Discovery of Prognostic Signature Genes for Overall Survival Prediction in Gastric Cancer

Gancao Xiexin Decoction inhibits gastric carcinoma proliferation and migration by regulating the JAK2/STAT3 signalling pathway

ETHNOPHARMACOLOGICAL RELEVANCE

The incidence of gastric carcinoma (GC) is increasing rapidly. Traditional Chinese Medicine (TCM) plays a unique role in the treatment of GC. At present, Gancao Xiexin Decoction (GCXXD) has been proved to have a good therapeutic effect on diseases of the spleen and stomach system, but relevant molecular mechanisms remain incompletely explained.

AIM OF STUDY

The mechanism of GCXXD for GC was investigated by network pharmacology and verified by cell experiments.

MATERIALS AND METHODS

Firstly, the public database was used to identify the core targets and key pathways of GCXXD in treating GC, followed by molecular docking and survival analysis. Subsequently, the effects of GCXXD on human gastric cancer AGS and HGC-27 cells were confirmed by a series of experiments, such as CCK-8, colony formation, apoptosis, cell cycle, wound scratch assay, transwell chamber assay, qRT-PCR and Western blot.

RESULTS

This study identified quercetin, wogonin, kaempferol, baicalein, sitosterol and beta-sitosterol as key ingredients, along with AKT1, TP53, JUN, STAT3, TNF, MAPK3, HSP90AA1 and EGFR as co targets, and the JAK/STAT signalling pathway as the key pathway. The experimental results showed that GCXXD inhibited the growth of GC cells, increased the apoptosis rate and the ratio of G0/G1 phase cells, and weakened the clone formation rate and inhibited cell migration and invasion. It also reduces the expression of core target genes and downregulates the expression of JAK2, p-JAK2, STAT3, and p-STAT3 proteins.

CONCLUSION

GCXXD inhibits GC cell growth, reduces clonogenic capacity, induces apoptosis, blocks the cell cycle, and decreases cell migration and invasion rates by inhibiting the JAK2/STAT3 signalling pathway.

RSRC2 Expression Inhibits Malignant Progression of Triple-Negative Breast Cancer by Transcriptionally Regulating SCIN Expression

Triple-negative breast cancer (TNBC) has a shorter survival time and higher mortality rate than other molecular subtypes. RSRC2 is a newly discovered tumor suppressor gene. However, the potential functional mechanism of RSRC2 in TNBC remains unknown so far. Multiple bioinformatics databases were used. A Human Transcriptome Array 2.0 analysis, ChIP-seq analysis, ChIP-qPCR, RT-qPCR, Western blot, cell function assays in vitro and a metastatic mouse model in vivo were performed to demonstrate the role of RSRC2 in TNBC. Through the analysis of various databases, RSRC2 expression was the lowest in TNBC tissues compared to other molecular subtypes. The low expression of RSRC2 was associated with a worse prognosis for patients with breast cancer. The transcriptome array, ChIP-seq and bioinformatics analysis identified that GRHL2 and SCIN might have a close relationship with RSRC2. The functional bioinformatics enrichment analysis and functional cell experiments showed that RSRC2 was involved in cell adhesion, cell proliferation, cell migration and invasion. Furthermore, RSRC2 expression suppressed SCIN expression but not GRHL2 expression. SCIN re-expression in the RSRC2 overexpression cells or SCIN knockdown in the RSRC2 knockdown cells reversed the cellular function caused by RSRC2. Mechanistically, RSRC2 transcriptionally inhibited SCIN expression. In summary, our study reveals that RSRC2 acts as a tumor suppressor in TNBC development and progression through negatively regulating SCIN-mediated cell function, thus providing a potential target for TNBC treatment.

Good or bad: Paradox of plasminogen activator inhibitor 1 (PAI-1) in digestive system tumors

The fibrinolytic system is involved in many physiological functions, among which the important members can interact with each other, either synergistically or antagonistically to participate in the pathogenesis of many diseases. Plasminogen activator inhibitor 1 (PAI-1) acts as a crucial element of the fibrinolytic system and functions in an anti-fibrinolytic manner in the normal coagulation process. It inhibits plasminogen activator, and affects the relationship between cells and extracellular matrix. PAI-1 not only involved in blood diseases, inflammation, obesity and metabolic syndrome but also in tumor pathology. Especially PAI-1 plays a different role in different digestive tumors as an oncogene or cancer suppressor, even a dual role for the same cancer. We term this phenomenon "PAI-1 paradox". PAI-1 is acknowledged to have both uPA-dependent and -independent effects, and its different actions can result in both beneficial and adverse consequences. Therefore, this review will elaborate on PAI-1 structure, the dual value of PAI-1 in different digestive system tumors, gene polymorphisms, the uPA-dependent and -independent mechanisms of regulatory networks, and the drugs targeted by PAI-1 to deepen the comprehensive understanding of PAI-1 in digestive system tumors.

