Anatomical predispositions for silent cerebral infarction post carotid artery stenting: A retrospective cohort.

BACKGROUND: Silent cerebral infarction (SCI) that manifests following carotid artery stenting (CAS) has been postulated to correlate with cognitive decline, the onset of dementia, and an increased risk of subsequent cerebrovascular events. This investigation aimed to thoroughly examine the potential anatomical predispositions that are linked to the occurrence of SCI post-CAS, and further develop a predictive nomogram that could accurately forecast the risk of SCI post-CAS. METHODS: The present investigation conducted a retrospective examination of datasets from 250 individuals presenting with carotid artery stenosis who had been subjected to CAS within a tertiary healthcare institution from June 2020 to November 2021. Stratified by the procedural date, participants were allocated into a training cohort and a validation cohort. A nomogram was constructed predicated on salient prognostic determinants discerned via a multivariate logistic regression analysis. RESULTS: An aggregate of 184 patients were incorporated into the study, of which 60 (32.6%) manifested SCI, whereas 124 (67.4%) did not. Within the training cohort (n=123), age (OR 1.08, 95%CI 1.01-1.16; P=0.034), aortic arch type (Type III vs. I: OR 10.79, 95%CI 2.12-54.81; P=0.005), aortic arch variant (OR 47.71, 95%CI 6.05-376.09; P<0.001), common carotid artery (CCA) ostium lesions (OR 6.93, 95%CI 1.49-32.32; P=0.014), and proximal tortuosity index (TI) (OR 1.01, 95%CI 1.00-1.02; P=0.029) were demarcated as standalone risk predispositions for SCI subsequent to CAS. The concordance index (C-index) for the training cohort's nomogram stood at 0.89 (95% CI, 0.84-0.95). Moreover, the said nomogram exhibited commendable efficacy within the validation cohort (C-index=0.94) as well as the entire participant base (C-index=0.90). Furthermore, the decision curve analysis illustrated the exemplary clinical applicability of the nomogram. CONCLUSIONS: The findings of this inquiry underscore that age, aortic arch type, aortic arch variant, CCA ostium lesions, and proximal TI serve as independent determinants linked with SCI post-CAS. The formulated nomogram, predicated on these risk factors, possesses robust prognostic significance and might serve as a valuable adjunct to inform clinical decision-making.

Preparation of biocompatibility coating on magnesium alloy surface by sodium alginate and carboxymethyl chitosan hydrogel.

Magnesium alloy is an excellent material for biodegradable cerebrovascular stents. However, the rapid degradation rate of magnesium alloy will make stent unstable. To improve the biocompatibility of magnesium alloy, in this study, biodegradable sodium alginate and carboxymethyl chitosan (SA/CMCS) was used to coat onto hydrothermally treated the surface of magnesium alloy by a dipping coating method. The results show that the SA/CMCS coating facilitates the growth, proliferation, and migration of endothelial cells and promotes neovascularization. Moreover, the SA/CMCS coating suppresses macrophage activation while promoting their transformation into M2 type macrophages. Overall, the SA/CMCS coating demonstrates positive effects on the safety and biocompatibility of magnesium alloy after implantation, and provide a promising therapy for the treatment of intracranial atherosclerotic stenosis in the future.

Vascular stability of brain arteriovenous malformations after partial embolization.

INTRODUCTION: Brain arteriovenous malformation (bAVM) might have a higher risk of rupture after partial embolization, and previous studies have shown that some metrics of vascular stability are related to bAVM rupture risk. OBJECTIVE: To analyze vascular stability of bAVM in patients after partial embolization. METHODS: Twenty-four patients who underwent partial embolization were classified into the short-term, medium-term, and long-term groups, according to the time interval between partial embolization and surgery. The control group consisted of 9 bAVM patients who underwent surgery alone. Hemodynamic changes after partial embolization were measured by angiogram. The inflammatory infiltrates and cell-cell junctions were evaluated by MMP-9 and VE-cadherin. At the protein level, the proliferative and apoptotic events of bAVMs were analyzed by immunohistochemical staining of VEGFA, eNOS, and caspase-3. Finally, neovascularity and apoptotic cells were assessed by CD31 staining and TUNEL staining. RESULTS: Immediately after partial embolization, the blood flow velocity of most bAVMs increased. The quantity of MMP-9 in the medium-term group was the highest, and VE-cadherin in the medium-term group was the lowest. The expression levels of VEGFA, eNOS, and neovascularity were highest in the medium-term group. Similarly, the expression level of caspase-3 and the number of apoptotic cells were highest in the medium-term group. CONCLUSION: The biomarkers for bAVM vascular stability were most abnormal between 1 and 28 days after partial embolization.

