Screening of Potential Biomarkers for Gastric Cancer with Diagnostic Value Using Label-free Global Proteome Analysis

The prognostic value of RHBDF2 in Pan-Cancer, and its correlation with cell Adhesion of Hepatocellular Carcinoma

The impact of RHBDF2 on the expression and potential function in many cancers is still unknown. Therefore, the expression and methylation modification of RHBDF2 were evaluated across TCGA cancers in this study. Moreover, two methods, COX regression and Kaplan-Meier, were utilized for analyses of the prognoses of RHBDF2 in patients. Besides, the association between RHBDF2 and immune microenvironment, mutation, tumor mutation burden and microsatellite instability was analyzed with Pearson correlation. We verified RHBDF2 expression in hepatocellular carcinoma (HCC) compared with normal cell and tissue samples, detected the effects of RHBDF2 knockdown on biological functions in HCC cells, and detected CD4, CD8 and CD68 expression in hepatocellular carcinoma tissues and paired normal tissues. Given these results, the significant mRNA overexpression and promoter hypomethylation of RHBDF2 in various tumor types was showed, and a clear relationship between RHBDF2 overexpression and unfavourable overall survival and progression-free survival was observed, including liver hepatocellular carcinoma (LIHC), glioma (GBMLGG) and pancreatic adenocarcinoma (PAAD). Additionally, hypomethylation of RHBDF2 can affect the overall survival in some tumors. Furthermore, a clear correlation between RHBDF2 and infiltration of immune cells, immune-related molecules, TMB and MSI was observed. Besides, RHBDF2 expression is upregulated in HCC cells and tissues, and RHBDF2 knockdown could decrease the cell adhesion ability of HCC cells. More importantly, the expression of CD4, CD8 and CD68 was higher in HCC tissues. Altogether, the research denoted that RHBDF2 can be a prognostic biomarker for cancers according to these results and participate in cell adhesion of HCC cells.

Plasma GPI and PGD are associated with vascular normalization and may serve as novel prognostic biomarkers for lung adenocarcinoma: Multi-omics and multi-dimensional analysis

The aim of this study was to explore potential novel plasma protein biomarkers for lung adenocarcinoma (LUAD). A plasma proteomics analysis was carried out and candidate protein biomarkers were validated in 102 LUAD cases and 102 matched healthy controls. The same LUAD tumor tissues were detected to explore the correlation between the expression of candidate proteins in tissues and plasma and vascular normalization. A LUAD active metastasis mice model was constructed to explore the role of candidate proteins for lung metastasis. GPI and PGD were verified to be upregulated in plasma from LUAD patients, and the expression of GPI in tumor tissue was positively correlated with the expression of GPI in plasma and negatively correlated with the normalization of tumor blood vessels. Meanwhile, a negative correlation between the expression of GPI and PGD in plasma and tumor vascular normalization was discovered. In the LUAD active metastasis model, the lowest levels of vascular normalization and the highest expression of GPI and PGD were found in mice with lung metastases. This study found that GPI and PGD may be potential plasma biomarkers for LUAD, and monitoring those may infer the risk of metastasis and malignancy of the tumor. SIGNIFICANT: We identified GPI and PGD as potential novel diagnostic and prognostic biomarkers for LUAD. PGD and GPI can be used as diagnostic biomarkers in combination with other available strategies to assist in the screening and diagnosis of LUAD, and as prognostic biomarkers aid in predict the risk of tumor metastasis and malignancy in patients with LUAD.

