Practical implications of gene-expression-based assays for breast oncologists

Vimentin DNA methylation predicts survival in breast cancer

The Vimentin gene plays a pivotal role in epithelial-to-mesenchymal transition and is known to be overexpressed in the prognostically poor basal-like breast cancer subtype. Recent studies have reported Vimentin DNA methylation in association with poor clinical outcomes in other solid tumors, but not in breast cancer. We therefore quantified Vimentin DNA methylation using MALDI-TOF mass spectrometry in breast tumors and matched normal pairs in association with gene expression and survival in a hospital-based study of breast cancer patients. Gene expression data via qRT-PCR in cell lines and oligomicroarray data from breast tissues were correlated with percent methylation in the Vimentin promoter. A threshold of 20 percent average methylation compared with matched normal pairs was set for bivariate and multivariate tests of association between methylation and tumor subtype, tumor histopathology, and survival. Vimentin was differentially methylated in luminal breast cancer cell lines, and in luminal A, luminal B, and HER2-enriched breast tumor subtypes, but was rare in basal-like cell lines and tumors. Increased methylation was strongly correlated with decreased mRNA expression in cell lines, and had a moderate inverse correlation in breast tumors. Vimentin methylation predicted poor overall survival independent of race, subtype, stage, nodal status, or metastatic disease and holds promise as a new prognostic biomarker for breast cancer patients.

Prognostic significance of progesterone receptor-positive tumor cells within immunohistochemically defined luminal A breast cancer

PURPOSE

Current immunohistochemical (IHC)-based definitions of luminal A and B breast cancers are imperfect when compared with multigene expression-based assays. In this study, we sought to improve the IHC subtyping by examining the pathologic and gene expression characteristics of genomically defined luminal A and B subtypes.

PATIENTS AND METHODS

Gene expression and pathologic features were collected from primary tumors across five independent cohorts: British Columbia Cancer Agency (BCCA) tamoxifen-treated only, Grupo Español de Investigación en Cáncer de Mama 9906 trial, BCCA no systemic treatment cohort, PAM50 microarray training data set, and a combined publicly available microarray data set. Optimal cutoffs of percentage of progesterone receptor (PR) -positive tumor cells to predict survival were derived and independently tested. Multivariable Cox models were used to test the prognostic significance.

RESULTS

Clinicopathologic comparisons among luminal A and B subtypes consistently identified higher rates of PR positivity, human epidermal growth factor receptor 2 (HER2) negativity, and histologic grade 1 in luminal A tumors. Quantitative PR gene and protein expression were also found to be significantly higher in luminal A tumors. An empiric cutoff of more than 20% of PR-positive tumor cells was statistically chosen and proved significant for predicting survival differences within IHC-defined luminal A tumors independently of endocrine therapy administration. Finally, no additional prognostic value within hormonal receptor (HR) -positive/HER2-negative disease was observed with the use of the IHC4 score when intrinsic IHC-based subtypes were used that included the more than 20% PR-positive tumor cells and vice versa.

CONCLUSION

Semiquantitative IHC expression of PR adds prognostic value within the current IHC-based luminal A definition by improving the identification of good outcome breast cancers. The new proposed IHC-based definition of luminal A tumors is HR positive/HER2 negative/Ki-67 less than 14%, and PR more than 20%.

Luminal B tumors are the most frequent molecular subtype in breast cancer of North African women: an immunohistochemical profile study from Morocco

Background

Breast cancer may be classified into luminal A, luminal B, HER2+/ER-, basal-like and normal-like subtypes based on gene expression profiling or immunohistochemical (IHC) characteristics. The aim of our study is to show the molecular profile characteristic of breast cancer in the North African population of Morocco. This work showed preliminary results and correlations with clinicopathological and histological parameters. Three hundred and ninety primary breast carcinomas tumor tissues were immunostained for ER, PR, HER2, CK5/6, CK8/18 and Ki67 using paraffin tissue.

Methods

We reviewed 390 cases of breast cancer diagnosed on January 2008 to December 2011 at the Department of pathology, Hassan II teaching hospital, Fez, Morocco. Age, size tumor, metastatic profile, node involvement profile, histological type and immunohistochemical profile were studied.

Results

The average age was 46 years; our patients were diagnosed late with a high average tumor size. Luminal B subtype was more prevalent (41.8%), followed by luminal A (30.5%), basal-like (13, 6%), Her2-overexpressing (9, 2%), and unclassified subtype (4.9%).

Conclusion

This study showed that molecular classification and biological profile may be different according to geographical distribution, to encourage further studies to know the genomic profile of tumors and the environment.

