Cancer remains among the most complex diseases of the modern era, responsible for approximately 10 million deaths annually worldwide. This paper presents original computational and literature-based analysis of the cellular and molecular mechanisms underlying five major human cancers — breast, lung, colorectal, prostate, and leukaemia — using systematic analysis of publicly available genomic databases (TCGA, COSMIC, cBioPortal) and Python-based computational modelling. Key oncogenic drivers, tumour suppressor inactivation, metastatic mechanisms, and tumour growth kinetics are characterised and compared across cancer types. Mathematical models of tumour growth (exponential, logistic, Gompertz) are fitted against literature-derived data, with the Gompertz model achieving the strongest fit (R²=0.97). Treatment strategies including targeted molecular therapy and immune checkpoint inhibition are evaluated against their molecular drivers. Principal findings confirm that TP53 inactivation and PI3K/AKT/mTOR dysregulation are the most prevalent pan-cancer molecular vulnerabilities, and that microsatellite instability-high (MSI-H) status is a pan-cancer biomarker for checkpoint immunotherapy responsiveness
Emaan Azam Warsi (Tue,) studied this question.