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Xiang D, Zhou L, Yang R, Yuan F, Xu Y, Yang Y, Qiao Y, Li X. Advances in Ferroptosis-Inducing Agents by Targeted Delivery System in Cancer Therapy. Int J Nanomedicine 2024; 19:2091-2112. [PMID: 38476278 PMCID: PMC10929151 DOI: 10.2147/ijn.s448715] [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: 11/09/2023] [Accepted: 02/16/2024] [Indexed: 03/14/2024] Open
Abstract
Currently, cancer remains one of the most significant threats to human health. Treatment of most cancers remains challenging, despite the implementation of diverse therapies in clinical practice. In recent years, research on the mechanism of ferroptosis has presented novel perspectives for cancer treatment. Ferroptosis is a regulated cell death process caused by lipid peroxidation of membrane unsaturated fatty acids catalyzed by iron ions. The rapid development of bio-nanotechnology has generated considerable interest in exploiting iron-induced cell death as a new therapeutic target against cancer. This article provides a comprehensive overview of recent advancements at the intersection of iron-induced cell death and bionanotechnology. In this respect, the mechanism of iron-induced cell death and its relation to cancer are summarized. Furthermore, the feasibility of a nano-drug delivery system based on iron-induced cell death for cancer treatment is introduced and analyzed. Secondly, strategies for inducing iron-induced cell death using nanodrug delivery technology are discussed, including promoting Fenton reactions, inhibiting glutathione peroxidase 4, reducing low glutathione levels, and inhibiting system Xc-. Additionally, the article explores the potential of combined treatment strategies involving iron-induced cell death and bionanotechnology. Finally, the application prospects and challenges of iron-induced nanoagents for cancer treatment are discussed.
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Affiliation(s)
- Debiao Xiang
- Department of Pharmacy, The Third Hospital of Changsha, Changsha, Hunan Province, People’s Republic of China
- Hunan Provincial Key Laboratory of Anti-Resistance Microbial Drugs, Changsha, Hunan Province, People’s Republic of China
- The Clinical Application Research Institute of Antibiotics in Changsha, Changsha, Hunan Province, People’s Republic of China
| | - Lili Zhou
- College of Pharmacy, Hunan University of Chinese Medicine, Changsha, Hunan Province, People’s Republic of China
| | - Rui Yang
- Department of Pharmacy, The Third Hospital of Changsha, Changsha, Hunan Province, People’s Republic of China
- College of Pharmacy, Hunan University of Chinese Medicine, Changsha, Hunan Province, People’s Republic of China
| | - Fang Yuan
- Department of Pharmacy, The Third Hospital of Changsha, Changsha, Hunan Province, People’s Republic of China
- Hunan Provincial Key Laboratory of Anti-Resistance Microbial Drugs, Changsha, Hunan Province, People’s Republic of China
- The Clinical Application Research Institute of Antibiotics in Changsha, Changsha, Hunan Province, People’s Republic of China
| | - Yilin Xu
- College of Pharmacy, Hunan University of Chinese Medicine, Changsha, Hunan Province, People’s Republic of China
| | - Yuan Yang
- Department of Pharmacy, The Third Hospital of Changsha, Changsha, Hunan Province, People’s Republic of China
- College of Pharmacy, Hunan University of Chinese Medicine, Changsha, Hunan Province, People’s Republic of China
| | - Yong Qiao
- Department of Pharmacy, The Third Hospital of Changsha, Changsha, Hunan Province, People’s Republic of China
- Hunan Provincial Key Laboratory of Anti-Resistance Microbial Drugs, Changsha, Hunan Province, People’s Republic of China
- The Clinical Application Research Institute of Antibiotics in Changsha, Changsha, Hunan Province, People’s Republic of China
| | - Xin Li
- Department of Pharmacy, The Third Hospital of Changsha, Changsha, Hunan Province, People’s Republic of China
- Hunan Provincial Key Laboratory of Anti-Resistance Microbial Drugs, Changsha, Hunan Province, People’s Republic of China
- The Clinical Application Research Institute of Antibiotics in Changsha, Changsha, Hunan Province, People’s Republic of China