Stool Protein Mass Spectrometry Identifies Biomarkers for Early Detection of Diffuse-type Gastric Cancer

There is a high unmet need for early detection approaches for diffuse gastric cancer (DGC). We examined whether the stool proteome of mouse models of gastric cancer (GC) and individuals with hereditary diffuse gastric cancer (HDGC) have utility as biomarkers for early detection. Proteomic mass spectrometry of the stool of a genetically engineered mouse model driven by oncogenic KrasG12D and loss of p53 and Cdh1 in gastric parietal cells [known as Triple Conditional (TCON) mice] identified differentially abundant proteins compared with littermate controls. Immunoblot assays validated a panel of proteins, including actinin alpha 4 (ACTN4), N-acylsphingosine amidohydrolase 2 (ASAH2), dipeptidyl peptidase 4 (DPP4), and valosin-containing protein (VCP), as enriched in TCON stool compared with littermate control stool. Immunofluorescence analysis of these proteins in TCON stomach sections revealed increased protein expression compared with littermate controls. Proteomic mass spectrometry of stool obtained from patients with HDGC with CDH1 mutations identified increased expression of ASAH2, DPP4, VCP, lactotransferrin (LTF), and tropomyosin-2 relative to stool from healthy sex- and age-matched donors. Chemical inhibition of ASAH2 using C6 urea ceramide was toxic to GC cell lines and GC patient-derived organoids. This toxicity was reversed by adding downstream products of the S1P synthesis pathway, which suggested a dependency on ASAH2 activity in GC. An exploratory analysis of the HDGC stool microbiome identified features that correlated with patient tumors. Herein, we provide evidence supporting the potential of analyzing stool biomarkers for the early detection of DGC. Prevention Relevance: This study highlights a novel panel of stool protein biomarkers that correlate with the presence of DGC and has potential use as early detection to improve clinical outcomes.

TagP, a PAAR-domain containing protein, plays roles in the fitness and virulence of Acinetobacter baumannii

Background

Type VI secretion system (T6SS) is widely present in Gram-negative bacteria and directly mediates antagonistic prokaryote interactions. PAAR (proline-alanine-alanine-arginine repeats) proteins have been proven essential for T6SS-mediated secretion and target cell killing. Although PAAR proteins are commonly found in A. baumannii, their biological functions are not fully disclosed yet. In this study, we investigated the functions of a PAAR protein termed TagP (T6SS-associated-gene PAAR), encoded by the gene ACX60_RS09070 outside the core T6SS locus of A. baumannii strain ATCC 17978.

Methods

In this study, tagP null and complement A. baumannii ATCC 17978 strains were constructed. The influence of TagP on T6SS function was investigated through Hcp detection and bacterial competition assay; the influence on environmental fitness was studied through in vitro growth, biofilm formation assay, surface motility assay, survivability in various simulated environmental conditions; the influence on pathogenicity was explored through cell adhesion and invasion assays, intramacrophage survival assay, serum survival assay, and G. melonella Killing assays. Quantitative transcriptomic and proteomic analyses were utilized to observe the global impact of TagP on bacterial status.

Results

Compared with the wildtype strain, the tagP null mutant was impaired in several tested phenotypes such as surface motility, biofilm formation, tolerance to adverse environments, adherence to eukaryotic cells, endurance to serum complement killing, and virulence to Galleria melonella. Notably, although RNA-Seq and proteomics analysis revealed that many genes were significantly down-regulated in the tagP null mutant compared to the wildtype strain, there is no significant difference in their antagonistic abilities. We also found that Histone-like nucleoid structuring protein (H-NS) was significantly upregulated in the tagP null mutant at both mRNA and protein levels.

Conclusions

This study enriches our understanding of the biofunction of PAAR proteins in A. baumannii. The results indicates that TagP involved in a unique modulation of fitness and virulence control in A. baumannii, it is more than a classic PAAR protein involved in T6SS, while how TagP play roles in the fitness and virulence of A. baumannii needs further investigation to clarify.

Construction of oxidative phosphorylation-related prognostic risk score model in uveal melanoma

BACKGROUND

Uveal melanoma (UVM) is a malignant intraocular tumor in adults. Targeting genes related to oxidative phosphorylation (OXPHOS) may play a role in anti-tumor therapy. However, the clinical significance of oxidative phosphorylation in UVM is unclear.

