The present study determined the levels of plasma biomarkers in patients with gastric carcinoma (GC) and investigated their clinical significance and diagnostic value. Between April 2014 and December 2018, 90 patients with GC, 90 patients with precancerous lesions (Pre) and 45 healthy controls (NC) were recruited from the Affiliated Liutie Central Hospital of Guangxi Medical University. Five markers were measured: microRNA-650 (miRNA-650; using reverse transcription-quantitative polymerase chain reaction), and carcinoembryonic antigen (CEA), carbohydrate antigen (CA)125, CA211 and CA50 using electrochemiluminescence. Circulating markers were all upregulated in patients with GC (P<0.05), and CA211 and CA50 were significantly increased in patients with Pre. The miRNA-650 and CA211 had an area under the curve (AUC) of 0.700 (moderate) and 0.866 (high), respectively, in the diagnosis of GC. Differentiation of GC from Pre yielded an AUC of 0.665 (low) and 0.708 (moderate), respectively. The combination model of miRNA-650 and CA211 showed an appropriate value of AUC (0.887) to discriminate the GC patients from the healthy subjects with a sensitivity and specificity of 82.5 and 97.7%. Additionally, differentiating GC from Pre yielded an AUC of 0.767 with a sensitivity of 57.1% and a specificity of 95%, respectively. In terms of clinicopathological features, the expression of miRNA-650 and CA211 in plasma was not associated with the patients' age, sex, Tumor-Node-Metastasis stage, or histological type. In conclusion, plasma miRNA-650 and CA211 is a promising and powerful non-invasive marker for the detection of GC.

Previous researches have highlighted that low-expressing deoxyribonuclease1-like 3 (DNASE1L3) may play a role as a potential prognostic biomarker in several cancers. However, the diagnosis and prognosis roles of DNASE1L3 gene in lung adenocarcinoma (LUAD) remain largely unknown. This research aimed to explore the diagnosis value, prognostic value, and potential oncogenic roles of DNASE1L3 in LUAD. We performed bioinformatics analysis on LUAD datasets downloaded from TCGA (The Cancer Genome Atlas) and GEO (Gene Expression Omnibus), and jointly analyzed with various online databases. We found that both the mRNA and protein levels of DNASE1L3 in patients with LUAD were noticeably lower than that in normal tissues. Low DNASE1L3 expression was significantly associated with higher pathological stages, T stages, and poor prognosis in LUAD cohorts. Multivariate analysis revealed that DNASE1L3 was an independent factor affecting overall survival (HR = 0.680, p = 0.027). Moreover, decreased DNASE1L3 showed strong diagnostic efficiency for LUAD. Results indicated that the mRNA level of DNASE1L3 was positively correlated with the infiltration of various immune cells, immune checkpoints in LUAD, especially with some m6A methylation regulators. In addition, enrichment function analysis revealed that the co-expressed genes may participate in the process of intercellular signal transduction and transmission. GSEA indicated that DNASE1L3 was positively related to G protein-coupled receptor ligand biding (NES = 1.738; P adjust = 0.044; FDR = 0.033) and G alpha (i) signaling events (NES = 1.635; P adjust = 0.044; FDR = 0.033). Our results demonstrated that decreased DNASE1L3 may serve as a novel diagnostic and prognostic biomarker associating with immune infiltrates in lung adenocarcinoma.

Background: Recent studies highlight the carcinogenesis role of SHC-adaptor protein 1 (SHC1) in cancer initiation, development, and progression. However, its aberrant expression, diagnostic and prognostic value remain unknown in a variety of tumors.Methods: The SHC1 expression profiles were analyzed using GTEx database, TCGA database, Oncomine and CPTAC database. The survival analysis was conducted using GEPIA2, Kaplan-Meier Plotter, UALCAN, and PrognoScan. The diagnostic values of SHC1 were calculated with the “pROC” package in R software. The genetic alteration of SHC1 and mutations were analyzed using cBioPortal. TIMER2 was employed to estimate the correlations between SHC1 expression and tumor-infiltrating immune cells in the TCGA cohort. Enrichment analysis of SHC1 was conducted using the R package “clusterProfiler.”Results: SHC1 was ubiquitously highly expressed and closely associated with worse prognosis of multiple major cancer types (all p &lt; 0.05). Further, SHC1 gene mutations were strongly linked to poor OS and DFS in SKCM (all p &lt; 0.05). An enhanced phosphorylation level of SHC1 at the S139 site was observed in clear cell RCC. Additionally, the results revealed SHC1 expression was strongly linked to TMB, MMRs, MSI, TAMs, DNA methylation, m6A RNA methylation, tumor-associated immune infiltration, and immune checkpoints in multiple cancers (all p &lt; 0.05). In addition, the results of the ROC analysis indicated the SHC1 exhibited strong diagnostic capability for KICH (AUC = 0.92), LIHC (AUC = 0.95), and PAAD (AUC = 0.95). Finally, enrichment analysis indicated that SHC1 may potentially involve in the regulation of numerous signaling pathways in cancer metabolism and protein phosphorylation-related functions.Conclusions: These findings highlight that SHC1 plays an important role in the tumor immune microenvironment, and SHC1 has been identified to have prognostic and diagnostic value in multiple cancers. Thus, SHC1 is a potential target for cancer immunotherapy and effective prognostic and diagnostic biomarker.

