Platelet-lymphocyte ratio predicts chemotherapy response and prognosis in patients with gastric cancer undergoing radical resection.

Background: Amounting literatures have reported the significance of systemic inflammatory markers for evaluating tumor prognosis. But few studies have systematically compared their superiority and their impact on adjuvant chemotherapy. Aims: We aimed to investigate the ability of inflammatory markers to predict the efficacy of chemotherapy in GC patients undergoing radical therapy and to identify an effective methodology based on the study's findings that would enable clinicians to differentiate between chemotherapy-responsive populations. Methods: We retrospectively enrolled 730 GC patients who underwent radical gastrectomy. Fibrinogen (FIB), platelet-lymphocyte ratio (PLR), systemic inflammation response index (SIRI), prognostic nutritional index (PNI), systemic immune-inflammation index (SII), neutrophil-lymphocyte ratio (NLR) and lymph node ratio (LNR) were grouped according to cutoff values. Their clinical significance for GC prognosis was determined by multivariate COX regression analysis in the 730 GC patients and high/low PLR status subgroups. Cases were divided into four groups according to PLR status and adjuvant chemotherapy status and survival was compared among groups. Results: Multivariate analysis showed that PLR was an independent prognostic factor for overall survival (OS) and disease-free survival (DFS) of GC patients. Adjuvant chemotherapy improved survival more significantly in patients with low PLR than that with high PLR. Among patients receiving adjuvant chemotherapy, low PLR was significantly associated with prolonged survival in TNM stage II, but not in TNM stage III. Conclusion: Preoperative high PLR is an independent risk factor for GC patients undergoing radical gastrectomy and adversely affects the postoperative chemotherapy effect.

Glucose metabolism-based signature predicts prognosis and immunotherapy strategies for colon adenocarcinoma.

BACKGROUND: The global prevalence and metastasis rates of colon adenocarcinoma (COAD) are high, and therapeutic success is limited. Although previous research has primarily explored changes in gene phenotypes, the incidence rate of COAD remains unchanged. Metabolic reprogramming is a crucial aspect of cancer research and therapy. The present study aims to develop cluster and polygenic risk prediction models for COAD based on glucose metabolism pathways to assess the survival status of patients and potentially identify novel immunotherapy strategies and related therapeutic targets. METHODS: COAD-specific data (including clinicopathological information and gene expression profiles) were sourced from The Cancer Genome Atlas (TCGA) and two Gene Expression Omnibus (GEO) datasets (GSE33113 and GSE39582). Gene sets related to glucose metabolism were obtained from the MSigDB database. The Gene Set Variation Analysis (GSVA) method was utilized to calculate pathway scores for glucose metabolism. The hclust function in R, part of the Pheatmap package, was used to establish a clustering system. The mutation characteristics of identified clusters were assessed via MOVICS software, and differentially expressed genes (DEGs) were filtered using limma software. Signature analysis was performed using the least absolute shrinkage and selection operator (LASSO) method. Survival curves, survival receiver operating characteristic (ROC) curves and multivariate Cox regression were analyzed to assess the efficacy and accuracy of the signature for prognostic prediction. The pRRophetic program was employed to predict drug sensitivity, with data sourced from the Genomics of Drug Sensitivity in Cancer (GDSC) database. RESULTS: Four COAD subgroups (i.e., C1, C2, C3 and C4) were identified based on glucose metabolism, with the C4 group having higher survival rates. These four clusters were bifurcated into a new Clust2 system (C1 + C2 + C3 and C4). In total, 2175 DEGs were obtained (C1 + C2 + C3 vs. C4), from which 139 prognosis-related genes were identified. ROC curves predicting 1-, 3- and 5-year survival based on a signature containing nine genes showed an area under the curve greater than 0.7. Meanwhile, the study also found this feature to be an important predictor of prognosis in COAD and accordingly assessed the risk score, with higher risk scores being associated with a worse prognosis. The high-risk and low-risk groups responded differently to immunotherapy and chemotherapeutic agents, and there were differences in functional enrichment pathways. CONCLUSIONS: This unique signature based on glucose metabolism may potentially provide a basis for predicting patient prognosis, biological characteristics and more effective immunotherapy strategies for COAD.

Prognostic utility of TME-associated genes in pancreatic cancer.

Background: Pancreatic cancer (PC) is a deadly disease. The tumor microenvironment (TME) participates in PC oncogenesis. This study focuses on the assessment of the prognostic and treatment utility of TME-associated genes in PC. Methods: After obtaining the differentially expressed TME-related genes, univariate and multivariate Cox analyses and least absolute shrinkage and selection operator (LASSO) were performed to identify genes related to prognosis, and a risk model was established to evaluate risk scores, based on The Cancer Genome Atlas (TCGA) data set, and it was validated by external data sets from the Gene Expression Omnibus (GEO) and Clinical Proteomic Tumor Analysis Consortium (CPTAC). Multiomics analyses were adopted to explore the potential mechanisms, discover novel treatment targets, and assess the sensitivities of immunotherapy and chemotherapy. Results: Five TME-associated genes, namely, FERMT1, CARD9, IL20RB, MET, and MMP3, were identified and a risk score formula constructed. Next, their mRNA expressions were verified in cancer and normal pancreatic cells. Multiple algorithms confirmed that the risk model displayed a reliable ability of prognosis prediction and was an independent prognostic factor, indicating that high-risk patients had poor outcomes. Immunocyte infiltration, gene set enrichment analysis (GSEA), and single-cell analysis all showed a strong relationship between immune mechanism and low-risk samples. The risk score could predict the sensitivity of immunotherapy and some chemotherapy regimens, which included oxaliplatin and irinotecan. Various latent treatment targets (LAG3, TIGIT, and ARID1A) were addressed by mutation landscape based on the risk model. Conclusion: The risk model based on TME-related genes can reflect the prognosis of PC patients and functions as a novel set of biomarkers for PC therapy.

