Background: Lung squamous cell carcinoma (LUSC) is one of the most common types of lung carcinoma and has specific clinicopathologic characteristics. In this study, we screened novel molecular biomarkers relevant to the prognosis of LUSC to explore new diagnostic and treatment approaches for this disease.

Methods: We downloaded GSE73402 from the Gene Expression Omnibus (GEO) database. GSE73402 contains 62 samples, which could be classified as four subtypes according to their pathology and stages. Via weighted gene coexpression network analysis (WGCNA), the main module was identified and was further analyzed using differentially expressed genes (DEGs) analysis. Then, by protein-protein interaction (PPI) network and Gene Expression Profiling Interactive Analysis (GEPIA), hub genes were screened for potential biomarkers of LUSC.

Results: Via WGCNA, the yellow module containing 349 genes was identified, and it is strongly related to the subtype of CIS (carcinoma in situ). DEGs analysis detected 180 genes that expressed differentially between the subtype of CIS and subtype of early-stage carcinoma (Stage I and Stage II). A PPI network of DEGs was constructed, and the top 20 genes with the highest correlations were selected for GEPIA database to explore their effect on LUSC survival prognosis. Finally, ITGA5, TUBB3, SCNN1B, and SERPINE1 were screened as hub genes in LUSC.

Conclusions: ITGA5, TUBB3, SCNN1B, and SERPINE1 may have great diagnostic and prognostic significance for LUSC and have great potential to be new treatment targets for LUSC.

Nonalcoholic fatty liver disease (NAFLD) is one of the most common liver diseases worldwide. An accumulation of fat, followed by inflammation, is the major cause of NAFLD progression. During inflammation, macrophages are the most abundant immune cells recruited to the site of injury. Macrophages are classified into "proinflammatory" M1 macrophages, and "anti-inflammatory" M2 macrophages. In NAFLD, M1 macrophages are the most prominent macrophages that lead to an excessive inflammatory response. Previously, we found that baicalin could polarize macrophages into anti-inflammatory M2c subtype macrophages with an increased level of MERTK expression. Several studies have also shown a strong correlation between MERTK expression and cholesterol efflux, efferocytosis, as well as phagocytosis capability. Therefore, in this study, we aim to elucidate the potential and efficacy of mononuclear-cell (MNC)-derived MERTK^+/hi M2c macrophages induced by baicalin as a cell-based therapy for NAFLD treatment. In our results, we have demonstrated that a MERTK^+/hi M2c macrophage injection to NAFLD mice contributes to an increased level of serum HDL secretion in the liver, a decline in the circulating CD4⁺CD25^- and CD8⁺CD25^- T cells and lowers the total NAFLD pathological score by lessening the inflammation, necrosis, and fibrosis. In the liver, profibrotic COL1A1 and FN, proinflammation TNFα, as well as the regulator of lipid metabolism PPARɣ expression, were also downregulated after injection. In parallel, the transcriptomic profiles of the injected MERTK^+/hi M2c macrophages showed that the various genes directly or indirectly involved in NAFLD progression (e.g., SERPINE1, FADS2) were also suppressed. Downregulation of cytokines and inflammation-associated genes, such as CCR5, may promote a pro-resolving milieu in the NAFLD liver. Altogether, cell-based therapy using MERTK^+/hi M2c macrophages is promising, as it ameliorates NAFLD in mice.

Keywords: M2c; MERTK; NAFLD; baicalin; macrophage.

