Transcriptomic and Protein Expression Analysis Reveals Clinicopathological Significance of Bloom Syndrome Helicase (BLM) in Breast Cancer

BLM has key roles in homologous recombination repair, telomere maintenance and DNA replication. Germ-line mutation in the BLM gene causes Bloom’s syndrome, a rare disorder characterised by premature aging and predisposition to multiple cancers including breast cancer. The clinicopathological significance of BLM in sporadic breast cancers is unknown. We investigated BLM mRNA expression in the Molecular Taxonomy of Breast Cancer International Consortium cohort (n=1950) and validated in an external dataset of 2413 tumours. BLM protein level was evaluated in the Nottingham Tenovus series comprising 1650 breast tumours. High BLM mRNA expression was highly significantly associated with high histological grade, larger tumour size, ER negative, PgR negative and triple negative phenotypes (ps<0.0001). High BLM mRNA expression was also linked to aggressive molecular phenotypes including PAM50.Her2 (p<0.0001), PAM50.Bas al (p<0.0001) and PAM50.LumB (p<0.0001) and Genufu subtype (ER+/Her2-/High proliferation) (p<0.0001). PAM50.LumA tumours and Genufu subtype (ER+/Her2-/low proliferation) were more likely to express low levels of BLM mRNA (ps<0.0001). Integrative molecular clusters (intClust) intClust.1 (p<0.0001), intClust.5 (p<0.0001), intClust.9 (p<0.0 001) and intClust.10 (p<0.0001) were also more likely in tumours with high BLM mRNA expression. High BLM mRNA expression was associated with poor breast cancer specific survival (BCSS) (ps<0.000001). At the protein level, altered sub-cellular localisation with high cytoplasmic BLM and low nuclear BLM was linked to aggressive phenotypes. In multivariate analysis, BLM mRNA and BLM protein levels independently influenced BCSS ( p=0.03). This is the first and the largest study to provide evidence that BLM is a promising biomarker in breast cancer

RECQL4 helicase has oncogenic potential in sporadic breast cancers

RECQL4 helicase is a molecular motor that unwinds DNA, a process essential during DNA replication and DNA repair. Germ-line mutations in RECQL4 cause type II Rothmund–Thomson syndrome (RTS), characterized by a premature ageing phenotype and cancer predisposition. RECQL4 is widely considered to be a tumour suppressor, although its role in human breast cancer is largely unknown. As the RECQL4 gene is localized to chromosome 8q24, a site frequently amplified in sporadic breast cancers, we hypothesized that it may play an oncogenic role in breast tumourigenesis. To address this, we analysed large cohorts for gene copy number changes (n = 1977), mRNA expression (n = 1977) and protein level (n = 1902). Breast cancer incidence was also explored in 58 patients with type II RTS. DNA replication dynamics and chemosensitivity was evaluated in RECQL4-depleted breast cancer cells in vitro. Amplification or gain in gene copy number (30.6%), high-level mRNA expression (51%) and high levels of protein (23%) significantly associated with aggressive tumour behaviour, including lymph node positivity, larger tumour size, HER2 overexpression, ER-negativity, triple-negative phenotypes and poor survival. RECQL4 depletion impaired the DNA replication rate and increased chemosensitivity in cultured breast cancer cells. Thus, although recognized as a ’safe guardian of the genome’, our data provide compelling evidence that RECQL4 is tumour promoting in established breast cancers

Clinicopathological and prognostic significance of RECQL5 helicase expression in breast cancers

RECQL5 is a member of the RecQ family of DNA helicases and has key roles in homologous recombination, base excision repair, replication and transcription. The clinicopathological significance of RECQL5 expression in breast cancer is unknown. In the current study we have evaluated RECQL5 mRNA expression in 1977 breast cancers, and RECQL5 protein level in 1902 breast cancers [Nottingham Tenovus series (n=1650) and ER- cohort (n=252)]. Expression levels were correlated to aggressive phenotypes and survival outcomes. High RECQL5 mRNA expression was significantly associated with high histological grade (p=0.007), HER2 overexpression (p=0.032), ER+/HER2-/high proliferation genefu subtype, integrative molecular clusters (intClust 1and 9) and poor breast cancer specific survival (BCSS) (ps<0.0001). In sub-group analysis, high RECQL5 mRNA level remains significantly associated with poor BCSS in ER+ cohort (p<0.0001) but not in ER- cohort (p=0.116). At the protein level, in tumours with low RAD51, high RECQL5 level was significantly associated with high histological grade (p<0.0001), higher mitotic index (p=0.008), de-differentiation (p=0.025), pleomorphism (p=0.027) and poor BCSS (P=0.003). In sub-group analysis, high RECQL5/low RAD51 remains significantly associated with poor BCSS in ER+ cohort (p=0.010), but not in ER- cohort (p=0.628). In multivariate analysis, high RECQL5 mRNA and high RECQL5/low RAD51 nuclear protein co-expression independently influenced BCSS (p=0.022) in whole cohort and in the ER+ sub-group. Pre-clinically, we show that exogenous expression of RECQL5 in MCF10A cells can drive proliferation supporting an oncogenic function for RECQL5 in breast cancer. We conclude that RECQL5 is a promising biomarker in breast cancer

