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

MATHEMATICAL BIOSCIENCES AND ENGINEERING 2022年第2期19卷 1448-1470页

作者： Liu, Jing Zhang, Xuefang Ye, Ting Dong, Yongjian Zhang, Wenfeng Wu, Fenglin Bo, Huaben Shao, Hongwei Zhang, Rongxin Shen, Han Guangdong Pharmaceut Univ Sch Life Sci & Biopharmaceut Guangdong Prov Key Lab Biotechnol Drug Candidates Guangzhou 510006 Guangdong Peoples R China Southern Med Univ Affiliated Dongguan Hosp Dongguan Peoples Hosp Dept Radiat Oncol Dongguan 523059 Guangdong Peoples R China

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 nineIRG 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

关键词： metastatic melanoma tumor microenvironment estimate algorithm prognostic model bioinformatics

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A prognostic signature based on immune-related genes for cervical squamous cell carcinoma and endocervical adenocarcinoma

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INTERNATIONAL IMMUNOPHARMACOLOGY 2020年 88卷 106884-106884页

作者： Liu, Jinhui Wu, Zhipeng Wang, Yichun Nie, Sipei Sun, Rui Yang, Jing Cheng, Wenjun Nanjing Med Univ Dept Gynecol Affiliated Hosp 1 300 Guangzhou Rd Nanjing 210029 Peoples R China Nanjing Med Univ Dept Urol Affiliated Sir Run Run Hosp Nanjing Jiangsu Peoples R China Nanjing Med Univ Dept Urol Affiliated Hosp 1 Nanjing 210029 Peoples R China

Cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) is the fourth commonest female malignancy worldwide. CESC progresses in immune-microenvironment mainly composed of infiltrating immune and stromal cells. Here, we performed an integrated analysis incorporating the expression profiles from the Cancer Genome Atlas (TCGA) database and scores of immune and stromal cells calculated by Estimation of Stromal and Immune cells in Malignant Tumours using Expression data (estimate) algorithm. A two-gene signature (CD1C and CD6 genes) was established to predict the prognosis of CESC. Based on this signature, patients were divided into the high- and low-risk groups, and this signature showed good prognostic performance according to the results of Kaplan-Meier analysis and receiver operating characteristic (ROC) analysis in train set and two validation sets. A nomogram was built for evaluating the clinical applicability of this signature. In addition, based on Tumor Immune Estimation Resource (TIMER) database, 2 hub genes showed negative correlations with tumor purity and positive correlations with infiltrating levels of immune filtrating cells. What's more, we propose new treatment strategies for the two prognostic subtypes. Low- risk patients were found presenting with a higher level of immune checkpoint molecules and showing higher immunogenicity in immunophenoscore (IPS) analysis, which indicated a better response for immunotherapy. Meanwhile, estimated by Genomics of Drug Sensitivity in Cancer (GDSC) database, the high-risk patients showed sensitive responses to five chemotherapy drugs. Finally, 10 candidate small-molecule drugs for CESC were defined. In summary, the CD1C-CD6 signature can accurately predict the prognosis of CESC.

关键词： CESC Immune microenvironment estimate algorithm Prognosis TCGA

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CSF1R is a Prognostic Biomarker and Correlated with Immune Cell Infiltration in the Gastric Cancer Microenvironment

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PHARMACOGENOMICS & PERSONALIZED MEDICINE 2021年 14卷 445-457页

作者： Chen, Di Xiong, Lina Zhang, Li Yu, Honglu Xu, Yushuang Wang, Mengmeng Jiang, Xin Xiong, Zhifan Huazhong Univ Sci & Technol Liyuan Hosp Tongji Med Coll Dept Gastroenterol Wuhan 430061 Peoples R China

