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Abstract Background Cathepsin-K (CTSK) is overexpressed in Gastric cancer (GC) and the mechanism of its overexpression in GC is still unclear. The present work found CTSK as a potential predictive biomarker and immunotherapeutic target for GC based on the tumor microenvironment (TME). Methods From public databases, gene expression profiles and clinical data of GC were downloaded to analyze the distribution of stromal and immune cells and tumor abundance in TME. Differentially expressed genes (DEGs) associated with TME were obtained by differential analysis, followed by cross-screening to obtain CTSK as a gene associated with TME. Next, a series of methods and tools were employed to explore the relationships between clinicopathological features of GC and CTSK expression as well as prognosis, tumor immune microenvironment, immune checkpoints and drug sensitivity. And GSEA was used to investigate the potential role of CTSK in the tumor microenvironment of GC. Results From the dataset, we obtained a total of 656 DEGs associated with TME and the stromal component of TME was found to be closely involved in GC prognosis. CTSK was cross-screened as the key gene associated with TME by the PPI network and univariate Cox regression analysis. Pan-cancer analysis revealed significant high expression of CTSK in a variety of cancers. Subsequently, we hypothesized that high-expressed CTSK was closely correlated with poor prognosis and lymph node metastasis of tumors, and that CTSK, a GC TME-related gene, was largely involved in a range of biological behaviors of tumors, with a significant correlation between several immune cells. Conclusion CTSK was validated as a potential prognostic biomarker related to TME of GC and could be a promising next-generation immunotherapeutic target for GC.

BackgroundAmounting 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.AimsWe 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.MethodsWe 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.ResultsMultivariate 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.ConclusionPreoperative high PLR is an independent risk factor for GC patients undergoing radical gastrectomy and adversely affects the postoperative chemotherapy effect.

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 Although emerging evidence has revealed that LHPP, a histidine phosphatase protein, suppresses the progression of different cancers, a pan-cancer analysis still remains unavailable. Therefore, we first utilized different bioinformatics tools to explore the tumor inhibitory role of LHPP protein across 33 tumor types based on the TCGA project. Additionally, HGC-27 gastric cancer cells were used to evaluate the biological functions of LHPP after stable transfection with lentiviruses. Consequently, LHPP mRNA and protein expression were down-regulated in the most cancer tissues corresponding to normal tissues. The data showed that patients with higher LHPP performance had a better prognosis of overall survival (OS) and disease-free survival (DFS) in brain glioma and renal carcinoma. In addition, we found that enhancement of LHPP expression attenuated the proliferation, migration and invasion of gastric cancer cells. The expression levels of cell-cycle-related and EMT-related molecules, such as CDK4, CyclinD1, Vimentin and Snail, were clearly reduced. Moreover, a genetic alteration analysis showed that the most frequent mutation types in LHPP protein was amplification. The patients without LHPP mutation showed a better tendency of prognosis in UCEC, STAD and COAD. Cancer-associated fibroblast infiltration was also observed in head and neck squamous cell carcinoma, stomach adenocarcinoma and testicular germ cell tumors. In summary, our pancancer analysis among various tumor types could provide a comprehensive understanding of LHPP biological function in the progression of malignant diseases and promote the development of novel therapeutic targets.

Abstract The roles of phospholysine phosphohistidine inorganic pyrophosphate phosphatase (LHPP) in tumorigenesis have been recently proven in hepatocellular carcinoma (HCC), cervical, pancreatic, bladder, and thyroid cancers. Previous research demonstrated that LHPP repressed cell proliferation and growth by inactivating the phosphatidylinositol 3-kinase/AKT signaling pathway in vitro and in vivo. However, the functions and potential mechanisms of LHPP as a tumor suppressor in colorectal cancer (CRC) metastasis are still unknown. Consequently, the Transwell assay and xenograft nude model showed that LHPP inhibited migration and invasion of CRC cells in vitro and in vivo, respectively. The expression of total and nuclear epithelial-to-mesenchymal transition (EMT)-related proteins were significantly reduced after LHPP upregulation. Human Gene Expression Array and IPA (Ingenuity Pathway Analysis) commercial software were applied to identify differentially expressed genes (DEGs) and potential cell signaling pathways. A total of 330 different genes were observed, including 177 upregulated genes and 153 downregulated genes. Bioinformatics analysis suggested that the transforming growth factor-β (TGF-β) signaling pathway was highly inactivated in this study. Then, Smad3 phosphorylation was apparently decreased, whereas Smad7 expression was markedly enhanced after upregulating LHPP expression. These results were proven once again after TGF-β1 stimulation. Furthermore, a specific inhibitor of Smad3 phosphorylation (SIS3) was applied to verify that LHPP repressed EMT of cancer cells by attenuating TGF-β/Smad signaling. The results suggested that suppression of the TGF-β/Smad signaling pathway by LHPP overexpression could be abolished by SIS3.

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 high-risk 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.

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.