Ki67 expression in invasive breast cancer: the use of tissue microarrays compared with whole tissue sections.

BACKGROUND: Although the prognostic value of Ki67 in breast cancer is well documented, using optimal cut-points for patient stratification, reproducibility of the scoring and interpretation of the results remains a matter of debate particularly when using tissue microarrays (TMAs). This study aims to assess Ki67 expression assessed on TMAs and their matched whole tissue sections (WTS). Moreover, whether the cut-off used for WTS is reproducible on TMA in BC molecular classes and the association between Ki67 expression cut-off, assessed on TMAs and WTS, and clinicopathological parameters and patient outcome were tested. METHOD: A large series (n = 707) of primary invasive breast tumours were immunostained for Ki67 using both TMA and WTS and assessed as percentage staining and correlated with each other, clinicopathological parameters and patient outcome. In addition, MKI67 mRNA expression was correlated with Ki67 protein levels on WTS and TMAs in a subset of cases included in the METABRIC study. RESULTS: There was moderate concordance in Ki67 expression between WTS and TMA when analysed as a continuous variable (Intraclass correlation coefficient = 0.61) and low concordance when dichotomised (kappa value = 0.3). TMA showed low levels of Ki67 with mean percentage of expression of 35 and 22% on WTS and TMA, respectively. MKI67 mRNA expression was significantly correlated with protein expression determined on WTS (Spearman Correlation, r = 0.52) and to a lesser extent on TMA (r = 0.34) (p < 0.001). Regarding prediction of patient outcome, statistically significant differences were detected upon stratification of patients with tumours expressing Ki67 at 10, 15, 20, 25 or 30% in TMA. Using TMA, ≥20% Ki67 provided the best prognostic cut-off particularly in triple-negative and HER2-positive classes. CONCLUSION: Ki67 expression in breast cancer can be evaluated using TMA although different cut-points are required to emulate results from WTS. A cut-off of ≥20% for Ki67 expression in BC provides the best prognostic correlations when TMAs are used

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

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

The multifunctional solute carrier 3A2 (SLC3A2) confers a poor prognosis in the highly proliferative breast cancer subtypes

Background: Breast cancer (BC) is a heterogeneous disease characterised by variant biology, metabolic activity and patient outcome. This study aimed to evaluate the biological and prognostic value of the membrane solute carrier, SLC3A2 in BC with emphasis on the intrinsic molecular subtypes. Methods: SLC3A2 was assessed at the genomic level, using METABRIC data (n=1,980), and proteomic level, using immunohistochemistry on TMA sections constructed from a large well-characterised primary BC cohort (n=2,500). SLC3A2 expression was correlated with clinicopathological parameters, molecular subtypes, and patient outcome. Results: SLC3A2 mRNA and protein expression were strongly correlated with higher tumour grade and poor Nottingham prognostic index (NPI). High expression of SLC3A2 was observed in triple negative (TN), HER2+, and ER+ high proliferation subtypes. SLC3A2 mRNA and protein expression were significantly associated with the expression of c-MYC in all BC subtypes (p<0.001). High expression of SLC3A2 protein was associated with poor patient outcome (p<0.001)), but only in the ER+ high proliferation (p=0.01) and triple negative (p=0.04) subtypes. In multivariate analysis SLC3A2 protein was an independent risk factor for shorter breast cancer specific survival (p<0.001). Conclusions: SLC3A2 appears to play a role in the aggressive BC subtypes driven by MYC and could act as a potential prognostic marker. Functional assessment is necessary to reveal its potential therapeutic value in the different BC subtypes

MYC functions are specific in biological subtypes of breast cancer and confers resistance to endocrine therapy in luminal tumours.