Purpose: The tumor microenvironment (TME) plays a crucial role in the progression and prognosis of gastric cancer (GC). This study investigated TME-associated genes and explored their roles in the GC microenvironment. Methods: A total of 330 GC samples were extracted from TCGA. estimate and CIBERSORT algorithms were utilized to evaluate the stromal and immune scores of GC samples and the fraction of 22 immune cells infiltrated in the TME. Then, the TME-related differentially expressed genes (DEGs) were determined through integrative analysis. Protein-protein interaction (PPI) network and Cox regression analysis were conducted to analyze DEGs, and CSF1R was determined as the most crucial gene. We further probed the role of CSF1R in the GC microenvironment and evaluated the prognostic value of CSF1R. Results: We identified 560 TME-related DEGs and found CSF1R associated with the development and prognosis of GC. Further analysis showed that CSF1R was involved in immune-related signaling pathways. Furthermore, CIBERSORT analysis revealed that CSF1R expression correlated with several kinds of infiltrating immune cells, including tumor-associated macrophages (TAMs), B cells, NK cells, neutrophils, eosinophils, T cells, dendritic cells, and so on. Conclusion: In summary, CSF1R might take part in the modulation of immune-active status in the GC microenvironment and could be a promising biomarker for GC therapy and prognosis.

关键词： CSF1R gastric cancer tumor microenvironment infiltrating immune cells estimate algorithm CIBERSORT algorithm

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Exploring TCGA database for identification of potential prognostic genes in stomach adenocarcinoma

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CANCER CELL INTERNATIONAL 2020年第1期20卷 264-264页

作者： Zhou, Lin Huang, Wei Yu, He-Fen Feng, Ya-Juan Teng, Xu Univ Sci & Technol China Sch Informat Sci & Technol Hefei 230026 Anhui Peoples R China Capital Med Univ Sch Basic Med Sci Dept Biochem & Mol Biol Beijing Key Lab Tumor Invas & Metastasis Beijing 100069 Peoples R China

Background Stomach adenocarcinoma (STAD) is the fifth most prevalent cancer in the world and ranks third among cancer-related deaths worldwide. The tumour microenvironment (TME) plays an important role in tumorigenesis, development, and metastasis. Hence, we calculated the immune and stromal scores to find the potential prognosis-related genes in STAD using bioinformatics analysis. Methods The estimate algorithm was used to calculate the immune/stromal scores of the STAD samples. Functional enrichment analysis, protein-protein interaction (PPI) network analysis, and overall survival analysis were then performed on differential genes. And we validated these genes using data from the Gene Expression Omnibus database. Finally, we used the Human Protein Atlas (HPA) databases to verify these genes at the protein levels by IHC. Results Data analysis revealed correlation between stromal/immune scores and the TNM staging system. The top 10 core genes extracted from the PPI network, and primarily involved in immune responses, extracellular matrix, and cell adhesion. There are 31 genes have been validated with poor prognosis and 16 genes were upregulated in tumour tissues compared with normal tissues at the protein level. Conclusions In summary, we identified genes associated with the tumour microenvironment with prognostic implications in STAD, which may become potential therapeutic markers leading to better clinical outcomes.

关键词： Tumour microenvironment Stomach adenocarcinoma TCGA estimate algorithm Prognosis

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Stromal score as a prognostic factor in primary gastric cancer and close association with tumor immune microenvironment

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CANCER MEDICINE 2020年第14期9卷 4980-4990页

作者： Mao, Min Yu, Qingliang Huang, Rongzhi Lu, Yunxin Wang, Zhen Liao, Liang Guangxi Med Univ Clin Med Coll 1 Nanning Peoples R China Guangxi Med Univ Qinzhou Peoples Hosp 1 Affiliated Hosp 10 Dept Orthoped Surg Qinzhou Peoples R China Guangxi Med Univ Affiliated Hosp 1 Dept Gastrointestinal Surg Nanning Peoples R China Guangxi Med Univ Affiliated Hosp 1 Dept Traumat Orthoped & Hand Surg Nanning Peoples R China

Background Gastric cancer remains one of the major causes for tumor-related deaths worldwide. Our study aimed to provide an understanding of primary gastric cancer and prompt its clinical diagnosis and treatment. Methods We integrated the expression profiles and overall survival information of primary gastric cancer in TCGA and GEO database and estimated the stromal score of each sample by the estimate R package. Stromal score and clinicopathologic characteristics associated with overall survival were analyzed by using Cox regression and the Kaplan-Meier method. Gene set enrichment analysis (GSEA) and KEGG analysis were performed to explore the potential molecular mechanism in TCGA dataset. The relationship between immunotherapy-associated markers or immune cell types and stromal score was explored by using Pearson correlation analysis. Results A total of 796 samples were collected for the analysis. Patients with stromal score-high showed poor overall survival (P < .01, HR: 1.407, 95% CI: 1.144-1.731) and identified as an independent prognostic factor. KEGG analysis revealed that stromal score actively involved in diverse tumor-associated pathways. GSEA analysis also revealed stromal score associated with diverse immune-related biological processes. Furthermore, stromal score was related with immunotherapy-associated markers and multiple immune cells. Conclusion Our results showed that stromal score could serve as a potential prognostic biomarker in primary gastric cancer and play an important role in the recognition, surveillance, and prognosis of gastric cancer.

