Structure vs. Function of TRIB1—Myeloid Neoplasms and Beyond

The Tribbles family of proteins—comprising TRIB1, TRIB2, TRIB3 and more distantly related STK40—play important, but distinct, roles in differentiation, development and oncogenesis. Of the four Tribbles proteins, TRIB1 has been most well characterised structurally and plays roles in diverse cancer types. The most well-understood role of TRIB1 is in acute myeloid leukaemia, where it can regulate C/EBP transcription factors and kinase pathways. Structure–function studies have uncovered conformational switching of TRIB1 from an inactive to an active state when it binds to C/EBPα. This conformational switching is centred on the active site of TRIB1, which appears to be accessible to small-molecule inhibitors in spite of its inability to bind ATP. Beyond myeloid neoplasms, TRIB1 plays diverse roles in signalling pathways with well-established roles in tumour progression. Thus, TRIB1 can affect both development and chemoresistance in leukaemia; glioma; and breast, lung and prostate cancers. The pervasive roles of TRIB1 and other Tribbles proteins across breast, prostate, lung and other cancer types, combined with small-molecule susceptibility shown by mechanistic studies, suggests an exciting potential for Tribbles as direct targets of small molecules or biomarkers to predict treatment response

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

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

Identification of chemokine receptors as potential modulators of endocrine resistance in oestrogen receptor–positive breast cancers

Introduction Endocrine therapies target oestrogenic stimulation of breast cancer (BC) growth, but resistance remains problematic. Our aims in this study were (1) to identify genes most strongly associated with resistance to endocrine therapy by intersecting global gene transcription data from patients treated presurgically with the aromatase inhibitor anastrazole with those from MCF7 cells adapted to long-term oestrogen deprivation (LTED) (2) to assess the clinical value of selected genes in public clinical data sets and (3) to determine the impact of targeting these genes with novel agents. Methods Gene expression and Ki67 data were available from 69 postmenopausal women with oestrogen receptor–positive (ER+) early BC, at baseline and 2 weeks after anastrazole treatment, and from cell lines adapted to LTED. The functional consequences of target genes on proliferation, ER-mediated transcription and downstream cell signalling were assessed. Results By intersecting genes predictive of a poor change in Ki67 with those upregulated in LTED cells, we identified 32 genes strongly correlated with poor antiproliferative response that were associated with inflammation and/or immunity. In a panel of LTED cell lines, C-X-C chemokine receptor type 7 (CXCR7) and CXCR4 were upregulated compared to their wild types (wt), and CXCR7, but not CXCR4, was associated with reduced relapse-free survival in patients with ER+ BC. The CXCR4 small interfering RNA variant (siCXCR4) had no specific effect on the proliferation of wt-SUM44, wt-MCF7 and their LTED derivatives. In contrast, siCXCR7, as well as CCX733, a CXCR7 antagonist, specifically suppressed the proliferation of MCF7-LTED cells. siCXCR7 suppressed proteins associated with G1/S transition and inhibited ER transactivation in MCF7-LTED, but not wt-MCF7, by impeding association between ER and proline-, glutamic acid– and leucine-rich protein 1, an ER coactivator. Conclusions These data highlight CXCR7 as a potential therapeutic target warranting clinical investigation in endocrine-resistant BC

Relationship Between Plasma Estradiol Levels and Estrogen-Responsive Gene Expression in Estrogen Receptor–Positive Breast Cancer in Postmenopausal Women

To determine whether plasma estradiol (E2) levels are related to gene expression in estrogen receptor (ER)–positive breast cancers in postmenopausal women

A novel diffuse gastric cancer susceptibility variant in E-cadherin (CDH1) intron 2: A case control study in an Italian population

<p>Abstract</p> <p>Background</p> <p>Inherited genetic factors such as E-cadherin (<it>CDH1</it>) promoter variants are believed to influence the risk towards sporadic diffuse gastric cancer (DGC). Recently, a new regulatory region essential for <it>CDH1 </it>transcription has been identified in <it>CDH1 </it>intron 2.</p> <p>Methods</p> <p>We genotyped all known polymorphisms located within conserved sequences of <it>CDH1 </it>intron 2 (rs10673765, rs9932686, rs1125557, rs9282650, rs9931853) in an Italian population consisting of 134 DGC cases and 100 healthy controls (55 patient relatives and 45 unrelated, matched individuals). The influence of individual variants on DGC risk was assessed using χ²-tests and logistic regression. The relative contribution of alleles was estimated by haplotype analysis.</p> <p>Results</p> <p>We observed a significant (p < 0.0004) association of the <it>CDH1 </it>163+37235G>A variant (rs1125557) with DGC risk. Odds ratios were 4.55 (95%CI = 2.09–9.93) and 1.38 (95%CI = 0.75–2.55) for AA and GA carriers, respectively. When adjusted for age, sex, smoking status, alcohol intake and <it>H. pylori </it>infection, the risk estimates remained largely significant for AA carriers. Haplotype analysis suggested the 163+37235A-allele contributes to disease risk independently of the other variants studied.</p> <p>Conclusion</p> <p>The <it>CDH1 </it>163+37235G>A polymorphism may represent a novel susceptibility variant for sporadic DGC if confirmed in other populations. Considering the broad expression of E-cadherin in epithelia, this exploratory study encourages further evaluation of the 163+37235A-allele as a susceptibility variant in other carcinomas.</p

