Pattern Recognition Receptors (PRRs) in Macrophages Possess Prognosis and Immunotherapy Potential for Melanoma

BackgroundPattern recognition receptors (PRRs) family plays a vital role in the initial stage of innate immune response and the subsequent activation of adaptive immunity. Increasing evidences have indicated that several PRRs play critical roles in the progress of inflammation and tumorigenesis. However, the comprehensive significance of PRRs family in clinical prognosis of different cancers is still elusive.MethodsWe analyzed expression of 20 canonical PRRs in tumor samples from 9502 patients of 33 tumor types. Next, we used expression profiles of PRRs in skin cutaneous melanoma (SKCM) to build a Cox prognosis model. Then, we analyzed immune infiltration features and immune activity of high risk score and low risk score patients. Finally, we analyzed the single-cell sequencing data of different cancers and detected the expression of PRRs in mouse melanoma model to identify PRRs-expressing cell types.ResultsWe found PRRs had a significantly positive correlation with prognosis in SKCM rather than other tumors, and PRR-based Cox model had a much better prognosis potential than any single PRR. Further analysis shows risk score could indicate immunocyte infiltration and immune activity in SKCM. We also found the expressions of some PRR genes were highly correlated with the expression of immune checkpoints molecules in SKCM, indicating they could be indicators for clinical immune therapy. Finally, we found only in SKCM samples, the expression of PRRs is especially high in a subpopulation of macrophages with a trait of CD206 low expression, probably explaining why PRRs have prognosis potential in melanoma.ConclusionsOur study reveals PRR family in macrophages has a positive prognosis potential in melanoma and could be valuable for clinical prognosis and immune therapy.

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Immune profiles of male giant panda (Ailuropoda melanoleuca) during breeding season

10.21203/rs.3.rs-29894/v2 ◽

2021 ◽

Author(s):

haibo shen ◽

Caiwu Li ◽

Ming He ◽

Yan Huang ◽

Jing Wang ◽

...

Keyword(s):

Pattern Recognition ◽

Breeding Season ◽

Giant Panda ◽

Expression Profiles ◽

Killer Cell ◽

Pattern Recognition Receptors ◽

Ailuropoda Melanoleuca ◽

Giant Pandas ◽

Altered Expression ◽

Immune Related Genes

Abstract Background: The giant panda (Ailuropoda melanoleuca) is a threatened endemic Chinese species and a flagship species of national and global conservation concern. Life history theory proposes that reproduction and immunity can be mutually constraining and interrelated. Knowledge of immunity changes of male giant pandas during the breeding season is limited.Results: Here, we researched peripheral blood gene expression profiles associated with immunity. Thirteen captive giant pandas, ranging from 9 to 11 years old, were divided into two groups based on their reproductive status. We identified 318 up-regulated DEGs and 43 down-regulated DEGs, which were enriched in 87 GO terms and 6 KEGG pathways. Additionally, we obtained 45 immune-related genes with altered expression, mostly up-regulated, and identified four hub genes HSPA4, SUGT1, SOD1, and IL1B in PPI analysis. These 45 genes were related to pattern recognition receptors, autophagy, peroxisome, proteasome, natural killer cell, antigen processing and presentation. SUGT1 and IL1B were related to pattern recognition receptors. HSP90AA1 was the most up-regulated gene and is a member of heat shock protein 90 family. HSP90 contributes to the translocation of extracellular antigen. KLRD1 encodes CD94, whose complex is an inhibitor of the cytotoxic activity of NK cells, was down-regulated. IGIP, which has the capability of inducing IgA production by B cells, was down-regulated, suggesting low concentration of IgA in male giant pandas. Our results suggest that most immune-related genes were up-regulated and more related to innate immune than adaptive immune. Conclusions: Our results indicated that breeding male giant pandas presented an immunoenhancement in innate immunity, enhanced antigen presentation and processing in cellular immunity compared to non-breeding males. The humoral immunity of male giant pandas may show a tendency to decrease during the breeding season. This study will provide a foundation for further studies of immunity and reproduction in male giant pandas.

