Racial Differences in the Biochemical Effects of Stress in Pregnancy

Prenatal stress has been linked to preterm birth via inflammatory dysregulation. We conducted a cross-sectional study on female participants who delivered live, singleton infants at University of Pittsburgh Medical Center Magee Women’s Hospital. Participants (n = 200) were stratified by cumulative risk scores using a combination of individual factors (maternal education, diabetes, hypertension, smoking, relationship status, obesity, depression) and neighborhood deprivation scores. We hypothesized that inflammatory cytokines levels differ by risk group and race. Multiplex analyses of IL-6, IL-8, IL-10, IL-13 and TNF-alpha were run. We found that Black birthing people had more risk factors for chronic stress and had lower levels of IL-6 compared to White birthing people. When stratified by risk group and race, low-risk Black birthing people had lower levels of IL-6 compared to low-risk White birthing people, and high-risk Black birthing people had lower levels of IL-8 compared to high-risk White birthing people. Higher area deprivation scores were associated with lower IL-6 levels. Our results suggest that the relationship between chronic stress and inflammatory cytokines is modified by race. We theorize that Black birthing people encounter repetitive stress due to racism and social disadvantage which may result in stress pathway desensitization and a blunted cytokine response to future stressors.

Download Full-text

Differences In Community and Academic Practice Patterns For Newly Diagnosed Myelodysplastic Syndromes (MDS) Patients In Minnesota: A Population Based Study

Blood ◽

10.1182/blood.v122.21.2798.2798 ◽

2013 ◽

Vol 122 (21) ◽

pp. 2798-2798 ◽

Cited By ~ 1

Author(s):

Daniel Pease ◽

Julie A Ross ◽

Phuong L. Nguyen ◽

Betsy Hirsch ◽

Adina Cioc ◽

...

Keyword(s):

High Risk ◽

Supportive Care ◽

Practice Patterns ◽

Risk Group ◽

Population Based ◽

Low Risk ◽

Risk Scores ◽

First Year ◽

Newly Diagnosed ◽

Population Based Study

Abstract Introduction Expanding treatment options for MDS have changed therapeutic decision-making for clinicians. To better characterize therapeutic choices in newly diagnosed MDS, we report the practice patterns captured during the first year of MDS diagnosis for patients enrolled in our statewide population-based study. We highlight a comparison of treatment in community and academic centers. Methods Adults in Minnesota with MDS (AIMMS) is a statewide prospective population-based study conducted by the University of Minnesota (UMN), Mayo Clinic, and Minnesota Department of Health. Starting in April 2010, all newly diagnosed adult cases (ages 20+) of MDS were invited to participate. After patient enrollment, central review was performed consisting of independent hematopathology and cytogenetic review coupled with oncologist chart review assigning prognostic risk scores [International Prognostic Scoring System (IPSS) and IPSS-R (Revised)] and abstracting treatment exposures. All enrolled patients with one year follow-up were included in this analysis. Treatment was divided into supportive, active, transplant, or other. Supportive care included observation, growth factors, and transfusions. Active care included azacitidine, decitabine, lenalidomide, or 7+3 chemotherapy. Academic centers were defined as the UMN and Mayo Clinic; all other centers were designated as community based practices. Results The median patient age was 73 years, with 68% males. IPSS and IPSS-R risk scores were calculated for 100% and 97% of patients, respectively. Treatment choices stratified by IPSS risk group showed 89% low risk, 53% INT-1, 31% INT-2, and 13% high risk with supportive care; active and transplant strategies were utilized for 9% low risk, 44% INT-1, 64% INT-2, and 88% high risk. INT-1 in the community received 70% supportive treatment, in academic 35%. Active treatment for INT-1 was 30% in community and 45% in academic. Community INT-2 received supportive care in 45% of cases, in academic 23%. Transplants were limited to academic centers, with the highest rate in INT-2 at 34%. Among community diagnoses, 100% of high risk, 52% INT-2, 26% INT-1, and 13% low risk were referred to an academic center. Comparison of age <65 and 65+ years showed 83% of transplants occurred in those <65. INT-2/high risk group patients <65 received 95% active therapy or transplant, compared to 51% of those 65+. Discussion This prospective, population based study provides a well-defined patient cohort based on central review of pathologic and clinical data. Evaluation of practice patterns during the first year after diagnosis showed higher utilization of active and transplant treatment strategies as IPSS risk score increased. Further, compared to community, higher utilization occurred for patients at academic centers, suggesting more aggressive treatment in these settings. Age was also a predictor of treatment choice. In addition, referral patterns followed IPSS score. Whether these treatment differences are driven by patient preference and/or translate into improved disease control and decreased mortality requires continued prospective analysis and will be detailed in future reports. Disclosures No relevant conflicts of interest to declare.

