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Wang X, Yang F, Sun Z, Zhao G, Pu Q, Geng C, Dong K, Zhang X, Liu Z, Song H. NKAIN1, as an oncogene, promotes the proliferation and metastasis of breast cancer, affecting its prognosis. Mol Carcinog 2024; 63:1392-1405. [PMID: 38651944 DOI: 10.1002/mc.23732] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2024] [Revised: 03/31/2024] [Accepted: 04/08/2024] [Indexed: 04/25/2024]
Abstract
Na, K-ATPase interaction (NKAIN) is a transmembrane protein family, which can interact with Na, K-ATPase β1 subunit. NKAIN1 plays an important role in alcohol-dependent diseases such as endometrial and prostate cancers. However, the relationship between NKAIN1 and human breast cancer has not been studied. Hence, this study aimed to explore the relationship between NKAIN1 expression and breast cancer. Data used in this study were mainly from the Cancer Genome Atlas, including differential expression analysis, Kaplan-Meier survival analysis, receiver operating characteristic curve analysis, multiple Cox regression analysis, co-expression gene analysis, and gene set enrichment analysis. Analyses were performed using reverse transcription-quantitative polymerase chain reaction, western blot analysis, and immunohistochemistry on 46 collected samples. The knockdown or overexpression of NKAIN1 in vitro in MCF-7 and MDA-MB-231 cell lines altered the proliferation and migration abilities of tumor cells. In vivo experiments further confirmed that NKAIN1 knockdown effectively inhibited the proliferation and migration of cancer cells. Therefore, our study identified NKAIN1 as an oncogene that is highly expressed in breast cancer tissues. The findings highlight the potential of NKAIN1 as a molecular biomarker of breast cancer.
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Affiliation(s)
- XiMei Wang
- Department of General Surgery, Qilu Hospital (Qingdao), Cheeloo College of Medicine, Shandong University, Qingdao, China
| | - FangZheng Yang
- Department of General Surgery, Qilu Hospital (Qingdao), Cheeloo College of Medicine, Shandong University, Qingdao, China
| | - Zhi Sun
- Department of General Surgery, Qilu Hospital (Qingdao), Cheeloo College of Medicine, Shandong University, Qingdao, China
- Department of Breast Disease(II), Shandong Second Provincial General Hospital, Jinan, China
| | - GuangHui Zhao
- Department of Medical Experimental Center, Qilu Hospital (Qingdao), Cheeloo College of Medicine, Shandong University, Qingdao, China
- Qingdao Key Lab of Mitochondrial Medicine, Qingdao, China
| | - Qian Pu
- Department of General Surgery, Qilu Hospital (Qingdao), Cheeloo College of Medicine, Shandong University, Qingdao, China
| | - ChenChen Geng
- Department of General Surgery, Qilu Hospital (Qingdao), Cheeloo College of Medicine, Shandong University, Qingdao, China
| | - Ke Dong
- Department of General Surgery, Qilu Hospital (Qingdao), Cheeloo College of Medicine, Shandong University, Qingdao, China
| | - XiaoDong Zhang
- Department of Medical Experimental Center, Qilu Hospital (Qingdao), Cheeloo College of Medicine, Shandong University, Qingdao, China
- Qingdao Key Lab of Mitochondrial Medicine, Qingdao, China
| | - ZiQian Liu
- Department of Medical Experimental Center, Qilu Hospital (Qingdao), Cheeloo College of Medicine, Shandong University, Qingdao, China
- Qingdao Key Lab of Mitochondrial Medicine, Qingdao, China
| | - HaiYun Song
- Department of Pathology, Qilu Hospital (Qingdao), Cheeloo College of Medicine, Shandong University, Qingdao, China
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Que X, Fan J, Chen D, Nie Z, Chen P. Brevilin A Inhibits Prostate Cancer Progression by Decreasing PAX5-Activated SOX4. Mol Biotechnol 2024:10.1007/s12033-024-01183-w. [PMID: 38744788 DOI: 10.1007/s12033-024-01183-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Accepted: 04/16/2024] [Indexed: 05/16/2024]
Abstract
Brevilin A possesses inhibitory effects on the development of prostate cancer (PCa); however, the underlying mechanism remains unclear. The present work aims to analyze how Brevilin A regulates PCa cell malignancy. RNA expression of paired box 5 (PAX5) and SRY-box transcription factor 4 (SOX4) was analyzed by quantitative real-time polymerase chain reaction. Protein expression of PAX5, SOX4, and nuclear proliferation marker (Ki67) was detected by western blotting or immunohistochemistry assay. The viability, proliferation, apoptosis, and migratory and invasive abilities of PCa cells were investigated by cell counting kit-8 (CCK-8), 5-Ethynyl-2'-deoxyuridine (EdU), flow cytometry, and transwell assays, respectively. The association between PAX5 and SOX4 was identified by dual-luciferase reporter assay and chromatin immunoprecipitation assay. Xenograft mouse model assay was used to reveal the effect of Brevilin A on tumor tumorigenesis in vivo. PAX5 and SOX4 expression were upregulated in PCa tissues and cells relative to normal prostate tissues and human prostate epithelial cells. Brevilin A treatment inhibited PAX5 protein expression in PCa cells. Additionally, Brevilin A inhibited proliferation, migration and invasion and induced apoptosis of PCa cells, whereas these effects were attenuated after PAX5 overexpression. SOX4 was transcriptionally activated by PAX5, and its introduction partially relieved the inhibitory effects of PAX5 knockdown on PCa cell malignancy. Moreover, Brevilin A delayed tumor formation in vivo. Brevilin A inhibited PCa progression by regulating SOX4 expression in a PAX5-dependent manner, providing a promising anti-tumor drug for PCa.
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Affiliation(s)
- Xinxiang Que
- Department of Urology, Xiantao First People's Hospital, No. 29, Mianzhou Avenue, Nancheng New District, Xiantao, 433000, Hubei, China
| | - Jianqun Fan
- Ultrasound Imaging Department, Xiantao First People's Hospital, Xiantao, 433000, Hubei, China
| | - Desheng Chen
- Department of Urology, Xiantao First People's Hospital, No. 29, Mianzhou Avenue, Nancheng New District, Xiantao, 433000, Hubei, China
| | - Zhen Nie
- Department of Urology, Xiantao First People's Hospital, No. 29, Mianzhou Avenue, Nancheng New District, Xiantao, 433000, Hubei, China
| | - Peng Chen
- Department of Urology, Xiantao First People's Hospital, No. 29, Mianzhou Avenue, Nancheng New District, Xiantao, 433000, Hubei, China.
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Su X, Fu C, Liu F, Bian R, Jing P. T-cell exhaustion prediction algorithm in tumor microenvironment for evaluating prognostic stratification and immunotherapy effect of esophageal cancer. ENVIRONMENTAL TOXICOLOGY 2024; 39:592-611. [PMID: 37493251 DOI: 10.1002/tox.23887] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Revised: 06/01/2023] [Accepted: 06/29/2023] [Indexed: 07/27/2023]
Abstract
Esophageal cancer (EC) is a common digestive malignancy that ranks sixth in cancer deaths, with a 5-year survival rate of 15%-25%. As a result, reliable prognostic biomarkers are required to accurately predict the prognosis of EC. T-cell exhaustion (TEX) is associated with poorer prognosis and immune infiltration in EC. In this study, nine risk genes were finally screened to constitute the prognostic model using least absolute shrinkage and selection operator analysis. Patients were divided into two groups based on the expression of the TEX-related genes: high-risk group and low-risk group. The expression of TEX-related genes differed significantly between the two groups. The findings revealed that the risk model developed was highly related to the clinical prognosis and amount of immune cell infiltration in EC patients. It was also significantly correlated with the therapeutic sensitivity of multiple chemotherapeutic agents in EC patients. Subsequently, we successfully constructed drug-resistant cell lines KYSE480/CDDP-R and KYSE180/CDDP-R to verify the correlation between PD-1 and drug resistance in EC. Then, we examined the mRNA and protein expression levels of PD-1 in parental and drug-resistant cells using qPCR and WB. It was found that the expression level of PD-1 was significantly increased in the plasma red of drug-resistant cells. Next, we knocked down PD-1 in drug-resistant cells and found that the resistance of EC cells to CDDP was significantly reduced. And the proportion of apoptotic cells in cells treated with 6 μM CDDP for 24 h was significantly in increase. The TEX-based risk model achieved good prediction results for prognosis prediction in EC patients. And it was also significantly associated with the level of immune cell infiltration and drug therapy sensitivity of EC patients. Additionally, the downregulation of PD-1 may be associated with increased drug sensitivity in EC and enhanced T-cell infiltration. The high-risk group had lower TIDE scores, indicating that the high-risk group benefits more after receiving immunotherapy. Thus, the TEX-based risk model can be used as a novel tumor prognostic biomarker.