HER2/HER3 heterodimers and p21 expression are capable of predicting adjuvant trastuzumab response in HER2+ breast cancer

Human epidermal growth factor receptor 2 (HER2) plays an important role in breast cancer progression and provides predictive information for response to targeted therapy including trastuzumab although this is limited. Downstream pathways, such as PI3K/Akt, are associated with HER2/HER3 heterodimerization promoting survival and proliferation amongst cancer cells. Thus, patient outcome and trastuzumab therapy effectiveness might be further characterised by HER2/HER3 dimerisation and its signalling pathways. HER2/HER3 dimerisation status was assessed, using chromogenic in situ Proximity Ligation Assay, in two breast cancer series: early stage primary breast cancer, including 224 HER2+ patients that were not submitted to trastuzumab, and HER2+ breast cancer where patients were treated with adjuvant trastuzumab (n = 143). Levels of biomarkers including PI3K, pAKT, ER, PgR, HER3, BCL2, p53, PTEN and p21 were measured using immunohistochemistry. Levels of HER2/HER3 heterodimers were compared with biomarker expression and patient outcome. An association between high levels of HER2/HER3 dimerisation and absence of hormone receptors, ER and PgR, was observed. We further show for the first time the presence of HER2/HER3 heterodimers and the loss of p21 expression in HER2+ breast cancer predicts a significantly poorer outcome when submitted to adjuvant trastuzumab. Breast cancer patients that reveal high levels of HER2/HER3 dimerisation and loss of p21 are associated with poor survival prognosis in patients with HER2+ breast cancer treated with adjuvant trastuzumab. Further quantification analysis of HER dimer/ligand complexes and downstream signalling pathways will begin to unravel the complex associations with patient outcome and its relationship with sensitivity to targeted treatment

Characterisation of HER heterodimers in breast cancer using in situ proximity ligation assay

HER2 plays an important role in breast cancer progression and provides predictive and prognostic information. HER2 receptor family members function through dimerisation, which can lead to impact on cell function, growth and differentiation; however, their value in breast cancer development remains to be defined. This study aims to examine the relationships of HER2 heterodimers to breast cancer characteristics in trastuzumab naïve and treated cases. HER2 protein (IHC), HER2 gene (chromogenic ISH) and HER2 heterodimerisation status [chromogenic in situ proximity ligation assay (PLA)] were assessed in two breast cancer series prepared in tissue microarray (TMA) format. A range of signals/cell for each HER2 heterodimer was detected (0–34.6 signals/cell). The vast majority of cases with HER2 heterodimers showed HER2 gene amplification and/or protein expression. There was an association between HER2 dimerisation with HER3 and HER4 and their protein expression level but no such association was found in with HER1 (EGFR). Of the HER2+ cases, 74, 66, and 58 % showed heterodimers with EGFR, HER3 and HER4, respectively. 51 % of HER2+ tumours expressed all three heterodimers whereas 23 % of the cases did not show expression of any of the three heterodimers. There was an inverse association between the presence and levels of HER2 heterodimers and hormone receptor expression in HER2+ tumours. Tumours exhibiting high levels of HER2 heterodimers demonstrated aggressive clinicopathological features and poor outcome. In the HER2+ cases, dimerisation with EGFR and HER3 but not with HER4 showed an association with aggressive features. There was no association between HER2 heterodimers with patient breast cancer-specific survival or recurrence in HER2+ breast cancer in those patients receiving trastuzumab or not. Our results demonstrate that HER2 dimerisation is a complex process that may underlie the biological heterogeneity of HER2 positive tumours and may identify patients suitable for a specific targeted therapy but does not predict patient outcome for those receiving trastuzumab. PLA proved to be a useful tool for detecting, visualising and quantifying the frequency of protein–protein interactions in archival formalin-fixed paraffin-embedded tissue samples

Clinicopathological Significance of ATM-Chk2 Expression in Sporadic Breast Cancers: a Comprehensive Analysis in Large Cohorts

