Megha Padi

Interests

Research

All cells contain a large network of interacting genes and proteins that carry out necessary functions. But we still don’t understand how this network is disrupted in complex diseases like cancer, heart disease, diabetes, or asthma. The Padi lab develops new computational approaches to integrate genomic “big data” and model how cellular networks are functionally altered by disease, genetic variation, epigenetics, and other factors. Our ultimate goal is to identify drivers of disease, propose new therapeutic targets, and predict prognosis and drug response in a patient-specific manner. For example, we are using network analysis to understand how viruses induce tumorigenesis, how genetic variants combine to produce complex phenotypes, and how cancer cell lines and tumors respond to drugs. We use cell culture experiments to refine and validate our predictive network models. If you are interested in working in the field of computational genomics, systems biology, and network science, please contact Dr. Megha Padi at mpadi@email.arizona.edu.

Courses

Scholarly Contributions

Journals/Publications

• Mouneimne, G., Langlais, P. R., Wolgemuth, C. W., Padi, M., Roman, M. R., Parker, J. D., Wang, A., Grant, A. D., Ly, K. T., & Parker, S. S. (2023). EVL and MIM/MTSS1 regulate actin cytoskeletal remodeling to promote dendritic filopodia in developing neurons. Journal of Cell Biology.
• Parker, S. S., Ly, K. T., Grant, A. D., Wang, A., Parker, J. D., Roman, M. R., Padi, M., Wolgemuth, C. W., Langlais, P. R., & Mouneimne, G. (2021). EVL and MIM/MTSS1 regulate actin cytoskeletal remodeling to promote dendritic filopodia in developing neurons. Journal of Cell Biology.
• Grant, A., Xicola, R. M., Nguyen, V., Lim, J., Thorne, C., Salhia, B., Llor, X., Ellis, N., & Padi, M. (2021). Molecular drivers of tumor progression in microsatellite stable APC mutation-negative colorectal cancers. Scientific reports, 11(1), 23507.
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  The tumor suppressor gene adenomatous polyposis coli (APC) is the initiating mutation in approximately 80% of all colorectal cancers (CRC), underscoring the importance of aberrant regulation of intracellular WNT signaling in CRC development. Recent studies have found that early-onset CRC exhibits an increased proportion of tumors lacking an APC mutation. We set out to identify mechanisms underlying APC mutation-negative (APC) CRCs. We analyzed data from The Cancer Genome Atlas to compare clinical phenotypes, somatic mutations, copy number variations, gene fusions, RNA expression, and DNA methylation profiles between APC and APC mutation-positive (APC) microsatellite stable CRCs. Transcriptionally, APC CRCs clustered into two approximately equal groups. Cluster One was associated with enhanced mitochondrial activation. Cluster Two was strikingly associated with genetic inactivation or decreased RNA expression of the WNT antagonist RNF43, increased expression of the WNT agonist RSPO3, activating mutation of BRAF, or increased methylation and decreased expression of AXIN2. APC CRCs exhibited evidence of increased immune cell infiltration, with significant correlation between M2 macrophages and RSPO3. APC CRCs comprise two groups of tumors characterized by enhanced mitochondrial activation or increased sensitivity to extracellular WNT, suggesting that they could be respectively susceptible to inhibition of these pathways.
• Watson, A. W., Grant, A. D., Parker, S. S., Hill, S., Whalen, M. B., Chakrabarti, J., Harman, M. W., Roman, M. R., Forte, B. L., Gowan, C. C., Castro-Portuguez, R., Stolze, L. K., Franck, C., Cusanovich, D. A., Zavros, Y., Padi, M., Romanoski, C. E., & Mouneimne, G. (2021). Breast tumor stiffness instructs bone metastasis via maintenance of mechanical conditioning. Cell reports, 35(13), 109293.
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  While the immediate and transitory response of breast cancer cells to pathological stiffness in their native microenvironment has been well explored, it remains unclear how stiffness-induced phenotypes are maintained over time after cancer cell dissemination in vivo. Here, we show that fibrotic-like matrix stiffness promotes distinct metastatic phenotypes in cancer cells, which are preserved after transition to softer microenvironments, such as bone marrow. Using differential gene expression analysis of stiffness-responsive breast cancer cells, we establish a multigenic score of mechanical conditioning (MeCo) and find that it is associated with bone metastasis in patients with breast cancer. The maintenance of mechanical conditioning is regulated by RUNX2, an osteogenic transcription factor, established driver of bone metastasis, and mitotic bookmarker that preserves chromatin accessibility at target gene loci. Using genetic and functional approaches, we demonstrate that mechanical conditioning maintenance can be simulated, repressed, or extended, with corresponding changes in bone metastatic potential.
