Video Q&A: molecular profiling of breast cancer.
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ABSTRACT:
SUBMITTER: Caldas C
PROVIDER: S-EPMC3719854 | biostudies-literature | 2013 Jun
REPOSITORIES: biostudies-literature
Publications
In this video Q&A, we talk to Professor Carlos Caldas about the identification of breast cancer subtypes through molecular profiling, and the clinical implications for diagnosis and treatment. ...[more]
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Project description:INTRODUCTION: Identification of new therapeutic agents for breast cancer (BC) requires preclinical models that reproduce the molecular characteristics of their respective clinical tumors. In this work, we analyzed the genomic and gene expression profiles of human BC xenografts and the corresponding patient tumors. METHODS: Eighteen BC xenografts were obtained by grafting tumor fragments from patients into Swiss nude mice. Molecular characterization of patient tumors and xenografts was performed by DNA copy number analysis and gene expression analysis using Affymetrix Microarrays. RESULTS: Comparison analysis showed that 14/18 pairs of tumors shared more than 56% of copy number alterations (CNA). Unsupervised hierarchical clustering analysis showed that 16/18 pairs segregated together, confirming the similarity between tumor pairs. Analysis of recurrent CNA changes between patient tumors and xenografts showed losses in 176 chromosomal regions and gains in 202 chromosomal regions. Gene expression profile analysis showed that less than 5% of genes had recurrent variations between patient tumors and their respective xenografts; these genes largely corresponded to human stromal compartment genes. Finally, analysis of different passages of the same tumor showed that sequential mouse-to-mouse tumor grafts did not affect genomic rearrangements or gene expression profiles, suggesting genetic stability of these models over time. CONCLUSIONS: This panel of human BC xenografts maintains the overall genomic and gene expression profile of the corresponding patient tumors and remains stable throughout sequential in vivo generations. The observed genomic profile and gene expression differences appear to be due to the loss of human stromal genes. These xenografts, therefore, represent a validated model for preclinical investigation of new therapeutic agents.
| S-EPMC3496128 | biostudies-literature
Project description:BackgroundTumors develop by progression through a series of stages. Every cell of the tumor microenvironment is constantly changing in the flow of the cancer progression. It has become clear in recent years that stroma is essential for tumor maintenance and growth. Here, we aimed to give a chronological order of gene expression changes given in the dynamical framework of microinvasive breast cancer microenvironment.MethodsRNA-seq was performed on seven microinvasive breast cancers. For each of them we microdissected seven different portions of the tumor, four related to the breast epithelium and three to the stroma. Breast epithelium was chronologically subdivided in normal breast epithelium (NBE), carcinoma in situ (CIS), emerging invasive fingers (EIF) and invasive breast cancer (IBC). For each of the breast epithelium subdivisions we collected the adjacent stroma (S): S-NBE, S-EIF and S-IBC.ResultsThe overall differentially expressed genes (DEGs) in all the compartments were analysed and evaluated to understand the pathways involved in tumor progression. Then we analysed the DEGs of the epithelial and stromal portions in comparison with the normal portions. We observed that the stromal cells are necessary for the development and the maintenance of the tumor, especially in tumor progression. Moreover the most important genes involved in the main metabolic pathways were analysed and the communications within the different cell compartments were highlighted.ConclusionsAs a future perspective, a deeply study of the identified key genes, particularly in the stromal cells, will be crucial to develop an anticancer therapy that is undergoing a conversion from a cancer cell-centric strategy to a stroma-centric strategy, more genomically stable.
| S-EPMC6547528 | biostudies-literature
Project description:The implementation of molecular profiling technologies in oncology deepens our knowledge for the molecular landscapes of cancer diagnoses, identifying aberrations that could be linked with specific therapeutic vulnerabilities. In particular, there is an increasing list of molecularly targeted anticancer agents undergoing clinical development that aim to block specific molecular aberrations. This leads to a paradigm shift, with an increasing list of specific aberrations dictating the treatment of patients with cancer. This paradigm shift impacts the field of clinical trials, since the classical approach of having clinico-pathological disease characteristics dictating the patients' enrolment in oncology trials shifts towards the implementation of molecular profiling as pre-screening step. In order to facilitate the successful clinical development of these new anticancer drugs within specific molecular niches of cancer diagnoses, there have been developed new, innovative trial designs that could be classified as follows: i) longitudinal cohort studies that implement (or not) "nested" downstream trials, 2) studies that assess the clinical utility of molecular profiling, 3) "master" protocol trials, iv) "basket" trials, v) trials following an adaptive design. In the present article, we review these innovative study designs, providing representative examples from each category and we discuss the challenges that still need to be addressed in this era of new generation oncology trials implementing molecular profiling. Emphasis is put on the field of breast cancer clinical trials.
