Combined analysis of somatic mutations and gene expression reveals nuclear speckles-associated enhanced stemness in gingivobuccal carcinoma under DNA damage response
Sachendra Kumar , Tamasa De , Janavi Subramani , Annapoorni Rangarajan , Debnath Pal
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引用次数: 0
Abstract
Smokeless tobacco chewing habits in India lead to a high prevalence of Gingivobuccal oral squamous cell carcinoma (OSCC-GB). Cancer stem cells (CSCs) are a sub-population of cancer cells within a tumor with stem-like properties and are believed to contribute to tumor initiation, progression, increased resistance to drug therapy, and promote post-therapeutic cancer relapse. An RNA-sequencing data-based combined analysis of somatic mutations and gene expression was performed to explore the role of CSCs in disease progression using the novel Indian-origin OSCC-GB cell line ‘IIOC019’ from a patient with tobacco-chewing habit. The identified DNA damage-related known mutational signature (1 bp T/(A) nucleotide insertions and C>T mutations) indicates the impact of smokeless tobacco-related carcinogens in the IIOC019 cell line. The differentially expressed somatic variants, functional impact predictions, and survival analysis reveal the role of DNA damage response (DDR)-related genes in OSCC-GB, with the SON gene as a significant player. The study suggests that the loss-of-function in a somatic variant of the SON gene is linked to nuclear speckles-associated enhanced stemness and increased risk of disease progression in OSCC-GB under DDR conditions. The newly identified CSC-associated somatic variants appear to promote cancer spread, local recurrence, and resistance to chemotherapy or radiotherapy, contributing to the high mortality rates among Indian OSCC-GB patients.
期刊介绍:
Computational Biology and Chemistry publishes original research papers and review articles in all areas of computational life sciences. High quality research contributions with a major computational component in the areas of nucleic acid and protein sequence research, molecular evolution, molecular genetics (functional genomics and proteomics), theory and practice of either biology-specific or chemical-biology-specific modeling, and structural biology of nucleic acids and proteins are particularly welcome. Exceptionally high quality research work in bioinformatics, systems biology, ecology, computational pharmacology, metabolism, biomedical engineering, epidemiology, and statistical genetics will also be considered.
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