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Yang J, Wang C, Zhang Y, Cheng S, Wu M, Gu S, Xu S, Wu Y, Wang Y. A novel autophagy-related gene signature associated with prognosis and immune microenvironment in ovarian cancer. J Ovarian Res 2023; 16:86. [PMID: 37120633 PMCID: PMC10148536 DOI: 10.1186/s13048-023-01167-5] [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: 03/14/2023] [Accepted: 04/25/2023] [Indexed: 05/01/2023] Open
Abstract
Ovarian cancer (OV), the most fatal gynecological malignance worldwide, has high recurrence rates and poor prognosis. Recently, emerging evidence supports that autophagy, a highly regulated multi-step self-digestive process, plays an essential role in OV progression. Accordingly, we filtered 52 potential autophagy-related genes (ATGs) among the 6197 differentially expressed genes (DEGs) identified in TCGA-OV samples (n = 372) and normal controls (n = 180). Based on the LASSO-Cox analysis, we distinguished a 2-gene prognostic signature, namely FOXO1 and CASP8, with promising prognostic value (p-value < 0.001). Together with corresponding clinical features, we constructed a nomogram model for 1-year, 2-year, and 3-year survival, which was validated in both in training (TCGA-OV, p-value < 0.001) and validation (ICGC-OV, p-value = 0.030) cohorts. Interestingly, we evaluated the immune infiltration landscape through the CIBERSORT algorithm, which indicated the upregulation of 5 immune cells, including CD8 + T cells, Tregs, and Macrophages M2, and high expression of critical immune checkpoints (CTLA4, HAVCR2, PDCD1LG2, and TIGIT) in high-risk group. Stepwise, high-risk group exhibited better sensitivity towards chemotherapies of Bleomycin, Sorafenib, Veliparib, and Vinblastine, though less sensitive to immunotherapy. Especially, based on the IHC of tissue microarrays among 125 patients in our institution, we demonstrated that aberrant upregulation of FOXO1 in OV was related to metastasis and poor prognosis. Moreover, FOXO1 could significantly promote tumor invasiveness, migration, and proliferation in OV cell lines, which was assessed through the Transwell, wound-healing, and CCK-8 assay, respectively. Briefly, the autophagy-related signature was a reliable tool to evaluate immune responses and predict prognosis in the realm of OV precision medicine.
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Affiliation(s)
- Jiani Yang
- Department of Gynecology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, 200092, China
- Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai First Maternity and Infant Hospital, School of Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Tongji University, Shanghai, 200092, China
| | - Chao Wang
- Department of Gynecology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, 200092, China
- Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai First Maternity and Infant Hospital, School of Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Tongji University, Shanghai, 200092, China
| | - Yue Zhang
- Department of Gynecology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, 200092, China
- Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai First Maternity and Infant Hospital, School of Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Tongji University, Shanghai, 200092, China
| | - Shanshan Cheng
- Department of Obstetrics and Gynecology, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, China
| | - Meixuan Wu
- Department of Obstetrics and Gynecology, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, China
| | - Sijia Gu
- Department of Obstetrics and Gynecology, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, China
| | - Shilin Xu
- Department of Obstetrics and Gynecology, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, China
| | - Yongsong Wu
- Department of Obstetrics and Gynecology, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, China
| | - Yu Wang
- Department of Gynecology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, 200092, China.
- Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai First Maternity and Infant Hospital, School of Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Tongji University, Shanghai, 200092, China.
