Lessons learned from the intrinsic subtypes of breast cancer in the quest for precision therapy

Antiproliferative Effect of Inorganic and Organic Selenium Compounds in Breast Cell Lines

Triple-negative breast cancer (TNBC) is an aggressive, fast-growing tumor that is more likely to spread to distant organs. Among women diagnosed with breast cancer, the prevalence of TNBC is 20%, and treatment is currently limited to chemotherapy. Selenium (Se), an essential micronutrient, has been explored as an antiproliferative agent. Therefore, this study aimed to evaluate the effects of exposure to organic (selenomethionine, ebselen, and diphenyl diselenide) and inorganic (sodium selenate and sodium selenite) Se molecules in different breast cell lines. The compounds were tested at 1, 10, 50, and 100 μM for 48 h in the non-tumor breast cell line (MCF-10A) and TNBC derivatives cell lines (BT-549 and MDA-MB-231). The effects of Se on cell viability, apoptotic and necrotic processes, colony formation, and cell migration were analyzed. Exposure to selenomethionine and selenate did not alter the evaluated parameters. However, selenomethionine had the highest selectivity index (SI). The exposure to the highest doses of selenite, ebselen, and diphenyl diselenide resulted in antiproliferative and antimetastatic effects. Selenite had a high SI to the BT cell line; however, the SI of ebselen and diphenyl diselenide was low in both tumoral cell lines. In conclusion, the Se compounds had different effects on the breast cell lines, and additional tests are needed to reveal the antiproliferative effects of Se compounds.

Combination of Conventional Drugs with Biocompounds Derived from Cinnamic Acid: A Promising Option for Breast Cancer Therapy

Despite the options available for breast cancer (BC) therapy, several adverse effects and resistance limit the success of the treatment. Furthermore, the use of a single drug is associated with a high failure rate. We investigated through a systematic review the in vitro effects of the combination between conventional drugs and bioactive compounds derived from cinnamic acid in BC treatment. The information was acquired from the following databases: PubMed, Web of Science, Embase, Scopus, Lilacs and Cochrane library. We focused on "Cinnamates", "Drug Combinations" and "Breast neoplasms" for publications dating between January 2012 and December 2022, based on the PRISMA statement. The references of the articles were carefully reviewed. Finally, nine eligible studies were included. The majority of these studies were performed using MCF-7, MDA-MB-231, MDA-MB-468 and BT-20 cell lines and the combination between cisplatin, paclitaxel, doxorubicin, tamoxifen, dactolisib and veliparib, with caffeic acid phenethyl ester, eugenol, 3-caffeoylquinic acid, salvianolic acid A, ferulic acid, caffeic acid, rosmarinic acid and ursolic acid. The combination improved overall conventional drug effects, with increased cytotoxicity, antimigratory effect and reversing resistance. Combining conventional drugs with bioactive compounds derived from cinnamic acid could emerge as a privileged scaffold for establishing new treatment options for different BC types.

Identification of a novel cancer microbiome signature for predicting prognosis of human breast cancer patients

BACKGROUND

Prognosis of breast cancer (BC) patients differs considerably and identifying reliable prognostic biomarker(s) is imperative. With evidence that the microbiome plays a critical role in the response to cancer therapies, we aimed to identify a cancer microbiome signature for predicting the prognosis of BC patients.

METHODS

The TCGA BC microbiome data (TCGA-BRCA-microbiome) was downloaded from cBioPortal. Univariate and multivariate Cox regression analyses were used to examine association of microbial abundance with overall survival (OS) and to identify a microbial signature for creating a prognostic scoring model. The performance of the scoring model was assessed by the area under the ROC curve (AUC). Nomograms using the microbial signature, clinical factors, and molecular subtypes were established to predict OS and progression-free survival (PFS).

RESULTS

Among 1406 genera, the abundances of 94 genera were significantly associated with BC patient OS in TCGA-BRCA-microbiome dataset. From that set we identified a 15-microbe prognostic signature and developed a 15-microbial abundance prognostic scoring (MAPS) model. Patients in low-risk group significantly prolong OS and PFS as compared to those in high-risk group. The time-dependent ROC curves with MAPS showed good predictive efficacy both in OS and PFS. Moreover, MAPS is an independent prognostic factor for OS and PFS over clinical factors and PAM50-based molecular subtypes and superior to the previously published 12-gene signature. The integration of MAPS into nomograms significantly improved prognosis prediction.

CONCLUSION

MAPS was successfully established to have independent prognostic value, and our study provides a new avenue for developing prognostic biomarkers by microbiome profiling.