Download Full-text

Prognostic Modeling of Patients with Metastatic Melanoma Based on Tumor Immune Microenvironment Characteristics

10.21203/rs.3.rs-730205/v1 ◽

2021 ◽

Author(s):

Jing Liu ◽

Ting Ye ◽

Xue fang Zhang ◽

Yong jian Dong ◽

Wen feng Zhang ◽

...

Keyword(s):

High Risk ◽

Metastatic Melanoma ◽

Prognostic Model ◽

Cox Regression ◽

Risk Group ◽

Low Risk ◽

Risk Scores ◽

Immune Microenvironment ◽

Immune Infiltration ◽

Tumor Immune Microenvironment

Abstract Most of the malignant melanomas are already in the middle and advanced stages when they are diagnosed, which is often accompanied by the metastasis and spread of other organs.Besides, the prognosis of patients is bleak. The characteristics of the local immune microenvironment in metastatic melanoma have important implications for both tumor progression and tumor treatment. In this study, data on patients with metastatic melanoma from the TCGA and GEO datasets were selected for immune, stromal, and estimate scores, and overlapping differentially expressed genes (DEGs) were screened. A nine-IRGs prognostic model (ALOX5AP, ARHGAP15, CCL8, FCER1G, GBP4, HCK, MMP9, RARRES2 and TRIM22) was established by univariate COX regression, LASSO and multivariate COX regression. Receiver operating characteristic (ROC) curves were used to test the predictive accuracy of the model. Immune infiltration was analyzed by using CIBERSORT, Xcell and ssGSEA in high-risk and low-risk groups. The immune infiltration of the high-risk group was significantly lower than that of the low-risk group. Immune checkpoint analysis revealed that the expression of PDCD1, CTLA4, TIGIT, CD274, HAVR2 and LAG3 were significantly different in groups with different levels of risk scores. WGCNA analysis found that the yellow-green module contained seven genes (ALOX5AP, FCER1G, GBP4, HCK, MMP9, RARRES2 and TRIM22) from the nine-IRG prognostic model, of which the yellow-green module had the highest correlation with risk scores. The results of GO and KEGG suggested that the genes in the yellow-green module were mainly enriched in immune-related biological processes. Finally, we analyzed the prognostic ability and expression characteristics of ALOX5AP, ARHGAP15, CCL8, FCER1G, GBP4, HCK, MMP9, RARRES2 and TRIM22 in metastatic melanoma. Overall, a prognostic model for metastatic melanoma based on the characteristics of the tumor immune microenvironment was established, which was helpful for further studies.It could function well in helping people to understand the characteristics of the immune microenvironment in metastatic melanoma and to find possible therapeutic targets.

Download Full-text

Identification of N6-Methyladenosine-Associated Long Non-coding RNAs for Immunotherapeutic Response and Prognosis in Patients With Pancreatic Cancer

Frontiers in Cell and Developmental Biology ◽

10.3389/fcell.2021.748442 ◽

2021 ◽

Vol 9 ◽

Author(s):

Xinshuang Yu ◽

Peng Dong ◽

Yu Yan ◽

Fengjun Liu ◽

Hui Wang ◽

...