RNA binding proteins (RBPs) are essential for critical biological processes such as translation regulation and mRNA processing, and misfunctions of these proteins are associated with diseases such as cancer and neurodegeneration. SERBP1 (SERPINE1 mRNA Binding Protein 1) is an RBP that comprises two RG/RGG repeat regions yet lacks other recognizable RNA-binding motifs. It is involved in mRNA maturation, and translational regulation. It was initially identified as a hyaluronic acid binding protein, but recent studies have identified central roles for SERBP1 in brain function and development, especially neurogenesis and synaptogenesis. SERBP1 regulates One-carbon metabolism and epigenetic modification of histones, and increased SERBP1 expression in cancers such as leukemia, ovarian, prostate, liver and glioblastoma is correlated with poor patient outcomes. Despite these important regulatory roles for SERBP1, little is known about its structural and dynamic properties, nor about the molecular mechanisms governing its interaction with mRNA. Here, we define SERBP1 as an intrinsically disordered protein, containing highly conserved elements that were shown to be functionally important. The RNA binding activity of SERBP1 was explored using solution NMR and other biophysical techniques. The outcome of these experiments revealed that SERBP1 preferentially samples compact conformations including a central, stable α-helix and show that SERBP1 recognizes G-rich RNA sequences at the C-terminus involving the RGG box and neighboring residues. Despite the role in RNA recognition, the RGG boxes do not seem to stabilize the central helix and the central helix does not participate in RNA binding. Further, SERBP1 undergoes liquid-liquid phase separation, mediated by salt and RNA, and both RGG boxes are necessary for the efficient formation of condensed phases. Together, these results provide a foundation for understanding the molecular mechanisms of SERBP1 functions in physiological and pathological processes.

Keywords: NMR; RNA binding protein; SERBP1; intrinsically disordered protein; mRNA binding.

Chlorhexidine digluconate (CHX) is considered the gold standard for oral cavity antiseptic treatment. Nevertheless, several in vitro studies have reported detrimental effects in oral tissue repair. The aim of the present study was to evaluate the in vivo effect of post-surgical CHX mouth rinse on gingival tissue (G) 24 h after injury. G biopsies were obtained in three patients 24 h after surgery with the indication of post-surgical 0.12% CHX use and were compared with those obtained from the same patients without any antiseptic use. Changes in collagen production, cell proliferation, and apoptosis were examined by histological and Ki-67/P53 immunohistochemical analysis. Fibrotic markers (COL1A1, αSMA), proapoptotic protein (BAX) expression, and wound healing-related gene modulation (RAC1, SERPINE1, TIMP1) were analyzed by quantitative real-time PCR analysis. CHX was able to reduce cellular proliferation and increase collagen deposition, proapoptotic molecule and fibrotic marker expression, and myofibroblast differentiation, reduce expression of RAC1 and trigger expression of SERPINE1 and TIMP1, showing "scar wound healing response" pattern. This study assessed for the first time the in vivo effects of CHX on gingival tissue. The demonstration of a CHX-induced fibrotic transformation, leading to scar repair, supports the need for new post-surgical clinical protocols based on a strategic and personalized use of CHX.

Keywords: apoptosis; chlorhexidine digluconate; gingiva; human biopsy; wound healing.

Platelet concentrate products are increasingly used in many medical disciplines due to their regenerative properties. As they contain a variety of chemokines, cytokines, and growth factors, they are used to support the healing of chronic or complicated wounds. To date, underlying cellular mechanisms have been insufficiently investigated. Therefore, we analyzed the influence of Platelet-Released Growth Factors (PRGF) on human dermal fibroblasts. Whole transcriptome sequencing and gene ontology (GO) enrichment analysis of PRGF-treated fibroblasts revealed an induction of several genes involved in the formation of the extracellular matrix (ECM). Real-time PCR analyses of PRGF-treated fibroblasts and skin explants confirmed the induction of ECM-related genes, in particular transforming growth factor beta-induced protein (TGFBI), fibronectin 1 (FN1), matrix metalloproteinase-9 (MMP-9), transglutaminase 2 (TGM2), fermitin family member 1 (FERMT1), collagen type I alpha 1 (COL1A1), a disintegrin and metalloproteinase 19 (ADAM19), serpin family E member 1 (SERPINE1) and lysyl oxidase-like 3 (LOXL3). The induction of these genes was time-dependent and in part influenced by the epidermal growth factor receptor (EGFR). Moreover, PRGF induced migration and proliferation of the fibroblasts. Taken together, the observed effects of PRGF on human fibroblasts may contribute to the underlying mechanisms that support the beneficial wound-healing effects of thrombocyte concentrate products.

