Genome-wide transcriptomics and copy number profiling identify patient-specific CNV-lncRNA-mRNA regulatory triplets in colorectal cancer

Advances in Precision Medicine Approaches for Colorectal Cancer: From Molecular Profiling to Targeted Therapies

Precision medicine is transforming colorectal cancer treatment through the integration of advanced technologies and biomarkers, enhancing personalized and effective disease management. Identification of key driver mutations and molecular profiling have deepened our comprehension of the genetic alterations in colorectal cancer, facilitating targeted therapy and immunotherapy selection. Biomarkers such as microsatellite instability (MSI) and DNA mismatch repair deficiency (dMMR) guide treatment decisions, opening avenues for immunotherapy. Emerging technologies such as liquid biopsies, artificial intelligence, and machine learning promise to revolutionize early detection, monitoring, and treatment selection in precision medicine. Despite these advancements, ethical and regulatory challenges, including equitable access and data privacy, emphasize the importance of responsible implementation. The dynamic nature of colorectal cancer, with its tumor heterogeneity and clonal evolution, underscores the necessity for adaptive and personalized treatment strategies. The future of precision medicine in colorectal cancer lies in its potential to enhance patient care, clinical outcomes, and our understanding of this intricate disease, marked by ongoing evolution in the field. The current reviews focus on providing in-depth knowledge on the various and diverse approaches utilized for precision medicine against colorectal cancer, at both molecular and biochemical levels.

ncRS: A resource of non-coding RNAs in sepsis

Sepsis, a life-threatening condition triggered by the body's response to infection, presents a significant global healthcare challenge characterized by disarrayed host responses, widespread inflammation, organ impairment, and heightened mortality rates. This study introduces the ncRS database (http://www.ncrdb.cn), a meticulously curated repository housing 1144 experimentally validated non-coding RNAs (ncRNAs) intricately linked with sepsis. ncRS offers comprehensive RNA data, exhaustive experimental insights, and integrated annotations from diverse databases. This resource empowers researchers and clinicians to decipher ncRNAs' roles in sepsis pathogenesis, potentially identifying vital biomarkers for early diagnosis and prognosis, thus facilitating personalized treatments.

Identifying the prognosis implication, immunotherapy response prediction value, and potential targeted compound inhibitors of integrin subunit α3 (ITGA3) in human cancers

The integrin subunit α3 (ITGA3) is a member of the integrin alpha chain protein family, which could promote progression, metastasis, and invasion in some cancers. Still, its function in the tumor microenvironment (TME), cancer prognosis, and immunotherapy remains unclear. A multifaceted analysis of ITGA3 in pan-cancer utilizing various databases and online web tools revealed ITGA3 was aberrantly expressed in tumor tissues and upregulated in most cancers, which may be related to ITGA3 genomic alterations and methylation modification. In addition, ITGA3 was significantly correlated with the poor or better prognosis of cancer patients, immune-related pathways in hallmark, immune infiltration, and immune checkpoints, revealing a biological function of ITGA3 in the tumor progression, tumor microenvironment, and tumor immunity. We also found that ITGA3 could predict the response to tumor immunotherapy based on cytokine-treated samples and immunotherapy cohorts. ITGA3 may participate in shaping and regulating the tumor microenvironment to affect the tumor immune response, which was a promising immunotherapy response predictive biomarker and potential therapeutic target to work synergistically with cancer immunotherapy to boost the response and efficacy. Finally, potential targeted compound inhibitors and sensitive drugs were screened using databases ConnectivityMap (CMap) and CellMiner, and AutoDock Tools was used for molecular docking.