Keyword(s):

Pancreatic Cancer ◽

T Cell ◽

High Risk ◽

Messenger Rna ◽

Risk Group ◽

High Risk Group ◽

Low Risk ◽

Risk Scores ◽

Significant Difference ◽

Selection Operator

Pancreatic cancer is a highly aggressive disease with poor prognosis. N6-methyladenosine (m6A) is critical for post-transcriptional modification of messenger RNA (mRNA) and long non-coding RNA (lncRNA). However, the m6A-associated lncRNAs (m6A-lncRNA) and their values in predicting clinical outcomes and immune microenvironmental status in pancreatic cancer patients remain largely unexplored. This study aimed to evaluate the importance of m6A-lncRNA and established a m6A-lncRNA signature for predicting immunotherapeutic response and prognosis of pancreatic cancer. The m6A-lncRNA co-expression networks were constructed using data from the TCGA and GTEx database. Based on the least absolute shrinkage and selection operator (LASSO) analysis, we constructed an 8 m6A-lncRNA signature risk model, and selection operator (LASSO) analysis, and stratified patients into the high- and low-risk groups with significant difference in overall survival (OS) (HR = 2.68, 95% CI = 1.74–4.14, P < 0.0001). Patients in the high-risk group showed significantly reduced OS compared to patients in the low-risk group (P < 0.001). The clinical characteristics and m6A-lncRNA risk scores were used to construct a nomogram which accurately predicted the OS in pancreatic cancer. TIMER 2.0 were used to investigate tumor immune infiltrating cells and its relationship with pancreatic cancer. CIBERSORT analysis revealed increased higher infiltration proportions of M0 and M2 macrophages, and lower infiltration of naive B cell, CD8+ T cell and Treg cells in the high-risk group. Compared to the low-risk group, functional annotation using ssGSEA showed that T cell infiltration and the differential immune-related check-point genes are expressed at low level in the high-risk group (P < 0.05). In summary, our study constructed a novel m6A-associated lncRNAs signature to predict immunotherapeutic responses and provided a novel nomogram for the prognosis prediction of pancreatic cancer.

Download Full-text

The Immune Heterogeneity Between Pulmonary Adenocarcinoma and Squamous Cell Carcinoma: A Comprehensive Analysis Based on lncRNA Model

Frontiers in Immunology ◽

10.3389/fimmu.2021.547333 ◽

2021 ◽

Vol 12 ◽

Author(s):

Tao Yan ◽

Guoyuan Ma ◽

Kai Wang ◽

Weidong Liu ◽

Weiqing Zhong ◽

...

Keyword(s):

Lung Cancer ◽

Squamous Cell Carcinoma ◽

T Cell ◽

High Risk ◽

Cell Carcinoma ◽

Squamous Cell ◽

Risk Group ◽

Low Risk ◽

Gene Set Enrichment Analysis ◽

Risk Scores

Adenocarcinoma (AD) and squamous cell carcinoma (SCC) are both classified as major forms of non-small cell lung cancer, but differences in clinical prognoses and molecular mechanisms are remarkable. Recent studies have supported the importance of understanding immune status in that it influences clinical outcomes of cancer, and immunotherapies based on the theory of “immune editing” have had notable clinical success. Our study aimed to identify specific long non-coding (lnc) RNAs that control key immune-related genes and to use them to construct risk models for AD and SCC. Risk scores were used to separate patients into high- and low-risk groups, and we validated the prognostic significance of both risk scores with our own cohorts. A Gene Set Enrichment Analysis suggested that the immune responses of patients in the AD high-risk group and the SCC low-risk group tended to be weakened. Evaluation of immune infiltration revealed that the degree of infiltration of dendritic cells is of particular importance in AD. In addition, prediction of responses to immune checkpoint inhibitor (ICI) treatments, based on the T Cell Immune Dysfunction and Exclusion and immunophenoscore models, indicated that deterioration of the immune microenvironment is due mainly to T cell exclusion in AD patients and T cell dysfunction in SCC patients and that high-risk patients with SCC might benefit from ICI treatment. The prediction of downstream targets via The Cancer Proteome Atlas and RNA-seq analyses of a transfected lung cancer cell line indicated that the lncRNA LINC00996 is a potential therapeutic target in AD.

