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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. [ABSTRACT FROM AUTHOR]

Purpose: A high postoperative recurrence rate seriously impedes colon cancer (CC) patients from achieving long-term survival. Here, we aimed to develop a Treg-related classifier that can help predict recurrence-free survival (RFS) and therapy benefits of stage I–III colon cancer. Methods: A Treg-related prognostic classifier was built through a variety of bioinformatic methods, whose performance was assessed by KM survival curves, time-dependent receiver operating characteristic (tROC), and Harrell's concordance index (C-index). A prognostic nomogram was generated using this classifier and other traditional clinical parameters. Moreover, the predictive values of this classifier for immunotherapy and chemotherapy therapeutic efficacy were tested using multiple immunotherapy sets and R package "pRRophetic". Results: A nine Treg-related classifier categorized CC patients into high- and low-risk groups with distinct RFS in the multiple datasets (all p < 0.05). The AUC values of 5-year RFS were 0.712, 0.588, 0.669, and 0.662 in the training, 1st, 2nd, and entire validation sets, respectively. Furthermore, this classifier was identified as an independent predictor of RFS. Finally, a nomogram combining this classifier and three clinical variables was generated, the analysis of tROC, C-index, calibration curves, and the comparative analysis with other signatures confirmed its predictive performance. Moreover, KM analysis exhibited an obvious discrepancy in the subgroups, especially in different TNM stages and with adjuvant chemotherapy. We detected the difference between the two risk subsets of immune cell sub-population and the response to immunotherapy and chemotherapy. Conclusions: We built a robust Treg-related classifier and generated a prognostic nomogram that predicts recurrence-free survival in stage I–III colon cancer that can identify high-risk patients for more personalized and effective therapy. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Colorectal cancer (CRC) is a common tumor disease of the digestive system with high incidence and mortality. Cuproptosis has recently been found to be a new form of cell death. The clinical significance of cuproptosis-related genes (CRGs) in CRC is not clear. In this study, The Cancer Genome Atlas Colon and Rectal Cancer dataset was used to analyze the relationship between CRGs and clinical characteristics of CRC by differential expression analysis and Kaplan-Meier survival (K-M) analysis. Based on CRGs, prognosis model and risk score of CRC was constructed in COADREAD by multivariate Cox analysis. Receiver operating curves (ROC) analysis, K-M analysis and calibration analysis in GDC TCGA Colon Cancer dataset were applied to validating model. Subsequently, the relationship between risk score of CRC and immune microenvironment was analyzed by multiple immune score algorithms. Finally, we found that most CRGs were differentially expressed between tumors and normal tissues. Some CRGs were differentially expressed among different clinical characteristics. K-M analysis showed that the CRGs were related to overall survival (OS), disease-specific survival, and progression-free survival. Subsequently, DLAT and CDKN2A were identified as risk factors for OS in CRC by multivariate Cox analysis, and the risk score was established. K-M analysis showed that there was a significant difference in OS between the highrisk and low-risk groups, which were grouped by risk score median. ROC analysis showed that the risk score performs well in predicting the 1-year, 3-year and 5-year OS. Enrichment analysis showed that the differentially expressed genes between the high- and low-risk groups were enriched in immune-related signaling pathways. Further analysis showed that there were significant differences in the levels of immune cells and stromal cells between the high- and low-risk groups. The high-risk group had higher levels of immune cells and interstitial cells. At the same time, the high-risk group had a higher immune escape ability, and the predicted immune treatment response in the high-risk group was poor. In conclusion, CRGs can be used as prognostic factors in CRC and are closely related to the levels of immune cells and stromal cells in the tumor microenvironment. [ABSTRACT FROM AUTHOR]

Background/Aims: Elevated pretreatment plasma D-dimer level has been reported as an unfavorable prognostic indicator in several malignancies. The aim of this meta-analysis was to evaluate the prognostic value of elevated D-dimer level in solid tumors. Methods: A comprehensive search of electronic databases up to June 10, 2017 was carried out by two independent reviewers. We included studies exploring the association between pretreatment plasma D-dimer level and patients' survival outcomes in solid tumors. Overall survival (OS) was regarded as primary outcome and progression-free survival (PFS), disease-free survival (DFS) as well as cancer-specific survival (CSS) were chosen as secondary outcomes. Hazard ratio and 95% confidence interval (CI) were extracted directly or indirectly from included studies. Results: 49 studies with 13001 patients were included in our meta-analysis. Elevated D-dimer was markedly associated with poor OS (pooled HR = 1.90, 95% CI = 1.63 - 2.20, P < 0.001). The effect was observed in all different tumor sites, disease stages, cut-off values and ethnicities. Meanwhile, patients with a high plasma D-dimer had a shorter PFS (HR = 1.46, 95% CI = 1.22-1.76; P < 0.001), DFS (HR = 2.02, 95% CI = 1.56-2.62) and CSS (HR = 2.04, 95% CI= 1.58 - 2.64). Conclusions: Analysis of the pretreatment plasma D-dimer might provide useful information to predict prognosis in patients with solid tumors. [ABSTRACT FROM AUTHOR]

The occurrence of chemotherapy-induced alterations in markers of haemostasis during chemotherapy has been reported previously. However, the change of the haemostasis markers in the cyclophosphamide, epirubicin and fluorouracil (CEF) regimen remains unclear. The aim of the present study was to identify the change of the haemostasis markers during systemic chemotherapy (600 mg/m2 cyclophosphamide, 80 mg/m2 epirubicin and 500 mg/m2 fluorouracil; four courses over 21 days) to investigate its influence on the haemostasis markers of breast cancer patients and to discuss the requirement of anticoagulation therapy. D-dimer, activated partial thromboplastin time (APTT), prothrombin time (PT) and fibrinogen (FIB) values were obtained before chemotherapy and on days 1, 4, 7 and 21. The results show that PT, D-dimer and FIB were not prolonged prior to chemotherapy compared to that under the control. APTT was prolonged until day 4. The levels of D-dimer and APTT were significantly higher compared to those of the breast cancer patients before receiving chemotherapy and controls on days 1, 4, 7 and 21 after chemotherapy. Alteration of the haemostasis markers occurred in the breast cancer patients under the CEF chemotherapy regimen. As there is an increased risk of deep vein thrombosis and pool prognosis of cancer patients, anticoagulant therapy should be considered. [ABSTRACT FROM AUTHOR]

Recent studies demonstrated that microRNA (miRNA) expression is dysregulated in numerous human cancers. In this study, we investigated the expression patterns of 8 miRNAs in gastric cancer and evaluated their clinical significance in order to identify potential biomarkers for gastric cancer diagnosis. Total RNA was extracted from gastric cancer and normal tissues from 20 pairs of paraffine-mbedded specimens. The expression levels of the miRNAs were detected by quantitative reverse transcriptase polymerase chain reaction using specific stem-loop primers, with U6 as the internal reference gene. The association between miRNA expression level and clinicopathological factors was investigated. The expression of miR-21, -103, -106a, -221 and -222 in gastric cancer samples was significantly higher compared to that in the paired normal samples. Conversely, the expression of miR-143 and -195 in cancer tissues was significantly lower compared to that in normal tissues. However, miR-126 exhibited no difference between gastric cancer and normal tissues. A multivariate analysis demonstrated that the expression of miR-143 and -195 were associated with clinicopathological parameters, including depth of invasion and lymph node metastasis. This association may be applicable to future decisions regarding treatment or as a diagnostic biomarker. [ABSTRACT FROM AUTHOR]