The potential use and experimental validation of genomic instability-related lncRNA in pancreatic carcinoma.

This study explored the potential role of long noncoding RNA (lncRNAs) associated with genomic instability in the diagnosis and treatment of pancreatic adenocarcinoma (PAAD). Transcriptome and single-nucleotide variation data of PAAD samples were downloaded from the cancer genome atlas database to explore genomic instability-associated lncRNAs. We constructed a genomic instability-associated lncRNA prognostic signature. Then gene ontology and Kyoto encyclopedia of genes and genomes enrichment analyses were used to explore the physiological role of lncRNAs involved in genomic instability. Tumor microenvironments, immunotherapy response, immune cell infiltration, immune checkpoint, and drug sensitivity were compared between high-risk and low-risk groups. In vitro experiments were performed for external validation. Six lncRNAs associated with genomic instability were identified, capable of predicting the prognosis of PAAD. Patients were assigned to low-risk or high-risk groups using these biomarkers, with better or worse prognosis, respectively. The tumor immune score, immune cell infiltration, and efficacy of immunotherapy were worse in the high-risk group. A drug sensitivity analysis revealed the high- and low-risk groups had different half-maximal inhibitory concentrations. The expression of cancer susceptibility candidate 8 was significantly higher in tumor tissues than in normal tissues, while the expression of LYPLAL1-AS1 exhibited an opposite pattern. They may be potential diagnostic or prognostic biomarkers for patients with pancreatic cancer. Genomic instability-associated lncRNAs were explored in this study and predicted the prognosis of PAAD and stratified patients risk in PAAD. These lncRNAs also predicted the efficacy of immunotherapy and potential therapeutic targets in PAAD.

Construction of a Pyroptosis-Related Genes Signature to Improve the Prognostic Prediction and Therapeutic Drugs Selection in Patients with Pancreatic Cancer.

Background: Effective prognostic assessment and appropriate drug selection are important for the clinical management of pancreatic cancer (PaC). Here, we aimed to establish a pyroptosis-associated genes (PRGs) signature to predict the prognostic outcomes of PaC and guide clinical drug therapy. Methods: We identified the differentially expressed PRGs between pancreatic adenocarcinoma (n = 178) and control pancreas samples (n = 171) obtained from different databases, and performed Lasso and Cox regression analysis to create a prognosis signature. Kaplan-Meier (K-M) survival curves and time-dependent receiver operating characteristics were further constructed to assess the utility of the risk model. The International Cancer Genome Consortium (ICGC) PACA-AU cohort (n = 95) was used as a validation dataset to examine the validity of this prognostic model. The correlations of risk score (RS) with clinical features, immune cell infiltration, tumor mutation burden and half-maximal inhibitory concentrations (IC50) of chemotherapeutic drugs were analyzed, and the expression levels of PRGs in cell lines were detected. Results: A prognostic signature was constructed, which consisted of 4 PRGs (AIM2, IL18, GSMDC and PLCG1). K-M analysis demonstrated a remarkable difference in overall survival (OS) time between low-risk (LR) and high-risk (HR) groups (P < 0.001). The RS contributed to the progression of PaC, and could be a significant independent factor for prognostic prediction. The validation of the ICGC cohort confirmed the effectiveness of the proposed signature. The patients with a HR score in the TCGA cohort had higher tumor mutation burden and more sensitivity to paclitaxel, gemcitabine, 5-fluorouracil and cisplatin than those with a LR score. The differential expression levels of signature genes were verified in vitro. Conclusion: The PRGs signature can be applied for predicting the prognosis of PaC, and may provide useful information for selection of therapeutic drugs.

Risk-Related Genes and Associated Signaling Pathways of Gastrointestinal Stromal Tumors.

