Gene Expression-based Molecular Subtypes Research Articles

A Genomically and Clinically Annotated Patient-Derived Xenograft Resource for Preclinical Research in Non-Small Cell Lung Cancer.

Patient-derived xenografts of lung cancer retain key features observed in the originating patient tumors and show expected responses to treatment with standard-of-care agents, providing experimentally tractable and reproducible models for preclinical investigations.

Deconvolution of the Immune Microenvironment Can Predict the Outcome of Myeloma Patients and Inform Potential Intervention Strategies

IntroductionThe microenvironment of cells around multiple myeloma (MM) tumors strongly influences patient outcomes, as evidenced by the success of immunomodulatory therapies. To develop precision immunotherapeutic approaches, it is essential to identify and enumerate pro- and anti-myelomatous cell types within the bone marrow.MethodsThe population of immune and other non-tumor cell types was estimated from RNA microarray data derived from paired whole bone marrow (WBM) core biopsies and CD138-enriched (CD138+) bone marrow aspirates at presentation from 405 newly diagnosed MM patients who underwent similar treatments. Expression profiles from CD138+ cells were used to infer the residual transcriptome contribution of immune and stromal cells in the WBM array data. We performed unsupervised clustering of the estimated microenvironment gene expression profiles and calculated the statistical significance of cluster splitting using the R packages ConsensusClusterPlus and sigclust, respectively. Individual cell type composition of these microenvironments was estimated using the DCQ algorithm and a gene expression signature matrix based on the published LM22 leukocyte matrix (Newman et al., 2015) that we augmented with phenotypic profiles of 5 bone marrow-specific cell types (myelomatous plasma cells, plasma memory cells, osteoclasts, osteoblasts, and adipocytes).ResultsThis deconvolution approach accurately estimated the percent of tumor cells in WBM core biopsy as estimated by both microscopy and flow cytometry (PCC = 0.57, RMSE = 10.9%). Unsupervised consensus clustering of whole bone marrow microenvironment gene expression data revealed 5 significantly different subtypes. The two largest subtypes, Cluster 1 (N=136) and Cluster 2 (N=128), had the most divergent outcomes with median PFS values of 78 months and 53 months, respectively. Cluster 1 was significantly enriched for ISS-I patients (FDR < 0.02) while Cluster 2 was enriched for ISS-III patients (FDR < 7x10^-5). Cluster 2 showed a significant increase in estimated M1 macrophages, CD8+ T cells, adipocytes, and dendritic cells with a decrease in estimated osteoclasts versus all other clusters combined (FDRs < 0.05). Cluster 5 (N=63) had the second worst PFS at 55 months, however, it had 44% fewer than expected ISS-III patients (FDR = 0.04). Cluster 5 had fewer estimated T cells and adipocytes, and it was the only cluster with a significant (3-fold) increase in estimated NK cells compared to the other clusters combined (FDRs < 0.05). No clusters were significantly enriched for older individuals, hyperdiploidy or common chromosomal translocations (t(4;14), t(11;14), t(14;16)). No clusters were significantly enriched for CD138+ gene expression-defined high risk patients (UAMS GEP-70) or CD138+ gene expression-based molecular subtypes (Zhan et al., 2006).ConclusionsWe demonstrated the technical feasibility to accurately delineate CD138+ expression profiles from a bulk transcriptome admixture and to use the residual microenvironment transcriptome to cluster patients into distinct microenvironment subtypes. Within these subtypes, the clinical outcomes are not explained by CD138+ molecular features nor ISS stage. For example, Cluster 5 has patients with poor prognosis compared to the rest of the cohort, yet it is not significantly enriched for high risk translocations, ISS-III patients, nor GEP-70 high risk patients. Cluster 5 patients show significant decrease in both CD8+ T cell infiltrate and activated dendritic cells, perhaps reflective of a high risk immune state that would not be responsive to checkpoint inhibition. Moreover, Cluster 5 patients are the only ones to have an increase in NK cells, suggesting one could try to stimulate these NK cells to reinvigorate their anti-tumor immunity. Cluster 2, with the poorest prognosis patients and highest tumor burden (by ISS stage), shows increased CD8+ T cells and dendritic cells (where all other clusters are neutral or decreased in these cell types). Cluster 2 patients may thus benefit from checkpoint blockade, and we plan to further explore relevant checkpoint-related pathways in this cohort. Adding this layer of immune-microenvironment to the analysis of myeloma patient samples enables us to formulate biological hypotheses independent of CD138+ biology and may eventually guide more tailored therapeutic interventions and improve outcomes for patients. [Display omitted] DisclosuresDanziger:Celgene Corporation: Employment. Dervan:Twinstrand Biosciences: Equity Ownership; Celgene Corporation: Employment, Equity Ownership. Schmitz:Celgene Corporation: Employment. Copeland:Celgene Corporation: Employment. Fitch:Celgene Corporation: Employment. Newhall:Celgene Corporation: Employment, Equity Ownership. Barlogie:Celgene Corporation: Consultancy, Research Funding; Millenium Pharmaceuticals: Consultancy, Research Funding. Foy:Celgene Corporation: Employment, Equity Ownership. Trotter:Celgene Corporation: Equity Ownership; Celgene Institute for Translational Research Europe: Employment. Hershberg:Adaptive Biotechnologies: Membership on an entity's Board of Directors or advisory committees; Fraizer Healthcare Partners: Consultancy; NanoString Technologies: Membership on an entity's Board of Directors or advisory committees; Celgene Corporation: Employment, Equity Ownership. Ratushny:Celgene Corporation: Employment. Morgan:Takeda: Consultancy, Honoraria; Bristol Myers: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding.