Distinct Clinical Impact and Biological Function of Angiopoietin and Angiopoietin-like Proteins in Human Breast Cancer

Secreted angiopoietin/angiopoietin-like (ANGPT/ANGPTL) proteins are involved in many biological processes. However, the role of these proteins in human breast cancers (BCs) remains largely unclear. Here, we conducted integrated omics analyses to evaluate the clinical impact of ANGPT/ANGPTL proteins and to elucidate their biological functions. In BCs, we identified rare mutations in ANGPT/ANGPTL genes, frequent gains of ANGPT1, ANGPT4, and ANGPTL1, and frequent losses of ANGPT2, ANGPTL5, and ANGPTL7, but observed that ANGPTL1, 2, and 4 were robustly downregulated in multiple datasets. The expression levels of ANGPTL1, 5, and 8 were positively correlated with overall survival (OS), while the expression levels of ANGPTL4 were negatively correlated with OS. Additionally, the expression levels of ANGPTL1 and 7 were positively correlated with distant metastasis-free survival (DMFS), while the expression levels of ANGPT2 and ANGPTL4 were negatively correlated with DMFS. The prognostic impacts of ANGPT/ANGPTL genes depended on the molecular subtypes and on clinical factors. We discovered that various ANGPT/ANGPTL genes were co-expressed with various genes involved in different pathways. Finally, with the exception of ANGPTL3, the remaining genes showed significant correlations with cancer-associated fibroblasts, endothelial cells, and microenvironment score, whereas only ANGPTL6 was significantly correlated with immune score. Our findings provide strong evidence for the distinct clinical impact and biological function of ANGPT/ANGPTL proteins, but the question of whether some of them could be potential therapeutic targets still needs further investigation in BCs.

Survival analysis in breast cancer using proteomic data from four independent datasets

Breast cancer clinical treatment selection is based on the immunohistochemical determination of four protein biomarkers: ESR1, PGR, HER2, and MKI67. Our aim was to correlate immunohistochemical results to proteome-level technologies in measuring the expression of these markers. We also aimed to integrate available proteome-level breast cancer datasets to identify and validate new prognostic biomarker candidates. We searched studies involving breast cancer patient cohorts with published survival and proteomic information. Immunohistochemistry and proteomic technologies were compared using the Mann-Whitney test. Receiver operating characteristics (ROC) curves were generated to validate discriminative power. Cox regression and Kaplan-Meier survival analysis were calculated to assess prognostic power. False Discovery Rate was computed to correct for multiple hypothesis testing. We established a database integrating protein expression data and survival information from four independent cohorts for 1229 breast cancer patients. In all four studies combined, a total of 7342 unique proteins were identified, and 1417 of these were identified in at least three datasets. ESR1, PGR, and HER2 protein expression levels determined by RPPA or LC-MS/MS methods showed a significant correlation with the levels determined by immunohistochemistry (p < 0.0001). PGR and ESR1 levels showed a moderate correlation (correlation coefficient = 0.17, p = 0.0399). An additional panel of candidate proteins, including apoptosis-related proteins (BCL2,), adhesion markers (CDH1, CLDN3, CLDN7) and basal markers (cytokeratins), were validated as prognostic biomarkers. Finally, we expanded our previously established web tool designed to validate survival-associated biomarkers by including the proteomic datasets analyzed in this study ( https://kmplot.com/ ). In summary, large proteomic studies now provide sufficient data enabling the validation and ranking of potential protein biomarkers.

Molecular intrinsic versus clinical subtyping in breast cancer: A comprehensive review

Breast cancer is a heterogeneous disease manifesting diversity at the molecular, histological and clinical level. The development of breast cancer classification was centered on informing clinical decisions. The current approach to the classification of breast cancer, which categorizes this disease into clinical subtypes based on the detection of estrogen receptor, progesterone receptor, human epidermal growth factor receptor 2, and proliferation marker Ki67, is not ideal. This is manifested as a heterogeneity of therapeutic responses and outcomes within the clinical subtypes. The newer classification model, based on gene expression profiling (intrinsic subtyping) informs about transcriptional responses downstream from IHC single markers, revealing deeper appreciation for the disease heterogeneity and capturing tumor biology in a more comprehensive way than an expression of a single protein or gene alone. While accumulating evidences suggest that intrinsic subtypes provide clinically relevant information beyond clinical surrogates, it is imperative to establish whether the current conventional immunohistochemistry-based clinical subtyping approach could be improved by gene expression profiling and if this approach has a potential to translate into clinical practice.

Epithelial-Mesenchymal Transition Programs and Cancer Stem Cell Phenotypes: Mediators of Breast Cancer Therapy Resistance

Epithelial-mesenchymal transition (EMT) programs play essential functions in normal morphogenesis and organogenesis, including that occurring during mammary gland development and glandular regeneration. Historically, EMT programs were believed to reflect a loss of epithelial gene expression signatures and morphologies that give way to those associated with mesenchymal cells and their enhanced migratory and invasive behaviors. However, accumulating evidence now paints EMT programs as representing a spectrum of phenotypic behaviors that also serve to enhance cell survival, immune tolerance, and perhaps even metastatic dormancy. Equally important, the activation of EMT programs in transformed mammary epithelial cells not only enhances their acquisition of invasive and metastatic behaviors, but also expands their generation of chemoresistant breast cancer stem cells (BCSC). Importantly, the net effect of these events results in the appearance of recurrent metastatic lesions that remain refractory to the armamentarium of chemotherapies and targeted therapeutic agents deployed against advanced stage breast cancers. Here we review the molecular and cellular mechanisms that contribute to the pathophysiology of EMT programs in human breast cancers and how these events impact their "stemness" and acquisition of chemoresistant phenotypes.