Comprehensive analysis of autophagy-related gene expression profiles identified five gene biomarkers associated with immune infiltration and advanced plaques in carotid atherosclerosis.

BACKGROUND: Autophagy plays an important role in the progression of carotid atherosclerosis (CAS). This study aimed to identify hub autophagy-related genes (ATGs) associated with CAS. METHODS: GSE43292 and GSE28829 datasets of early and advanced CAS plaques were enrolled from the Gene Expression Omnibus (GEO) database. A comprehensive analysis of differentially expressed ATGs (DE-ATGs) was conducted. Functional enrichment assay was used to explore biological functions of DE-ATGs. The hub ATGs were identified by protein-protein interaction (PPI) network. Immunohistochemistry (IHC) and Real-time reverse transcription-quantitative polymerase chain reaction (RT-qPCR) were used to validate hub ATGs at the protein level and mRNA level. Correlation analysis of hub ATGs with immune cells was also conducted. In addition, a competitive endogenous RNA (ceRNA) network was constructed, and diagnostic value of hub ATGs was evaluated. RESULTS: A total of 19 DE-ATGs were identified in early and advanced CAS plaques. Functional enrichment analysis of DE-ATGs suggested that they were closely correlated to autophagy, apoptosis, and lipid regulation. Moreover, 5 hub ATGs, including TNFSF10, ITGA6, CTSD, CCL2, and CASP1, were identified and further verified by IHC. The area under the curve (AUC) values of the 5 hub ATGs were 0.818, 0.732, 0.792, 0.814, and 0.812, respectively. Competing endogenous RNA (ceRNA) networks targeting the hub ATGs were also constructed. In addition, the 5 hub ATGs were found to be closely associated with immune cell infiltration in CAS. CONCLUSION: In this study, we identified 5 hub ATGs including CASP1, CCL2, CTSD, ITGA6 and TNFSF10, which could serve as candidate diagnostic biomarkers and therapeutic targets.

A machine learning-derived gene signature for assessing rupture risk and circulatory immunopathologic landscape in patients with intracranial aneurysms.

Background: Intracranial aneurysm (IA) is an uncommon but severe subtype of cerebrovascular disease, with high mortality after aneurysm rupture. Current risk assessments are mainly based on clinical and imaging data. This study aimed to develop a molecular assay tool for optimizing the IA risk monitoring system. Methods: Peripheral blood gene expression datasets obtained from the Gene Expression Omnibus were integrated into a discovery cohort. Weighted gene co-expression network analysis (WGCNA) and machine learning integrative approaches were utilized to construct a risk signature. QRT-PCR assay was performed to validate the model in an in-house cohort. Immunopathological features were estimated using bioinformatics methods. Results: A four-gene machine learning-derived gene signature (MLDGS) was constructed for identifying patients with IA rupture. The AUC of MLDGS was 1.00 and 0.88 in discovery and validation cohorts, respectively. Calibration curve and decision curve analysis also confirmed the good performance of the MLDGS model. MLDGS was remarkably correlated with the circulating immunopathologic landscape. Higher MLDGS scores may represent higher abundance of innate immune cells, lower abundance of adaptive immune cells, and worse vascular stability. Conclusions: The MLDGS provides a promising molecular assay panel for identifying patients with adverse immunopathological features and high risk of aneurysm rupture, contributing to advances in IA precision medicine.

Six macrophage-associated genes in synovium constitute a novel diagnostic signature for osteoarthritis.