Abstract PO-008: Know thy neighbor: Deciphering the intra-tumor heterogeneity in ovarian cancer with molecular assessment of subtype heterogeneity (MASH)

Abstract The treatment of ovarian cancer has shifted away from the one-model-fit-all practice in this era of precision medicine. The current treatment for ovarian cancer has evolved to stratify patients based on histology and the mutation status. For instance, BRCA mutated non-mucinous ovarian cancer will be recommended for PARP inhibitor treatment in both the first- and second-line maintenance settings. However, beyond this concept of BRCAness, there still exists background heterogeneity at the transcriptomic level. In high grade serous carcinoma (HGSC), diverse molecular heterogeneity based on gene expression profiling has been shown by the Australian and the TCGA cohorts. This molecular heterogeneity has been demonstrated to be very robust and reproducible by a large-scale meta-analysis study consisting of 1,538 samples. At least 5 distinct gene-expression based molecular subtypes (GEMS) have been identified. The C1 and C5 subtype from the Tothill dataset corresponds to the Mesenchymal and Proliferative subtype from the TCGA dataset and the Mes and Stem-A subtype from the 1,538 meta-analysis dataset, respectively. These GEMS have been correlated with patient survival. The C1/Mesenchymal/Mes and C5/Proliferative/Stem-A GEMS are associated with poorer survival outcomes. Contentions have always been whether these GEMS could be used for patient stratification. To achieve this, a tool to decipher the intra-tumor heterogeneity (ITH) of GEMS is needed to ascertain whether a robust stratification scheme is feasible. Molecular assessment of subtype heterogeneity (MASH) was developed to comprehensively report on the composition of all transcriptomic subtypes within a tumor. Using MASH on 3431 ovarian cancer samples, correlation and association analyses with survival, metastasis and clinical outcomes were performed to assess the impact of GEMS composition as a surrogate for ITH. We identified that 30% of ovarian tumours consist of two or more GEMS. When biological features of the GEMS constituents were examined, we identified significant impact on clinical outcomes with the presence of poor prognostic GEMS (Mes or Stem-A). Poorer outcomes correlated with having higher degrees of poor prognostic GEMS populations within the tumor. Finally, a clinically applicable MASH assay using NanoString® technology was developed to comprehensively describe constituents of GEMS in ovarian cancer. Citation Format: Tuan Zea Tan, Valerie Heong, Jieru Ye, Diana Lim, Jeffrey Low, Mahesh Choolani, Clare Scott, David S.P. Tan, Ruby Y.J. Huang. Know thy neighbor: Deciphering the intra-tumor heterogeneity in ovarian cancer with molecular assessment of subtype heterogeneity (MASH) [abstract]. In: Proceedings of the AACR Virtual Special Conference on Tumor Heterogeneity: From Single Cells to Clinical Impact; 2020 Sep 17-18. Philadelphia (PA): AACR; Cancer Res 2020;80(21 Suppl):Abstract nr PO-008.