The Ongoing Search for Biomarkers of CDK4/6 Inhibitor Responsiveness in Breast Cancer

CDK4 inhibitors (CDK4/6i), such as palbociclib, ribociclib, and abemaciclib, are approved in combination with hormonal therapy as a front-line treatment for metastatic HR+, HER2- breast cancer. Their targets, CDK4 and CDK6, are cell-cycle regulatory proteins governing the G1-S phase transition across many tissue types. A key challenge remains to uncover biomarkers to identify those patients that may benefit from this class of drugs. Although CDK4/6i addition to estrogen modulation therapy essentially doubles the median progression-free survival, overall survival is not significantly increased. However, in reality only a subset of treated patients respond. Many patients exhibit primary resistance to CDK4/6 inhibition and do not derive any benefit from these agents, often switching to chemotherapy within 6 months. Some patients initially benefit from treatment, but later develop secondary resistance. This highlights the need for complementary or companion diagnostics to pinpoint patients who would respond. In addition, because CDK4 is a bona fide target in other tumor types where CDK4/6i therapy is currently in clinical trials, the lack of target identification may obscure benefit to a subset of patients there as well. This review summarizes the current status of CDK4/6i biomarker test development, both in clinical trials and at the bench, with particular attention paid to those which have a strong biological basis as well as supportive clinical data.

Half-sandwich Os(ii) and Ru(ii) bathophenanthroline complexes: anticancer drug candidates with unusual potency and a cellular activity profile in highly invasive triple-negative breast cancer cells

There is an urgent need to discover new, selective compounds to add to the limited arsenal of chemotherapeutics displaying selective toxicity for aggressive triple-negative breast cancer (TNBC) cells. The effect of two, recently developed metal-based half-sandwich complexes [Os(η6-pcym)(bphen)(dca)]PF6 (Os-dca) and [Ru(η6-pcym)(bphen)(dca)]PF6 (Ru-dca) [pcym = 1-methyl-4-(propan-2-yl)benzene (p-cymene); bphen = 4,7-diphenyl-1,10-phenanthroline (bathophenanthroline); dca = dichloroacetate] on triple-negative breast cancer cells MDA-MB-231 is reported. The complexes display selective toxicity in several tumor cells (at submicromolar concentrations), and a prominent effect is observed against highly progressive triple negative breast cancer MDA-MB-231 cells for Os-dca. The lower potency of Ru-dca in comparison with Os-dca is apparently connected with a relatively quick release of the dca ligand due to the hydrolysis of Ru-dca before this complex enters the cells. Remarkably, both Os-dca and Ru-dca reduce successfully metastasis-related properties of the triple-negative breast cancer cells such as migration, invasion, and re-adhesion. The anti-metastatic effects of Os-dca and Ru-dca are associated with their ability to suppress matrix metalloproteinase activity and/or production and reduce the expression of aquaporins. Further detailed mechanistic studies reveal that Os-dca reverses Warburg's effect and oncosis seems to be a prominent mode of cell death that predominates over apoptosis. As such, Os-dca can efficiently overcome the resistance of cancer cells to clinically-used apoptotic inducers cisplatin and carboplatin. The cytostatic and anti-metastatic properties of Os-dca in MDA-MB-231 provide a strong impetus for the development of new metal-based compounds to target hardly treatable human TNBC cells and displaying different modes of action compared to the antitumor metallodrugs in clinical use.

Drosophila as a Model System to Study Nonautonomous Mechanisms Affecting Tumour Growth and Cell Death

The study of cancer has represented a central focus in medical research for over a century. The great complexity and constant evolution of the pathology require the use of multiple research model systems and interdisciplinary approaches. This is necessary in order to achieve a comprehensive understanding into the mechanisms driving disease initiation and progression, to aid the development of appropriate therapies. In recent decades, the fruit fly Drosophila melanogaster and its associated powerful genetic tools have become a very attractive model system to study tumour-intrinsic and non-tumour-derived processes that mediate tumour development in vivo. In this review, we will summarize recent work on Drosophila as a model system to study cancer biology. We will focus on the interactions between tumours and their microenvironment, including extrinsic mechanisms affecting tumour growth and how tumours impact systemic host physiology.

A multi-step classifier addressing cohort heterogeneity improves performance of prognostic biomarkers in three cancer types

Cancer research continues to highlight the extensive genetic diversity that exists both between and within tumors. This intrinsic heterogeneity poses one of the central challenges to predicting patient clinical outcome and the personalization of treatments. Despite progress in some individual tumor types, it is not yet possible to prospectively, accurately classify patients by expected survival. One hypothesis proposed to explain this is that the prognostic classifiers developed to date are insufficiently sensitive and specific; however it is also possible that patients are not equally easy to classify by any given biomarker. We demonstrate in a cohort of 45 AJCC stage III melanoma patients that clinico-pathologic biomarkers can identify those patients that are most likely to be misclassified by a molecular biomarker. The process of modelling the classifiability of patients was then replicated in a cohort of 49 stage II breast cancer patients and 53 stage III colon cancer patients. A multi-step procedure incorporating this information not only improved classification accuracy but also indicated the specific clinical attributes that had made classification problematic in each cohort. These findings show that, even when cohorts are of moderate size, including features that explain the patient-specific performance of a prognostic biomarker in a classification framework can improve the modelling and estimation of survival.

