Yue Xu

Robust enumeration of cell subsets from tissue expression profiles

We introduce CIBERSORT, a method for characterizing cell composition of complex tissues from their gene expression profiles. When applied to enumeration of hematopoietic subsets in RNA mixtures from fresh, frozen and fixed tissues, including solid tumors, CIBERSORT outperformed other methods with respect to noise, unknown mixture content and closely related cell types. CIBERSORT should enable large-scale analysis of RNA mixtures for cellular biomarkers and therapeutic targets (http://cibersort.stanford.edu/).

The prognostic landscape of genes and infiltrating immune cells across human cancers

Molecular profiles of tumors and tumor-associated cells hold great promise as biomarkers of clinical outcomes. However, existing data sets are fragmented and difficult to analyze systematically. Here we present a pan-cancer resource and meta-analysis of expression signatures from ∼18,000 human tumors with overall survival outcomes across 39 malignancies. By using this resource, we identified a forkhead box MI (FOXM1) regulatory network as a major predictor of adverse outcomes, and we found that expression of favorably prognostic genes, including KLRB1 (encoding CD161), largely reflect tumor-associated leukocytes. By applying CIBERSORT, a computational approach for inferring leukocyte representation in bulk tumor transcriptomes, we identified complex associations between 22 distinct leukocyte subsets and cancer survival. For example, tumor-associated neutrophil and plasma cell signatures emerged as significant but opposite predictors of survival for diverse solid tumors, including breast and lung adenocarcinomas. This resource and associated analytical tools (http://precog.stanford.edu) may help delineate prognostic genes and leukocyte subsets within and across cancers, shed light on the impact of tumor heterogeneity on cancer outcomes, and facilitate the discovery of biomarkers and therapeutic targets.

Non–Small Cell Lung Cancer: Identifying Prognostic Imaging Biomarkers by Leveraging Public Gene Expression Microarray Data—Methods and Preliminary Results

PURPOSE To identify prognostic imaging biomarkers in non-small cell lung cancer (NSCLC) by means of a radiogenomics strategy that integrates gene expression and medical images in patients for whom survival outcomes are not available by leveraging survival data in public gene expression data sets. MATERIALS AND METHODS A radiogenomics strategy for associating image features with clusters of coexpressed genes (metagenes) was defined. First, a radiogenomics correlation map is created for a pairwise association between image features and metagenes. Next, predictive models of metagenes are built in terms of image features by using sparse linear regression. Similarly, predictive models of image features are built in terms of metagenes. Finally, the prognostic significance of the predicted image features are evaluated in a public gene expression data set with survival outcomes. This radiogenomics strategy was applied to a cohort of 26 patients with NSCLC for whom gene expression and 180 image features from computed tomography (CT) and positron emission tomography (PET)/CT were available. RESULTS There were 243 statistically significant pairwise correlations between image features and metagenes of NSCLC. Metagenes were predicted in terms of image features with an accuracy of 59%-83%. One hundred fourteen of 180 CT image features and the PET standardized uptake value were predicted in terms of metagenes with an accuracy of 65%-86%. When the predicted image features were mapped to a public gene expression data set with survival outcomes, tumor size, edge shape, and sharpness ranked highest for prognostic significance. CONCLUSION This radiogenomics strategy for identifying imaging biomarkers may enable a more rapid evaluation of novel imaging modalities, thereby accelerating their translation to personalized medicine.

A Rare Population of CD24+ITGB4+Notchhi Cells Drives Tumor Propagation in NSCLC and Requires Notch3 for Self-Renewal

Sustained tumor progression has been attributed to a distinct population of tumor-propagating cells (TPCs). To identify TPCs relevant to lung cancer pathogenesis, we investigated functional heterogeneity in tumor cells isolated from Kras-driven mouse models of non-small-cell lung cancer (NSCLC). CD24(+)ITGB4(+)Notch(hi) cells are capable of propagating tumor growth in both a clonogenic and an orthotopic serial transplantation assay. While all four Notch receptors mark TPCs, Notch3 plays a nonredundant role in tumor cell propagation in two mouse models and in human NSCLC. The TPC population is enriched after chemotherapy, and the gene signature of mouse TPCs correlates with poor prognosis in human NSCLC. The role of Notch3 in tumor propagation may provide a therapeutic target for NSCLC.

