Ischemic stroke is the leading cause of long-term disability in adults, accounting for 80% of stroke cases. Diffusion weighted imaging (DWI) examination is the main test for acute ischemic stroke, but in recent years, several studies have shown that some patients show negative DWI examination after the onset of ischemic stroke with symptoms of significant neurological deficits. In this study, we investigated potential biomarkers related to immune metabolism in the peripheral blood of DWI-negative versus DWI-positive patients after ischemic stroke and explored their possible regulatory processes in ischemic stroke. The datasets related to ischemic stroke were downloaded from the GEO database, immune-related genes and metabolism-related genes were obtained from the ImmPort database and MSigDB database, respectively, and immune-related differential genes were obtained based on immune scores using the algorithm of the R software package \"GSVA.\" Candidate genes were selected based on intersections, hub genes were screened using the algorithm in Cytoscape software, and finally, GeneMANIA analysis, GSEA enrichment analysis, subcellular localization, gene transcription factor and gene-drug interaction networks, and disease correlation analyses were performed for the hub genes. Five hub genes (GART, TYMS, PPAT, CTPS1, and PAICS) were obtained by PPI network analysis and software analysis. Among them, PPAT and PAICS may be the real hub genes with consistent and significantly differentiated results from the discovery and validation sets. The functions of these hub genes may be related to pathways such as nucleotide biosynthetic processes. The constructed hub gene ceRNA network showed that hsa-10a-5p is the key miRNA connecting PAICS and multiple lncRNAs in this study. Differential genes related to immunity and metabolism in DWI-negative and DWI-positive patients after IS were identified using bioinformatics analysis, and their pathways and related TF-RNAs, miRNAs, and lncRNAs were identified. These genes may be considered effective targets for the diagnosis and treatment of ischemic stroke.

Hepatocellular carcinoma (HCC), partly because of its complexity and high heterogeneity, has a poor prognosis and an extremely high mortality rate. In this study, mRNA sequencing expression profiles and relevant clinical data of HCC patients were gathered from different public databases. Kaplan-Meier survival curves as well as ROC curves validated that OLA1|CLEC3B was an independent predictor with better predictive capability of HCC prognosis compared to OLA1 and CLEC3B separately. Further, the cell transfection experiment verified that knockdown of OLA1 inhibited cell proliferation, facilitated apoptosis, and improved sensitivity of HCC cells to gemcitabine. In this study, the prognostic model of HCC composed of OLA1/CLEC3B genes was constructed and verified, and the prediction ability was favorable. A higher level of OLA1 along with a lower level of CEC3B is a sign of poor prognosis in HCC. We revealed a novel gene pair OLA1|CLEC3B overexpressed in HCC patients, which may serve as a promising independent predictor of HCC survival and an approach for innovative diagnostic and therapeutic strategies.

UNASSIGNED: Hepatocellular carcinoma (HCC), one of the commonest cancers at present, possesses elevated mortality. This study explored the predictive value of CSTF2/PDE2A for HCC prognosis.
UNASSIGNED: In this study, clinical information and RNA sequencing expression profiles of HCC patients were acquired from common databases. Kaplan-Meier curve compound with time-dependent ROC curve, nomogram model, and univariate/multivariate Cox analysis were carried out to access the prediction capacity of CSTF2/PDE2A. The immune status, tumor microenvironment, drug sensitivity, biological function and pathway between HCC and adjacent non-tumorous tissue were analyzed and compared. Finally, RT-qPCR, Western blot, and apoptosis assays were performed to verify the effect on HCC cells of CSTF2/PDE2A.
UNASSIGNED: The optimal cut-off value of CSTF2, PDE2A and CSTF2/PDE2A was 6.95, 0.95 and 3.63, respectively. In TCGA and ICGC cohorts, the high group of CSTF2/PDE2A presented higher OS compared to low group. The area under the curve (AUC) for OS at 1-, 2-, and 3-years predicted by CSTF2/PDE2A were 0.731/0.695, 0.713/0.732 and 0.689/0.755, higher than the counterparts of the single gene CSTF2 and PDE2A. Multivariate Cox analysis revealed that CSTF2/PDE2A (HR = 1.860/3.236, 95% CI = 1.265-2.733/1.575-6.645) was an independent prognostic factor for HCC. The OS nomogram model created according to five independent factors including CSTF2/PDE2A showed excellent capacity for HCC prognosis. Furthermore, the immune status of the CSTF2/PDE2A high group was deleted, cell cycle-related genes and chemotherapy resistance were increased. Finally, cell experiments revealed distinct differences in the proliferation, apoptosis, protein and mRNA expression of HCC cells after si-CSTF2 transfection compared with the negative control.
UNASSIGNED: Taken together, the gene pair CSTF2/PDE2A is able to forecast the prognosis of HCC and regulates cell cycle, which is promising as a novel prognostic predictor of HCC.