Background: Synovial macrophages play important roles in the formation and progression of osteoarthritis (OA). This study aimed to explore the biological and clinical significance of macrophage-associated genes (MAGs) in OA. Methods: The OA synovial gene expression profiles GSE89408 and GSE82107 were obtained from the GEO database. Single-sample gene set enrichment analysis (ssGSEA) and GSEA were employed to decipher differences in immune infiltration and macrophage-associated biological pathways, respectively. Protein-protein interaction (PPI) network analysis and machine learning were utilized to establish a macrophage-associated gene diagnostic signature (MAGDS). RT-qPCR was performed to test the expression of key MAGs in murine models. Results: OA synovium presented high levels of immune infiltration and activation of macrophage-associated biological pathways. A total of 55 differentially expressed MAGs were identified. Using PPI analysis and machine learning, a MAGDS consisting of IL1B, C5AR1, FCGR2B, IL10, IL6, and TYROBP was established for OA diagnosis (AUC = 0.910) and molecular pathological evaluation. Patients with high MAGDS scores may possess higher levels of immune infiltration and expression of matrix metalloproteinases (MMPs), implying poor biological alterations. The diagnostic value of MAGDS was also validated in an external cohort (AUC = 0.886). The expression of key MAGs was validated in a murine model using RT-qPCR. Additionally, a competitive endogenous RNA network was constructed to reveal the potential posttranscriptional regulatory mechanisms. Conclusions: We developed and validated a MAGDS model with the ability to accurately diagnose and characterize biological alterations in OA. The six key MAGs may also be latent targets for immunoregulatory therapy.

Transcriptome-Based Dissection of Intracranial Aneurysms Unveils an "Immuno-Thermal" Microenvironment and Defines a Pathological Feature-Derived Gene Signature for Risk Estimation.

Immune inflammation plays an essential role in the formation and rupture of intracranial aneurysm (IA). However, the current limited knowledge of alterations in the immune microenvironment of IA has hampered the mastery of pathological mechanisms and technological advances, such as molecular diagnostic and coated stent-based molecular therapy. In this study, seven IA datasets were enrolled from the GEO database to decode the immune microenvironment and relevant biometric alterations. The ssGSEA algorithm was employed for immune infiltration assessment. IAs displayed abundant immune cell infiltration, activated immune-related pathways, and high expression of immune-related genes. Several immunosuppression cells and genes were also coordinately upregulated in IAs. Five immune-related hub genes, including CXCL10, IL6, IL10, STAT1, and VEGFA, were identified from the protein-protein interaction network and further detected at the protein level. CeRNA networks and latent drugs targeting the hub genes were predicted for targeted therapy reference. Two gene modules recognized via WCGNA were functionally associated with contractile smooth muscle loss and extracellular matrix metabolism, respectively. In blood datasets, a pathological feature-derived gene signature (PFDGS) for IA diagnosis and rupture risk prediction was established using machine learning. Patients with high PFDGS scores may possess adverse biological alterations and present with a high risk of morbidity or IA rupture, requiring more vigilance or prompt intervention. Overall, we systematically unveiled an "immuno-thermal" microenvironment characterized by co-enhanced immune activation and immunosuppression in IA, which provides a novel insight into molecular pathology. The PFDGS is a promising signature for optimizing risk surveillance and clinical decision-making in IA patients.

Development and Validation of Ischemic Events Related Signature After Carotid Endarterectomy.

Background: Ischemic events after carotid endarterectomy (CEA) in carotid artery stenosis patients are unforeseeable and alarming. Therefore, we aimed to establish a novel model to prevent recurrent ischemic events after CEA. Methods: Ninety-eight peripheral blood mononuclear cell samples were collected from carotid artery stenosis patients. Based on weighted gene co-expression network analysis, we performed whole transcriptome correlation analysis and extracted the key module related to ischemic events. The biological functions of the 292 genes in the key module were annotated via GO and KEGG enrichment analysis, and the protein-protein interaction (PPI) network was constructed via the STRING database and Cytoscape software. The enrolled samples were divided into train (n = 66), validation (n = 28), and total sets (n = 94). In the train set, the random forest algorithm was used to identify critical genes for predicting ischemic events after CEA, and further dimension reduction was performed by LASSO logistic regression. A diagnosis model was established in the train set and verified in the validation and total sets. Furthermore, fifty peripheral venous blood samples from patients with carotid stenosis in our hospital were used as an independent cohort to validation the model by RT-qPCR. Meanwhile, GSEA, ssGSEA, CIBERSORT, and MCP-counter were used to enrichment analysis in high- and low-risk groups, which were divided by the median risk score. Results: We established an eight-gene model consisting of PLSCR1, ECRP, CASP5, SPTSSA, MSRB1, BCL6, FBP1, and LST1. The ROC-AUCs and PR-AUCs of the train, validation, total, and independent cohort were 0.891 and 0.725, 0.826 and 0.364, 0.869 and 0.654, 0.792 and 0.372, respectively. GSEA, ssGSEA, CIBERSORT, and MCP-counter analyses further revealed that high-risk patients presented enhanced immune signatures, which indicated that immunotherapy may improve clinical outcomes in these patients. Conclusion: An eight-gene model with high accuracy for predicting ischemic events after CEA was constructed. This model might be a promising tool to facilitate the clinical management and postoperative surveillance of carotid artery stenosis patients.