关键词： estimate algorithm primary gastric cancer stromal score tumor microenvironment

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Prognostic values of the immune microenvironment-related non-coding RNA IGF2BP2-AS1 in bladder cancer

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CELL CYCLE 2022年第23期21卷 2533-2549页

作者： Ding, Ke Zheng, Zhihuan Han, Yu Huang, Xiangyun Cent South Univ Xiangya Hosp Dept Urol Changsha Peoples R China Cent South Univ Xiangya Hosp 2 Dept Anesthesiol Changsha 412008 Hunan Peoples R China

Bladder cancer can range from noninvasive to invasive tumors. When non-muscle invasive bladder cancer (NMIBC) recurs, patients could endure long-term invasive malignancies with a high disease-specific death rate. Immune escape frequently results in tumor development, metastases, unfavorable prognosis, and failure of immunotherapy. Based on the median immune score, this study used estimate scores to evaluate 411 bladder cancer cases from TCGA-BLCA. Two hundred two ncRNAs were differentially expressed in two groups, where 29 candidates appeared to be associated with the overall survival of bladder cancer patients. LASSO algorithm was performed to establish the risk score model of 13-ncRNA. Risk scores were computed for cases in the training set, validation set, and TCGA-BLCA set;Poor prognosis in cases with higher risk scores was based on the training set, validating set, and TCGA-BLCA set. Among the 13 ncRNAs, IGF2BP2-AS1, MAGF-AS1, ARHGAP5-AS1, and LINC00942 were significantly correlated with the overall survival of bladder cancer patients. Pearson's correlation analysis based on TCGA-BLCA identified 2093, 3107, 386, and 936 mRNAs co-expressed with IGF2BP2-AS1, MAGF-AS1, ARHGAP5-AS1, and LINC00942, respectively. Conclusively, the 13 ncRNA signature exhibited a feasible predictive prognostic value for bladder cancer patients. IGF2BP2-AS1 expression was higher in bladder cancer tissues and significantly correlated to immune-related factors, suggesting that IGF2BP2-AS1 represents a promising immune-related target for treating bladder cancer patients.

关键词： Bladder cancer estimate algorithm LASSO algorithm non-coding RNA IGF2BP2-AS1

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Prognostic value of tumour microenvironment-related genes by TCGA database in rectal cancer

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JOURNAL OF CELLULAR AND MOLECULAR MEDICINE 2021年第12期25卷 5811-5822页

作者： Li, Chao Liu, Tao Liu, Yi Zhang, Jiantao Zuo, Didi First Hosp Jilin Univ Dept Colorectal & Anal Surg Changchun Peoples R China First Hosp Jilin Univ Dept Endocrinol & Metab Changchun Peoples R China