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Feng J, Yu Y, Yin W, Qian S. Development and verification of a 7-lncRNA prognostic model based on tumor immunity for patients with ovarian cancer. J Ovarian Res 2023; 16:31. [PMID: 36739404 PMCID: PMC9898952 DOI: 10.1186/s13048-023-01099-0] [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: 08/15/2022] [Accepted: 01/11/2023] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Both immune-reaction and lncRNAs play significant roles in the proliferation, invasion, and metastasis of ovarian cancer (OC). In this study, we aimed to construct an immune-related lncRNA risk model for patients with OC. METHOD Single sample GSEA (ssGSEA) algorithm was used to analyze the proportion of immune cells in The Cancer Genome Atlas (TCGA) and the hclust algorithm was used to conduct immune typing according to the proportion of immune cells for OC patients. The stromal and immune scores were computed utilizing the ESTIMATE algorithm. Weighted gene co-expression network analysis (WGCNA) and differentially expressed genes (DEGs) analyses were utilized to detect immune cluster-related lncRNAs. The least absolute shrinkage and selection operator (LASSO) regression was conducted for lncRNA selection. The selected lncRNAs were used to construct a prognosis-related risk model, which was then validated in Gene Expression Omnibus (GEO) database and in vitro validation. RESULTS We identify two subtypes based on the ssGSEA analysis, high immunity cluster (immunity_H) and low immunity cluster (immunity_L). The proportion of patients in immunity_H cluster was significantly higher than that in immunity_L cluster. The ESTIMATE related scores are relative high in immunity_H group. Through WGCNA and LASSO analyses, we identified 141 immune cluster-related lncRNAs and found that these genes were mainly enriched in autophagy. A signature consisting of 7 lncRNAs, including AL391832.3, LINC00892, LINC02207, LINC02416, PSMB8.AS1, AC078788.1 and AC104971.3, were selected as the basis for classifying patients into high- and low-risk groups. Survival analysis and area under the ROC curve (AUC) of the signature pointed out that this risk model had high accuracy in predicting the prognosis of patients with OC. We also conducted the drug sensitive prediction and found that rapamycin outperformed in patient with high risk score. In vitro experiments also confirmed our prediction. CONCLUSIONS We identified 7 immune-related prognostic lncRNAs that effectively predicted survival in OC patients. These findings may offer a valuable indicator for clinical stratification management and personalized therapeutic options for these patients.
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Affiliation(s)
- Jing Feng
- grid.452270.60000 0004 0614 4777Gynecology Department 2, Cangzhou Central Hospital, No. 16, Xinhua West Road, Yunhe District, Cangzhou, Hebei Province 061000 China
| | - Yiping Yu
- grid.452270.60000 0004 0614 4777Gynecology Department 2, Cangzhou Central Hospital, No. 16, Xinhua West Road, Yunhe District, Cangzhou, Hebei Province 061000 China
| | - Wen Yin
- grid.452270.60000 0004 0614 4777Gynecology Department 2, Cangzhou Central Hospital, No. 16, Xinhua West Road, Yunhe District, Cangzhou, Hebei Province 061000 China
| | - Sumin Qian
- grid.452270.60000 0004 0614 4777Gynecology Department 2, Cangzhou Central Hospital, No. 16, Xinhua West Road, Yunhe District, Cangzhou, Hebei Province 061000 China
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Li S, Li Q, Ren Y, Yi J, Guo J, Kong X. HSV: The scout and assault for digestive system tumors. Front Mol Biosci 2023; 10:1142498. [PMID: 36926680 PMCID: PMC10011716 DOI: 10.3389/fmolb.2023.1142498] [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: 01/11/2023] [Accepted: 02/15/2023] [Indexed: 03/08/2023] Open
Abstract
More than 25% of all malignant tumors are digestive system tumors (DSTs), which mostly include esophageal cancer, gastric cancer, pancreatic cancer, liver cancer, gallbladder cancer and cholangiocarcinoma, and colorectal cancer. DSTs have emerged as one of the prominent reasons of morbidity and death in many nations and areas around the world, posing a serious threat to human life and health. General treatments such as radiotherapy, chemotherapy, and surgical resection can poorly cure the patients and have a bad prognosis. A type of immunotherapy known as oncolytic virus therapy, have recently shown extraordinary anti-tumor effectiveness. One of the viruses that has been the subject of the greatest research in this field, the herpes simplex virus (HSV), has shown excellent potential in DSTs. With a discussion of HSV-1 based on recent studies, we outline the therapeutic effects of HSV on a number of DSTs in this review. Additionally, the critical function of HSV in the detection of cancers is discussed, and some HSV future possibilities are shown.
