DACH1: its role as a classifier of long term good prognosis in luminal breast cancer

Background: Oestrogen receptor (ER) positive (luminal) tumours account for the largest proportion of females with breast cancer. Theirs is a heterogeneous disease presenting clinical challenges in managing their treatment. Three main biological luminal groups have been identified but clinically these can be distilled into two prognostic groups in which Luminal A are accorded good prognosis and Luminal B correlate with poor prognosis. Further biomarkers are needed to attain classification consensus. Machine learning approaches like Artificial Neural Networks (ANNs) have been used for classification and identification of biomarkers in breast cancer using high throughput data. In this study, we have used an artificial neural network (ANN) approach to identify DACH1 as a candidate luminal marker and its role in predicting clinical outcome in breast cancer is assessed. Materials and methods: A reiterative ANN approach incorporating a network inferencing algorithm was used to identify ER- associated biomarkers in a publically available cDNA microarray dataset. DACH1 was identified in having a strong influence on ER associated markers and a positive association with ER. Its clinical relevance in predicting breast cancer specific survival was investigated by statistically assessing protein expression levels after immunohistochemistry in a series of unselected breast cancers, formatted as a tissue microarray. Results: Strong nuclear DACH1 staining is more prevalent in tubular and lobular breast cancer. Its expression correlated with ER-alpha positive tumours expressing PgR, epithelial cytokeratins (CK)18/19 and 'luminal-like' markers of good prognosis including FOXA1 and RERG (p , 0.05). DACH1 is increased in patients showing longer cancer specific survival and disease free interval and reduced metastasis formation (p , 0.001). Nuclear DACH1 showed a negative association with markers of aggressive growth and poor prognosis. Conclusion: Nuclear DACH1 expression appears to be a Luminal A biomarker predictive of good prognosis, but is not independent of clinical stage, tumour size, NPI status or systemic therapy

Single-strand selective monofunctional uracil-DNA glycosylase (SMUG1) deficiency is linked to aggressive breast cancer and predicts response to adjuvant therapy

Uracil in DNA is an important cause of mutagenesis. SMUG1 is a uracil DNA glycosylase that removes uracil through base excision repair. SMUG1 also processes radiation induced oxidative base damage as well as 5-fluorouracil incorporated into DNA during chemotherapy. We investigated SMUG1 mRNA expression in 249 primary breast cancers. SMUG1 protein expression was investigated in 1165 breast tumours randomised into two cohorts [training set (n=583) and test set (n=582)]. SMUG1 and chemotherapy response was also investigated in a series of 315 ER negative tumours (n=315). For mechanistic insights, SMUG1 was correlated to biomarkers of aggressive phenotype, DNA repair, cell cycle and apoptosis. Low SMUG1 mRNA expression was associated with adverse disease specific survival (p=0.008) and disease free survival (p=0.008). Low SMUG1 protein expression (25%) was associated with high histological grade (p<0.0001), high mitotic index (p<0.0001), pleomorphism (p<0.0001), glandular de-differentiation (p=0.0001), absence of hormonal receptors (ER-/PgR-/AR) (p<0.0001), presence of basal-like (p<0.0001) and triple negative phenotypes (p<0.0001). Low SMUG1 protein expression was associated with loss of BRCA1 (p<0.0001), ATM (p<0.0001) and XRCC1 (p<0.0001). Low p27 (p<0.0001), low p21 (p=0.023), mutant p53 (p=0.037), low MDM2 (p<0.0001), low MDM4 (p=0.004), low Bcl-2 (p=0.001), low Bax (p=0.003) and high MIB1 (p<0.0001) were likely in low SMUG1 tumours. Low SMUG1 protein expression was associated with poor prognosis in univariate (p<0.001) and multivariate analysis (p<0.01). In ER+ cohort that received adjuvant endocrine therapy, low SMUG1 protein expression remains associated with poor survival (p<0.01). In ER- cohort that received adjuvant chemotherapy, low SMUG1 protein expression is associated with improved survival (p=0.043). Our study suggests that low SMUG1 expression may correlate to adverse clinicopathological features and predict response to adjuvant therapy in breast cancer