Keywords: extracellular matrix (ECM); fibroblasts; platelet-released growth factors (PRGF); wound healing.

This research revealed that 15 modules were obtained through weighted gene co-expression network analysis (WGCNA), among which the magenta and blue modules were significantly associated with Alzheimer's Disease (AD). There were 121 genes in the magenta module, and 1022 genes in the blue module. Through the differently expressed genes (DEGs) analysis, significant differences were shown in 134 genes (88 were up-regulated and 46 were down-regulated). 34 immune-key genes were obtained after 3 types of genes were crossed. Functional enrichment analysis showed that these genes were mainly enriched in cytokine receptor activity, immune receptor activity, and integrin family cell surface interactions. Through protein-protein interaction (PPI) network analysis, 10 hub genes were obtained: SERPINE1, ZBTB16, CD44, BCL6, HMOX1, SLC11A1, CEACAM8, ITGA5, SOCS3, and IL4R. Through immune-infiltration analysis, significant differences were demonstrated in 4 immune cells: CD8+ T cells, resting NK cells, M2 macrophages and activated dendritic cells, and a significant positive correlation was shown between CD8+ T cells and macrophages M2, or between resting NK cells and activated dendritic cells. CEACAM8 was positively correlated with CD8+ T cells and macrophages M2, and negatively correlated with activated dendritic cells and resting NK cells while the other 9 genes showed the opposite. Receiver operating characteristic (ROC) curve analysis demonstrated that both the differential immune cells and 10 hub genes had good diagnostic values. In GSE122063, the hub genes were verified and BCL6, CD44, HMOX1, IL4R, ITGA5 and SOCS3 were up-regulated. Meanwhile, the expression of hub genes was up-regulated in the brain tissues of AD rats. This study is of great significance for the diagnosis and therapy of AD.

Keywords: Alzheimer’s Disease (AD); ROC curve analysis; immune-infiltration analysis; immune-related genes; weighted gene co-expression network analysis (WGCNA).

Senescence is believed to be a pivotal player in the onset and progression of tumors as well as cancer therapy. However, the guiding roles of senescence in clinical outcomes and therapy selection for patients with cancer remain obscure, largely due to the absence of a feasible senescence signature. Here, by integrative analysis of single cell and bulk transcriptome data from multiple datasets of gastric cancer patients, we uncovered senescence as a veiled tumor feature characterized by senescence gene signature enriched, unexpectedly, in the noncancerous cells, and further identified two distinct senescence-associated subtypes based on the unsupervised clustering. Patients with the senescence subtype had higher tumor mutation loads and better prognosis as compared with the aggressive subtype. By the machine learning, we constructed a scoring system termed as senescore based on six signature genes: ADH1B, IL1A, SERPINE1, SPARC, EZH2, and TNFAIP2. Higher senescore demonstrated robustly predictive capability for longer overall and recurrence-free survival in 2290 gastric cancer samples, which was independently validated by the multiplex staining analysis of gastric cancer samples on the tissue microarray. Remarkably, the senescore signature served as a reliable predictor of chemotherapeutic and immunotherapeutic efficacies, with high-senescore patients benefited from immunotherapy, while low-senescore patients were responsive to chemotherapy. Collectively, we report senescence as a heretofore unrecognized hallmark of gastric cancer that impacts patient outcomes and therapeutic efficacy.

