The rapid development of high-throughput sequencing has generated large volumes of cross-sectional cancer genomic data, providing an important basis for studying tumor evolution. Reconstructing cancer progression from these static observations, however, remains challenging because temporal information is not directly observed and because genomic and multi-omics measurements are affected by biological heterogeneity and technical noise. This review examines three linked components: cross-sectional cancer genomic data, mutational-signature-based cancer progression inference, and clonal-evolution-based cancer progression inference. We compare the biological assumptions, data requirements, inferential targets, sources of uncertainty, validation strategies, and clinical applicability of these approaches, and discuss how single-cell and spatial technologies can complement cross-sectional inference. Rather than treating inferred trajectories as direct observations of tumor history, we emphasize the conditions under which evolutionary information can be extracted from cross-sectional data and the limitations that remain. We further distinguish established methodological evidence from emerging clinical applications, with the aim of clarifying current capabilities and priorities for future inference of cancer progression.
Abstract: Cervical cancer, primarily caused by high-risk human papillomavirus (HPV) strains, remains a significant global health concern. Conventional treatments, such as chemotherapy, radiotherapy, and surgery, have notable limitations and side effects, prompting the search for safer alternatives. Plant-derived phytochemicals have shown promise as natural bioactive compounds in cervical cancer therapy. This review highlights an integrative approach that combines in silico modeling, in vitro assays, and in vivo animal studies to assess the anticancer potential of these compounds. In silico methods, including molecular docking and virtual screening, have been used to identify compounds that target HPV oncoproteins and related cellular pathways. In vitro studies have demonstrated that phytochemicals, such as apigenin, luteolin, berberine, curcumin, and epigallocatechin-3- gallate, inhibit cervical cancer cell growth, induce apoptosis, and modulate signaling pathways in a dose-dependent manner. In vivo xenograft models further validated the antitumor efficacy of these compounds. This combined strategy accelerates the development of natural product-based therapies, reduces costs, and enhances translational success. Future research should focus on improving in silico predictive accuracy, employing more physiologically relevant in vitro models, optimizing delivery systems, exploring synergistic combinations, and identifying candidates for clinical trials. Utilizing natural inhibitors can result in safer and more effective therapies to alleviate the global impact of cervical cancer.
Abstract: Cancer genomics has transformed the field of oncology, with cancer now considered a highly heterogeneous and genetically complex disease driven by a variety of somatic and germline alterations. This complexity, which includes mutations in oncogenes and tumor suppressor genes, often undermines conventional therapies and leads to drug resistance and relapse, underscoring the critical need for precision medicine. CRISPR-Cas9 system is a revolutionary gene-editing technology that can overcome these challenges by allowing for precise, efficient, and programmable genome modification. Here, the study reviews the different applications of CRISPR-Cas9 in cancer research and therapy. It highlights its foundational role in creating advanced in vitro and in vivo cancer models, enabling the accurate reproduction of tumor biology and the performance of mechanistic studies. Also discussed is the utility of CRISPR-based functional genomic screens to identify novel therapeutic targets and resistance mechanisms. Therapeutically, CRISPR-Cas9 provides promising strategies such as direct gene modification for oncogene inactivation, tumor suppressor restoration, and reversal of multidrug resistance. The most advanced clinical application of it is in immunotherapy, especially the engineering of improved CAR-T cells and other immune effectors. In addition, CRISPR-targeted tumor microenvironment and oncogenic virus offer new strategies for cancer treatment. The problems of off-target effects, delivery challenges, and ethical concerns are serious obstacles despite its enormous potential. Progress in delivery systems and genome-editing precision, as well as in clinical trials, continues to advance CRISPR-Cas9 to become part of routine oncology practice, and to drive forward the paradigm of personalized cancer therapy.
Nanostructured lipid carriers (NLCs) are revolutionary lipid-based drug delivery systems composed of biocompatible solid and liquid lipids combined with surfactants and co-surfactants. Their structural flexibility and favourable safety profile have supported their increasing use in nanotechnology for the delivery of a broad range of therapeutic agents. Newly, the application of artificial intelligence (AI) in NLC-based drug delivery has been revealed as an approach to advance formulation design and aiming competence in colon cancer treatment. Machine learning and predictive modelling methodologies allow organized analysis of formulation variables and assistance in forecasting carrier performance. NLCs, classified as second-generation lipid carriers, are entering the market to overcome the issues of solid lipid nanoparticles (SLNs), such as low drug loading and drug leakage during storage. Although initially investigated primarily for lipophilic drugs, subsequent research has demonstrated their suitability for hydrophilic compounds. Their high biocompatibility and low immunogenicity further support their use in safe drug delivery applications. This review scrutinizes the considerations behind formulation design, various structural features, and manufacturing procedures of NLCs, with prominence on their benefits over earlier lipid-based carriers. In addition, therapeutic applications are précised, and the prospective role of AI-assisted formulation approaches in improving directing accuracy and therapeutic results in colon cancer is discussed.
Abstract: Breast cancer is one of the most common cancers in women worldwide. Compared to its incidence, the cure rate remains relatively low. Various treatment methods, such as radiotherapy and chemotherapy, are available but often involve severe toxicity and limited curability. Recent research has shown that NDDS formulations can selectively target breast cancer cells without damaging surrounding tissues or organs. This comprehensive review provides details on nanocarriers and their loaded delivery systems as effective strategies for breast cancer treatment. Anti-neoplastic agents and phytoconstituents are often combined and formulated into nanocarrier systems to enhance solubility, increase half-life and biodistribution, and reduce adverse effects and immunogenicity. This review highlights the necessity and advantages of nanocarriers and their formulations as potential next-generation tools for safe, preventive, and maximally effective breast cancer therapy. Additionally, it provides an updated synthesis of nanocarrier-based approaches, focusing on recent clinical and preclinical innovations in drug delivery, diagnostics, and personalized medicine.