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Affiliation(s)
- Sheng Li
- College of Traditional Chinese medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Qingbo Li
- College of Traditional Chinese medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Yi Ren
- College of Traditional Chinese medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Jia Yi
- College of Traditional Chinese medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Jinhe Guo
- College of Traditional Chinese medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Xianbin Kong
- College of Traditional Chinese medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, China
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Nokhostin F, Azadehrah M, Azadehrah M. The multifaced role and therapeutic regulation of autophagy in ovarian cancer. Clin Transl Oncol 2022; 25:1207-1217. [PMID: 36534371 DOI: 10.1007/s12094-022-03045-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2022] [Accepted: 12/07/2022] [Indexed: 12/23/2022]
Abstract
Ovarian cancer (OC) is one of the tumors that occurs most frequently in women. Autophagy is involved in cell homeostasis, biomolecule recycling, and survival, making it a potential target for anti-tumor drugs. It is worth noting that growing evidence reveals a close link between autophagy and OC. In the context of OC, autophagy demonstrates activity as both a tumor suppressor and a tumor promoter, depending on the context. Autophagy's exact function in OC is greatly reliant on the tumor microenvironment (TME) and other conditions, such as hypoxia, nutritional deficiency, chemotherapy, and so on. However, what can be concluded from different studies is that autophagy-related signaling pathways, especially PI3K/AKT/mTOR axis, increase in advanced stages and malignant phenotype of the disease reduces autophagy and ultimately leads to tumor progression. This study sought to present a thorough understanding of the role of autophagy-related signaling pathways in OC and existing therapies targeting these signaling pathways.
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Affiliation(s)
- Fahimeh Nokhostin
- Department of Obstetrics and Gynecology, Faculty of Medicine, Shahid Sadughi University of Medical Sciences, Yazd, Iran
| | - Mahboobeh Azadehrah
- Cancer Research Center, Golestan University of Medical Sciences, Gorgan, Iran
| | - Malihe Azadehrah
- Cancer Research Center, Golestan University of Medical Sciences, Gorgan, Iran.
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Liu H, Li Y. Potential roles of Cornichon Family AMPA Receptor Auxiliary Protein 4 (CNIH4) in head and neck squamous cell carcinoma. Cancer Biomark 2022; 35:439-450. [PMID: 36404537 DOI: 10.3233/cbm-220143] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND It is of great clinical significance to discover novel biomarkers for neck squamous cell carcinoma (HNSCC) treatments. We discovered a potential cancer-related gene, Cornichon Family AMPA Receptor Auxiliary Protein 4 (CNIH4), that can be a biomarker for HNSCC. METHODS We access multiple open databases and analyzed bulk mRNA-sequencing, protein staining, and single-cell mRNA-sequencing data of HNSCC and investigated the diagnostic and prognostic value of CNIH4 in HNSCC. The potential association between CNIH4 and the immune microenvironment of HNSCC was also estimated. RESULTS CNIH4 was significantly up-regulated in HNSCC compared with non-cancer tissues. Higher CNIH4 resulted in a shorter overall survival time and we further constructed a survival nomogram for clinical applications. 2012 and 421 genes were identified as positive and negative differentially expressed genes of CNIH4 in HNSCC respectively. These genes were mostly mapped to "Cell cycle", "DNA replicate", "Cytokine-cytokine receptor interaction" KEGG pathways. Functions associated with CNIH4 were "stemness", "cell cycle", and "DNA repair" in single-cell data. CNIH4 potentially affected immune cell infiltration levels and cancer immune therapy. CONCLUSION CNIH4 is a potential diagnostic and prognostic biomarker associated with cancer stemness and immunity in HNSCC.