BACKGROUND: MYC is amplified in approximately 15% of breast cancers (BCs) and is associated with poor outcome. c-MYC protein is multi-faceted and participates in many aspects of cellular function and is linked with therapeutic response in BCs. We hypothesised that the functional role of c-MYC differs between molecular subtypes of BCs. METHODS: We therefore investigated the correlation between c-MYC protein expression and other proteins involved in different cellular functions together with clinicopathological parameters, patients' outcome and treatments in a large early-stage molecularly characterised series of primary invasive BCs (n=1106) using immunohistochemistry. The METABRIC BC cohort (n=1980) was evaluated for MYC mRNA expression and a systems biology approach utilised to identify genes associated with MYC in the different BC molecular subtypes. RESULTS: High MYC and c-MYC expression was significantly associated with poor prognostic factors, including grade and basal-like BCs. In luminal A tumours, c-MYC was associated with ATM (P=0.005), Cyclin B1 (P=0.002), PIK3CA (P=0.009) and Ki67 (P<0.001). In contrast, in basal-like tumours, c-MYC showed positive association with Cyclin E (P=0.003) and p16 (P=0.042) expression only. c-MYC was an independent predictor of a shorter distant metastases-free survival in luminal A LN+ tumours treated with endocrine therapy (ET; P=0.013). In luminal tumours treated with ET, MYC mRNA expression was associated with BC-specific survival (P=0.001). In ER-positive tumours, MYC was associated with expression of translational genes while in ER-negative tumours it was associated with upregulation of glucose metabolism genes. CONCLUSIONS: c-MYC function is associated with specific molecular subtypes of BCs and its overexpression confers resistance to ET. The diverse mechanisms of c-MYC function in the different molecular classes of BCs warrants further investigation particularly as potential therapeutic targets

Mediator complex (MED) 7: a biomarker associated with good prognosis in invasive breast cancer, especially ER+ luminal subtypes

Background: Mediator complex (MED) proteins have a key role in transcriptional regulation, some interacting with the oestrogen receptor (ER). Interrogation of the METABRIC cohort suggested that MED7 may regulate lymphovascular invasion (LVI). Thus MED7 expression was assessed in large breast cancer (BC) cohorts to determine clinicopathological significance. Methods: MED7 gene expression was investigated in the METABRIC cohort (n = 1980) and externally validated using bc-GenExMiner v4.0. Immunohistochemical expression was assessed in the Nottingham primary BC series (n = 1280). Associations with clinicopathological variables and patient outcome were evaluated. Results: High MED7 mRNA and protein expression was associated with good prognostic factors: low grade, smaller tumour size, good NPI, positive hormone receptor status (p < 0.001), and negative LVI (p = 0.04) status. Higher MED7 protein expression was associated with improved BC-specific survival within the whole cohort and ER+/luminal subgroup. Pooled MED7 gene expression data in the external validation cohort confirmed association with better survival, corroborating with the protein expression. On multivariate analysis, MED7 protein was independently predictive of longer BC-specific survival in the whole cohort and Luminal A subtype (p < 0.001). Conclusions: MED7 is an important prognostic marker in BC, particularly in ER+luminal subtypes, associated with improved survival and warrants future functional analysis

Markers of progression in early-stage invasive breast cancer: a predictive immunohistochemical panel algorithm for distant recurrence risk stratification

Accurate distant metastasis (DM) prediction is critical for risk stratification and effective treatment decisions in breast cancer (BC). Many prognostic markers/models based on tissue marker studies are continually emerging using conventional statistical approaches analysing complex/dimensional data association with DM/poor prognosis. However, few of them have fulfilled satisfactory evidences for clinical application. This study aimed at building DM risk assessment algorithm for BC patients. A well-characterised series of early invasive primary operable BC (n=1902), with immunohistochemical (IHC) expression of a panel of biomarkers (n=31) formed the material of this study. Decision tree algorithm was computed using WEKA software, utilising quantitative biomarkers’ expression and the absence/presence of distant metastases. Fifteen biomarkers were significantly associated with DM, with six temporal subgroups characterised based on time-to-development of DM ranging from 15 years of follow-up. Of these 15 biomarkers, 10 had a significant expression pattern where Ki67LI, HER2, p53, N-cadherin, P-cadherin, PIK3CA and TOMM34 showed significantly higher expressions with earlier development of DM. In contrast, higher expressions of ER, PR, and BCL2, were associated with delayed occurrence of DM. DM prediction algorithm was built utilising cases informative for the 15 significant markers. Four risk groups of patients were characterised. Three markers; p53, HER2 and BCL2 predicted the probability of DM, based on software-generated cut-offs, with a precision rate of 81.1% for positive predictive value and 77.3%, for the negative predictive value. This algorithm reiterates the reported prognostic values of these three markers and underscores their central biologic role in BC progression. Further independent validation of this pruned panel of biomarkers is therefore warranted

