Cancer-Specific Biomarkers across Multiple Carcinomas

Wed, 01 Oct 2025 00:00:00 +0000

Full title: Machine Learning-Driven Identification and Quantitative Validation of Cancer-Specific Biomarkers across Multiple Carcinomas of Different Anatomic Sites

Collaborating institutions

Bangladesh Medical University (BMU): Department of Virology (lead), Gynecological Oncology, Otolaryngology–Head & Neck Surgery, Surgical Oncology, and Pathology
Shahjalal University of Science and Technology (SUST): Department of Biochemistry and Molecular Biology (lead)
National Institute of Cancer Research & Hospital (NICRH): Department of Surgical Oncology

Abstract

Background: Early detection is critical for improving cancer prognosis, yet existing diagnostic biomarkers often lack adequate sensitivity and specificity. Advances in RNA sequencing, including single-cell RNA sequencing (scRNA-seq), have deepened our understanding of tumor heterogeneity. Computational pipelines can suggest potential biomarkers, but rigorous molecular validation is essential to confirm their clinical relevance.

Methods: The project integrates bioinformatic analyses with molecular validation. The dry-lab phase covers acquisition and analysis of RNA-seq and scRNA-seq datasets, differential gene expression profiling, and machine learning-based biomarker prioritization. The wet-lab phase validates candidates in human tissue samples. Histopathological examination ensures sample integrity, and DNA, RNA and protein extractions enable validation through qRT-PCR, PCR assays and ELISA. Bioinformatic tools then place validated biomarkers within their molecular pathways.

Expected results: A curated list of validated cancer-specific biomarkers, their expression profiles and associated molecular networks, along with key pathways underlying tumorigenesis across multiple anatomical sites.

Conclusion: By combining computational discovery with wet-lab validation, the study aims to establish highly sensitive and specific biomarkers for early cancer detection, contributing to precision oncology and better patient outcomes.

Project design

Research team

Principal Investigator: Dr. S. M. Rashed Ul Islam, Associate Professor, Department of Virology, BMU

Co-Principal Investigator: Tanvir Hossain, Department of Biochemistry and Molecular Biology, SUST

Co-Investigator	Position	Department	Institution
Dr. Jannatul Ferdous	Professor	Gynecological Oncology	BMU
Dr. Syed Farhan Ali Razib	Associate Professor	Otolaryngology–Head & Neck Surgery	BMU
Dr. Hasan Shahrear Ahmed	Associate Professor	Surgical Oncology	BMU
Dr. Ashrafur Rahman	Assistant Professor	Surgical Oncology	NICRH
Dr. Bishnu Pada Dey	Associate Professor	Pathology	BMU
Papia Rahman	Lecturer	Biochemistry and Molecular Biology	SUST

Collaboration and ethics