Cytosolic phospholipase A2-α expression in breast cancer is associated with EGFR expression and correlates with an adverse prognosis in luminal tumours

BACKGROUND: The eicosanoid signalling pathway promotes the progression of malignancies through the production of proliferative prostaglandins (PGs). Cytosolic phospholipase A(2)α (cPLA(2)α) activity provides the substrate for cyclooxygenase-dependent PG release, and we have previously found that cPLA(2)α expression correlated with EGFR/HER2 over-expression in a small number of breast cancer cell lines. METHODS: The importance of differential cPLA(2)α activity in clinical breast cancer was established by relating the expression of cPLA(2)α in tissue samples from breast cancer patients, and two microarray-based gene expression datasets to different clinicopathological and therapeutic parameters. RESULTS: High cPLA(2)α mRNA expression correlated with clinical parameters of poor prognosis, which are characteristic of highly invasive tumours of the HER2-positive and basal-like subtype, including low oestrogen receptor expression and high EGFR expression. High cPLA(2)α expression decreased overall survival in patients with luminal cancers, and correlated with a reduced effect of tamoxifen treatment. The cPLA(2)α expression was an independent predictive parameter of poor response to endocrine therapy in the first 5 years of follow-up. CONCLUSION: This study shows a role of cPLA(2)α in luminal breast cancer progression, in which the enzyme could represent a novel therapeutic target and a predictive marker

Proliferation Index: A Continuous Model to Predict Prognosis in Patients with Tumours of the Ewing's Sarcoma Family

The prognostic value of proliferation index (PI) and apoptotic index (AI), caspase-8, -9 and -10 expression have been investigated in primary Ewing's sarcoma family of tumours (ESFT). Proliferating cells, detected by immunohistochemistry for Ki-67, were identified in 91% (91/100) of tumours with a median PI of 14 (range 0–87). Apoptotic cells, identified using the TUNEL assay, were detected in 96% (76/79) of ESFT; the median AI was 3 (range 0–33). Caspase-8 protein expression was negative (0) in 14% (11/79), low (1) in 33% (26/79), medium (2) in 38% (30/79) and high (3) in 15% (12/79) of tumours, caspase-9 expression was low (1) in 66% (39/59) and high (3) in 34% (20/59), and caspase-10 protein was low (1) in 37% (23/62) and negative (0) in 63% (39/62) of primary ESFT. There was no apparent relationship between caspase-8, -9 and -10 expression, PI and AI. PI was predictive of relapse-free survival (RFS; p = 0.011) and overall survival (OS; p = <0.001) in a continuous model, whereas AI did not predict outcome. Patients with tumours expressing low levels of caspase-9 protein had a trend towards a worse RFS than patients with tumours expressing higher levels of caspase-9 protein (p = 0.054, log rank test), although expression of caspases-8, -9 and/or -10 did not significantly predict RFS or OS. In a multivariate analysis model that included tumour site, tumour volume, the presence of metastatic disease at diagnosis, PI and AI, PI independently predicts OS (p = 0.003). Consistent with previous publications, patients with pelvic tumours had a significantly worse OS than patients with tumours at other sites (p = 0.028); patients with a pelvic tumour and a PI≥20 had a 6 fold-increased risk of death. These studies advocate the evaluation of PI in a risk model of outcome for patients with ESFT

Cyclin A and cyclin D1 as significant prognostic markers in colorectal cancer patients

BACKGROUND: Colorectal cancer is a common cancer all over the world. Aberrations in the cell cycle checkpoints have been shown to be of prognostic significance in colorectal cancer. METHODS: The expression of cyclin D1, cyclin A, histone H3 and Ki-67 was examined in 60 colorectal cancer cases for co-regulation and impact on overall survival using immunohistochemistry, southern blot and in situ hybridization techniques. Immunoreactivity was evaluated semi quantitatively by determining the staining index of the studied proteins. RESULTS: There was a significant correlation between cyclin D1 gene amplification and protein overexpression (concordance = 63.6%) and between Ki-67 and the other studied proteins. The staining index for Ki-67, cyclin A and D1 was higher in large, poorly differentiated tumors. The staining index of cyclin D1 was significantly higher in cases with deeply invasive tumors and nodal metastasis. Overexpression of cyclin A and D1 and amplification of cyclin D1 were associated with reduced overall survival. Multivariate analysis shows that cyclin D1 and A are two independent prognostic factors in colorectal cancer patients. CONCLUSIONS: Loss of cell cycle checkpoints control is common in colorectal cancer. Cyclin A and D1 are superior independent indicators of poor prognosis in colorectal cancer patients. Therefore, they may help in predicting the clinical outcome of those patients on an individual basis and could be considered important therapeutic targets

Application of a risk-management framework for integration of stromal tumor-infiltrating lymphocytes in clinical trials

Stromal tumor-infiltrating lymphocytes (sTILs) are a potential predictive biomarker for immunotherapy response in metastatic triple-negative breast cancer (TNBC). To incorporate sTILs into clinical trials and diagnostics, reliable assessment is essential. In this review, we propose a new concept, namely the implementation of a risk-management framework that enables the use of sTILs as a stratification factor in clinical trials. We present the design of a biomarker risk-mitigation workflow that can be applied to any biomarker incorporation in clinical trials. We demonstrate the implementation of this concept using sTILs as an integral biomarker in a single-center phase II immunotherapy trial for metastatic TNBC (TONIC trial, NCT02499367), using this workflow to mitigate risks of suboptimal inclusion of sTILs in this specific trial. In this review, we demonstrate that a web-based scoring platform can mitigate potential risk factors when including sTILs in clinical trials, and we argue that this framework can be applied for any future biomarker-driven clinical trial setting