ESR1 Is Co-Expressed with Closely Adjacent Uncharacterised Genes Spanning a Breast Cancer Susceptibility Locus at 6q25.1

Approximately 80% of human breast carcinomas present as oestrogen receptor α-positive (ER+ve) disease, and ER status is a critical factor in treatment decision-making. Recently, single nucleotide polymorphisms (SNPs) in the region immediately upstream of the ER gene (ESR1) on 6q25.1 have been associated with breast cancer risk. Our investigation of factors associated with the level of expression of ESR1 in ER+ve tumours has revealed unexpected associations between genes in this region and ESR1 expression that are important to consider in studies of the genetic causes of breast cancer risk. RNA from tumour biopsies taken from 104 postmenopausal women before and after 2 weeks treatment with an aromatase (oestrogen synthase) inhibitor was analyzed on Illumina 48K microarrays. Multiple-testing corrected Spearman correlation revealed that three previously uncharacterized open reading frames (ORFs) located immediately upstream of ESR1, C6ORF96, C6ORF97, and C6ORF211 were highly correlated with ESR1 (Rs = 0.67, 0.64, and 0.55 respectively, FDR<1×10−7). Publicly available datasets confirmed this relationship in other groups of ER+ve tumours. DNA copy number changes did not account for the correlations. The correlations were maintained in cultured cells. An ERα antagonist did not affect the ORFs' expression or their correlation with ESR1, suggesting their transcriptional co-activation is not directly mediated by ERα. siRNA inhibition of C6ORF211 suppressed proliferation in MCF7 cells, and C6ORF211 positively correlated with a proliferation metagene in tumours. In contrast, C6ORF97 expression correlated negatively with the metagene and predicted for improved disease-free survival in a tamoxifen-treated published dataset, independently of ESR1. Our observations suggest that some of the biological effects previously attributed to ER could be mediated and/or modified by these co-expressed genes. The co-expression and function of these genes may be important influences on the recently identified relationship between SNPs in this region and breast cancer risk

Fatty acid oxidation is associated with proliferation and prognosis in breast and other cancers

Abstract Background Altered cellular metabolism is a hallmark of cancer but the association between utilisation of particular metabolic pathways in tumours and patient outcome is poorly understood. We sought to investigate the association between fatty acid metabolism and outcome in breast and other cancers. Methods Cox regression analysis and Gene Set Enrichment Analysis (GSEA) of a gene expression dataset from primary breast tumours with well annotated clinical and survival information was used to identify genesets associated with outcome. A geneset representing fatty acid oxidation (FAO) was then examined in other datasets. A doxycycline-inducible breast cancer cell line model overexpressing the rate-limiting enzyme in FAO, carnitine palmitoyl transferase 1A (CPT1A) was generated and analysed to confirm the association between FAO and cancer-associated characteristics in vitro. Results We identified a gene expression signature composed of 19 genes associated with fatty acid oxidation (FAO) that was significantly associated with patient outcome. We validated this observation in eight independent breast cancer datasets, and also observed the FAO signature to be prognostic in other cancer types. Furthermore, the FAO signature expression was significantly downregulated in tumours, compared to normal tissues from a variety of anatomic origins. In breast cancer, the expression of CPT1A was higher in oestrogen receptor (ER)-positive, compared to ER-negative tumours and cell lines. Importantly, overexpression of CPT1A significantly decreased the proliferation and wound healing migration rates of MDA-MB231 breast cancer cells, compared to basal expression control. Conclusions Our findings suggest that FAO is downregulated in multiple tumour types, and activation of this pathway may lower cancer cell proliferation, and is associated with improved outcomes in some cancers

Restriction site associated DNA sequencing for tumour mutation burden estimation and mutation signature analysis

Abstract Background Genome‐wide measures of genetic disruption such as tumour mutation burden (TMB) and mutation signatures are emerging as useful biomarkers to stratify patients for treatment. Clinicians commonly use cancer gene panels for tumour mutation burden estimation, and whole genome sequencing is the gold standard for mutation signature analysis. However, the accuracy and cost associated with these assays limits their utility at scale. Methods WGS data from 560 breast cancer patients was used for in silico library simulations to evaluate the accuracy of an FDA approved cancer gene panel as well as restriction enzyme associated DNA sequencing (RADseq) libraries for TMB estimation and mutation signature analysis. We also transfected a mouse mammary cell line with APOBEC enzymes and sequenced resulting clones to evaluate the efficacy of RADseq in an experimental setting. Results RADseq had improved accuracy of TMB estimation and derivation of mutation profiles when compared to the FDA approved cancer panel. Using simulated immune checkpoint blockade (ICB) trials, we show that inaccurate TMB estimation leads to a reduction in power for deriving an optimal TMB cutoff to stratify patients for immune checkpoint blockade treatment. Additionally, prioritisation of APOBEC hypermutated tumours in these trials optimises TMB cutoff determination for breast cancer. The utility of RADseq in an experimental setting was also demonstrated, based on characterisation of an APOBEC mutation signature in an APOBEC3A transfected mouse cell line. Conclusion In conclusion, our work demonstrates that RADseq has the potential to be used as a cost‐effective, accurate solution for TMB estimation and mutation signature analysis by both clinicians and basic researchers