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Affiliation(s)
- Xiangyu Su
- School of Medicine, Southeast University, Nanjing, China
- Department of Oncology, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Chenchun Fu
- Department of Oncology, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Fei Liu
- Department of Oncology, Luhe People's Hospital of Nanjing, Nanjing, China
| | - Rongrong Bian
- Department of Oncology, Luhe People's Hospital of Nanjing, Nanjing, China
| | - Ping Jing
- Department of Gastroenterology, Luhe People's Hospital of Nanjing, Nanjing, China
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Li T, Chen S, Zhang Y, Zhao Q, Ma K, Jiang X, Xiang R, Zhai F, Ling G. Ensemble learning-based gene signature and risk model for predicting prognosis of triple-negative breast cancer. Funct Integr Genomics 2023; 23:81. [PMID: 36917262 DOI: 10.1007/s10142-023-01009-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2023] [Revised: 02/27/2023] [Accepted: 03/03/2023] [Indexed: 03/15/2023]
Abstract
Although medical science has been fully developed, due to the high heterogeneity of triple-negative breast cancer (TNBC), it is still difficult to use reasonable and precise treatment. In this study, based on local optimization-feature screening and genomics screening strategy, we screened 25 feature genes. In multiple machine learning algorithms, feature genes have excellent discriminative diagnostic performance among samples composed of multiple large datasets. After screening at the single-cell level, we identified genes expressed substantially in myeloid cells (MCGs) that have a potential association with TNBC. Based on MCGs, we distinguished two types of TNBC patients who showed considerable differences in survival status and immune-related characteristics. Immune-related gene risk scores (IRGRS) were established, and their validity was verified using validation cohorts. A total of 25 feature genes were obtained, among which CXCL9, CXCL10, CCL7, SPHK1, and TREM1 were identified as the result after single-cell level analysis and screening. According to these entries, the cohort was divided into MCA and MCB subtypes, and the two subtypes had significant differences in survival status and tumor-immune microenvironment. After Lasso-Cox screening, IDO1, GNLY, IRF1, CTLA4, and CXCR6 were selected for constructing IRGRS. There were significant differences in drug sensitivity and immunotherapy sensitivity among high-IRGRS and low-IRGRS groups. We revealed the dynamic relationship between TNBC and TIME, identified a potential biomarker called Granulysin (GNLY) related to immunity, and developed a multi-process machine learning package called "MPMLearning 1.0" in Python.
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Affiliation(s)
- Tiancheng Li
- School of Pharmacy, Shenyang Pharmaceutical University, Shenyang, 110016, China
| | - Siqi Chen
- School of Medical Devices, Shenyang Pharmaceutical University, Shenyang, 110016, China
| | - Yuqi Zhang
- School of Medical Devices, Shenyang Pharmaceutical University, Shenyang, 110016, China
| | - Qianqian Zhao
- School of Life Sciences and Biopharmaceutical Science, Shenyang Pharmaceutical University, Shenyang, 110016, China
| | - Kai Ma
- School of Pharmacy, Shenyang Pharmaceutical University, Shenyang, 110016, China
| | - Xiwei Jiang
- School of Medical Devices, Shenyang Pharmaceutical University, Shenyang, 110016, China
| | - Rongwu Xiang
- School of Medical Devices, Shenyang Pharmaceutical University, Shenyang, 110016, China
- Liaoning Medical Big Data and Artificial Intelligence Engineering Technology Research Center, Shenyang, 110016, China
| | - Fei Zhai
- School of Medical Devices, Shenyang Pharmaceutical University, Shenyang, 110016, China.
| | - Guixia Ling
- School of Medical Devices, Shenyang Pharmaceutical University, Shenyang, 110016, China.
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Su X, Wang G, Zheng S, Ge C, Kong F, Wang C. Comprehensive Explorations of CCL28 in Lung Adenocarcinoma Immunotherapy and Experimental Validation. J Inflamm Res 2023; 16:1325-1342. [PMID: 37006812 PMCID: PMC10065022 DOI: 10.2147/jir.s399193] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Accepted: 03/17/2023] [Indexed: 03/29/2023] Open
Abstract
Background Chemokines have been reported to play an important role in cancer immunotherapy. This study aimed to explore the chemokines involved in lung cancer immunotherapy. Methods All the public data were downloaded from The Cancer Genome Atlas Program database. Quantitative real time-PCR was used to detect the mRNA level of specific molecules and Western blot was used for the protein level. Other experiments used include luciferase reporter experiments, flow cytometric analysis, Chromatin immunoprecipitation assay, ELISA and co-cultured system. Results We found that the CCL7, CCL11, CCL14, CCL24, CCL25, CCL26, CCL28 had a higher level, while the CCL17, CCL23 had a lower level in immunotherapy non-responders. Also, we found that immunotherapy non-responders had a higher level of CD56dim NK cells, NK cells, Th1 cells, Th2 cells and Treg, yet a lower level of iDC and Th17 cells. Biological enrichment analysis indicated that in the patients with high Treg infiltration, the pathways of pancreas beta cells, KRAS signaling, coagulation, WNT BETA catenin signaling, bile acid metabolism, interferon alpha response, hedgehog signaling, PI3K/AKT/mTOR signaling, apical surface, myogenesis were significantly enriched in. CCL7, CCL11, CCL26 and CCL28 were selected for further analysis. Compared with the patients with high CCL7, CCL11, CCL26 and CCL28 expression, the patients with low CCL7, CCL11, CCL26 and CCL28 expression had a better performance of immunotherapy response and this effect might partly be due to Treg cells. Furthermore, biological exploration and clinical correlation of CCL7, CCL11, CCL26 and CCL28 were conducted, Finally, CCL28 was selected for validation. Experiments showed that under the hypoxia condition, HIF-1α was upregulated, which can directly bind to the promoter region of CCL28 and lead to its higher level. Also, CCL28 secreted by lung cancer cells could induce Tregs infiltration. Conclusion Our study provides a novel insight focused on the chemokines in lung cancer immunotherapy. Also, CCL28 was identified as an underlying biomarker for lung cancer immunotherapy.
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Affiliation(s)
- Xiangyu Su
- School of Medicine, Southeast University, Nanjing, 210009, People’s Republic of China
- Department of Oncology, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, 210009, People’s Republic of China
| | - Guoqing Wang
- Department of Pathology, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, 210009, People’s Republic of China
| | - Shiya Zheng
- Department of Oncology, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, 210009, People’s Republic of China
| | - Chang Ge
- Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, 210028, People’s Republic of China
| | - Fei Kong
- Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, 210028, People’s Republic of China
| | - Cailian Wang
- School of Medicine, Southeast University, Nanjing, 210009, People’s Republic of China
- Department of Oncology, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, 210009, People’s Republic of China
- Correspondence: Cailian Wang, Email
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Identification of a Five Immune Term Signature for Prognosis and Therapy Options (Immunotherapy versus Targeted Therapy) for Patients with Hepatocellular Carcinoma. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 2023; 2023:8958962. [PMID: 36785674 PMCID: PMC9918845 DOI: 10.1155/2023/8958962] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Revised: 10/15/2022] [Accepted: 10/17/2022] [Indexed: 02/05/2023]
Abstract
Background Immune microenvironment implicated in liver cancer development. Nevertheless, previous studies have not fully investigated the immune microenvironment in liver cancer. Methods The open-access data used for analysis were obtained from The Cancer Genome Atlas (TCGA-LIHC) and the International Cancer Genome Consortium databases (ICGC-JP and ICGC-FR). R program was employed to analyze all the data statistically. Results First, the TCGA-LIHC, ICGC-FR, and ICGC-JP cohorts were selected for our analysis, which were merged into a combined cohort. Then, we quantified 53 immune terms in this combined cohort with large populations using the ssGSEA algorithm. Next, a prognostic approach was established based on five immune principles (CORE.SERUM.RESPONSE.UP, angiogenesis, CD8.T.cells, Th2.cells, and B.cells) was established, which showed great prognostic prediction efficiency. Clinical correlation analysis demonstrated that high-risk patients could reveal higher progressive clinical features. Next, to examine the inherent biological variations in high- and low-risk patients, pathway enrichment tests were conducted. DNA repair, E2F targets, G2M checkpoints, HEDGEHOG signaling, mTORC1 signaling, and MYC target were positively correlated with the risk score. Examination of genomic instability revealed that high-risk patients may exhibit a higher tumor mutation burden score. Meanwhile, the risk score showed a strong positive correlation with the tumor stemness index. In addition, the Tumor Immune Dysfunction and Exclusion outcome indicated that high-risk patients could be higher responsive to immunotherapy, whereas low-risk patients may be higher responsive to Erlotinib. Finally, six characteristic genes DEPDC1, DEPDC1B, NGFR, CALCRL, PRR11, and TRIP13 were identified for risk group prediction. Conclusions In summary, our study identified a signature as a useful tool to indicate prognosis and therapy options for liver cancer patients.
