Tyler Moss

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

Metabolic shifts toward glutamine regulate tumor growth, invasion and bioenergetics in ovarian cancer

Glutamine can play a critical role in cellular growth in multiple cancers. Glutamine‐addicted cancer cells are dependent on glutamine for viability, and their metabolism is reprogrammed for glutamine utilization through the tricarboxylic acid (TCA) cycle. Here, we have uncovered a missing link between cancer invasiveness and glutamine dependence. Using isotope tracer and bioenergetic analysis, we found that low‐invasive ovarian cancer (OVCA) cells are glutamine independent, whereas high‐invasive OVCA cells are markedly glutamine dependent. Consistent with our findings, OVCA patients’ microarray data suggest that glutaminolysis correlates with poor survival. Notably, the ratio of gene expression associated with glutamine anabolism versus catabolism has emerged as a novel biomarker for patient prognosis. Significantly, we found that glutamine regulates the activation of STAT3, a mediator of signaling pathways which regulates cancer hallmarks in invasive OVCA cells. Our findings suggest that a combined approach of targeting high‐invasive OVCA cells by blocking glutamines entry into the TCA cycle, along with targeting low‐invasive OVCA cells by inhibiting glutamine synthesis and STAT3 may lead to potential therapeutic approaches for treating OVCAs.

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.

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.

Comprehensive Genomic Characterization of Upper Tract Urothelial Carcinoma

BACKGROUND Upper urinary tract urothelial cancer (UTUC) may have unique etiologic and genomic factors compared to bladder cancer. OBJECTIVE To characterize the genomic landscape of UTUC and provide insights into its biology using comprehensive integrated genomic analyses. DESIGN, SETTING, AND PARTICIPANTS We collected 31 untreated snap-frozen UTUC samples from two institutions and carried out whole-exome sequencing (WES) of DNA, RNA sequencing (RNAseq), and protein analysis. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS Adjusting for batch effects, consensus mutation calls from independent pipelines identified DNA mutations, gene expression clusters using unsupervised consensus hierarchical clustering (UCHC), and protein expression levels that were correlated with relevant clinical variables, The Cancer Genome Atlas, and other published data. RESULTS AND LIMITATIONS WES identified mutations in FGFR3 (74.1%; 92% low-grade, 60% high-grade), KMT2D (44.4%), PIK3CA (25.9%), and TP53 (22.2%). APOBEC and CpG were the most common mutational signatures. UCHC of RNAseq data segregated samples into four molecular subtypes with the following characteristics. Cluster 1: no PIK3CA mutations, nonsmokers, high-grade <pT2 tumors, high recurrences. Cluster 2: 100% FGFR3 mutations, low-grade tumors, tobacco use, noninvasive disease, no bladder recurrences. Cluster 3: 100% FGFR3 mutations, 71% PIK3CA, no TP53 mutations, five bladder recurrences, tobacco use, tumors all <pT2. Cluster 4: KMT2D (62.5%), FGFR3 (50%), TP53 (50%) mutations, no PIK3CA mutations, high-grade pT2+ disease, tobacco use, carcinoma in situ, shorter survival. We identified a novel SH3KBP1-CNTNAP5 fusion. CONCLUSIONS Mutations in UTUC occur at differing frequencies from bladder cancer, with four unique molecular and clinical subtypes. A novel SH3KBP1 fusion regulates RTK signaling. Further studies are needed to validate the described subtypes, explore their responses to therapy, and better define the novel fusion mutation. PATIENT SUMMARY We conducted a comprehensive study of the genetics of upper urinary tract urothelial cancer by evaluating DNA, RNA and protein expression in 31 tumors. We identified four molecular subtypes with distinct behaviors. Future studies will determine if these subtypes appear to have different responses to treatments.

Copy Number Gain of hsa-miR-569 at 3q26.2 Leads to Loss of TP53INP1 and Aggressiveness of Epithelial Cancers

Small noncoding miRNAs represent underexplored targets of genomic aberrations and emerging therapeutic targets. The 3q26.2 amplicon is among the most frequent genomic aberrations in multiple cancer lineages including ovarian and breast cancers. We demonstrate that hsa-miR-569 (hereafter designated as miR569), which is overexpressed in a subset of ovarian and breast cancers, at least in part due to the 3q26.2 amplicon, alters cell survival and proliferation. Downregulation of TP53INP1 expression by miR569 is required for the effects of miR569 on survival and proliferation. Targeting miR569 sensitizes ovarian and breast cancer cells overexpressing miR569 to cisplatin by increasing cell death both in vitro and in vivo. Thus targeting miR569 could potentially benefit patients with the 3q26.2 amplicon and subsequent miR569 elevation.

The ZNF304-integrin axis protects against anoikis in cancer

Ovarian cancer (OC) is a highly metastatic disease, but no effective strategies to target this process are currently available. Here, an integrative computational analysis of the Cancer Genome Atlas OC data set and experimental validation identifies a zinc finger transcription factor ZNF304 associated with OC metastasis. High tumoral ZNF304 expression is associated with poor overall survival in OC patients. Through reverse phase protein array analysis, we demonstrate that ZNF304 promotes multiple proto-oncogenic pathways important for cell survival, migration and invasion. ZNF304 transcriptionally regulates β1 integrin, which subsequently regulates Src/focal adhesion kinase and paxillin and prevents anoikis. In vivo delivery of ZNF304 siRNA by a dual assembly nanoparticle leads to sustained gene silencing for 14 days, increased anoikis and reduced tumour growth in orthotopic mouse models of OC. Taken together, ZNF304 is a transcriptional regulator of β1 integrin, promotes cancer cell survival and protects against anoikis in OC.

Regulation of the T-box transcription factor Tbx3 by the tumour suppressor microRNA-206 in breast cancer

Background:The Tbx3 transcription factor is over-expressed in breast cancer, where it has been implicated in proliferation, migration and regulation of the cancer stem cell population. The mechanisms that regulate Tbx3 expression in cancer have not been fully explored. In this study, we demonstrate that Tbx3 is repressed by the tumour suppressor miR-206 in breast cancer cells.Methods:Bioinformatics prediction programmes and luciferase reporter assays were used to demonstrate that miR-206 negatively regulates Tbx3. We examined the impact of miR-206 on Tbx3 expression in breast cancer cells using miR-206 mimic and inhibitor. Gene/protein expression was examined by quantitative reverse-transcription–PCR and immunoblotting. The effects of miR-206 and Tbx3 on apoptosis, proliferation, invasion and cancer stem cell population was investigated by cell-death detection, colony formation, 3D-Matrigel and tumorsphere assays.Results:In this study, we examined the regulation of Tbx3 by miR-206. We demonstrate that Tbx3 is directly repressed by miR-206, and that this repression of Tbx3 is necessary for miR-206 to inhibit breast tumour cell proliferation and invasion, and decrease the cancer stem cell population. Moreover, Tbx3 and miR-206 expression are inversely correlated in human breast cancer. Kaplan–Meier analysis indicates that patients exhibiting a combination of high Tbx3 and low miR-206 expression have a lower probability of survival when compared with patients with low Tbx3 and high miR-206 expression. These studies uncover a novel mechanism of Tbx3 regulation and identify a new target of the tumour suppressor miR-206.Conclusions:The present study identified Tbx3 as a novel target of tumour suppressor miR-206 and characterised the miR-206/Tbx3 signalling pathway, which is involved in proliferation, invasion and maintenance of the cancer stem cell population in breast cancer cells. Our results suggest that restoration of miR-206 in Tbx3-positive breast cancer could be exploited for therapeutic benefit.

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.