METHOD

The 134 OXPHOS-related genes were obtained from the KEGG pathway, the TCGA UVM dataset contained 80 samples, served as the training set, while GSE22138 and GSE39717 was used as the validation set. LASSO regression was carried out to identify OXPHOS-related prognostic genes. The coefficients obtained from Cox multivariate regression analysis were used to calculate a risk score, which facilitated the construction of a prognostic model. Kaplan-Meier survival analysis, logrank test and ROC curve using the time "timeROC" package were conducted. The immune cell frequency in low- and high-risk group was analyzed through Cibersort tool. The specific genomic alterations were analyzed by "maftools" R package. The differential expressed genes between low- or high-risk group were analyzed and performed Gene Ontology (GO) and GSEA. Finally, we verified the function of CYC1 in UVM by gene silencing in vitro.

RESULTS

A total of 9 OXPHOS-related prognostic genes were identified, including NDUFB1, NDUFB8, ATP12A, NDUFA3, CYC1, COX6B1, ATP6V1G2, ATP4B and NDUFB4. The UVM prognostic risk model was constructed based on the 9 OXPHOS-related prognostic genes. The prognosis of patients in the high-risk group was poorer than low-risk group. Besides, the ROC curve demonstrated that the area under the curve of the model for predicting the 1 to 5-year survival rate of UVM patients were all more than 0.88. External validation in GSE22138 and GSE39717 dataset revealed that these 9 genes could also be utilized to evaluate and predict the overall survival of patients with UVM. The risk score levels related to immune cell frequency and specific genomic alterations. The DEGs between the low- and high- risk group were enriched in tumor OXPHOS and immune related pathway. In vitro experiments, CYC1 silencing significantly inhibited UVM cell proliferation and invasion, induced cell apoptosis.

CONCLUSION

In sum, a prognostic risk score model based on oxidative phosphorylation-related genes in UVM was developed to enhance understanding of the disease. This prognostic risk score model may help to find potential therapeutic targets for UVM patients. CYC1 acts as an oncogene role in UVM.

Gene crosstalk between COVID-19 and preeclampsia revealed by blood transcriptome analysis

Background

The extensive spread of coronavirus disease 2019 (COVID-19) has led to a rapid increase in global mortality. Preeclampsia is a commonly observed pregnancy ailment characterized by high maternal morbidity and mortality rates, in addition to the restriction of fetal growth within the uterine environment. Pregnant individuals afflicted with vascular disorders, including preeclampsia, exhibit an increased susceptibility to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection via mechanisms that have not been fully delineated. Additionally, the intricate molecular mechanisms underlying preeclampsia and COVID-19 have not been fully elucidated. This study aimed to discern commonalities in gene expression, regulators, and pathways shared between COVID-19 and preeclampsia. The objective was to uncover potential insights that could contribute to novel treatment strategies for both COVID-19 and preeclampsia.

Method

Transcriptomic datasets for COVID-19 peripheral blood (GSE152418) and preeclampsia blood (GSE48424) were initially sourced from the Gene Expression Omnibus (GEO) database. Subsequent to that, we conducted a subanalysis by selecting females from the GSE152418 dataset and employed the "Deseq2" package to identify genes that exhibited differential expression. Simultaneously, the "limma" package was applied to identify differentially expressed genes (DEGs) in the preeclampsia dataset (GSE48424). Following that, an intersection analysis was conducted to identify the common DEGs obtained from both the COVID-19 and preeclampsia datasets. The identified shared DEGs were subsequently utilized for functional enrichment analysis, transcription factor (TF) and microRNAs (miRNA) prediction, pathway analysis, and identification of potential candidate drugs. Finally, to validate the bioinformatics findings, we collected peripheral blood mononuclear cell (PBMC) samples from healthy individuals, COVID-19 patients, and Preeclampsia patients. The abundance of the top 10 Hub genes in both diseases was assessed using real-time quantitative polymerase chain reaction (RT-qPCR).