Plasminogen activator inhibitor type 1 (PAI-1) is a main inhibitor of fibrinolysis. The PAI-1 gene (SERPINE1) harbors genetic variants with the potential of modifying plasma levels of PAI-1. A delicate balance exists between the coagulation and fibrinolytic system, and changes in PAI-1 have been suggested to compromise establishment of a successful pregnancy. Therefore, this systematic review investigated the association between genetic variants and/or plasma levels of PAI-1 and placenta-mediated pregnancy complications. An extensive literature search was conducted in PubMed, Embase, and Web of Science on the 29^th of April 2021. All studies underwent quality rating according to The Study Quality Assessment Tools checklist provided by National Heart, Lung and Blood Institute. A total of 71 studies were included, among which 60 studies investigated PAI-1 genotypes and 11 studies measured PAI-1 plasma levels. In 32 out of 59 studies, no association was found between the PAI-1 4G/5G polymorphism (rs1799768) and placenta-mediated pregnancy complications, which was stated as no significant difference in the genotype distribution comparing women with and without placenta-mediated pregnancy complications or no significantly increased odds of placenta-mediated pregnancy complications carrying the 4G/4G or 4G/5G genotype. Eight out of 11 studies reported significantly higher PAI-1 plasma levels in preeclamptic women than in women without preeclampsia. In conclusion, no clear evidence indicates that PAI-1 polymorphisms are associated with placenta-mediated pregnancy complications, and the possible association between high PAI-1 plasma levels and preeclampsia needs further investigations. Thus, investigation of PAI-1 genotypes and PAI-1 plasma levels does not currently seem to have a place in daily clinical practice managing placenta-mediated pregnancy complications.

Shenling Baizhu Powder (SBP), a famous Traditional Chinese Medicine (TCM) formulation, has been widely used in the adjuvant treatment of cancers, including breast cancer. This study aims to identify potential new targets for breast cancer treatment based on the network pharmacology of SBP. <P> Methods: By analyzing the relationship between herbs and target proteins, potential targets of multiple herbs in SBP were identified by network pharmacology analysis. Besides, by comparing the data of breast cancer tissue with normal tissue, upregulated genes in two breast cancer expression profiles were found. Thereafter, the expression level and prognosis of activator of heat shock protein 90 (HSP90) ATPase activity 1 (AHSA1) were further analyzed in breast cancer by bioinformatics analysis, and the network module of AHSA1 binding protein was constructed. Furthermore, the effect of knocking down AHSA1 on the proliferation, migration, and invasion of breast cancer cells was verified by MTT, clone formation assay, and transwell assay. <P> Results: Vascular endothelial growth factor A (VEGFA), intercellular adhesion molecule 1 (ICAM1), chemokine (C-X-C motif) ligand 8 (CXCL8), AHSA1, and serpin family E member 1 (SERPINE1) were associated with multiple herbs in SBP. AHSA1 was remarkably upregulated in breast cancer tissues and positively correlated with poor overall survival and disease metastasis-free survival. Furthermore, knockdown of AHSA1 significantly inhibited the migration and invasion in MCF-7 and MDA-MB-231 breast cancer cells but had no obvious effect on proliferation. In addition, among the proteins that bind to AHSAl, the network composed of proteasome, chaperonin, and heat shock proteins is closely connected, and these proteins are associated with poor prognosis in a variety of cancers. <P> Conclusion: AHSA1 is positively correlated with breast cancer progression and might act as a novel therapeutic target for breast cancer.

Keywords: AHSA1; Shenling Baizhu Powder; breast cancer; invasion; migration; network pharmacology.

Background: Gastric cancer (GC) is a highly molecular heterogeneous tumor with poor prognosis. Epithelial-mesenchymal transition (EMT) process and cancer stem cells (CSCs) are reported to share common signaling pathways and cause poor prognosis in GC. Considering about the close relationship between these two processes, we aimed to establish a gene signature based on both processes to achieve better prognostic prediction in GC.

Methods: The gene signature was constructed by univariate Cox and the least absolute shrinkage and selection operator (LASSO) Cox regression analyses by using The Cancer Genome Atlas (TCGA) GC cohort. We performed enrichment analyses to explore the potential mechanisms of the gene signature. Kaplan-Meier analysis and time-dependent receiver operating characteristic (ROC) curves were implemented to assess its prognostic value in TCGA cohort. The prognostic value of gene signature on overall survival (OS), disease-free survival (DFS), and drug sensitivity was validated in different cohorts. Quantitative reverse transcription polymerase chain reaction (RT-qPCR) validation of the prognostic value of gene signature for OS and DFS prediction was performed in the Fudan cohort.