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Affiliation(s)
- Hengrui Liu
- Tianjin Yinuo Biomedical Co., Ltd., Tianjin, China
| | - Yixue Li
- Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China.,Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, Guangdong, China
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Xiong L, Tan J, Feng Y, Wang D, Liu X, Feng Y, Li S. Protein expression profiling identifies a prognostic model for ovarian cancer. BMC Womens Health 2022; 22:292. [PMID: 35840928 PMCID: PMC9284690 DOI: 10.1186/s12905-022-01876-x] [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: 02/09/2022] [Accepted: 07/11/2022] [Indexed: 11/10/2022] Open
Abstract
Abstract
Background
Owing to the high morbidity and mortality, ovarian cancer has seriously endangered female health. Development of reliable models can facilitate prognosis monitoring and help relieve the distress.
Methods
Using the data archived in the TCPA and TCGA databases, proteins having significant survival effects on ovarian cancer patients were screened by univariate Cox regression analysis. Patients with complete information concerning protein expression, survival, and clinical variables were included. A risk model was then constructed by performing multiple Cox regression analysis. After validation, the predictive power of the risk model was assessed. The prognostic effect and the biological function of the model were evaluated using co-expression analysis and enrichment analysis.
Results
394 patients were included in model construction and validation. Using univariate Cox regression analysis, we identified a total of 20 proteins associated with overall survival of ovarian cancer patients (p < 0.01). Based on multiple Cox regression analysis, six proteins (GSK3α/β, HSP70, MEK1, MTOR, BAD, and NDRG1) were used for model construction. Patients in the high-risk group had unfavorable overall survival (p < 0.001) and poor disease-specific survival (p = 0.001). All these six proteins also had survival prognostic effects. Multiple Cox regression analysis demonstrated the risk model as an independent prognostic factor (p < 0.001). In receiver operating characteristic curve analysis, the risk model displayed higher predictive power than age, tumor grade, and tumor stage, with an area under the curve value of 0.789. Analysis of co-expressed proteins and differentially expressed genes based on the risk model further revealed its prognostic implication.
Conclusions
The risk model composed of GSK3α/β, HSP70, MEK1, MTOR, BAD, and NDRG1 could predict survival prognosis of ovarian cancer patients efficiently and help disease management.
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Sun Y, Li J, Wang L, Cong T, Zhai X, Li L, Wu H, Li S, Xiao Z. Identification of Potential Diagnoses Based on Immune Infiltration and Autophagy Characteristics in Major Depressive Disorder. Front Genet 2022; 13:702366. [PMID: 35559009 PMCID: PMC9087348 DOI: 10.3389/fgene.2022.702366] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Accepted: 03/25/2022] [Indexed: 12/12/2022] Open
Abstract
Background: Major depressive disorder (MDD) is a serious mental illness characterized by mood changes and high suicide rates. However, no studies are available to support a blood test method for MDD diagnosis. The objective of this research was to identify potential peripheral blood biomarkers for MDD and characterize the novel pathophysiology. Methods: We accessed whole blood microarray sequencing data for MDD and control samples from public databases. Biological functions were analysed by GO and KEGG pathway enrichment analyses using the clusterprofile R package. Infiltrated immune cell (IIC) proportions were identified using the CIBERSORT algorithm. Clustering was performed using the ConsensusClusterPlus R package. Protein–protein interactions (PPI) were assessed by constructing a PPI network using STRING and visualized