Development and Validation of the Gene Expression Predictor of High-grade Serous Ovarian Carcinoma Molecular SubTYPE (PrOTYPE).

Gene expression-based molecular subtypes of high-grade serous tubo-ovarian cancer (HGSOC), demonstrated across multiple studies, may provide improved stratification for molecularly targeted trials. However, evaluation of clinical utility has been hindered by nonstandardized methods, which are not applicable in a clinical setting. We sought to generate a clinical grade minimal gene set assay for classification of individual tumor specimens into HGSOC subtypes and confirm previously reported subtype-associated features. Adopting two independent approaches, we derived and internally validated algorithms for subtype prediction using published gene expression data from 1,650 tumors. We applied resulting models to NanoString data on 3,829 HGSOCs from the Ovarian Tumor Tissue Analysis consortium. We further developed, confirmed, and validated a reduced, minimal gene set predictor, with methods suitable for a single-patient setting. Gene expression data were used to derive the predictor of high-grade serous ovarian carcinoma molecular subtype (PrOTYPE) assay. We established a de facto standard as a consensus of two parallel approaches. PrOTYPE subtypes are significantly associated with age, stage, residual disease, tumor-infiltrating lymphocytes, and outcome. The locked-down clinical grade PrOTYPE test includes a model with 55 genes that predicted gene expression subtype with >95% accuracy that was maintained in all analytic and biological validations. We validated the PrOTYPE assay following the Institute of Medicine guidelines for the development of omics-based tests. This fully defined and locked-down clinical grade assay will enable trial design with molecular subtype stratification and allow for objective assessment of the predictive value of HGSOC molecular subtypes in precision medicine applications.See related commentary by McMullen et al., p. 5271.

Abstract A03: PrOTYPE (Predictor of high-grade-serous Ovarian carcinoma molecular subTYPE): The development and validation of a clinical-grade consensus classifier for the molecular subtypes of high-grade serous tubo-ovarian cancer

Abstract Background: Gene expression-based molecular subtypes of high-grade serous tubo-ovarian cancer (HGSOC) are distinguished by differential immune and stromal infiltration and may provide opportunities for targeted therapies. Integration of molecular subtypes into clinical trials has been hindered by inconsistent subtyping methodology. Methods: Adopting two independent approaches, we derived and internally validated algorithms for molecular subtype prediction from gene-expression array data in 1,650 tumors. We applied resulting models to assign labels to 3829 HGSOCs from the Ovarian Tumor Tissue Analysis (OTTA) consortium evaluated on NanoString. Using the labeled NanoString data, we developed, confirmed, and validated a minimal gene set, clinical-grade test and prediction tool. We also used the OTTA dataset to evaluate associations between molecular subtype, biologic, and clinical features. Findings: The locked-down test included a model with 55 genes that predicted HGSOC molecular subtype with &amp;gt;95% accuracy. Subtype varied between primary and metastatic site taken at the time of primary surgery, and was significantly associated with age, stage, CD8+ lymphocyte infiltration, residual disease, and outcome. In multivariable models, molecular subtypes lose their prognostic significance in the presence of risk factors such as residual disease and BRCA1/2 germline mutations. Interpretation: We validated the Predictor of high-grade-serous Ovarian carcinoma molecular subTYPE, or PrOTYPE, following the Institute of Medicine guidelines for the development of omics-based tests. This simple-to-use, cost-effective, fully defined, and locked-down clinical-grade assay will facilitate molecular subtype stratification into clinical trial design. PrOTYPE will allow for objective assessment of HGSOC molecular subtype predictive value in precision medicine applications. Citation Format: Aline Talhouk, Joshy George, Chen Wang, Ellen Goode, Susan Ramus, Jennifer Doherty, David Bowtell, Michael Anglesio, OTTA Consortium. PrOTYPE (Predictor of high-grade-serous Ovarian carcinoma molecular subTYPE): The development and validation of a clinical-grade consensus classifier for the molecular subtypes of high-grade serous tubo-ovarian cancer [abstract]. In: Proceedings of the AACR Special Conference on Advances in Ovarian Cancer Research; 2019 Sep 13-16, 2019; Atlanta, GA. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(13_Suppl):Abstract nr A03.