Protein biomarkers for subtyping breast cancer and implications for future research

INTRODUCTION

Breast cancer subtypes are currently defined by a combination of morphologic, genomic, and proteomic characteristics. These subtypes provide a molecular portrait of the tumor that aids diagnosis, prognosis, and treatment escalation/de-escalation options. Gene expression signatures describing intrinsic breast cancer subtypes for predicting risk of recurrence have been rapidly adopted in the clinic. Despite the use of subtype classifications, many patients develop drug resistance, breast cancer recurrence, or therapy failure. Areas covered: This review provides a summary of immunohistochemistry, reverse phase protein array, mass spectrometry, and integrative studies that are revealing differences in biological functions within and between breast cancer subtypes. We conclude with a discussion of rigor and reproducibility for proteomic-based biomarker discovery. Expert commentary: Innovations in proteomics, including implementation of assay guidelines and standards, are facilitating refinement of breast cancer subtypes. Proteomic and phosphoproteomic information distinguish biologically functional subtypes, are predictive of recurrence, and indicate likelihood of drug resistance. Actionable, activated signal transduction pathways can now be quantified and characterized. Proteomic biomarker validation in large, well-designed studies should become a public health priority to capitalize on the wealth of information gleaned from the proteome.

HER2 is not a cancer subtype but rather a pan-cancer event and is highly enriched in AR-driven breast tumors

BACKGROUND

Approximately one in five breast cancers are driven by amplification and overexpression of the human epidermal growth factor receptor 2 (HER2) receptor kinase, and HER2-enriched (HER2E) is one of four major transcriptional subtypes of breast cancer. We set out to understand the genomics of HER2 amplification independent of subtype, and the underlying drivers and biology of HER2E tumors.

METHODS

We investigated published genomic data from 3155 breast tumors and 5391 non-breast tumors.

RESULTS

HER2 amplification is a distinct driver event seen in all breast cancer subtypes, rather than a subtype marker, with major characteristics restricted to amplification and overexpression of HER2 and neighboring genes. The HER2E subtype has a distinctive transcriptional landscape independent of HER2A that reflects androgen receptor signaling as replacement for estrogen receptor (ER)-driven tumorigenesis. HER2 amplification is also an event in 1.8% of non-breast tumors.

CONCLUSIONS

These discoveries reveal therapeutic opportunities for combining anti-HER2 therapy with anti-androgen agents in breast cancer, and highlight the potential for broader therapeutic use of HER2 inhibitors.

Cytotoxicity and anti-tumor effects of new ruthenium complexes on triple negative breast cancer cells

Triple-negative breast cancer (TNBC) is a highly aggressive breast cancer subtype. The high rate of metastasis associated to the fact that these cells frequently display multidrug resistance, make the treatment of metastatic disease difficult. Development of antitumor metal-based drugs was started with the discovery of cisplatin, however, the severe side effects represent a limitation for its clinical use. Ruthenium (Ru) complexes with different ligands have been successfully studied as prospective antitumor drugs. In this work, we demonstrated the activity of a series of biphosphine bipyridine Ru complexes (1) [Ru(SO4)(dppb)(bipy)], (2) [Ru(CO3)(dppb)(bipy)], (3) [Ru(C2O4)(dppb)(bipy)] and (4) [Ru(CH3CO2)(dppb)(bipy)]PF6 [where dppb = 1,4-bis(diphenylphosphino)butane and bipy = 2,2'-bipyridine], on proliferation of TNBC (MDA-MB-231), estrogen-dependent breast tumor cells (MCF-7) and a non-tumor breast cell line (MCF-10A). Complex (4) was most effective among the complexes and was selected to be further investigated on effects on tumor cell adhesion, migration, invasion and in apoptosis. Moreover, DNA and HSA binding properties of this complex were also investigated. Results show that complex (4) was more efficient inhibiting proliferation of MDA-MB-231 cells over non-tumor cells. In addition, complex (4) was able to inhibit MDA-MB231 cells adhesion, migration and invasion and to induce apoptosis and inhibit MMP-9 secretion in TNBC cells. Complex (4) should be further investigated in vivo in order to stablish its potential to improve breast cancer treatment.

The Changing World of Breast Cancer: A Radiologist's Perspective

Compared with other fields of medicine, there is hardly an area that has seen such fast development as the world of breast cancer. Indeed, the way we treat breast cancer has changed fundamentally over the past decades. Breast imaging has always been an integral part of this change, and it undergoes constant adjustment to new ways of thinking. This relates not only to the technical tools we use for diagnosing breast cancer but also to the way diagnostic information is used to guide treatment. There is a constant change of concepts for and attitudes toward breast cancer, and a constant flux of new ideas, new treatment approaches, and new insights into the molecular and biological behavior of this disease. Clinical breast radiologists and even more so, clinician scientists, interested in breast imaging need to keep abreast with this rapidly changing world. Diagnostic or treatment approaches that are considered useful today may be abandoned tomorrow. Approaches that seem irrelevant or far too extravagant today may prove clinically useful and adequate next year. Radiologists must constantly question what they do, and align their clinical aims and research objectives with the changing needs of contemporary breast oncology. Moreover, knowledge about the past helps better understand present debates and controversies. Accordingly, in this article, we provide an overview on the evolution of breast imaging and breast cancer treatment, describe current areas of research, and offer an outlook regarding the years to come.