Results: A prognostic signature including SERPINE1, EDIL3, RGS4, and MATN3 (SERM signature) was constructed to predict OS, DFS, and drug sensitivity in GC. Enrichment analyses illustrated that the gene signature has tight connection with the CSC and EMT processes in GC. Patients were divided into two groups based on the risk score obtained from the formula. The Kaplan-Meier analyses indicated high-risk group yielded significantly poor prognosis compared with low-risk group. Pearson's correlation analysis indicated that the risk score was positively correlated with carboplatin and 5-fluorouracil IC50 of GC cell lines. Multivariate Cox regression analyses showed that the gene signature was an independent prognostic factor for predicting GC patients' OS, DFS, and susceptibility to adjuvant chemotherapy.

Conclusions: Our SERM prognostic signature is of great value for OS, DFS, and drug sensitivity prediction in GC, which may give guidance to the development of targeted therapy for CSC- and EMT-related gene in the future.

Keywords: cancer stem cells; drug sensitivity prediction; epithelial-mesenchymal transition; gastric cancer; prognostic signature.

Major depressive disorder (MDD) has become the second most common disease worldwide, making it a threat to human health. Cyperi Rhizoma (CR) is a traditional herbal medicine with antidepressant properties. Traditional Chinese medicine theory states that CR relieves MDD by dispersing stagnated liver qi to soothe the liver, but the material basis and underlying mechanism have not been elucidated. In this study, we identified the active compounds and potential anti-MDD targets of CR by network pharmacology-based approaches. Through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, we hypothesized that the anti-MDD effect of CR may be mediated by an altered response of the liver to lipopolysaccharide (LPS) and glucose metabolism. Through bioinformatics analysis, comparing normal and MDD liver tissue in rats with spontaneous diabetes, we identified differentially expressed genes (DEGs) and selected PAI-1 (SERPINE1) as a target of CR in combating MDD. Molecular docking and molecular dynamics analysis also verified the binding of the active compound quercetin to PAI-1. It can be concluded that quercetin is the active compound of CR that acts against MDD by targeting PAI-1 to enhance the liver response to LPS and glucose metabolism. This study not only reveals the material basis and underlying mechanism of CR against MDD through soothing the liver but also provides evidence for PAI-1 as a potential target and quercetin as a potential agent for MDD treatment.

Background: Many studies have indicated that autophagy plays an important role in multiple cancers, including hepatocellular carcinoma (HCC). This study aimed to establish a prognostic signature for HCC based on autophagy-related genes (ARGs) to predict the prognosis of patients.

Methods: The list of ARGs was derived from screening National Center for Biotechnology Information (NCBI)-Gene and Molecular Signatures Database (MSigDB) datasets. Differential analysis was conducted via the R limma package in HCC patients based on The Cancer Genome Atlas (TCGA) database. Univariate and multivariate Cox regression analysis were conducted to identify key prognostic ARGs via the survival package. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were performed by clusterProfiler package. The Estimation of Stromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) algorithm was used to conduct immune analysis. Finally, the correlation between the prognostic model and clinical characteristics was also assessed, including age, tumor-node-metastasis (TNM) stages, and tumor grades.

Results: Firstly, 106 differential ARGs were identified and 10 candidates were further confirmed via Cox regression analysis, including BAMBI, HIF1A, SERPINE1, EZH2, SLC9A3R1, IGFBP3, HSPB8, DAB2, CXCL1 and PRNP. The receiver operating characteristic (ROC) curve analysis revealed that the ARGs risk model had a well diagnostic positive rate with 1-year area under the curve (AUC) =0.688 and 3-year AUC =0.674. Correlation analysis indicated that only advanced tumor stages were positively associated with high ARGs scores with P=0.0227. There were also significant differences in tumor purity (P=6.71e-05), infiltrating cell analysis (P=7.77e-05), immune analysis (P=7.9e-05), and stromal cells analysis (P=0.0015) in high- and low-risk ARGs samples. The genes HIF1A, IGFBP3, and DAB2 were found to have high frequent missense mutations in samples with high-risk ARGs scores. Lastly, we also established a nomogram to predict overall survival (OS) of HCC by integrating ARGs scores and other clinical parameters.