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Chen J, Jin H, Zhou H, Hei X, Liu K. Research into the characteristic molecules significantly affecting liver cancer immunotherapy. Front Immunol 2023; 14:1029427. [PMID: 36860864 PMCID: PMC9968832 DOI: 10.3389/fimmu.2023.1029427] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2022] [Accepted: 02/01/2023] [Indexed: 02/15/2023] Open
Abstract
Background The past decade has witnessed unprecedented scientific breakthroughs, including immunotherapy, which has great potential in clinical applications for liver cancer. Methods Public data were obtained from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases and analyzed with R software. Results The LASSO and SVM-RFE machine learning algorithms identified 16 differentially expressed genes (DEGs) related to immunotherapy, namely, GNG8, MYH1, CHRNA3, DPEP1, PRSS35, CKMT1B, CNKSR1, C14orf180, POU3F1, SAG, POU2AF1, IGFBPL1, CDCA7, ZNF492, ZDHHC22, and SFRP2. Moreover, a logistic model (CombinedScore) was established based on these DEGs, showing an excellent prediction performance for liver cancer immunotherapy. Patients with a low CombinedScore might respond better to immunotherapy. Gene Set Enrichment Analysis showed that many metabolism pathways were activated in patients with a high CombinedScore, including butanoate metabolism, bile acid metabolism, fatty acid metabolism, glycine serine and threonine metabolism, and propanoate metabolism. Our comprehensive analysis showed that the CombinedScore was negatively correlated with the levels of most tumor-infiltrating immune cells and the activities of key steps of cancer immunity cycles. Continually, the CombinedScore was negatively associated with the expression of most immune checkpoints and immunotherapy response-related pathways. Moreover, patients with a high and a low CombinedScore exhibited diverse genomic features. Furthermore, we found that CDCA7 was significantly correlated with patient survival. Further analysis showed that CDCA7 was positively associated with M0 macrophages and negatively associated with M2 macrophages, suggesting that CDCA7 could influence the progression of liver cancer cells by affecting macrophage polarization. Next, single-cell analysis showed that CDCA7 was mainly expressed in prolif T cells. Immunohistochemical results confirmed that the staining intensity of CDCA7 was prominently increased in the nucleus in primary liver cancer tissues compared to adjacent non-tumor tissues. Conclusions Our results provide novel insights into the DEGs and factors affecting liver cancer immunotherapy. Meanwhile, CDCA7 was identified as a potential therapeutic target in this patient population.
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Affiliation(s)
- Junhong Chen
- Department of Hepatobiliary and Pancreatic Surgery II, General Surgery Center, The First Hospital of Jilin University, Changchun, China
| | - Hengwei Jin
- Department of Hepatobiliary and Pancreatic Surgery II, General Surgery Center, The First Hospital of Jilin University, Changchun, China
| | - Hao Zhou
- Department of Hepatobiliary and Pancreatic Surgery II, General Surgery Center, The First Hospital of Jilin University, Changchun, China
| | - Xufei Hei
- Department of Hepatobiliary and Pancreatic Surgery II, General Surgery Center, The First Hospital of Jilin University, Changchun, China
| | - Kai Liu
- Department of Hepatobiliary and Pancreatic Surgery II, General Surgery Center, The First Hospital of Jilin University, Changchun, China
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Zhang Y, Li Y, Zuo Z, Li T, An Y, Zhang W. An epithelial-mesenchymal transition-related mRNA signature associated with the prognosis, immune infiltration and therapeutic response of colon adenocarcinoma. Pathol Oncol Res 2023; 29:1611016. [PMID: 36910014 PMCID: PMC9998511 DOI: 10.3389/pore.2023.1611016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Accepted: 02/14/2023] [Indexed: 03/14/2023]
Abstract
Background: Epithelial-mesenchymal transition (EMT) is closely associated with cancer cell metastasis. Colon adenocarcinoma (COAD) is one of the most common malignancies in the world, and its metastasis leading to poor prognosis remains a challenge for clinicians. The purpose of this study was to explore the prognostic value of EMT-related genes (EMTRGs) by bioinformatics analysis and to develop a new EMTRGs prognostic signature for COAD. Methods: The TCGA-COAD dataset was downloaded from the TCGA portal as the training cohort, and the GSE17538 and GSE29621 datasets were obtained from the GEO database as the validation cohort. The best EMTRGs prognostic signature was constructed by differential expression analysis, Cox, and LASSO regression analysis. Gene set enrichment analysis (GSEA) is used to reveal pathways that are enriched in high-risk and low-risk groups. Differences in tumor immune cell levels were analyzed using microenvironmental cell population counter and single sample gene set enrichment analysis. Subclass mapping analysis and Genomics of Drug Sensitivity in Cancer were applied for prediction of immunotherapy response and chemotherapy response, respectively. Results: A total of 77 differentially expressed EMTRGs were identified in the TCGA-COAD cohort, and they were significantly associated with functions and pathways related to cancer cell metastasis, proliferation, and apoptosis. We constructed EMTRGs prognostic signature with COMP, MYL9, PCOLCE2, SCG2, and TIMP1 as new COAD prognostic biomarkers. The high-risk group had a poorer prognosis with enhanced immune cell infiltration. The GSEA demonstrated that the high-risk group was involved in "ECM Receptor Interaction," "WNT Signaling Pathway" and "Colorectal Cancer." Furthermore, patients with high risk scores may respond to anti-CTLA4 therapy and may be more resistant to targeted therapy agents BI 2536 and ABT-888. Conclusion: Together, we developed a new EMTRGs prognostic signature that can be an independent prognostic factor for COAD. This study has guiding implications for individualized counseling and treatment of COAD patients.
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Affiliation(s)
- Yu Zhang
- Department of Gastroenterology, The First People's Hospital of Yunnan Province, Affiliated Hospital of Kunming University of Science and Technology, Kunming, China.,Yunnan Digestive Endoscopy Clinical Medical Center, Kunming, China
| | - Yan Li
- Department of Gastroenterology, The First People's Hospital of Yunnan Province, Affiliated Hospital of Kunming University of Science and Technology, Kunming, China.,Yunnan Digestive Endoscopy Clinical Medical Center, Kunming, China
| | - Zan Zuo
- Department of Gastroenterology, The First People's Hospital of Yunnan Province, Affiliated Hospital of Kunming University of Science and Technology, Kunming, China.,Yunnan Digestive Endoscopy Clinical Medical Center, Kunming, China
| | - Ting Li
- Department of Gastroenterology, The First People's Hospital of Yunnan Province, Affiliated Hospital of Kunming University of Science and Technology, Kunming, China.,Yunnan Digestive Endoscopy Clinical Medical Center, Kunming, China
| | - Ying An
- Department of Gastroenterology, The First People's Hospital of Yunnan Province, Affiliated Hospital of Kunming University of Science and Technology, Kunming, China.,Yunnan Digestive Endoscopy Clinical Medical Center, Kunming, China
| | - Wenjing Zhang
- Faculty of Medicine, Kunming University of Science and Technology, Kunming, China.,Department of Medical Oncology, The First People's Hospital of Yunnan Province, Affiliated Hospital of Kunming University of Science and Technology, Kunming, China
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Comprehensive Analysis Based on the Cancer Immunotherapy and Immune Activation of Gastric Cancer Patients. Genet Res (Camb) 2023; 2023:4674536. [PMID: 36923953 PMCID: PMC10010888 DOI: 10.1155/2023/4674536] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Revised: 01/12/2023] [Accepted: 01/17/2023] [Indexed: 03/08/2023] Open
Abstract
When it comes to aggressiveness and prognosis, immune cells play an important role in the microenvironment of gastric cancer (GC). Currently, there is no well-established evidence that immune status typing is reliable as a prognostic tool for gastric cancer. This study aimed to develop a genetic signature based on immune status typing for the stratification of gastric cancer risk. TCGA data were used for gene expression and clinical characteristics analysis. A ssGSEA algorithm was applied to type the gastric cancer cohorts. A multivariate and univariate Cox regression and a lasso regression were conducted to determine which genes are associated with gastric cancer prognosis. Finally, we were able to produce a 6-gene prognostic prediction model using immune-related genes. Further analysis revealed that the prognostic prediction model is closely related to the prognosis of patients with GC. Nomograms incorporating genetic signatures and risk factors produced better calibration results. The relationship between the risk score and gastric cancer T stage was also significantly correlated with multiple immune markers related to specific immune cell subsets. According to these results, patients' outcomes and tumor immune cell infiltration correlate with risk scores. In addition, immune cellular-based genetic signatures can contribute to improved risk stratification for gastric cancer. Clinical decisions regarding immunotherapy and followup can be guided by these features.