Download Full-text

Prognostic modeling of patients with metastatic melanoma based on tumor immune microenvironment characteristics

Mathematical Biosciences and Engineering ◽

10.3934/mbe.2022067 ◽

2021 ◽

Vol 19 (2) ◽

pp. 1448-1470

Author(s):

Jing Liu ◽

◽

Xuefang Zhang ◽

Ting Ye ◽

Yongjian Dong ◽

...

Keyword(s):

High Risk ◽

Metastatic Melanoma ◽

Prognostic Model ◽

Cox Regression ◽

Risk Group ◽

Low Risk ◽

Risk Scores ◽

Immune Microenvironment ◽

Immune Infiltration ◽

Tumor Immune Microenvironment

<abstract> <p>Most of the malignant melanomas are already in the middle and advanced stages when they are diagnosed, which is often accompanied by the metastasis and spread of other organs. Besides, the prognosis of patients is bleak. The characteristics of the local immune microenvironment in metastatic melanoma have important implications for both tumor progression and tumor treatment. In this study, data on patients with metastatic melanoma from the TCGA and GEO datasets were selected for immune, stromal, and estimate scores, and overlapping differentially expressed genes were screened. A nine-IRGs prognostic model (ALOX5AP, ARHGAP15, CCL8, FCER1G, GBP4, HCK, MMP9, RARRES2 and TRIM22) was established by univariate COX regression, LASSO and multivariate COX regression. Receiver operating characteristic curves were used to test the predictive accuracy of the model. Immune infiltration was analyzed by using CIBERSORT and Xcell in high-risk and low-risk groups. The immune infiltration of the high-risk group was significantly lower than that of the low-risk group. Immune checkpoint analysis revealed that the expression of PDCD1, CTLA4, TIGIT, CD274, HAVR2 and LAG3 demonstrated the visible difference in groups with different levels of risk scores. WGCNA analysis found that the yellow-green module contained seven genes from the nine-IRG prognostic model, and the yellow-green module had the highest correlation with risk scores. The results of GO and KEGG suggested that the genes in the yellow-green module were mainly enriched in immune-related biological processes. Finally, the expression characteristics of ALOX5AP, ARHGAP15, CCL8, FCER1G, GBP4, HCK, MMP9, RARRES2 and TRIM22 were analyzed between metastatic melanoma and normal samples. Overall, a prognostic model for metastatic melanoma based on the tumor immune microenvironment characteristics was established, which left plenty of space for further studies. It could function well in helping people to understand characteristics of the immune microenvironment in metastatic melanoma.</p> </abstract>

Download Full-text

Expression of immune-related genes as prognostic biomarkers for the assessment of osteosarcoma clinical outcomes

Scientific Reports ◽

10.1038/s41598-021-03677-y ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Junjie Guo ◽

Xiaoyang Li ◽

Shen Shen ◽

Xuejian Wu

Keyword(s):

