DNA

Human papillomavirus (HPV) infection is a leading cause of cervical cancer and a significant contributor to anogenital and oropharyngeal malignancies worldwide. While the oncogenic functions of HPV oncoproteins E6 and E7 in disrupting nuclear tumor suppressor pathways are well established, their influence on mitochondrial biology has only recently emerged as a critical facet of HPV-driven carcinogenesis. This review synthesizes current evidence on the qualitative and quantitative alterations of mitochondrial DNA (mtDNA) and their functional consequences in HPV-associated cancers. We discuss how E6 and E7 modulate mitochondrial dynamics, bioenergetics, and redox balance, contributing to metabolic reprogramming, resistance to apoptosis, and adaptation to tumor microenvironmental stress. We also examine the clinical significance of mtDNA mutations, deletions, and copy number variations as potential biomarkers for diagnosis, prognosis, and therapy response. Advances in multi-omics approaches, high-throughput sequencing, and patient-derived organoid models have accelerated the exploration of mitochondria as therapeutic targets. Integrating mitochondrial profiling into HPV-related cancer research holds promise for identifying novel metabolic vulnerabilities and guiding the development of mitochondria-directed treatment strategies.

This review aims to provide a broad, multidisciplinary perspective on how dynamic genomics and systems biology are transforming modern healthcare, with a focus on cancer especially liver cancer (HCC). It explains how integrating multi-omics technologies such as genomics, transcriptomics, proteomics, interactomics, metabolomics, and spatial transcriptomics deepens our understanding of the complex tumor environment. These innovations enable precise patient stratification based on molecular, spatial, and functional tumor characteristics, allowing for personalized treatment plans. Emphasizing the role of regulatory networks and cell-specific pathways, the review shows how mapping these networks using multi-omics data can predict resistance, identify therapeutic targets, and aid in the development of targeted therapies. The approach shifts from standard, uniform treatments to flexible, real-time strategies guided by technologies such as liquid biopsies and wearable biosensors. A case study showcases the benefits of personalized therapy, which integrates epigenetic modifications, checkpoint inhibitors, and ongoing multi-omics monitoring in a patient with HCC. Future innovations, such as cloud-based genomic ecosystems, federated learning for privacy, and AI-driven data analysis, are also discussed to enhance decision-making and outcomes. The review underscores a move toward predictive and preventive healthcare by integrating layered data into clinical workflows. It reviews ongoing clinical trials using advanced molecular and immunological techniques for HCC. Overall, it promotes a systemic, technological, and spatial approach to cancer treatment, emphasizing the importance of experimental, biochemical–functional, and biophysical data-driven insights in personalizing medicine.

Familial cancers are caused by inherited mutations in specific genes that regulate cell growth, division, and repair. Approximately 5–10% of all cancer cases have a hereditary component, where germline mutations in certain genes increase an individual’s susceptibility to developing cancer. Two major categories of genes are involved in cancer development: tumour suppressor genes and oncogenes. Both play critical roles in regulating normal cell behaviour, and when mutated, they can contribute to uncontrolled cell proliferation and tumour formation. In addition to genetic mutations, epigenetic alterations also play a significant role in familial cancer. Epigenetics refers to changes in gene expression due to DNA methylation, histone modifications, and the dysregulation of non-coding RNAs without alter the underlying DNA sequence. Familial cancer syndromes follow various inheritance patterns, including autosomal dominant, autosomal recessive, X-linked, and mitochondrial inheritance, each with distinct characteristics. Identifying genetic mutations associated with familial cancers is a cornerstone of genetic counselling, which helps individuals and families navigate the complex intersection of genetics, cancer risk, and prevention. Early identification of mutations enables personalized strategies for risk reduction, early detection, and, when applicable, targeted treatment options, ultimately improving patient outcomes.