| S-EPMC4944544 | biostudies-literature
Project description:Precision oncology with next generation sequencing (NGS) using tumor tissue with or without blood has begun in Japan. Tumor molecular profiling tests are available, including the OncoGuide™ NCC Oncopanel System and FoundationOne® CDx (F1CDx). Our purpose was to identify potentially actionable genetic alterations in breast cancer with this comprehensive tumor profiling test. We enrolled 115 patients with pathologically diagnosed advanced or metastatic breast cancer. Comprehensive tumor genomic profiling, microsatellite instability, and tumor mutational burden (TMB) were determined using F1CDx. Testing was successful in 109/115 cases (94.8%). Clinically actionable alterations were identified in 76% of advanced breast cancer patients. The most frequent short variants were in TP53 (48.6%), PIK3CA (38.5%), GATA3 (11.0%), PTEN (11.0%), and BRCA1 (10.1%), and structural variants were in ERBB2 (24.8%), MYC (21.1%), RAD21 (21.1%), CCND1 (11.9%), FGF19 (10.1%), and PTEN (10.1%). Regarding human epidermal growth factor receptor (HER)2 status, 106/109 samples (97.2%) were concordant between F1CDx and HER2 testing with immunohistochemistry/fluorescence in situ hybridization. However, ERBB2 amplification was newly detected in four samples and ERBB2 mutations were detected in five HER2-negative breast cancer samples. Oncogenic BRCA mutations were found in three samples with F1CDx among 27 germline testing-negative samples. The mean TMB in all samples was 6.28 mut/Mb and tended to be higher in luminal B and triple-negative breast cancer (mean = 8.1 and 5.9 mut/Mb, respectively) compared with other subtypes. In conclusion, we established a system for precision oncology and obtained preliminary data with NGS as the first step. The information in this clinical sequencing panel will help guide the development of new treatments for breast cancer patients.
| S-EPMC7877356 | biostudies-literature
Project description:Breast cancer metastasis to gynaecological organs is an understudied pattern of tumour spread. We explored clinico-pathological and molecular features of these metastases to better understand whether this pattern of dissemination is organotropic or a consequence of wider metastatic dissemination. Primary and metastatic tumours from 54 breast cancer patients with gynaecological metastases were analysed using immunohistochemistry, DNA copy-number profiling, and targeted sequencing of 386 cancer-related genes. The median age of primary tumour diagnosis amongst patients with gynaecological metastases was significantly younger compared to a general breast cancer population (46.5 versus 60 years; p < 0.0001). Median age at metastatic diagnosis was 54.4, time to progression was 4.8 years (range 0-20 years), and survival following a diagnosis of metastasis was 1.95 years (range 0-18 years). Patients had an average of five involved sites (most frequently ovary, fallopian tube, omentum/peritoneum), with fewer instances of spread to the lungs, liver, or brain. Invasive lobular histology and luminal A-like phenotype were over-represented in this group (42.8 and 87.5%, respectively) and most patients had involved axillary lymph nodes (p < 0.001). Primary tumours frequently co-expressed oestrogen receptor cofactors (GATA3, FOXA1) and harboured amplifications at 8p12, 8q24, and 11q13. In terms of phenotype conversion, oestrogen receptor status was generally maintained in metastases, FOXA1 increased, and expression of progesterone receptor, androgen receptor, and GATA3 decreased. ESR1 and novel AR mutations were identified. Metastasis to gynaecological organs is a complication frequently affecting young women with invasive lobular carcinoma and luminal A-like breast cancer, and hence may be driven by sustained hormonal signalling. Molecular analyses reveal a spectrum of factors that could contribute to de novo or acquired resistance to therapy and disease progression.