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Wang T, Jian W, Xue W, Meng Y, Xia Z, Li Q, Xu S, Dong Y, Mao A, Zhang C. Integration analysis identifies MYBL1 as a novel immunotherapy biomarker affecting the immune microenvironment in clear cell renal cell carcinoma: Evidence based on machine learning and experiments. Front Immunol 2022; 13:1080403. [PMID: 36591240 PMCID: PMC9794576 DOI: 10.3389/fimmu.2022.1080403] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Accepted: 11/30/2022] [Indexed: 12/23/2022] Open
Abstract
Background Previous studies have identified MYBL1 as a cancer-promoting molecule in numerous types of cancer. Nevertheless, the role of MYBL in renal cancer remains unclear. Methods Genomic and clinical data of clear cell renal cell carcinoma (ccRCC) was get from the Cancer Genome Atlas (TCGA) database. CCK8, colony formation, and 5-ethynyl-2'-deoxyuridine assay were utilized to evaluate the performance of cell proliferation. Cell apoptosis was detected using the flow cytometric analysis. The protein level of MYBL1 in different tissues was evaluated using immunohistochemistry. A machine learning algorithm was utilized to identify the prognosis signature based on MYBL1-derived molecules. Results Here, we comprehensively investigated the role of MYBL1 in ccRCC. Here, we noticed a higher level of MYBL1 in ccRCC patients in both RNA and protein levels. Further analysis showed that MYBL1 was correlated with progressive clinical characteristics and worse prognosis performance. Biological enrichment analysis showed that MYBL1 can activate multiple oncogenic pathways in ccRCC. Moreover, we found that MYBL1 can remodel the immune microenvironment of ccRCC and affect the immunotherapy response. In vitro and in vivo assays indicated that MYBL1 was upregulated in ccRCC cells and can promote cellular malignant behaviors of ccRCC. Ultimately, an machine learning algorithm - LASSO logistics regression was utilized to identify a prognosis signature based on the MYBL1-derived molecules, which showed satisfactory prediction ability on patient prognosis in both training and validation cohorts. Conclusions Our result indicated that MYBL1 is a novel biomarker of ccRCC, which can remodel the tumor microenvironment, affect immunotherapy response and guide precision medicine in ccRCC.
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Affiliation(s)
- Tengda Wang
- Urology Surgery Department, The First Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Wengang Jian
- Urology Surgery Department, The First Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Wei Xue
- Urology Surgery Department, The First Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Yuyang Meng
- Urology Surgery Department, The First Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Zhinan Xia
- Urology Surgery Department, The First Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Qinchen Li
- The Fourth Affiliated Hospital, International Institutes of Medicine, Zhejiang University School of Medicine, Yiwu, Zhejiang, China
| | - Shenhao Xu
- The Fourth Affiliated Hospital, International Institutes of Medicine, Zhejiang University School of Medicine, Yiwu, Zhejiang, China
| | - Yu Dong
- The Fourth Affiliated Hospital, International Institutes of Medicine, Zhejiang University School of Medicine, Yiwu, Zhejiang, China
| | - Anli Mao
- The Fourth Affiliated Hospital, International Institutes of Medicine, Zhejiang University School of Medicine, Yiwu, Zhejiang, China
| | - Cheng Zhang
- Urology Surgery Department, The First Affiliated Hospital of Harbin Medical University, Harbin, China,The Fourth Affiliated Hospital, International Institutes of Medicine, Zhejiang University School of Medicine, Yiwu, Zhejiang, China,*Correspondence: Cheng Zhang,
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11
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Wang Q, Zhang X, Du K, Wu X, Zhou Y, Chen D, Zeng L. Machine learning identifies characteristics molecules of cancer associated fibroblasts significantly correlated with the prognosis, immunotherapy response and immune microenvironment in lung adenocarcinoma. Front Oncol 2022; 12:1059253. [PMID: 36439484 PMCID: PMC9682016 DOI: 10.3389/fonc.2022.1059253] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2022] [Accepted: 10/24/2022] [Indexed: 09/21/2023] Open
Abstract
BACKGROUND Lung adenocarcinoma (LUAD) is a highly lethal disease with a dramatic pro-fibrocytic response. Cancer-associated fibroblasts (CAFs) have been reported to play a key role in lung adenocarcinoma. METHODS Marker genes of CAFs were obtained from the Cell Marker website. Single sample gene set enrichment analysis (ssGSEA) was used for CAFs quantification. R and GraphPad Prism software were utilized for all analysis. Quantitative real-time PCR (qRT-PCR) was utilized to detect the RNA level of specific molecules. RESULTS Based on the ssGSEA algorithm and obtained CAFs markers, the LUAD patients with low- and high-CAFs infiltration were successfully identified, which had different response patterns to immunotherapy. Through the machine learning algorithm - LASSO logistic regression, we identified 44 characteristic molecules of CAFs. Furthermore, a prognosis signature consisting of seven characteristic genes was established, which showed great prognosis prediction ability. Additionally, we found that patients in the low-risk group might have better outcomes when receiving immunotherapy of PD-1, but not CTLA4. Also, the biological enrichment analysis revealed that immune response-related pathways were significantly associated with CAFs infiltration. Meanwhile, we investigated the underlying biological and microenvironment difference in patients with high- and low-risk groups. Finally, we identified that AMPD1 might be a novel target for LUAD immunotherapy. Patients with a high level of AMPD1 were correlated with worse responses to immunotherapy. Moreover, immunohistochemistry showed that the protein level of AMPD1 was higher in lung cancer. Results of qRT-PCR demonstrated that AMPD1 was upregulated in A549 cells compared with BEAS-2B. Meanwhile, we found that the knockdown of AMPD4 can significantly reduce the expression of CTLA4 and PDCD1, but not CD274 and PDCD1LG2. CONCLUSION We comprehensively explored the role of CAFs and its characteristics molecules in LUAD immunotherapy and developed an effective signature to indicate patients prognosis and immunotherapy response. Moreover, AMPD1 was identified as a novel target for lung cancer immunotherapy.
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Affiliation(s)
- Qian Wang
- Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China
| | - Xunlang Zhang
- Department of Geriatric, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China
| | - Kangming Du
- Department of Vascular Surgery, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China
| | - Xinhui Wu
- Department of Geriatric, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China
| | - Yexin Zhou
- Guangxi University of Chinese Medicine, Nanning, China
| | - Diang Chen
- Department of Urology Surgery, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China
| | - Lin Zeng
- Department of Neurosurgery, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China
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12
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Wang J, He X, Bai Y, Du G, Cai M. Identification and validation of novel biomarkers affecting bladder cancer immunotherapy via machine learning and its association with M2 macrophages. Front Immunol 2022; 13:1051063. [PMID: 36439109 PMCID: PMC9681792 DOI: 10.3389/fimmu.2022.1051063] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Accepted: 10/17/2022] [Indexed: 09/22/2023] Open
Abstract
BACKGROUND Immunotherapy has shown promising results in bladder cancer therapy options. METHODS Analysis of open-access data was conducted using the R software. Open-access data were obtained from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and IMvigor210 databases. Immunofluorescence and co-culture systems were utilized to validate the effect of PTHLH on M2 macrophage polarization. RESULTS Here, through the combined (TCGA, GSE128959, GSE13507, and GSE83586) and IMvigor210 cohorts, we comprehensively investigated the biological and immune microenvironment differences in patients with diverse immunotherapy responses. Meanwhile, we found that M2 macrophage could affect bladder cancer immunotherapy sensibility. Moreover, based on the machine learning algorithm (LASSO logistics regression), PTHLH, BHMT2, and NGFR were identified, which all have good prediction abilities for patient immunotherapy. Then, a logistics regression model was established based on PTHLH, BHMT2, and NGFR, and each patient was assigned a logistics score. Subsequently, we investigated the difference in patients with high low logistics scores, including biological enrichment, immune microenvironment, and genomic characteristics. Meanwhile, data from the Human Protein Atlas database indicated a higher protein level of PTHLH in bladder cancer tissue. Immunofluorescence indicated that the knockdown of PTHLH in bladder cancer cells can significantly inhibit the M2 polarization of co-culture M0 macrophages. CONCLUSIONS Our study investigated the difference between bladder cancer immunotherapy responders and non-responders. Meanwhile, the PTHLH was identified as a novel biomarker for bladder cancer immunotherapy.