A meta-analysis of lung cancer gene expression identifies PTK7 as a survival gene in lung adenocarcinoma

Lung cancer remains the most common cause of cancer-related death worldwide and it continues to lack effective treatment. The increasingly large and diverse public databases of lung cancer gene expression constitute a rich source of candidate oncogenic drivers and therapeutic targets. To define novel targets for lung adenocarcinoma, we conducted a large-scale meta-analysis of genes specifically overexpressed in adenocarcinoma. We identified an 11-gene signature that was overexpressed consistently in adenocarcinoma specimens relative to normal lung tissue. Six genes in this signature were specifically overexpressed in adenocarcinoma relative to other subtypes of non-small cell lung cancer (NSCLC). Among these genes was the little studied protein tyrosine kinase PTK7. Immunohistochemical analysis confirmed that PTK7 is highly expressed in primary adenocarcinoma patient samples. RNA interference-mediated attenuation of PTK7 decreased cell viability and increased apoptosis in a subset of adenocarcinoma cell lines. Further, loss of PTK7 activated the MKK7-JNK stress response pathway and impaired tumor growth in xenotransplantation assays. Our work defines PTK7 as a highly and specifically expressed gene in adenocarcinoma and a potential therapeutic target in this subset of NSCLC.

miR-1 Induces Growth Arrest and Apoptosis in Malignant Mesothelioma

BACKGROUND We investigated microRNA expression profiles of malignant pleural mesothelioma (MPM) specimens to identify novel microRNA that are potentially involved in the oncogenic transformation of human pleural cells. METHODS microRNA microarray transcriptional profiling studies of 25 MPM primary tumors were performed. We used normal pleural tissue from an unmatched patient cohort as normal comparators. To confirm microarray data, we used real-time quantitative polymerase chain reaction. Representative cell lines H513 and H2052 were used in functional analyses of miR-1. RESULTS In addition to several novel MPM-associated microRNAs, we observed that the expression level of miR-1 was significantly lower in tumors as compared with normal pleural specimens. Subsequently, pre-miR of miR-1 was introduced into MPM cell lines to overexpress this microRNA. Phenotypic changes of these altered cells were assayed. The cellular proliferation rate was significantly inhibited after overexpression of miR-1. Early and late apoptosis was increased markedly in miR-1-transfected cell lines. Taken together, these data suggested that overexpression of miR-1 induced apoptosis in these MPM cell lines, acting as a tumor suppressor. We confirmed our observations by assessing in the transduced MPM cells cell cycle-related, proapoptotic, and antiapoptotic genes, which all showed coordinated, significant changes characteristic of the apoptotic phenotype. CONCLUSIONS Further investigation and validation of our microRNA database of MPM may elucidate previously unrecognized molecular pathways and/or mechanisms by identifying novel microRNAs that are involved in malignant transformation. Our study has now found miR-1 to be one of these MPM-associated microRNAs, with potential pathogenic and therapeutic significance.

Liquid chromatography/mass spectrometry methods for measuring dipeptide abundance in non‐small‐cell lung cancer

RATIONALE Metabolomic profiling is a promising methodology of identifying candidate biomarkers for disease detection and monitoring. Although lung cancer is among the leading causes of cancer-related mortality worldwide, the lung tumor metabolome has not been fully characterized. METHODS We utilized a targeted metabolomic approach to analyze discrete groups of related metabolites. We adopted a dansyl [5-(dimethylamino)-1-naphthalene sulfonamide] derivatization with liquid chromatography/mass spectrometry (LC/MS) to analyze changes of metabolites from paired tumor and normal lung tissues. Identification of dansylated dipeptides was confirmed with synthetic standards. A systematic analysis of retention times was required to reliably identify isobaric dipeptides. We validated our findings in a separate sample cohort. RESULTS We produced a database of the LC retention times and MS/MS spectra of 361 dansyl dipeptides. Interpretation of the spectra is presented. Using this standard data, we identified a total of 279 dipeptides in lung tumor tissue. The abundance of 90 dipeptides was selectively increased in lung tumor tissue compared to normal tissue. In a second set of validation tissues, 12 dipeptides were selectively increased. CONCLUSIONS A systematic evaluation of certain metabolite classes in lung tumors may identify promising disease-specific metabolites. Our database of all possible dipeptides will facilitate ongoing translational applications of metabolomic profiling as it relates to lung cancer.

Overexpression of micro ribonucleic acid‐591 inhibits cell proliferation and invasion of malignant pleural mesothelioma cells

Malignant pleural mesothelioma (MPM) is an aggressive cancer refractory to current therapies. Reduced expression of micro ribonucleic acid (miR)‐591 in a range of cancer types has suggested it is a potent tumor suppressor, and overexpression has been shown to inhibit tumor cell growth. The role of miR‐591 in MPM is largely unknown.

