One major reason for the failure of advanced colorectal cancer (CRC) treatment is the occurrence of chemoresistance to fluoropyrimidine (FU)-based chemotherapy. Various reports showed that ectopic expression and function of microRNAs (miRNAs) played key roles to mediate apoptosis at the post-transcriptional level. To further explore the possible mechanisms, we evaluated the prognostic effect of miR-218 in patients with CRC receiving 5-FU-based treatment and investigated the proapoptotic role of miR-218 in vitro. Primary tumour specimens and adjacent non-tumour sites were used to determine miR-218 expression distribution and explore its potential prognostic value in response to 5-FU-based treatment in patients with CRC. HCT116 and HT29 cells were transfected with precursor miR-218 or negative control, followed by assays to investigate its influence on apoptosis, cell proliferation and pathways involved in molecular mechanisms of chemoresistance to 5-FU. Results showed that high miR-218 expression was associated with positive response to firstline 5-FU treatment in CRC patients. MiR-218 promoted apoptosis, inhibited cell proliferation and caused cell cycle arrest in CRC cells by suppressing BIRC5 expression. Furthermore, miR-218 enhanced 5-FU cytotoxicity in CRC cells by suppressing the 5-FU targeted enzyme, thymidylate synthase (TS). In conclusion, we demonstrated that high miR-218 expression had a positive prognostic value in 5-FU-based treatments for CRC patients and discovered a novel mechanism mediated by miR-218 to promote apoptosis and to function synergistically with 5-FU to promote chemosensitivity by suppressing BIRC5 and TS in CRC. These suggest the unique potential of miR-218 as a novel candidate for developing miR-218-based therapeutic strategies in CRC.
BackgroundPreoperative prediction of lymph node (LN) status is of crucial importance for appropriate treatment planning in patients with colorectal cancer (CRC). In this study, we sought to develop and validate a non-invasive nomogram model to preoperatively predict LN metastasis in CRC.MethodsDevelopment of the nomogram entailed three subsequent stages with specific patient sets. In the discovery set (n = 20), LN-status-related miRNAs were screened from high-throughput sequencing data of human CRC serum samples. In the training set (n = 218), a miRNA panel-clinicopathologic nomogram was developed by logistic regression analysis for preoperative prediction of LN metastasis. In the validation set (n = 198), we validated the above nomogram with respect to its discrimination, calibration and clinical application.FindingsFour differently expressed miRNAs (miR-122-5p, miR-146b-5p, miR-186-5p and miR-193a-5p) were identified in the serum samples from CRC patients with and without LN metastasis, which also had regulatory effects on CRC cell migration. The combined miRNA panel could provide higher LN prediction capability compared with computed tomography (CT) scans (P < .0001 in both the training and validation sets). Furthermore, a nomogram integrating the miRNA-based panel and CT-reported LN status was constructed in the training set, which performed well in both the training and validation sets (AUC: 0.913 and 0.883, respectively). Decision curve analysis demonstrated the clinical usefulness of the nomogram.InterpretationOur nomogram is a reliable prediction model that can be conveniently and efficiently used to improve the accuracy of preoperative prediction of LN metastasis in patients with CRC.
Necroptosis is a newly identified programmed cell death associated with the biological process of various cancers, including esophageal carcinoma (ESCA). Meanwhile, the dysregulation of long non-coding RNAs (lncRNAs) is greatly implicated in ESCA progression and necroptosis regulation. However, the lncRNAs involved in regulating necroptosis in ESCA are still unclear. In this study, we aim to explore the expression profile of necroptosis-related lncRNAs (NRLs), and evaluate their roles in ESCA prognosis and treatment. In the present study, 198 differentially expressed NRLs were identified between the ESCA and adjacent normal tissues through screening the data extracted from the Cancer Genome Atlas (TCGA) database. And, a prognostic panel consisting of 6 NRLs was constructed using the LASSO algorithm and multivariate Cox regression analysis. The ESCA patients with high risks had a markedly reduced survival time and higher mortality prevalence. Moreover, C-index of 6 NRLs-panel was superior to 48 published prognostic models based on lncRNAs or mRNAs for ESCA. There were significant differences between the high-risk and low-risk groups in tumor-related pathways, genetic mutations, and drug sensitivity responses. In vitro analysis revealed that inhibition of PVT1 impeded the proliferation, migration, and colony formation of ESCA cells, increased the expressions of p-RIP1 and p-MLKL and promoted necroptosis. By contrast, PVT1 overexpression resulted in a decrease in necroptotic cell death events, thus promoting tumor progression. Collectively, the established 6-NRLs panel was a promising biomarker for the prognostic prediction of ESCA. Moreover, our current findings provided potential targets for individualized therapy for ESCA patients.
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