Integrated Analysis of Multi-Omics Alteration, Immune Profile, and Pharmacological Landscape of Pyroptosis-Derived lncRNA Pairs in Gastric Cancer.

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.

Clinical Significance and Immune Landscape of a Pyroptosis-Derived LncRNA Signature for Glioblastoma.

Introduction: Pyroptosis was recently implicated in the initiation and progression of tumors, including glioblastoma (GBM). This study aimed to explore the clinical significance of pyroptosis-related lncRNAs (PRLs) in GBM. Methods: Three independent cohorts were retrieved from the TCGA and CGGA databases. The consensus clustering and weighted gene coexpression network analysis (WGCNA) were applied to identify PRLs. The LASSO algorithm was employed to develop and validate a pyroptosis-related lncRNA signature (PRLS) in three independent cohorts. The molecular characteristics, clinical significances, tumor microenvironment, immune checkpoints profiles, and benefits of chemotherapy and immunotherapy regarding to PRLS were also explored. Results: In the WGCNA framework, a key module that highly correlated with pyroptosis was extracted for identifying PRLs. Univariate Cox analysis further revealed the associations between PRLs and overall survival. Based on the expression profiles of PRLs, the PRLS was initially developed in TCGA cohort (n = 143) and then validated in two CGGA cohorts (n = 374). Multivariate Cox analysis demonstrated that our PRLS model was an independent risk factor. More importantly, this signature displayed a stable and accurate performance in predicting prognosis at 1, 3, and 5 years, with all AUCs above 0.7. The decision curve analysis also indicated that our signature had promising clinical application. In addition, patients with high PRLS score suggested a more abundant immune infiltration, higher expression of immune checkpoint genes, and better response to immunotherapy but worse to chemotherapy. Conclusion: A novel pyroptosis-related lncRNA signature with a robust performance was constructed and validated in multiple cohorts. This signature provided new perspectives for clinical management and precise treatments of GBM.

Machine learning-based integration develops an immune-derived lncRNA signature for improving outcomes in colorectal cancer.

Long noncoding RNAs (lncRNAs) are recently implicated in modifying immunology in colorectal cancer (CRC). Nevertheless, the clinical significance of immune-related lncRNAs remains largely unexplored. In this study, we develope a machine learning-based integrative procedure for constructing a consensus immune-related lncRNA signature (IRLS). IRLS is an independent risk factor for overall survival and displays stable and powerful performance, but only demonstrates limited predictive value for relapse-free survival. Additionally, IRLS possesses distinctly superior accuracy than traditional clinical variables, molecular features, and 109 published signatures. Besides, the high-risk group is sensitive to fluorouracil-based adjuvant chemotherapy, while the low-risk group benefits more from bevacizumab. Notably, the low-risk group displays abundant lymphocyte infiltration, high expression of CD8A and PD-L1, and a response to pembrolizumab. Taken together, IRLS could serve as a robust and promising tool to improve clinical outcomes for individual CRC patients.

Integrative analysis from multi-center studies identities a consensus machine learning-derived lncRNA signature for stage II/III colorectal cancer.