• Lim, J. T., Chen, C., Grant, A. D., & Padi, M. (2020). Generating Ensembles of Gene Regulatory Networks to Assess Robustness of Disease Modules. Frontiers in genetics, 11, 603264.
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  The use of biological networks such as protein-protein interaction and transcriptional regulatory networks is becoming an integral part of genomics research. However, these networks are not static, and during phenotypic transitions like disease onset, they can acquire new "communities" (or highly interacting groups) of genes that carry out cellular processes. Disease communities can be detected by maximizing a modularity-based score, but since biological systems and network inference algorithms are inherently noisy, it remains a challenge to determine whether these changes represent real cellular responses or whether they appeared by random chance. Here, we introduce Constrained Random Alteration of Network Edges (CRANE), a method for randomizing networks with fixed node strengths. CRANE can be used to generate a null distribution of gene regulatory networks that can in turn be used to rank the most significant changes in candidate disease communities. Compared to other approaches, such as consensus clustering or commonly used generative models, CRANE emulates biologically realistic networks and recovers simulated disease modules with higher accuracy. When applied to breast and ovarian cancer networks, CRANE improves the identification of cancer-relevant GO terms while reducing the signal from non-specific housekeeping processes.
• Lim, J. T., Singh, N., Leuvano, L. A., Calvert, V. S., Petricoin, E. F., Teachey, D. T., Lock, R. B., Padi, M., Kraft, A. S., & Padi, S. K. (2020). PIM Kinase Inhibitors Block the Growth of Primary T-cell Acute Lymphoblastic Leukemia: Resistance Pathways Identified by Network Modeling Analysis. Molecular cancer therapeutics, 19(9), 1809-1821.
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  Despite significant progress in understanding the genetic landscape of T-cell acute lymphoblastic leukemia (T-ALL), the discovery of novel therapeutic targets has been difficult. Our results demonstrate that the levels of PIM1 protein kinase is elevated in early T-cell precursor ALL (ETP-ALL) but not in mature T-ALL primary samples. Small-molecule PIM inhibitor (PIMi) treatment decreases leukemia burden in ETP-ALL. However, treatment of animals carrying ETP-ALL with PIMi was not curative. To model other pathways that could be targeted to complement PIMi activity, HSB-2 cells, previously characterized as a PIMi-sensitive T-ALL cell line, were grown in increasing doses of PIMi. Gene set enrichment analysis of RNA sequencing data and functional enrichment of network modules demonstrated that the HOXA9, mTOR, MYC, NFκB, and PI3K-AKT pathways were activated in HSB-2 cells after long-term PIM inhibition. Reverse phase protein array-based pathway activation mapping demonstrated alterations in the mTOR, PI3K-AKT, and NFκB pathways, as well. PIMi-tolerant HSB-2 cells contained phosphorylated RelA-S536 consistent with activation of the NFκB pathway. The combination of NFκB and PIMis markedly reduced the proliferation in PIMi-resistant leukemic cells showing that this pathway plays an important role in driving the growth of T-ALL. Together these results demonstrate key pathways that are activated when HSB-2 cell line develop resistance to PIMi and suggest pathways that can be rationally targeted in combination with PIM kinases to inhibit T-ALL growth.
• Meeks, L. G., De Oliveira Pessoa, D., Martinez, J. A., Limesand, K. H., & Padi, M. (2021). Integration of metabolomics and transcriptomics reveals convergent pathways driving radiation-induced salivary gland dysfunction. Physiological genomics.