using Cytoscape software. Rats were exposed to chronic unpredictable mild stress (CUMS) for 6 weeks to induce stress behaviour. Stress behaviour was evaluated by open field experiments and forced swimming tests. Flow cytometry was used to analyse the proportion of CD8+ T cells. The expression of the corresponding key genes was detected by qRT–PCR. Results: We divided MDD patients into CD8H and CD8L clusters. The functional enrichment of marker genes in the CD8H cluster indicated that autophagy-related terms and pathways were significantly enriched. Furthermore, we obtained 110 autophagy-related marker genes (ARMGs) in the CD8H cluster through intersection analysis. GO and KEGG analyses further showed that these ARMGs may regulate a variety of autophagy processes and be involved in the onset and advancement of MDD. Finally, 10 key ARMGs were identified through PPI analysis: RAB1A, GNAI3, VAMP7, RAB33B, MYC, LAMP2, RAB11A, HIF1A, KIF5B, and PTEN. In the CUMS model, flow cytometric analysis confirmed the above findings. qRT–PCR revealed significant decreases in the mRNA levels of Gnai3, Rab33b, Lamp2, and Kif5b in the CUMS groups. Conclusion: In this study, MDD was divided into two subtypes. We combined immune infiltrating CD8+ T cells with autophagy-related genes and screened a total of 10 ARMG genes. In particular, RAB1A, GNAI3, RAB33B, LAMP2, and KIF5B were first reported in MDD. These genes may offer new hope for the clinical diagnosis of MDD.
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Affiliation(s)
- Ye Sun
- Department of Anesthesiology, The Second Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Jinying Li
- Department of Anesthesiology, The Second Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Lin Wang
- Department of Anesthesiology, The Second Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Ting Cong
- Department of Anesthesiology, The Second Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Xiuli Zhai
- Department of Anesthesiology, Inner Mongolia People's Hospital, Hohhot, China
| | - Liya Li
- Department of Anesthesiology, The Second Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Haikuo Wu
- Department of Anesthesiology, The Second Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Shouxin Li
- Department of Anesthesiology, The Second Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Zhaoyang Xiao
- Department of Anesthesiology, The Second Affiliated Hospital of Dalian Medical University, Dalian, China
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Kuang Y, Ye N, Kyani A, Ljungman M, Paulsen M, Chen H, Zhou M, Wild C, Chen H, Zhou J, Neamati N. Induction of Genes Implicated in Stress Response and Autophagy by a Novel Quinolin-8-yl-nicotinamide QN523 in Pancreatic Cancer. J Med Chem 2022; 65:6133-6156. [PMID: 35439009 PMCID: PMC9195374 DOI: 10.1021/acs.jmedchem.1c02207] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Using a cytotoxicity-based phenotypic screen of a highly diverse library of 20,000 small-molecule compounds, we identified a quinolin-8-yl-nicotinamide, QN519, as a promising lead. QN519 represents a novel scaffold with drug-like properties, showing potent in vitro cytotoxicity in a panel of 12 cancer cell lines. Subsequently, lead optimization campaign generated compounds with IC50 values < 1 μM. An optimized compound, QN523, shows significant in vivo efficacy in a pancreatic cancer xenograft model. QN523 treatment significantly increased the expression of HSPA5, DDIT3, TRIB3, and ATF3 genes, suggesting activation of the stress response pathway. We also observed a significant increase in the expression of WIPI1, HERPUD1, GABARAPL1, and MAP1LC3B, implicating autophagy as a major mechanism of action. Due to the lack of effective treatments for pancreatic cancer, discovery of novel agents such as the QN series of compounds with unique mechanism of action has the potential to fulfill a clear unmet medical need.