Structures of MPND Reveal the Molecular Recognition of Nucleosomes

Adenine N⁶ methylation in DNA (6mA) is a well-known epigenetic modification in bacteria, phages, and eukaryotes. Recent research has identified the Mpr1/Pad1 N-terminal (MPN) domain-containing protein (MPND) as a sensor protein that may recognize DNA 6mA modification in eukaryotes. However, the structural details of MPND and the molecular mechanism of their interaction remain unknown. Herein, we report the first crystal structures of the apo-MPND and MPND-DNA complex at resolutions of 2.06 Å and 2.47 Å, respectively. In solution, the assemblies of both apo-MPND and MPND-DNA are dynamic. In addition, MPND was found to possess the ability to bind directly to histones, no matter the N-terminal restriction enzyme-adenine methylase-associated domain or the C-terminal MPN domain. Moreover, the DNA and the two acidic regions of MPND synergistically enhance the interaction between MPND and histones. Therefore, our findings provide the first structural information regarding the MPND-DNA complex and also provide evidence of MPND-nucleosome interactions, thereby laying the foundation for further studies on gene control and transcriptional regulation.

Models for Predicting Response to Immunotherapy and Prognosis in Patients with Gastric Cancer: DNA Damage Response Genes

Objective

DNA damage response (DDR) is a complex system that maintains genetic integrity and the stable replication and transmission of genetic material. m6A modifies DDR-related gene expression and affects the balance of DNA damage response in tumor cells. In this study, a risk model based on m6A-modified DDR-related gene was established to evaluate its role in patients with gastric cancer.

Methods

We downloaded 639 DNA damage response genes from the Gene Set Enrichment Analysis (GSEA) database and constructed risk score models using typed differential genes. We used Kaplan-Meier curves and risk curves to verify the clinical relevance of the model, which was then validated with the univariate and multifactorial Cox analysis, ROC, C-index, and nomogram, and finally this model was used to evaluate the correlation of the risk score model with immune microenvironment, microsatellite instability (MSI), tumor mutational burden (TMB), and immune checkpoints.

Results

In this study, 337 samples in The Cancer Genome Atlas (TCGA) database were used as training set to construct a DDR-related gene model, and GSE84437 was used as external data set for verification. We found that the prognosis and immunotherapy effect of gastric cancer patients in the low-risk group were significantly better than those in the high-risk group.

Conclusion

We screened eight DDR-related genes (ZBTB7A, POLQ, CHEK1, NPDC1, RAMP1, AXIN2, SFRP2, and APOD) to establish a risk model, which can predict the prognosis of gastric cancer patients and guide the clinical implementation of immunotherapy.

RAI14 Promotes Melanoma Progression by Regulating the FBXO32/c-MYC Pathway

Melanoma originates from the malignant transformation of melanocytes. Compared with other skin cancers, melanoma has a higher fatality rate. The 5-year survival rate of patients with early-stage primary melanoma through surgical resection can reach more than 90%. However, the 5-year survival rate of patients with metastatic melanoma is only 25%. Therefore, accurate assessment of melanoma progression is critical. Previous studies have found that Retinoic Acid Induced 14(RAI14) is critical in tumorigenesis. However, the biological function of RAI14 for the development of melanoma is unclear. In this study, RAI14 is highly expressed in melanoma and correlated with prognosis. The expression of RAI14 can affect the proliferation, migration and invasion of melanoma cells. F-Box Protein 32(FBXO32) is an E3 ubiquitin ligase of c-MYC. We found that RAI14 affects the transcriptional expression of FBXO32 and regulates the stability of c-MYC. These results suggest that RAI14 play an important role in the growth of melanoma and is expected to be a therapeutic target for melanoma.

