Inferring Pathway Activity toward Precise Disease Classification

The advent of microarray technology has made it possible to classify disease states based on gene expression profiles of patients. Typically, marker genes are selected by measuring the power of their expression profiles to discriminate among patients of different disease states. However, expression-based classification can be challenging in complex diseases due to factors such as cellular heterogeneity within a tissue sample and genetic heterogeneity across patients. A promising technique for coping with these challenges is to incorporate pathway information into the disease classification procedure in order to classify disease based on the activity of entire signaling pathways or protein complexes rather than on the expression levels of individual genes or proteins. We propose a new classification method based on pathway activities inferred for each patient. For each pathway, an activity level is summarized from the gene expression levels of its condition-responsive genes (CORGs), defined as the subset of genes in the pathway whose combined expression delivers optimal discriminative power for the disease phenotype. We show that classifiers using pathway activity achieve better performance than classifiers based on individual gene expression, for both simple and complex case-control studies including differentiation of perturbed from non-perturbed cells and subtyping of several different kinds of cancer. Moreover, the new method outperforms several previous approaches that use a static (i.e., non-conditional) definition of pathways. Within a pathway, the identified CORGs may facilitate the development of better diagnostic markers and the discovery of core alterations in human disease

The Genomic Analysis of Lactic Acidosis and Acidosis Response in Human Cancers

The tumor microenvironment has a significant impact on tumor development. Two important determinants in this environment are hypoxia and lactic acidosis. Although lactic acidosis has long been recognized as an important factor in cancer, relatively little is known about how cells respond to lactic acidosis and how that response relates to cancer phenotypes. We develop genome-scale gene expression studies to dissect transcriptional responses of primary human mammary epithelial cells to lactic acidosis and hypoxia in vitro and to explore how they are linked to clinical tumor phenotypes in vivo. The resulting experimental signatures of responses to lactic acidosis and hypoxia are evaluated in a heterogeneous set of breast cancer datasets. A strong lactic acidosis response signature identifies a subgroup of low-risk breast cancer patients having distinct metabolic profiles suggestive of a preference for aerobic respiration. The association of lactic acidosis response with good survival outcomes may relate to the role of lactic acidosis in directing energy generation toward aerobic respiration and utilization of other energy sources via inhibition of glycolysis. This “inhibition of glycolysis” phenotype in tumors is likely caused by the repression of glycolysis gene expression and Akt inhibition. Our study presents a genomic evaluation of the prognostic information of a lactic acidosis response independent of the hypoxic response. Our results identify causal roles of lactic acidosis in metabolic reprogramming, and the direct functional consequence of lactic acidosis pathway activity on cellular responses and tumor development. The study also demonstrates the utility of genomic analysis that maps expression-based findings from in vitro experiments to human samples to assess links to in vivo clinical phenotypes

Latent Factor Analysis to Discover Pathway-Associated Putative Segmental Aneuploidies in Human Cancers

Tumor microenvironmental stresses, such as hypoxia and lactic acidosis, play important roles in tumor progression. Although gene signatures reflecting the influence of these stresses are powerful approaches to link expression with phenotypes, they do not fully reflect the complexity of human cancers. Here, we describe the use of latent factor models to further dissect the stress gene signatures in a breast cancer expression dataset. The genes in these latent factors are coordinately expressed in tumors and depict distinct, interacting components of the biological processes. The genes in several latent factors are highly enriched in chromosomal locations. When these factors are analyzed in independent datasets with gene expression and array CGH data, the expression values of these factors are highly correlated with copy number alterations (CNAs) of the corresponding BAC clones in both the cell lines and tumors. Therefore, variation in the expression of these pathway-associated factors is at least partially caused by variation in gene dosage and CNAs among breast cancers. We have also found the expression of two latent factors without any chromosomal enrichment is highly associated with 12q CNA, likely an instance of “trans”-variations in which CNA leads to the variations in gene expression outside of the CNA region. In addition, we have found that factor 26 (1q CNA) is negatively correlated with HIF-1α protein and hypoxia pathways in breast tumors and cell lines. This agrees with, and for the first time links, known good prognosis associated with both a low hypoxia signature and the presence of CNA in this region. Taken together, these results suggest the possibility that tumor segmental aneuploidy makes significant contributions to variation in the lactic acidosis/hypoxia gene signatures in human cancers and demonstrate that latent factor analysis is a powerful means to uncover such a linkage

Lactic Acidosis Triggers Starvation Response with Paradoxical Induction of TXNIP through MondoA