Labeling of Breast Cancer Patient-derived Xenografts with Traceable Reporters for Tumor Growth and Metastasis Studies

The use of preclinical models to study tumor biology and response to treatment is central to cancer research. Long-established human cell lines, and many transgenic mouse models, often fail to recapitulate the key aspects of human malignancies. Thus, alternative models that better represent the heterogeneity of patients' tumors and their metastases are being developed. Patient-derived xenograft (PDX) models in which surgically resected tumor samples are engrafted into immunocompromised mice have become an attractive alternative as they can be transplanted through multiple generations,and more efficiently reflect tumor heterogeneity than xenografts derived from human cancer cell lines. A limitation to the use of PDXs is that they are difficult to transfect or transduce to introduce traceable reporters or to manipulate gene expression. The current protocol describes methods to transduce dissociated tumor cells from PDXs with high transduction efficiency, and the use of labeled PDXs for experimental models of breast cancer metastases. The protocol also demonstrates the use of labeled PDXs in experimental metastasis models to study the organ-colonization process of the metastatic cascade. Metastases to different organs can be easily visualized and quantified using bioluminescent imaging in live animals, or GFP expression during dissection and in excised organs. These methods provide a powerful tool to extend the use of multiple types of PDXs to metastasis research.

Antibody-Guided In Vivo Imaging for Early Detection of Mammary Gland Tumors

BACKGROUND: Earlier detection of transformed cells using target-specific imaging techniques holds great promise. We have developed TAB 004, a monoclonal antibody highly specific to a protein sequence accessible in the tumor form of MUC1 (tMUC1). We present data assessing both the specificity and sensitivity of TAB 004 in vitro and in genetically engineered mice in vivo. METHODS: Polyoma Middle T Antigen mice were crossed to the human MUC1.Tg mice to generate MMT mice. In MMT mice, mammary gland hyperplasia is observed between 6 and 10 weeks of age that progresses to ductal carcinoma in situ by 12 to 14 weeks and adenocarcinoma by 18 to 24 weeks. Approximately 40% of these mice develop metastasis to the lung and other organs with a tumor evolution that closely mimics human breast cancer progression. Tumor progression was monitored in MMT mice (from ages 8 to 22 weeks) by in vivo imaging following retro-orbital injections of the TAB 004 conjugated to indocyanine green (TAB-ICG). At euthanasia, mammary gland tumors and normal epithelial tissues were collected for further analyses. RESULTS: In vivo imaging following TAB-ICG injection permitted significantly earlier detection of tumors compared with physical examination. Furthermore, TAB-ICG administration in MMT mice enabled the detection of lung metastases while sparing recognition of normal epithelia. CONCLUSIONS: The data highlight the specificity and the sensitivity of the TAB 004 antibody in differentiating normal versus tumor form of MUC1 and its utility as a targeted imaging agent for early detection, tumor monitoring response, as well as potential clinical use for targeted drug delivery.

Differential tumor infiltration by T-cells characterizes intrinsic molecular subtypes in breast cancer

Background

Molecular subtypes of breast cancer and presence of tumor-infiltrating immune cells have both been implicated as important predictive and prognostic factors for improved risk stratification and treatment individualization of breast cancer patients. Their association, however, has not been studied in detail. The aim of this study was to evaluate the expression of the T cell markers CD8, FoxP3, CD3 and ζ-chain in molecular subtypes of the invasive margin and tumor center of breast cancer and corresponding sentinel nodes and to deduct prognostic information from these findings.

Methods

Tumor and sentinel node sections from 177 patients with primary, invasive, unilateral early-stage breast cancer were stained by immunohistochemistry and T-cell phenotypes quantified manually. Clinical data were collected from medical records.

Results

The degree of T-cell infiltration and expression of all markers differed significantly among the molecular subtypes, being highest in non-luminal, more aggressive tumors: more T-cell infiltration and higher expression of all markers were associated with hormone receptor negativity, higher proliferation and higher histological grades, but also with larger tumor size. Basal-like tumors, and most remarkably their tumor centers, hosted the highest number of FoxP3+ T-cells with an unfavorable ratio to cytotoxic CD8+ T-cells. T-cell infiltration was generally higher in the invasive margin than the tumor center. A scoring system based on densities of CD3 and CD8 could significantly separate molecular subtypes (p < 0.001).

Conclusions

Thus, immunological patterns with functional implications within each subtype are associated with prognostic factors. These findings should be further validated in studies using larger patient populations and longer follow-up.

Electronic supplementary material

The online version of this article (doi:10.1186/s12967-016-0983-9) contains supplementary material, which is available to authorized users.

Technical validation of an RT-qPCR in vitro diagnostic test system for the determination of breast cancer molecular subtypes by quantification of ERBB2, ESR1, PGR and MKI67 mRNA levels from formalin-fixed paraffin-embedded breast tumor specimens

Background

MammaTyper is a novel CE-marked in vitro diagnostic RT-qPCR assay which assigns routinely processed breast cancer specimens into the molecular subtypes Luminal A-like, Luminal B-like (HER2 positive or negative), HER2 positive (non-luminal) and Triple negative (ductal) according to the mRNA expression of ERBB2, ESR1, PGR and MKI67 and the St Gallen consensus surrogate clinical definition. Until now and regarding formalin-fixed, paraffin-embedded material (FFPE), this has been a task mostly accomplished by immunohistochemistry (IHC). However the discrepancy rates of IHC for the four breast cancer biomarkers are frequently under debate, especially for Ki-67 which carries the highest degree of inter- and even intra-observer variability. Herein we describe a series of studies in FFPE specimens which aim to fully validate the analytical performance of the MammaTyper assay, including the site to site reproducibility of the individual marker measurements.