Construction and validation of a novel coagulation-related 7-gene prognostic signature for gastric cancer

Background: Gastric cancer (GC) is the most common malignant tumor. Due to the lack of practical molecular markers, the prognosis of patients with advanced gastric cancer is still poor. A number of studies have confirmed that the coagulation system is closely related to tumor progression. Therefore, the purpose of this study was to construct a coagulation-related gene signature and prognostic model for GC by bioinformatics methods.

Methods: We downloaded the gene expression and clinical data of GC patients from the TCGA and GEO databases. In total, 216 coagulation-related genes (CRGs) were obtained from AmiGO 2. Weighted gene co-expression network analysis (WGCNA) was used to identify coagulation-related genes associated with the clinical features of GC. Last absolute shrinkage and selection operator (LASSO) Cox regression was utilized to shrink the relevant predictors of the coagulation system, and a Coag-Score prognostic model was constructed based on the coefficients. According to this risk model, GC patients were divided into high-risk and low-risk groups, and overall survival (OS) curves and receiver operating characteristic (ROC) curves were drawn in the training and validation sets, respectively. We also constructed nomograms for predicting 1-, 2-, and 3-year survival in GC patients. Single-sample gene set enrichment analysis (ssGSEA) was exploited to explore immune cells’ underlying mechanisms and correlations. The expression levels of coagulation-related genes were verified by real-time quantitative polymerase chain reaction (qRT-PCR) and immunohistochemistry (IHC).

Results: We identified seven CRGs employed to construct a Coag-Score risk model using WGCNA combined with LASSO regression. In both training and validation sets, GC patients in the high-risk group had worse OS than those in the low-risk group, and Coag-Score was identified as an independent predictor of OS, and the nomogram provided a quantitative method to predict the 1-, 2-, and 3-year survival rates of GC patients. Functional analysis showed that Coag-Score was mainly related to the MAPK signaling pathway, complement and coagulation cascades, angiogenesis, epithelial–mesenchymal transition (EMT), and KRAS signaling pathway. In addition, the high-risk group had a significantly higher infiltration enrichment score and was positively associated with immune checkpoint gene expression. Conclusion: Coagulation-related gene models provide new insights and targets for the diagnosis, prognosis prediction, and treatment management of GC patients.

Pan-Cancer Analysis of OLFML2B Expression and Its Association With Prognosis and Immune Infiltration

Background: The function of olfactomedin-like 2B (OLFML2B), as a member of the olfactomedin domain-containing protein family, remains ambiguous, especially in tumors. The current study explores the possible correlation between OLFML2B, prognosis, and immune infiltration in pan-cancer. Methods: We applied a number of bioinformatics techniques to probe the prospective function of OLFML2B, consisting of its association with prognosis, clinicopathology, alteration, GSEA, tumor microenvironment (TME), immune-associated genes, immune infiltration, tumor mutational burden (TMB), microsatellite instability (MSI), and drug sensitivity in several cancer types. qPCR and immunohistochemistry were used to identify OLFML2B expression in LIHC cell lines and liver cancer tissues. Results: We discovered that OLFML2B was overexpressed in 14 cancers and positively related to several cancer type prognoses. The expression of OLFML2B was further validated in the LIHC cell lines. OLFML2B expression was bound up with TMB in 13 cancers, MSI in 10 cancers, and TME in almost all cancers. Furthermore, OLFML2B was highly co-expressed with genes encoding immune activators and immune suppressors. We further found that OLFML2B played a role in infiltrating different types of immune cells, such as macrophages and cancer-associated fibroblasts. OLFML2B may influence various cancer and immune-related pathways, such as the PI3K-Akt signaling pathway, ECM-receptor interaction, focal adhesion, and leukocyte transendothelial migration. In addition, OLFML2B may increase drug resistance of binimetinib, cobimentinib, and trametinib. Conclusion: Our outcomes reveal that OLFML2B may act as a prognostic marker and a potential target in immunotherapy for diverse tumors due to its oncogenesis function and immune infiltration.