OBJECTIVE: There is increasing evidence for a close correlation between risk stratification, prognosis and the immune environment in colon adenocarcinoma (COAD). However, the efficacy of immunotherapy is different among different patients with COAD. Therefore, the current work tends to use immune-related gene to develop a gene-pair model to evaluate the COAD prognosis, and to develop a new method for risk stratification of COAD, which is conducive to better predict the immunotherapy effect of patients.
METHODS: Specifically, from the TCGA and GEO (GSE14333 and GSE39582) databases, we first collected gene expression profiles, associated survival follow-up information of COAD patients. Through systematic bioinformatics analysis, we established a prognosis-related model of colon cancer with three pairs of \"immune gene pairs\", with uni- and multivariate and lasso cox regression analyses verifying the model stability. Most immune cells showed markedly different levels of infiltration between the two risk subgroups calculated by the model. More, single-cell RNA-seq analyses were also performed to validate the selected genes in the immune gene-pair model.
RESULTS: A prognosis-related model of colon cancer with three pairs of \"immune gene pairs\" were built and validated by several datasets. The analysis of immune landscape of COAD revealed that low-risk subgroup obtained by the prognosis-related model for COAD can be further divided into three subclusters with different prognosis. Then, we applied the Tumor online Prognostic analyses Platform (ToPP) to construct a prognostic model using these five genes. Results show that APOD, ISG20 and STC2 are risk factors, while CXCL9 and IL7R are protection factors. We also found that only the five-gene model could also predict the prognosis of COAD patients, indicating the robustness of the gene-pair model. Among the five genes, including CXCL9, APOD, STC2, ISG20, and IL7R, in the gene-pair model, single-cell RNA sequencing reveals the high expression of CXCL9 and IL7R in inflammatory macrophages. Using cell-cell interaction and trajectory analysis, data indicate that CXCL9+/IL7R+ pro-inflammatory macrophages were capable of secreting and activating more anti-tumor pathways than CXCL9-/IL7R- pro-inflammatory macrophages.
CONCLUSIONS: In short, we have successfully developed an \"immune gene pair\" related model that can judge the prognostic status of patients with COAD and may contribute to risk stratification and evaluate potential beneficiaries of immunotherapy, providing new ideas for the anti-COAD management and therapy.

UNASSIGNED: Metastasis remains the leading cause of mortality in patients diagnosed with colorectal cancer (CRC). The pivotal contribution of the immune microenvironment in the initiation and progression of CRC metastasis has gained significant attention.
UNASSIGNED: A total of 453 CRC patients from The Cancer Genome Atlas (TCGA) were included as the training set, and GSE39582, GSE17536, GSE29621, GSE71187 were included as the validation set. The single-sample gene set enrichment analysis (ssGSEA) was performed to assess the immune infiltration of patients. Least absolute shrinkage and selection operator (LASSO) regression analysis, Time-dependent receiver operating characteristic (ROC) and Kaplan-Meier analysis were used to construct and validate risk models based on R package. CTSW and FABP4-knockout CRC cells were constructed via CRISPR-Cas9 system. Western-blot and Transwell assay were utilized to explore the role of fatty acid binding protein 4 (FABP4) / cathepsin W (CTSW) in CRC metastasis and immunity.
UNASSIGNED: Based on the normal/tumor, high-/low-immune cell infiltration, and metastatic/non-metastatic group, we identified 161 differentially expressed genes. After random assignment and LASSO regression analysis, a prognostic model containing 3 metastasis- and immune-related gene pairs was constructed and represented good prognostic prediction efficiency in the training set and 4 independent CRC cohorts. According to this model, we clustered patients and found that the high-risk group was associated with stage, T and M stage. In addition, the high-risk group also shown higher immune infiltration and high sensitivity to PARP inhibitors. Further, FABP4 and CTSW derived from the constitutive model were identified to be involved in metastasis and immunity of CRC.
UNASSIGNED: In conclusion, a validated prognosis predictive model for CRC was constructed. CTSW and FABP4 are potential targets for CRC treatment.

