Elena G. Seviour

A pan-cancer proteomic perspective on The Cancer Genome Atlas

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.

Tumor microenvironment derived exosomes pleiotropically modulate cancer cell metabolism

Cancer-associated fibroblasts (CAFs) are a major cellular component of tumor microenvironment in most solid cancers. Altered cellular metabolism is a hallmark of cancer, and much of the published literature has focused on neoplastic cell-autonomous processes for these adaptations. We demonstrate that exosomes secreted by patient-derived CAFs can strikingly reprogram the metabolic machinery following their uptake by cancer cells. We find that CAF-derived exosomes (CDEs) inhibit mitochondrial oxidative phosphorylation, thereby increasing glycolysis and glutamine-dependent reductive carboxylation in cancer cells. Through 13C-labeled isotope labeling experiments we elucidate that exosomes supply amino acids to nutrient-deprived cancer cells in a mechanism similar to macropinocytosis, albeit without the previously described dependence on oncogenic-Kras signaling. Using intra-exosomal metabolomics, we provide compelling evidence that CDEs contain intact metabolites, including amino acids, lipids, and TCA-cycle intermediates that are avidly utilized by cancer cells for central carbon metabolism and promoting tumor growth under nutrient deprivation or nutrient stressed conditions. DOI: http://dx.doi.org/10.7554/eLife.10250.001

The glucose-deprivation network counteracts lapatinib-induced toxicity in resistant ErbB2-positive breast cancer cells

Dynamic interactions between intracellular networks regulate cellular homeostasis and responses to perturbations. Targeted therapy is aimed at perturbing oncogene addiction pathways in cancer, however, development of acquired resistance to these drugs is a significant clinical problem. A network‐based computational analysis of global gene expression data from matched sensitive and acquired drug‐resistant cells to lapatinib, an EGFR/ErbB2 inhibitor, revealed an increased expression of the glucose deprivation response network, including glucagon signaling, glucose uptake, gluconeogenesis and unfolded protein response in the resistant cells. Importantly, the glucose deprivation response markers correlated significantly with high clinical relapse rates in ErbB2‐positive breast cancer patients. Further, forcing drug‐sensitive cells into glucose deprivation rendered them more resistant to lapatinib. Using a chemical genomics bioinformatics mining of the CMAP database, we identified drugs that specifically target the glucose deprivation response networks to overcome the resistant phenotype and reduced survival of resistant cells. This study implicates the chronic activation of cellular compensatory networks in response to targeted therapy and suggests novel combinations targeting signaling and metabolic networks in tumors with acquired resistance.

Cupid: simultaneous reconstruction of microRNA-target and ceRNA networks

We introduce a method for simultaneous prediction of microRNA-target interactions and their mediated competitive endogenous RNA (ceRNA) interactions. Using high-throughput validation assays in breast cancer cell lines, we show that our integrative approach significantly improves on microRNA-target prediction accuracy as assessed by both mRNA and protein level measurements. Our biochemical assays support nearly 500 microRNA-target interactions with evidence for regulation in breast cancer tumors. Moreover, these assays constitute the most extensive validation platform for computationally inferred networks of microRNA-target interactions in breast cancer tumors, providing a useful benchmark to ascertain future improvements.

A miR-192-EGR1-HOXB9 regulatory network controls the angiogenic switch in cancer

A deeper mechanistic understanding of tumour angiogenesis regulation is needed to improve current anti-angiogenic therapies. Here we present evidence from systems-based miRNA analyses of large-scale patient data sets along with in vitro and in vivo experiments that miR-192 is a key regulator of angiogenesis. The potent anti-angiogenic effect of miR-192 stems from its ability to globally downregulate angiogenic pathways in cancer cells through regulation of EGR1 and HOXB9. Low miR-192 expression in human tumours is predictive of poor clinical outcome in several cancer types. Using 1,2-dioleoyl-sn-glycero-3-phosphatidylcholine (DOPC) nanoliposomes, we show that miR-192 delivery leads to inhibition of tumour angiogenesis in multiple ovarian and renal tumour models, resulting in tumour regression and growth inhibition. This anti-angiogenic and anti-tumour effect is more robust than that observed with an anti-VEGF antibody. Collectively, these data identify miR-192 as a central node in tumour angiogenesis and support the use of miR-192 in an anti-angiogenesis therapy.

Functional proteomics identifies miRNAs to target a p27/Myc/phospho-Rb signature in breast and ovarian cancer

The myc oncogene is overexpressed in almost half of all breast and ovarian cancers, but attempts at therapeutic interventions against myc have proven to be challenging. Myc regulates multiple biological processes, including the cell cycle, and as such is associated with cell proliferation and tumor progression. We identified a protein signature of high myc, low p27 and high phospho-Rb significantly correlated with poor patient survival in breast and ovarian cancers. Screening of a miRNA library by functional proteomics in multiple cell lines and integration of data from patient tumors revealed a panel of five microRNAs (miRNAs) (miR-124, miR-365, miR-34b*, miR-18a and miR-506) as potential tumor suppressors capable of reversing the p27/myc/phospho-Rb protein signature. Mechanistic studies revealed an RNA-activation function of miR-124 resulting in direct induction of p27 protein levels by binding to and inducing transcription on the p27 promoter region leading to a subsequent G1 arrest. Additionally, in vivo studies utilizing a xenograft model demonstrated that nanoparticle-mediated delivery of miR-124 could reduce tumor growth and sensitize cells to etoposide, suggesting a clinical application of miRNAs as therapeutics to target the functional effect of myc on tumor growth.