BACKGROUND: Long non-coding RNAs (lncRNAs) have recently emerged as essential biomarkers of cancer progression. However, studies are limited regarding lncRNAs correlated with recurrence and fluorouracil-based adjuvant chemotherapy (ACT) in stage II/III colorectal cancer (CRC). METHODS: 1640 stage II/III CRC patients were enrolled from 15 independent datasets and a clinical in-house cohort. 10 prevalent machine learning algorithms were collected and then combined into 76 combinations. 109 published transcriptome signatures were also retrieved. qRT-PCR assay was performed to verify our model. FINDINGS: We comprehensively identified 27 stably recurrence-related lncRNAs from multi-center cohorts. According to these lncRNAs, a consensus machine learning-derived lncRNA signature (CMDLncS) that exhibited best power for predicting recurrence risk was determined from 76 kinds of algorithm combinations. A high CMDLncS indicated unfavorable recurrence and mortality rates. CMDLncS not only could work independently of common clinical traits (e.g., AJCC stage) and molecular features (e.g., microsatellite state, KRAS mutation), but also presented dramatically better performance than these variables. qRT-PCR results from 173 patients further verified our in-silico findings and assessed its feasible in different centers. Comparisons of CMDLncS with 109 published transcriptome signatures further demonstrated its predictive superiority. Additionally, patients with high CMDLncS benefited more from fluorouracil-based ACT and were characterized by activation of stromal and epithelial-mesenchymal transition, while patients with low CMDLncS suggested the sensitivity to bevacizumab and displayed enhanced immune activation. INTERPRETATION: CMDLncS provides an attractive platform for identifying patient at high risk of recurrence and could optimize precision treatment to improve the clinical outcomes in stage II/III CRC. FUNDING: This study was supported by the National Natural Science Foundation of China (81,972,663); Henan Province Young and Middle-Aged Health Science and Technology Innovation Talent Project (YXKC2020037); and Henan Provincial Health Commission Joint Youth Project (SB201902014).

Integrated Transcriptome Analysis Reveals the Impact of Photodynamic Therapy on Cerebrovascular Endothelial Cells.

Blood vessels in the brain tissue form a compact vessel structure and play an essential role in maintaining the homeostasis of the neurovascular system. The low dosage of photodynamic intervention (PDT) significantly affects the expression of cellular biomarkers. To understand the impact of photodynamic interventions on cerebrovascular endothelial cells, we evaluated the dosage-dependent impact of porfimer sodium-mediated PDT on B.END3 cells using flow cytometer, comet assay, RNA sequencing, and bioinformatics analysis. To examine whether PDT can induce disorder of intracellular organelles, we did not observe any significance damage of DNA and cellular skeleton. Moreover, expression levels of cellular transporters-related genes were significantly altered, implying the drawbacks of PDT on cerebrovascular functions. To address the potential molecular mechanisms of these phenotypes, RNA sequencing and bioinformatics analysis were employed to identify critical genes and pathways among these processes. The gene ontology (GO) analysis and protein-protein interaction (PPI) identified 15 hub genes, highly associated with cellular mitosis process (CDK1, CDC20, MCM5, MCM7, MCM4, CCNA2, AURKB, KIF2C, ESPL1, BUB1B) and DNA replication (POLE2, PLOE, CDC45, CDC6). Gene set enrichment analysis (GSEA) reveals that TNF-α/NF-κB and KRAS pathways may play a critical role in regulating expression levels of transporter-related genes. To further perform qRT-PCR assays, we find that TNF-α/NF-κB and KRAS pathways were substantially up-regulated, consistent with GSEA analysis. The current findings suggested that a low dosage of PDT intervention may be detrimental to the homeostasis of blood-brain barrier (BBB) by inducing the inflammatory response and affecting the expression of surface biomarkers.

Computational Recognition and Clinical Verification of TGF-ß-Derived miRNA Signature With Potential Implications in Prognosis and Immunotherapy of Intrahepatic Cholangiocarcinoma.

MicroRNAs (miRNAs) were recently implicated in modifying the transforming growth factor ß (TGF-ß) signaling in multiple cancers. However, TGF-ß-derived miRNAs and their potential clinical significance remain largely unexplored in intrahepatic cholangiocarcinoma (ICC). In this study, we proposed an integrated framework that enables the identification of TGF-ß-derived miRNAs in ICC (termed "TGFmitor"). A total of 36 TGF-ß-derived miRNAs were identified, of which nine significantly correlated with overall survival (OS) and aberrantly expressed in ICC. According to these miRNAs, we discovered and validated a TGF-ß associated miRNA signature (TAMIS) in GSE53870 (n =63) and TCGA-CHOL (n =32). To further confirm the clinical interpretation of TAMIS, another validation based on qRT-PCR results from 181 ICC tissues was performed. TAMIS was proven to be an independent risk indicator for both OS and relapse-free survival (RFS). TAMIS also displayed robust performance in three cohorts, with satisfactory AUCs and C-index. Besides, patients with low TAMIS were characterized by superior levels of CD8+ T cells infiltration and PD-L1 expression, while patients with high TAMIS possessed enhanced CMTM6 expression. Kaplan-Meier analysis suggested CMTM6 could further stratify TAMIS. The TAMIShighCMTM6high subtype had the worst prognosis and lowest levels of CD8A and PD-L1 expression relative to the other subtypes, indicating this subtype might behave as "super-cold" tumors. Notably, the improved discrimination was observed when CMTM6 was combined with TAMIS. Overall, our signature could serve as a powerful tool to help improve prognostic management and immunotherapies of ICC patients.