High Risk ◽

Risk Score ◽

Risk Group ◽

Low Risk ◽

Functional Enrichment ◽

Risk Scores ◽

Survival Prediction ◽

Promising Therapeutic Approach ◽

Score Model ◽

Immune Related Genes

AbstractCancer immunotherapy is a promising therapeutic approach, but the prognostic value of immune-related genes in osteosarcoma (OS) is unknown. Here, Target-OS RNA-seq data were analyzed to detect differentially expressed genes (DEGs) between OS subgroups, followed by functional enrichment analysis. Cox proportional risk regression was performed for each immune-related gene, and a risk score model to predict the prognosis of patients with OS was constructed. The risk scores were calculated using the risk signature to divide the training set into high-risk and low-risk groups, and validation was performed with GSE21257. We identified two immune-associated clusters, C1 and C2. C1 was closely related to immunity, and the immune score was significantly higher in C1 than in C2. Furthermore, we validated 6 immune cell hub genes related to the prognosis of OS: CD8A, KIR2DL1, CD79A, APBB1IP, GAL, and PLD3. Survival analysis revealed that the prognosis of the high-risk group was significantly worse than that of the low-risk group. We also explored whether the 6-gene prognostic risk model was effective for survival prediction. In conclusion, the constructed a risk score model based on immune-related genes and the survival of patients with OS could be a potential tool for targeted therapy.

Download Full-text

Hematopoietic Cell Transplantation - Comorbidity Index (HCT-CI) as a Surrgoate Marker for Predition of Transplant Outcome for Pateints (pts) with Multiple Myeloma (MM) Undergoing Autologous Stem Cell Transplantation (ASCT): High HCT-CI Score Predicts for Poor Outcome.

Blood ◽

10.1182/blood.v110.11.5104.5104 ◽

2007 ◽

Vol 110 (11) ◽

pp. 5104-5104

Author(s):

Mohamed I. Farhat ◽

Ronald Myint ◽

Stephanie A. Gregory ◽

Parameswaran Venugopal ◽

Mohamad Kassar ◽

...

Keyword(s):

Multiple Myeloma ◽

High Risk ◽

Cell Transplantation ◽

Cox Regression ◽

Risk Group ◽

High Risk Group ◽

Low Risk ◽

Heart Valve Disease ◽

Risk Scores ◽

Transplant Outcome

Abstract Background: For all “transplant eligible” pts with MM, established practice guidelines recommend ASCT as part of the front line treatment. However, the definition of “transplant eligible” remains undefined. The HCT-CI is a new tool that encapsulates pre-transplant comorbidities used in predicting transplant outcomes in pts undergoing allogeneic SCT. This scoring system has been shown to be a good predictor for non-relapse mortality (NRM) & survival in pts undergoing alloSCT. In this study, we hypothesize that HCT-CI could predict the transplant outcome on pts with MM undergoing ASCT and could potentially be utilized as a tool for selecting pts with MM for transplant. Methods: A retrospective analysis of 75 pts with multiple myeloma whom underwent ASCT in our institution between 02/99 and 12/03 with a median follow up of 30 months. Pts were assigned scores based on the HCT-CI. Definitions of comorbidities were as previously reported by Sorror et. al. (Blood2005; 106:2912). Results: Median age was 56 years (38 – 73); M:F 1:1. 51 pts received a single & 24 had tandem ASCT. The majority of pt. had IgG myeloma (IgG kappa: 45; IgG Lambda 17). Comorbidities (points, number of pts): mild hepatic (1,16), renal (2,6), cardiac (1,8), arrhythmia (1,1), heart valve disease (3,4), cerebrovascular (1,8), DM (1,11), PUD (2,2), inflammatory bowel disease (1,0), Tumor (3,6), pulmonary (2,5), psychiatric (1,8), rheumatologic (2,3), infection (1,6), and obesity (1,10). HCT-CI score of 0 seen in 32%, 1 in 28%, 2–8 in 40% of the pts, with a median score of 1.65. 20 patients died with only one due to NRM. Pts were categorized into 2 groups: low-risk (scores of 0–1) – 46 pts and high-risk (scores 2–8) – 29. Using a cox regression model, the low risk group had a survival advantage (HR = 2.55, P = 0.04). Using Kaplan Meier survival estimate comparing the low risk and high risk group (figure1), the 5 yrs overall survival were 77% & 22% respectively (P = 0.04). While the median survival for the high risk group was 3.52 years, it has not been reached for the low risk group. Conclusion: Here, we have demonstrated a survival benefit for pts with low (0–1) compared with high (≥ 2) HCT-CI score. In addition, the outcome of pts with high HCT-CI score was also similar to non-transplant pts as published in the literature. This raises the question of “benefit” of ASCT for pts with high HCT-CI score. Thus, HCT-CI may serve as a useful tool to select pts whom would benefit most from ASCT. Figure 1 Figure 1