ATM-Chk2 network is critical for genomic stability, and its deregulation may influence breast cancer pathogenesis. We investigated ATM and Chk2 protein levels in two cohorts [cohort 1 (n = 1650) and cohort 2 (n = 252)]. ATM and Chk2 mRNA expression was evaluated in the Molecular Taxonomy of Breast Cancer International Consortium cohort (n = 1950). Low nuclear ATM protein level was significantly associated with aggressive breast cancer including larger tumors, higher tumor grade, higher mitotic index, pleomorphism, tumor type, lymphovascular invasion, estrogen receptor (ER)−, PR−, AR−, triple-negative, and basal-like phenotypes (Ps b .05). Breast cancer 1, early onset negative, low XRCC1, low SMUG1, high FEN1, high MIB1, p53 mutants, low MDM2, low Bcl-2, low p21, low Bax, high CDK1, and low Chk2 were also more frequent in tumors with low nuclear ATM level (Ps b .05). Low ATM protein level was significantly associated with poor survival including in patients with ER-negative tumors who received adjuvant anthracycline or cyclophosphamide, methotrexate, and 5-fluorouracil–based adjuvant chemotherapy (Ps b .05). Low nuclear Chk2 protein was likely in ER−/PR−/AR−; HER-2 positive; breast cancer 1, early onset negative; low XRCC1; low SMUG1; low APE1; low polβ; low DNA-PKcs; low ATM; low Bcl-2; and low TOPO2A tumors (P b .05). In patients with ER+ tumors who received endocrine therapy or ER-negative tumors who received chemotherapy, nuclear Chk2 levels did not significantly influence survival. In p53 mutant tumors, low ATM (P b .000001) or high Chk2 (P b .01) was associated with poor survival. When investigated together, low-ATM/high-Chk2 tumors have the worst survival (P = .0033). Our data suggest that ATM-Chk2 levels in sporadic breast cancer may have prognostic and predictive significance

SHON expression predicts response and relapse risk of breast cancer patients after anthracycline-based combination chemotherapy or tamoxifen treatment

BACKGROUND: SHON nuclear expression (SHON-Nuc+) was previously reported to predict clinical outcomes to tamoxifen therapy in ERα+ breast cancer (BC). Herein we determined if SHON expression detected by specific monoclonal antibodies could provide a more accurate prediction and serve as a biomarker for anthracycline-based combination chemotherapy (ACT).METHODS: SHON expression was determined by immunohistochemistry in the Nottingham early-stage-BC cohort (n=1,650) who, if eligible, received adjuvant tamoxifen; the Nottingham ERα- early-stage-BC (n=697) patients who received adjuvant ACT; and the Nottingham locally advanced-BC cohort who received pre- operative ACT with/without taxanes (Neo-ACT, n=120) and if eligible, 5-year adjuvant tamoxifen treatment. Prognostic significance of SHON and its relationship with the clinical outcome of treatments were analysed.RESULTS: As previously reported, SHON-Nuc+ in high risk/ERα+ patients was significantly associated with a 48% death risk reduction after exclusive adjuvant tamoxifen treatment compared with SHON-Nuc- [HR(95%CI)=0.52(0.34-0.78), p=0.002]. Meanwhile, in ERα- patients treated with adjuvant ACT, SHON cytoplasmic expression (SHON-Cyto+) was significantly associated with a 50% death risk reduction compared with SHON-Cyto- [HR(95%CI)=0.50(0.34-0.73), p=0.0003]. Moreover, in patients received Neo-ACT, SHON-Nuc- or SHON-Cyto+ was associated with an increased pathological complete response (pCR) compared with SHON-Nuc+ [21% vs 4%; OR(95%CI)=5.88(1.28-27.03), p=0.012], or SHON-Cyto- [20.5% vs 4.5%; OR(95%CI)=5.43(1.18-25.03), p=0.017], respectively. After receiving Neo-ACT, patients with SHON-Nuc+ had a significantly lower distant relapse risk compared to those with SHON-Nuc- [HR(95%CI)=0.41(0.19-0.87), p=0.038], whereas SHON-Cyto+ patients had a significantly higher distant relapse risk compared to SHON-Cyto- patients [HR(95%CI)=4.63(1.05-20.39), p=0.043]. Furthermore, multivariate Cox regression analyses revealed that SHON-Cyto+ was independently associated with a higher risk of distant relapse after Neo-ACT and 5- year tamoxifen treatment [HR(95%CI)=5.08(1.13-44.52), p=0.037]. The interaction term between ERα status and SHON-Nuc+ (p=0.005), and between SHON-Nuc+ and tamoxifen therapy (p=0.007), were both statistically significant.CONCLUSION: SHON-Nuc+ in tumours predicts response to tamoxifen in ERα+ BC while SHON-Cyto+ predicts response to ACT

