Dissection of a metastatic gene expression signature into distinct components.
ABSTRACT: BACKGROUND: Metastasis, the process whereby cancer cells spread, is in part caused by an incompletely understood interplay between cancer cells and the surrounding stroma. Gene expression studies typically analyze samples containing tumor cells and stroma. Samples with less than 50% tumor cells are generally excluded, thereby reducing the number of patients that can benefit from clinically relevant signatures. RESULTS: For a head-neck squamous cell carcinoma (HNSCC) primary tumor expression signature that predicts the presence of lymph node metastasis, we first show that reduced proportions of tumor cells results in decreased predictive accuracy. To determine the influence of stroma on the predictive signature and to investigate the interaction between tumor cells and the surrounding microenvironment, we used laser capture microdissection to divide the metastatic signature into six distinct components based on tumor versus stroma expression and on association with the metastatic phenotype. A strikingly skewed distribution of metastasis associated genes is revealed. CONCLUSION: Dissection of predictive signatures into different components has implications for design of expression signatures and for our understanding of the metastatic process. Compared to primary tumors that have not formed metastases, primary HNSCC tumors that have metastasized are characterized by predominant down-regulation of tumor cell specific genes and exclusive up-regulation of stromal cell specific genes. The skewed distribution agrees with poor signature performance on samples that contain less than 50% tumor cells. Methods for reducing tumor composition bias that lead to greater predictive accuracy and an increase in the types of samples that can be included are presented.
Project description:BACKGROUND:Clinical grading systems using clinical features alongside nomograms lack precision in guiding treatment decisions in prostate cancer (PCa). There is a critical need for identification of biomarkers that can more accurately stratify patients with primary PCa. OBJECTIVE:To identify a robust prognostic signature to better distinguish indolent from aggressive prostate cancer (PCa). DESIGN, SETTING, AND PARTICIPANTS:To develop the signature, whole-genome and whole-transcriptome sequencing was conducted on five PCa patient-derived xenograft (PDX) models collected from independent foci of a single primary tumor and exhibiting variable metastatic phenotypes. Multiple independent clinical cohorts including an intermediate-risk cohort were used to validate the biomarkers. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS:The outcome measurement defining aggressive PCa was metastasis following radical prostatectomy. A generalized linear model with lasso regularization was used to build a 93-gene stroma-derived metastasis signature (SDMS). The SDMS association with metastasis was assessed using a Wilcoxon rank-sum test. Performance was evaluated using the area under the curve (AUC) for the receiver operating characteristic, and Kaplan-Meier curves. Univariable and multivariable regression models were used to compare the SDMS alongside clinicopathological variables and reported signatures. AUC was assessed to determine if SDMS is additive or synergistic to previously reported signatures. RESULTS AND LIMITATIONS:A close association between stromal gene expression and metastatic phenotype was observed. Accordingly, the SDMS was modeled and validated in multiple independent clinical cohorts. Patients with higher SDMS scores were found to have worse prognosis. Furthermore, SDMS was an independent prognostic factor, can stratify risk in intermediate-risk PCa, and can improve the performance of other previously reported signatures. CONCLUSIONS:Profiling of stromal gene expression led to development of an SDMS that was validated as independently prognostic for the metastatic potential of prostate tumors. PATIENT SUMMARY:Our stroma-derived metastasis signature can predict the metastatic potential of early stage disease and will strengthen decisions regarding selection of active surveillance versus surgery and/or radiation therapy for prostate cancer patients. Furthermore, profiling of stroma cells should be more consistent than profiling of diverse cellular populations of heterogeneous tumors.
Project description:Metastasis accounts for most of cancer-related deaths. Paracrine signaling between tumor cells and the stroma induces changes in the tumor microenvironment required for metastasis. Transcription factor c-Myb was associated with breast cancer (BC) progression but its role in metastasis remains unclear. Here we show that increased c-Myb expression in BC cells inhibits spontaneous lung metastasis through impaired tumor cell extravasation. On contrary, BC cells with increased lung metastatic capacity exhibited low c-Myb levels. We identified a specific inflammatory signature, including Ccl2 chemokine, that was expressed in lung metastatic cells but was suppressed in tumor cells with higher c-Myb levels. Tumor cell-derived Ccl2 expression facilitated lung metastasis and rescued trans-endothelial migration of c-Myb overexpressing cells. Clinical data show that the identified inflammatory signature, together with a MYB expression, predicts lung metastasis relapse in BC patients. These results demonstrate that the c-Myb-regulated transcriptional program in BCs results in a blunted inflammatory response and consequently suppresses lung metastasis.