Purpose: Knowledge on the potential association between differential gene expression and risk of gastrointestinal stromal tumors (GISTs) is currently limited. We used bioinformatics tools to identify differentially expressed genes in GIST samples and the related signaling pathways of these genes. Patients and Methods: The GSE136755 dataset was obtained from the GEO database and differentially expressed genes (CENPA, CDK1, TPX2, CCNB1, CCNA2, BUB1, AURKA, KIF11, NDC80) were screened using String and Cytoscape bioinformatics tools. Then, three groups of eight patients at high, intermediate and low risk of GIST were selected from patients diagnosed with GIST by immunohistochemistry in our hospital from October 2020 to March 2021. Differential expression of CDK1 and BUB1 was verified by comparing the amount of expressed p21-Activated kinase 4 (PAK4) protein in pathological sections. Results: SPSS26.0 analysis showed that the expression level of PAK4 in GISTs was significantly higher than in normal tissues and paratumoral tissues and there was significant difference among the three groups of patients (P < 0.01). PAK4 levels in paratumoral and normal tissues were negligible with no significant difference between the tissues. Conclusion: CENPA, CDK1, TPX2, CCNB1, CCNA2, BUB1, AURKA, KIF11 and NDC80 gene expression can be used as biomarkers to assess the risk of gastrointestinal stromal tumors whereby expression increases gradually with the increased risk of GIST formation. The genes encode proteins that regulate the division, proliferation and apoptosis of gastrointestinal stromal tumors mainly through PI3K/AKT, MARK, P53, WNT and other signaling pathways.

[Efficacy of bismuth-based quadruple therapy as first-line treatment for Helicobacter pylori infection].

OBJECTIVE: To evaluate the efficacy of bismuth-based quadruple therapy as the first-line treatment for H.pylori infection. METHODS: A total of 136 patients with H.pylori related peptic ulcer or chronic gastritis were randomized into two groups: 67 patients in bismuth-based quadruple group received esomeprazole 20 mg, clarithromycin 0.5 g,amoxicillin 1.0 g,and bismuth potassium citrate 220 mg for 7 d; 69 patients in standard triple group received esomeprazole 20 mg, clarithromycin 0.5 g and amoxicillin 1.0 g for 7 d. Outcome of eradication therapy was assessed by (14)C-UBT. On ITT and PP analysis, calculating the cost-effectiveness ratio (C/E) and the incremental cost-effectiveness ratio (delta C/delta E). RESULT: On ITT and PP analysis, the eradication rates of the quadruple therapy group were 82.09% and 88.71%, and those of the triple therapy group were 66.67% and 73.02% (P<0.05). The cost-effectiveness ratio of two groups was 4.15 and 4.82; The incremental cost-effectiveness ratio of quadruple therapy group was 1.02 as against triple therapy group. CONCLUSION: Compared to the standard triple therapy regimen, the bismuth-containing quadruple therapy regimen has higher eradication rate and cost-effectiveness, which can be recommended as the fist-line treatment for H.pylori infection.

Comparison of Endoscopic Ultrasound-Guided Fine Needle Aspiration with 19-Gauge and 22-Gauge Needles for Solid Pancreatic Lesions.

PURPOSE: We aimed to compare the histological and/or cytological diagnostic outcomes of EUS-FNA using 19G and 22G needles for solid pancreatic lesions and to evaluate the feasibility and safety of 19G needle. PATIENTS AND METHODS: Data from patients with solid pancreatic lesions, who underwent EUS-FNA, were retrospectively retrieved from a single tertiary center from June 2017 to January 2021. The sensitivity, specificity, and accuracy of diagnosis, sample adequacy, number and time of punctures, and adverse events, were compared between the 19G and 22G groups. Univariate and multivariate logistic regression analyses were used to identify optimal factors for a correct histological diagnosis. RESULTS: A total of 186 patients (19G group, n = 90; 22G group, n = 96) were analyzed in the study. The higher sensitivity and accuracy were observed in 19G group than those in the 22G group both in histological evaluation (89.3% vs 76%, p = 0.031; 91.1% vs 79.2%, p = 0.023; respectively) and in the combined histological and cytological evaluations (93.3% vs 81.3%, p = 0.027; 94.4% vs 84.3%, p = 0.027, respectively). However, there were no significant differences in specificity, positive predictive value (PPV), and negative predictive value (NPV). The number of needle passes and the puncture time were significantly lower in the 19G group than that in the 22G group (1.66 ± 0.07 vs 2.25 ± 0.08, p < 0.001; 125.4 ± 4.93s vs 169.0 ± 5.6s p < 0.001; respectively). Only 2 cases were failed in the 19G group and no serious complications occurred. Univariate and multivariate logistic analyses suggested that CA199 levels and needle types are related to the accuracy of the EUS-FNA histological diagnosis. CONCLUSION: EUS-FNA using a 19G needle is effective and safe for solid pancreatic lesions. Compared with the 22G needle, EUS-FNA with a 19G needle can obtain a better histological diagnostic accuracy of solid pancreatic lesions, and with fewer needle passes and in a shorter time.