Analytical validation of a standardised scoring protocol for Ki67 immunohistochemistry on breast cancer excision whole sections: an international multicentre collaboration

Aims The nuclear proliferation marker Ki67 assayed by immunohistochemistry has multiple potential uses in breast cancer, but an unacceptable level of interlaboratory variability has hampered its clinical utility. The International Ki67 in Breast Cancer Working Group has undertaken a systematic programme to determine whether Ki67 measurement can be analytically validated and standardised among laboratories. This study addresses whether acceptable scoring reproducibility can be achieved on excision whole sections. Methods and results Adjacent sections from 30 primary ER+ breast cancers were centrally stained for Ki67 and sections were circulated among 23 pathologists in 12 countries. All pathologists scored Ki67 by two methods: (i) global: four fields of 100 tumour cells each were selected to reflect observed heterogeneity in nuclear staining; (ii) hot-spot: the field with highest apparent Ki67 index was selected and up to 500 cells scored. The intraclass correlation coefficient (ICC) for the global method [confidence interval (CI) = 0.87; 95% CI = 0.799-0.93] marginally met the prespecified success criterion (lower 95% CI >= 0.8), while the ICC for the hot-spot method (0.83; 95% CI = 0.74-0.90) did not. Visually, interobserver concordance in location of selected hot-spots varies between cases. The median times for scoring were 9 and 6 min for global and hot-spot methods, respectively. Conclusions The global scoring method demonstrates adequate reproducibility to warrant next steps towards evaluation for technical and clinical validity in appropriate cohorts of cases. The time taken for scoring by either method is practical using counting software we are making publicly available. Establishment of external quality assessment schemes is likely to improve the reproducibility between laboratories further

Analytical validation of a standardized scoring protocol for Ki67: phase 3 of an international multicenter collaboration

Pathological analysis of the nuclear proliferation biomarker Ki67 has multiple potential roles in breast and other cancers. However, clinical utility of the immunohistochemical (IHC) assay for Ki67 immunohistochemistry has been hampered by unacceptable between-laboratory analytical variability. The International Ki67 Working Group has conducted a series of studies aiming to decrease this variability and improve the evaluation of Ki67. This study tries to assess whether acceptable performance can be achieved on prestained core-cut biopsies using a standardized scoring method. Sections from 30 primary ER+ breast cancer core biopsies were centrally stained for Ki67 and circulated among 22 laboratories in 11 countries. Each laboratory scored Ki67 using three methods: (1) global (4 fields of 100 cells each); (2) weighted global (same as global but weighted by estimated percentages of total area); and (3) hot-spot (single field of 500 cells). The intraclass correlation coefficient (ICC), a measure of interlaboratory agreement, for the unweighted global method (0.87; 95% credible interval (CI): 0.81–0.93) met the prespecified success criterion for scoring reproducibility, whereas that for the weighted global (0.87; 95% CI: 0.7999–0.93) and hot-spot methods (0.84; 95% CI: 0.77–0.92) marginally failed to do so. The unweighted global assessment of Ki67 IHC analysis on core biopsies met the prespecified criterion of success for scoring reproducibility. A few cases still showed large scoring discrepancies. Establishment of external quality assessment schemes is likely to improve the agreement between laboratories further. Additional evaluations are needed to assess staining variability and clinical validity in appropriate cohorts of samples

Minimising Immunohistochemical False Negative ER Classification Using a Complementary 23 Gene Expression Signature of ER Status

BACKGROUND: Expression of the oestrogen receptor (ER) in breast cancer predicts benefit from endocrine therapy. Minimising the frequency of false negative ER status classification is essential to identify all patients with ER positive breast cancers who should be offered endocrine therapies in order to improve clinical outcome. In routine oncological practice ER status is determined by semi-quantitative methods such as immunohistochemistry (IHC) or other immunoassays in which the ER expression level is compared to an empirical threshold. The clinical relevance of gene expression-based ER subtypes as compared to IHC-based determination has not been systematically evaluated. Here we attempt to reduce the frequency of false negative ER status classification using two gene expression approaches and compare these methods to IHC based ER status in terms of predictive and prognostic concordance with clinical outcome. METHODOLOGY/PRINCIPAL FINDINGS: Firstly, ER status was discriminated by fitting the bimodal expression of ESR1 to a mixed Gaussian model. The discriminative power of ESR1 suggested bimodal expression as an efficient way to stratify breast cancer; therefore we identified a set of genes whose expression was both strongly bimodal, mimicking ESR expression status, and highly expressed in breast epithelial cell lines, to derive a 23-gene ER expression signature-based classifier. We assessed our classifiers in seven published breast cancer cohorts by comparing the gene expression-based ER status to IHC-based ER status as a predictor of clinical outcome in both untreated and tamoxifen treated cohorts. In untreated breast cancer cohorts, the 23 gene signature-based ER status provided significantly improved prognostic power compared to IHC-based ER status (P = 0.006). In tamoxifen-treated cohorts, the 23 gene ER expression signature predicted clinical outcome (HR = 2.20, P = 0.00035). These complementary ER signature-based strategies estimated that between 15.1% and 21.8% patients of IHC-based negative ER status would be classified with ER positive breast cancer. CONCLUSION/SIGNIFICANCE: Expression-based ER status classification may complement IHC to minimise false negative ER status classification and optimise patient stratification for endocrine therapies