Result

A total of 355 overlapping DEGs were identified in both preeclampsia and COVID-19 datasets. Subsequent ontological analysis, encompassing Gene Ontology (GO) functional assessment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, revealed a significant association between the two conditions. Protein-protein interactions (PPIs) were constructed using the STRING database. Additionally, the top 10 hub genes (MRPL11, MRPS12, UQCRH, ATP5I, UQCRQ, ATP5D, COX6B1, ATP5O, ATP5H, NDUFA6) were selected based on their ranking scores using the degree algorithm, which considered the shared DEGs. Moreover, transcription factor-gene interactions, protein-drug interactions, co-regulatory networks of DEGs and miRNAs, and protein-drug interactions involving the shared DEGs were also identified in the datasets. Finally, RT-PCR results confirmed that 10 hub genes do exhibit distinct expression profiles in the two diseases.

Conclusion

This study successfully identified overlapping DEGs, functional pathways, and regulatory elements between COVID-19 and preeclampsia. The findings provide valuable insights into the shared molecular mechanisms and potential therapeutic targets for both diseases. The validation through RT-qPCR further supports the distinct expression profiles of the identified hub genes in COVID-19 and preeclampsia, emphasizing their potential roles as biomarkers or therapeutic targets in these conditions.

Prognostic Value and Therapeutic Significance of CCL Chemokines in Gastric Cancer

BACKGROUND

Gastric cancer is one of the most common malignant tumours of the gastrointestinal tract, which has a significant negative impact on human health.

AIMS

CCL chemokines play important roles in a variety of tumor microenvironments; nevertheless, gastric cancer has surprisingly limited associations with CCL chemokines.

METHODS

In our study, we comprehensively utilized bioinformatics analysis tools and databases such as cBioPortal, UALCAN, GEPIA, GeneMANIA, STRING, and TRRUST to clarify the clinical significance and biology function of CCL chemokines in gastric cancer.

RESULTS

The mRNA expression levels of CCL1/3/4/5/7/8/14/15/18/20/21/22/26 were up-regulated, while the mRNA expression levels of CCL2/11/13/16/17/19/23/24/25/28 were down-regulated. The chemokine significantly associated with the pathological stage of gastric cancer is CCL2/11/19/21. In gastric cancer, the expression level of CCL chemokines was not associated with disease-free survival, but low expression of CCL14 was significantly associated with longer overall survival. Therein, associated with the regulation of CCL chemokines are only 10 transcription factors (RELA, NFKB1, STAT6, IRF3, REL, SPI1, STAT1, STAT3, JUN and SP1). The major biological process and functional enrichment of CCL chemokines are to induce cell-directed migration.

CONCLUSION

These results may indicate that CCL chemokines may be immunotherapeutic targets and promising prognostic biomarkers for gastric cancer.

Data-driven decision-making for precision diagnosis of digestive diseases

Modern omics technologies can generate massive amounts of biomedical data, providing unprecedented opportunities for individualized precision medicine. However, traditional statistical methods cannot effectively process and utilize such big data. To meet this new challenge, machine learning algorithms have been developed and applied rapidly in recent years, which are capable of reducing dimensionality, extracting features, organizing data and forming automatable data-driven clinical decision systems. Data-driven clinical decision-making have promising applications in precision medicine and has been studied in digestive diseases, including early diagnosis and screening, molecular typing, staging and stratification of digestive malignancies, as well as precise diagnosis of Crohn's disease, auxiliary diagnosis of imaging and endoscopy, differential diagnosis of cystic lesions, etiology discrimination of acute abdominal pain, stratification of upper gastrointestinal bleeding (UGIB), and real-time diagnosis of esophageal motility function, showing good application prospects. Herein, we reviewed the recent progress of data-driven clinical decision making in precision diagnosis of digestive diseases and discussed the limitations of data-driven decision making after a brief introduction of methods for data-driven decision making.