The non-coding RNA (ncRNA) regulation appears to be associated to the diagnosis and targeted therapy of complex diseases. Motifs of non-coding RNAs and genes in the competing endogenous RNA (ceRNA) network would probably contribute to the accurate prediction of serous ovarian carcinoma (SOC). We conducted a microarray study profiling the whole transcriptomes of eight human SOCs and eight controls and constructed a ceRNA network including mRNAs, long ncRNAs, and circular RNAs (circRNAs). Novel form of motifs (mRNA-ncRNA-mRNA) were identified from the ceRNA network and defined as non-coding RNA\'s competing endogenous gene pairs (ceGPs), using a proposed method denoised individualized pair analysis of gene expression (deiPAGE). 18 cricRNA\'s ceGPs (cceGPs) were identified from multiple cohorts and were fused as an indicator (SOC index) for SOC discrimination, which carried a high predictive capacity in independent cohorts. SOC index was negatively correlated with the CD8+/CD4+ ratio in tumour-infiltration, reflecting the migration and growth of tumour cells in ovarian cancer progression. Moreover, most of the RNAs in SOC index were experimentally validated involved in ovarian cancer development. Our results elucidate the discriminative capability of SOC index and suggest that the novel competing endogenous motifs play important roles in expression regulation and could be potential target for investigating ovarian cancer mechanism or its therapy.

Lung adenocarcinoma is the most common histological subtype of lung cancer which causes the largest number of deaths worldwide. Exploring reliable prognostic biomarkers based on biological behaviors and molecular mechanisms is essential for predicting prognosis and individualized treatment strategies. Ferroptosis is a recently discovered type of regulated cell death. We downloaded ferroptosis-related genes from the literature and collected transcriptome profiles of lung adenocarcinoma from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) to construct ferroptosis-related gene-pair matrixes. Then, we performed the least absolute shrinkage and selection operator regression to build our prognostic ferroptosis-related gene-pair index (FRGPI) in TCGA training matrix. Our study validated FRGPI through ROC curves, Kaplan-Meier methods, and Cox hazard analyses in TCGA and GEO cohorts. The optimal cut-off 0.081 stratified patients into low- and high-FRGPI groups. Also, the low-FRGPI group had a significantly better prognosis than the high-FRGPI group. For further study, we analyzed differentially expressed ferroptosis-related genes between high- and low-FRGPI groups. Gene set enrichment analysis (GSEA) enrichment maps indicated that \"cell cycle,\" \"DNA replication,\" \"proteasome,\" and \"the p53 signaling pathway\" were significantly enriched in the high-FRGPI group. The high-FRGPI group also presented higher infiltration of M1 macrophages. Meanwhile, there were few differences in adaptive immune responses between high- and low-FRGPI groups. In conclusion, FRGPI was an independent prognostic biomarker which might be beneficial for guiding individualized tumor therapy.

Background: Recent evidence demonstrates that pyroptosis-derived long non-coding RNAs (lncRNAs) have profound impacts on the initiation, progression, and microenvironment of tumors. However, the roles of pyroptosis-derived lncRNAs (PDLs) in gastric cancer (GC) remain elusive. Methods: We comprehensively analyzed the multi-omics data of 839 GC patients from three independent cohorts. The previous gene set enrichment analysis embedding algorithm was utilized to identify PDLs. A gene pair pipeline was developed to facilitate clinical translation via qualitative relative expression orders. The LASSO algorithm was used to construct and validate a pyroptosis-derived lncRNA pair prognostics signature (PLPPS). The associations between PLPPS and multi-omics alteration, immune profile, and pharmacological landscape were further investigated. Results: A total of 350 PDLs and 61,075 PDL pairs in the training set were generated. Cox regression revealed 15 PDL pairs associated with overall survival, which were utilized to construct the PLPPS model via the LASSO algorithm. The high-risk group demonstrated adverse prognosis relative to the low-risk group. Remarkably, genomic analysis suggested that the lower tumor mutation burden and gene mutation frequency (e.g., TTN, MUC16, and LRP1B) were found in the high-risk group patients. The copy number variants were not significantly different between the two groups. Additionally, the high-risk group possessed lower immune cell infiltration abundance and might be resistant to a few chemotherapeutic drugs (including cisplatin, paclitaxel, and gemcitabine). Conclusion: PDLs were closely implicated in the biological process and prognosis of GC, and our PLPPS model could serve as a promising tool to advance prognostic management and personalized treatment of GC patients.