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Comprehensive Analysis of Cell Cycle-Related Genes in Patients With Prostate Cancer

Frontiers in Oncology ◽

10.3389/fonc.2021.796795 ◽

2022 ◽

Vol 11 ◽

Author(s):

Zehua Liu ◽

Rongfang Pan ◽

Wenxian Li ◽

Yanjiang Li

Keyword(s):

Prostate Cancer ◽

Cell Cycle ◽

Risk Score ◽

Risk Model ◽

Cox Regression ◽

Expression Profiles ◽

Functional Enrichment ◽

Cancer Center ◽

Clinical Prognosis ◽

Normal Tissues

This study aimed to identify critical cell cycle-related genes (CCRGs) in prostate cancer (PRAD) and to evaluate the clinical prognostic value of the gene panel selected. Gene set variation analysis (GSVA) of dysregulated genes between PRAD and normal tissues demonstrated that the cell cycle-related pathways played vital roles in PRAD. Patients were classified into four clusters, which were associated with recurrence-free survival (RFS). Moreover, 200 prognostic-related genes were selected using the Kaplan–Meier (KM) survival analysis and univariable Cox regression. The prognostic CCRG risk score was constructed using random forest survival and multivariate regression Cox methods, and their efficiency was validated in Memorial Sloan Kettering Cancer Center (MSKCC) and GSE70770. We identified nine survival-related genes: CCNL2, CDCA5, KAT2A, CHTF18, SPC24, EME2, CDK5RAP3, CDC20, and PTTG1. Based on the median risk score, the patients were divided into two groups. Then the functional enrichment analyses, mutational profiles, immune components, estimated half-maximal inhibitory concentration (IC50), and candidate drugs were screened of these two groups. In addition, the characteristics of nine hub CCRGs were explored in Oncomine, cBioPortal, and the Human Protein Atlas (HPA) datasets. Finally, the expression profiles of these hub CCRGs were validated in RWPE-1 and three PRAD cell lines (PC-3, C4-2, and DU-145). In conclusion, our study systematically explored the role of CCRGs in PRAD and constructed a risk model that can predict the clinical prognosis and immunotherapeutic benefits.

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A Novel Ferroptosis-Related Biomarker Signature to Predict Overall Survival of Esophageal Squamous Cell Carcinoma

Frontiers in Molecular Biosciences ◽

10.3389/fmolb.2021.675193 ◽

2021 ◽

Vol 8 ◽

Author(s):

Jiahang Song ◽

Yanhu Liu ◽

Xiang Guan ◽

Xun Zhang ◽

Wenda Yu ◽

...

Keyword(s):

Squamous Cell Carcinoma ◽

Esophageal Squamous Cell Carcinoma ◽

Cell Carcinoma ◽

Risk Score ◽

Squamous Cell ◽

Risk Model ◽

Expression Profiles ◽

Gene Signature ◽

Immune Checkpoints ◽

Related Gene

Esophageal squamous cell carcinoma (ESCC) accounts for the main esophageal cancer (ESCA) type, which is also associated with the greatest malignant grade and low survival rates worldwide. Ferroptosis is recently discovered as a kind of programmed cell death, which is indicated in various reports to be involved in the regulation of tumor biological behaviors. This work focused on the comprehensive evaluation of the association between ferroptosis-related gene (FRG) expression profiles and prognosis in ESCC patients based on The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). ALOX12, ALOX12B, ANGPTL7, DRD4, MAPK9, SLC38A1, and ZNF419 were selected to develop a novel ferroptosis-related gene signature for GEO and TCGA cohorts. The prognostic risk model exactly classified patients who had diverse survival outcomes. In addition, this study identified the ferroptosis-related signature as a factor to independently predict the risk of ESCC. Thereafter, we also constructed the prognosis nomogram by incorporating clinical factors and risk score, and the calibration plots illustrated good prognostic performance. Moreover, the association of the risk score with immune checkpoints was observed. Collectively, the proposed ferroptosis-related gene signature in our study is effective and has a potential clinical application to predict the prognosis of ESCC.