Clinical Significance and Inflammatory Landscape of aNovel Recurrence-Associated Immune Signature in Stage II/III Colorectal Cancer.

Background: A considerable number of patients with stage II/III colorectal cancer (CRC) will relapse within 5 years after surgery, which is a leading cause of death in early-stage CRC. The current TNM stage system is limited due to the heterogeneous clinical outcomes displayed in patients of same stage. Therefore, searching for a novel tool to identify patients at high recurrence-risk for improving post-operative individual management is an urgent need. Methods: Using four independent public cohorts and qRT-PCR data from 66 tissues, we developed and validated a recurrence-associated immune signature (RAIS) based on global immune genes. The clinical and molecular features, tumor immune microenvironment landscape, and immune checkpoints profiles of RAIS were also investigated. Results: In five independent cohorts, this novel scoring system was proven to be an independent recurrent factor and displayed excellent discrimination and calibration in predicting the recurrence-risk at 1~5 years. Further analysis revealed that the high-risk group displayed high mutation rate of TP53, while the low-risk group had more abundance of activated CD4+/CD8+ T cells and high expression of PD-1/PD-L1. Conclusions: The RAIS model is highly predictive of recurrence in patients with stage II/III CRC, which might serve as a powerful tool to further optimize decision-making in adjuvant chemotherapy and immunotherapy, as well as tailor surveillance protocol for individual patients.

Development and clinical validation of a novel six-gene signature for accurately predicting the recurrence risk of patients with stage II/III colorectal cancer.

BACKGROUND: A large number of patients with stage II/III colorectal cancer (CRC) have a high recurrence rate after radical resection. We aimed to develop a novel tool to stratify patients with different recurrence-risk for optimizing decision-making in post-operative surveillance and therapeutic regimens. METHODS: We retrospectively enrolled four independent cohorts from the Gene Expression Omnibus and 66 CRC tissues from our hospital. The initial signature discovery was conducted in GSE143985 (n = 91). This was followed by independent validation of this signature in GSE17536 (n = 111), GSE29621 (n = 40), and GSE92921 (n = 59). Further experimental validation using qRT-PCR assays (n = 66) was performed to ensure the robustness and clinical feasible of this signature. RESULTS: We developed a novel recurrence-related signature consisting of six genes. This signature was validated to be significantly associated with dismal recurrence-free survival in five cohorts GSE143985 (HR: 4.296 [2.612-7.065], P < 0.0001), GSE17536 (HR: 2.354 [1.662-3.334], P < 0.0001), GSE29621 (HR: 3.934 [1.622-9.539], P = 0.0024), GSE92921 (HR: 7.080 [2.011-24.924], P = 0.0023), and qPCR assays (HR: 3.654 [2.217-6.020], P < 0.0001). This signature was also proven to be an independent recurrent factor. More importantly, this signature displayed excellent discrimination and calibration in predicting the recurrence-risk at 1-5 years, with most AUCs were above 0.9, average C-index for the five cohorts was 0.8795, and near-perfect calibration. CONCLUSIONS: We discovered and experimental validated a novel gene signature with stable and powerful performance for identifying patients at high recurrence-risk in stage II/III CRC.

Comprehensive Molecular Analyses of a Novel Mutational Signature Classification System with Regard to Prognosis, Genomic Alterations, and Immune Landscape in Glioma.