Although lactic acidosis is a prominent feature of solid tumors, we still have limited understanding of the mechanisms by which lactic acidosis influences metabolic phenotypes of cancer cells. We compared global transcriptional responses of breast cancer cells in response to three distinct tumor microenvironmental stresses: lactic acidosis, glucose deprivation, and hypoxia. We found that lactic acidosis and glucose deprivation trigger highly similar transcriptional responses, each inducing features of starvation response. In contrast to their comparable effects on gene expression, lactic acidosis and glucose deprivation have opposing effects on glucose uptake. This divergence of metabolic responses in the context of highly similar transcriptional responses allows the identification of a small subset of genes that are regulated in opposite directions by these two conditions. Among these selected genes, TXNIP and its paralogue ARRDC4 are both induced under lactic acidosis and repressed with glucose deprivation. This induction of TXNIP under lactic acidosis is caused by the activation of the glucose-sensing helix-loop-helix transcriptional complex MondoA:Mlx, which is usually triggered upon glucose exposure. Therefore, the upregulation of TXNIP significantly contributes to inhibition of tumor glycolytic phenotypes under lactic acidosis. Expression levels of TXNIP and ARRDC4 in human cancers are also highly correlated with predicted lactic acidosis pathway activities and associated with favorable clinical outcomes. Lactic acidosis triggers features of starvation response while activating the glucose-sensing MondoA-TXNIP pathways and contributing to the “anti-Warburg” metabolic effects and anti-tumor properties of cancer cells. These results stem from integrative analysis of transcriptome and metabolic response data under various tumor microenvironmental stresses and open new paths to explore how these stresses influence phenotypic and metabolic adaptations in human cancers

Widefield Optical Imaging of Changes in Uptake of Glucose and Tissue Extracellular pH in Head and Neck Cancer

The overall objective of this study is to develop an optical imaging approach to simultaneously measure altered cell metabolism and changes in tissue extracellular pH with the progression of cancer using clinically isolated biopsies. In this study, 19 pairs of clinically normal and abnormal biopsies were obtained from consenting head and neck cancer patients at UCDMC. Fluorescence intensity of tissue biopsies before and after topical delivery of 2-NBDG (2-[N-(7-nitrobenz-2-oxa-1,3-diazol-4-yl)amino]-2-deoxy-D-glucose) and Alexa 647-pHLIP (pH (low) insertion peptide) was measured non-invasively by widefield imaging, and correlated with pathological diagnosis. The results of widefield imaging of clinical biopsies demonstrated that 2-NBDG and pHLIP peptide can accurately distinguish the pathologically normal and abnormal biopsies. The results also demonstrated the potential of this approach to detect sub-epithelial lesions. Topical application of the contrast agents generated a significant increase in fluorescence contrast (3–4 fold) in the cancer biopsies as compared to the normal biopsies, irrespective of the patient and location of the biopsy within a head and neck cavity. This unpaired comparison across all the cancer patients in this study highlights the specificity of the imaging approach. Furthermore, the results of this study indicated that changes in intracellular glucose metabolism and cancer acidosis are initiated in the early stages of cancer and these changes are correlated with the progression of the disease. In conclusion, this novel optical molecular imaging approach to measure multiple biomarkers in cancer has a significant potential to be a useful tool for improving early detection and prognostic evaluation of oral neoplasia

Germline BAP1 mutations induce a Warburg effect

Carriers of heterozygous germline BAP1 mutations (BAP1(+/-)) develop cancer. We studied plasma from 16 (BAP1(+/-)) individuals from 2 families carrying different germline BAP1 mutations and 30 BAP1 wild-type (BAP1(WT)) controls from these same families. Plasma samples were analyzed by liquid chromatography time-of-flight mass spectrometry (LC-TOF-MS), ultra-performance liquid chromatography triple quadrupole mass spectrometry (UPLC-TQ-MS), and gas chromatography time-of-flight mass spectrometry (GC-TOF-MS). We found a clear separation in the metabolic profile between BAP1(WT) and (BAP1(+/-)) individuals. We confirmed the specificity of the data in vitro using 12 cell cultures of primary fibroblasts we derived from skin punch biopsies from 12/46 of these same individuals, 6 (BAP1(+/-)) carriers and 6 controls from both families. (BAP1(+/-)) fibroblasts displayed increased aerobic glycolysis and lactate secretion, and reduced mitochondrial respiration and ATP production compared with BAP1(WT). siRNA-mediated downregulation of BAP1 in primary BAP1(WT) fibroblasts and in primary human mesothelial cells, led to the same reduced mitochondrial respiration and increased aerobic glycolysis as we detected in primary fibroblasts from carriers of (BAP1(+/-)) mutations. The plasma and cell culture results were highly reproducible and were specifically and only linked to BAP1 status and not to gender, age or family, or cell type, and required an intact BAP1 catalytic activity. Accordingly, we were able to build a metabolomic model capable of predicting BAP1 status with 100% accuracy using data from human plasma. Our data provide the first experimental evidence supporting the hypothesis that aerobic glycolysis, also known as the 'Warburg effect', does not necessarily occur as an adaptive process that is consequence of carcinogenesis, but rather that it may also predate malignancy by many years and facilitate carcinogenesis