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Early atypical signs and insula hypometabolism predict survival in multiple system atrophy

Journal of Neurology Neurosurgery & Psychiatry ◽

10.1136/jnnp-2020-324823 ◽

2021 ◽

pp. jnnp-2020-324823

Author(s):

Stephan Grimaldi ◽

Mohamed Boucekine ◽

Tatiana Witjas ◽

Frederique Fluchere ◽

Jean-Philippe Azulay ◽

...

Keyword(s):

Prognostic Factors ◽

Multiple System Atrophy ◽

Median Survival ◽

Risk Score ◽

Cox Regression ◽

Cox Model ◽

Clinical Prognosis ◽

Cox Regression Analysis ◽

Brain Pet ◽

Left Insula

ObjectiveWe aim to search for predictors of survival among clinical and brain 18F-FDG positron emission tomography (PET) metabolic features in our cohort of patients with multiple system atrophy (MSA).MethodsWe included patients with a ‘probable’ MSA diagnosis for whom a clinical evaluation and a brain PET were performed early in the course of the disease (median 3 years, IQR 2–5). A retrospective analysis was conducted using standardised data collection. Brain PET metabolism was characterised using the Automated Anatomical Labelling Atlas. A Cox model was applied to look for factors influencing survival. Kaplan-Meier method estimated the survival rate. We proposed to develop a predictive ‘risk score’, categorised into low-risk and high-risk groups, using significant variables entered in multivariate Cox regression analysis.ResultsEighty-five patients were included. The overall median survival was 8 years (CI 6.64 to 9.36). Poor prognostic factors were orthostatic hypotension (HR=6.04 (CI 1.58 to 23.12), p=0.009), stridor (HR=3.41 (CI 1.31 to 8.87), p=0.012) and glucose PET hypometabolism in the left insula (HR=0.78 (CI 0.66 to 0.92), p=0.004). Good prognostic factors were time to diagnosis (HR=0.68 (CI 0.54 to 0.86), p=0.001) and use of selective serotonin reuptake inhibitor (SSRI) (HR=0.17 (CI 0.06 to 0.46), p<0.001). The risk score revealed a 5-year gap separating the median survival of the two groups obtained (5 years vs 10 years; HR=5.82 (CI 2.94 to 11.49), p<0.001).ConclusionThe clinical prognosis factors we have described support published studies. Here, we also suggest that brain PET is of interest for prognosis assessment and in particular in the search for left insula hypometabolism. Moreover, SSRIs are a potential drug candidate to slow the progression of the disease.

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Identification of the Ferroptosis-Related Long Non-Coding RNAs Signature to Improve the Prognosis Prediction in patients with NSCLC

10.21203/rs.3.rs-598005/v1 ◽

2021 ◽

Author(s):

Meng Li ◽

Yanpeng Zhang ◽

Meng Fan ◽

Hui Ren ◽

Mingwei Chen ◽

...

Keyword(s):