Background: Glioma is the most common malignant brain tumor with complex carcinogenic process and poor prognosis. The current molecular classification cannot fully elucidate the molecular diversity of glioma. Methods: Using broad public datasets, we performed cluster analysis based on the mutational signatures and further investigated the multidimensional heterogeneity of the novel glioma molecular subtypes. The clinical significance and immune landscape of four clusters also investigated. The nomogram was developed using the mutational clusters and clinical characteristics. Results: Four heterogenous clusters were identified, termed C1, C2, C3, and C4, respectively. These clusters presented distinct molecular features: C1 was characterized by signature 1, PTEN mutation, chromosome seven amplification and chromosome 10 deletion; C2 was characterized by signature 8 and FLG mutation; C3 was characterized by signature 3 and 13, ATRX and TP53 mutations, and 11p15.1, 11p15.5, and 13q14.2 deletions; and C4 was characterized by signature 16, IDH1 mutation and chromosome 1p and 19q deletions. These clusters also varied in biological functions and immune status. We underlined the potential immune escape mechanisms: abundant stromal and immunosuppressive cells infiltration and immune checkpoints (ICPs) blockade in C1; lack of immune cells, low immunogenicity and antigen presentation defect in C2 and C4; and ICPs blockade in C3. Moreover, C4 possessed a better prognosis, and C1 and C3 were more likely to benefit from immunotherapy. A nomogram with excellent performance was also developed for assessing the prognosis of patients with glioma. Conclusion: Our results can enhance the mastery of molecular features and facilitate the precise treatment and clinical management of glioma.

Establishment and experimental validation of an immune miRNA signature for assessing prognosis and immune landscape of patients with colorectal cancer.

As essential regulators of gene expression, miRNAs are engaged in the initiation and progression of colorectal cancer (CRC), including antitumour immune response. In this study, we proposed an integrated algorithm, ImmuMiRNA, for identifying miRNA modulators of immune-associated pathways. Based on these immune-associated miRNAs, we applied the LASSO algorithm to develop a reliable and individualized signature for evaluating overall survival (OS) and inflammatory landscape of CRC patients. An external public data set and qRT-PCR data from 40 samples were further utilized to validate this signature. As a result, an immune-associated miRNA prognostic signature (IAMIPS) consisting of three miRNAs (miR-194-3P, miR-216a-5p and miR-3677-3p) was established and validated. Patients in the high-risk group possessed worse OS. After stratification for clinical factors, the signature remained a powerful independent predictor for OS. IAMIPS displayed much better accuracy than the traditional clinical stage in assessing the prognosis of CRC. Further analysis revealed that patients in the high-risk group were characterized by inflammatory response, abundance immune cell infiltration, and higher immune checkpoint profiles and tumour mutation burden (TMB). In conclusion, the IAMIPS is highly predictive of OS in patients with CRC, which may serve as a powerful prognostic tool to further optimize immunotherapies for cancer.

The Identification and Validation of Two Heterogenous Subtypes and a Risk Signature Based on Ferroptosis in Hepatocellular Carcinoma.

BACKGROUND: Ferroptosis is essential for tumorigenesis and progression of hepatocellular carcinoma (HCC). The heterogeneity of ferroptosis and its relationship with tumor microenvironment (TME) have still remain elusive. METHODS: Based on 74 ferroptosis related genes (FRGs) and 3,933 HCC samples from 32 datasets, we comprehensively explored the heterogenous ferroptosis subtypes. The clinical significance, functional status, immune infiltration, immune escape mechanisms, and genomic alterations of different subtypes were further investigated. RESULTS: We identified and validated two heterogeneous ferroptosis subtypes: C1 was metabolismlowimmunityhigh subtype and C2 was metabolismhighimmunitylow subtype. Compared to C2, C1 owned worse prognosis, and C1 tended to occur in the patients with clinical characteristics such as younger, female, advanced stage, higher grade, vascular invasion. C1 and C2 were more sensitive to immunotherapy and sorafenib, respectively. The immune escape mechanisms of C1 might be accumulating more immunosuppressive cells, inhibitory cytokines, and immune checkpoints, while C2 was mainly associated with inferior immunogenicity, defecting in antigen presentation, and lacking leukocytes. In addition, C1 was characterized by BAP1 mutation, MYC amplification, and SCD1 methylation, while C2 was characterized by the significant alterations in cell cycle and chromatin remodeling processes. We also constructed and validated a robust and promising signature termed ferroptosis related risk score (FRRS) for assessing prognosis and immunotherapy. CONCLUSION: We identified and validated two heterogeneous ferroptosis subtypes and a reliable risk signature which used to assess prognosis and immunotherapy. Our results facilitated the understood of ferroptosis as well as clinical management and precise therapy of HCC.