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  Radiation therapy for head and neck cancer causes damage to the surrounding salivary glands, resulting in salivary gland hypofunction and xerostomia. Current treatments do not provide lasting restoration of salivary gland function following radiation; therefore, a new mechanistic understanding of the radiation-induced damage response is necessary for identifying therapeutic targets. The purpose of the present study was to investigate the metabolic phenotype of radiation-induced damage in parotid salivary glands by integrating transcriptomic and metabolomic data. Integrated data were then analyzed to identify significant gene-metabolite interactions. Mice received a single 5 Gy dose of targeted head and neck radiation. Parotid tissue samples were collected 5 days following treatment for RNA sequencing and metabolomics analysis. Altered metabolites and transcripts significantly converged on a specific region in the metabolic reaction network. Both integrative pathway enrichment using rank-based statistics and network analysis highlighted significantly coordinated changes in glutathione metabolism, energy metabolism (TCA cycle and thermogenesis), peroxisomal lipid metabolism, and bile acid production with radiation. Integrated changes observed in energy metabolism suggest that radiation induces a mitochondrial dysfunction phenotype. These findings validated previous pathways involved in the radiation-damage response, such as altered energy metabolism, and identified robust signatures in salivary glands, such as reduced glutathione metabolism, that may be driving salivary gland dysfunction.
• Grant, A. D., Vail, P., Padi, M., Witkiewicz, A. K., & Knudsen, E. S. (2019). Interrogating Mutant Allele Expression via Customized Reference Genomes to Define Influential Cancer Mutations. Scientific reports, 9(1), 12766.
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  Genetic alterations are essential for cancer initiation and progression. However, differentiating mutations that drive the tumor phenotype from mutations that do not affect tumor fitness remains a fundamental challenge in cancer biology. To better understand the impact of a given mutation within cancer, RNA-sequencing data was used to categorize mutations based on their allelic expression. For this purpose, we developed the MAXX (Mutation Allelic Expression Extractor) software, which is highly effective at delineating the allelic expression of both single nucleotide variants and small insertions and deletions. Results from MAXX demonstrated that mutations can be separated into three groups based on their expression of the mutant allele, lack of expression from both alleles, or expression of only the wild-type allele. By taking into consideration the allelic expression patterns of genes that are mutated in PDAC, it was possible to increase the sensitivity of widely used driver mutation detection methods, as well as identify subtypes that have prognostic significance and are associated with sensitivity to select classes of therapeutic agents in cell culture. Thus, differentiating mutations based on their mutant allele expression via MAXX represents a means to parse somatic variants in tumor genomes, helping to elucidate a gene's respective role in cancer.
• Pearson, T., Caporaso, J. G., Yellowhair, M., Bokulich, N. A., Padi, M., Roe, D. J., Wertheim, B. C., Linhart, M., Martinez, J. A., Bilagody, C., Hornstra, H., Alberts, D. S., Lance, P., & Thompson, P. A. (2019). Effects of ursodeoxycholic acid on the gut microbiome and colorectal adenoma development. Cancer medicine.
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  It has been previously reported that ursodeoxycholic acid (UDCA), a therapeutic bile acid, reduced risk for advanced colorectal adenoma in men but not women. Interactions between the gut microbiome and fecal bile acid composition as a factor in colorectal cancer neoplasia have been postulated but evidence is limited to small cohorts and animal studies. Using banked stool samples collected as part of a phase III randomized clinical trial of UDCA for the prevention of colorectal adenomatous polyps, we compared change in the microbiome composition after a 3-year intervention in a subset of participants randomized to oral UDCA at 8-10 mg/kg of body weight per day (n = 198) or placebo (n = 203). Study participants randomized to UDCA experienced compositional changes in their microbiome that were statistically more similar to other individuals in the UDCA arm than to those in the placebo arm. This reflected a UDCA-associated shift in microbial community composition (P  0.05). These UDCA-associated shifts in microbial community distance metrics from baseline to end-of-study were not associated with risk of any or advanced adenoma (all P > 0.05) in men or women. Separate analyses of microbial networks revealed an overrepresentation of Faecalibacterium prausnitzii in the post-UDCA arm and an inverse relationship between F prausnitzii and Ruminococcus gnavus. In men who received UDCA, the overrepresentation of F prausnitzii and underrepresentation of R gnavus were more prominent in those with no adenoma recurrence at follow-up compared to men with recurrence. This relationship was not observed in women. Daily UDCA use modestly influences the relative abundance of microbial species in stool and affects the microbial network composition with suggestive evidence for sex-specific effects of UDCA on stool microbial community composition as a modifier of colorectal adenoma risk.