Day-to-day route choice modeling incorporating inertial behavior

Accurate route choice modeling is one of the most important aspects when predicting the effects of transport policy and dynamic traffic management. Moreover, the effectiveness of intervention measures to a large extent depends on travelers’ response to the changes these measures cause. As a complement to utility maximization theory there is growing interest in alternative approaches which debate assumptions of perfect information, rationality and homogeneity. Empirical research on suboptimal choice behavior from the perspective of travel time has led to various theories including bounded rationality, habit, satisficing and perception bias. Although these theories may differ in a strict behavioral sense, there are various analytical similarities that make it impossible to empirically distinguish between them based on observed choice alone. However, one of the phenomena that can be observed in route choice is inertial behavior, i.e. the tendency of travelers to repeatedly choosing their current path, even if this path is or becomes the non-shortest path.\ud \ud Using observations from a real-world route choice experiment, a new day-to-day dynamic route choice model, consisting of a Dynamic Expected Shortest Path Module and a Choice Strategy Module was developed, which accounts for four identified choice strategies including inertia. The data contained actual route choice data for 5 OD-pairs that were collected for a panel of 20 subjects over 20 days during peak hours on regular working days. Experienced travel conditions were recorded using a GPS device while a pre- and post-task questionnaire was included, with information about demographics, experience, but also on perceptions about traffic conditions and preference levels. First, individual’s route choice behavior is investigated, contributing to the current understanding of the daily route choice behavior of individuals, and more particular, providing insights in and understanding of factors and mechanisms that contribute to inertial behavior. Therewith, it complements the current knowledge of route choice behavior. The new model was calibrated and validated using an enter-wise regression method and a jack-knife cross validation method, and compared with a number of existing model approaches: based on the shortest path, on prospect theory, regret theory, fixed thresholds theory and on the SILK theory. Additionally, the model was extended using an agent-based approach based on Bayesian simulation in order to see the effect of this approach on the model performance. Lastly, the indifference band is quantified by altering the model attribute related to travel time within the developed model. Besides this, the data analysis and the fixed threshold theory were used to quantify the indifference band for comparison.\ud \ud Results showed that individual characteristics and characteristics of the choice situations were most important in explaining exposed choice strategies, while variables on experience were found to be less important. The 2-step-model provided correct predictions in 75.35% of the cases and had one of the most constant performances when applied on different choice situations, which places it among the state-of-the-art models with the highest performances. When examining model performances of the new and state-of-the-art models for every OD-pair, it is found that some models perform better on certain OD-pairs than others and vice versa (some performed very low < 50%). This implies that in certain circumstances or choice situations a certain route choice model would be the best to use, and suggests that a hybrid model using different choice models for different choice situations could significantly improve current modeling practice. Additionally, it was found that the model performance reduced considerably when parameter correlations were ignored which highlights that explanatory variables of route choice behavior are strongly correlated and are therefore crucial in obtaining accurate model results. Lastly, inertia thresholds between 12.1% and 22.1% of the average trip travel time were found on an individual level, and 12.6% to 16.3% of the average trip travel time on the situational level (i.e. per OD-pair). These findings in conjunction with the observation that about one-third of the choices were inertial choices, offers indication of the extent individuals allow suboptimal choice situations, and as such the potential to realize system improvements.\ud \ud The data available for this research was limited in the number of subjects, choice situations and trips. It requires bigger and richer data to enable a much more thorough analysis of how people move through traffic networks, and when and how they access and react to change in the traffic system, as well as to validate the modelling results. When considering the issue of data for travel behaviour analysis, and in particular the analysis of travellers’ choices for choice alternatives, the behavioural phenomena explored in this research are generally hard or impossible to include in simulated or hypothetical environments. Specifically issues as perception error, habit or bounded rationality must preferably be studied in real-life environments, where actual trips are being made without experimenter instructions. Using new ICT technologies it is possible to overcome some of the deficiencies of revealed preference (RP) data as used in this study or stated preference (SP) data, and obtain bigger and richer data than was up till now the case. Future research will use Experience Sampling (ES) by means of a smartphone app to collect additional data for model refinement and validation. For each user of the app a mobility profile is collected, which enables a longitudinal analysis of travel behaviour. The ES-method combines SP with RP by asking a subject about its preferences in a certain situation (SP) directly after that particular situation has revealed itself (RP), thus the context where the stated preference is recorded is directly linked to a real life situation that has just occurred. ES is a powerful method for understanding a range of psychological phenomena, such as mood, behaviour, thoughts or feelings, as they occur in the daily lives of individuals. However, this method is not often used in travel behaviour research. In a later stage a multimodal route planner facility of the app will be used to analyse travellers’ choices and reasoning in response to specific information messages they receive. The paper elaborates on the experimental design