Download Full-text

Identifying a Hypoxia-Related Long Non-Coding RNAs Signature to Improve the Prediction of Prognosis and Immunotherapy Response in Hepatocellular Carcinoma

Frontiers in Genetics ◽

10.3389/fgene.2021.785185 ◽

2021 ◽

Vol 12 ◽

Author(s):

Pingfei Tang ◽

Weiming Qu ◽

Taoli Wang ◽

Minji Liu ◽

Dajun Wu ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Targeted Therapy ◽

High Risk ◽

Clinical Outcomes ◽

Risk Group ◽

Low Risk ◽

Risk Scores ◽

Prognostic Signature ◽

Testing Dataset ◽

Non Coding Rnas

Abstract Background: Both hypoxia and long non-coding RNAs (lncRNAs) contribute to the tumor progression in hepatocellular carcinoma (HCC). We sought to establish a hypoxia-related lncRNA signature and explore its correlation with immunotherapy response in HCC.Materials and Methods: Hypoxia-related differentially expressed lncRNAs (HRDELs) were identified by conducting the differential gene expression analyses in GSE155505 and The Cancer Genome Atlas (TCGA)- liver hepatocellular carcinoma (LIHC) datasets. The HRDELs landscape in patients with HCC in TCGA-LIHC was dissected by an unsupervised clustering method. Patients in the TCGA-LIHC cohort were stochastically split into the training and testing dataset. The prognostic signature was developed using LASSO (least absolute shrinkage and selection operator) penalty Cox and multivariable Cox analyses. The tumor immune microenvironment was delineated by the single-sample gene set enrichment analysis (ssGSEA) algorithm. The Tumor Immune Dysfunction and Exclusion (TIDE) algorithm was applied to evaluate the predictive value of the constructed signature in immunotherapeutic responsiveness.Results: A total of 55 HRDELs were identified through integrated bioinformatical analyses in GSE155505 and TCGA-LIHC. Patients in the TCGA-LIHC cohort were categorized into three HRDELs-specific clusters associated with different clinical outcomes. The prognostic signature involving five hypoxia-related lncRNAs (LINC00869, CAHM, RHPN1-AS1, MKLN1-AS, and DUXAP8) was constructed in the training dataset and then validated in the testing dataset and entire TCGA-LIHC cohort. The 5-years AUC of the constructed signature for prognostic prediction reaches 0.705 and is superior to that of age, AJCC stage, and histopathological grade. Patients with high-risk scores consistently had poorer overall survival outcomes than those with low-risk scores irrespective of other clinical parameters status. The low-risk group had more abundance in activated CD8+ T cell and activated B cell and were predicted to be more responsive to immunotherapy and targeted therapy than the high-risk group.Conclusion: We established a reliable hypoxia-related lncRNAs signature that could accurately predict the clinical outcomes of HCC patients and correlate with immunotherapy response and targeted drug sensitivity, providing new insights for immunotherapy and targeted therapy in HCC.

Download Full-text

Impact of infectious etiology on the outcome of Taiwanese patients hospitalized with community acquired pneumonia

The Journal of Infection in Developing Countries ◽

10.3855/jidc.2834 ◽

2013 ◽

Vol 7 (02) ◽

pp. 116-124 ◽

Cited By ~ 3

Author(s):

Yuan-Ti Lee ◽

Shiuan-Chih Chen ◽

Kuei-Chuan Chan ◽

Tzu-Chin Wu ◽

Shih-Ming Tsao ◽

...