Virtual slide

http://www.diagnosticpathology.diagnomx.eu/vs/1675272504826544

Concordance among gene expression-based predictors for ER-positive breast cancer treated with adjuvant tamoxifen

BACKGROUND

ER-positive (ER+) breast cancer includes all of the intrinsic molecular subtypes, although the luminal A and B subtypes predominate. In this study, we evaluated the ability of six clinically relevant genomic signatures to predict relapse in patients with ER+ tumors treated with adjuvant tamoxifen only.

METHODS

Four microarray datasets were combined and research-based versions of PAM50 intrinsic subtyping and risk of relapse (PAM50-ROR) score, 21-gene recurrence score (OncotypeDX), Mammaprint, Rotterdam 76 gene, index of sensitivity to endocrine therapy (SET) and an estrogen-induced gene set were evaluated. Distant relapse-free survival (DRFS) was estimated by Kaplan-Meier and log-rank tests, and multivariable analyses were done using Cox regression analysis. Harrell's C-index was also used to estimate performance.

RESULTS

All signatures were prognostic in patients with ER+ node-negative tumors, whereas most were prognostic in ER+ node-positive disease. Among the signatures evaluated, PAM50-ROR, OncotypeDX, Mammaprint and SET were consistently found to be independent predictors of relapse. A combination of all signatures significantly increased the performance prediction. Importantly, low-risk tumors (>90% DRFS at 8.5 years) were identified by the majority of signatures only within node-negative disease, and these tumors were mostly luminal A (78%-100%).

CONCLUSIONS

Most established genomic signatures were successful in outcome predictions in ER+ breast cancer and provided statistically independent information. From a clinical perspective, multiple signatures combined together most accurately predicted outcome, but a common finding was that each signature identified a subset of luminal A patients with node-negative disease who might be considered suitable candidates for adjuvant endocrine therapy alone.

Retinoids and breast cancer: new clues to increase their activity and selectivity

All-trans retinoic acid and derivatives (retinoids) are promising agents in the management of certain hematologic malignancies and solid tumors, including breast cancer. Retinoids are endowed with anti-proliferative, cyto-differentiating and apoptotic effects that are largely mediated by activation of the nuclear hormone retinoic acid receptors RARα, RARβ and RARγ. These are ligand-dependent transcriptional factors controlling the expression of numerous genes. The relative importance of each receptor subtype for the anti-tumor activity of retinoids is largely unknown. Clarification of this point is of fundamental importance for the rational design of retinoid-based therapeutic approaches aimed at controlling a heterogeneous type of tumors, like breast cancer.

The molecular profile of luminal B breast cancer

Molecular profiling studies have found that estrogen receptor-positive (ER+) human breast cancers are comprised of at least two distinct diseases with differing biologies. With the advent of DNA microarrays, global gene expression patterns were used to define the luminal A and luminal B subtypes of ER+ breast cancer, with luminal B cancers showing a more aggressive phenotype including substantially worse outcomes in patients. The luminal B subtype designation could be considered a surrogate for those ER+ tumors having low progesterone receptors, high proliferation, high grade, and predicted poor response to hormone therapy. While they express estrogen receptors, luminal B cancers do not show a corresponding expression of estrogen-regulated genes, and may therefore rely upon alternative pathways for growth. At the molecular level, luminal B cancers appear dramatically distinct from luminal A cancers, at the levels of gene expression, gene copy, somatic mutation, and DNA methylation; luminal B cancers are also genetically and genomically altered to a greater extent than luminal A cancers. While, in the clinical setting, luminal B is typically regarded as an ER+, hormone-sensitive disease, more research is needed into how to better treat it. Comprehensive profiling initiatives, such as The Cancer Genome Atlas, have recently provided us a catalog of mutated or copy altered genes, from which new therapeutic targets could potentially be mined. Candidate pathways that might be targeted in luminal B include those involving growth factor receptors, including HER2 and EGFR, as well as PI3K/Akt/mTor.

Is breast cancer staging obsolete?

The stages of breast cancer range from 0 to IV. In proper usage, “stage” describes the cancer at diagno-sis, although “stage” is also loosely used to describe cancer progression. For example, a stage II cancer is sometimes said to have progressed to become stage IV (but not stage III). [...]

