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Zhao S, Ye B, Chi H, Cheng C, Liu J. Identification of peripheral blood immune infiltration signatures and construction of monocyte-associated signatures in ovarian cancer and Alzheimer's disease using single-cell sequencing. Heliyon 2023; 9:e17454. [PMID: 37449151 PMCID: PMC10336450 DOI: 10.1016/j.heliyon.2023.e17454] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 06/12/2023] [Accepted: 06/18/2023] [Indexed: 07/18/2023] Open
Abstract
Background Ovarian cancer (OC) is a common tumor of the female reproductive system, while Alzheimer's disease (AD) is a prevalent neurodegenerative disease that primarily affects cognitive function in the elderly. Monocytes are immune cells in the blood that can enter tissues and transform into macrophages, thus participating in immune and inflammatory responses. Overall, monocytes may play an important role in Alzheimer's disease and ovarian cancer. Methods The CIBERSORT algorithm results indicate a potential crucial role of monocytes/macrophages in OC and AD. To identify monocyte marker genes, single-cell RNA-seq data of peripheral blood mononuclear cells (PBMCs) from OC and AD patients were analyzed. Enrichment analysis of various cell subpopulations was performed using the "irGSEA" R package. The estimation of cell cycle was conducted with the "tricycle" R package, and intercellular communication networks were analyzed using "CellChat". For 134 monocyte-associated genes (MRGs), bulk RNA-seq data from two diseased tissues were obtained. Cox regression analysis was employed to develop risk models, categorizing patients into high-risk (HR) and low-risk (LR) groups. The model's accuracy was validated using an external GEO cohort. The different risk groups were evaluated in terms of immune cell infiltration, mutational status, signaling pathways, immune checkpoint expression, and immunotherapy. To identify characteristic MRGs in AD, two machine learning algorithms, namely random forest and support vector machine (SVM), were utilized. Results Based on Cox regression analysis, a risk model consisting of seven genes was developed in OC, indicating a better prognosis for patients in the LR group. The LR group had a higher tumor mutation burden, immune cell infiltration abundance, and immune checkpoint expression. The results of the TIDE algorithm and the IMvigor210 cohort showed that the LR group was more likely to benefit from immunotherapy. Finally, ZFP36L1 and AP1S2 were identified as characteristic MRGs affecting OC and AD progression. Conclusion The risk profile containing seven genes identified in this study may help further guide clinical management and targeted therapy for OC. ZFP36L1 and AP1S2 may serve as biomarkers and new therapeutic targets for patients with OC and AD.
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Affiliation(s)
- Songyun Zhao
- Department of Neurosurgery, Wuxi People's Hospital Affiliated to Nanjing Medical University, Wuxi, 214000, China
| | - Bicheng Ye
- School of Clinical Medicine, Yangzhou Polytechnic College, Yangzhou, 225000, China
| | - Hao Chi
- Clinical Medical College, Southwest Medical University, Luzhou, 646000, China
| | - Chao Cheng
- Department of Neurosurgery, Wuxi People's Hospital Affiliated to Nanjing Medical University, Wuxi, 214000, China
| | - Jinhui Liu
- Department of Gynecology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 210000, China
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He YB, Fang LW, Hu D, Chen SL, Shen SY, Chen KL, Mu J, Li JY, Zhang H, Yong-lin L, Zhang L. Necroptosis-associated long noncoding RNAs can predict prognosis and differentiate between cold and hot tumors in ovarian cancer. Front Oncol 2022; 12:967207. [PMID: 35965557 PMCID: PMC9366220 DOI: 10.3389/fonc.2022.967207] [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: 06/12/2022] [Accepted: 06/30/2022] [Indexed: 12/05/2022] Open
Abstract
Objective The mortality rate of ovarian cancer (OC) is the highest among all gynecologic cancers. To predict the prognosis and the efficacy of immunotherapy, we identified new biomarkers. Methods The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression Project (GTEx) databases were used to extract ovarian cancer transcriptomes. By performing the co-expression analysis, we identified necroptosis-associated long noncoding RNAs (lncRNAs). We used the least absolute shrinkage and selection operator (LASSO) to build the risk model. The qRT-PCR assay was conducted to confirm the differential expression of lncRNAs in the ovarian cancer cell line SK-OV-3. Gene Set Enrichment Analysis, Kaplan-Meier analysis, and the nomogram were used to determine the lncRNAs model. Additionally, the risk model was estimated to evaluate the efficacy of immunotherapy and chemotherapy. We classified necroptosis-associated IncRNAs into two clusters to distinguish between cold and hot tumors. Results The model was constructed using six necroptosis-associated lncRNAs. The calibration plots from the model showed good consistency with the prognostic predictions. The overall survival of one, three, and five-year areas under the ROC curve (AUC) was 0.691, 0.678, and 0.691, respectively. There were significant differences in the IC50 between the risk groups, which could serve as a guide to systemic treatment. The results of the qRT-PCR assay showed that AL928654.1, AL133371.2, AC007991.4, and LINC00996 were significantly higher in the SK-OV-3 cell line than in the Iose-80 cell line (P < 0.05). The clusters could be applied to differentiate between cold and hot tumors more accurately and assist in accurate mediation. Cluster 2 was more vulnerable to immunotherapies and was identified as the hot tumor. Conclusion Necroptosis-associated lncRNAs are reliable predictors of prognosis and can provide a treatment strategy by screening for hot tumors.
