SCDb: an integrated database of stomach cancer

Delineating protein biomarkers for gastric cancers: A catalogue of mass spectrometry-based markers and assessing their suitability for targeted proteomics applications

Gastric cancer (GC) is a global health concern. To facilitate improved management of GCs protein biomarkers have been identified through mass spectrometry-based proteomics platforms. In order to exhibit clinical utility of such data, we congregated over 6800 differentially regulated proteins in GCs from proteomics studies and recorded the mass spectrometry platforms, association of the protein with infectious agents, protein identifiers, sample size and clinical characters of samples used with details on validation. Development of targeted proteomics methods is the cornerstone for pursuing these markers into clinical utility. Therefore, we developed Protein Biomarker Matrix for Gastric Cancer (PBMGC), a simple catalogue of robustness of each protein. This analysis yielded the identification of robust tissue, serum, urine and prognostic protein panels which can be further tested for their clinical utility. We also ascertained proteotypic tryptic peptides of 5631 proteins suitable for developing MRM assays. Extensive characterization of these peptides was carried out to record peptide ions, mass/charge and enhanced specific peptide features. With the vision of catering to proteomics researchers, the data generated through this analysis has been catalogued at Gastric Cancer Proteomics DataBase (GCPDB) (https://ciods.in/gcpdb/). Users can browse and download the data and improve GCPDB by submitting recently published data. SIGNIFICANCE: Mass spectrometry-based proteomics platforms have accumulated substantial data on protein differential regulation in gastric cancer (GC) clinical samples. The utility of such data in clinical applications is limited by search for suitable biomarker panels for assessing GCs. We assembled over 6800 differentially regulated proteins in GCs from proteomics studies and recorded the corresponding details including mass spectrometry platforms, status on the association of the protein with infectious agents, protein identifiers from different databases, sample size and clinical characters of samples used in test and control conditions along with details on their validation. Towards the vision of utilizing these markers in clinical assays, Protein Biomarker Matrix for Gastric Cancer (PBMGC) was developed and clinically relevant multi-protein panels were identified. We also demonstrated identification and characterization of tryptic proteotypic tryptic peptides of 5631 proteins biomarkers of GCs which are suitable for development of multiple reaction monitoring (MRM) assays in a SCIEX QTRAP instrument. With the moto of catering to proteomics researchers, the data generated through this analysis has been catalogued at Gastric Cancer Proteomics DataBase (GCPDB) (https://ciods.in/gcpdb/). The users can browse and download details on different markers and improve GCPDB by submitting recently published data. Such an analysis could lay a cornerstone for building more such resources or conduct such analysis in different clinical conditions to uptake and develop targeted proteomics as the method of choice for clinical applications.

β-Glucan-Mediated Oral Codelivery of 5FU and Bcl2 siRNA Attenuates Stomach Cancer

Based on cancer-related deaths, stomach cancer is ranked fifth, and first among Hispanics. Lack of technologies for early diagnosis and unavailability of target-specific therapeutics are largely the causes of the poor therapeutic outcomes from existing chemotherapeutics. Currently available therapeutic modalities are invasive and require systemic delivery, although the cancer is localized in the stomach at its early stage. Therefore, we hypothesize that an oral local delivery approach can extend the retention duration of the therapeutics modalities within the stomach and thereby enhance therapeutic efficacy. To accomplish this, we have developed a ß-glucan (BG)-based oral delivery vehicle that can adhere to the mucus lining of the stomach for an extended period while controlling the release of Bcl2 siRNA and 5-fluorouracil (5FU) payload for over 6 h. We found that Bcl2 siRNA selectively knocked down the Bcl2 gene in a C57BL/6 stomach cancer mouse model followed by upregulation of apoptosis and remission of cancer. BG was found to be very effective in maintaining the stability of siRNA for at least 6 h, when submerged in simulated gastric juice tested in vitro. To investigate the potential therapeutic effects in vivo, we used a stomach cancer mouse model, where C57BL/6 mice were treated with 5FU, BG/5FU, siRNA, BG/siRNA, and BG/5FU/siRNA. Higher inhibition of Bcl2 and therapeutic efficacy were observed in mice treated with BG/5FU/siRNA confirmed with Western blotting and a TUNEL assay. Significant reduction in the tumor region was observed with histology (H&E) and immunohistochemistry (Ki67, TUNEL, and Bcl2) analyses. Overall, the oral formulation shows improved efficacy with nonsignificant side effects compared to the conventional treatment tested in the gastric cancer mouse model.