The molecular limitations of biomarker research in bladder cancer.

Urothelial carcinoma of the bladder (UCB) is a common malignancy with limited systemic treatment options in advanced stages. Despite recent advances in immunotherapy, the majority of patients do not respond to these treatments. There is an unmet need for developing robust biomarkers to inform treatment decisions and identify patients who are likely to respond. A MEDLINE/PubMed literature search was performed, focusing on tissue-based and circulating biomarkers, and their potential in muscle-invasive UCB. UCB is a heterogeneous disease that consists of several clonal and subclonal populations, each with a mix of truncal and private genomic alterations. This inter- and intra-tumoral heterogeneous landscape results in the development of treatment resistance. Tumor heterogeneity also constitutes a barrier to the development of robust markers of response and resistance to chemotherapy and immunotherapy. Defects in DNA repair genes and a high tumor mutational burden independently confer sensitivity to cisplatin-based chemotherapy and checkpoint inhibitors. Oncogenic alterations such as FGFR3 mutations and fusions are associated with response to FGFR3 inhibitors. Several emerging potential biomarkers, including gene expression-based molecular subtypes, T-cell receptor clonality, and tissue- or blood-based immune-gene profiling, require prospective testing and validation. Tissue-based biomarkers such as PD-L1 immunohistochemistry have several limitations due to discordance in assay methodology and trial designs. Novel liquid-biopsy techniques are promising as potential biomarkers. Validated biomarkers that capture the complexity of the biology of both the tumor and the tumor microenvironment are needed in muscle-invasive UCB. Standardization of methods is critical to developing reliable biomarkers to guide clinical management.

Abstract A30: Frizzled-7 (FZD7)-mediated non-canonical Wnt-Planar Cell Polarity (PCP) signalling pathway as a novel molecular driver for the C5/Proliferative/Stem-A molecular subtype of ovarian cancer.

Abstract Ovarian cancer (OC), in particular high grade serous carcinoma (HGSC), has been shown to exhibit diverse molecular heterogeneity based on gene expression profiling by the Australian and the TCGA cohorts. This molecular heterogeneity has been demonstrated to be very robust and reproducible by a large-scale meta-analysis study consisting of 1,538 samples from our group. At least 5 distinct gene-expression based molecular subtypes (GEMS) of EOC have been identified. The C5 subtype from the Tothill dataset corresponds to the Proliferative subtype from the TCGA dataset and the Stem-A subtype from the 1,538 meta-analysis dataset. These GEMS have been correlated with patient survival. The C5/Proliferative/Stem-A GEMS is associated with poorer survival outcomes. From our own study, Stem-A OC cells tend to display preferential chemosensitivity towards microtubule depolymerizing agents affecting the plus-end dynamics of microtubule such as vincristine and vinorelbine. Interestingly, Stem-A as well as non-Stem-A cells are equally sensitive to microtubule stabilizing agents such as paclitaxel. The biology of this C5/Proliferative/Stem-A-subtyped OC is still elusive and requires in-depth study. Here, we demonstrate that a Wnt receptor Frizzled-7 (FZD7) is crucial for the aggressiveness of the C5/Proliferative/Stem-A GEMS. Silencing FZD7 in the Stem-A-subtyped OC induces decrease in cell proliferation and cell cycle arrest. Silencing FZD7 also induced compaction of OC cell colony and strengthening of actin cytoskeleton at cell-cell junctions. Stable FZD7 knockdown clones further demonstrate significant decrease in anoikis resistance, spheroid forming ability, and tumorigenesis in xenografts. We further show that these functional changes acts via the Wnt-planar cell polarity (PCP) pathway downstream of FZD7. A subset of PCP pathway genes is also enriched in Stem-A tumors. Transient silencing of three downstream PCP pathway genes, CELSR3, PRICKLE4, PTK7, gave rise to similar functional phenotypes as silencing FZD7. These FZD7-PCP silenced Stem-A OC cells also demonstrate enhanced sensitivity to the microtubule depolymerizing agent vinorelbine. We conclude that the FZD7-PCP pathway drives the aggressiveness of the C5/Proliferative/Stem-A-subtyped OC and can be potentially utilized as the marker to identify the Stem-A subgroup. Molecularly stratifying OC patients and targeting C5/Proliferative/Stem-A subtype with therapeutics against FZD7-PCP pathway would be a novel strategy for OC. Citation Format: Mohammad Asad, Meng Kang Wong, Tuan Zea Tan, David Virshup, Jean Paul Thiery, Ruby Yun-Ju Huang. Frizzled-7 (FZD7)-mediated non-canonical Wnt-Planar Cell Polarity (PCP) signalling pathway as a novel molecular driver for the C5/Proliferative/Stem-A molecular subtype of ovarian cancer. [abstract]. In: Proceedings of the AACR Special Conference on Advances in Ovarian Cancer Research: Exploiting Vulnerabilities; Oct 17-20, 2015; Orlando, FL. Philadelphia (PA): AACR; Clin Cancer Res 2016;22(2 Suppl):Abstract nr A30.

