Oncotarget最新文献

Generative AI is revolutionizing oncological imaging, enhancing cancer detection and diagnosis. This editorial explores its impact on expanding datasets, improving image quality, and enabling predictive oncology. We discuss ethical considerations and introduce a unique perspective on personalized cancer screening using AI-generated digital twins. This approach could optimize screening protocols, improve early detection, and tailor treatment plans. While challenges remain, generative AI in oncological imaging offers unprecedented opportunities to advance cancer care and improve patient outcomes.

Artificial intelligence (AI) is revolutionizing society and healthcare, offering new possibilities for precision medicine. Immunotherapy in oncology (IO) has similarly transformed cancer treatment through novel mechanisms of therapeutic action, but has also led to atypical response patterns that challenge traditional methods for response evaluation. This editorial explores the role of AI in addressing these challenges through the development of new biomarkers for precise disease characterization, and in particular those built on imaging for the early response assessment of patients diagnosed with cancer and treated with IO. Properly leveraged AI-based techniques could herald a new era of precision medicine guided by non-invasive, imaging-based disease evaluation.

Despite advances in breast cancer screening and treatment, prognosis for metastatic disease remains dismal at 30% five-year survival. This is due, in large, to the failure of current therapeutics to target properties unique to metastatic cells. One of the drivers of metastasis is miR-10b, a small noncoding RNA implicated in cancer cell invasion, migration, viability, and proliferation. We have developed a nanodrug, termed MN-anti-miR10b, that delivers anti-miR-10b antisense oligomers to cancer cells. In mouse models of metastatic triple-negative breast cancer, MN-anti-miR10b has been shown to prevent onset of metastasis and eliminate existing metastases in combination with chemotherapy, even after treatment has been stopped. Recent studies have implicated miR-10b in conferring stem cell-like properties onto cancer cells, such as chemoresistance. In this study, we show transcriptional evidence that inhibition of miR-10b with MN-anti-miR10b activates developmental processes in cancer cells and that stem-like cancer cells have increased miR-10b expression. We then demonstrate that treatment of breast cancer cells with MN-anti-miR10b reduces their stemness, confirming that these properties make metastatic cells susceptible to the nanodrug actions. Collectively, these findings indicate that inhibition of miR-10b functions to impair breast cancer cell stemness, positioning MN-anti-miR10b as an effective treatment option for stem-like breast cancer subtypes.

The vacuolar H⁺-ATPase (V-ATPase) is an ATP-dependent proton pump that functions to control the pH of intracellular compartments as well as to transport protons across the plasma membrane of various cell types, including cancer cells. We have previously shown that selective inhibition of plasma membrane V-ATPases in breast tumor cells inhibits the invasion of these cells in vitro. We have now developed a nanobody directed against an extracellular epitope of the mouse V-ATPase c subunit. We show that treatment of 4T1-12B mouse breast cancer cells with this nanobody inhibits V-ATPase-dependent acidification of the media and invasion of these cells in vitro. We further find that injection of this nanobody into mice implanted with 4T1-12B cells orthotopically in the mammary fat pad inhibits metastasis of tumor cells to lung. These results suggest that plasma membrane V-ATPases represent a novel therapeutic target to limit breast cancer metastasis.

Colorectal cancer (CRC) is highly prevalent and is a major cause of cancer-related deaths worldwide. The incidence rate of CRC remains alarmingly high despite screening measures. The main curative treatment for CRC is a surgical resection of the diseased bowel segment. Postoperative complications usually involve a weakened gut barrier and a dissemination of bacterial proinflammatory lipopolysaccharides. Herein we discuss how gut microbiota and microbial metabolites regulate basal inflammation levels in the gut and the healing process of the bowel after surgery. We further elaborate on the restoration of the gut barrier function in patients with CRC and how this potentially impacts the dissemination and implantation of CRC cells in extracolonic tissues, contributing therefore to worse survival after surgery.

Overexpression of the secretory protein renalase-1 negatively impacts the survival of melanoma and pancreatic cancer patients, while inhibition of renalase-1 signaling drives tumor rejection by promoting T-cell activation. Thus, we investigated the chemical complementarity between melanoma-resident, T-cell receptor (TCR) complementarity-determining region 3 (CDR3) amino acid sequences (AAs) and the renalase-1 protein. Increasing complementarity of TCR CDR3s to renalase-1 AAs, as assessed by a chemical complementarity scoring algorithm, was associated with improved overall survival (OS) in melanoma patients. The expression levels of several immune signature genes were significantly, positively correlated with increasing TCR CDR3-renalase-1 complementarity scores. Additionally, the survival association observed with high complementarity of TCR CDR3s to renalase-1 AAs was more robust in cases with low renalase-1 gene expression levels. Mapping of TCR CDR3-renalase-1 in silico interaction sites identified major epitope candidates including RP220, the signaling module of the renalase-1 protein, consistent with the fact that a monoclonal antibody to RP220 is a potent inhibitor of melanoma growth. These findings indicate that renalase-1 is a potential antigen for TCR recognition in melanoma and could be considered as a target for immunotherapy.