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Suzuki T, Conant A, Jung Y, Bax R, Antonissen A, Chen W, Yu G, Ioffe YJ, Wang C, Unternaehrer JJ. A Stem-like Patient-Derived Ovarian Cancer Model of Platinum Resistance Reveals Dissociation of Stemness and Resistance. Int J Mol Sci 2024; 25:3843. [PMID: 38612653 PMCID: PMC11011340 DOI: 10.3390/ijms25073843] [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: 02/26/2024] [Revised: 03/22/2024] [Accepted: 03/25/2024] [Indexed: 04/14/2024] Open
Abstract
To understand chemoresistance in the context of cancer stem cells (CSC), a cisplatin resistance model was developed using a high-grade serous ovarian cancer patient-derived, cisplatin-sensitive sample, PDX4. As a molecular subtype-specific stem-like cell line, PDX4 was selected for its representative features, including its histopathological and BRCA2 mutation status, and exposed to cisplatin in vitro. In the cisplatin-resistant cells, transcriptomics were carried out, and cell morphology, protein expression, and functional status were characterized. Additionally, potential signaling pathways involved in cisplatin resistance were explored. Our findings reveal the presence of distinct molecular signatures and phenotypic changes in cisplatin-resistant PDX4 compared to their sensitive counterparts. Surprisingly, we observed that chemoresistance was not inherently linked with increased stemness. In fact, although resistant cells expressed a combination of EMT and stemness markers, functional assays revealed that they were less proliferative, migratory, and clonogenic-features indicative of an underlying complex mechanism for cell survival. Furthermore, DNA damage tolerance and cellular stress management pathways were enriched. This novel, syngeneic model provides a valuable platform for investigating the underlying mechanisms of cisplatin resistance in a clinically relevant context, contributing to the development of targeted therapies tailored to combat resistance in stem-like ovarian cancer.
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Affiliation(s)
- Tise Suzuki
- Division of Biochemistry, Department of Basic Sciences, Loma Linda University, Loma Linda, CA 92354, USA
| | - Ashlyn Conant
- Division of Biochemistry, Department of Basic Sciences, Loma Linda University, Loma Linda, CA 92354, USA
| | - Yeonkyu Jung
- Division of Biochemistry, Department of Basic Sciences, Loma Linda University, Loma Linda, CA 92354, USA
- Department of Biology, California State University San Bernardino, San Bernardino, CA 92407, USA
| | - Ryan Bax
- Division of Biochemistry, Department of Basic Sciences, Loma Linda University, Loma Linda, CA 92354, USA
| | - Ashley Antonissen
- Division of Biochemistry, Department of Basic Sciences, Loma Linda University, Loma Linda, CA 92354, USA
- Department of Biology, California State University San Bernardino, San Bernardino, CA 92407, USA
| | - Wanqiu Chen
- Division of Biochemistry, Department of Basic Sciences, Loma Linda University, Loma Linda, CA 92354, USA
- Center for Genomics, Loma Linda University, Loma Linda, CA 92354, USA
| | - Gary Yu
- Department of Population and Family Health, Mailman School of Public Health, Columbia University, New York, NY 10032, USA
| | - Yevgeniya J Ioffe
- Division of Gynecologic Oncology, Department of Gynecology and Obstetrics, Loma Linda University Medical Center, Loma Linda, CA 92354, USA
| | - Charles Wang
- Division of Biochemistry, Department of Basic Sciences, Loma Linda University, Loma Linda, CA 92354, USA
- Center for Genomics, Loma Linda University, Loma Linda, CA 92354, USA
| | - Juli J Unternaehrer
- Division of Biochemistry, Department of Basic Sciences, Loma Linda University, Loma Linda, CA 92354, USA
- Division of Gynecologic Oncology, Department of Gynecology and Obstetrics, Loma Linda University Medical Center, Loma Linda, CA 92354, USA
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Wang Y, Lin Y, Wu S, Sun J, Meng Y, Jin E, Kong D, Duan G, Bei S, Fan Z, Wu G, Hao L, Song S, Tang B, Zhao W. BioKA: a curated and integrated biomarker knowledgebase for animals. Nucleic Acids Res 2024; 52:D1121-D1130. [PMID: 37843156 PMCID: PMC10767812 DOI: 10.1093/nar/gkad873] [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] [Received: 08/15/2023] [Revised: 09/19/2023] [Accepted: 09/29/2023] [Indexed: 10/17/2023] Open
Abstract
Biomarkers play an important role in various area such as personalized medicine, drug development, clinical care, and molecule breeding. However, existing animals' biomarker resources predominantly focus on human diseases, leaving a significant gap in non-human animal disease understanding and breeding research. To address this limitation, we present BioKA (Biomarker Knowledgebase for Animals, https://ngdc.cncb.ac.cn/bioka), a curated and integrated knowledgebase encompassing multiple animal species, diseases/traits, and annotated resources. Currently, BioKA houses 16 296 biomarkers associated with 951 mapped diseases/traits across 31 species from 4747 references, including 11 925 gene/protein biomarkers, 1784 miRNA biomarkers, 1043 mutation biomarkers, 773 metabolic biomarkers, 357 circRNA biomarkers and 127 lncRNA biomarkers. Furthermore, BioKA integrates various annotations such as GOs, protein structures, protein-protein interaction networks, miRNA targets and so on, and constructs an interactive knowledge network of biomarkers including circRNA-miRNA-mRNA associations, lncRNA-miRNA associations and protein-protein associations, which is convenient for efficient data exploration. Moreover, BioKA provides detailed information on 308 breeds/strains of 13 species, and homologous annotations for 8784 biomarkers across 16 species, and offers three online application tools. The comprehensive knowledge provided by BioKA not only advances human disease research but also contributes to a deeper understanding of animal diseases and supports livestock breeding.