Sex differences in the progression of glucose metabolism dysfunction in Alzheimer's disease

Alzheimer's disease (AD) is a common neurodegenerative disease characterized by amyloid plaques and impaired brain metabolism. Because women have a higher prevalence of AD than men, sex differences are of great interest. Using cross-sectional and longitudinal data, we showed sex-dependent metabolic dysregulations in the brains of AD patients. Cohort 1 (South Korean, n = 181) underwent Pittsburgh compound B-PET, fluorodeoxyglucose-PET, magnetic resonance imaging, and blood biomarker (plasma tau and beta-amyloid 42 and 40) measurements at baseline and two-year follow-ups. Transcriptome analysis of data from Cohorts 2 and 3 (European, n = 78; Singaporean, n = 18) revealed sex differences in AD-related alterations in brain metabolism. In women (but not in men), all imaging indicators displayed consistent correlation curves with AD progression. At the two-year follow-up, clear brain metabolic impairment was revealed only in women, and the plasma beta-amyloid 42/40 ratio was a possible biomarker for brain metabolism in women. Furthermore, our transcriptome analysis revealed sex differences in transcriptomes and metabolism in the brains of AD patients as well as a molecular network of 25 female-specific glucose metabolic genes (FGGs). We discovered four key-attractor FGG genes (ALDOA, ENO2, PRKACB, and PPP2R5D) that were associated with amyloid/tau-related genes (APP, MAPT, BACE1, and BACE2). Furthermore, these genes successfully distinguished amyloid positivity in women. Understanding sex differences in the pathogenesis of AD and considering these differences will improve development of effective diagnostics and therapeutic treatments for AD.

PYY modulates the tumorigenesis and progression of colorectal cancer unveiled by proteomics

Despite decrease in mortality caused by colorectal cancer (CRC), there remains no effective therapeutic method for patients with CRC. We attempted to screen biomarkers with therapeutic values in CRC. Proteomic analysis was performed on tumor, tumor-adjacent, and normal tissues derived from five patients with colon adenocarcinoma (COAD) via label-free proteome profiling. Differentially expressed proteins (DEPs) were identified, and functional annotation was performed based on the gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. The effect of marker proteins on CRC was determined via cell function experiments and using tumor organoid models. The localization of the marker proteins was determined via immunofluorescence. A total of 126 DEPs were identified in COAD tissues compared with normal tissues, of which Peptide YY (PYY) overlapped among the tumor, adjacent, and normal groups. DEPs in the cancer group vs. normal group were enriched in the regulation of cell cycle checkpoint, developmental process, focal adhesion, and apoptosis-related pathways. The low expression of PYY in CRC tissues was verified via qRT-PCR, western blotting, and immunohistochemistry. Overexpression of PYY promoted apoptosis and inhibited the proliferation, migration, and invasion of HCT116 and HT29 cells. Furthermore, PYY was secreted by neurons and its supplementation suppressed tumor organoid growth in a dose-dependent manner. In conclusion, PYY exerted inhibitory action on CRC and could be a therapeutic target for CRC.

Systematic identification of cell-fate regulatory programs using a single-cell atlas of mouse development

Waddington's epigenetic landscape is a metaphor frequently used to illustrate cell differentiation. Recent advances in single-cell genomics are altering our understanding of the Waddington landscape, yet the molecular mechanisms of cell-fate decisions remain poorly understood. We constructed a cell landscape of mouse lineage differentiation during development at the single-cell level and described both lineage-common and lineage-specific regulatory programs during cell-type maturation. We also found lineage-common regulatory programs that are broadly active during the development of invertebrates and vertebrates. In particular, we identified Xbp1 as an evolutionarily conserved regulator of cell-fate determinations across different species. We demonstrated that Xbp1 transcriptional regulation is important for the stabilization of the gene-regulatory networks for a wide range of mouse cell types. Our results offer genetic and molecular insights into cellular gene-regulatory programs and will serve as a basis for further advancing the understanding of cell-fate decisions.

