Expression of Lamin A/C in early-stage breast cancer and its prognostic value

Purpose: Lamins A/C, a major component of the nuclear lamina, plays key roles in maintaining nuclear integrity, regulation of gene expression, cell proliferation and apoptosis. Reduced lamin A/C expression in cancer has been reported to be a sign of poor prognosis. However, its clinical significance in breast cancer remains to be defined. This study aimed to evaluate expression and prognostic significance of lamin A/C in early-stage breast cancer.Methods: Using immunohistochemical staining of tissue microarrays, expression of lamin A/C was evaluated in a large well-characterised series of early-stage operable breast cancer (n=938) obtained from Nottingham Primary Breast Carcinoma Series. Association of lamin A/C expression with clinicopathological parameters and outcome was evaluated.Results: Positive expression rate of lamin A/C in breast cancer was 42.2% (n=398). Reduced/loss of expression of lamin A/C was significantly associated with high histological grade (p [less than] 0.001), larger tumour size (p=0.004), poor Nottingham Prognostic Index (NPI) score (p [less than] 0.001), lymphovascular invasion (p=0.014) and development of distant metastasis (p=0.027). Survival analysis showed that reduced/loss of expression of lamin A/C was significantly associated with shorter breast cancer specific survival (p=0.008).Conclusion: This study suggests lamin A/C plays a role in breast cancer and loss of its expression is associated with variables of poor prognosis and shorter outcome

Combining clustering and classification ensembles: A novel pipeline to identify breast cancer profiles

Breast Cancer is one of the most common causes of cancer death in women, representing a very complex disease with varied molecular alterations. To assist breast cancer prognosis, the classification of patients into biological groups is of great significance for treatment strategies. Recent studies have used an ensemble of multiple clustering algorithms to elucidate the most characteristic biological groups of breast cancer. However, the combination of various clustering methods resulted in a number of patients remaining unclustered. Therefore, a framework still needs to be developed which can assign as many unclustered (i.e. biologically diverse) patients to one of the identified groups in order to improve classification. Therefore, in this paper we develop a novel classification framework which introduces a new ensemble classification stage after the ensemble clustering stage to target the unclustered patients. Thus, a step-by-step pipeline is introduced which couples ensemble clustering with ensemble classification for the identification of core groups, data distribution in them and improvement in final classification results by targeting the unclustered data. The proposed pipeline is employed on a novel real world breast cancer dataset and subsequently its robustness and stability are examined by testing it on standard datasets. The results show that by using the presented framework, an improved classification is obtained. Finally, the results have been verified using statistical tests, visualisation techniques, cluster quality assessment and interpretation from clinical experts

The combined expression of solute carriers is associated with a poor prognosis in highly proliferative ER+ breast cancer

Purpose: Breast cancer (BC) is a heterogeneous disease characterised by variant biology, metabolic activity, and patient outcome. Glutamine availability for growth and progression of BC is important in several BC subtypes. This study aimed to evaluate the biological and prognostic role of the combined expression of key glutamine transporters, SLC1A5, SLC7A5 and SLC3A2 in BC with emphasis on the intrinsic molecular subtypes. Methods: SLC1A5, SLC7A5 and SLC3A2 were assessed at the protein level, using immunohistochemistry on tissue microarrays constructed from a large well characterised BC cohort (n=2,248). Patients were stratified into accredited clusters based on protein expression and correlated with clinicopathological parameters, molecular subtypes, and patient outcome. Results: Clustering analysis of SLC1A5, SLC7A5 and SLC3A2 identified three clusters Low SLCs (SLC1A5-/SLC7A5-/SLC3A2-), High SLC1A5 (SLC1A5+/SLC7A5-/SLC3A2-) and High SLCs (SLC1A5+/SLC7A5+/SLC3A2+) which had distinct correlations to known prognostic factors and patient outcome (p<0.001). The key regulator of tumour cell metabolism, c-MYC, was significantly expressed in tumours in the High SLCs cluster (p<0.001). When different BC subtypes were considered, the association with the poor outcome was observed in the ER+ high proliferation/luminal B class only (p= 0.003). In multivariate analysis, SLC clusters were independent risk factor for shorter breast cancer specific survival (p= 0.001). Conclusion: The co-operative expression of SLC1A5, SLC7A5 and SLC3A2 appears to play a role in the aggressive subclass of ER+ high proliferation/ luminal BC, driven by c-MYC, and therefore have the potential to act as therapeutic targets, particularly in synergism

Current trials to reduce surgical intervention in ductal carcinoma in situ of the breast: critical review

