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Huma Asif, PhD

Assistant Professor, Division of Experimental Pathology

Dr. Asif is a member of the Division of Experimental Pathology and serves as the Assistant Director of the High-Throughput Genome Center in the Department of Pathology at the University of Pittsburgh.

Research Interests

My research focuses on understanding disease mechanisms using multi-omics approaches. We integrate genomic, transcriptomic, and epigenomic data with advanced statistical and machine learning methods to identify molecular biomarkers linked to disease progression and patient outcomes.

Over the past few years, I have developed a strong interest in exploring racial disparities in cancer. We utilize public datasets such as The Cancer Genome Atlas (TCGA) to investigate how epigenetic alterations, immune infiltration, and biological aging impact tumor behavior and survival across different racial groups. In one of my studies, I identified hypomethylation in endometrial tumors, revealing thirty-eight epigenetic signature genes (ESGs) significantly associated with survival outcomes in Black and White women. This work also showed that tumors from women with higher African ancestry exhibited increased hypomethylation compared to those with lower African ancestry, with these genes enriched in drug metabolism pathways. These findings offer new insights into how genetic ancestry may influence cancer progression and treatment response.

I am interested in examining biological aging in tumors to understand its contribution to racial disparities in cancer outcomes.

As part of my broader research activities, I collaborate with investigators at the High-Throughput Genome Center and the Department of Pathology to analyze next-generation sequencing data including ChIP-seq, RRBS, CUT&RUN, transcriptomics, and whole-exome sequencing to address diverse biological questions.

Representative Publications

View Dr. Asif publications on PubMed

  1. Asif H, Kim JJ. Comparing self-reported race and genetic ancestry for identifying potential differentially methylated sites in endometrial cancer: insights from African ancestry proportions using machine learning models. Mol Oncol. 2025.
  2. Asif H, Foley G, Simon M, Roque D, Kim JJ. Analysis of endometrial carcinoma TCGA reveals differences in DNA methylation in tumors from Black and White women. Gynecol Oncol. 2022;170:1-10.
  3. Li Y, Asif H, Feng Y, Kim JJ, Wei JJ. Somatic. Cells. 2024;13(17).
  4. Li Y, Xu X, Asif H, Feng Y, Kohrn BF, Kennedy SR, et al. Myometrial oxidative stress drives MED12 mutations in leiomyoma. Cell Biosci. 2022;12(1):111.
  5. Asif H, Alliey-Rodriguez N, Keedy S, Tamminga CA, Sweeney JA, Pearlson G, et al. GWAS significance thresholds for deep phenotyping studies can depend upon minor allele frequencies and sample size. Molecular Psychiatry. 2020.