• Padi, M., & Quackenbush, J. (2018). Detecting phenotype-driven transitions in regulatory network structure. NPJ systems biology and applications, 4, 16.
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  Complex traits and diseases like human height or cancer are often not caused by a single mutation or genetic variant, but instead arise from functional changes in the underlying molecular network. Biological networks are known to be highly modular and contain dense "communities" of genes that carry out cellular processes, but these structures change between tissues, during development, and in disease. While many methods exist for inferring networks and analyzing their topologies separately, there is a lack of robust methods for quantifying differences in network structure. Here, we describe ALPACA (ALtered Partitions Across Community Architectures), a method for comparing two genome-scale networks derived from different phenotypic states to identify condition-specific modules. In simulations, ALPACA leads to more nuanced, sensitive, and robust module discovery than currently available network comparison methods. As an application, we use ALPACA to compare transcriptional networks in three contexts: angiogenic and non-angiogenic subtypes of ovarian cancer, human fibroblasts expressing transforming viral oncogenes, and sexual dimorphism in human breast tissue. In each case, ALPACA identifies modules enriched for processes relevant to the phenotype. For example, modules specific to angiogenic ovarian tumors are enriched for genes associated with blood vessel development, and modules found in female breast tissue are enriched for genes involved in estrogen receptor and ERK signaling. The functional relevance of these new modules suggests that not only can ALPACA identify structural changes in complex networks, but also that these changes may be relevant for characterizing biological phenotypes.
• Sharma, A., Halu, A., Decano, J. L., Padi, M., Liu, Y. Y., Prasad, R. B., Fadista, J., Santolini, M., Menche, J., Weiss, S. T., Vidal, M., Silverman, E. K., Aikawa, M., Barabási, A. L., Groop, L., & Loscalzo, J. (2018). Controllability in an islet specific regulatory network identifies the transcriptional factor NFATC4, which regulates Type 2 Diabetes associated genes. NPJ systems biology and applications, 4, 25.
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  Probing the dynamic control features of biological networks represents a new frontier in capturing the dysregulated pathways in complex diseases. Here, using patient samples obtained from a pancreatic islet transplantation program, we constructed a tissue-specific gene regulatory network and used the control centrality (Cc) concept to identify the high control centrality (HiCc) pathways, which might serve as key pathobiological pathways for Type 2 Diabetes (T2D). We found that HiCc pathway genes were significantly enriched with modest GWAS -values in the DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) study. We identified variants regulating gene expression (expression quantitative loci, eQTL) of HiCc pathway genes in islet samples. These eQTL genes showed higher levels of differential expression compared to non-eQTL genes in low, medium, and high glucose concentrations in rat islets. Among genes with highly significant eQTL evidence, NFATC4 belonged to four HiCc pathways. We asked if the expressions of T2D-associated candidate genes from GWAS and literature are regulated by Nfatc4 in rat islets. Extensive in vitro silencing of Nfatc4 in rat islet cells displayed reduced expression of 16, and increased expression of four putative downstream T2D genes. Overall, our approach uncovers the mechanistic connection of NFATC4 with downstream targets including a previously unknown one, TCF7L2, and establishes the HiCc pathways' relationship to T2D.

Presentations

• Padi, M. (2018, March). Detecting phenotype-driven transitions in regulatory network structure. CompleNet 2018. Boston, MA.

Poster Presentations

• Padi, M., Limesand, K. H., Martinez, J. A., De Oliveira Pessoa, D., & Meeks, L. (2021). Integration of metabolomics and transcriptomics reveals convergent pathways driving radiation-induced salivary gland dysfunction.. Cold Springs Harbor Network Biology conference. virtual.