About Salma Khan, PhD

I began my professional career as a Gynecologist in Bangladesh where woman prefers to consult with lady doctors only.  I have seen patients dying of cancer without treatment or lack of early diagnosis.  My journey began at that time to develop myself as a scientist who can explore the unsolved questions to cure cancer or to establish early diagnostic tools.  I then took the opportunity of Gov. of Japan’s scholarship for PhD degree in Gynecologic Pathology/Reproductive Physiology.  I have enjoyed every day of my life doing experiments and amazingly saw the progress of research when Gleevac was marketed to save the life of Leukemia patients.  That’s the day, I decided to stay in cancer research field and discover some drugs to cure cancer or adjuvants to existing cancer therapy and encourage and educate my students to do so.

When I joined Loma Linda University, I have mastered protein purification from a large-scale culture Bio-reactor, Mass-spectrometric analysis, Flow-Cytometry (both cell cycle analysis by PI staining and cell-surface staining), exosome purification, confocal microscopy, siRNA, and Real-Time PCR.

While I was a post-doc researcher at Cedars-Sinai Medical Center since 2001 in a complex Pathology laboratory and research collaborative environment; providing molecular pathology support for a variety of projects in breast cancer, optimization and establishment of fluorescent in-situ hybridization (FISH) technique including synthesis of probe from BAC clone, labeling, and hybridizing into both metaphase spread and archival tissues, DNA purification from microdissected archival samples, Methylation specific PCR (MSP) to study epigenetic silencing of PTEN gene, primer optimization for LOH study primarily in breast, ovary, prostate cancer, and malignant melanoma.  My previous paper is on epigenetic titled "PTEN promoter is methylated in a proportion of invasive breast cancers.

My research plan integrates molecular oncology, health disparities, and translational therapeutics to address pressing challenges in endocrine and gynecologic cancers. I aim to understand how tumor genetics, microenvironmental interactions, and ancestry-linked biology influence cancer progression and therapeutic response. By combining omics technologies, bioinformatics, artificial intelligence, and molecular pathology, my ultimate goal is to develop precision medicine strategies that reduce disparities and improve survival in thyroid and ovarian cancers.

Thyroid Cancer: Disparities and Translational Therapeutics

Thyroid cancer is the most common endocrine malignancy, with rising incidence and persistent racial disparities in outcomes. My work has advanced two complementary areas:

  1. Disparities in Papillary Thyroid Cancer
    • Using bulk RNA-sequencing, we identified ancestry-specific gene expression signatures in papillary thyroid carcinoma (PTC), highlighting immune and stromal pathway differences between racial groups (Barseghyan et al., Curr Oncol, 2025).
    • A comprehensive literature synthesis (Rood et al., Cancer Health Disparities, 2023) contextualized these molecular findings with epidemiologic and socioeconomic factors.
  2. Novel Therapeutics in Anaplastic Thyroid Cancer (ATC)
    • In ATC, one of the most lethal endocrine cancers, we mapped mutational landmarks that suggest therapeutic vulnerabilities (Pakkianathan et al., J. Clin. Med., 2025).
    • We proposed targeting surface-expressed proteins with ligand-bound therapies, extending concepts of radioligand therapy beyond the sodium-iodide symporter (Pakkianathan et al., J. Endocrine Soc., 2025).
    • Additionally, our work on PDLIM7 regulatory networks identified novel partners that modulate thyroid tumor progression (Rood et al., Curr Oncol, 2023).

Collectively, these studies define a multi-pronged therapeutic strategy: addressing disparities, leveraging genetic vulnerabilities, targeting cell-surface ligands, and modulating the tumor microenvironment (TME).

 

Ovarian Cancer: Genomic Instability, MicroRNAs, and AI-Driven Biomarkers

High-grade serous ovarian cancer (HGSOC) is a highly lethal disease with limited therapeutic options. My research addresses two unmet needs: understanding microRNA/genomic instability and equity-driven biomarker discovery.

  • MicroRNA Signatures: We identified miRNA patterns associated with genomic instability distinguishing high-grade from low-grade tumors (Muinde et al., Trends in Cancer Research, 2024). These signatures hold promise for risk stratification and therapy response prediction.
  • AI-Enhanced Morphometrics: Leveraging machine learning, we discovered cellular morphometric biomarkers that reveal unique tumor immune microenvironments in African ancestry HGSOC tissues (Muinde et al., Mol Cancer Res, under review). This approach highlights how AI-guided pathology can reveal ancestry-linked TME differences and inform immunotherapy strategies.

These studies exemplify my focus on integrating computational discovery with biological interpretation to improve diagnostics and advance precision oncology.

 

Cross-Cancer and Interdisciplinary Contributions

Beyond thyroid and ovarian cancers, my collaborative work spans prevention, nanomedicine, and global oncology:

  • Vitamin D and Cancer Prevention: Reviews on vitamin D signaling in liver cancer (Lamia et al., J BMANA, 2025) and colorectal cancer (Tamanna et al., Disease & Research, 2024) highlight its role as a modifiable pathway in oncogenesis.
  • Nanomedicine: A study on silver nanoparticle–DNA interactions (Perry et al., J Nanopart Res, 2025) contributes to understanding nanoscale drug delivery mechanisms.
  • Global Health Equity: A review of cervical cancer burden in Nigeria (Lawal et al., Gynecol Reprod Health, 2023) underscores the need for accessible screening and prevention in low-resource settings.

These works reflect my broader commitment to equity, prevention, and interdisciplinary collaboration in oncology.

 

Future Research Directions

My program will continue to expand in three synergistic directions:

  1. Dissecting Ancestry-Linked Tumor Biology
    • Utilize single-cell and spatial transcriptomics to profile tumor-immune-stromal interactions across diverse cohorts.
    • Apply multi-omics integration (genomics, transcriptomics, proteomics) to uncover ancestry-associated drivers of disparities.
  2. Therapeutic Innovation in Endocrine and Ovarian Cancers
    • Advance surface-targeted ligand therapies for ATC, incorporating nanotechnology and antibody-drug conjugates.
    • Explore CAF- and immune-targeted interventions to reprogram the ovarian cancer TME.
    • Investigate miRNA modulation as a therapeutic avenue for genomic instability.
  3. Equity and AI-Driven Precision Oncology
    • Implement AI-enhanced histopathology pipelines to generate explainable biomarkers of tumor biology.
    • Partner with national and global collaborators to ensure representation of understudied minority populations in datasets and clinical studies.

Conclusion

Through a multi-disciplinary, high throughput approach, my research program addresses critical gaps in thyroid and ovarian cancers—from unraveling molecular disparities to pioneering novel therapeutic strategies. By integrating molecular pathology, bioinformatics, and translational therapeutics, I aim to reduce inequities and improve outcomes for patients across diverse populations.