BACKGROUND: Ischemic stroke (IS) is a principal contributor to long-term disability in adults. A new cell death mediated by iron is ferroptosis, characterized by lethal aggregation of lipid peroxidation. However, a paucity of ferroptosis-related biomarkers early identify IS until now. This study investigated potential ferroptosis-related gene pair biomarkers in IS and explored their roles in immune infiltration.
RESULTS: In total, we identified 6 differentially expressed ferroptosis-related genes (DEFRGs) in the metadata cohort. Of these genes, 4 DEFRGs were incorporated into the competitive endogenous RNA (ceRNA) network, including 78 lncRNA-miRNA and 16 miRNA-mRNA interactions. Based on relative expression values of DEFRGs, we constructed gene pairs. An integrated scheme consisting of machine learning algorithms, ceRNA network, and gene pair was proposed to screen the key DEFRG biomarkers. The receiver operating characteristic (ROC) curve witnessed that the diagnostic performance of DEFRG pair CDKN1A/JUN was superior to that of single gene. Moreover, the CIBERSORT algorithm exhibited immune infiltration landscapes: plasma cells, resting NK cells, and resting mast cells infiltrated less in IS samples than controls. Spearman correlation analysis confirmed a significant correlation between plasma cells and CDKN1A/JUN (CDKN1A: r = - 0.503, P < 0.001, JUN: r = - 0.330, P = 0.025).
CONCLUSIONS: Our findings suggested that CDKN1A/JUN could be a robust and promising gene-pair diagnostic biomarker for IS, regulating ferroptosis during IS progression via C9orf106/C9orf139-miR-22-3p-CDKN1A and GAS5-miR-139-5p/miR-429-JUN axes. Meanwhile, plasma cells might exert a vital interplay in IS immune microenvironment, providing an innovative insight for IS therapeutic target.

Oxidative stress (OS) irreversibly affects the pathogenesis of intervertebral disc degeneration (IDD). Certain non-coding RNAs act as competitive endogenous RNAs (ceRNAs) that regulate IDD progression. Analyzing the signatures of oxidative stress-related gene (OSRG) pairs and regulatory ceRNA mechanisms and immune-infiltration patterns associated with IDD may enable researchers to distinguish IDD and reveal the underlying mechanisms. In this study, OSRGs were downloaded and identified using the Gene Expression Omnibus database. Functional-enrichment analysis revealed the involvement of oxidative stress-related pathways and processes, and a ceRNA network was generated. Differentially expressed oxidative stress-related genes (De-OSRGs) were used to construct De-OSRG pairs, which were screened, and candidate De-OSRG pairs were identified. Immune cell-related gene pairs were selected via immune-infiltration analysis. A potential long non-coding RNA-microRNA-mRNA axis was determined, and clinical values were assessed. Eighteen De-OSRGs were identified that were primarily related to intricate signal-transduction pathways, apoptosis-related biological processes, and multiple kinase-related molecular functions. A ceRNA network consisting of 653 long non-coding RNA-microRNA links and 42 mRNA-miRNA links was constructed. Three candidate De-OSRG pairs were screened out from 13 De-OSRG pairs. The abundances of resting memory CD4+ T cells, resting dendritic cells, and CD8+ T cells differed between the control and IDD groups. CD8+ T cell infiltration correlated negatively with cyclin B1 (CCNB1) expression and positively with protein kinase D1 (PKD1) expression. CCNB1-PKD1 was the only pair that was differentially expressed in IDD, was correlated with CD8+ T cells, and displayed better predictive accuracy compared to individual genes. The PKD1-miR-20b-5p-AP000797 and CCNB1-miR-212-3p-AC079834 axes may regulate IDD. Our findings indicate that the OSRG pair CCNB1-PKD1, which regulates oxidative stress during IDD development, is a robust signature for identifying IDD. This OSRG pair and increased infiltration of CD8+ T cells, which play important roles in IDD, were functionally associated. Thus, the OSRG pair CCNB1-PKD1 is promising target for treating IDD.