Abstract LB-219: Higher levels of mast cells associate with favorable outcomes in non-small cell lung cancer and correlate with lower malignant cell proliferation

The tumor microenvironment (TME) involves complex interactions between malignant and stromal cell types. Much of our knowledge of cancer biology has been derived from studying molecular mechanisms underlying bulk tumors, with a focus on specific malignant pathways that have become dysregulated during tumorigenesis and tumor progression. Although studies have identified interactions between malignant and stromal cells within the TME, few have sought to comprehensively identify such relationships. Here, we performed RNA-seq on bulk and flow-sorted non-small cell primary human lung tumors enriching for malignant cells, endothelial cells, immune cells, and fibroblasts. We derived a map of cell-specific differential gene expression of prognostically associated secreted factors and cell surface markers, and computationally reconstructed pairwise cross-talk between cell types. We found significant novel associations between transcriptional profiles of malignant populations and specific stromal populations, focusing here on mast cells. We identified presence of infiltrating mast cells to be negatively correlated with malignant cell proliferation. Expression of TPSAB1 (Tryptase Alpha/Beta 1) is largely confined to mast cells, and its high expression in both adenocarcinoma and squamous cell carcinoma is favorably prognostic in both histologies across multiple datasets based on gene expression data. We validated the prognostic relevance of mast cells in NSCLC by immunohistochemical (IHC) staining of a lung tumor tissue microarray (TMA) for MCT (mast cell tryptase). Higher mast cell count was associated with better overall survival across all NSCLC, or when considering either adenocarcinoma or squamous cell carcinoma alone. When mast cell counts were quantified as “High”, “Intermediate”, “Low”, and “Negative” levels without reference to clinical outcomes, these were statistically significantly associated with survival. Negative-, low-, and intermediate-levels of mast cells all conferred worse prognosis than high mast-cell levels. Mast cell levels remained prognostic in multivariate analysis with independent clinical factors including age, stage, and gender. Finally, we directly evaluated the relationship of mast cell levels to tumor proliferation by staining the same samples for the proliferation marker KI67. The percentage of tumor cells staining positive for KI67 was lower in tumors with high vs low numbers of mast cells (p=0.048, Wilcox rank-sum test). In summary, we identified and validated a specific inverse relationship between levels of infiltrating mast cells and malignant cell proliferation. These results illustrate the utility of transcriptomic profiling of flow-sorted subpopulations from solid tumors in order to identify tumor-microenvironment interactions that may have prognostic and therapeutic relevance. Citation Format: Andrew J. Gentles, Angela Hui, Weiguo Feng, Ramesh V. Nair, Alice Yu, Majid Shafiq, Erna Forgo, Amanda Khuong, Yue Xu, Chuong D. Hoang, Robert B. West, Matt van de Rijn, Maximilian Diehn, Sylvia K. Plevritis. Higher levels of mast cells associate with favorable outcomes in non-small cell lung cancer and correlate with lower malignant cell proliferation [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr LB-219. doi:10.1158/1538-7445.AM2017-LB-219

Abstract 266: Notch3 is a marker of tumor-propagating cells in non-small cell lung cancer and is required for their self-renewal.

Proceedings: AACR 104th Annual Meeting 2013; Apr 6-10, 2013; Washington, DC We investigated tumor cell heterogeneity in mouse models of non-small cell lung cancer (NSCLC) that recapitulate key genetic events in this disease. In tumors driven by simultaneous expression of an oncogenic Kras allele and loss of the tumor suppressor Trp53, only a relatively rare subset of tumor cells is capable of propagating tumor growth in both a clonogenic in vitro assay and an in vivo orthotopic transplantation assay. The tumor-propagating cell (TPC) population was enriched by sorting for the combination of the cell surface markers CD24, ITGB4 and Notch(1-4). We demonstrate a critical and specific role for Notch3 signaling in the maintenance of TPCs in the KrasG12D; Trp53fl/fl mouse model. Knock-down of Notch3, but not Notch 1, 2 or 4, decreased self-renewal of TPCs in vitro. In addition, knock-down of Notch3 was critical for tumor propagation in vivo. The relevance of these studies to human NSCLC was confirmed by demonstrating a significant effect of Notch inhibition on the self-renewal of primary human lung adenocarcinoma cells in ex vivo cultures established directly from patients. These findings identify a novel subpopulation of tumor cells with distinct functional capabilities, underscoring the importance of interrogating heterogeneity in NSCLC. The unique role of Notch3 in tumor propagation may provide a novel therapeutic target for the treatment of non-small cell lung cancer.   Citation Format: Yanyan Zheng, Cecile de la Cruz, Leanne Sayles, Chris Alleyne-Chin, Yue Xu, Chuong D. Hoang, Joseph B. Shrager, Erica Jackson, Alejandro Sweet-Cordero. Notch3 is a marker of tumor-propagating cells in non-small cell lung cancer and is required for their self-renewal. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 266. doi:10.1158/1538-7445.AM2013-266