Risk Score ◽

Cox Regression ◽

Cox Model ◽

Expression Profiles ◽

External Validation ◽

Risk Groups ◽

Differentially Expressed ◽

Roc Curve Analysis ◽

Cox Regression Analysis ◽

Kaplan Meier

Abstract Background: Non-small cell lung cancer (NSCLC) is the most prevalent type of lung carcinoma with an unfavorable prognosis. Ferroptosis, a novel iron-dependent programmed cell death, is involved in the development of multiple cancers. Of note, the prognostic value of ferroptosis-related lncRNAs in NSCLC remains uncertain. Methods: Gene expression profiles and clinical information of NSCLC were retrieved from the TCGA database. Ferroptosis-related genes (FRGs) were explored in the FerrDb database and ferroptosis-related lncRNAs (FRGs-lncRNAs) were identified by the correlation analysis and the LncTarD database. Next, The differentially expressed FRGs-lncRNAs were screened and FRGs-lncRNAs associated with the prognosis were explored by univariate Cox regression analysis and Kaplan-Meier survival analysis. Then, an FRGs-lncRNAs signature was constructed by the Lasso-penalized Cox model in the training cohort and verified by internal and external validation. Finally, the potential correlation between risk score, immune response, and chemotherapeutic sensitivity was further investigated.Results: 129 lncRNAs with a potential regulatory relationship with 59 differentially expressed FRGs were found in NSCLC and 10 FRGs-lncRNAs associated with the prognosis of NSCLC were identified (P<0.05). 9 prognostic-related FRGs-lncRNAs (AQP4-AS1, DANCR, LINC00460, LINC00892, LINC00996, MED4-AS1, SNHG7, UCA1, and WWC2-AS2) were used to construct the prognostic model and stratify patients with NSCLC into high- and low-risk groups. Kaplan-Meier analysis demonstrated a worse outcome in patients with high risk (P<0.05). Moreover, a good predictive capacity of this signature in predicting NSCLC prognosis was confirmed by the ROC curve analysis. Additionally, 45 immune checkpoint genes and 8 m6A-related genes were found differentially expressed in the two risk groups, and the sensitivity of 28 chemotherapeutics were identified to be correlated with the risk score. Conclusion: A novel FRGs-lncRNAs signature was successfully constructed, which may contribute to improving the management strategies of NSCLC.

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Comprehensive Analysis of a ceRNA Network Reveals Potential Prognostic lncRNAs Involved in Progression of Bladder Cancer

10.21203/rs.3.rs-434872/v1 ◽

2021 ◽

Author(s):

Dehua Ou ◽

Zesong Wu ◽

Peilin Shen ◽

Yingkai Hong ◽

Si Chen ◽

...

Keyword(s):

Bladder Cancer ◽

Risk Score ◽

Cox Model ◽

Expression Profiles ◽

Training Group ◽

Survival Prediction ◽

Competing Endogenous Rna ◽

Aberrant Expression ◽

Cerna Network ◽

Risk Patients

Abstract Background: The aberrant expression of long non-coding RNAs (lncRNAs) has attracted more and more attention in the biological field of bladder cancer(BC). We aim to construct a competing endogenous RNA(ceRNA) network reveals potential prognostic lncRNAs involved in progression of BC.Results: Expression profiles of messenger RNA(mRNA), micro RNA(miRNA) and lncRNA of 397 BC samples and 19 non-tumor tissues were downloaded from The Cancer Genome Atlas(TCGA) database. Patients with BC were randomly divided into training group (n=198) and validation group (n=199). Then, 130 lncRNAs, 159 miRNAs and 2,048 mRNAs were identified as differentially expressed genes (DEGs, |logFC|>1, FDR<0.01) related to BC progression. Nextly, we constructed an BC associated deregulated competing endogenous RNA(ceRNA) network with 70 lncRNAs, 30 miRNAs, and 62 mRNAs involved in. Subsequently, a seven-lncRNA signature was constructed by establishing a LASSO Cox model with 13 lncRNAs associated with survival from the ceRNA network. This signature can well distinguish high-risk patients from low-risk patients in training group and verification group. Furthermore, we combined the risk score model with other clinical fictures to estimate the ability of survival prediction. The result suggested that the risk score can be selected as an independent prognostic factor for overall survival(OS) rate. Conclusion: In this study, we construct a ceRNA network related to progression of BC and established an seven-lncRNA signature, which was a candidate prognostic biomarker for prognostic prediction of BC patients .

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Identification of an Immunologic Signature of Lung Adenocarcinomas Based on Genome-Wide Immune Expression Profiles

Frontiers in Molecular Biosciences ◽

10.3389/fmolb.2020.603701 ◽

2021 ◽

Vol 7 ◽

Author(s):

Bo Ling ◽

Guangbin Ye ◽

Qiuhua Zhao ◽

Yan Jiang ◽

Lingling Liang ◽

...