DNA polymerase B deficiency is linked to aggressive breast cancer: a comprehensive analysis of gene copy number, mRNA and protein expression in multiple cohorts

Short arm of chromosome 8 is a hot spot for chromosomal breaks, losses and amplifications in breast cancer. Although such genetic changes may have phenotypic consequences, the identity of candidate gene(s) remains to be clearly defined. Pol β gene is localized to chromosome 8p12 - p11 and encodes a key DNA base excision repair protein. Pol β may be a tumour suppressor and involved in breast cancer pathogenesis. We conducted the first and the largest study to comprehensively evaluate pol β in breast cancer. We investigated pol β gene copy number changes in two cohorts (n=128 & n=1952), pol β mRNA expression in two cohorts (n=249 & n=1952) and pol β protein expression in two cohorts (n=1406 & n=252). Artificial neural network analysis for pol β interacting genes was performed in 249 tumours. For mechanistic insights, pol β gene copy number changes, mRNA and protein levels were investigated together in 1 28 tumours and validated in 1952 tumours. Low pol β mRNA expression as well as low pol β protein expression was associated high grade, lymph node positivity, pleomorphism, triple negative, basal - like phenotypes and poor survival (ps<0.001). In oestrogen receptor (ER) positive sub - group that received tamoxifen, low pol β protein remains associated with aggressive phenotype and poor survival (ps<0.001). Artificial neural network analysis revealed ER as a top pol β interacting gene. Mechanistically, there was strong positive correlation between pol β gene copy number changes and pol β mRNA expression (p<0.0000001) and between pol β mRNA and pol β protein expression (p<0.0000001). This is the first study to provide evidence that pol β deficiency is linked to aggressive breast cancer and may have prognostic and predictive significance in patients

Breast cancer histologic grading using digital microscopy: concordance and outcome association

Aims: Virtual microscopy utilising digital whole slide imaging (WSI) is increasingly used in breast pathology. Histologic grade is one of the strongest prognostic factors in breast cancer (BC). This study aims at investigating the agreement between BC grading using traditional light microscopy (LM) and digital whole slide imaging (WSI) with consideration of reproducibility and impact on outcome prediction. Methods: A large (n=1675) well-characterised cohort of BC originally graded by LM was re-graded using WSI. Two separate virtual-based grading sessions (V1 and V2) were performed with a three months washout period. Outcome was assessed using breast cancer specific and distant metastasis free survival. Results: The concordance between LM grading and WSI was strong (LM/SWI Cramer’s V: V1=0.576, and V2=0.579). The agreement regarding grade components was as follows: Tubule formation=0.538, Pleomorphism=0.422 and Mitosis=0.514. Greatest discordance was observed between adjacent grades whereas high/low grade discordance was uncommon (1.5%). The intra-observer agreement for the two WSI sessions was substantial for grade (V1/V2 Cramer’s V=0.676; kappa=0.648) and grade components (Cramer’s V T=0.628, P=0.573 and M=0.580). Grading using both platforms showed strong association with outcome (All p-value <0.001). Although mitotic scores assessed using both platforms were strongly associated with outcome, WSI tends to underestimate mitotic counts. Conclusions: Virtual microscopy is a reliable and reproducible method for assessing BC histologic grade. Regardless of the observer or assessment platform, histologic grade is a significant predictor of outcome. Continuing advances in imaging technology could potentially provide improved performance of WSI BC grading and in particular mitotic count assessment

Microarray studies reveal novel genes associated with endocrine resistance in breast cancer