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Affiliation(s)
- Junkang Wang
- Department of Outpatient, Sichuan Academy of Medical Sciences and Sichuan Provincial People’s Hospital, Chengdu, Sichuan, China
| | - Xiaojuan He
- Department of Outpatient, Sichuan Academy of Medical Sciences and Sichuan Provincial People’s Hospital, Chengdu, Sichuan, China
| | - Yifeng Bai
- Department of Cancer Center, Sichuan Academy of Medical Sciences and Sichuan People’s Hospital, Chengdu, Sichuan, China
| | - Guanghui Du
- Department of Outpatient, Sichuan Academy of Medical Sciences and Sichuan Provincial People’s Hospital, Chengdu, Sichuan, China
| | - Minhong Cai
- Healthcare-associated Infection Management Office, Sichuan Academy of Medical Sciences and Sichuan People’s Hospital, Chengdu, Sichuan, China
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13
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Identification of Glucose Metabolism-Related Genes in the Progression from Nonalcoholic Fatty Liver Disease to Hepatocellular Carcinoma. Genet Res (Camb) 2022; 2022:8566342. [PMID: 36407083 PMCID: PMC9649330 DOI: 10.1155/2022/8566342] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Accepted: 10/10/2022] [Indexed: 11/05/2022] Open
Abstract
Nonalcoholic fatty liver disease (NAFLD) is a manifestation of hepatic metabolic syndrome that varies in severity. Hepatocellular carcinoma progresses from NAFLD when there is heterogeneity in the infiltration of immune cells and molecules. A precise molecular classification of NAFLD remains lacking, allowing further exploration of the link between NAFLD and hepatocellular carcinoma. In this work, a weighted gene coexpression network analysis was used to identify two coexpression modules based on multiple omics data used to differentiate NAFLD subtypes. Additionally, key genes in the process of glucose metabolism and NAFLD were used to construct a prognostic model in a cohort of patients with hepatocellular carcinoma. Furthermore, the specific expression of signature genes in hepatocellular carcinoma cells was analyzed using a single-cell RNA sequencing approach. A total of 19 liver tissues of NAFLD patients were obtained from the GEO database, and 81 glucose metabolism-related genes were downloaded from the CTD database. In addition, based on nine signature genes, we constructed a prognostic model to divide the HCC cohort into high and low-risk groups. We also demonstrated a significant correlation between prognostic models and clinical phenotypes. Furthermore, we integrated single-cell RNA-sequencing data and immunology data to assess potential relationships between different molecular subtypes and hepatocellular carcinoma. Finally, our study discovered that the glucose metabolism pathway may play an important role in the process of NAFLD-hepatocellular carcinoma. In addition, three glucose metabolism-related genes (SERPINE1, VCAN, and TFPI2) may be the potential targets for the immunotherapy of patients with NAFLD-hepatocellular carcinoma.
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14
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Zhan X, Feng S, Zhou X, Liao W, Zhao B, Yang Q, Tan Q, Shen J. Immunotherapy response and microenvironment provide biomarkers of immunotherapy options for patients with lung adenocarcinoma. Front Genet 2022; 13:1047435. [PMID: 36386793 PMCID: PMC9640754 DOI: 10.3389/fgene.2022.1047435] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2022] [Accepted: 10/17/2022] [Indexed: 11/30/2022] Open
Abstract
Background: Immunotherapy has been a promising approach option for lung cancer. Method: All the open-accessed data was obtained from the Cancer Genome Atlas (TCGA) database. All the analysis was conducted using the R software analysis. Results: Firstly, the genes differentially expressed in lung cancer immunotherapy responders and non-responders were identified. Then, the lung adenocarcinoma immunotherapy-related genes were determined by LASSO logistic regression and SVM-RFE, respectively. A total of 18 immunotherapy response-related genes were included in our investigation. Subsequently, we constructed the logistics score model. Patients with high logistics score had a better clinical effect on immunotherapy, with 63.2% of patients responding to immunotherapy, while only 12.1% of patients in the low logistics score group responded to immunotherapy. Moreover, we found that pathways related to immunotherapy were mainly enriched in metabolic pathways such as fatty acid metabolism, bile acid metabolism, oxidative phosphorylation, and carcinogenic pathways such as KRAS signaling. Logistics score was positively correlated with NK cells activated, Mast cells resting, Monocytes, Macrophages M2, dendritic cells resting, dendritic cells activated and eosinophils, while was negatively related to Tregs, macrophages M0, macrophages M1, and mast cells activated. In addition, ERVH48-1 was screened for single-cell exploration. The expression of ERVH48-1 increased in patients with distant metastasis, and ERVH48-1 was associated with pathways such as pancreas beta cells, spermatogenesis, G2M checkpoints and KRAS signaling. The result of quantitative real-time PCR showed that ERVH48-1 was upregulated in lung cancer cells. Conclusion: Our study developed an effective signature to predict the immunotherapy response of lung cancer patients.
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Affiliation(s)
- Xue Zhan
- Chongqing Key Laboratory of Traditional Chinese Medicine for Prevention and Cure of Metabolic Diseases, College of Traditional Chinese Medicine, Chongqing Medical University, Chongqing, China
| | - Shihan Feng
- Chongqing Key Laboratory of Traditional Chinese Medicine for Prevention and Cure of Metabolic Diseases, College of Traditional Chinese Medicine, Chongqing Medical University, Chongqing, China
| | - Xutao Zhou
- Department of Oncology, Jiulongpo Hospital of Traditional Chinese Medicine, Chongqing, China
| | - Wei Liao
- Department of Oncology, Jiulongpo Hospital of Traditional Chinese Medicine, Chongqing, China
| | - Bin Zhao
- Department of Oncology, Chongqing Hospital of Traditional Chinese Medicine, Chongqing, China
| | - Qian Yang
- Chongqing Key Laboratory of Traditional Chinese Medicine for Prevention and Cure of Metabolic Diseases, College of Traditional Chinese Medicine, Chongqing Medical University, Chongqing, China
| | - Qi Tan
- Chongqing Key Laboratory of Traditional Chinese Medicine for Prevention and Cure of Metabolic Diseases, College of Traditional Chinese Medicine, Chongqing Medical University, Chongqing, China
| | - Jian Shen
- Chongqing Key Laboratory of Traditional Chinese Medicine for Prevention and Cure of Metabolic Diseases, College of Traditional Chinese Medicine, Chongqing Medical University, Chongqing, China
- *Correspondence: Jian Shen,
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15
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Establishment and Validation of a Machine Learning Prediction Model Based on Big Data for Predicting the Risk of Bone Metastasis in Renal Cell Carcinoma Patients. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 2022; 2022:5676570. [PMID: 36226243 PMCID: PMC9550489 DOI: 10.1155/2022/5676570] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Accepted: 07/28/2022] [Indexed: 11/23/2022]
Abstract
Purpose Since the prognosis of renal cell carcinoma (RCC) patients with bone metastasis (BM) is poor, this study is aimed at using big data to build a machine learning (ML) model to predict the risk of BM in RCC patients. Methods A retrospective study was conducted on 40,355 RCC patients in the SEER database from 2010 to 2017. LASSO regression and multivariate logistic regression analysis was performed to determine independent risk factors of RCC-BM. Six ML algorithm models, including LR, GBM, XGB, RF, DT, and NBC, were used to establish risk models for predicting RCC-BM. The prediction performance of ML models was weighed by 10-fold cross-validation. Results The study investigated 40,355 patients diagnosed with RCC in the SEER database, where 1,811 (4.5%) were BM patients. Independent risk factors for BM were tumor grade, T stage, N stage, liver metastasis, lung metastasis, and brain metastasis. Among the RCC-BM risk prediction models established by six ML algorithms, the XGB model showed the best prediction performance (AUC = 0.891). Therefore, a network calculator based on the XGB model was established to individually assess the risk of BM in patients with RCC. Conclusion The XGB risk prediction model based on the ML algorithm performed a good prediction effect on BM in RCC patients.