Anillin is a prognostic factor and is correlated with genovariation in pancreatic cancer based on databases analysis.

Pancreatic cancer has a low survival rate globally. Anillin (ANLN) is involved in the pathogenesis of pancreatic cancer (PC). The present study used databases and reverse transcription-quantitative PCR to investigate the association between ANLN expression, clinical variables and the survival rate of patients with pancreatic cancer. Gene expression of ANLN in normal and cancer tissues was analyzed using data from The Cancer Genome Atlas, Oncomine and Gene Expression database of Normal and Tumor tissues 2 and ANOVA, and the association between ANLN mRNA expression and ANLN genovariation was analyzed using cBioPortal. The association between ANLN expression and the survival, clinical, pathological and prognostic characteristics of PC was analyzed using Kaplan-Meier (K-M) survival analysis, Kruskal Wallis and Mann Whitney-U tests, and logistic and Cox regression models. Gene Set Enrichment Analysis (GSEA) revealed the molecular pathways underpinning ANLN function in PC. Overexpression of ANLN was observed in PC cells (normal vs. tumor, P<0.01) and tissues (normal vs. tumor, P=0.008). Enhanced ANLN expression was associated with high tumor grade (grade 1 vs. grade 3, odds ratio: 5.662, P<0.001). However, ANLN expression was not associated with other clinical features (all P>0.05). K-M analysis suggested that increased ANLN expression was associated with poor survival (P=0.002). Univariate and multivariate analysis revealed the ANLN is an independent prognostic factor for PC (P<0.001). GSEA demonstrated the p53, cell cycle, DNA replication, mismatch repair, nucleotide excision repair and PC pathways were associated with low expression of ANLN. Overall, ANLN is more highly expressed in PC compared with in normal tissue, and is associated with poor differentiation. The expression of ANLN may be a novel prognostic marker of poor survival. Finally, ANLN exert its functions in PC through the p53, cell cycle, DNA replication, mismatch repair and nucleotide excision repair and pathways.

Roux-en-Y and Billroth II Reconstruction after Pancreaticoduodenectomy: A Meta-Analysis of Complications.

OBJECTIVE: To evaluate Roux-en-Y and Billroth II reconstruction following pancreaticoduodenectomy (PD). METHODS: PubMed, Embase, the Cochrane Library, and the Web of Science were searched to identify randomized controlled trials (RCTs) and controlled clinical trials that compared Roux-en-Y and Billroth II reconstruction following PD up to December 2019. RevMan 5.3 software was used for the statistical analysis. RESULTS: Four RCTs and five controlled clinical trials were included, with a total of 1,072 patients (500 and 572 patients in the Roux-en-Y and Billroth II groups, respectively). No significant differences in delayed gastric emptying (DGE), A-grade DGE, B-grade DGE, or C-grade DGE were observed between the Roux-en-Y and Billroth II reconstruction groups after PD (odds ratio [OR] = 1.01, 95% confidence interval [CI]: 0.50-2.03, P = 0.98; OR = 0.49, 95% CI: 0.17-1.45, P = 0.20; OR = 0.63, 95% CI: 0.29-1.38, P = 0.25; and OR = 2.13, 95% CI: 0.38-11.99, P = 0.39). No significant difference in the incidence of postoperative pancreatic fistula, abscess, bile leaks, infection, postoperative bleeding, or the length of the postoperative hospital stay was observed between the Roux-en-Y and Billroth II groups (P > 0.05), but the operation time was significantly different (mean difference [MD] = 31.65, 95% CI: 7.14-56.17, P = 0.01). CONCLUSIONS: Billroth II reconstruction after PD did not significantly reduce the incidence of DGE or other complications but shortened the operation time compared to Roux-en-Y reconstruction. However, the results must be verified by further high-quality, large RCTs or controlled clinical trials.

The efficacy and adverse reactions of DCF and FOLFOXs regimens for patients with advanced gastric cancer in China: a meta-analysis.

BACKGROUND: Gastric cancer is a malignant tumor originating from the gastric mucosal epithelium, ranking fourth in the incidence of male malignant tumors and third in mortality rate. The aim of this study is to investigate the efficacy and adverse reactions of DCF and FOLFOXs regimens in the treatment of advanced gastric cancer. METHODS: Relevant prospective clinical controlled studies were retrieved from WanFang Data, CBM, CNKI, PubMed, The Cochrane Library and Embase databases and meta-analysis was performed using RevMan 5.3 software. RESULTS: The effective rates of DCF group and FOLFOXs group were basically the same (RR 1.06, 95% CI: 0.92-1.23, P=0.41). The incidence of nausea and vomiting (RR 1.36, 95% CI: 1.15-1.60), anemia (RR 2.04, 95% CI: 1.55-2.68), thrombocytopenia (RR 1.52, 95% CI: 1.15-2.01) and leukopenia (RR 1.70, 95% CI: 1.44-2.01) with FOLFOXs regimen were significantly lower than DCF regimen, while the incidence of sensory neurotoxicity was significantly higher than DCF regimen (RR 0.53, 95% CI: 0.38-0.74). There were no significant differences in efficacy, ORR and DCR between different doses in the FOLFOXs group (P=0.233). CONCLUSIONS: The efficacy of FOLFOXs regimen was comparable to that of DCF regimen in the treatment of advanced gastric cancer, but the incidence of adverse reactions was significantly lower, and there were no significant differences between different therapeutic doses.