Cellular Senescence-Related Genes: Predicting Prognosis in Gastric Cancer

Our study aimed to explore the effect of cellular senescence and to find potential therapeutic strategies for gastric cancer. Cellular senescence-related genes were acquired from the CellAge database, while gastric cancer data were obtained from GEO and TCGA databases. SMARCA4 had the highest mutation frequency (6%), and it was linked to higher overall survival (OS) and progression-free survival (PFS). The gastric cancer data in TCGA database served as a training set to construct a prognostic risk score signature, and GEO data were used as a testing set to validate the accuracy of the signature. Patients with the low-risk score group had a longer survival time, while the high-risk score group is the opposite. Patients with low-risk scores had higher immune infiltration and active immune-related pathways. The results of drug sensitivity analysis and the TIDE algorithm showed that the low-risk score group was more susceptible to chemotherapy and immunotherapy. Most patients with mutation genes had a lower risk score than the wild type. Therefore, the risk score signature with cellular senescence-related genes can predict gastric cancer prognosis and identify gastric cancer patients who are sensitive to chemotherapy and immunotherapy.

High Expression of RAI14 in Triple-Negative Breast Cancer Participates in Immune Recruitment and Implies Poor Prognosis Through Bioinformatics Analyses

Objective: The purpose of current research is to explore the function of retinoic acid-induced protein 14 (RAI14), being a reciprocal protein of carboxypeptidase N1 (CPN1), and as a biomarker for prognosis and immunoregulatory effects in breast cancers.

Methods: Interacting proteins of CPN1 were characterized by co-immunoprecipitation (CO-IP) and mass spectrometry. We evaluated RAI14 expression and related clinical prognosis based on bioinformatics methods. The level of relevance between RAI14 and infiltrating immune cells biomarkers was investigated by using TIMER and certificated by immunohistochemical staining and cytology experiments.

Results: RAI14 is an interacting protein of CPN1. Higher RAI14 expression in TNBC was significantly correlated with poor prognosis in TNBC, especially (RFS: HR = 1.32, p = 0.015; DFS: HR = 1.18, p = 0.035). The estrogen receptor (ER), P53 status, and histological types and triple-negative status were observed and correlated with RAI14 expression. Moreover, the level of RAI14 was positive in relation with the expression of CD163 (M2 macrophages marker, r = 0.393, p = 1.89e-06) and PD-1 (T-cell exhaustion marker, r = 0.626, p = 4.82e-03), indicating RAI14 levels were mainly related to M2 macrophages and T-cell exhaustion infiltration in TNBC. Furthermore, CPN1 overexpression was accompanied by RAI14 and PD-L1 upregulation, and a correlation was found among them.

Conclusions: RAI14 is a potential downstream molecule of CPN1, which may be a potential prognostic biomarker and identification of an immunosuppressive tumor microenvironment in TNBC.

Combining Algorithms to Find Signatures That Predict Risk in Early-Stage Stomach Cancer

This study applied two mathematical algorithms, lattice up-stream targeting (LUST) and D-basis, to the identification of prognostic signatures from cancer gene expression data. The LUST algorithm looks for metagenes, which are sets of genes that are either overexpressed or underexpressed in the same patients. Whereas LUST runs unsupervised by clinical data, the D-basis algorithm uses implications and association rules to relate gene expression to clinical outcomes. The D-basis selects a small subset of the metagene (a signature) to predict survival. The two algorithms, LUST and D-basis, were combined and applied to mRNA expression and clinical data from The Cancer Genome Atlas (TCGA) for 203 stage 1 and 2 stomach cancer patients. Two small (four-gene) signatures effectively predict survival in early-stage stomach cancer patients. These signatures could be used as a guide for treatment. The first signature (DU4) consists of genes that are underexpressed on the long-survival/low-risk group: FLRT2, KCNB1, MYOC, and TNXB. The second signature consists of genes that are overexpressed on the short-survival/high-risk group: ASB5, SFRP1, SMYD1, and TACR2. Another nine-gene signature (REC9) predicts recurrence: BNC2, CCDC8, DPYSL3, MOXD1, MXRA8, PRELP, SCARF2, TAGLN, and ZNF423. Each patient is assigned a score that is a linear combination of the expression levels for the genes in the signature. Scores below a selected threshold predict low-risk/long survival, whereas high scores indicate a high risk of short survival. The metagenes associate with TCGA cluster C1. Both our signatures and cluster C1 identify tumors that are genomically silent, and have a low mutation load or mutation count. Furthermore, our signatures identify tumors that are predominantly in the WHO classification of poorly cohesive and the Lauren class of diffuse samples, which have a poor prognosis.