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16
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Chen J, Chen S, Dai X, Ma L, Chen Y, Bian W, Sun Y. Exploration of the underlying biological differences and targets in ovarian cancer patients with diverse immunotherapy response. Front Immunol 2022; 13:1007326. [PMID: 36189254 PMCID: PMC9521167 DOI: 10.3389/fimmu.2022.1007326] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2022] [Accepted: 08/16/2022] [Indexed: 11/30/2022] Open
Abstract
Background Preclinical trials of immunotherapy in ovarian cancer (OC) have shown promising results. This makes it meaningful to prospectively examine the biological mechanisms explaining the differences in response performances to immunotherapy among OC patients. Methods Open-accessed data was obtained from the Cancer Genome Atlas and Gene Expression Omnibus database. All the analysis was conducted using the R software. Results We firstly performed the TIDE analysis to evaluate the immunotherapy response rate of OC patients. The machine learning algorithm LASSO logistic regression and SVM-RFE were used to identify the characteristic genes. The genes DPT, RUNX1T1, PTPRN, LSAMP, FDCSP and COL6A6 were selected for molecular typing. Our result showed that the patients in Cluster1 might have a better prognosis and might be more sensitive to immunotherapy, including PD-1 and CTLA4 therapy options. Pathway enrichment analysis showed that in Cluster2, the pathway of EMT, TNFα/NF-kB signaling, IL2/STAT5 signaling, inflammatory response, KRAS signaling, apical junction, complement, interferon-gamma response and allograft rejection were significantly activated. Also, genomic instability analysis was performed to identify the underlying genomic difference between the different Cluster patients. Single-cell analysis showed that the DPT, COL6A6, LSAMP and RUNX1T1 were mainly expressed in the fibroblasts. We then quantified the CAFs infiltration in the OC samples. The result showed that patients with low CAFs infiltration might have a lower TIDE score and a higher proportion of immunotherapy responders. Also, we found all the characteristic genes DPT, RUNX1T1, PTPRN, LSAMP, FDCSP and COL6A6 were upregulated in the patients with high CAFs infiltration. Immune infiltration analysis showed that the patients in Cluster2 might have a higher infiltration of naive B cells, activated NK cells and resting Dendritic cells. Conclusions In summary, our study provides new insights into ovarian cancer immunotherapy. Meanwhile, specific targets DPT, RUNX1T1, PTPRN, LSAMP, FDCSP, COL6A6 and CAFs were identified for OC immunotherapy.
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Affiliation(s)
- Jinjin Chen
- Oncology Department, The First People’s Hospital of Yancheng City, The Yancheng Clinical College of Xuzhou Medical University, Yancheng, China
| | - Surong Chen
- Oncology Department, The First People’s Hospital of Yancheng City, The Yancheng Clinical College of Xuzhou Medical University, Yancheng, China
| | - Xichao Dai
- Oncology Department, The First People’s Hospital of Yancheng City, The Yancheng Clinical College of Xuzhou Medical University, Yancheng, China
| | - Liang Ma
- Oncology Department, The First People’s Hospital of Yancheng City, The Yancheng Clinical College of Xuzhou Medical University, Yancheng, China
| | - Yu Chen
- Oncology Department, The First People’s Hospital of Yancheng City, The Yancheng Clinical College of Xuzhou Medical University, Yancheng, China
| | - Weigang Bian
- Oncology Department, The First People’s Hospital of Yancheng City, The Yancheng Clinical College of Xuzhou Medical University, Yancheng, China
- *Correspondence: Weigang Bian, ; Yunhao Sun,
| | - Yunhao Sun
- Department of Thoracic Surgery, The First People’s Hospital of Yancheng City, The Yancheng Clinical College of Xuzhou Medical University, Yancheng, China
- *Correspondence: Weigang Bian, ; Yunhao Sun,
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17
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Mejía-Hernández JO, Keam SP, Saleh R, Muntz F, Fox SB, Byrne D, Kogan A, Pang L, Huynh J, Litchfield C, Caramia F, Lozano G, He H, You JM, Sandhu S, Williams SG, Haupt Y, Haupt S. Modelling aggressive prostate cancers of young men in immune-competent mice, driven by isogenic Trp53 alterations and Pten loss. Cell Death Dis 2022; 13:777. [PMID: 36075907 PMCID: PMC9465983 DOI: 10.1038/s41419-022-05211-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Revised: 08/18/2022] [Accepted: 08/23/2022] [Indexed: 01/21/2023]
Abstract
Understanding prostate cancer onset and progression in order to rationally treat this disease has been critically limited by a dire lack of relevant pre-clinical animal models. We have generated a set of genetically engineered mice that mimic human prostate cancer, initiated from the gland epithelia. We chose driver gene mutations that are specifically relevant to cancers of young men, where aggressive disease poses accentuated survival risks. An outstanding advantage of our models are their intact repertoires of immune cells. These mice provide invaluable insight into the importance of immune responses in prostate cancer and offer scope for studying treatments, including immunotherapies. Our prostate cancer models strongly support the role of tumour suppressor p53 in functioning to critically restrain the emergence of cancer pathways that drive cell cycle progression; alter metabolism and vasculature to fuel tumour growth; and mediate epithelial to mesenchymal-transition, as vital to invasion. Importantly, we also discovered that the type of p53 alteration dictates the specific immune cell profiles most significantly disrupted, in a temporal manner, with ramifications for disease progression. These new orthotopic mouse models demonstrate that each of the isogenic hotspot p53 amino acid mutations studied (R172H and R245W, the mouse equivalents of human R175H and R248W respectively), drive unique cellular changes affecting pathways of proliferation and immunity. Our findings support the hypothesis that individual p53 mutations confer their own particular oncogenic gain of function in prostate cancer.
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Affiliation(s)
- Javier Octavio Mejía-Hernández
- grid.1055.10000000403978434Peter MacCallum Cancer Centre, 305 Grattan St, Melbourne, VIC 3000 Australia ,grid.1008.90000 0001 2179 088XSir Peter MacCallum Department of Oncology, The University of Melbourne, Parkville, VIC 3010 Australia ,grid.1055.10000000403978434Tumour Suppression and Cancer Sex Disparity Laboratory, Peter MacCallum Cancer Centre, 305 Grattan St, Melbourne, VIC 3000 Australia ,Present Address: Telix Pharmaceuticals Ltd, Melbourne, VIC 3051 Australia
| | - Simon P. Keam
- grid.1055.10000000403978434Peter MacCallum Cancer Centre, 305 Grattan St, Melbourne, VIC 3000 Australia ,grid.1008.90000 0001 2179 088XSir Peter MacCallum Department of Oncology, The University of Melbourne, Parkville, VIC 3010 Australia ,grid.1055.10000000403978434Tumour Suppression and Cancer Sex Disparity Laboratory, Peter MacCallum Cancer Centre, 305 Grattan St, Melbourne, VIC 3000 Australia ,grid.1135.60000 0001 1512 2287Present Address: CSL Innovation, CSL Ltd, Melbourne, VIC 3052 Australia
| | - Reem Saleh
- grid.1055.10000000403978434Peter MacCallum Cancer Centre, 305 Grattan St, Melbourne, VIC 3000 Australia ,grid.1008.90000 0001 2179 088XSir Peter MacCallum Department of Oncology, The University of Melbourne, Parkville, VIC 3010 Australia ,grid.1055.10000000403978434Tumour Suppression and Cancer Sex Disparity Laboratory, Peter MacCallum Cancer Centre, 305 Grattan St, Melbourne, VIC 3000 Australia
| | - Fenella Muntz
- grid.1055.10000000403978434Peter MacCallum Cancer Centre, 305 Grattan St, Melbourne, VIC 3000 Australia
| | - Stephen B. Fox
- grid.1055.10000000403978434Peter MacCallum Cancer Centre, 305 Grattan St, Melbourne, VIC 3000 Australia ,grid.1008.90000 0001 2179 088XSir Peter MacCallum Department of Oncology, The University of Melbourne, Parkville, VIC 3010 Australia ,grid.1055.10000000403978434Pathology Department, Peter MacCallum Cancer Centre, 305 Grattan St, Melbourne, VIC 3000 Australia
| | - David Byrne
- grid.1055.10000000403978434Peter MacCallum Cancer Centre, 305 Grattan St, Melbourne, VIC 3000 Australia ,grid.1055.10000000403978434Pathology Department, Peter MacCallum Cancer Centre, 305 Grattan St, Melbourne, VIC 3000 Australia
| | - Arielle Kogan
