BackgroundBlocking the programmed death protein 1 (PD-1)/programmed death-ligand 1 (PD-L1) pathway in hepatocellular carcinoma (HCC) is a very promising approach in immunotherapy. However, the correlation and prognostic values of serum soluble PD-1 and PD-L1 (sPD-1/sPD-L1) have not been explored conjointly in HCC patients.MethodsThis study retrospectively included 120 HCC patients receiving radical resection. The serum levels of sPD-1/sPD-L1 and inflammatory cytokines were measured by antibody array assay. Immunohistochemistry was applied to assess both the expression of membrane-bound PD-L1, and the number of CD4+ tumor-infiltrating lymphocytes (TILs) and CD8+ TILs.ResultsThe best cut-off values of sPD-1 and sPD-L1 for predicting disease-free survival (DFS) were 33.0 µg/ml and 11.2 µg/ml, respectively. Multivariable analysis showed that sPD-L1 was a negative independent prognostic factor [DFS, Hazard Ratio (HR) 2.58, 95% CI 1.14–5.84, P = 0.023; overall survival (OS), HR 1.77, 95% CI 1.01–3.12, P = 0.048], while sPD-1 was a favorable independent prognostic factor (DFS, HR 0.32, 95% CI 0.14–0.74, P = 0.007; OS, HR 0.54, 95% CI 0.30–0.98, P = 0.044) in HCC patients. We also observed some similar associations between inflammatory cytokines (IL-10, IL-17, TNF-α) and sPD-1 or sPD-L1, as well as a close positive association between sPD-1 and sPD-L1. No significant associations of sPD-1/sPD-L1 with either intra-tumoral PD-L1 expression, or the numbers of CD4+ TILs and CD8+ TILs were determined.ConclusionsOur findings indicate that sPD-1 and sPD-L1 are independent prognostic factors with opposite prognostic roles in predicting both DFS and OS in HCC patients.Electronic supplementary materialThe online version of this article (10.1007/s00262-018-2271-4) contains supplementary material, which is available to authorized users.
Background. The current M1 stage in nasopharyngeal carcinoma (NPC) does not differentiate patients based on metastatic site and number of metastases. This study aims to subdivide the M1 stage of NPC patients with bone-only metastases and to identify the patients who may benefit from combined chemoradiotherapy (CRT). Methods. Between 1998 and 2007, 312 patients diagnosed with bone-only metastasis at Sun Yat-sen University Cancer Center were enrolled.Various possible subdivisions of M1 stage were considered, including by the time order of metastasis (synchronous vs. metachronous), involvement of specific bone metastatic site, the number of metastatic sites, and the number of metastases. The correlation of the subdivisions of M1 stage with overall survival (OS) was determined by Cox regression. Results. The median OS was 23.4 months. Patients with more than three metastatic sites had significantly poorer OS than patients with three or fewer metastatic sites (16.2 vs. 32.4
Background: An accumulating body of evidence suggests that long non-coding RNAs (lncRNAs) can serve as potential cancer prognostic factors. However, the utility of lncRNA combinations in estimating overall survival (OS) for hepatocellular carcinoma (HCC) remains to be elucidated. This study aimed to construct a powerful lncRNA signature related to the OS for HCC to enhance prognostic accuracy. Methods: The expression patterns of lncRNAs and related clinical data of 371 HCC patients were obtained based on The Cancer Genome Atlas (TCGA). Differentially expressed lncRNAs (DElncRNAs) were acquired by comparing tumors with adjacent normal samples. lncRNAs displaying significant association with OS were screened through univariate Cox regression analysis and the least absolute shrinkage and selection operator (LASSO) algorithm. All cases were classified into the validation or training group at the ratio of 3:7 to validate the constructed lncRNA signature. Data from the Gene Expression Omnibus (GEO) were used for external validation. We conducted real-time polymerase chain reaction (PCR) and assays for Transwell invasion, migration, CCK-8, and colony formation to determine the biological roles of lncRNA. Gene set enrichment analysis (GSEA) of the lncRNA model risk score was also conducted. Results: We identified 1292 DElncRNAs, among which 172 were significant in univariate Cox regression analysis. In the training group (n = 263), LASSO regression analysis confirmed 11 DElncRNAs including AC010547.1, AC010280.2, AC015712.7, GACAT3 (gastric cancer associated transcript 3), AC079466.1, AC089983.1, AC051618.1, AL121721.1, LINC01747, LINC01517, and AC008750.3. The prognostic risk score was calculated, and the constructed risk model showed significant correlation with HCC OS (log-rank P-value of 8.489e-9, hazard ratio of 3.648, 95% confidence interval: 2.238-5.945). The area under the curve (AUC) for this lncRNA model was up to 0.846. This risk model was confirmed in the validation group (n = 108), the entire cohort, and the external GEO dataset (n = 203). GACAT3 was highly expressed in HCC tissues and cell lines. Based on online databases, GACAT3 expression independently affects both Li et al. Prognostic lncRNA Signature for HCC OS and disease-free survival in HCC patients. Silencing GACAT3 in vitro significantly suppressed HCC cell proliferation, invasion, and migration. Moreover, pathways related to the lncRNA model risk score were confirmed by GSEA. Conclusion: The lncRNA signature established in this study can be used to predict HCC prognosis, which could provide novel clinical evidence to guide targeted HCC treatment.
Purpose: To establish a useful prognostic nomogram to predict long-term overall survival for patients with tongue squamous cell carcinoma (TSCC) after R0 resection.Patients and Methods: The nomogram was developed using a retrospective cohort of 235 TSCC patients from Sun Yat-sen University Cancer Center between 1 January 2000 and 31 December 2007. An independent dataset of 223 patients was used for external validation. Multivariate Cox proportional hazards model (backward selection; the Akaike information criteria) was applied to select variables for construction of the nomogram. Discrimination and calibration were performed using the area under the receiver operating characteristic (ROC) curve (AUC) and calibration plots.Results: Using the backward selection of clinically-relevant variables, depth of invasion (hazard ratio [HR], 3.55; P < 0.001), pN (HR, 3.48; P = 0.01), age (HR, 1.03; P < 0.01) and neck dissection (HR, 0.53; P = 0.04) were selected as independent predictive factors of survival. A nomogram was thus established to predict survival of TSCC patients after R0 resection. The calibration curve demonstrated that the nomogram was able to accurately predict 5-year overall survival (OS). In addition, our data showed the AUC of the nomogram were 0.78 and 0.71 based on the internal and external validation, which were significantly better than the 7th TNM stage (0.64/0.55).Conclusion: The proposed nomogram resulted in accurate prognostic prediction of the 5-year OS for TSCC patients with R0 resection.
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