Methods

Tumor RNA was extracted with the novel RNXtract RNA extraction kit. Synthetic RNA was used to assess the sensitivity of the RNXtract kit. DNA and RNA specific qPCR assays were used so as to determine analyte specificity of RNXtract. For the assessment of limit of blank, limit of detection, analytical measurement range and PCR efficiency of the MammaTyper kit serial dilutions of samples were used. Analytical precision studies of MammaTyper were built around two different real time PCR platforms and involved breast tumor samples belonging to different subtypes analyzed across multiple sites and under various stipulated conditions. The MammaTyper assay robustness was tested against RNA input variations, alternative extraction methods and tumor cell content.

Results

Individual assays were linear up to at least 32.33 and 33.56 Cqs (quantification cycles) for the two qPCR platforms tested. PCR efficiency ranged from 99 to 109 %. In qPCR platform 1, estimates for assay specific inter-site standard deviations (SD) were between 0.14 and 0.20 Cqs accompanied by >94 % concordant single marker assignments for all four markers. In platform 2, the inter-site SD estimates were between 0.40 and 0.66 Cqs while the concordance for single marker assignments was >94 % for all four markers. The agreement reached between the two qPCR systems located in one site was 100 % for ERBB2, 96.9 % for ESR1, 97.2 % for PGR and 98.6 % for MKI67. RT-qPCR for individual markers was stable up to a 64-fold dilution for a typical clinical sample. There was no change in assay performance detected at the level of individual markers or subtypes after using different RNA isolation methods. The presence of up to 80 % of surrounding non-tumor tissue including in situ carcinoma did not affect the assay output. Sixteen out of 20 RNXtract eluates yielded more than 50 ng/μl of RNA (average RNA output: 233 ng/μl), whereas DNA contamination per sample was restricted to less than 15 ng/μl. Median recovery rate of RNA extraction was 91.0 %.

Conclusions

In this study the performance characteristics of MammaTyper were successfully validated. The various sources of analytical perturbations resulted in negligible variations in individual marker assessments. Therefore, MammaTyper may serve as a technical improvement to current standards for decentralized FFPE-based routine assessment of the commonly used breast cancer biomarkers and for molecular subtyping of breast cancer specimens.

Electronic supplementary material

The online version of this article (doi:10.1186/s12885-016-2476-x) contains supplementary material, which is available to authorized users.

Potential Safety Loophole of Fat Grafting in Breast Cancer Patients

Autologous fat grafting (AFG) accounts for 9.1 % of all cosmetic surgical procedures in the world. Its use has been increasing tremendously in breast reconstruction and produces satisfying outcomes. However, the lack of standard guidelines for routine screening protocols in breast cancer patients before and after AFG warrants consideration of the safety of AFG use in post-mastectomy and post-lumpectomy reconstruction. This manuscript examines AFG in breast reconstruction publications and details the complications, the mechanism of AFG, as well as the relationship between adipose stem cells (ASCs) and cancer recurrence. The ASCs transferred in AFG act as multiple potent stem cells, which can impact cancer recurrence in various ways. Both in vitro and in vivo studies show that ASCs can stimulate the recurrence of breast cancer. Based on a review of existing evidence, we provide recommendations and guidelines for AFG use in breast reconstruction to aid in clinical decision-making. Further investigations are needed to evaluate the long-term clinical safety of AFG as well as the proposed guidelines.

NO LEVEL ASSIGNED

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Expression profiling of small intestinal neuroendocrine tumors identifies subgroups with clinical relevance, prognostic markers and therapeutic targets

We wanted to define the transcriptome of small intestinal neuroendocrine tumors in order to identify clinically relevant subgroups of tumors, prognostic markers and novel targets for treatment. Genome-wide expression profiling was conducted on tumor biopsies from 33 patients with well-differentiated neuroendocrine tumors of the distal ileum and metastatic disease at the time of diagnosis. Unsupervised hierarchical clustering analysis identified three groups of tumors. The largest group, comprising half of the tumors, was characterized by longer patient survival and higher expression of neuroendocrine markers, including SSTR2. Tumors with higher grade (G2/3) or gain of chromosome 14 were associated with shorter patient survival and increased expression of cell cycle-promoting genes. Pathway analysis predicted the prostaglandin E receptor 2 (PTGER2) as the most significantly activated regulator in tumors of higher grade, whereas Forkhead box M1 (FOXM1) was the most significantly activated regulator in tumors with gain of chromosome 14. Druggable genes identified from expression profiles included clinically proven SSTR2 and also novel targets, for example, receptor tyrosine kinases (RET, FGFR1/3, PDGFRB and FLT1), epigenetic regulators, molecular chaperones and signal transduction molecules. Evaluation of candidate drug targets on neuroendocrine tumors cells (GOT1) showed significant inhibition of tumor cell growth after treatment with tyrosine kinase inhibitors or inhibitors of HDAC, HSP90 and AKT. In conclusion, we have defined the transcriptome of small intestinal neuroendocrine tumors and identified novel subgroups with clinical relevance. We found specific gene expression patterns associated with tumor grade and chromosomal alterations. Our data also suggest novel prognostic biomarkers and therapies for these patients.