- grid.1055.10000000403978434Peter MacCallum Cancer Centre, 305 Grattan St, Melbourne, VIC 3000 Australia ,grid.1008.90000 0001 2179 088XSir Peter MacCallum Department of Oncology, The University of Melbourne, Parkville, VIC 3010 Australia ,grid.1055.10000000403978434Tumour Suppression and Cancer Sex Disparity Laboratory, Peter MacCallum Cancer Centre, 305 Grattan St, Melbourne, VIC 3000 Australia
| | - Lokman Pang
- grid.1018.80000 0001 2342 0938Olivia Newton-John Cancer Research Institute, School of Cancer Medicine, La Trobe University, Heidelberg, VIC 3084 Australia
| | - Jennifer Huynh
- grid.1018.80000 0001 2342 0938Olivia Newton-John Cancer Research Institute, School of Cancer Medicine, La Trobe University, Heidelberg, VIC 3084 Australia
| | - Cassandra Litchfield
- grid.1055.10000000403978434Peter MacCallum Cancer Centre, 305 Grattan St, Melbourne, VIC 3000 Australia ,grid.1008.90000 0001 2179 088XSir Peter MacCallum Department of Oncology, The University of Melbourne, Parkville, VIC 3010 Australia ,grid.1055.10000000403978434Tumour Suppression and Cancer Sex Disparity Laboratory, Peter MacCallum Cancer Centre, 305 Grattan St, Melbourne, VIC 3000 Australia
| | - Franco Caramia
- grid.1055.10000000403978434Peter MacCallum Cancer Centre, 305 Grattan St, Melbourne, VIC 3000 Australia ,grid.1008.90000 0001 2179 088XSir Peter MacCallum Department of Oncology, The University of Melbourne, Parkville, VIC 3010 Australia ,grid.1055.10000000403978434Tumour Suppression and Cancer Sex Disparity Laboratory, Peter MacCallum Cancer Centre, 305 Grattan St, Melbourne, VIC 3000 Australia
| | - Guillermina Lozano
- grid.240145.60000 0001 2291 4776Department of Genetics, The University of Texas MD Anderson Cancer Center, Houston, TX USA ,grid.267308.80000 0000 9206 2401University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, University of Texas, Houston, TX USA
| | - Hua He
- grid.240145.60000 0001 2291 4776Department of Hematopathology, UT MD Anderson Cancer Center, Houston, TX USA
| | - James M. You
- grid.267308.80000 0000 9206 2401University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, University of Texas, Houston, TX USA ,grid.240145.60000 0001 2291 4776Department of Hematopathology, UT MD Anderson Cancer Center, Houston, TX USA
| | - Shahneen Sandhu
- grid.1055.10000000403978434Peter MacCallum Cancer Centre, 305 Grattan St, Melbourne, VIC 3000 Australia ,grid.1008.90000 0001 2179 088XSir Peter MacCallum Department of Oncology, The University of Melbourne, Parkville, VIC 3010 Australia ,grid.1055.10000000403978434Department of Medical Oncology, Peter MacCallum Cancer Centre, Parkville, VIC 3000 Australia
| | - Scott G. Williams
- grid.1055.10000000403978434Peter MacCallum Cancer Centre, 305 Grattan St, Melbourne, VIC 3000 Australia ,grid.1008.90000 0001 2179 088XSir Peter MacCallum Department of Oncology, The University of Melbourne, Parkville, VIC 3010 Australia ,grid.1055.10000000403978434Division of Radiation Oncology, Peter MacCallum Cancer Centre, 305 Grattan St, Melbourne, VIC 3000 Australia
| | - Ygal Haupt
- grid.1055.10000000403978434Peter MacCallum Cancer Centre, 305 Grattan St, Melbourne, VIC 3000 Australia ,grid.1008.90000 0001 2179 088XSir Peter MacCallum Department of Oncology, The University of Melbourne, Parkville, VIC 3010 Australia ,grid.1055.10000000403978434Tumour Suppression and Cancer Sex Disparity Laboratory, Peter MacCallum Cancer Centre, 305 Grattan St, Melbourne, VIC 3000 Australia ,Present Address: Vittail Ltd, Melbourne, VIC 3146 Australia
| | - Sue Haupt
- grid.1055.10000000403978434Peter MacCallum Cancer Centre, 305 Grattan St, Melbourne, VIC 3000 Australia ,grid.1008.90000 0001 2179 088XSir Peter MacCallum Department of Oncology, The University of Melbourne, Parkville, VIC 3010 Australia ,grid.1055.10000000403978434Tumour Suppression and Cancer Sex Disparity Laboratory, Peter MacCallum Cancer Centre, 305 Grattan St, Melbourne, VIC 3000 Australia
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Liang S, Fang K, Li S, Liu D, Yi Q. Immune Microenvironment Terms Signature Robustly Predicts the Prognosis and Immunotherapy Response in Bladder Cancer Based on Large Population Cohorts. Front Genet 2022; 13:872441. [PMID: 35615381 PMCID: PMC9126043 DOI: 10.3389/fgene.2022.872441] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2022] [Accepted: 03/28/2022] [Indexed: 11/18/2022] Open
Abstract
Immune microenvironment is implicated in cancer progression. However, the role of immune microenvironment in bladder cancer has not been fully explored. Open-accessed datasets GSE120736, GSE128959, GSE13507, GSE31684, GSE32548, GSE48075, GSE83586, and The Cancer Genome Atlas (TCGA) database were enrolled in our study. Single-sample gene set enrichment analysis (ssGSEA) was used to quantify 53 immune terms in combined BLCA cohorts. The top 10 important immune terms were identified through random forest algorithm for model establishment. Our model showed satisfactory efficacy in prognosis prediction. Furthermore, we explored clinical and genomic feature differences between high- and low-risk groups. The results indicated that the patients in the high-risk group might be associated with worse clinical features. Gene set enrichment analysis showed that epithelial–mesenchymal translational, mTORC1 signaling, mitotic spindle, glycolysis, E2F target, and G2M checkpoint pathways were aberrantly activated in high-risk patients, partially explaining its worse prognosis. Patients in the low-risk group showed better immunotherapy response according to TIDE and TCIA analysis, indicating that our model could effectively predict the immunotherapy response rate. KCNH4, UGT1A1, TPO, SHANK1, PITX3, MYH1, MYH13, KRT3, DEC1, and OBP2A genes were identified as feature genes in the high- and low-risk patients. CMAP analysis was performed to identify potential compounds targeting the riskscore.
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Affiliation(s)
- Shengjie Liang
- Department of Urology, Shanghai Pudong Hospital, Fudan University Pudong Medical Center, Shanghai, China
| | - Kai Fang
- Department of Urology, Shanghai Pudong Hospital, Fudan University Pudong Medical Center, Shanghai, China
| | - Simin Li
- Department of Urology, Shanghai Pudong Hospital, Fudan University Pudong Medical Center, Shanghai, China
| | - Dong Liu
- Department of Urology, Shanghai Pudong Hospital, Fudan University Pudong Medical Center, Shanghai, China
| | - Qingtong Yi
- Department of Urology, Shanghai Pudong Hospital, Fudan University Pudong Medical Center, Shanghai, China
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19
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Prognostic Risk Signature and Comprehensive Analyses of Endoplasmic Reticulum Stress-Related Genes in Lung Adenocarcinoma. J Immunol Res 2022; 2022:6567916. [PMID: 35571564 PMCID: PMC9096573 DOI: 10.1155/2022/6567916] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Revised: 03/29/2022] [Accepted: 04/04/2022] [Indexed: 12/24/2022] Open
Abstract
Lung adenocarcinoma (LUAD) is the main pathological subtype of non-small-cell lung cancer. Endoplasmic reticulum stress (ERS) has been found to be involved in multiple tumor-related biological processes. At present, a comprehensive analysis of ERS-related genes in LUAD is still lacking. A total of 1034 samples from TCGA and GEO were used to screen differentially expressed genes. Further, Random Forest algorithm was utilized to screen characteristic genes related to prognosis. Then, LASSO Cox regression was used to construct a prognostic signature. Taking the median of signature score as the threshold, patients were separated into high-risk (HR) group and low-risk (LR) group. Tumor mutation burden (TMB), immune cell infiltration, cancer stem cell infiltration, expression of HLA, and immune checkpoints of the two risk groups were analyzed. TIDE score was used to evaluate the response of the two risk groups to immunotherapy. Finally, the gene expression was verified in clinical tissues with RT-qPCR. An eight-gene signature (ADRB2, AGER, CDKN3, GJB2, SFTPC, SLC2A1, SLC6A4, and SSR4) was constructed. TMB and cancer stem cell infiltration were higher in the HR group than the LR group. TIDE score and expression level of HLA were higher in the LR group than the HR group. Expression level of immune checkpoints, including CD28, CD27, IDO2, and others, were higher in the LR group. Multiple drugs approved by FAD, targeting ERS-related genes, were available for the treatment of LUAD. In summary, we established a stable prognostic model based on ERS-related genes to help the classification of LUAD patients and looked for new treatment strategies from aspects of immunity, tumor mutation, and tumor stem cell infiltration.