Abstract P6-05-27: p53, c-Myc and EGFR protein interactions confer worse prognosis in patients with triple negative breast cancer (TNBC)

Abstract Background - aim: TNBC is a heterogeneous disease comprising different molecular subtypes that are mostly defined by gene expression profiling and are related to patient outcome. Herein, we investigated the prognostic significance of molecular subtype-related, surrogate protein markers. Methods: Immunohistochemistry was applied on tissue microarrays containing a series of 330 centrally assessed TNBC from early high-risk breast cancer patients treated with anthracyclines and/or taxanes. The following markers were examined (in parentheses: cut-offs for low/high and negative/positive): Ki67 (14%); p53 (10%); c-Myc (10%); P-cadherin (10%); E-cadherin (10%); Claudin-7 (H-score median: 105); CK5 (1%); EGFR (1%); androgen receptor (AR [1%]). Results: The majority of tumors (269/327, 81.5%) were grade-III ductal carcinomas of no special type. Tumors were frequently positive for Ki67 (239/314, 76.1%), E-cadherin (193/271, 71.2%), P-cadherin (249/302, 82.5%) and expressed markers of the basal phenotype (CK5+ and/or EGFR+, 268/316, 84.8%). Grade-III, Ki67-high carcinomas and tumours positive for E- and P-cadherin were more prevalent among those of basal phenotype (Fisher's exact p&amp;lt;0.001). Tumors expressing low levels of Claudin-7 were infrequently positive for AR and EGFR proteins (p = 0.015 and p = 0.003, respectively). AR positivity was more frequent among CK5 negative, grade I-II, and Ki67-low tumors (p = 0.021, p = 0.05 and p = 0.011 respectively). When examined individually, none of these markers was related to patient outcome. An interaction was noticed between p53 and c-Myc immunopositivity (Wald's p = 0.028 for disease-free [DFS] and p = 0.005 for overall survival [OS]). Among patients with c-Myc negative tumors, patients with p53 positive tumors (n = 63) had shorter median DFS (46.8 months) and OS (56 months) (HR 1.9; 95%CI 1.0-3.9; p = 0.049 and HR 2.28; 95%CI 1.0-4.8; p = 0.031, respectively) as compared to those with p53 negative tumors (n = 56; median DFS 69 months, OS 70 months). Similarly, in the absence of p53, c-Myc expression correlated with shorter median OS (44.5 months) (HR 2.1; 95%CI 1.0-4.5; p = 0.038) but showed only a trend for shorter DFS as compared to c-Myc negative tumors. p53 protein status was a discriminating factor for EGFR negative tumors (Wald's p = 0.052), whereby p53 positive tumors (n = 54) were associated with reduced DFS as compared to p53 negative tumors (n = 68; median DFS: 47 vs. 68.8 months; HR 2.1; 95%CI 1.1-4.0; p = 0.025). Accordingly, EGFR immunopositivity conferred a trend for shorter DFS within p53 negative cases. Conclusions: In the current study, it was not possible to assign prognostic significance to individual proteins that have been introduced as surrogate markers for gene expression-based molecular subtypes in TNBC. By contrast, significant interactions involving the status of p53 and c-Myc or EGFR were observed. It seems that aberrant p53 adversely influences tumor behaviour in the absence of c-Myc and EGFR, while the opposite is also effective but to a lesser extent. These findings are hypothesis generating and need to be pursued in sufficiently powered studies for validating the apparently mutually exclusive adverse effects of p53, c-Myc and EGFR on tumor behaviour. Citation Information: Cancer Res 2013;73(24 Suppl): Abstract nr P6-05-27.

