling proteins in 300 ER+ breast cancers using IHC . Significant correlations were identified with key members of the PI3K-Akt and MAPK supporting their role in NIS regulation in vivo. Importantly, in both patient cohorts NIS was found to be significantly associated with poor outcome, and we hypothesis that this is an effect of enhanced growth factor signalling and activation of pathways in biologically more aggressive ER+ cancer (ER+/PgR-) may also regulate NIS and suggest future directions of research. Lastly, as a pilot study expression of Src kinase, a non receptor tyrosine kinase implicated in tamoxifen resistance and breast cancer virulence, was analysed by IHC in the ER+ breast cancer patient cohort. Interestingly nuclear Src kinase was found to be associated with improved outcome and hypothesise that Src Kinase expression in breast cancer may have varying roles in the different subtypes of breast cancer, an important consideration as Src Kinase inhibitors are currently in clinical trials. This pilot study formed a hypothesis that was subsequently examined in another student’s PhD thesis

Admixture Mapping of African–American Women in the AMBER Consortium Identifies New Loci for Breast Cancer and Estrogen-Receptor Subtypes

Recent genetic admixture coupled with striking differences in incidence of estrogen receptor (ER) breast cancer subtypes, as well as severity, between women of African and European ancestry, provides an excellent rationale for performing admixture mapping in African American women with breast cancer risk. We performed the largest breast cancer admixture mapping study with in African American women to identify novel genomic regions associated with the disease. We conducted a genome-wide admixture scan using 2,624 autosomal ancestry informative markers (AIMs) in 3,629 breast cancer cases (including 1,968 ER-positive, 1093 ER-negative, and 601 triple-negative) and 4,658 controls from the African American Breast Cancer Epidemiology and Risk (AMBER) Consortium, a collaborative study of four large geographically different epidemiological studies of breast cancer in African American women. We used an independent case-control study to test for SNP association in regions with genome-wide significant admixture signals. We found two novel genome-wide significant regions of excess African ancestry, 4p16.1 and 17q25.1, associated with ER-positive breast cancer. Two regions known to harbor breast cancer variants, 10q26 and 11q13, were also identified with excess of African ancestry. Fine-mapping of the identified genome-wide significant regions suggests the presence of significant genetic associations with ER-positive breast cancer in 4p16.1 and 11q13. In summary, we identified three novel genomic regions associated with breast cancer risk by ER status, suggesting that additional previously unidentified variants may contribute to the racial differences in breast cancer risk in the African American population

BRCA2 polymorphic stop codon K3326X and the risk of breast, prostate, and ovarian cancers

Background: The K3326X variant in BRCA2 (BRCA2*c.9976A>T; p.Lys3326*; rs11571833) has been found to be associated with small increased risks of breast cancer. However, it is not clear to what extent linkage disequilibrium with fully pathogenic mutations might account for this association. There is scant information about the effect of K3326X in other hormone-related cancers. Methods: Using weighted logistic regression, we analyzed data from the large iCOGS study including 76 637 cancer case patients and 83 796 control patients to estimate odds ratios (ORw) and 95% confidence intervals (CIs) for K3326X variant carriers in relation to breast, ovarian, and prostate cancer risks, with weights defined as probability of not having a pathogenic BRCA2 variant. Using Cox proportional hazards modeling, we also examined the associations of K3326X with breast and ovarian cancer risks among 7183 BRCA1 variant carriers. All statistical tests were two-sided. Results: The K3326X variant was associated with breast (ORw = 1.28, 95% CI = 1.17 to 1.40, P = 5.9x10- 6) and invasive ovarian cancer (ORw = 1.26, 95% CI = 1.10 to 1.43, P = 3.8x10-3). These associations were stronger for serous ovarian cancer and for estrogen receptor–negative breast cancer (ORw = 1.46, 95% CI = 1.2 to 1.70, P = 3.4x10-5 and ORw = 1.50, 95% CI = 1.28 to 1.76, P = 4.1x10-5, respectively). For BRCA1 mutation carriers, there was a statistically significant inverse association of the K3326X variant with risk of ovarian cancer (HR = 0.43, 95% CI = 0.22 to 0.84, P = .013) but no association with breast cancer. No association with prostate cancer was observed. Conclusions: Our study provides evidence that the K3326X variant is associated with risk of developing breast and ovarian cancers independent of other pathogenic variants in BRCA2. Further studies are needed to determine the biological mechanism of action responsible for these associations

The Potential for Enhancing the Power of Genetic Association Studies in African Americans through the Reuse of Existing Genotype Data

We consider the feasibility of reusing existing control data obtained in genetic association studies in order to reduce costs for new studies. We discuss controlling for the population differences between cases and controls that are implicit in studies utilizing external control data. We give theoretical calculations of the statistical power of a test due to Bourgain et al (Am J Human Genet 2003), applied to the problem of dealing with case-control differences in genetic ancestry related to population isolation or population admixture. Theoretical results show that there may exist bounds for the non-centrality parameter for a test of association that places limits on study power even if sample sizes can grow arbitrarily large. We apply this method to data from a multi-center, geographically-diverse, genome-wide association study of breast cancer in African-American women. Our analysis of these data shows that admixture proportions differ by center with the average fraction of European admixture ranging from approximately 20% for participants from study sites in the Eastern United States to 25% for participants from West Coast sites. However, these differences in average admixture fraction between sites are largely counterbalanced by considerable diversity in individual admixture proportion within each study site. Our results suggest that statistical correction for admixture differences is feasible for future studies of African-Americans, utilizing the existing controls from the African-American Breast Cancer study, even if case ascertainment for the future studies is not balanced over the same centers or regions that supplied the controls for the current study

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

Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial

Background Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy

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

Genome-wide association studies in women of African ancestry identified 3q26.21 as a novel susceptibility locus for oestrogen receptor negative breast cancer

Multiple breast cancer loci have been identified in previous genome-wide association studies, but they were mainly conducted in populations of European ancestry. Women of African ancestry are more likely to have young-onset and oestrogen receptor (ER) negative breast cancer for reasons that are unknown and understudied. To identify genetic risk factors for breast cancer in women of African descent, we conducted a meta-analysis of two genome-wide association studies of breast cancer; one study consists of 1,657 cases and 2,029 controls genotyped with Illumina's HumanOmni2.5 BeadChip and the other study included 3,016 cases and 2,745 controls genotyped using Illumina Human1M-Duo BeadChip. The top 18,376 single nucleotide polymorphisms (SNP) from the meta-analysis were replicated in the third study that consists of 1,984 African Americans cases and 2,939 controls. We found that SNP rs13074711, 26.5 Kb upstream of TNFSF10 at 3q26.21, was significantly associated with risk of oestrogen receptor (ER)-negative breast cancer (odds ratio [OR]=1.29, 95% CI: 1.18-1.40; P = 1.8 × 10 (-) (8)). Functional annotations suggest that the TNFSF10 gene may be involved in breast cancer aetiology, but further functional experiments are needed. In addition, we confirmed SNP rs10069690 was the best indicator for ER-negative breast cancer at 5p15.33 (OR = 1.30; P = 2.4 × 10 (-) (10)) and identified rs12998806 as the best indicator for ER-positive breast cancer at 2q35 (OR = 1.34; P = 2.2 × 10 (-) (8)) for women of African ancestry. These findings demonstrated additional susceptibility alleles for breast cancer can be revealed in diverse populations and have important public health implications in building race/ethnicity-specific risk prediction model for breast cancer