Keyword(s):

High Risk ◽

Chlamydia Pneumoniae ◽

Risk Group ◽

Medical Center ◽

Pneumonia Severity Index ◽

Community Acquired Pneumonia ◽

High Risk Group ◽

Low Risk ◽

Empiric Treatment ◽

Infectious Etiology

Introduction: This study aimed to assess the relationships between infectious etiology, empiric treatment, and outcomes in Taiwanese patients with community acquired pneumonia (CAP). Methodology: A retrospective analysis of the data of 208 adult patients from a single medical center was performed with patients classified as having low or high disease severity based on the Pneumonia Severity Index (PSI). Patients with PSI ≤ 90 (n=120) were classified as low severity and patients with PSI > 90 (n=88) were classified as high severity. Results: The low-risk group had significantly higher rates of infection with Chlamydia pneumoniae (C. pneumoniae) and Mycoplasma pneumoniae (M. pneumoniae), whereas the high-risk group had significantly higher rates of infection with Klebsiella pneumoniae (K. pneumoniae) and Pseudomonas aeruginosa (P. aeruginosa) (p < 0.05). Empiric treatment in both groups was in accordance with the 2007 guidelines issued by the Infectious Diseases Society of America/American Thoracic Society (IDSA/ATS). Twenty-nine of 208 patients (13.9%) died, one in the low-risk group and 28 in the high-risk group. The highest rates of mortality were in patients infected with P. aeruginosa or K. pneumoniae. Conclusions: In the present study, we demonstrated that the patients with different severity had different microbiologic etiology. In general, P. aeruginosa and K. pneumoniae were the most commonly isolated organisms in high-risk patients who died from CAP. We showed that use of the IIDSA/ATS guidelines for treatment of CAP in Taiwan resulted in a better outcome in the low PSI group.

Download Full-text

Molecular Analysis of Prognosis and Immune Pathways of Pancreatic Cancer Based on TNF Family Members

Journal of Oncology ◽

10.1155/2021/2676996 ◽

2021 ◽

Vol 2021 ◽

pp. 1-13

Author(s):

Zemin Zhu ◽

Caixi Tang ◽

Tao Xu ◽

Zhijian Zhao

Keyword(s):

High Risk ◽

Risk Score ◽

Risk Group ◽

Family Members ◽

Enrichment Analysis ◽

High Risk Group ◽

Low Risk ◽

Risk Scores ◽

Score Model ◽

Vesicle Cycle

Background. Tumor necrosis factor (TNF) family members play a vital role in anticancer therapy. This study aimed to screen the critical markers for the prognostic analysis of pancreatic adenocarcinoma (PAAD) by analyzing the clustering patterns of TNF family members in PAAD. Methods. In this study, the NMF clustering method was adopted to cluster samples from The Cancer Genome Atlas (TCGA) to acquire the clustering pattern of the TNF family in PAAD. Differential gene analysis was performed according to TNF family gene clusters. The support vector machine (SVM) method was conducted for further gene screening, and the risk score model of the screened genes was constructed by Lasso. The single sample gene set enrichment analysis (ssGSEA) method was adopted for immunoenrichment analysis and tumor immune cycle analysis. Genes associated with risk scores were analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Results. We clustered PAAD into two groups based on TNF family genes. Nineteen TNF family genes were significantly associated with the clinical characteristics of PAAD patients. The risk score formula was composed of RHOD, UBE2C, KLHDC7b, MSLN, ADAM8, NME3, GNG2, and MCOLN3. GSE57495 and GSE62452 datasets verified that patients in the high-risk group had a worse prognosis than those in the low-risk group. The risk score-related genes analyzed by GO and KEGG were mainly involved in the modulation of chemical synaptic transmission and synaptic vesicle cycle pathway. There were significant differences in the expression of 15 immune cells between the high-risk group and the low-risk group. The risk score was positively correlated with HCK, interferon, MHC-I, and STAT1. The expression of genes relevant to chemokine, immunostimulator, MHC, and receptor was strongly associated with the risk score. Conclusion. The risk score model based on the TNF family can predict the prognosis and immune status of PAAD patients. Further research is needed to verify the clinical prognostic value of risk scores.

Download Full-text