Rectal cancer is a common malignant tumour and the progression is highly affected by the tumour microenvironment (TME). This study intended to assess the relationship between TME and prognosis, and explore prognostic genes of rectal cancer. The gene expression profile of rectal cancer was obtained from TCGA and immune/stromal scores were calculated by Estimation of Stromal and Immune cells in Malignant Tumors using Expression data (estimate) algorithm. The correlation between immune/stromal scores and survival time as well as clinical characteristics were evaluated. Differentially expressed genes (DEGs) were identified according to the stromal/immune scores, and the functional enrichment analyses were conducted to explore functions and pathways of DEGs. The survival analyses were conducted to clarify the DEGs with prognostic value, and the protein-protein interaction (PPI) network was performed to explore the interrelation of prognostic DEGs. Finally, we validated prognostic DEGs using data from the Gene Expression Omnibus (GEO) database by PrognoScan, and we verified these genes at the protein levels using the Human Protein Atlas (HPA) databases. We downloaded gene expression profiles of 83 rectal cancer patients from The Cancer Genome Atlas (TCGA) database. The Kaplan-Meier plot demonstrated that low-immune score was associated with worse clinical outcome (P = .034), metastasis (M1 vs. M0, P = .031) and lymphatic invasion (+ vs. -, P < .001). A total of 540 genes were screened as DEGs with 539 up-regulated genes and 1 down-regulated gene. In addition, 60 DEGs were identified associated with overall survival. Functional enrichment analyses and PPI networks showed that the DEGs are mainly participated in immune process, and cytokine-cytokine receptor interaction. Finally, 19 prognostic genes were verified by and from GEO, and five genes (ADAM23, ARHGAP20, ICOS, IRF4, MMRN1) were significantly different in tumour tissues compared with normal tissues at the protein le

关键词： estimate algorithm overall survival prognosis rectal cancer tumour microenvironment

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Prognostic value of immune-related genes and comparative analysis of immune cell infiltration in lung adenocarcinoma: sex differences

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BIOLOGY OF SEX DIFFERENCES 2021年第1期12卷 1页

作者： Fan, Tao Li, Chunxiang He, Jie Wuhan Univ Renmin Hosp Dept Oncol 238th Jiefang Rd Wuhan 430060 Peoples R China Chinese Acad Med Sci & Peking Union Med Coll Canc Hosp Natl Clin Res Ctr Canc Dept Thorac SurgNatl Canc Ctr Beijing 100021 Peoples R China

Background Lung adenocarcinoma (LUAD) is one of the most important subtypes of lung cancer. Compared with male LUAD patients, female patients have a higher incidence, but better long-term survival rate, with unknown reasons. In this study, we aimed to explore the effect of sex differences on immune cell infiltration in lung tumor microenvironment (TME), and tried to clarify the reasons for the different clinical characteristics of male and female LUAD patients, by conducting a comparative analysis of the TME. Methods Using estimate algorithm, we calculated immune and stromal scores of tumor samples downloaded from TCGA database according to immune or stromal components in TME. GO and KEGG enrichment analysis were conducted to reveal biological processes of these intersecting genes of high- and low-score groups. Cox regression analysis and protein-protein interaction (PPI) network analysis were performed to screen immune-related prognostic genes in female (CCR2, LCP2, and PTPRC) and male (BTK and CCR2) patients. Kaplan-Meier survival analysis was used to evaluate prognostic value of these identified genes. Mann-Whitney test was used to compare various indicators of male patients and female patients. The main results were subsequently validated in 420 cases from GSE72094. Results 304 and 368 intersecting genes were identified in female and male patients, respectively. The immune score ranged from -943.17 to 3229.35 among female patients and from -541.75 to 3441.78 among male patients. The stromal score ranged from -1790.23 to 2097.27 among female patients and from -1786.94 to 1722.70 among male patients. The immune and stromal scores of women were higher than those of men (p < 0.05). CCR2, LCP2 and PTPRC were identified as the most important immune-related prognostic genes in female LUAD patients. BTK and CCR2 were identified as the most important immune-related prognostic genes in male LUAD patients. Female patients had a higher proportion of memory B cells than that

关键词： Lung adenocarcinoma Sex differences Tumor microenvironment estimate algorithm Tumor-infiltrating immune cells

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Identification of Four Genes as Prognosis Signatures in Lung Adenocarcinoma Microenvironment

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PHARMACOGENOMICS & PERSONALIZED MEDICINE 2021年 14卷 15-26页

作者： Yao, Yan Zhang, Tingting Qi, Lingyu Liu, Ruijuan Liu, Gongxi Li, Jie Sun, Changgang Weifang Med Univ Clin Med Coll Weifang Shandong Peoples R China Shandong Univ Tradit Chinese Med Coll Clin Med 1 Jinan Shandong Peoples R China Weifang Tradit Chinese Hosp Dept Oncol Weifang Shandong Peoples R China Shandong Univ Tradit Chinese Med Innovat Inst Chinese Med & Pharm Jinan Shandong Peoples R China