The high proportion of ductal carcinoma in situ (DCIS) presented in mammographic screening and the relatively low risk of progression to invasive disease have raised questions related to overtreatment. Following a review of current DCIS management protocols a more conservative approach has been suggested. Clinical trials have been introduced to evaluate the option of avoiding surgical intervention in a proportion of patients with DCIS defined as “low-risk” using certain clinicopathological criteria. These trials can potentially provide evidence-based models of active surveillance (with or without endocrine therapy) as a future management approach. Despite the undisputable fact of our need to address the obvious overtreatment of screen-detected DCIS, some important questions need to be considered regarding these trials including the eligibility criteria and definition of risk, the proportion of patient eligible for inclusion, and the length of time required for proper analysis of the trials' outcome in view of the long-term natural history of DCIS progression particularly the low-risk group. These factors can potentially affect the practicality and future impact of such trials. This review provides critical analysis of current DCIS management trials and highlights critical issues related to their practicality and the expected outcome

The intra-tumoural stroma in patients with breast cancer increases with age

PURPOSE: The tumour microenvironment in older patients is subject to changes. The tumour-stroma ratio (TSR) was evaluated in order to estimate the amount of intra-tumoural stroma and to evaluate the prognostic value of the TSR in older patients with breast cancer (≥ 70 years).METHODS: Two retrospective cohorts, the FOCUS study (N = 619) and the Nottingham Breast Cancer series (N = 1793), were used for assessment of the TSR on haematoxylin and eosin stained tissue slides.RESULTS: The intra-tumoural stroma increases with age in the FOCUS study and the Nottingham Breast Cancer series (B 0.031, 95% CI 0.006-0.057, p = 0.016 and B 0.034, 95% CI 0.015-0.054, p CONCLUSIONS: The intra-tumoural stroma increases with age. This might be the result of an activated tumour microenvironment. The TSR did not validate as an independent prognostic parameter in patients ≥ 70 years in contrast to young women with breast cancer as published previously.Surgical oncolog

Loss of MED23 leads to poor prognosis in invasive breast cancer

Purpose of the study: The molecular mechanism of lymphovascular invasion (LVI) which determines the early metastatic phenotype in breast cancer is still not fully understood. Lead from the METABRIC study revealed that MED23 correlated with negative LVI status (p=0.00005). Hence MED23 expression was studied at the protein level for correlations with LVI and other clinical-pathological parameters. Methods: The METABRIC BC cohort (n=1980) was evaluated for MED23 mRNA expression and prognostic impact externally validated using the online bc-GenExminer 4.0. Correlation between MED23 protein expression with clinicopathological parameters, patient outcome and other biomarkers were explored (Nottingham Tenovus series; n=1255) using immunohistochemistry (IHC). Results: High MED23 mRNA expression was negatively associated with tumour stage and was differentially expressed in good prognosis integrative clusters 7 and 8 (p<0.001). MED23 IHC revealed nuclear expression (n-MED23). Although no association was found with LVI, higher n-MED23 expression correlated with low NPI, low grade, older age, ER+ status, low Ki67 index and low N-cadherin expression (p<0.05). Positive correlations with PTEN, GATA3, STAT3 and CDC42 (p<0.001), indicate possible interacting pathways. In univariate analysis, high n-MED23 expression showed better long-term patient outcome in the whole cohort and ER+ subgroups (p<0.05). Pooled MED23 expression in an external validation cohort (ER+LN-) also showed association with better patient outcome (p<0.02, HR=0.82, 95% CI 0.69-0.98). Conclusion: Results of the study suggest that loss of n-MED23 is a marker of poor prognosis in invasive BC, results re-enforced by expression data. The difference in correlation with LVI at gene and protein level highlights the importance of IHC validation and indicates MED23 as a probable bystander in the LVI cascade

A common classification framework for neuroendocrine neoplasms: an International Agency for Research on Cancer (IARC) and World Health Organization (WHO) expert consensus proposal.

The classification of neuroendocrine neoplasms (NENs) differs between organ systems and currently causes considerable confusion. A uniform classification framework for NENs at any anatomical location may reduce inconsistencies and contradictions among the various systems currently in use. The classification suggested here is intended to allow pathologists and clinicians to manage their patients with NENs consistently, while acknowledging organ-specific differences in classification criteria, tumor biology, and prognostic factors. The classification suggested is based on a consensus conference held at the International Agency for Research on Cancer (IARC) in November 2017 and subsequent discussion with additional experts. The key feature of the new classification is a distinction between differentiated neuroendocrine tumors (NETs), also designated carcinoid tumors in some systems, and poorly differentiated NECs, as they both share common expression of neuroendocrine markers. This dichotomous morphological subdivision into NETs and NECs is supported by genetic evidence at specific anatomic sites as well as clinical, epidemiologic, histologic, and prognostic differences. In many organ systems, NETs are graded as G1, G2, or G3 based on mitotic count and/or Ki-67 labeling index, and/or the presence of necrosis; NECs are considered high grade by definition. We believe this conceptual approach can form the basis for the next generation of NEN classifications and will allow more consistent taxonomy to understand how neoplasms from different organ systems inter-relate clinically and genetically