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This study aimed to investigate the role of the long non-coding RNA (lncRNA) LINC00342-207 (LINC00342) in the development and progression of primary hepatocellular carcinoma (HCC). Forty-two surgically resected HCC tissues and corresponding paracancerous tissues were collected from October 2019 to December 2020 and examined for lncRNA LINC00342, microRNA (miR)-19a-3p, miR-545-5p, miR-203a-3p, cell cycle protein D1 (CyclinD1/CCND1), murine double minute 2 (MDM2), and fibroblast growth factor 2 (FGF2) expression. The disease-free survival and overall survival of patients with HCC were followed up. HCC cell lines and the normal hepatocyte cell line HL-7702 were cultured and the expression level of LINC00342 was measured. HepG2 cells were transfected with LINC00342 siRNA, LINC00342 overexpression plasmid, miR-19a-3p mimics and their corresponding suppressors, miR-545-5p mimics and their corresponding suppressors, and miR-203a-3p mimics and their corresponding suppressors. The proliferation, apoptosis, migration, and invasion of HepG2 cells were detected. Stably transfected HepG2 cells were inoculated into the left axilla of male BALB/c nude mice, and the volume and quality of transplanted tumors as well as the expression levels of LINC00342, miR-19a-3p, miR-545-5p, miR-203a-3p, CCND1, MDM2, and FGF2 were examined. LINC00342 played an oncogenic role in HCC and exhibited inhibitory effects on proliferation, migration, and invasion, and promoted the apoptosis of HepG2 cells. Moreover, it inhibited the growth of transplanted tumors in vivo in mice. Mechanistically, the oncogenic effect of LINC00342 was associated with the targeted regulation of the miR-19a-3p/CCND1, miR-545-5p/MDM2, and miR-203a-3p/FGF2 axes.
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Background: The risk and prognosis of pancreatic cancer with lung metastasis (PCLM) are not well-defined. Thus, this study aimed to identify the risk and prognostic factors for these patients, and establish predictive nomogram models. Methods: Patients diagnosed with PCLM between 2010 and 2016 were identified from the Surveillance, Epidemiology, and End Results (SEER) database. Independent risk factors and prognostic factors were identified using logistic regression and Cox regression analyses. Nomograms were constructed to predict the risk and survival of PCLM, and the area under the curve (AUC), C-index, and calibration curve were used to determine the predictive accuracy and discriminability of the established nomogram, while the decision curve analysis was used to confirm the clinical effectiveness. Results: A total of 11287 cases with complete information were included; 601 (5.3%) patients with PC had lung metastases. Multivariable logistic analysis demonstrated that primary site, histological subtype, and brain, bone, and liver metastases were independent risk factors for lung metastases. We constructed a risk prediction nomogram model for the development of lung metastases among PC patients. The c-index of the established diagnostic nomogram was 0.786 (95%CI 0.726-0.846). Multivariable Cox regression analysis demonstrated that primary site, liver metastases, surgery, and chemotherapy were independent prognostic factors for both overall survival (OS) and cancer-specific survival (CSS), while bone metastases were independent prognostic factors for CSS. The C-indices for the OS and CSS prediction nomograms were 0.76 (95% CI 0.74-0.78) and 0.76 (95% CI 0.74-0.78), respectively. Based on the AUC of the receiver operating characteristic (ROC) analysis, calibration plots, and decision curve analysis (DCA), we concluded that the risk and prognosis model of PCBM exhibits excellent performance. Conclusions: The present study identified the risk and prognostic factors of PCLM and further established nomograms, which can help clinicians effectively identify high-risk patients and predict their clinical outcomes.
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PURPOSE: To validate the prognostic value and evaluate the predictive value of response to adjuvant chemotherapy of perineural invasion (PNI) in node-negative colon cancer using the National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER) 18 tumor registry database. METHODS: Patients diagnosed with colon cancer from the SEER database between January 1, 2010 and December 31, 2015 were identified. Chi-square analysis was performed to evaluate different demographic and clinical features of patients between PNI-negative (PNI (-)) and PNI-positive (PNI (+)) groups. Univariate and multivariate Cox proportional hazard regression models were built to examine the relationship of demographic and clinical features and survival outcomes with the hazard ratios (HRs) and 95% confidence intervals (CIs). RESULTS: In total, 57,255 node-negative colon cancer patients were extracted from the SEER database. The receipt of chemotherapy was not an independent prognostic factor for CSS in T3 colon cancer with or without the presence of PNI (P >0.05). The receipt of chemotherapy was independently associated with 34.0% decreased risk of cancer-specific mortality compared with those without the receipt of chemotherapy in T4 colon cancer without the presence of PNI (HR = 0.660, 95%CI = 0.559-0.779, P <0.001); the receipt of chemotherapy was independently associated with 36.0% decreased risk of cancer-specific mortality compared with those without the receipt of chemotherapy in T4 colon cancer with the presence of PNI (HR = 0.640, 95%CI = 0.438-0.935, P = 0.021). CONCLUSIONS: The present study demonstrated the poor prognosis of PNI (+) in both stage I and II colon cancer. However, the presence of PNI was not a predictive factor of response to adjuvant chemotherapy in node-negative colon cancer.