This research explores bacterial communities in individuals diagnosed with oral cancer, comparing them to healthy individuals to identify potential variations associated with the condition. The study involved collecting 40 swabs from oral cancer patients, post-therapeutic patients, and healthy individuals, amplifying DNA samples, processing raw data using Perl scripts and Prinseq Lite, performing metagenomic analysis using QIIME 2-2022.2, and taxonomic classification using Greengenes2. There are 91.89% of good quality sequences for downstream analysis. Analysis data indicates that individuals who suffer from oral cancer had much higher prevalence of phylum Actinobacteriota, Firmicutes_A, Campylobacterota, Fusobacteriota, and Patescibacteria. Total 298 species identify in current study, among this Leptotrichia (0.0015%), Prevotella (0.0041%), and Capnocytophaga (0.0052%) are predominant in oral cancer patients compare to healthy individuals. 23 species are absent in normal individuals and post-therapeutic patients but are dominant in oral cancer patients. The increased occurrence suggests a link between this group of bacteria and oral cancer. By comparing the abundance of alpha and beta microorganisms in patients with oral cancer to those in good health, the study highlights the importance of the oral microbial community in maintaining health and preventing disease. It also studies how habits like tobacco use affect microbial communities and how they can raise the risk of disease. In cancer patients, oxidative stress and glycolysis are enhanced, and while certain metabolic abnormalities recovered after therapy, many remain, showing the long-term impact of the illness and treatment. These data suggest that post-treatment microbial regeneration may not occur, increasing cancer recurrence risk. The study’s finding of microbial biomarkers, particularly those related to dysbiosis and changed tumor microenvironment, may inform oral cancer prognostic, therapeutic, and diagnostic methods. This metagenomic work contributes to a better understanding of how lifestyle factors influence microbial ecosystems, allowing lifestyle adjustments to lessen health risks associated with changes in microbial populations.