Keyword(s):

Gene Expression ◽

Lung Cancer ◽

Risk Score ◽

Cox Regression ◽

Expression Profiles ◽

External Validation ◽

Immune Gene ◽

Clinical Prognosis ◽

Resistance Pathway ◽

Lung Adenocarcinomas

Background: Lung cancer is one of the most common types of cancer, and it has a poor prognosis. It is urgent to identify prognostic biomarkers to guide therapy.Methods: The immune gene expression profiles for patients with lung adenocarcinomas (LUADs) were obtained from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO). The relationships between the expression of 45 immune checkpoint genes (ICGs) and prognosis were analyzed. Additionally, the correlations between the expression of 45 biomarkers and immunotherapy biomarkers, including tumor mutation burden (TMB), mismatch repair defects, neoantigens, and others, were identified. Ultimately, prognostic ICGs were combined to determine immune subgroups, and the prognostic differences between these subgroups were identified in LUAD.Results: A total of 11 and nine ICGs closely related to prognosis were obtained from the GEO and TCGA databases, respectively. CD200R1 expression had a significant negative correlation with TMB and neoantigens. CD200R1 showed a significant positive correlation with CD8A, CD68, and GZMB, indicating that it may cause the disordered expression of adaptive immune resistance pathway genes. Multivariable Cox regression was used to construct a signature composed of four prognostic ICGs (IDO1, CD274, CTLA4, and CD200R1): Risk Score = −0.002*IDO1+0.031*CD274−0.069*CTLA4−0.517*CD200R1. The median Risk Score was used to classify the samples for the high- and low-risk groups. We observed significant differences between groups in the training, testing, and external validation cohorts.Conclusion: Our research provides a method of integrating ICG expression profiles and clinical prognosis information to predict lung cancer prognosis, which will provide a unique reference for gene immunotherapy for LUAD.

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Immune profiles of male giant panda (Ailuropoda melanoleuca) during the breeding season

BMC Genomics ◽

10.1186/s12864-021-07456-x ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Haibo Shen ◽

Caiwu Li ◽

Ming He ◽

Yan Huang ◽

Jing Wang ◽

...

Keyword(s):

Pattern Recognition ◽

Breeding Season ◽

Giant Panda ◽

Expression Profiles ◽

Killer Cell ◽

Pattern Recognition Receptors ◽

Ailuropoda Melanoleuca ◽

Giant Pandas ◽

Altered Expression ◽

Immune Related Genes

Abstract Background The giant panda (Ailuropoda melanoleuca) is a threatened endemic Chinese species and a flagship species of national and global conservation concern. Life history theory proposes that reproduction and immunity can be mutually constraining and interrelated. Knowledge of immunity changes of male giant pandas during the breeding season is limited. Results Here, we researched peripheral blood gene expression profiles associated with immunity. Thirteen captive giant pandas, ranging from 9 to 11 years old, were divided into two groups based on their reproductive status. We identified 318 up-regulated DEGs and 43 down-regulated DEGs, which were enriched in 87 GO terms and 6 KEGG pathways. Additionally, we obtained 45 immune-related genes with altered expression, mostly up-regulated, and identified four hub genes HSPA4, SUGT1, SOD1, and IL1B in PPI analysis. These 45 genes were related to pattern recognition receptors, autophagy, peroxisome, proteasome, natural killer cell, antigen processing and presentation. SUGT1 and IL1B were related to pattern recognition receptors. HSP90AA1 was the most up-regulated gene and is a member of heat shock protein 90 family. HSP90 contributes to the translocation of extracellular antigen. KLRD1 encodes CD94, whose complex is an inhibitor of the cytotoxic activity of NK cells, was down-regulated. IGIP, which has the capability of inducing IgA production by B cells, was down-regulated, suggesting low concentration of IgA in male giant pandas. Our results suggest that most immune-related genes were up-regulated and more related to innate immune than adaptive immune. Conclusions Our results indicated that breeding male giant pandas presented an immunoenhancement in innate immunity, enhanced antigen presentation and processing in cellular immunity compared to non-breeding males. The humoral immunity of male giant pandas may show a tendency to decrease during the breeding season. This study will provide a foundation for further studies of immunity and reproduction in male giant pandas.

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