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Introduction: Low serum selenium and altered tumour RNA expression of certain selenoproteins are associated with a poor breast cancer prognosis. Selenoprotein expression stringently depends on selenium availability, hence circulating selenium may interact with tumour selenoprotein expression. However, there is no matched analysis to date. Methods: This study included 1453 patients with newly diagnosed breast cancer from the multicentric prospective Sweden Cancerome Analysis Network – Breast study. Total serum selenium, selenoprotein P and glutathione peroxidase 3 were analysed at time of diagnosis. Bulk RNA-sequencing was conducted in matched tumour tissues. Fully adjusted Cox regression models with an interaction term were employed to detect dose-dependent interactions of circulating selenium with the associations of tumour selenoprotein mRNA expression and mortality. Results: 237 deaths were recorded within ~ 9 years follow-up. All three serum selenium biomarkers correlated positively (p < 0.001). All selenoproteins except for GPX6 were expressed in tumour tissues. Single cell RNA-sequencing revealed a heterogeneous expression pattern in the tumour microenvironment. Circulating selenium correlated positively with tumour SELENOW and SELENON expression (p < 0.001). In fully adjusted models, the associations of DIO1, DIO3 and SELENOM with mortality were dose-dependently modified by serum selenium (p < 0.001, p = 0.020, p = 0.038, respectively). With increasing selenium, DIO1 and SELENOM associated with lower, whereas DIO3 expression associated with higher mortality. Association of DIO1 with lower mortality was only apparent in patients with high selenium [above median (70.36 µg/L)], and the HR (95%CI) for one-unit increase in log(FPKM + 1) was 0.70 (0.50–0.98). Conclusions: This first unbiased analysis of serum selenium with the breast cancer selenotranscriptome identified an effect-modification of selenium on the associations of DIO1, SELENOM, and DIO3 with prognosis. Selenium substitution in patients with DIO1-expressing tumours merits consideration to improve survival. [ABSTRACT FROM AUTHOR]

Objective: To investigate CITED1 as a potential biomarker of anti-endocrine response and breast cancer recurrence, given its previously determined role in mediating estrogen-dependant transcription. The study is a continuation of earlier work establishing the role of CITED1 in mammary gland development. Results: CITED1 mRNA is associated with estrogen-receptor positivity and selectively expressed in the GOBO dataset of cell lines and tumours representing the luminal-molecular subtype. In patients treated with tamoxifen, higher CITED1 correlated with better outcome, suggesting a role in anti-estrogen response. The effect was particularly evident in the subset of estrogen-receptor positive, lymph-node negative (ER+/LN−) patients although noticeable divergence of the groups was apparent only after five years. Tissue microarray (TMA) analysis further validated the association of CITED1 protein, by immunohistochemistry, with favourable outcome in ER+, tamoxifen-treated patients. Although we also found a favourable response to anti-endocrine treatment in a larger TCGA dataset, the tamoxifen-specific effect was not replicated. Finally, MCF7 cells overexpressing CITED1 showed selective amplification of AREG but not TGFα suggesting that maintenance of specific ERα-CITED1 mediated transcription is important for the long-term response to anti-endocrine therapy. These findings together confirm the proposed mechanism of action of CITED1 and support its potential use as a prognostic biomarker. [ABSTRACT FROM AUTHOR]

Simple Summary: This study aims to assess the reliability of using a core-needle biopsy (CNB) for preoperative tumor characterization using gene expression analysis and conventional immunohistochemistry (IHC) analysis for clinical biomarkers in early breast cancer. Obtaining a preoperative CNB is a standard procedure in the evaluation of a primary breast cancer, with previous studies suggesting that it can be considered trustworthy to perform immunohistochemical analysis on CNB samples. However, little research has been carried out to evaluate whether gene expression-based biomarker assessment can be carried out reliably on the preoperative CNB. This information is important as genomic profiling is gaining ever-increasing importance in the treatment of early breast cancer. In early breast cancer, a preoperative core-needle biopsy (CNB) is vital to confirm the malignancy of suspected lesions and for assessing the expression of treatment predictive and prognostic biomarkers in the tumor to choose the optimal treatments, emphasizing the importance of obtaining reliable results when biomarker status is assessed on a CNB specimen. This study aims to determine the concordance between biomarker status assessed as part of clinical workup on a CNB compared to a medically untreated surgical specimen. Paired CNB and surgical specimens from 259 patients that were part of the SCAN-B cohort were studied. The concordance between immunohistochemical (IHC) and gene expression (GEX) based biomarker status was investigated. Biomarkers of interest included estrogen receptor (ER; specifically, the alpha variant), progesterone receptor (PgR), Ki67, HER2, and tumor molecular subtype. In general, moderate to very good correlation in biomarker status between the paired CNB and surgical specimens was observed for both IHC assessment (83–99% agreement, kappa range 0.474–0.917) and GEX assessment (70–97% agreement, kappa range 0.552–0.800), respectively. However, using IHC, 52% of cases with low Ki67 status in the CNB shifted to high Ki67 status in the surgical specimen (McNemar's p = 0.011). Similarly, when using GEX, a significant shift from negative to positive ER (47%) and from low to high Ki67 (16%) was observed between the CNB and surgical specimen (McNemar's p = 0.027 and p = 0.002 respectively). When comparing biomarker status between different techniques (IHC vs. GEX) performed on either CNBs or surgical specimens, the agreement in ER, PgR, and HER2 status was generally over 80% in both CNBs and surgical specimens (kappa range 0.395–0.708), but Ki67 and tumor molecular subtype showed lower concordance levels between IHC and GEX (48–62% agreement, kappa range 0.152–0.398). These results suggest that both the techniques used for collecting tissue samples and analyzing biomarker status have the potential to affect the results of biomarker assessment, potentially also impacting treatment decisions and patient survival outcomes. [ABSTRACT FROM AUTHOR]