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Affiliation(s)
- Yi-bo He
- Department of Clinical Lab, The First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, China
- The First School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, China
| | - Lu-wei Fang
- The First School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, China
| | - Dan Hu
- Department of Clinical Lab, The Cixi Integrated Traditional Chinese and Western Medicine Medical and Health Group Cixi Red Cross Hospital, Cixi, China
| | - Shi-liang Chen
- Department of Clinical Lab, The First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, China
- The First School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, China
| | - Si-yu Shen
- The First School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, China
| | - Kai-li Chen
- The First School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, China
| | - Jie Mu
- The First School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, China
| | - Jun-yu Li
- Department of Pharmacy, Sanya Women and Children Hospital Managed by Shanghai Children’s Medical Center, Sanya, China
| | - Hongpan Zhang
- Department of Oncology, Affiliated Hospital of North Sichuan Medical College, Nanchong, China
- *Correspondence: Li Zhang, ; Hongpan Zhang, ; Liu Yong-lin,
| | - Liu Yong-lin
- Reproductive Centre, Sanya Women and Children Hospital Managed by Shanghai Children’s Medical Center, Sanya, China
- *Correspondence: Li Zhang, ; Hongpan Zhang, ; Liu Yong-lin,
| | - Li Zhang
- Obstetrics and Gynaecology, The First Affiliated Hospital of Zhejiang Chinese Medical, Hangzhou, China
- *Correspondence: Li Zhang, ; Hongpan Zhang, ; Liu Yong-lin,
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Ashrafizadeh M, Zarrabi A, Hushmandi K, Hashemi F, Rahmani Moghadam E, Raei M, Kalantari M, Tavakol S, Mohammadinejad R, Najafi M, Tay FR, Makvandi P. Progress in Natural Compounds/siRNA Co-delivery Employing Nanovehicles for Cancer Therapy. ACS COMBINATORIAL SCIENCE 2020; 22:669-700. [PMID: 33095554 PMCID: PMC8015217 DOI: 10.1021/acscombsci.0c00099] [Citation(s) in RCA: 53] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/21/2020] [Revised: 10/05/2020] [Indexed: 02/06/2023]
Abstract
Chemotherapy using natural compounds, such as resveratrol, curcumin, paclitaxel, docetaxel, etoposide, doxorubicin, and camptothecin, is of importance in cancer therapy because of the outstanding therapeutic activity and multitargeting capability of these compounds. However, poor solubility and bioavailability of natural compounds have limited their efficacy in cancer therapy. To circumvent this hurdle, nanocarriers have been designed to improve the antitumor activity of the aforementioned compounds. Nevertheless, cancer treatment is still a challenge, demanding novel strategies. It is well-known that a combination of natural products and gene therapy is advantageous over monotherapy. Delivery of multiple therapeutic agents/small interfering RNA (siRNA) as a potent gene-editing tool in cancer therapy can maximize the synergistic effects against tumor cells. In the present review, co-delivery of natural compounds/siRNA using nanovehicles are highlighted to provide a backdrop for future research.
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Affiliation(s)
- Milad Ashrafizadeh
- Faculty
of Engineering and Natural Sciences, Sabanci
University, Orta Mahalle,
Üniversite Caddesi No. 27, Orhanlı,
Tuzla, 34956 Istanbul, Turkey
- Sabanci
University Nanotechnology Research and Application Center (SUNUM), Tuzla 34956, Istanbul Turkey
| | - Ali Zarrabi
- Sabanci
University Nanotechnology Research and Application Center (SUNUM), Tuzla 34956, Istanbul Turkey
| | - Kiavash Hushmandi
- Department
of Food Hygiene and Quality Control, Division of Epidemiology &
Zoonoses, Faculty of Veterinary Medicine, University of Tehran, Tehran 1419963114, Iran
| | - Farid Hashemi
- Department
of Comparative Biosciences, Faculty of Veterinary Medicine, University of Tehran, Tehran, Iran
| | - Ebrahim Rahmani Moghadam
- Department
of Anatomical Sciences, School of Medicine, Student Research Committee, Shiraz University of Medical Sciences, Shiraz 7134814336, Iran
| | - Mehdi Raei
- Health Research
Center, Life Style Institute, Baqiyatallah
University of Medical Sciences, Tehran 1435916471, Iran
| | - Mahshad Kalantari
- Department
of Genetics, Tehran Medical Sciences Branch, Azad University, Tehran 19168931813, Iran
| | - Shima Tavakol
- Cellular
and Molecular Research Center, Iran University
of Medical Sciences, Tehran 1449614525, Iran
| | - Reza Mohammadinejad
- Pharmaceutics
Research Center, Institute of Neuropharmacology, Kerman University of Medical Sciences, Kerman 7616911319, Iran
| | - Masoud Najafi
- Medical
Technology Research Center, Institute of Health Technology, Kermanshah University of Medical Sciences, Kermanshah 6715847141, Iran
- Radiology
and Nuclear Medicine Department, School of Paramedical Sciences, Kermanshah University of Medical Sciences, Kermanshah 6715847141, Iran
| | - Franklin R. Tay
- College
of Graduate Studies, Augusta University, Augusta, Georgia 30912, United States
| | - Pooyan Makvandi
- Istituto
Italiano di Tecnologia, Centre for Micro-BioRobotics, viale Rinaldo Piaggio 34, 56025 Pontedera, Pisa Italy
- Department
of Medical Nanotechnology, Faculty of Advanced Technologies in Medicine, Iran University of Medical Sciences, 14496-14535 Tehran, Iran
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Hazekawa M, Nishinakagawa T, Kawakubo-Yasukochi T, Nakashima M. Glypican-3 gene silencing for ovarian cancer using siRNA-PLGA hybrid micelles in a murine peritoneal dissemination model. J Pharmacol Sci 2019; 139:231-239. [DOI: 10.1016/j.jphs.2019.01.009] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2018] [Revised: 01/20/2019] [Accepted: 01/29/2019] [Indexed: 01/31/2023] Open
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