PAM50 assay and the three-gene model for identifying the major and clinically relevant molecular subtypes of breast cancer

It has recently been proposed that a three-gene model (SCMGENE) that measures ESR1, ERBB2, and AURKA identifies the major breast cancer intrinsic subtypes and provides robust discrimination for clinical use in a manner very similar to a 50-gene subtype predictor (PAM50). However, the clinical relevance of both predictors was not fully explored, which is needed given that a ~30 % discordance rate between these two predictors was observed. Using the same datasets and subtype calls provided by Haibe-Kains and colleagues, we compared the SCMGENE assignments and the research-based PAM50 assignments in terms of their ability to (1) predict patient outcome, (2) predict pathological complete response (pCR) after anthracycline/taxane-based chemotherapy, and (3) capture the main biological diversity displayed by all genes from a microarray. In terms of survival predictions, both assays provided independent prognostic information from each other and beyond the data provided by standard clinical–pathological variables; however, the amount of prognostic information was found to be significantly greater with the PAM50 assay than the SCMGENE assay. In terms of chemotherapy response, the PAM50 assay was the only assay to provide independent predictive information of pCR in multivariate models. Finally, compared to the SCMGENE predictor, the PAM50 assay explained a significantly greater amount of gene expression diversity as captured by the two main principal components of the breast cancer microarray data. Our results show that classification of the major and clinically relevant molecular subtypes of breast cancer are best captured using larger gene panels.

Science to practice: what do molecular biologic studies in rodent models add to our understanding of interventional oncologic procedures including percutaneous ablation by using glyceraldehyde-3-phosphate dehydrogenase antagonists?

In this basic research study, Ganapathy-Kanniappan et al advance our understanding of how to block the glycolytic pathway to inhibit tumor progression by using image guided procedures (1). This was accomplished by demonstrating their ability to perform molecular targeting of glyceraldehyde-3-phosphate dehydrogenase (GAPDH) in human hepatocellular carcinoma (HCC) by using percutaneous injection of either inhibitor--3-bromopyruvate (3-BrPA) or short hairpin RNA (shRNA). They take the critical step of providing further rationale for potentially advancing this therapy into clinical trials by demonstrating that GAPDH expression strongly correlates with c-jun, a proto-oncogene involved in liver tumorigenesis in human HCC (2).

Immunohistochemistry profiles of breast ductal carcinoma: factor analysis of digital image analysis data

BACKGROUND

Molecular studies of breast cancer revealed biological heterogeneity of the disease and opened new perspectives for personalized therapy. While multiple gene expression-based systems have been developed, current clinical practice is largely based upon conventional clinical and pathologic criteria. This gap may be filled by development of combined multi-IHC indices to characterize biological and clinical behaviour of the tumours. Digital image analysis (DA) with multivariate statistics of the data opens new opportunities in this field.

METHODS

Tissue microarrays of 109 patients with breast ductal carcinoma were stained for a set of 10 IHC markers (ER, PR, HER2, Ki67, AR, BCL2, HIF-1α, SATB1, p53, and p16). Aperio imaging platform with the Genie, Nuclear and Membrane algorithms were used for the DA. Factor analysis of the DA data was performed in the whole group and hormone receptor (HR) positive subgroup of the patients (n = 85).

RESULTS

Major factor potentially reflecting aggressive disease behaviour (i-Grade) was extracted, characterized by opposite loadings of ER/PR/AR/BCL2 and Ki67/HIF-1α. The i-Grade factor scores revealed bimodal distribution and were strongly associated with higher Nottingham histological grade (G) and more aggressive intrinsic subtypes. In HR-positive tumours, the aggressiveness of the tumour was best defined by positive Ki67 and negative ER loadings. High Ki67/ER factor scores were strongly associated with the higher G and Luminal B types, but also were detected in a set of G1 and Luminal A cases, potentially indicating high risk patients in these categories. Inverse relation between HER2 and PR expression was found in the HR-positive tumours pointing at differential information conveyed by the ER and PR expression. SATB1 along with HIF-1α reflected the second major factor of variation in our patients; in the HR-positive group they were inversely associated with the HR and BCL2 expression and represented the major factor of variation. Finally, we confirmed high expression levels of p16 in Triple-negative tumours.

CONCLUSION

Factor analysis of multiple IHC biomarkers measured by automated DA is an efficient exploratory tool clarifying complex interdependencies in the breast ductal carcinoma IHC profiles and informative value of single IHC markers. Integrated IHC indices may provide additional risk stratifications for the currently used grading systems and prove to be useful in clinical outcome studies.

VIRTUAL SLIDES

The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/1512077125668949.

Targeting insulin-like growth factor in breast cancer therapeutics

The insulin-like growth factor (IGF) pathway holds crucial role in cell growth, differentiation and proliferation. Aberrant regulation of the IGF system has been attributed to the pathogenesis of breast cancer and has been shown to contribute to various stages of breast carcinogenesis. Therefore, targeting the IGF-related axis represents a promising strategy, mainly aiming to bypass the resistance of currently employed treatment options in breast cancer patients. Nevertheless, major limitations have aroused despite the early stage of clinical development of various IGF-system modulators. The present review highlights the current status and considers the future perspectives of IGF-system targeting in breast cancer therapeutics.