The Changing World of Breast Cancer: A Radiologist's Perspective

Compared with other fields of medicine, there is hardly an area that has seen such fast development as the world of breast cancer. Indeed, the way we treat breast cancer has changed fundamentally over the past decades. Breast imaging has always been an integral part of this change, and it undergoes constant adjustment to new ways of thinking. This relates not only to the technical tools we use for diagnosing breast cancer but also to the way diagnostic information is used to guide treatment. There is a constant change of concepts for and attitudes toward breast cancer, and a constant flux of new ideas, new treatment approaches, and new insights into the molecular and biological behavior of this disease. Clinical breast radiologists and even more so, clinician scientists, interested in breast imaging need to keep abreast with this rapidly changing world. Diagnostic or treatment approaches that are considered useful today may be abandoned tomorrow. Approaches that seem irrelevant or far too extravagant today may prove clinically useful and adequate next year. Radiologists must constantly question what they do, and align their clinical aims and research objectives with the changing needs of contemporary breast oncology. Moreover, knowledge about the past helps better understand present debates and controversies. Accordingly, in this article, we provide an overview on the evolution of breast imaging and breast cancer treatment, describe current areas of research, and offer an outlook regarding the years to come.

The immune microenvironment of breast ductal carcinoma in situ

The host immune response has a key role in breast cancer progression and response to therapy. However, relative to primary invasive breast cancers, the immune milieu of breast ductal carcinoma in situ (DCIS) is less understood. Here, we profile tumor infiltrating lymphocytes and expression of the immune checkpoint ligand programmed death ligand 1 (PD-L1) in 27 cases of DCIS with known estrogen receptor (ER), progesterone receptor, and human epidermal growth factor 2 (HER-2) expression using tissue microarrays. Twenty-four cases were pure DCIS and three had associated invasive ductal carcinoma. Tumors were stained by immunohistochemistry for PD-L1, as well as the lymphocyte markers CD3, CD4, CD8, FoxP3, and CD20. The expression of PD-L1 by DCIS carcinoma cells and tumor infiltrating lymphocytes was determined, and the average tumor infiltrating lymphocytes per high power field were manually scored. None of the DCIS cells expressed PD-L1, but 81% of DCIS lesions contained PD-L1+ tumor infiltrating lymphocytes. DCIS with moderate-diffuse tumor infiltrating lymphocytes was more likely to have PD-L1+ tumor infiltrating lymphocytes (P=0.004). Tumor infiltrating lymphocytes with high levels of PD-L1 expression (>50% cells) were seen only in triple-negative DCIS (P=0.0008), and PD-L1-tumor infiltrating lymphocytes were seen only in ER+/HER-2-DCIS (P=0.12). The presence of PD-L1+ tumor infiltrating lymphocytes was associated with a younger mean patient age (P=0.01). Further characterization of the DCIS immune microenvironment may identify useful targets for immune-based therapy and breast cancer prevention.

Technical innovation in adjuvant radiotherapy: Evolution and evaluation of new treatments for today and tomorrow

Recent innovations in breast cancer radiotherapy include intensity modulated radiotherapy, brachytherapy and intraoperative radiotherapy and current trials are seeking to evaluate their value in optimizing local control while maintaining cosmetic effects. Future clinical dividends in local control and survival may come from the identification of molecular signatures of breast cancer radiosensitivity, the development of predictive signatures and identification of immunohistochemical markers of risk of local recurrence. The importance of tumour heterogeneity is being increasingly recognized as an important factor in determining radiotherapy response and an improved understanding of the biology of the tumour microenvironment may identify targets that allow enhanced radiosensitisation or reversal of radioresistance when inhibited. This review describes recent developments in these areas.

Decoding breast cancer tissue-stroma interactions using species-specific sequencing

INTRODUCTION

Decoding transcriptional effects of experimental tissue-tissue or cell-cell interactions is important; for example, to better understand tumor-stroma interactions after transplantation of human cells into mouse (xenografting). Transcriptome analysis of intermixed human and mouse cells has, however, frequently relied on the need to separate the two cell populations prior to transcriptome analysis, which introduces confounding effects on gene expression.

METHODS

To circumvent this problem, we here describe a bioinformatics-based, genome-wide transcriptome analysis technique, which allows the human and mouse transcriptomes to be decoded from a mixed mouse and human cell population. The technique is based on a bioinformatic separation of the mouse and human transcriptomes from the initial mixed-species transcriptome resulting from sequencing an excised tumor/stroma specimen without prior cell sorting.

RESULTS

Under stringent separation criteria, i.e., with a read misassignment frequency of 0.2 %, we show that 99 % of the genes can successfully be assigned to be of mouse or human origin, both in silico, in cultured cells and in vivo. We use a new species-specific sequencing technology-referred to as S(3) ("S-cube")-to provide new insights into the Notch downstream response following Notch ligand-stimulation and to explore transcriptional changes following transplantation of two different breast cancer cell lines (luminal MCF7 and basal-type MDA-MB-231) into mammary fat pad tissue in mice of different immunological status. We find that MCF7 and MDA-MB-231 respond differently to fat pad xenografting and the stromal response to transplantation of MCF7 and MDA-MB-231 cells was also distinct.

CONCLUSIONS

In conclusion, the data show that the S(3) technology allows for faithful recording of transcriptomic changes when human and mouse cells are intermixed and that it can be applied to address a broad spectrum of research questions.

Identification of novel genetic markers of breast cancer survival

BACKGROUND

Survival after a diagnosis of breast cancer varies considerably between patients, and some of this variation may be because of germline genetic variation. We aimed to identify genetic markers associated with breast cancer-specific survival.