Conclusions: Our study established an autophagy-related signature for predicting the prognosis of HCC patients, providing a thorough understanding of the underlying mechanisms of autophagy in HCC.

Keywords: Autophagy-related genes (ARGs); The Cancer Genome Atlas (TCGA); hepatocellular carcinoma (HCC); prognosis.

The serine protease inhibitor clade E member 1 (SERPINE1) is a major inhibitor of tissue plasminogen activator and urokinase, and has been implicated in the development and progression of a variety of tumors. In this study, mRNA microarray and TCGA database were used to comprehensively analyze the upregulation of SERPINE1 in gastric cancer (GC) tissues compared with the normal stomach tissues. Kaplan-Meier results confirmed that patients with high SERPINE1 expression exhibited worse overall survival and disease-free survival. In addition, cell proliferation, cell scratches, transwell migration and invasion assay showed that SERPINE1 knockdown inhibited the proliferation, migration and invasion of GC ells. Western blot showed that the expression of VEGF and IL-6 was significantly upregulated after overexpression of SERPINE1. Meanwhile, SERPINE1 was positively correlated with the level of immune infiltration using the online analysis tools TISIDB and TIMER. And SERPINE1 expression increased with the increase of malignancy of GC which were detected by Immunohistochemistry. Finally, tumorigenesis experiments in nude mice further demonstrated that SERPINE1 could promote the occurrence and development of GC, while deletion of SERPINE1 inhibited the progression of GC. In summary, SERPINE1 was highly expressed in GC tissues, and SERPINE1 was helpful for differential diagnosis of pathological grade of gastric mucosal lesions. SERPINE1 might regulate the expression of VEGF and IL-6 through the VEGF signaling pathway and JAK-STAT3 inflammatory signaling pathway, thus ultimately affecting the invasion and migration of GC cells.

Aim: The biology of recurrent pregnancy loss and recurrent implantation failure (RPL-RIF) is complex with multi-factorial etiology, with defective thrombosis being one of the most important and highly prevalent causes. The role of several thrombophilia related genes and variants associated with RPL-RIF is widely reported, and this study aimed to identify the risk associated with these genes in the Indian population.

Methods: Next generation sequencing (NGS) was employed for the current study. NGS enables sequencing of multiple genes, identification of new variants, and establishment of genetic correlations with reproductive failure in diverse population groups. The present NGS based study evaluates association of twenty-nine genotypes of ten coagulation pathway genes (F2, F5, F13, MTR, MTRR, MTHFR, ANXA5, PROZ, SERPINE1 and VEGFA) with RPL-RIF in 540 female subjects - 474 patients with early recurrent pregnancy loss, late pregnancy loss, pregnancy complications in late gestation and recurrent implantation failure, with 66 controls.

Results: The results emphasize inclusion of genotypes of seven thrombophilia genes (MTHFR, MTRR, MTR, ANXA5, PROZ, SERPINE1, VEGFA) for diagnosis of inherited thrombophilia risk for RPL-RIF in Indian population, as against the common practice of testing limited to F2, F5 and MTHFR genes.

Conclusion: Deriving risk magnitude from Combined Risk Analysis and interpretation of high-risk haplotypes are crucial components for evidence based personalized management such as selection of drugs and dosage, and prenatal or pre-implantation recommendations, for high-risk patients in fertility and obstetric clinics.

Keywords: RIF; RPL; polymorphisms; thrombophilia.