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Affiliation(s)
- Yuting Kuang
- Department of Medicinal Chemistry, College of Pharmacy, Rogel Cancer Center, University of Michigan, Ann Arbor, MI 48109, USA
| | - Na Ye
- Chemical Biology Program, Department of Pharmacology and Toxicology, University of Texas Medical Branch (UTMB), Galveston, TX 77550, USA
| | - Armita Kyani
- Department of Medicinal Chemistry, College of Pharmacy, Rogel Cancer Center, University of Michigan, Ann Arbor, MI 48109, USA
| | - Mats Ljungman
- Department of Radiation Oncology, Rogel Cancer Center and Center for RNA Biomedicine, University of Michigan, Ann Arbor, MI 48109, USA
| | - Michelle Paulsen
- Department of Radiation Oncology, Rogel Cancer Center and Center for RNA Biomedicine, University of Michigan, Ann Arbor, MI 48109, USA
| | - Haijun Chen
- Chemical Biology Program, Department of Pharmacology and Toxicology, University of Texas Medical Branch (UTMB), Galveston, TX 77550, USA
| | - Mingxiang Zhou
- Chemical Biology Program, Department of Pharmacology and Toxicology, University of Texas Medical Branch (UTMB), Galveston, TX 77550, USA
| | - Christopher Wild
- Chemical Biology Program, Department of Pharmacology and Toxicology, University of Texas Medical Branch (UTMB), Galveston, TX 77550, USA
| | - Haiying Chen
- Chemical Biology Program, Department of Pharmacology and Toxicology, University of Texas Medical Branch (UTMB), Galveston, TX 77550, USA
| | - Jia Zhou
- Chemical Biology Program, Department of Pharmacology and Toxicology, University of Texas Medical Branch (UTMB), Galveston, TX 77550, USA
| | - Nouri Neamati
- Department of Medicinal Chemistry, College of Pharmacy, Rogel Cancer Center, University of Michigan, Ann Arbor, MI 48109, USA
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Liu LP, Lu L, Zhao QQ, Kou QJ, Jiang ZZ, Gui R, Luo YW, Zhao QY. Identification and Validation of the Pyroptosis-Related Molecular Subtypes of Lung Adenocarcinoma by Bioinformatics and Machine Learning. Front Cell Dev Biol 2021; 9:756340. [PMID: 34805165 PMCID: PMC8599430 DOI: 10.3389/fcell.2021.756340] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Accepted: 10/04/2021] [Indexed: 12/20/2022] Open
Abstract
Lung cancer remains the leading cause of cancer death globally, with lung adenocarcinoma (LUAD) being its most prevalent subtype. Due to the heterogeneity of LUAD, patients given the same treatment regimen may have different responses and clinical outcomes. Therefore, identifying new subtypes of LUAD is important for predicting prognosis and providing personalized treatment for patients. Pyroptosis-related genes play an essential role in anticancer, but there is limited research investigating pyroptosis in LUAD. In this study, 33 pyroptosis gene expression profiles and clinical information were collected from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. By bioinformatics and machine learning analyses, we identified novel subtypes of LUAD based on 10 pyroptosis-related genes and further validated them in the GEO dataset, with machine learning models performing up to an AUC of 1 for classifying in GEO. A web-based tool was established for clinicians to use our clustering model (http://www.aimedicallab.com/tool/aiml-subphe-luad.html). LUAD patients were clustered into 3 subtypes (A, B, and C), and survival analysis showed that B had the best survival outcome and C had the worst survival outcome. The relationships between pyroptosis gene expression and clinical characteristics were further analyzed in the three molecular subtypes. Immune profiling revealed significant differences in immune cell infiltration among the three molecular subtypes. GO enrichment and KEGG pathway analyses were performed based on the differential genes of the three subtypes, indicating that differentially expressed genes (DEGs) were involved in multiple cellular and biological functions, including RNA catabolic process, mRNA catabolic process, and pathways of neurodegeneration-multiple diseases. Finally, we developed an 8-gene prognostic model that accurately predicted 1-, 3-, and 5-year overall survival. In conclusion, pyroptosis-related genes may play a critical role in LUAD, and provide new insights into the underlying mechanisms of LUAD.