Potential Prognostic Value and Mechanism of Stromal-Immune Signature in Tumor Microenvironment for Stomach Adenocarcinoma.

Stomach adenocarcinoma (STAD) is one of the most common malignancies. But the molecular mechanism is unknown. In this study, we downloaded the transcriptional profiles and clinical data of 344 STAD and 30 normal samples from The Cancer Genome Atlas (TCGA) database. Stromal and immune scores of STAD were calculated by the Estimation of Stromal and Immune cells in Malignant Tumor tissues using Expression data (ESTIMATE) algorithm, and association of stromal/immune scores with tumor differentiation/T/N/M stage and survival was investigated. The differentially expressed genes (DEGs) between high and low score groups (based on media) were identified, and prognostic genes over-/underexpressed in both STAD and stromal/immune signature were retrieved. Furthermore, proportions of 22 infiltrating immune cells for the cohort from TCGA were estimated by the Cell-type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT) algorithm, and association of 22 immune cells with tumor differentiation/T/N/M stage and survival was investigated. Next, coexpression analysis of 22 immune cells and intersection genes over-/underexpressed in both STAD and stromal signature was conducted. We found high stromal and immune scores and macrophage infiltration predicting poor tumor differentiation and severe local invasion, obtained a list of prognostic genes based on stromal-immune signature, and explored the interaction of collagen, chemokines such as CXCL9, CXCL10, and CXCL11, and macrophage through coexpression analysis and may provide novel prognostic biomarkers and immunotherapeutic targets for STAD.

Development of a Prognostic Signature Based on Single-Cell RNA Sequencing Data of Immune Cells in Intrahepatic Cholangiocarcinoma.

Analysis of single-cell RNA sequencing (scRNA-seq) data of immune cells from the tumor microenvironment (TME) may identify tumor progression biomarkers. This study was designed to investigate the prognostic value of differentially expressed genes (DEGs) in intrahepatic cholangiocarcinoma (ICC) using scRNA-seq. We downloaded the scRNA-seq data of 33,991 cell samples, including 17,090 ICC cell samples and 16,901 ICC adjacent tissue cell samples regarded as normal cells. scRNA-seq data were processed and classified into 20 clusters. The immune cell clusters were extracted and processed again in the same way, and each type of immune cells was divided into several subclusters. In total, 337 marker genes of macrophages and 427 marker genes of B cells were identified by comparing ICC subclusters with normal subclusters. Finally, 659 DEGs were obtained by merging B cell and macrophage marker genes. ICC sample clinical information and gene expression data were downloaded. A nine-prognosis-related-gene (PRG) signature was established by analyzing the correlation between DEGs and overall survival in ICC. The robustness and validity of the signature were verified. Functional enrichment analysis revealed that the nine PRGs were mainly involved in tumor immune mechanisms. In conclusion, we established a PRG signature based on scRNA-seq data from immune cells of patients with ICC. This PRG signature not only reflects the TME immune status but also provides new biomarkers for ICC prognosis.