| S-EPMC6317061 | biostudies-literature
Project description:Summary: Breast cancer cell lines have been used widely to investigate breast cancer pathobiology and new therapies. Breast cancer is a molecularly heterogeneous disease, and it is important to understand how well and which cell lines best model that diversity. In particular, microarray studies have identified molecular subtypes (luminal A, luminal B, ERBB2-associated, basal-like and normal-like) with characteristic gene-expression patterns and underlying DNA copy number alterations (CNAs). Here, we studied a collection of breast cancer cell lines to catalog molecular profiles and to assess their relation to breast cancer subtypes. Whole-genome DNA microarrays were used to profile gene expression and CNAs in a collection of 52 widely-used breast cancer cell lines, and comparisons were made to existing profiles of primary breast tumors. Hierarchical clustering was used to identify gene-expression subtypes, and Gene Set Enrichment Analysis (GSEA) to discover biological features of those subtypes. Genomic and transcriptional profiles were integrated to discover within high-amplitude CNAs candidate cancer genes with coordinately altered gene copy number and expression. Transcriptional profiling of breast cancer cell lines identified one luminal and two basal-like (A and B) subtypes. Luminal lines displayed an estrogen receptor (ER) signature and resembled luminal-A/B tumors, basal-A lines were associated with ETS-pathway and BRCA1 signatures and resembled basal-like tumors, and basal-B lines displayed mesenchymal and stem-cell characteristics. Compared to tumors, cell lines exhibited similar patterns of CNA, but an overall higher complexity of CNA (genetically simple luminal-A tumors were not represented), and only partial conservation of subtype-specific CNAs. We identified 80 high-level DNA amplifications and 13 presumptive homozygous deletions, and the resident genes with concomitantly altered gene-expression, highlighting known and novel candidate breast cancer genes. Overall, breast cancer cell lines were genetically more complex than tumors, but retained expression patterns with relevance to the luminal-basal subtype distinction. The compendium of molecular profiles defines cell lines suitable for investigations of subtype-specific pathobiology, biomarkers and therapies, and provides a resource for discovery of new breast cancer genes. HEEBO oligonucleotide microarrays from the Stanford Functional Genomics Facility were used to perform gene expression profiling of 50 human breast epithelial cell lines, in comparison to a universal RNA reference. Expression data were analyzed by hierarchical clustering to identify subgroups, and gene set enrichment analysis to identify subgroup-specific gene pathways.
| S-ECPF-GEOD-15361 | biostudies-other
Project description:BACKGROUND: Estrogen receptor positive (ER+) breast cancers (BC) are heterogeneous with regard to their clinical behavior and response to therapies. The ER is currently the best predictor of response to the anti-estrogen agent tamoxifen, yet up to 30-40% of ER+BC will relapse despite tamoxifen treatment. New prognostic biomarkers and further biological understanding of tamoxifen resistance are required. We used gene expression profiling to develop an outcome-based predictor using a training set of 255 ER+ BC samples from women treated with adjuvant tamoxifen monotherapy. We used clusters of highly correlated genes to develop our predictor to facilitate both signature stability and biological interpretation. Independent validation was performed using 362 tamoxifen-treated ER+ BC samples obtained from multiple institutions and treated with tamoxifen only in the adjuvant and metastatic settings. RESULTS: We developed a gene classifier consisting of 181 genes belonging to 13 biological clusters. In the independent set of adjuvantly-treated samples, it was able to define two distinct prognostic groups (HR 2.01 95%CI: 1.29-3.13; p = 0.002). Six of the 13 gene clusters represented pathways involved in cell cycle and proliferation. In 112 metastatic breast cancer patients treated with tamoxifen, one of the classifier components suggesting a cellular inflammatory mechanism was significantly predictive of response. CONCLUSION: We have developed a gene classifier that can predict clinical outcome in tamoxifen-treated ER+ BC patients. Whilst our study emphasizes the important role of proliferation genes in prognosis, our approach proposes other genes and pathways that may elucidate further mechanisms that influence clinical outcome and prediction of response to tamoxifen.