Ligustrazine exerts neuroprotective effects via circ_0008146/miR-709/Cx3cr1 axis to inhibit cell apoptosis and inflammation after cerebral ischemia/reperfusion injury

BACKGROUND

Ligustrazine is a traditional Chinese herbal medicine that has long been used to treat cerebral ischemic disorders. However, the molecular mechanisms of ligustrazine in cerebral ischemia/reperfusion (I/R) damage have not been clear elucidated. The aim of this study was to examine the neuroprotective mechanisms of ligustrazine in cerebral I/R.

METHODS

9 C57BL/6 mice were randomly divided to three groups: Sham group (n = 3), Middle cerebral artery occlusion (MCAO) group (n = 3), and MCAO + Ligustrazine group (n = 3). The neurological deficit score was evaluated, the cerebral infarct volume was measured by triphenylterazolium chloride (TTC) staining. Differentially expressed (DE) messenger RNAs (mRNAs), long noncoding RNAs (lncRNAs) and circular RNAs (circRNAs) were analyzed using the R package DEseq2 based on P-value < 0.05 and Log2 |fold change (FC)| ≥ 2 in sham group vs MCAO group and MCAO group vs ligustrazine group by high-throughput sequencing. Function enrichment analysis, the protein-protein interaction (PPI) of neurogenesis related genes were performed. The neurogenesis related competitive endogenous RNA (ceRNA) network was constructed.

RESULTS

The expression of circ_0008146 was considerably higher in the MCAO group than the Sham group, and ligustrazine treatment markedly decreased the expression of circ_0008146 in MCAO. Next, the circ_0008146 ceRNA network was established, including circ_0008146-miR-709-Cx3cr1 ceRNA network. Besides, real time quantitative polymerase chain reaction (RT-qPCR) assay identified that miR-709 expression was considerably lower and Cx3cr1 expression was higher in the MCAO group than Sham group, and ligustrazine treatment markedly increased the miR-709 expression and reduced Cx3cr1 expression in MCAO. Further, silencing of circ_0008146 inhibited the concentration of Interleukin 6 (IL-6), Tumor Necrosis Factor alpha (TNF-α) and reduced neuron cell death and up-regulated miR-709 expression and down-regulated Cx3cr1 expression in Lipopolysaccharide (LPS) induced BV-2 cells. Dual-Luciferase reporter gene assay verified that circ_0008146 targeted miR-709.

CONCLUSION

Ligustrazine targets circ_0008146/miR-709/Cx3cr1 axis to inhibit cell apoptosis and inflammation after cerebral ischemia/reperfusion injury.

The Diagnostic and Predictive Significance of Immune-Related Genes and Immune Characteristics in the Occurrence and Progression of IgA Nephropathy

Objective

To investigate the potential diagnostic and predictive significance of immune-related genes in IgA nephropathy (IgAN) and discover the abnormal glomerular inflammation in IgAN.

Methods

GSE116626 was used as a training set to identify different immune-related genes (DIRGs) and establish machine learning models for the diagnosis of IgAN; then, a nomogram model was generated based on GSE116626, and GSE115857 was used as a test set to evaluate its clinical value. Short Time-Series Expression Miner (STEM) analysis was also performed to explore the changing trend of DIRGs with the progression of IgAN lesions. GSE141344 was used with DIRGs to establish the ceRNA network associated with IgAN progression. Finally, ssGSEA analysis was performed on the GSE141295 dataset to discover the abnormal inflammation in IgAN.

Results

Machine learning (ML) performed excellently in diagnosing IgAN using six DIRGs. A nomogram model was constructed to predict IgAN based on the six DIRGs. Three trends related to IgAN lesions were identified using STEM analysis. A ceRNA network associated with IgAN progression which contained 8 miRNAs, 14 lncRNAs, and 3 mRNAs was established. A higher macrophage ratio and lower CD4+ T cell ratio in IgAN compared to controls were observed, and the correlation between macrophages and monocytes in the glomeruli of IgAN patients was inverse compared to controls.

Conclusion

This study reveals the diagnostic and predictive significance of DIRGs in IgAN and finds that the imbalance between macrophages and CD4+ immune cells may be an important pathomechanism of IgAN. These results provide potential directions for the treatment and prevention of IgAN.