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Affiliation(s)
- Le-Ping Liu
- Department of Blood Transfusion, The Third Xiangya Hospital of Central South University, Changsha, China
| | - Lu Lu
- Department of Blood Transfusion, The Third Xiangya Hospital of Central South University, Changsha, China
| | - Qiang-Qiang Zhao
- Department of Blood Transfusion, The Third Xiangya Hospital of Central South University, Changsha, China
| | - Qin-Jie Kou
- Department of Laboratory Medicine, The Third Xiangya Hospital of Central South University, Changsha, China
| | - Zhen-Zhen Jiang
- Department of Blood Transfusion, The Third Xiangya Hospital of Central South University, Changsha, China
| | - Rong Gui
- Department of Blood Transfusion, The Third Xiangya Hospital of Central South University, Changsha, China
| | - Yan-Wei Luo
- Department of Blood Transfusion, The Third Xiangya Hospital of Central South University, Changsha, China
| | - Qin-Yu Zhao
- Department of Blood Transfusion, The Third Xiangya Hospital of Central South University, Changsha, China.,College of Engineering and Computer Science, The Australian National University, Canberra, ACT, Australia
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Chen X, Lan H, He D, Xu R, Zhang Y, Cheng Y, Chen H, Xiao S, Cao K. Multi-Omics Profiling Identifies Risk Hypoxia-Related Signatures for Ovarian Cancer Prognosis. Front Immunol 2021; 12:645839. [PMID: 34349753 PMCID: PMC8327177 DOI: 10.3389/fimmu.2021.645839] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2020] [Accepted: 07/01/2021] [Indexed: 12/23/2022] Open
Abstract
Background Ovarian cancer (OC) has the highest mortality rate among gynecologic malignancy. Hypoxia is a driver of the malignant progression in OC, which results in poor prognosis. We herein aimed to develop a validated model that was based on the hypoxia genes to systematically evaluate its prognosis in tumor immune microenvironment (TIM). Results We identified 395 hypoxia-immune genes using weighted gene co-expression network analysis (WGCNA). We then established a nine hypoxia-related genes risk model using least absolute shrinkage and selection operator (LASSO) Cox regression, which efficiently distinguished high-risk patients from low-risk ones. We found that high-risk patients were significantly related to poor prognosis. The high-risk group showed unique immunosuppressive microenvironment, lower antigen presentation, and higher levels of inhibitory cytokines. There were also significant differences in somatic copy number alterations (SCNAs) and mutations between the high- and low-risk groups, indicating immune escape in the high-risk group. Tumor immune dysfunction and exclusion (TIDE) and SubMap algorithms showed that low-risk patients are significantly responsive to programmed cell death protein-1 (PD-1) inhibitors. Conclusions In this study, we highlighted the clinical significance of hypoxia in OC and established a hypoxia-related model for predicting prognosis and providing potential immunotherapy strategies.
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Affiliation(s)
- Xingyu Chen
- Department of Oncology, Third Xiangya Hospital of Central South University, Changsha, China
| | - Hua Lan
- Department of Obstetrics and Gynecology, Third Xiangya Hospital of Central South University, Changsha, China
| | - Dong He
- Department of Respiration, The Second People's Hospital of Hunan Province of Hunan University of Chinese Medicine, Changsha, China
| | - Runshi Xu
- Medical school, Hunan University of Chinese Medicine, Changsha, China
| | - Yao Zhang
- Department of Oncology, Third Xiangya Hospital of Central South University, Changsha, China
| | - Yaxin Cheng
- Department of Oncology, Third Xiangya Hospital of Central South University, Changsha, China
| | - Haotian Chen
- Department of Oncology, Third Xiangya Hospital of Central South University, Changsha, China
| | - Songshu Xiao
- Department of Obstetrics and Gynecology, Third Xiangya Hospital of Central South University, Changsha, China
| | - Ke Cao
- Department of Oncology, Third Xiangya Hospital of Central South University, Changsha, China
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