| S-EPMC2423197 | biostudies-literature
Project description:Transcriptomic profiling of breast tumors provides opportunity for subtyping and molecular-based patient stratification. In diagnostic applications the specimen profiled should be representative of the expression profile of the whole tumor and ideally capture properties of the most aggressive part of the tumor. However, breast cancers commonly exhibit intra-tumor heterogeneity at molecular, genomic and in phenotypic level, which can arise during tumor evolution. Currently it is not established to what extent a random sampling approach may influence molecular breast cancer diagnostics.In this study we applied RNA-sequencing to quantify gene expression in 43 pieces (2-5 pieces per tumor) from 12 breast tumors (Cohort 1). We determined molecular subtype and transcriptomic grade for all tumor pieces and analysed to what extent pieces originating from the same tumors are concordant or discordant with each other. Additionally, we validated our finding in an independent cohort consisting of 19 pieces (2-6 pieces per tumor) from 6 breast tumors (Cohort 2) profiled using microarray technique. Exome sequencing was also performed on this cohort, to investigate the extent of intra-tumor genomic heterogeneity versus the intra-tumor molecular subtype classifications.Molecular subtyping was consistent in 11 out of 12 tumors and transcriptomic grade assignments were consistent in 11 out of 12 tumors as well. Molecular subtype predictions revealed consistent subtypes in four out of six patients in this cohort 2. Interestingly, we observed extensive intra-tumor genomic heterogeneity in these tumor pieces but not in their molecular subtype classifications.Our results suggest that macroscopic intra-tumoral transcriptomic heterogeneity is limited and unlikely to have an impact on molecular diagnostics for most patients.
| S-EPMC5708109 | biostudies-literature
Project description:The B7 gene family has crucial roles in the regulation of adaptive cellular immunity. In cancer, deregulation of co-inhibitory B7 molecules is associated with reduced antitumor immunity and cancer immune evasion. FDA approval of cancer immunotherapy antibodies against cytotoxic T lymphocyte-associated protein 4 (CTLA-4) and programmed cell death-1 (PD-1)-both ligands of the B7 family-demonstrate the impact of these checkpoint regulators in cancer. Using data from cBioPortal, we performed comprehensive molecular profiling of the 10 currently known B7 family proteins in 105 different cancers. B7 family members were amplified in breast cancer: with B7 mRNA levels upregulated in a cohort of 1,098 patients with all types of breast cancer and in 82 patients with triple-negative breast cancer. Promoter methylation analysis indicated an epigenetic basis for deregulation of certain B7 family genes in breast cancer. Moreover, patients with B7-H6 genomic alterations had significantly worse overall survival, and certain clinical attributes were associated with B7-H6 expression, which indicates that B7-H6 may be a potential target for breast cancer immunotherapy. Finally, using network analysis (based on data from cBioportal), we identified BTLA, MARCH8, PLSCR1 and SMAD3 as potentially involved in T cell signaling under regulation of B7 family proteins.
| S-EPMC5007954 | biostudies-literature
Project description:BackgroundThere is a strong need to define the molecular changes in normal at-risk breast epithelium to identify biomarkers and new targets for breast cancer prevention and to develop a molecular signature for risk assessment. Improved methods of breast epithelial sampling are needed to promote whole-genome molecular profiling, increase ductal epithelial cell yield, and reduce sample cell heterogeneity.MethodsWe developed an improved method of breast ductal sampling with ductal lavage through a 22-gauge catheter and collection of ductal samples with a microaspirator. Women at normal risk or increased risk for breast cancer were studied. Ductal epithelial samples were analyzed for cytopathologic changes, cellular yield, epithelial cell purity, quality and quantity of DNA and RNA, and use in multiple downstream molecular applications.ResultsWe studied 50 subjects, including 40 subjects at normal risk for breast cancer and 37 subjects with non-nipple aspirate fluid-yielding ducts. This method provided multiple 1.0 mL samples of high ductal epithelial cell content (median ≥8 samples per subject of ≥5,000 cells per sample) with 80%-100% epithelial cell purity. Extraction of a single intact ductal sample (fluid and cells) or the separate frozen cellular component provided DNA and RNA for multiple downstream studies, including quantitative reverse transcription- polymerase chain reaction (PCR) for microRNA, quantitative PCR for the human telomerase reverse transcriptase gene, whole-genome DNA amplification, and array comparative genomic hybridization analysis.ConclusionAn improved breast epithelial sampling method has been developed, which should significantly expand the acquisition and biomarker analysis of breast ductal epithelium in women at risk for breast cancer.
| S-EPMC4462519 | biostudies-literature