Infiltrating stromal and immune cells form the major fraction of normal cells in tumour tissue and not only perturb the tumour signal in molecular studies but also have an important role in cancer biology. Here we describe ‘Estimation of STromal and Immune cells in MAlignant Tumours using Expression data’ (ESTIMATE)—a method that uses gene expression signatures to infer the fraction of stromal and immune cells in tumour samples. ESTIMATE scores correlate with DNA copy number-based tumour purity across samples from 11 different tumour types, profiled on Agilent, Affymetrix platforms or based on RNA sequencing and available through The Cancer Genome Atlas. The prediction accuracy is further corroborated using 3,809 transcriptional profiles available elsewhere in the public domain. The ESTIMATE method allows consideration of tumour-associated normal cells in genomic and transcriptomic studies. An R-library is available on https://sourceforge.net/projects/estimateproject/.

Protein levels and function are poorly predicted by genomic and transcriptomic analysis of patient tumors. Therefore, direct study of the functional proteome has the potential to provide a wealth of information that complements and extends genomic, epigenomic and transcriptomic analysis in The Cancer Genome Atlas (TCGA) projects. Here we use reverse-phase protein arrays to analyze 3,467 patient samples from 11 TCGA “Pan-Cancer” diseases, using 181 high-quality antibodies that target 128 total proteins and 53 post-translationally modified proteins. The resultant proteomic data is integrated with genomic and transcriptomic analyses of the same samples to identify commonalities, differences, emergent pathways and network biology within and across tumor lineages. In addition, tissue-specific signals are reduced computationally to enhance biomarker and target discovery spanning multiple tumor lineages. This integrative analysis, with an emphasis on pathways and potentially actionable proteins, provides a framework for determining the prognostic, predictive and therapeutic relevance of the functional proteome.

Summary The Drosophila Yorkie (Yki) protein and its mammalian homolog Yes-associated protein (YAP) are potent growth promoters and YAP overexpression is associated with multiple types of cancer [1,2]. Yki and YAP are transcriptional co-activators and function as downstream effectors of the Hippo tumor suppressor pathway [1–4]. The regulation of Yki and YAP by the Hippo signaling pathway has been extensively investigated, however, how they regulate gene expression is poorly understood. To identify additional regulators of Yki activity we performed a genome-wide RNAi screen in Drosophila S2 cells. In this screen, we identified the conserved protein Mask (Multiple ankyrin repeats single KH domain) as a novel promoter of Yki activity in vitro and validated this function in vivo in Drosophila. We found that Mask is required downstream of the Hippo pathway for Yki to induce target gene expression and that Mask forms complexes with Yki. The human Mask homolog MASK1 complexes with YAP and it is required for full activity of YAP and elevated MASK1 expression is associated with worsened outcomes for breast cancer patients. We conclude that Mask is a novel cofactor for Yki/YAP required for optimal Yki/YAP activity during development and oncogenesis.

Purpose The current study evaluated associative effects of breast cancer cells with the tumor microenvironment and its influence on tumor behavior. Experimental design Formalin-fixed paraffin embedded tissue and matched protein lysates were evaluated from two independent breast cancer patient data sets (TCGA and MD Anderson). Reverse-phase protein arrays (RPPA) were utilized to create a proteomics signature to define breast tumor subtypes. Expression patterns of cell lines and normal breast tissues were utilized to determine markers that were differentially expressed in stroma and cancer cells. Protein localization and stromal contents were evaluated for matched cases by imaging. Results A subtype of breast cancers designated “Reactive,” previously identified by RPPA that was not predicted by mRNA profiling, was extensively characterized. These tumors were primarily estrogen receptor (ER)-positive/human epidermal growth factor receptor (HER)2-negative, low-risk cancers as determined by enrichment of low-grade nuclei, lobular or tubular histopathology, and the luminal A subtype by PAM50. Reactive breast cancers contained high numbers of stromal cells and the highest extracellular matrix content typically without infiltration of immune cells. For ER-positive/HER2-negative cancers, the Reactive classification predicted favorable clinical outcomes in the TCGA cohort (HR = 0.36, P < 0.05). Conclusions A protein stromal signature in breast cancers is associated with a highly differentiated phenotype. The stromal compartment content and proteins are an extended phenotype not predicted by mRNA expression that could be utilized to sub-classify ER-positive/HER2-negative breast cancers.

The gold standard for determining the tumorigenic potential of human cancer cells is a xenotransplantation into immunodeficient mice. Higher tumorigenicity of cells is associated with earlier tumor onset. Here, we used xenotransplantation to assess the tumorigenic potential of human breast cancer cells following RNA interference-mediated inhibition of over 5000 genes. We identify 16 candidate tumor suppressors, one of which is the zinc-finger transcription factor SALL1. Analyzing this particular molecule in more detail, we show that inhibition of SALL1 correlates with reduced levels of CDH1, an important contributor to epithelial-tomesenchymal transition. Furthermore, SALL1 expression led to an increased migration and more than twice as many cells expressing a cancer stem cell signature. Also, SALL1 expression correlates with the survival of breast cancer patients. These findings cast new light on a gene that has previously been described to be relevant during embryogenesis, but not carcinogenesis.