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Affiliation(s)
- Yibo Wang
- National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yihao Lin
- National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Sicheng Wu
- National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jiani Sun
- National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yuyan Meng
- National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Enhui Jin
- National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Demian Kong
- National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Guangya Duan
- National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Shaoqi Bei
- Qilu University of Technology (Shandong Academy of Sciences), Shandong 250353, China
| | - Zhuojing Fan
- National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
| | - Gangao Wu
- National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
| | - Lili Hao
- National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
| | - Shuhui Song
- National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
| | - Bixia Tang
- National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
| | - Wenming Zhao
- National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
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Liu Y, Wang H. Biomarkers and targeted therapy for cancer stem cells. Trends Pharmacol Sci 2024; 45:56-66. [PMID: 38071088 PMCID: PMC10842814 DOI: 10.1016/j.tips.2023.11.006] [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: 11/02/2023] [Revised: 11/16/2023] [Accepted: 11/16/2023] [Indexed: 01/07/2024]
Abstract
Cancer stem cells (CSCs) are a small subpopulation of cancer cells with capabilities of self-renewal, differentiation, and tumorigenicity, and play a critical role in driving tumor heterogeneity that evolves insensitivity to therapeutics. For these reasons, extensive efforts have been made to identify and target CSCs to potentially improve the antitumor efficacy of therapeutics. While progress has been made to uncover certain CSC-associated biomarkers, the identification of CSC-specific markers, especially the targetable ones, remains a significant challenge. Here we provide an overview of the unique signaling and metabolic pathways of CSCs, summarize existing CSC biomarkers and CSC-targeted therapies, and discuss strategies to further differentiate CSCs from non-stem cancer cells and healthy cells for the development of enhanced CSC-targeted therapies.
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Affiliation(s)
- Yusheng Liu
- Department of Materials Science and Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Hua Wang
- Department of Materials Science and Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA; Cancer Center at Illinois (CCIL), Urbana, IL 61801, USA; Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA; Carle College of Medicine, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA; Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA; Materials Research Laboratory, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA; Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA.
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Cheng L, Li S, He K, Kang Y, Li T, Li C, Zhang Y, Zhang W, Huang Y. Melatonin regulates cancer migration and stemness and enhances the anti-tumour effect of cisplatin. J Cell Mol Med 2023. [PMID: 37307404 PMCID: PMC10399526 DOI: 10.1111/jcmm.17809] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Revised: 05/29/2023] [Accepted: 06/01/2023] [Indexed: 06/14/2023] Open
Abstract
Melatonin, a lipophilic hormone released from the pineal gland, has oncostatic effects on various types of cancers. However, its cancer treatment potential needs to be improved by deciphering its corresponding mechanisms of action and optimising therapeutic strategy. In the present study, melatonin inhibited gastric cancer cell migration and soft agar colony formation. Magnetic-activated cell sorting was applied to isolate CD133+ cancer stem cells. Gene expression analysis showed that melatonin lowered the upregulation of LC3-II expression in CD133+ cells compared to CD133- cells. Several long non-coding RNAs and many components in the canonical Wnt signalling pathway were altered in melatonin-treated cells. In addition, knockdown of long non-coding RNA H19 enhanced the expression of pro-apoptotic genes, Bax and Bak, induced by melatonin treatment. Combinatorial treatment with melatonin and cisplatin was investigated to improve the applicability of melatonin as an anticancer therapy. Combinatorial treatment increased the apoptosis rate and induced G0/G1 cell cycle arrest. Melatonin can regulate migration and stemness in gastric cancer cells by modifying many signalling pathways. Combinatorial treatment with melatonin and cisplatin has the potential to improve the therapeutic efficacy of both.
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Affiliation(s)
- Linglin Cheng
- College of Life and Health Sciences, Northeastern University, Shenyang, China
| | - Shubo Li
- Liaoning Center for Animal Disease Control and Prevention, Liaoning Agricultural Development Service Center, Shenyang, China
| | - Kailun He
- College of Life and Health Sciences, Northeastern University, Shenyang, China
| | - Ye Kang
- Department of Pathology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Tianye Li
- College of Life and Health Sciences, Northeastern University, Shenyang, China
| | - Chunting Li
- College of Life and Health Sciences, Northeastern University, Shenyang, China
| | - Yi Zhang
- College of Life and Health Sciences, Northeastern University, Shenyang, China
| | - Wanlu Zhang
- College of Life and Health Sciences, Northeastern University, Shenyang, China
| | - Yongye Huang
- College of Life and Health Sciences, Northeastern University, Shenyang, China
- Key Laboratory of Bioresource Research and Development of Liaoning Province, College of Life and Health Sciences, Northeastern University, Shenyang, China
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