Background Endocrine resistance is a major hurdle in breast cancer management, and determining the underlying factors driving its growth and aggressive behaviour should vastly improve treatment. Methods Microarray technology (BD Atlas Plastic Human 12 K Microarrays; GeneSifter software), verified by PCR, western blotting and immunocytochemisty, was used to identify genes increased in acquired resistant models to tamoxifen (TamR) or faslodex (FasR) as potential predictive/prognostic markers and new therapeutic targets. Results Alongside known breast cancer genes (β-catenin, PEA3, vitronectin, CD44), two novel genes in endocrine resistance were revealed (the latter never previously described in breast cancer): a securin/cell cycle regulator Pituitary Tumour Transforming Gene-1 (PTTG1), and GDNF receptor-alpha 3 (GFRα3) reported to promote cell survival signalling via RET coreceptor. Altered levels of PTTG1, GFRα3, or their associated family members were observed in further endocrine resistant states, including an additional faslodex resistant model that has progressed to a highly-aggressive state (FasR-Lt) and XMCF-7 cells resistant to oestrogen deprivation. PTTG1 and GFRα3 induction were also implicated in limiting response to anti-EGFR agents currently in breast cancer trials, with GFRα3 ligand (artemin) largely overcoming drug response. mRNA studies in clinical disease revealed PTTG1 associated with lymph node spread, high tumour grade and proliferation, while GFRα3 was enriched in ER-negative tumours and those expressing EGFR, profiles implying roles in clinical resistance and aggressive tumour behaviour. Promisingly, PTTG1 or GFRα3 siRNA knockdown promoted cell kill and inhibited proliferation in the resistant models. Conclusion Cumulatively, these data indicate PTTG1 and GFRα3 may provide useful biomarkers, and perhaps clinically relevant therapeutic targets for multiple resistant states

Recruitment of insulin receptor substrate-1 by erbB3 impacts on IGF-IR signalling in oestrogen receptor-positive breast cancer cells

Insulin-like growth factor receptor (IGF-IR) signalling classically involves phosphorylation of insulin receptor substrate-1 (IRS-1) to recruit key down-stream signalling pathways effecting breast cancer cell proliferation and survival. Recently, we have shown a further capacity for IRS-1 to associate with the epidermal growth factor receptor (EGFR/erbB1), with activation of EGFR promoting recruitment and phosphorylation of IRS-1 in an oestrogen receptor (ER)-positive tamoxifen-resistant breast cancer cell line. In this study, we examined recruitment of IRS-1 by another member of the erbB receptor family, erbB3, in three ER-positive breast cancer cell lines. Our studies revealed an interaction between erbB3 and IRS-1 in MCF-7, T47D and BT474 cells with HRGβ1 treatment significantly enhancing this recruitment and promoting IRS-1 phosphorylation at tyrosine (Y) 612, a specific phosphoinositide 3-kinase (PI3K) binding site. IRS-1 appears to play a key role in erbB3 signalling in MCF-7 and T47D cells as its knockdown using siRNA greatly impaired HRGβ1 signalling via PI3K/AKT in these cell lines. This novel interaction may have clinical relevance as immunohistochemical analysis of ER-positive breast cancer patient samples revealed IRS-1 Y612 expression positively correlated with total erbB3, p-AKT and Ki67 expression. Importantly, we found that recruitment of IRS-1 by erbB3 impaired IRS-1 recruitment by IGF-IR in both MCF-7 and T47D cells, whilst blockade of IGF-1R enhanced erbB3/IRS-1 interaction and sensitised both cell lines to HRGβ1. Consequently, blockade of erbB3 signalling enhanced the effects of IGF-IR inhibition in these cells. In conclusion, these and previous findings suggest that IRS-1 can be recruited to IGF-1R, EGFR and erbB3 in ER-positive breast cancer cells and this may provide an adaptive resistance mechanism when these receptors are targeted individually. Consequently co-targeting of IGF-IR and erbB receptors may prove to be a more effective strategy for the treatment of ER-positive breast cancer