Next-generation sequencing identifies high frequency of mutations in potentially clinically actionable genes in sebaceous carcinoma

Sebaceous carcinoma (SC) is a rare but aggressive malignancy with frequent recurrence and metastases. Surgery is the mainstay of therapy, but effective systemic therapies are lacking because the molecular alterations driving SC remain poorly understood. To identify these, we performed whole‐exome next‐generation sequencing of 409 cancer‐associated genes on 27 SCs (18 primary/locally recurrent ocular, 5 paired metastatic ocular, and 4 primary extraocular) from 20 patients. In ocular SC, we identified 139 non‐synonymous somatic mutations (median/lesion 3; range 0–23). Twenty‐five of 139 mutations (18%) occurred in potentially clinically actionable genes in 6 of 16 patients. The most common mutations were mutations in TP53 (n = 9), RB1 (n = 6), PIK3CA (n = 2), PTEN (n = 2), ERBB2 (n = 2), and NF1 (n = 2). TP53 and RB1 mutations were restricted to ocular SC and correlated with aberrant TP53 and RB protein expression. Systematic pathway analyses demonstrated convergence of these mutations to activation of the PI3K signalling cascade, and PI3K pathway activation was confirmed in tumours with PTEN and/or PIK3CA mutations. Considerable inter‐tumoural heterogeneity was observed between paired primary and metastatic ocular SCs. In primary extraocular SC, we identified 77 non‐synonymous somatic mutations (median/lesion 22.5; range 3–29). This overall higher mutational load was attributed to a microsatellite instability phenotype in three of four patients and somatically acquired mutations in mismatch repair genes in two of four patients. Eighteen of 77 mutations (23%) were in potentially clinically actionable genes in three of four patients, including BTK, FGFR2, PDGFRB, HRAS, and NF1 mutations. Identification of potentially clinically actionable mutations in 9 of 20 SC patients (45%) underscores the importance of next‐generation sequencing to expand the spectrum of genotype‐matched targeted therapies. Frequent activation of PI3K signalling pathways provides a strong rationale for application of mTOR inhibitors in the management of this disease. Copyright

Targeting KRas-dependent tumour growth, circulating tumour cells and metastasis in vivo by clinically significant MIR-193a-3p

KRas is mutated in a significant number of human cancers and so there is an urgent therapeutic need to target KRas signalling. To target KRas in lung cancers we used a systems approach of integrating a genome-wide miRNA screen with patient-derived phospho-proteomic signatures of the KRas downstream pathway, and identified miR-193a-3p, which directly targets KRas. Unique aspects of miR-193a-3p biology include two functionally independent target sites in the KRas 3′UTR and clinically significant correlation between miR-193a-3p and KRas expression in patients. Rescue experiments with mutated KRas 3’UTR showed very significantly that the anti-tumour effect of miR-193a-3p is via specific direct targeting of KRas and not due to other targets. Ex vivo and in vivo studies utilizing nanoliposome packaged miR-193a-3p demonstrated significant inhibition of tumour growth, circulating tumour cell viability and decreased metastasis. These studies show the broader applicability of using miR-193a-3p as a therapeutic agent to target KRas-mutant cancer.

Robust Selection Algorithm (RSA) for Multi-Omic Biomarker Discovery; Integration with Functional Network Analysis to Identify miRNA Regulated Pathways in Multiple Cancers.

MicroRNAs (miRNAs) play a crucial role in the maintenance of cellular homeostasis by regulating the expression of their target genes. As such, the dysregulation of miRNA expression has been frequently linked to cancer. With rapidly accumulating molecular data linked to patient outcome, the need for identification of robust multi-omic molecular markers is critical in order to provide clinical impact. While previous bioinformatic tools have been developed to identify potential biomarkers in cancer, these methods do not allow for rapid classification of oncogenes versus tumor suppressors taking into account robust differential expression, cutoffs, p-values and non-normality of the data. Here, we propose a methodology, Robust Selection Algorithm (RSA) that addresses these important problems in big data omics analysis. The robustness of the survival analysis is ensured by identification of optimal cutoff values of omics expression, strengthened by p-value computed through intensive random resampling taking into account any non-normality in the data and integration into multi-omic functional networks. Here we have analyzed pan-cancer miRNA patient data to identify functional pathways involved in cancer progression that are associated with selected miRNA identified by RSA. Our approach demonstrates the way in which existing survival analysis techniques can be integrated with a functional network analysis framework to efficiently identify promising biomarkers and novel therapeutic candidates across diseases.

Corrigendum: A pan-cancer proteomic perspective on The Cancer Genome Atlas

Nature Communications 5: Article number: 3887 (2014); Published 29 May 2014; Updated 28 Jan 2015 This Article contains an error in the Author contributions section that has resulted in incorrect credit for supervision of the network analysis. The correct Author contributions section is as follows: R.A.