Artificial intelligence methods available for cancer research

Cancer is a heterogeneous and multifaceted disease with a significant global footprint.Despite substantial technological advancements for battling cancer,early diagnosis and selection of effective treatment remains a challenge.With the convenience of large-scale datasets including multiple levels of data,new bioinformatic tools are needed to transform this wealth of information into clinically useful decision-support tools.In this field,artificial intelligence(AI)technologies with their highly diverse applications are rapidly gaining ground.Machine learning methods,such as Bayesian networks,support vector machines,decision trees,random forests,gradient boosting,and K-nearest neighbors,including neural network models like deep learning,have proven valuable in predictive,prognostic,and diagnostic studies.Researchers have recently employed large language models to tackle new dimensions of problems.However,leveraging the opportunity to utilize AI in clinical settings will require surpassing significant obstacles—a major issue is the lack of use of the available reporting guidelines obstructing the reproducibility of published studies.In this review,we discuss the applications of AI methods and explore their benefits and limitations.We summarize the available guidelines for AI in healthcare and highlight the potential role and impact of AI models on future directions in cancer research.

RIP140 regulates POLK gene expression and the response to alkylating drugs in colon cancer cells

Aim:The transcription factor RIP140(receptor interacting protein of 140 kDa)is involved in intestinal tumorigenesis.It plays a role in the control of microsatellite instability(MSI),through the regulation of MSH2 and MSH6 gene expression.The aim of this study was to explore its effect on the expression of POLK,the gene encoding the specialized translesion synthesis(TLS)DNA polymeraseκknown to perform accurate DNA synthesis at microsatellites.Methods:Different mouse models and engineered human colorectal cancer(CRC)cell lines were used to analyze by RT-qPCR,while Western blotting and luciferase assays were used to elucidate the role of RIP140 on POLK gene expression.Published DNA microarray datasets were reanalyzed.The in vitro sensitivity of CRC cells to methyl methane sulfonate and cisplatin was determined.Results:RIP140 positively regulates,at the transcriptional level,the expression of the POLK gene,and this effect involves,at least partly,the p53 tumor suppressor.In different cohorts of CRC biopsies(with or without MSI),a strong positive correlation was observed between RIP140 and POLK gene expression.In connection with its effect on POLK levels and the TLS function of this polymerase,the cellular response to methyl methane sulfonate was increased in cells lacking the Rip140 gene.Finally,the association of RIP140 expression with better overall survival of CRC patients was observed only when the corresponding tumors exhibited low levels of POLK,thus strengthening the functional link between the two genes in human CRC.Conclusion:The regulation of POLK gene expression by RIP140 could thus contribute to the maintenance of microsatellite stability,and more generally to the control of genome integrity.