Identification of Comprehensive Biomarkers in Patients With Mismatch Repair-Deficient Colon Adenocarcinoma Based on Parallel Multiomics.

Immunocheckpoint inhibitors have shown impressive efficacy in patients with colon cancer and other types of solid tumor that are mismatch repair-deficient (dMMR). Currently, PCR-capillary electrophoresis is one of the mainstream detection methods for dMMR, but its accuracy is still limited by germline mismatch repair (MMR) mutations, the functional redundancy of the MMR system, and abnormal methylation of MutL Homolog 1 promoter. Therefore, this study aimed to develop new biomarkers for dMMR based on artificial intelligence (AI) and pathologic images, which may help to improve the detection accuracy. To screen for the differential expression genes (DEGs) in dMMR patients and validate their diagnostic and prognostic efficiency, we used the expression profile data from the Cancer Genome Atlas (TCGA). The results showed that the expression of Immunoglobulin Lambda Joining 3 in dMMR patients was significantly downregulated and negatively correlated with the prognosis. Meanwhile, our diagnostic models based on pathologic image features showed good performance with area under the curves (AUCs) of 0.73, 0.86, and 0.81 in the training, test, and external validation sets (Jiangsu Traditional Chinese Medicine Hospital cohort). Based on gene expression and pathologic characteristics, we developed an effective prognosis model for dMMR patients through multiple Cox regression analysis (with AUC values of 0.88, 0.89, and 0.88 at 1-, 3-, and 5-year intervals, respectively). In conclusion, our results showed that Immunoglobulin Lambda Joining 3 and nucleus shape-related parameters (such as nuclear texture, nuclear eccentricity, nuclear size, and nuclear pixel intensity) were independent diagnostic and prognostic factors, suggesting that they could be used as new biomarkers for dMMR patients.

Melatonin Suppresses Neuropathic Pain via MT2-Dependent and -Independent Pathways in Dorsal Root Ganglia Neurons of Mice.

Melatonin (Mel) and its receptors (MT1 and MT2) have a well-documented efficacy in treating different pain conditions. However, the anti-nociceptive effects of Mel and Mel receptors in neuropathic pain (NP) are poorly understood. To elucidate this process, pain behaviors were measured in a dorsal root ganglia (DRG)-friendly sciatic nerve cuffing model. We detected up-regulation of MT2 expression in the DRGs of cuff-implanted mice and its activation by the agonist 8-M-PDOT (8MP). Also, Mel attenuated the mechanical and thermal allodynia induced by cuff implantation. Immunohistochemical analysis demonstrated the expression of MT2 in the DRG neurons, while MT1 was expressed in the satellite cells. In cultured primary neurons, microarray analysis and gene knockdown experiments demonstrated that MT2 activation by 8MP or Mel suppressed calcium signaling pathways via MAPK1, which were blocked by RAR-related orphan receptor alpha (RORα) activation with a high dose of Mel. Furthermore, expression of nitric oxide synthase 1 (NOS1) was down-regulated upon Mel treatment regardless of MT2 or RORα. Application of Mel or 8MP in cuff-implanted models inhibited the activation of peptidergic neurons and neuro-inflammation in the DRGs by down-regulating c-fos, calcitonin gene-related peptide [CGRP], and tumor necrosis factor-1α [TNF-1α] and interleukin-1ß [IL-1ß]. Addition of the MT2 antagonist luzindole blocked the effects of 8MP but not those of Mel. In conclusion, only MT2 was expressed in the DRG neurons and up-regulated upon cuff implantation. The analgesic effects of Mel in cuff-implanted mice were closely associated with both MT2-dependent (MAPK-calcium channels) and MT2-independent (NOS1) pathways in the DRG.