Project description:Melanoma can switch between proliferative and invasive states, which have identifying gene expression signatures that correlate with good and poor prognosis, respectively. However, the mechanisms controlling these signatures are poorly understood. In this study, we identify BMI1 as a key determinant of melanoma metastasis by which its overexpression enhanced and its deletion impaired dissemination. Remarkably, in this tumor type, BMI1 had no effect on proliferation or primary tumor growth but enhanced every step of the metastatic cascade. Consistent with the broad spectrum of effects, BMI1 activated widespread gene expression changes, which are characteristic of melanoma progression and also chemoresistance. Accordingly, we showed that up-regulation or down-regulation of BMI1 induced resistance or sensitivity to BRAF inhibitor treatment and that induction of noncanonical Wnt by BMI1 is required for this resistance. Finally, we showed that our BMI1-induced gene signature encompasses all of the hallmarks of the previously described melanoma invasive signature. Moreover, our signature is predictive of poor prognosis in human melanoma and is able to identify primary tumors that are likely to become metastatic. These data yield key insights into melanoma biology and establish BMI1 as a compelling drug target whose inhibition would suppress both metastasis and chemoresistance of melanoma.
Project description:Previous work identified the Rap1 GTPase-activating protein Sipa1 as a germ-line-encoded metastasis modifier. The bromodomain protein Brd4 physically interacts with and modulates the enzymatic activity of Sipa1. In vitro analysis of a highly metastatic mouse mammary tumor cell line ectopically expressing Brd4 demonstrates significant reduction of invasiveness without altering intrinsic growth rate. However, a dramatic reduction of tumor growth and pulmonary metastasis was observed after s.c. implantation into mice, implying that activation of Brd4 may somehow be manipulating response to tumor microenvironment in the in vivo setting. Further in vitro analysis shows that Brd4 modulates extracellular matrix gene expression, a class of genes frequently present in metastasis-predictive gene signatures. Microarray analysis of the mammary tumor cell lines identified a Brd4 activation signature that robustly predicted progression and/or survival in multiple human breast cancer datasets analyzed on different microarray platforms. Intriguingly, the Brd4 signature also almost perfectly matches a molecular classifier of low-grade tumors. Taken together, these data suggest that dysregulation of Brd4-associated pathways may play an important role in breast cancer progression and underlies multiple common prognostic signatures.
Project description:The epithelial-to-mesenchymal transition (EMT) is an essential developmental process which can be hijacked by cancer cells, leading to enhanced metastasis and chemoresistance in experimental models. Recent studies have linked gene expression of EMT-associated gene signatures to increased inflammatory immune response in multiple cancer types. However, these studies did not account for the potential confounding effects of gene expression by tumor-infiltrating mesenchymal stromal cells. In this study, we comprehensively dissect the associations between multiple EMT transcription factors and EMT markers with stromal and immune tumor infiltration. We find that EMT-related genes are highly correlated with intratumoral stromal cell abundance and identify a specific relationship between stroma-corrected ZEB1 expression and decreased immune activity in multiple cancer types. We derive a stroma-corrected ZEB1-activated transcriptional signature and demonstrate that this signature includes several known inhibitors of inflammation, including BMPR2. Finally, multivariate survival analysis reveals that ZEB1 and its expression signature are significantly associated with reduced overall survival in breast cancer patients. In conclusion, this study identifies a novel association between stroma-adjusted ZEB1 expression and tumor immune activity and addresses the critical issue of confounding between EMT-associated genes and tumor stromal content.
