Comput Biol Med. 2025 Nov;198(Pt A):111120. doi: 10.1016/j.compbiomed.2025.111120. Epub 2025 Sep 29.

ABSTRACT

Cancer is a leading, highly complex, and deadly disease that has become a major concern in modern medicine. Hepatocellular carcinoma is the most common primary liver cancer and a leading cause of global cancer mortality. Its development is predominantly associated with chronic liver diseases such as hepatitis B and C infections, cirrhosis, alcohol consumption, and non-alcoholic fatty liver disease. Molecular mechanisms underlying HCC involve genetic mutations, epigenetic changes, and disrupted signalling pathways, including Wnt/β-catenin and PI3K/AKT/mTOR. Early diagnosis remains challenging, as most cases are detected at advanced stages, limiting curative treatment options. Diagnostic advancements, including biomarkers like alpha-fetoprotein and cutting-edge imaging techniques such as CT, MRI, and ultrasound-based radiomics, have improved early detection. Treatment strategies depend on the disease stage, ranging from curative options like surgical resection and liver transplantation to palliative therapies, including transarterial chemoembolization, systemic therapies, and immunotherapy. Immune checkpoint inhibitors targeting PD-1/PD-L1 and CTLA-4 have shown promise for advanced HCC. In this review we discuss about emerging technologies, including artificial intelligence and multi-omics platforms for HCC management by enhancing diagnostic accuracy, identifying novel therapeutic targets, and enabling personalized treatments. Despite these advancements, the prognosis for HCC patients remains poor, underscoring the need for continued research into early detection, innovative therapies, and translational applications to effectively address this global health challenge.

PMID:41027344 | DOI:10.1016/j.compbiomed.2025.111120

Nat Rev Clin Oncol. 2025 Oct 3. doi: 10.1038/s41571-025-01077-z. Online ahead of print.

ABSTRACT

Patients with advanced-stage pancreatic ductal adenocarcinoma (PDAC) predominantly receive chemotherapy, and despite initial responses in some patients, most will have disease progression and often dismal outcomes. This lack of clinical effectiveness partly reflects not only cancer cell-intrinsic factors but also the presence of a tumour microenvironment (TME) that precludes access of both systemic therapies and circulating immune cells to the primary tumour, as well as supporting the growth of PDAC cells. Combined with improved preclinical models of PDAC, advances in single-cell spatial multi-omics and machine learning-based models have provided novel methods of untangling the complexities of the TME. In this Review, we focus on the desmoplastic stroma and both the intratumoural and intertumoural heterogeneity of PDAC, with an emphasis on cancer-associated fibroblasts and their surrounding immune cell niches. We describe new approaches in converting the immunologically 'cold' PDAC TME into a 'hot' TME by priming T cell activation, overcoming T cell exhaustion and unravelling myeloid cell-mediated immunosuppression. Furthermore, we explore integrated targets involving the TME, such as points of convergence among tumour, stromal and immune cell metabolism as well as oncogenic KRAS signalling. Finally, building on our experience with failed clinical trials in the past, we consider how this evolving comprehensive understanding of the TME will ensure future success in developing more effective therapies for patients with PDAC.

PMID:41044427 | DOI:10.1038/s41571-025-01077-z