Breast cancer is a disease of genomic alterations, of which the panorama of somatic mutations and how these relate to subtypes and therapy response is incompletely understood. Within SCAN‐B (ClinicalTrials.gov: NCT02306096), a prospective study elucidating the transcriptomic profiles for thousands of breast cancers, we developed a RNA‐seq pipeline for detection of SNVs/indels and profiled a real‐world cohort of 3,217 breast tumors. We describe the mutational landscape of primary breast cancer viewed through the transcriptome of a large population‐based cohort and relate it to patient survival. We demonstrate that RNA‐seq can be used to call mutations in genes such as PIK3CA,TP53, and ERBB2, as well as the status of molecular pathways and mutational burden, and identify potentially druggable mutations in 86.8% of tumors. To make this rich dataset available for the research community, we developed an open source web application, the SCAN‐B MutationExplorer (http://oncogenomics.bmc.lu.se/MutationExplorer). These results add another dimension to the use of RNA‐seq as a clinical tool, where both gene expression‐ and mutation‐based biomarkers can be interrogated in real‐time within 1 week of tumor sampling. Synopsis: A bioinformatics pipeline was developed for detection of single nucleotide variants and small insertions/deletions from RNA sequencing (RNA‐seq) data. The mutational landscape of 3,217 primary breast cancer transcriptomes in relation to patient survival was made available through a public web portal. An optimized pipeline for detection of single nucleotide variants and short insertions and deletions from RNA‐seq data was developed and applied to 3,217 primary breast tumors.The mutational portraits identified mutations in clinically important genes, including mutations in one or more potentially druggable genes in 85.3% percent of cases.Mutational portraits revealed significant relationships to patient outcome within specific treatment groups, including treatment resistance mutations.This rich dataset was made publicly available via our open source web‐based application, the SCAN‐B MutationExplorer, accessible at http://oncogenomics.bmc.lu.se/MutationExplorer. [ABSTRACT FROM AUTHOR]

Background: The basal-like breast cancer (BLBC) subtype is characterized by positive staining for basal mammary epithelial cytokeratin markers, lack of hormone receptor and HER2 expression, and poor prognosis with currently no approved molecularly-targeted therapies. The oncogenic signaling pathways driving basal-like tumorigenesis are not fully elucidated.Methods: One hundred sixteen unselected breast tumors were subjected to integrated analysis of phosphoinositide 3-kinase (PI3K) pathway related molecular aberrations by immunohistochemistry, mutation analysis, and gene expression profiling. Incidence and relationships between molecular biomarkers were characterized. Findings for select biomarkers were validated in an independent series. Synergistic cell killing in vitro and in vivo tumor therapy was investigated in breast cancer cell lines and mouse xenograft models, respectively.Results: Sixty-four % of cases had an oncogenic alteration to PIK3CA, PTEN, or INPP4B; when including upstream kinases HER2 and EGFR, 75 % of cases had one or more aberration including 97 % of estrogen receptor (ER)-negative tumors. PTEN-loss was significantly associated to stathmin and EGFR overexpression, positivity for the BLBC markers cytokeratin 5/14, and the BLBC molecular subtype by gene expression profiling, informing a potential therapeutic combination targeting these pathways in BLBC. Combination treatment of BLBC cell lines with the EGFR-inhibitor gefitinib plus the PI3K pathway inhibitor LY294002 was synergistic, and correspondingly, in an in vivo BLBC xenograft mouse model, gefitinib plus PI3K-inhibitor PWT-458 was more effective than either monotherapy and caused tumor regression.Conclusions: Our study emphasizes the importance of PI3K/PTEN pathway activity in ER-negative and basal-like breast cancer and supports the future clinical evaluation of combining EGFR and PI3K pathway inhibitors for the treatment of BLBC. [ABSTRACT FROM AUTHOR]

