Aritro Nath

Elevated free fatty acid uptake via CD36 promotes epithelial-mesenchymal transition in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the second-leading cause of cancer-related death worldwide, and the factors influencing HCC progression are poorly understood. Here we reveal that HCC progression via induction of epithelial-mesenchymal transition (EMT) is closely associated with the expression of CD36/fatty acid translocase and elevated free fatty acid (FFA) levels. Although obesity is manifested as elevated FFA levels, the degree of EMT was not associated with the body mass index of the patients, highlighting the specific roles of CD36 and FFA uptake. Treatment of human liver cancer cell lines with FFAs exacerbated the EMT phenotype, whereas chemical inhibition of CD36 mitigated these effects. Furthermore, the Wnt and TGF-β signaling pathways were activated upon FFA treatment, potentially acting as upstream activators of the EMT program. These results provide the first direct evidence associating CD36 and elevated FFAs with HCC progression.

Genetic alterations in fatty acid transport and metabolism genes are associated with metastatic progression and poor prognosis of human cancers

Reprogramming of cellular metabolism is a hallmark feature of cancer cells. While a distinct set of processes drive metastasis when compared to tumorigenesis, it is yet unclear if genetic alterations in metabolic pathways are associated with metastatic progression of human cancers. Here, we analyzed the mutation, copy number variation and gene expression patterns of a literature-derived model of metabolic genes associated with glycolysis (Warburg effect), fatty acid metabolism (lipogenesis, oxidation, lipolysis, esterification) and fatty acid uptake in >9000 primary or metastatic tumor samples from the multi-cancer TCGA datasets. Our association analysis revealed a uniform pattern of Warburg effect mutations influencing prognosis across all tumor types, while copy number alterations in the electron transport chain gene SCO2, fatty acid uptake (CAV1, CD36) and lipogenesis (PPARA, PPARD, MLXIPL) genes were enriched in metastatic tumors. Using gene expression profiles, we established a gene-signature (CAV1, CD36, MLXIPL, CPT1C, CYP2E1) that strongly associated with epithelial-mesenchymal program across multiple cancers. Moreover, stratification of samples based on the copy number or expression profiles of the genes identified in our analysis revealed a significant effect on patient survival rates, thus confirming prominent roles of fatty acid uptake and metabolism in metastatic progression and poor prognosis of human cancers.

The Double-stranded RNA–dependent Protein Kinase Differentially Regulates Insulin Receptor Substrates 1 and 2 in HepG2 Cells

The RNA-dependent protein kinase (PKR), initially known as a virus infection response protein, is found to differentially regulate two major players in the insulin signaling pathway, IRS1 and IRS2. PKR up-regulates the inhibitory phosphorylation of IRS1 and the expression of IRS2 at the transcriptional level.

Rapid fine conformational epitope mapping using comprehensive mutagenesis and deep sequencing

Background: A new method using comprehensive mutagenesis libraries, yeast display, and deep sequencing is proposed to determine fine conformational epitopes for three antibody-antigen interactions. Results: For three separate antigens, the experimentally determined conformational epitope is consistent with orthogonal experimental datasets. Conclusion: We conclude that this new methodology is reliable and sound. Significance: With this new method, four antibody-antigen interactions can be mapped per day. Knowledge of the fine location of neutralizing and non-neutralizing epitopes on human pathogens affords a better understanding of the structural basis of antibody efficacy, which will expedite rational design of vaccines, prophylactics, and therapeutics. However, full utilization of the wealth of information from single cell techniques and antibody repertoire sequencing awaits the development of a high throughput, inexpensive method to map the conformational epitopes for antibody-antigen interactions. Here we show such an approach that combines comprehensive mutagenesis, cell surface display, and DNA deep sequencing. We develop analytical equations to identify epitope positions and show the method effectiveness by mapping the fine epitope for different antibodies targeting TNF, pertussis toxin, and the cancer target TROP2. In all three cases, the experimentally determined conformational epitope was consistent with previous experimental datasets, confirming the reliability of the experimental pipeline. Once the comprehensive library is generated, fine conformational epitope maps can be prepared at a rate of four per day.

Signaling dynamics of palmitate-induced ER stress responses mediated by ATF4 in HepG2 cells

BackgroundPalmitic acid, the most common saturated free fatty acid, has been implicated in ER (endoplasmic reticulum) stress-mediated apoptosis. This lipoapotosis is dependent, in part, on the upregulation of the activating transcription factor-4 (ATF4). To better understand the mechanisms by which palmitate upregulates the expression level of ATF4, we integrated literature information on palmitate-induced ER stress signaling into a discrete dynamic model. The model provides an in silico framework that enables simulations and predictions. The model predictions were confirmed through further experiments in human hepatocellular carcinoma (HepG2) cells and the results were used to update the model and our current understanding of the signaling induced by palmitate.ResultsThe three key things from the in silico simulation and experimental results are: 1) palmitate induces different signaling pathways (PKR (double-stranded RNA-activated protein kinase), PERK (PKR-like ER kinase), PKA (cyclic AMP (cAMP)-dependent protein kinase A) in a time dependent-manner, 2) both ATF4 and CREB1 (cAMP-responsive element-binding protein 1) interact with the Atf4 promoter to contribute to a prolonged accumulation of ATF4, and 3) CREB1 is involved in ER-stress induced apoptosis upon palmitate treatment, by regulating ATF4 expression and possibly Ca2+ dependent-CaM (calmodulin) signaling pathway.ConclusionThe in silico model helped to delineate the essential signaling pathways in palmitate-mediated apoptosis.