METHODS

We conducted a large meta-analysis of studies in populations of European ancestry, including 37954 patients with 2900 deaths from breast cancer. Each study had been genotyped for between 200000 and 900000 single nucleotide polymorphisms (SNPs) across the genome; genotypes for nine million common variants were imputed using a common reference panel from the 1000 Genomes Project. We also carried out subtype-specific analyses based on 6881 estrogen receptor (ER)-negative patients (920 events) and 23059 ER-positive patients (1333 events). All statistical tests were two-sided.

RESULTS

We identified one new locus (rs2059614 at 11q24.2) associated with survival in ER-negative breast cancer cases (hazard ratio [HR] = 1.95, 95% confidence interval [CI] = 1.55 to 2.47, P = 1.91 x 10(-8)). Genotyping a subset of 2113 case patients, of which 300 were ER negative, provided supporting evidence for the quality of the imputation. The association in this set of case patients was stronger for the observed genotypes than for the imputed genotypes. A second locus (rs148760487 at 2q24.2) was associated at genome-wide statistical significance in initial analyses; the association was similar in ER-positive and ER-negative case patients. Here the results of genotyping suggested that the finding was less robust.

CONCLUSIONS

This is currently the largest study investigating genetic variation associated with breast cancer survival. Our results have potential clinical implications, as they confirm that germline genotype can provide prognostic information in addition to standard tumor prognostic factors.

Dose-reduced trastuzumab emtansine: active and safe in acute hepatic dysfunction

Breast cancer is the most common cancer in women worldwide. The majority of deaths attributed to breast cancer are a result of metastatic disease, and 30% of early breast cancers (EBC) will develop distant disease. The 5-year survival of patients with metastatic disease is estimated at 23%. Breast cancer subtypes continue to be stratified histologically on oestrogen, progesterone and human epidermal growth factor-2 (HER2) receptor expression. HER2-positive breast cancers represent 25% of all breast cancer diagnoses. The therapies available for metastatic breast cancer (MBC) are expanding, in particular within the field of HER2-positive disease, with the approval of trastuzumab, pertuzumab, lapatinib and trastuzumab emtansine (TDM-1). Recently, TDM-1 has been shown to improve progression-free survival in HER2 MBC when compared to capecitabine and lapatinib in clinical studies. Its main toxicities are deranged liver function tests and thrombocytopenia. There have also been cases of acute liver failure. Therefore, its use in acute hepatic dysfunction, to our knowledge, has been neither studied nor reported. We report a patient with progressive HER2-positive MBC who had previously responded to multiple HER2-targeted therapies that presented with acute hepatic dysfunction. She was treated with dose-reduced TDM-1 safely, with clear evidence of rapid biochemical, clinical and radiological response. This allowed dose escalation of TDM-1, and the patient maintains an ongoing response.

The impact of IGF-1R expression on the outcomes of patients with breast cancer: a meta-analysis

Purpose

The value of insulin-like growth factor 1 receptor (IGF-1R) for predicting survival of patients with breast cancer remains controversial. The purpose of this study was to perform a meta-analysis of the published data to attempt to clarify the impact of IGF-1R.

Methods

Studies published between January 1, 1990 and October 1, 2014 were identified using an electronic search to aggregate the available survival results. Studies were included if they reported detecting IGF-1R expression in the primary breast cancer and analyzed patient survival data according to IGF-1R status. The principal outcome measures were hazard ratios (HRs) for survival of IGF-1R-positive patients. Combined HRs and 95% confidence intervals (CIs) were estimated using fixed- or random-effects models according to between-study heterogeneity.

Results

Ten studies, involving 5,406 patients, satisfied our inclusion criteria. Data from five studies provided the impact of IGF-1R on overall survival (OS), three studies the impact on breast cancer-specific survival (BCSS), and seven studies the impact on disease-free survival (DFS). The results of meta-analysis showed that for DFS, membranous IGF-1R positivity was not a significant predictor. The combined HR for OS/BCSS was 0.63 (95% CI: 0.42–0.95, P=0.03), indicating that membranous IGF-1R positivity was a significant predictor of better survival. IGF-1R cytoplasmic positivity was significantly associated with longer DFS and OS/BCSS (combined HR: 0.56, 95% CI: 0.35–0.89, P=0.01; combined HR: 0.55, 95% CI: 0.35–0.85, P=0.008, respectively). The results of subgroup analysis suggested that membranous IGF-1R positivity in hormone-receptor-positive breast cancer was correlated with favorable DFS (combined HR: 0.61, 95% CI: 0.41–0.92, P=0.02) and OS/BCSS (combined HR: 0.73, 95% CI: 0.57–0.93, P=0.01). Membranous IGF-1R positivity in triple-negative breast cancer predicted worse DFS (combined HR: 1.86, 95% CI: 1.03–3.34, P=0.04). Membranous IGF-1R positivity in Her-2-positive or ER (estrogen receptor)-negative breast cancer was not found to be a significant prognostic indicator.

Conclusion

The results of this meta-analysis suggest that IGF-1R expression has different prognostic values for patients with breast cancers of different molecular subtypes. It was a favorable prognostic indicator in unselected breast cancers and hormone-receptor-positive cancers, but indicated poor survival in triple-negative breast cancers.