Abstract: Polycomb repressive complex 2 (PRC2) and its core member enhancer of zeste homolog 2 (EZH2) mediate the epigenetic gene silencing mark: trimethylation of lysine 27 on histone 3 (H3K27me3). H3K27me3 is characteristic of the chromatin at genes involved in developmental regulation in undifferentiated cells. Overexpression of EZH2 has been found in several cancer types such as breast, prostate, melanoma and bladder cancer. Moreover, overexpression is associated with highly proliferative and aggressive types of breast and prostate tumors. We have analyzed the abundance of EZH2 and H3K27me3 using immunohistochemistry in two large and well-characterized breast tumor data sets encompassing more than 400 tumors. The results have been analyzed in relation to the molecular subtypes of breast tumors (basal-like, luminal A, luminal B, HER2-enriched and normal-like), as well as in subtypes defined by clinical markers (triple negative, ER+/HER2−/Ki67low, ER+/HER2−/Ki67high and HER2+), and were validated in representative breast cancer cell lines by western blot. We found significantly different expression of both EZH2 and H3K27me3 across all subtypes with high abundance of EZH2 in basal-like, triple negative and HER2-enriched tumors, and high H3K27me3 in luminal A, HER2-enriched and normal-like tumors. Intriguingly, the two markers show an inverse correlation, particularly for the basal-like and triple negative tumors. Consequently, high expression of EZH2 was associated with poor distant disease-free survival whereas high expression of H3K27me3 was associated with better survival. Additionally, none of 182 breast tumors was found to carry a previously described EZH2 mutation affecting Tyr641. Our observation that increased expression of EZH2 does not necessarily correlate with increased abundance of H3K27me3 supports the idea that EZH2 can have effects beyond epigenetic silencing of target genes in breast cancer. [Copyright &y& Elsevier]

Basal-like breast cancer (BBC) is a subtype of breast cancer with poor prognosis. Inherited mutations of BRCA1, a cancer susceptibility gene involved in double-strand DNA break (DSB) repair, lead to breast cancers that are nearly always of the BBC subtype; however, the precise molecular lesions and oncogenic consequences of BRCA1 dysfunction are poorly understood. Here we show that heterozygous inactivation of the tumor suppressor gene Pten leads to the formation of basal-like mammary tumors in mice, and that loss of PTEN expression is significantly associated with the BBC subtype in human sporadic and BRCA1-associated hereditary breast cancers. In addition, we identify frequent gross PTEN mutations, involving intragenic chromosome breaks, inversions, deletions and micro copy number aberrations, specifically in BRCA1-deficient tumors. These data provide an example of a specific and recurrent oncogenic consequence of BRCA1-dependent dysfunction in DNA repair and provide insight into the pathogenesis of BBC with therapeutic implications. These findings also argue that obtaining an accurate census of genes mutated in cancer will require a systematic examination for gross gene rearrangements, particularly in tumors with deficient DSB repair. [ABSTRACT FROM AUTHOR]

Multigene expression signatures provide a molecular subdivision of early breast cancer associated with patient outcome. A gap remains in the validation of such signatures in clinical treatment groups of patients within population-based cohorts of unselected primary breast cancer representing contemporary disease stages and current treatments. A cohort of 3520 resectable breast cancers with RNA sequencing data included in the population-based SCAN-B initiative (ClinicalTrials.gov ID NCT02306096) were selected from a healthcare background population of 8587 patients diagnosed within the years 2010–2015. RNA profiles were classified according to 19 reported gene signatures including both gene expression subtypes (e.g. PAM50, IC10, CIT) and risk predictors (e.g. Oncotype DX, 70-gene, ROR). Classifications were analyzed in nine adjuvant clinical assessment groups: TNBC-ACT (adjuvant chemotherapy, n = 239), TNBC-untreated (n = 82), HER2+/ER− with anti-HER2+ ACT treatment (n = 110), HER2+/ER+ with anti-HER2 + ACT + endocrine treatment (n = 239), ER+/HER2−/LN− with endocrine treatment (n = 1113), ER+/HER2−/LN− with endocrine + ACT treatment (n = 243), ER+/HER2−/LN+ with endocrine treatment (n = 423), ER+/HER2−/LN+ with endocrine + ACT treatment (n = 433), and ER+/HER2−/LN− untreated (n = 200). Gene signature classification (e.g., proportion low-, high-risk) was generally well aligned with stratification based on current immunohistochemistry-based clinical practice. Most signatures did not provide any further risk stratification in TNBC and HER2+/ER– disease. Risk classifier agreement (low-, medium/intermediate-, high-risk groups) in ER+ assessment groups was on average 50–60% with occasional pair-wise comparisons having <30% agreement. Disregarding the intermediate-risk groups, the exact agreement between low- and high-risk groups was on average ~80–95%, for risk prediction signatures across all assessment groups. Outcome analyses were restricted to assessment groups of TNBC-ACT and endocrine treated ER+/HER2−/LN− and ER+/HER2−/LN+ cases. For ER+/HER2− disease, gene signatures appear to contribute additional prognostic value even at a relatively short follow-up time. Less apparent prognostic value was observed in the other groups for the tested signatures. The current study supports the usage of gene expression signatures in specific clinical treatment groups within population-based breast cancer. It also stresses the need of further development to reach higher consensus in individual patient classifications, especially for intermediate-risk patients, and the targeting of patients where current gene signatures and prognostic variables provide little support in clinical decision-making. [ABSTRACT FROM AUTHOR]