Background: Tumor microenvironment (TME) cells constitute a vital element of tumor tissues. Increasing evidence has shown that immune response in the microenvironment plays an active role in tumor invasion, metastasis, and recurrence, and is an important factor affecting tumor prognosis. Our study aimed to identify the gene signatures in lung adenocarcinoma (LUAD) microenvironment for prognosis and immunotherapy. Methods: In this study, we evaluated, for the first time, the stromal and immune scores of 594 patients from The Cancer Genome Atlas (TCGA) database with LUAD using the estimate algorithm. Three hundred and sixty-seven dysregulated immune-related genes were identified. Then, we performed functional enrichment analysis of these genes, and found the best gene model and construct the signature through univariate, Lasso and multivariate COX regression analysis. To assess the independently prognostic ability of the signature, the Kaplan-Meier survival analysis and Cox's proportional hazards model were performed. Results: Functional enrichment analysis and protein-protein interaction networks showed that the immune-related genes mainly played a role in immune response, activation/proliferation of immune-related cells, and chemokine activity. A prognostic model involving 6 genes was constructed and the signature was identified as an independent prognostic factor and significantly associated with the overall survival (OS) of LUAD. The area under curve (AUC) of the receiver operating characteristic curve (ROC curve) for the 6 genes signature in predicting the 3-year survival rate was 0.708. Finally, four genes (FOXN4, KLHL4, FAM83F and CCR2) can be used as candidate prognostic biomarkers for LUAD. Conclusion: Our findings will help evaluate the prognosis of LUAD and provide new ideas for exploring the potential relationship between TME and LUAD treatment and prognosis.

关键词： lung adenocarcinoma tumor microenvironment estimate algorithm immune-related gene prognosis signatures

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Grade II/III Glioma Microenvironment Mining and Its Prognostic Merit

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WORLD NEUROSURGERY 2019年 132卷 E76-E88页

作者： Chen, Jiawei Hou, Chongxian Wang, Peng Yang, Yong Zhou, Dong Guangdong Acad Med Sci Guangdong Prov Peoples Hosp Dept Neurosurg Guangzhou Guangdong Peoples R China Shantou Univ Med Coll Shantou Guangdong Peoples R China Hokkaido Univ Fac Med Dept Neurosurg Sapporo Hokkaido Japan

OBJECTIVE: The tumor microenvironment greatly influences tumor formation, invasion, and progression. The estimate (Estimation of STromal and Immune cells in MAlignant Tumor tissues) algorithm quantifies stromal and immune components in a tumor, reflecting the tumor microenvironment. This study aimed to explore key prognostic genes in a grade II/III glioma microenvironment. METHODS: We obtained stromal/immune scores for the Cancer Genome Atlas (TCGA) grade II/III glioma cohort from the online estimate portal. The associations of stromal/immune scores with clinicopathologic characteristics and overall survival of patients with grade II/III glioma were assessed by the Mann-Whitney U test and the Kaplan-Meier method, respectively. Functional enrichment analysis and protein-protein interaction network assessments were employed to analyze differentially expressed genes (DEGs). The top 7 genes with 5 or more edges in the protein-protein interaction network were selected. For validation, CGGA grade II/III glioma data were analyzed. RESULTS: The results showed that elevated stromal/immune/estimate score was significantly associated with poor survival of patients with TCGA grade II/III glioma. Functional enrichment analysis showed that DEGs were associated with immune cell regulation, extracellular matrix, cytokine activation, and receptor binding. The selected DEGs (interleukin-10, beta-2 microglobulin, C-C motif chemokine ligand 5, cluster of differentiation 74, human leukocyte antigen-DRA, lymphocyte cytosolic protein 2, and myxovirus resistance protein 1) showed prognostic values in patients with grade II/III glioma of the TCGA and CGGA database. CONCLUSIONS: Stromal/immune/estimate scores have prognostic values in patients with grade II/III glioma. The selected DEGs, including interleukin-10, beta-2 microglobulin, C-C motif chemokine ligand 5, cluster of differentiation 74, human leukocyte antigen-DRA, lymphocyte cytosolic protein 2, and myxovirus resistance protein 1, a

关键词： CGGA estimate algorithm Grade II/III glioma TCGA Tumor microenvironment

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