Patients with gastric cancer (GC) have a poor prognosis, which is mainly due to the low rate of early diagnosis. The present study aimed to evaluate whether circulating microRNA-130b (miR-130b) and blood routine parameters [neutrophil count (N#), lymphocyte count (L#), monocyte count (M#), neutrophil percentage (N%), lymphocyte percentage (L%), monocyte percentage (M%), hemoglobin (Hb) level, hematocrit (Hct), red blood cell distribution width (RDW), platelet count, platelet distribution width (PDW), mean platelet volume (MPV), MPV to platelet count ratio (MPV/PC), monocyte to lymphocyte ratio (MLR), neutrophil to lymphocyte ratio (NLR) and platelet to lymphocyte ratio (PLR)] are useful biomarkers for GC, early stage GC (EGC) and precancerous lesion (Pre) detection, and to identify more effective diagnostic models by combining circulating blood markers. Circulating levels of M#, M%, RDW-coefficient of variation (RDW-CV), MPV, PDW, MLR and NLR were significantly higher, and the levels of Hb and L% were significantly lower in patients with GC and Pre compared with those in healthy controls (NCs) (all P<0.05). The N#, N% and PLR in patients with GC were significantly higher and the Hct was significantly lower than those in the NCs (all P<0.05). The values of MPV/PC were significantly higher in the Pre cohort compared with those in the NCs. The area under the curve (AUC) of the receiver operating characteristic curve of potential biomarkers for GC was 0.634–0.887 individually, and this increased to 0.978 in the combination model of miR-130b-PDW-MLR-Hb. Additionally, the values for RDW-CV, PLR, NLR, N# and N% were positively correlated with cancer stage, while the values for MPV, L#, L%, Hb and Hct were negatively correlated with cancer stage. Furthermore, the circulating levels of miRNA-130b, and the values for NLR, RDW-CV, PDW, M%, red blood cell count, Hct, Hb and MLR differed between the EGC and NC groups. The AUC values of these biomarkers were 0.6491–0.911 individually in the diagnosis of EGC, and these increased to 0.960 in combination. In addition, the AUC values for miR-130b, RDW-CV, MPV/PC ratio, MLR, NLR, PDW, L%, M%, M# and Hb in the diagnosis of Pre were 0.638–0.811 individually. The dual-model of miR-130b-PDW manifested the largest AUC of 0.896 in the diagnosis of Pre, and the sensitivity and accuracy were increased when miR-130b and PDW were combined. All these results suggested that circulating miR-130b and blood routine parameters might be potential biomarkers, and combinations of measurements of these biomarkers may improve the GC, EGC and Pre diagnostic accuracy.

Background: Semaphorin 5B (SEMA5B) has been described to be involved in the development and progression of cancer. However, the potential diagnostic and prognosis roles and its correlation with tumor-infiltrating immune cells in KIRC have not been clearly reported yet.Methods: The mRNA level of SEMA5B was analyzed via the TCGA and GTEx database as well as the CCLE dataset and verified by GSE53757 and GSE40435 datasets. Meanwhile, the protein level of SEMA5B was analyzed by CPTAC and validated by HPA. The diagnostic value of SEMA5B was analyzed according to the TCGA database and validated by GSE53757, GSE46699, and GSE11024 + GSE46699 datasets. Then, the survival analysis was conducted using GEPIA2. R software (v3.6.3) was applied to investigate the relevance between SEMA5B and immune checkpoints and m6A RNA methylation regulator expression. The correlation between SEMA5B and MMRs and DNMT expression and tumor-infiltrating immune cells was explored via TIMER2. Co-expressed genes of SEMA5B were assessed by cBioPortal, and enrichment analysis was conducted by Metascape. The methylation analysis was conducted with MEXPRESS and MethSurv online tools. Gene set enrichment analysis (GSEA) was applied to annotate the biological function of SEMA5B.Results: SEMA5B was significantly upregulated at both the mRNA and protein levels in KIRC. Further analysis demonstrated that the mRNA expression of SEMA5B was significantly correlated with gender, age, T stage, pathologic stage, and histologic grade. High levels of SEMA5B were found to be a favorable prognostic factor and novel diagnostic biomarker for KIRC. SEMA5B expression was shown to be significantly associated with the abundance of immune cells in KIRC. Also, SEMA5B expression was significantly correlated with the abundance of MMR genes, DNMTs, and m6A regulators in KIRC. Enrichment analysis indicated that the co-expressed genes may involve in crosslinking in the extracellular matrix (ECM). GSEA disclosed that SYSTEMIC_LUPUS_ERYTHEMATOSUS and NABA_ECM_REGULATORS were prominently enriched in the SEMA5B low-expression phenotype. Finally, the methylation analysis demonstrated a correlation between hypermethylation of the SEMA5B gene and a poor prognosis in KIRC.Conclusion: Increased SEMA5B expression correlated with immune cell infiltration, which can be served as a favorable prognostic factor and a novel diagnostic biomarker for KIRC.