Research Brief

Research Synopsis by Dr. Iqbal Mahmud

I am an expert in cell and molecular biology, analytical chemistry, cancer metabolism, atherosclerosis,  immunometabolism, and multiomics, with extensive passion in bioinformatics, computational biology/chemistry, and artificial intelligence (AI), where I have discovered novel therapeutic targets and innovative drug discovery platforms for human diseases, including cancers. My major accomplishments are highlighted as follows:

Discovery of novel therapeutic targets and drug development through multiomics. I discovered DAXX (death domain-associated protein) as a novel biomarker and therapeutic target in multiple human cancers (Mahmud et al., Nucleic Acid Res. 2019).  My work on DAXX first uncovered the novel axis of de novo lipogenesis through protein-protein (DAXX-SREBPs) interactions in human cancer (Mahmud et al., Nature Communications 2023). Most importantly, I developed a therapeutic peptide corresponding to DAXX’s C-terminal SUMO-interacting motif (SIM2) that is cell-membrane permeable, disrupts the DAXX-SREBP1/2 interactions, and inhibits lipogenesis and tumor growth in multiple human cancers. These results establish DAXX as a druggable target and the SIM2 peptide as a potential therapeutic for cancer therapy (Liao & Mahmud, Patent Pub no. WO/2019/195693).

My research on global lipidomics revealed the novel role of chemerin (adipokine) signaling through fatty acid peroxidation and ferroptosis mechanisms (Tan & Mahmud et al., Cancer Discovery 2021). Later, chemerin signaling was interrogated with several GPCR signaling proteins (GPR1 and CMKLR1), and his research identified that chemerin modulates distinct lipid metabolism through CMKLR1 GPCR protein and is critical for ccRCC tumor growth (Wang & Mahmud et al., Cancer Research 2024).  This discovery led to the development of monoclonal antibody-based therapeutics targeting chemerin. Using untargeted lipidomics, I found that ccRCC can be classified into distinct subtypes based on their lipid profiles, with blocking chemerin signaling effectively suppressing growth of the more aggressive lipid subtype of ccRCCs, both as a monotherapy and in combination with the tyrosine kinase inhibitors, remaining effective even in tumors with acquired resistant tumors (Mahmud & Wang et al., Science advances, under review 2025).

My work also discovered that leucine drives OGR1-mediated lipogenesis and autophagy-dependent acid stress adaptation (Pillai & Mahmud et al., Cell Reports 2022). My investigation of CBP/p300 inhibition demonstrates advanced therapeutic target validation and reports that CBP/p300 inhibitors effectively block estrogen receptor function and inhibit breast cancer cell growth, revealing CBP and p300 as promising druggable targets for breast cancer treatment (Waddell & Mahmud et al., Cancers 2021). My research on sex-based multiomics analysis established a translational murine model of concurrent MASH and atherosclerosis, revealing sex-specific dietary responses and metabolic and transcriptional pathways as potential biomarkers and therapeutic targets (Mahmud et al., JHEP Reports, 2025). 

These studies collectively highlight my mastery of target identification, validation, and therapeutic development essential for translational cancer research.

Revolutionary Technology Development for Drug Discovery and Diagnostics. I have made pioneering contributions to drug discovery technology development through groundbreaking research that addresses fundamental challenges in therapeutic development. I developed innovative rapid screening technologies for noninvasive prostate cancer (PC) diagnosis and monitoring, including paper spray ionization (PSI-MS)-based metabolomics (Mahmud et al., Analytical Chemistry 2021; Mahmud et al., Anal Chem, under review 2025), segmented flow mass spectrometry (SF-MS)-based metabolomics (Mahmud et al., Journal of Proteome Research 2020), and data-driven classification algorithms (Mahmud et al., Analytical Chemistry 2022) that transformed PC classification and therapeutic monitoring. These technologies provide rapid, cost-effective platforms for drug efficacy assessment and patient stratification.