Predictive biomarkers in adult gliomas

This review summarizes recent studies on the predictive value of molecular markers in adult gliomas, including 1p/19q codeletion, MGMT methylation, IDH mutation and markers identified using omics and next-generation sequencing studies. The long-term results of the Radiation Therapy Oncology Group and European Organization for Research and Treatment of Cancer trials in anaplastic oligodendroglial glioma have shown that the 1p/19q codeletion predicts an overall survival benefit from early PCV (procarbazine CCNU vincristine) chemotherapy. This benefit can also be predicted using gene expression-based molecular subtypes of gliomas while the predictive value of the IDH mutation in this context requires further study. In elderly patients with glioblastoma, the analysis of MGMT methylation status in two phase III trials suggests that this alteration may guide treatment decisions; however, this finding still needs confirmation in prospective studies. Omics and next-generation sequencing studies have identified additional potential predictive markers. In particular, IDH mutations, BRAF V600E mutations and FGFR gene fusions might predict efficacy of therapies targeted against these alterations. Currently, the 1p/19q codeletion is the only well established predictive marker with clinical utility. However, it is likely that other molecular markers such as MGMT methylation, IDH mutation and those identified using omics and next-generation sequencing studies will further guide treatment decisions in adult gliomas.

Abstract 3347: A proneural signature profile predicts response to Notch inhibition in glioma stem cells

Abstract The Cancer Genome Atlas Network described genomic abnormalities and gene expression-based molecular subtypes of GBM that showed a strong relationship between subtypes, genomic alterations and different neural lineages. Future studies are required to elucidate the intricate relationship between tumor subtypes and treatment response. We have thus embarked on a comprehensive effort to detecting expression signatures that are associated with response to the therapy and these signatures may allow prospective selection of patients with high likelihood of responding to therapy. Notch signaling pathway is an evolutionarily conserved pathway that plays an important role in multiple cellular and developmental processes including cell fate decision, differentiation, proliferation, survival, angiogenesis and migration. Recent studies indicate that the Notch signaling pathway regulates normal stem cells in the brain, and glioma stem Cells (GSCs) with high Notch activity. We investigated the effects of Notch pathway inhibition on GSCs growth using commercially available inhibitors. Drug cytotoxicity test on 16 GSCs show differential growth response to Notch inhibitors stratifying GSCs into two groups: responders (6 cell lines) vs non-responders (10 cell lines). Gene expression clustering identified a responder gene signature enriched in 1: proneural genes such as Olig2, Sox-9, NKX2-2, and 2: Notch signaling component such as Notch-1, Notch-3, Hes-3 and Hes-5. These signature were validated by western blot analysis. Treatment with Notch inhibitors reduced neurosphere formation in vitro accompanied with attenuated Notch intracellular domain (NICD), Hes-1, Hes-3, and Hes-5. In addition, the expression of nestin-the stem cell marker was reduced and an increased expression of lineage differentiation markers TuJ1 and GFAP was observed following Notch inhibition. In conclusion, we have identified a responder signature for a group of glioma stem cells that can be targeted by Notch inhibitors and this may allow the selection of patients with high likelihood of responding to this therapy. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 3347. doi:1538-7445.AM2012-3347