Cross-Talk of Focal Adhesion-Related Gene Defines Prognosis and the Immune Microenvironment in Gastric Cancer

Background: Focal adhesion, as the intermediary between tumor cells and extracellular matrix communication, plays a variety of roles in tumor invasion, migration, and drug resistance. However, the potential role of focal adhesion-related genes in the microenvironment, immune cell infiltration, and drug sensitivity of gastric cancer (GC) has not yet been revealed.

Methods: The genetic and transcriptional perspectives of focal adhesion-related genes were systematically analyzed. From a genetic perspective, the focal adhesion index (FAI) was constructed based on 18 prognosis-related focus adhesion-related genes to evaluate the immune microenvironment and drug sensitivity. Then three prognosis-related genes were used for consistent clustering to identify GC subtypes. Finally, use FLT1, EGF, COL5A2, and M2 macrophages to develop risk signatures, and establish a nomogram together with clinicopathological characteristics.

Results: Mutations in the focal adhesion-related gene affect the survival time and clinical characteristics of GC patients. FAI has been associated with a shorter survival time, immune signaling pathways, M2 macrophage infiltration, epithelial-mesenchymal transition (EMT) signaling, and diffuse type of GC. FAI recognizes ALK, cell cycle, and BMX signaling pathways inhibitors as sensitive agents for the treatment of GC. FLT1, EGF, and COL5A2 may distinguish GC subtypes. The established risk signature is of great significance to the prognostic evaluation of GC based on FLT1, EGF, and COL5A2 and M2 macrophage expression.

Conclusion: The focal adhesion-related gene is a potential biomarker for the evaluation of the immune microenvironment and prognosis. This work emphasizes the potential impact of the focal adhesion pathway in GC therapy and highlights its guiding role in prognostic evaluation.

Biomarkers for Gastric Cancer Screening and Early Diagnosis

Gastric cancer is one of the most common cancers worldwide, with a bad prognosis associated with late-stage diagnosis, significantly decreasing the overall survival. This highlights the importance of early detection to improve the clinical course of these patients. Although screening programs, based on endoscopic or radiologic approaches, have been useful in countries with high incidence, they are not cost-effective in low-incidence populations as a massive screening strategy. Additionally, current biomarkers used in daily routine are not specific and sensitive enough, and most of them are obtained invasively. Thus, it is imperative to discover new noninvasive biomarkers able to diagnose early-stage gastric cancer. In this context, liquid biopsy is a promising strategy. In this review, we briefly discuss some of the potential biomarkers for gastric cancer screening and diagnosis identified in blood, saliva, urine, stool, and gastric juice.

SMOX expression predicts the prognosis of non-small cell lung cancer

Background

The development of non-small cell lung cancer (NSCLC) is very rapid, and the effect of its treatment is often closely related to the diagnosis time of the disease. Therefore, simple and convenient tumor biomarkers are helpful for the timely diagnosis and prevention of NSCLC.

Methods

Through univariate and multivariate Cox regression analyses, SMOX was determined as an independent prognostic factor of GSE42127, GSE41271, GSE68465, and TCGA datasets. Furthermore, western blot, reverse transcription-polymerase chain reaction (RT-PCR), and immunohistochemical analysis were performed to confirm the predictive efficiency of SMOX expression in NSCLC.

Results

Patients were divided into high and low expression groups according to the median value of SMOX expression, and Kaplan-Meier curves of multiple datasets indicated that patients with low SMOX expression had a better survival rate. According to the analysis of immune infiltration, the immune microenvironment, and immune checkpoints, SMOX expression of the high and low groups showed differences in immunity in NSCLC. By comparing cancer and adjacent tissues using western blot analysis, RT-PCR and immunohistochemical analysis, we found that SMOX was highly expressed in tumor tissues and had low expression in adjacent tissues. Simultaneously, the Kaplan-Meier curve suggested that among the 155 NSCLC patients, those with low SMOX expression had better survival.

Conclusions

SMOX can be used as an effective predictive target for NSCLC.