My landmark work on ion suppression correction and normalization of global metabolomics data solved a universal problem in mass spectrometry-based biomarker and drug discovery, significantly enhancing data reliability for therapeutic development (Mahmud et al., Nature Communications 2025). I co-developed TARO, an innovative computational framework for integrating microbiome and metabolomics data, enabling unprecedented insights into drug-microbiome interactions (Misra & Mahmud et al., Bioinformatics 2024). My investigations have uncovered how microbial species affect drug metabolism and therapeutic efficacy, particularly in the oral-gut axis affecting cancer therapeutics (Mahmud et al., manuscript in preparation for JACS, 2025).

I developed the xPEDITE platform for multiomics integration, featuring System Biology Graphical Notation (SBGN) pipelines for direct interpretation of drug mechanisms of action, enabling sophisticated visualization of drug toxicity (Mahmud et al., Journal of Proteome Research 2025), therapeutic resistance (Baek et al., Oncogene 2023), and multi-organ drug effects (Yuan et al., Nature Communications 2025, under revision). These tools have proven instrumental in elucidating drug mechanisms and optimizing therapeutic combinations, including high-fiber diet interventions that enhance immunotherapy response in melanoma patients (Daniel et al., Science 2025 under revision).

Therapeutic Target Discovery in Cancer Metabolism and Drug Resistance. Building on the central dogma of cancer metabolism (bioenergetics, biosynthesis, and redox balance) I have systematically identified druggable vulnerabilities across multiple cancer types. My comprehensive approach has yielded meaningful therapeutic discoveries through dissecting cancer bioenergetics (Qin et al., Blood 2025; Colbert et al., Cancer Cell 2023), redox-balance mechanisms (Chattopadhyay et al., British J. of Cancer 2024; Baek et al., Oncogene 2023), and macromolecule biosynthesis pathways (Mahmud et al., Nature Communications 2023; Pillai & Mahmud et al., Cell Reports 2022).

My research identified novel therapeutic targets including fatty acid binding proteins (FABP7) in ferroptosis resistance (Maria et al., Molecular Cancer 2025), SREBP2-driven cholesterol synthesis in castration-resistant prostate cancer (Chen et al., Nature Cancer 2025), and tumor-resident Lactobacillus in chemoradiation resistance (Colbert et al., Cancer Cell 2023). These discoveries have established therapeutic vulnerabilities and provided roadmaps for targeting core metabolic dependencies of tumor cells, particularly in drug-resistant cancers.

Precision Medicine and Biomarker Development for Therapeutics. I have established pioneering approaches in biomarker discovery that enable precision therapeutic strategies. He developed sophisticated computational frameworks for therapeutic target classification, including lipid ontology analysis for drug targeting (Gencel-Augusto et al., Cancer Discovery 2023), organelle-specific therapeutic vulnerabilities (Li et al., Journal of Biological Chemistry 2024), and inflammatory pathway targeting for combination therapies (Caitlyn et al., Nature Communications 2025, under revision).

My innovative methodologies have revealed actionable therapeutic mechanisms, including how specific lipid species influence drug sensitivity, such as chemerin regulation of ferroptosis resistance affecting immunotherapy response (Tan & Mahmud et al., Cancer Discovery 2021), cell cycle-dependent metabolic vulnerabilities for therapeutic targeting (Lee et al., Nature Communications 2024), and how concurrent genetic alterations create synthetic lethal opportunities for precision medicine (Chen et al., Nature Cancer 2025).

My research identified novel therapeutic biomarkers including non-coding RNAs such as miRNA-211 that can be targeted to disrupt metabolic homeostasis (Lee & Mahmud et al., Acta Neuropathol Commun. 2023; Yuan & Mahmud et al., Acta Neuropathol Commun. 2023) and oncogenic circular RNA circ_63706 that represents a druggable target in pediatric brain cancers (Katsushima et al., Acta Neuropathol Commun. 2023). Through these contributions, I have established essential frameworks for precision medicine approaches that integrate biomarker discovery with therapeutic development, significantly advancing targeted therapy strategies and drug development pipelines.