In this scoping review, we delve into the transformative potential of artificial intelligence (AI) in addressing challenges inherent in whole-genome sequencing (WGS) analysis, with a specific focus on its implications in oncology. Unveiling the limitations of existing sequencing technologies, the review illuminates how AI-powered methods emerge as innovative solutions to surmount these obstacles. The evolution of DNA sequencing technologies, progressing from Sanger sequencing to next-generation sequencing, sets the backdrop for AI’s emergence as a potent ally in processing and analyzing the voluminous genomic data generated. Particularly, deep learning methods play a pivotal role in extracting knowledge and discerning patterns from the vast landscape of genomic information. In the context of oncology, AI-powered methods exhibit considerable potential across diverse facets of WGS analysis, including variant calling, structural variation identification, and pharmacogenomic analysis. This review underscores the significance of multimodal approaches in diagnoses and therapies, highlighting the importance of ongoing research and development in AI-powered WGS techniques. Integrating AI into the analytical framework empowers scientists and clinicians to unravel the intricate interplay of genomics within the realm of multi-omics research, paving the way for more successful personalized and targeted treatments.

Disulfidptosis, a new form of programmed cell death, plays a role in multiple types of cancer. However, research on disulfidptosis in glioma is lacking. A disulfidptosis‐associated risk score was constructed using Cox regression modelling, while LASSO regression was applied for feature selection. To explore the relationship between the risk score and the immune microenvironment, we employed CIBERSORT, ssGSEA and ESTIMATE algorithms. Additionally, wet lab experiments were conducted to validate the functional role of the key disulfidptosis gene RPN1, demonstrating its ability to promote glioma cell proliferation and migration. Disulfidptosis genes were significantly upregulated in gliomas, influencing clinical features and survival. The risk score effectively predicted OS and varied among clinical subgroups. High‐risk scores correlated with tumour growth, invasion and immunosuppression. Patients with different risk scores showed distinct immune cell infiltration patterns. Most immune checkpoints and chemokines were positively associated with risk scores. Laboratory findings confirmed that RPN1 significantly promoted glioma cell proliferation and migration. Disulfidptosis‐based risk assessment stratifies glioma prognosis and reveals immune microenvironment characteristics, offering insights for personalised treatment strategies.

Transient receptor potential (TRP) channels are strongly associated with colon cancer development and progression. This study leveraged a multivariate Cox regression model on publicly available datasets to construct a TRP channels-associated gene signature, with further validation of signature in real world samples from our hospital treated patient samples. Kaplan-Meier (K-M) survival analysis and receiver operating characteristic (ROC) curves were employed to evaluate this gene signature’s predictive accuracy and robustness in both training and testing cohorts, respectively. Additionally, the study utilized the CIBERSORT algorithm and single-sample gene set enrichment analysis to explore the signature’s immune infiltration landscape and underlying functional implications. The support vector machine algorithm was applied to evaluate the signature’s potential in predicting chemotherapy outcomes. The findings unveiled a novel three TRP channels-related gene signature (MCOLN1, TRPM5, and TRPV4) in colon adenocarcinoma (COAD). The ROC and K-M survival curves in the training dataset (AUC = 0.761; p = 1.58e-05) and testing dataset (AUC = 0.699; p = 0.004) showed the signature’s robust predictive capability for the overall survival of COAD patients. Analysis of the immune infiltration landscape associated with the signature revealed higher immune infiltration, especially an increased presence of M2 macrophages, in high-risk group patients compared to their low-risk counterparts. High-risk score patients also exhibited potential responsiveness to immune checkpoint inhibitor therapy, evident through increased CD86 and PD-1 expression profiles. Moreover, the TRPM5 gene within the signature was highly expressed in the chemoresistance group (p = 0.00095) and associated with poor prognosis (p = 0.036) in COAD patients, highlighting its role as a hub gene of chemoresistance. Ultimately, this signature emerged as an independent prognosis factor for COAD patients (p = 6.48e-06) and expression of model gene are validated by public data and real-world patients. Overall, this bioinformatics study provides valuable insights into the prognostic implications and potential chemotherapy resistance mechanisms associated with TRPs-related genes in colon cancer.

ARPC1B⁺ cancer stem cells (CSCs) in pancreatic cancer are identified as a subpopulation resistant to gemcitabine. In our study, drug repositioning, molecular docking, and surface plasmon resonance (SPR) technique jointly revealed that CK-636 can directly target ARPC1B protein with high affinity. In vitro cytotoxicity, ex vivo organoid cultures, in vivo xenograft and orthotopic gemcitabine-resistant pancreatic cancer model demonstrated that combination therapy of gemcitabine plus CK-636 showed a superior anti-tumor effect compared with gemcitabine monotherapy. Our study demonstrated that CK-636 can act as a rational adjuvant to overcome gemcitabine resistance in pancreatic cancer therapy.

Reperfusion therapy is the mainstay of treatment for ischemic stroke (IS) but frequently exacerbates secondary injury. Following cerebral ischemia and hypoxia, lactate accumulates markedly. Traditionally regarded as a metabolic byproduct, lactate has gained new significance with the discovery of protein lactylation. In addition to experimental evidence, recent computational models have been developed to predict potential proteins and sites of lactylation. Nevertheless, the roles of lactate and lactylation in cerebral ischemia reperfusion (I/R) injury remain unclear and even controversial. Current studies suggest that ischemic and reperfusion phases differ in their pathological changes, and accumulating evidence indicates that non‐histone lactylation may aggravate injury. Proposed mechanisms include the promotion of neuronal death, exacerbation of neuroinflammation, modulation of mitochondrial function, and alteration of angiogenesis. Furthermore, potential crosstalk between lactylation and other post‐translational modifications, whether synergistic or antagonistic, may influence disease progression, yet such interactions in cerebral I/R injury have not been systematically investigated. Current strategies to modulate lactylation include targeting lactate levels, lactate dehydrogenase, transporters, and modifying enzymes. This review summarizes multiple factors influencing non‐histone lactylation and discusses potential intervention strategies, highlighting their advantages and limitations and providing new perspectives for the treatment of cerebral I/R injury.

Purpose: This study comprehensively analyzed the global clinical trials and depicted a landscape for non-alcoholic fatty liver disease (NAFLD) therapy. Methods: Using the Trialtrove database, we collected trial information of 2242 clinical trials. Using molecular docking analysis, we investigated the pharmacological properties of glucagon-like peptide-1 receptor (GLP-1R) agonist such as semaglutide and its binding affinity to GLP-1R protein. Based on the transcriptome data of NAFLD-related datasets, we analyzed the expression profile of GLP-1R across healthy liver and NAFLD samples. Results: Our clinical trial landscape revealed significant geographic disparities in NAFLD trials, with the US and China leading globally with 488 and 384 trials respectively. Phase IV accounted for the largest proportion (34.10%) among all trials. Among all the NAFLD-related agents, GLP-1R agonists were the most frequently used. In addition, GLP-1R was significantly and widely downregulated in NAFLD, especially in advanced stages such as non-alcoholic steatohepatitis. Conclusion: This study offers some valuable insights into the current status and future prospects of NAFLD clinical trials.