Discovering novel pharmacogenomic biomarkers by imputing drug response in cancer patients from large genomics studies

Obtaining accurate drug response data in large cohorts of cancer patients is very challenging; thus, most cancer pharmacogenomics discovery is conducted in preclinical studies, typically using cell lines and mouse models. However, these platforms suffer from serious limitations, including small sample sizes. Here, we have developed a novel computational method that allows us to impute drug response in very large clinical cancer genomics data sets, such as The Cancer Genome Atlas (TCGA). The approach works by creating statistical models relating gene expression to drug response in large panels of cancer cell lines and applying these models to tumor gene expression data in the clinical data sets (e.g., TCGA). This yields an imputed drug response for every drug in each patient. These imputed drug response data are then associated with somatic genetic variants measured in the clinical cohort, such as copy number changes or mutations in protein coding genes. These analyses recapitulated drug associations for known clinically actionable somatic genetic alterations and identified new predictive biomarkers for existing drugs.

Synergy Analysis Reveals Association between Insulin Signaling and Desmoplakin Expression in Palmitate Treated HepG2 Cells

The regulation of complex cellular activities in palmitate treated HepG2 cells, and the ensuing cytotoxic phenotype, involves cooperative interactions between genes. While previous approaches have largely focused on identifying individual target genes, elucidating interacting genes has thus far remained elusive. We applied the concept of information synergy to reconstruct a “gene-cooperativity” network for palmititate-induced cytotoxicity in liver cells. Our approach integrated gene expression data with metabolic profiles to select a subset of genes for network reconstruction. Subsequent analysis of the network revealed insulin signaling as the most significantly enriched pathway, and desmoplakin (DSP) as its top neighbor. We determined that palmitate significantly reduces DSP expression, and treatment with insulin restores the lost expression of DSP. Insulin resistance is a common pathological feature of fatty liver and related ailments, whereas loss of DSP has been noted in liver carcinoma. Reduced DSP expression can lead to loss of cell-cell adhesion via desmosomes, and disrupt the keratin intermediate filament network. Our findings suggest that DSP expression may be perturbed by palmitate and, along with insulin resistance, may play a role in palmitate induced cytotoxicity, and serve as potential targets for further studies on non-alcoholic fatty liver disease (NAFLD).

Pharmacogenetics and Pharmacogenomics of Targeted Therapeutics in Chronic Myeloid Leukemia

The advent of targeted therapeutics has greatly improved outcomes of chronic myeloid leukemia (CML) patients. Despite increased efficacy and better clinical responses over cytotoxic chemotherapies, many patients receiving targeted drugs exhibit a poor initial response, develop drug resistance, or undergo relapse after initial success. This inter-individual variation in response has heightened the interest in studying pharmacogenetics and pharmacogenomics (PGx) of cancer drugs. In this review, we discuss the influence of various germline and somatic factors on targeted drug response in CML. Specifically, we examine the role of genetic variants in drug metabolism genes, i.e. CYP3A family genes, and drug transporters, i.e. ABC and SLC family genes. Additionally, we focus on acquired somatic variations in BCR-ABL1, and the potential role played by additional downstream signaling pathways, in conferring resistance to targeted drugs in CML. This review highlights the importance of PGx of targeted therapeutics and its potential application to improving treatment decisions and patient outcomes.

Ensemble Classification of Cancer Types and Biomarker Identification

Preclinical Research

Characterization of transcription factor response kinetics in parallel

BackgroundTranscription factors (TFs) are effectors of cell signaling pathways that regulate gene expression. TF networks are highly interconnected; one signal can lead to changes in many TF levels, and one TF level can be changed by many different signals. TF regulation is central to normal cell function, with altered TF function being implicated in many disease conditions. Thus, measuring TF levels in parallel, and over time, is crucial for understanding the impact of stimuli on regulatory networks and on diseases.ResultsHere, we report the parallel analysis of temporal TF level changes due to multiple stimuli in distinct cell types. We have analyzed short-term dynamic changes in the levels of nuclear factor kappa-light-chain-enhancer of activated B cells (NF-kB), signal transducer and activator of transcription 3 (Stat3), cAMP response element-binding protein (CREB), glucocorticoid receptor (GR), and TATA binding protein (TBP), in breast and liver cancer cells after tumor necrosis factor-alpha (TNF-α) and palmitic acid (PA) exposure. In response to both stimuli, NF-kB and CREB levels were increased, Stat3 decreased, and TBP was constant. GR levels were unchanged in response to TNF-α stimulation and increased in response to PA treatment.ConclusionsOur results show significant overlap in signaling initiated by TNF-α and by PA, with the exception that the events leading to PA-mediated cytotoxicity likely also include induction of GR signaling. These results further illuminate the dynamics of TF responses to cytokine and fatty acid exposure, while concomitantly demonstrating the utility of parallel TF measurement approaches in the analysis of biological phenomena.