Project description:DNA copy number alterations (CNAs) are frequent in cancer, and recently developed CNA signatures revealed their value in molecular tumor stratification for patient prognosis and platinum resistance prediction in ovarian cancer. Head and neck squamous cell carcinoma (HNSCC) is also characterized by high CNAs. In this study, we determined CNA in 173 human papilloma virus-negative HNSCC from a Dutch multicenter cohort by low-coverage whole genome sequencing and tested the prognostic value of seven cancer-derived CNA signatures for these cisplatin- and radiotherapy-treated patients. We find that a high CNA signature 1 (s1) score is associated with low values for all other signatures and better patient outcomes in the Dutch cohorts and The Cancer Genome Atlas HNSCC data set. High s5 and s7 scores are associated with increased distant metastasis rates and high s6 scores with poor overall survival. High cumulative cisplatin doses result in improved outcomes in chemoradiotherapy-treated HNSCC patients. Here we find that tumors high in s1 or low in s6 are most responsive to a change in cisplatin dose. High s5 values, however, significantly increase the risk for metastasis in patients with low cumulative cisplatin doses. Together this suggests that the processes causing these CNA signatures affect cisplatin response in HNSCC. In conclusion, CNA signatures derived from a different cancer type were prognostic and associated with cisplatin response in HNSCC, suggesting they represent underlying molecular processes that define patient outcome.
Project description:While progression from normal prostatic epithelium to invasive cancer is driven by molecular alterations, tumor cells and cells in the cancer microenvironment are co-dependent and co-evolve. Few human studies to date have focused on stroma. Here, we performed gene expression profiling of laser capture microdissected normal non-neoplastic prostate epithelial tissue and compared it to non-transformed and neoplastic low-grade and high-grade prostate epithelial tissue from radical prostatectomies, each with its immediately surrounding stroma. Whereas benign epithelium in prostates with and without tumor were similar in gene expression space, stroma away from tumor was significantly different from that in prostates without cancer. A stromal gene signature reflecting bone remodeling and immune-related pathways was upregulated in high compared to low-Gleason grade cases. In validation data, the signature discriminated cases that developed metastasis from those that did not. These data suggest that the microenvironment may influence prostate cancer initiation, maintenance, and metastatic progression.Stromal cells contribute to tumor development but the mechanisms regulating this process are still unclear. Here the authors analyze gene expression profiles in the prostate and show that stromal gene signature changes ahead of the epithelial gene signature as prostate cancer initiates and progresses.
Project description:Metastasis requires tumor cells to navigate through a stiff stroma and squeeze through confined microenvironments. Whether tumors exploit unique biophysical properties to metastasize remains unclear. Data show that invading mammary tumor cells, when cultured in a stiffened three-dimensional extracellular matrix that recapitulates the primary tumor stroma, adopt a basal-like phenotype. Metastatic tumor cells and basal-like tumor cells exert higher integrin-mediated traction forces at the bulk and molecular levels, consistent with a motor-clutch model in which motors and clutches are both increased. Basal-like nonmalignant mammary epithelial cells also display an altered integrin adhesion molecular organization at the nanoscale and recruit a suite of paxillin-associated proteins implicated in invasion and metastasis. Phosphorylation of paxillin by Src family kinases, which regulates adhesion turnover, is similarly enhanced in the metastatic and basal-like tumor cells, fostered by a stiff matrix, and critical for tumor cell invasion in our assays. Bioinformatics reveals an unappreciated relationship between Src kinases, paxillin, and survival of breast cancer patients. Thus adoption of the basal-like adhesion phenotype may favor the recruitment of molecules that facilitate tumor metastasis to integrin-based adhesions. Analysis of the physical properties of tumor cells and integrin adhesion composition in biopsies may be predictive of patient outcome.
Project description:The extracellular matrix (ECM) is a major component of tumors and a significant contributor to cancer progression. In this study, we use proteomics to investigate the ECM of human mammary carcinoma xenografts and show that primary tumors of differing metastatic potential differ in ECM composition. Both tumor cells and stromal cells contribute to the tumor matrix and tumors of differing metastatic ability differ in both tumor- and stroma-derived ECM components. We define ECM signatures of poorly and highly metastatic mammary carcinomas and these signatures reveal up-regulation of signaling pathways including TGF? and VEGF. We further demonstrate that several proteins characteristic of highly metastatic tumors (LTBP3, SNED1, EGLN1, and S100A2) play causal roles in metastasis, albeit at different steps. Finally we show that high expression of LTBP3 and SNED1 correlates with poor outcome for ER(-)/PR(-)breast cancer patients. This study thus identifies novel biomarkers that may serve as prognostic and diagnostic tools. DOI: http://dx.doi.org/10.7554/eLife.01308.001.