Machine learning-based prediction of breast cancer growth rate in-vivo

BackgroundDetermining the rate of breast cancer (BC) growth in vivo, which can predict prognosis, has remained elusive despite its relevance for treatment, screening recommendations and medicolegal practice. We developed a model that predicts the rate of in vivo tumour growth using a unique study cohort of BC patients who had two serial mammograms wherein the tumour, visible in the diagnostic mammogram, was missed in the first screen.MethodsA serial mammography-derived in vivo growth rate (SM-INVIGOR) index was developed using tumour volumes from two serial mammograms and time interval between measurements. We then developed a machine learning-based surrogate model called Surr-INVIGOR using routinely assessed biomarkers to predict in vivo rate of tumour growth and extend the utility of this approach to a larger patient population. Surr-INVIGOR was validated using an independent cohort.ResultsSM-INVIGOR stratified discovery cohort patients into fast-growing versus slow-growing tumour subgroups, wherein patients with fast-growing tumours experienced poorer BC-specific survival. Our clinically relevant Surr-INVIGOR stratified tumours in the discovery cohort and was concordant with SM-INVIGOR. In the validation cohort, Surr-INVIGOR uncovered significant survival differences between patients with fast-growing and slow-growing tumours.ConclusionOur Surr-INVIGOR model predicts in vivo BC growth rate during the pre-diagnostic stage and offers several useful applications

Collagen (XI) alpha-1 chain (COL11A1) is an independent prognostic factor in breast ductal carcinoma in situ

Collagen11A1 (COL11A1) is a fibrillary type collagen constituting a minor component of the extracellular matrix and plays role in tissue tensile strength. Overexpression of COL11A1 expression is associated with aggressive behavior and poor outcome in several human malignancies. In this study, we evaluated the association between COL11A1 expression and clinicopathological parameters of the breast ductal carcinoma in situ (DCIS) and its prognostic value. COL11A1 protein expression was assessed immunohistochemically in a large well-characterized cohort of DCIS including pure (n = 776) and DCIS associated with invasive carcinoma (DCIS-mixed, n = 239). COL11A1 expression was assessed in tumor cells and surrounding stromal cells, and correlated with clinicopathological parameters, immunoprofile and disease outcome. In pure DCIS, high COL11A1 expression was observed in tumor cells and surrounding stromal cells in 25 and 13% of cases, respectively. Higher COL11A1 expression within the stromal cells was associated with hormone receptor negative, HER2 enriched and triple negative molecular subtypes and showed a positive linear correlation with proliferation index, dense tumor infiltrating lymphocytes and hypoxia-inducible factor 1 alpha. COL11A1 expression in tumor and stromal cells was significantly higher in DCIS associated with invasive carcinoma than in pure DCIS, and within the DCIS-mixed cohort, the invasive component showed higher COL11A1 expression than the DCIS component (all, p [less than] 0.0001). Overexpression of stromal COL11A1 was an independent predictor of shorter local recurrence-free interval for all recurrences (HR = 13.2, 95% CI = 6.9–25.4, p [less than] 0.0001) and for invasive recurrences (HR = 11.2, 95% CI = 4.9–25.8, p [les than] 0.0001). When incorporated with other risk factors, stromal COL11A1 provided better patient risk stratification. DCIS with higher stromal COL11A1 expression showed poor outcome even with adjuvant radiotherapy management. In conclusion, overexpression of stromal COL11A1 is associated with invasive recurrence in DCIS and is a potential marker to predict the response to radiotherapy

Impact of intratumoural heterogeneity on the assessment of Ki67 expression in breast cancer

In breast cancer (BC), the prognostic value of Ki67 expression is well-documented. Intratumoural heterogeneity (ITH) of Ki67 expression is amongst the several technical issues behind the lag of its inclusion into BC prognostic work-up. The immunohistochemical (IHC) expression of anti-Ki67 antibody (MIB1 clone) was assessed in four full-face (FF) sections from different primary tumour blocks and their matched axillary nodal (LN) metastases in a series of 55 BC. Assessment was made using the highest expression hot spots (HS), lowest expression (LS), and overall/average expression scores (AS) in each section. Heterogeneity score (Hes), co-efficient of variation, and correlation co-efficient were used to assess the levels of Ki67 ITH. Ki67 HS, LS, and AS scores were highly variable within the same section and between different sections of the primary tumour, with maximal variation observed in the LS (P\0.001). The least variability between the different slides was observed with HS scoring. Although the associations between Ki67 and clinicopathological and molecular variables were similar when using HS or AS, the best correlation between AS and HS was observed in tumours with high Ki67 expression only. Ki67 expression in LN deposits was less heterogeneous than in the primary tumours and was perfectly correlated with the HS Ki67 expression in the primary tumour sections (r = 0.98, P\0.001). In conclusion, assessment of Ki67 expression using HS scoring method on a full-face BC tissue section can represent the primary tumour growth fraction that is likely to metastasise. The association between Ki67 expression pattern in the LN metastasis and the HS in the primary tumour may reflect the temporal heterogeneity through clonal expansion