Stomach adenocarcinoma (STAD) is one of the most malignant cancers that endanger human health. There is growing evidence that competitive endogenous RNA (ceRNA) regulatory networks play an important role in various human tumors. However, the complexity and behavioral characteristics of the ceRNA network in STAD are still unclear. In this study, we constructed a ceRNA regulatory network to identify the potential prognostic biomarkers associated with STAD. The expression profile of lncRNA, miRNA, and mRNA was downloaded from The Cancer Genome Atlas (TCGA). After performing bioinformatics analysis, the CCDC144NL-AS1/hsa-miR-145-5p/SERPINE1 ceRNA network associated to STAD prognosis of STAD was obtained. The CCDC144NL-AS1/SERPINE1 axis in the ceRNA network was identified by correlation analysis and considered as a clinical prognosis model by Cox regression analysis. In addition, methylation analysis indicated that the abnormal upregulation of CCDC144NL-AS1/SERPINE1 axis might be related to the aberrant methylation of some sites, and immune infiltration analysis suggested that CCDC144NL-AS1/SERPINE1 axis probably influences the alteration of tumor immune microenvironment and the occurrence and development of STAD. In particular, the CCDC144NL-AS1/SERPINE1 axis based on the ceRNA network constructed in the present study might be an important novel factor correlating with the diagnosis and prognosis of STAD.

Keywords: CCDC144NL-AS1/SERPINE1 axis; competitive endogenous RNA; high throughput transcriptome data mining and computational verification; prognostic biomarker; stomach adenocarcinoma.

Background: Serpin peptidase inhibitor, clade E, member 1 (SERPINE1) has been investigated as an oncogene and potential biomarker in several cancers, including gastric cancer (GC). This study aimed to investigate SERPINE1 expression and its diagnostic and prognostic value by analyzing data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases.

Methods: A meta-analysis was performed to investigate SERPINE1 expression levels in GC tissues and adjacent normal tissues. Gene set enrichment, multi experiment matrix (MEM), and protein-protein interaction (PPI) network analyses were performed to identify the most enriched signaling pathways and SERPINE1-related module genes. A Cox regression model was used to develop a nomogram that was able to predict the overall survival (OS) and recurrence-free survival (RFS) of individual patients.

Results: Meta-analyses revealed an elevated trend in SERPINE1 expression levels in TCGA [standard mean difference (SMD) =0.95; 95% confidence interval (CI), 0.53-1.36; P<0.001]. The diagnostic meta-analysis results indicated that the area under the curve (AUC) of the summary receiver operating characteristic (SROC) was 0.80 (95% CI, 0.77-0.84). The factors identified to predict OS were age ≥60 years [hazard ratio (HR), 2.14; 95% CI, 1.45-3.16; P<0.01], R2 margins (HR, 2.70; 95% CI, 1.41-5.14; P<0.05), lymph node-positive proportion (HR, 3.38; 95% CI, 2.03-5.63; P<0.001), patient tumor status (HR, 3.33; 95% CI, 2.28-4.87; P<0.001), and OS risk score (HR, 2.72; 95% CI, 1.82-4.05; P<0.05). The following variables were associated with RFS: male sex (HR, 2.55; 95% CI, 1.46-4.45; P<0.01), R2 margins (HR, 13.08; 95% CI, 4.26-40.15; P<0.001), lymph node-positive proportion (HR, 2.55; 95% CI, 1.20-5.45; P<0.05), and RFS risk score (HR, 2.70; 95% CI, 1.82-4.06; P<0.001). The discriminative ability of the final model for OS and RFS was assessed using C statistics (0.755 for OS and 0.745 for RFS).

Conclusions: SERPINE1 was upregulated in GC, showed a high diagnostic value, and was associated with poorer OS and RFS. The OS and RFS risk for an individual patient could be estimated using these nomograms, which could lead to individualized therapeutic choices.

Keywords: Computational biology; meta-analysis; nomograms; plasminogen activator inhibitor-1 (PAI-1); stomach neoplasms.