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Liu S, He B, Li H. Bisphenol S promotes the progression of prostate cancer by regulating the expression of COL1A1 and COL1A2. Toxicology 2022; 472:153178. [DOI: 10.1016/j.tox.2022.153178] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Revised: 04/03/2022] [Accepted: 04/06/2022] [Indexed: 10/18/2022]
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Deng Y, Wang J, Hu Z, Cai Y, Xu Y, Xu K. Exploration of the immune microenvironment of breast cancer in large population cohorts. Front Endocrinol (Lausanne) 2022; 13:955630. [PMID: 36046784 PMCID: PMC9421148 DOI: 10.3389/fendo.2022.955630] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/29/2022] [Accepted: 07/14/2022] [Indexed: 11/13/2022] Open
Abstract
Tumor immune microenvironment is associated with tumor progression. However, previous studies have not fully explored the breast cancer (BC) immune microenvironment. All the data analyzed in this study were obtained from the open-access database, including The Cancer Genome Atlas, Gene Expression Omnibus (TCGA), and cBioPortal databases. R software v4.0 and SPSS 13.0 were used to perform all the statistical analysis. Firstly, the clinical and expression profile information of TCGA, GSE20685, GSE20711, GSE48390, GSE58812, and METABRIC cohorts was collected. Then, 53 immune terms were quantified using the single-sample Gene Set Enrichment Analysis (ssGSEA) algorithm. A prognosis model based on HER2_Immune_PCA, IL12_score, IL13_score, IL4_score, and IR7_score was established, which showed great prognosis prediction efficiency in both training group and validation group. A nomogram was then established for a better clinical application. Clinical correlation showed that elderly BC patients might have a higher riskscore. Pathway enrichment analysis showed that the pathway of oxidative phosphorylation, E2F targets, hedgehog signaling, adipogenesis, DNA repair, glycolysis, heme metabolism, and mTORC1 signaling was activated in the high-risk group. Moreover, Tumor Immune Dysfunction and Exclusion and Genomics of Drug Sensitivity in Cancer analysis showed that low-risk patients might be more sensitive to PD-1 therapy, cisplatin, gemcitabine, paclitaxel, and sunitinib. Finally, four genes, XCL1, XCL2, TNFRSF17, and IRF4, were identified for risk group classification. In summary, our signature is a useful tool for the prognosis and prediction of the drug sensitivity of BC.
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Affiliation(s)
- Youyuan Deng
- Department of General Surgery, Xiangtan Central Hospital, Xiangtan, China
| | - Jianguo Wang
- Department of General Surgery, Xiangtan Central Hospital, Xiangtan, China
- *Correspondence: Ke Xu, ; Jianguo Wang,
| | - Zhiya Hu
- Department of Pharmacy, Third Hospital of Changsha, Changsha, China
| | - Yurong Cai
- Department of General Surgery, Xiangtan Central Hospital, Xiangtan, China
| | - Yiping Xu
- Department of General Surgery, Xiangtan Central Hospital, Xiangtan, China
| | - Ke Xu
- Department of Oncology, The First Affiliated Hospital of Chengdu Medical College, Chengdu, China
- Clinical Medical College, Chengdu Medical College, Chengdu, China
- Key Clinical Specialty of Sichuan Province, Chengdu, China
- *Correspondence: Ke Xu, ; Jianguo Wang,
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Fang Z, Huang H, Wang L, Lin Z. Identification of the alpha linolenic acid metabolism-related signature associated with prognosis and the immune microenvironment in nasopharyngeal carcinoma. Front Endocrinol (Lausanne) 2022; 13:968984. [PMID: 35992141 PMCID: PMC9388792 DOI: 10.3389/fendo.2022.968984] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Accepted: 07/12/2022] [Indexed: 11/20/2022] Open
Abstract
BACKGROUND Tumor metabolism is important for cancer progression. Nevertheless, the role of the metabolism pathway and related molecules in nasopharyngeal carcinoma (NPC) is limited. METHODS Open-accessed data was downloaded from The Cancer Genome Atlas database. All the analysis was performed using the R software and the package in R environments. RESULTS In our study, we firstly explored the role of 21 metabolism-related pathways in NPC patients. We found that the steroid biosynthesis and biosynthesis of unsaturated fatty acids were risk factors, while the alpha linolenic acid metabolism was a protective factor. Then, the alpha linolenic acid metabolism aroused our interest. A total of 128 differentially expressed genes (DEGs) were identified, including 71 downregulated and 57 upregulated genes identified between high and low alpha linolenic acid metabolism level. Based on these DEGs, we constructed a prognosis model including DEFB4B, FOXL2NB, MDGA2, RTL1, SLURP2, TMEM151B and TSPAN19, which showed great prediction efficiency in both training and validation cohorts. Clinical correlation analysis showed that high-risk patients might have worse clinical pathology parameters. Pathway enrichment analysis showed that riskscore was positively correlated with angiogenesis, DNA repair, G2/M checkpoints, IL6/JAK/STAT3 signaling, KRAS signaling up, WNT beta-catenin signaling, PI3K/AKT/mTOR signaling, yet positively correlated with inflammatory response, xenobiotic metabolism, TNF-α signaling via NFKB and interferon-gamma response. Immune infiltration analysis showed that the riskscore was positively correlated with the M2 and M0 macrophages, but negatively correlated with neutrophils, plasma cells, follicular helper T cells and resting dendritic cells Moreover, we found that the low-risk patients might be more sensitive to immunotherapy and lapatinib. CONCLUSIONS In all, our study identified the genes associated with alpha linolenic acid metabolism and constructed an effective prognosis model which could robustly predict NPC patients prognosis.
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Affiliation(s)
- Zhijie Fang
- Department of Otolaryngology, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, China
| | - Hua Huang
- Department of Otolaryngology, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, China
| | - Liyu Wang
- The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, China
| | - Zhiqiang Lin
- Department of Otolaryngology, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, China
- *Correspondence: Zhiqiang Lin,
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Hu X, Zhou X, Zhang J, Li L. Sphingolipid metabolism is associated with osteosarcoma metastasis and prognosis: Evidence from interaction analysis. Front Endocrinol (Lausanne) 2022; 13:983606. [PMID: 36105405 PMCID: PMC9465041 DOI: 10.3389/fendo.2022.983606] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Accepted: 07/27/2022] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND Metabolism is widely involved in the occurrence and development of cancer. However, its role in osteosarcoma (OS) has not been elucidated. METHODS The open-accessed data included in this study were downloaded from The Cancer Genome Atlas (TCGA) database (TARGET-OS project). All the analysis was performed in R environments. RESULTS Based on the single sample gene set enrichment analysis algorithm, we quantified 21 metabolism terms in OS patients. Among these, sphingolipid metabolism was upregulated in the metastatic OS tissue and associated with a worse prognosis, therefore aroused our interest and selected for further analysis. Our result showed that sphingolipid metabolism could activate the Notch signaling and angiogenesis pathway, which might be responsible for the metastasis ability and poor prognosis. A protein-protein interaction network was constructed to illustrate the interaction of the differentially expressed genes between high and low sphingolipid metabolism. Immune analysis showed that multiple immune terms were upregulated in patients with high sphingolipid metabolism activity. Then, a prognosis model was established based on the identified DEGs between patients with high and low sphingolipid metabolism, which showed great prediction efficiency. Pathway enrichment showed the pathway of myogenesis, spermatogenesis, peroxisome, KRAS signaling, pancreas beta cells, apical surface, MYC target, WNT beta-catenin signaling, late estrogen response and apical junction was significantly enriched in high risk patients. Moreover, we found that the model genes MAGEB1, NPIPA2, PLA2G4B and MAGEA3 could effectively indicate sphingolipid metabolism and risk group. CONCLUSIONS In summary, our result showed that sphingolipid metabolism is associated with osteosarcoma metastasis and prognosis, which has the potential to be a therapeutic target for OS.
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Affiliation(s)
- Xinyue Hu
- School of Medicine, Southeast University, Nanjing, Jiangsu, China
| | - Xin Zhou
- Department of Orthopaedic surgery, The Affiliated Jiangning Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Jue Zhang
- Department of Orthopaedic surgery, The Affiliated Jiangning Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Liangliang Li
- Department of Orthopaedic surgery, The Affiliated Jiangning Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
- *Correspondence: Liangliang Li,
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