Ultrasound Image-Guided Nerve Block Combined with General Anesthesia under an Artificial Intelligence Algorithm on Patients Undergoing Radical Gastrectomy for Gastric Cancer during and after Operation

This study was aimed at investigating the location of gastric cancer by using a gastroscope image based on an artificial intelligence algorithm for gastric cancer and the effect of ultrasonic-guided nerve block combined with general anesthesia on patients undergoing gastric cancer surgery. A total of 160 patients who were undergoing gastric cancer surgery from March 2019 to March 2021 were collected as the research objects, and the convolutional neural network (CNN) algorithm was used to segment the gastroscope image of gastric cancer. The patients were randomly divided into a simple general anesthesia group of 80 cases and a transversus abdominis plane block combined with rectus abdominis sheath block combined with the general anesthesia group of 80 cases. Then, compare the systolic blood pressure (SBP), diastolic blood pressure (DBP), and heart rate (HR) at the four time points T0, T1, T2, and T3. The times of analgesic drug use within 48 hours after operation and postoperative adverse reactions were recorded. The visual analog scale (VAS) scores were also recorded at 4 h, 12 h, 24 h, and 48 h. The results show that the image quality after segmentation is good: the accuracy of tumor location is 75.67%, which is similar to that of professional endoscopists. Compared with the general anesthesia group, the transversus abdominis plane block combined with the rectus sheath block combined with the general anesthesia group had fewer anesthetics, and the difference was statistically significant (P < 0.05). Compared with the general anesthesia group, SBP, DBP, and HR were significantly reduced at T1, T2, and T3 in the transverse abdominis plane block combined with rectus sheath block and general anesthesia group (P < 0.05). Compared with the simple general anesthesia group, the VAS scores of the transversus abdominis plane block combined with rectus sheath block combined with the general anesthesia group decreased at 4 h, 12 h, and 24 h after surgery, and the difference was statistically significant (P < 0.05). The number of analgesics used in transversus abdominis plane block combined with the rectus sheath block combined with the general anesthesia group within 48 hours after operation was significantly less than that in the general anesthesia group, and the difference was statistically significant (P < 0.05). The average incidence of adverse reactions in the nerve block combined with the general anesthesia group was 2.5%, which was lower than the average incidence of 3.75% in the general anesthesia group. In summary, the CNN algorithm can accurately segment the lesions in the ultrasonic images of gastric cancer, which was convenient for doctors to make a more accurate judgment on the lesions, and provided a basis for the preoperative examination of radical gastrectomy for gastric cancer. Ultrasonic-guided nerve block combined with general anesthesia can effectively improve the analgesic effect of radical gastrectomy for gastric cancer, reduced intraoperative and postoperative adverse reactions and analgesic drug dosage, and had a good effect on postoperative recovery of patients. The combined application of these two methods can further improve the precision treatment of gastric cancer patients and accelerate postoperative recovery.

Machine learning algorithm of ultrasound-mediated intestinal function recovery and nursing efficacy analysis of lower gastrointestinal malignant tumor after surgery

Objectives:

In this paper, machine learning algorithms was used to explore the application value of ultrasound contrast in the early evaluation of neoadjuvant chemotherapy in patients with gastrointestinal malignant liver metastases, and analyzes the effect of sports nursing methods on intestinal function recovery.

Methods:

Forty-seven patients with gastrointestinal malignancies were divided into 25 patients (combined chemotherapy group) and 22 cases (chemotherapy group) from April 2018 to April 2019. Two groups of patients were treated with CEUS. The effective lesion patients and invalid quantitative parameters were compared between the two groups before and after treatment, and the postoperative routine nursing was implemented.

Results:

Chemotherapy group effective in 18 cases, accounting for 81.82%; 4 cases, 18.18%. Combination chemotherapy patients 21 cases, accounting for 84.00%; 4 cases, accounting for 16.00%.

Conclusion:

Based on early is important to assess the efficacy of neoadjuvant chemotherapy in patients with liver metastases peak intensity ultrasound contrast parameters of the machine learning algorithms malignant tumors in the gastrointestinal tract, post-operative care movement helps to restore bowel function.

Predicting Associations of miRNAs and Candidate Gastric Cancer Genes for Nanomedicine

Nanoscale miRNAs regulate the synthesis of most human proteins involved in differentiation, proliferation, cell cycle, apoptosis, and other processes associated with the growth and the development of an organism. miRNAs also play a number of important roles in the development of gastric cancer. In this work, we studied the quantitative characteristics of miRNA interactions with 69 candidate gastric cancer genes using bioinformatics approaches. To this end, the MirTarget program was used, which determines the characteristics of miRNA binding to mRNA in the 5′UTR, CDS, and 3′UTR. Associations of miRNAs with alternative target genes and associations of genes with alternative miRNAs were established. The cluster organization of miRNA binding sites (BSs) in mRNA was revealed, leading to the emergence of miRNA competition for binding to the mRNA of a target gene. Groups of target genes with clusters of overlapping BSs include miR-5095, miR-619-5p, miR-1273 family, miR-466, ID01030.3p-miR, ID00436.3p-miR, miR-574-5p, and ID00470.5p-miR. In the defined associations of target genes and miRNAs, miRNA BSs are organized into clusters of multiple BSs, which facilitate the design and the development of a system of chips that can be used to control the state of miRNA and target genes associations in gastric cancer.