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van Zyl E, Peneycad C, Perehiniak E, McKay BC. Cyclin-dependent kinase inhibitor 1 plays a more prominent role than activating transcription factor 4 or the p53 tumour suppressor in thapsigargin-induced G1 arrest. PeerJ 2023; 11:e16683. [PMID: 38130926 PMCID: PMC10734451 DOI: 10.7717/peerj.16683] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Accepted: 11/24/2023] [Indexed: 12/23/2023] Open
Abstract
Background Thapsigargin (Tg) is a compound that inhibits the SERCA calcium transporter leading to decreased endoplasmic reticulum (ER) Ca2+ levels. Many ER chaperones are required for proper folding of membrane-associated and secreted proteins, and they are Ca2+ dependent. Therefore, Tg leads to the accumulation of misfolded proteins in the ER, activating the unfolded protein response (UPR) to help restore homeostasis. Tg reportedly induces cell cycle arrest and apoptosis in many cell types but how these changes are linked to the UPR remains unclear. The activating transcription factor 4 (ATF4) plays a key role in regulating ER stress-induced gene expression so we sought to determine if ATF4 is required for Tg-induced cell cycle arrest and apoptosis using ATF4-deficient cells. Methods Two-parameter flow cytometric analysis of DNA replication and DNA content was used to assess the effects of Tg on cell cycle distribution in isogenic HCT116-derived cell lines either expressing or lacking ATF4. For comparison, we similarly assessed the Tg response in isogenic cell lines deleted of the p53 tumour suppressor and the p53-regulated p21WAF1 cyclin-dependent kinase inhibitor important in G1 and G2 arrests induced by DNA damage. Results Tg led to a large depletion of the S phase population with a prominent increase in the proportion of HCT116 cells in the G1 phase of the cell cycle. Importantly, this effect was largely independent of ATF4. We found that loss of p21WAF1 but not p53 permitted Tg treated cells to enter S phase and synthesize DNA. Therefore, p21WAF1plays an important role in these Tg-induced cell cycle alterations while ATF4 and p53 do not. Remarkably, the ATF4-, p53-and p21WAF1-deficient cell lines were all more sensitive to Tg-induced apoptosis. Taken together, p21WAF1 plays a larger role in regulating Tg-induced G1 and G2 arrests than ATF4 or p53 but these proteins similarly contribute to protection from Tg-induced apoptosis. This work highlights the complex network of stress responses that are activated in response to ER stress.
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Affiliation(s)
- Erin van Zyl
- Department of Biology, Carleton University, Ottawa, ON, Canada
| | - Claire Peneycad
- Department of Biology, Carleton University, Ottawa, ON, Canada
| | - Evan Perehiniak
- Department of Biology, Carleton University, Ottawa, ON, Canada
| | - Bruce C. McKay
- Department of Biology, Carleton University, Ottawa, ON, Canada
- Institute of Biochemistry, Carleton University, Ottawa, ON, Canada
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Abstract
Dysregulated RNA splicing is a molecular feature that characterizes almost all tumour types. Cancer-associated splicing alterations arise from both recurrent mutations and altered expression of trans-acting factors governing splicing catalysis and regulation. Cancer-associated splicing dysregulation can promote tumorigenesis via diverse mechanisms, contributing to increased cell proliferation, decreased apoptosis, enhanced migration and metastatic potential, resistance to chemotherapy and evasion of immune surveillance. Recent studies have identified specific cancer-associated isoforms that play critical roles in cancer cell transformation and growth and demonstrated the therapeutic benefits of correcting or otherwise antagonizing such cancer-associated mRNA isoforms. Clinical-grade small molecules that modulate or inhibit RNA splicing have similarly been developed as promising anticancer therapeutics. Here, we review splicing alterations characteristic of cancer cell transcriptomes, dysregulated splicing's contributions to tumour initiation and progression, and existing and emerging approaches for targeting splicing for cancer therapy. Finally, we discuss the outstanding questions and challenges that must be addressed to translate these findings into the clinic.
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Affiliation(s)
- Robert K Bradley
- Computational Biology Program, Public Health Sciences Division and Basic Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, USA.
| | - Olga Anczuków
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA.
- Department of Genetics and Genome Sciences, UConn Health, Farmington, CT, USA.
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Lee AQ, Konishi H, Duong C, Yoshida S, Davis RR, Van Dyke JE, Ijiri M, McLaughlin B, Kim K, Li Y, Beckett L, Nitin N, McPherson JD, Tepper CG, Satake N. A distinct subpopulation of leukemia initiating cells in acute precursor B lymphoblastic leukemia: quiescent phenotype and unique transcriptomic profile. Front Oncol 2022; 12:972323. [PMID: 36212452 PMCID: PMC9533407 DOI: 10.3389/fonc.2022.972323] [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: 06/18/2022] [Accepted: 08/24/2022] [Indexed: 02/01/2023] Open
Abstract
In leukemia, a distinct subpopulation of cancer-initiating cells called leukemia stem cells (LSCs) is believed to drive population expansion and tumor growth. Failing to eliminate LSCs may result in disease relapse regardless of the amount of non-LSCs destroyed. The first step in targeting and eliminating LSCs is to identify and characterize them. Acute precursor B lymphoblastic leukemia (B-ALL) cells derived from patients were incubated with fluorescent glucose analog 2-(N-(7-Nitrobenz-2-oxa-1, 3-diazol-4-yl) Amino)-2-Deoxyglucose (NBDG) and sorted based on NBDG uptake. Cell subpopulations defined by glucose uptake were then serially transplanted into mice and evaluated for leukemia initiating capacity. Gene expression profiles of these cells were characterized using RNA-Sequencing (RNA-Seq). A distinct population of NBDG-low cells was identified in patient B-ALL samples. These cells are a small population (1.92% of the entire leukemia population), have lower HLA expression, and are smaller in size (4.0 to 7.0 μm) than the rest of the leukemia population. All mice transplanted with NBDG-low cells developed leukemia between 5 and 14 weeks, while those transplanted with NBDG-high cells did not develop leukemia (p ≤ 0.0001-0.002). Serial transplantation of the NBDG-low mouse model resulted in successful leukemia development. NBDG-medium (NBDG-med) populations also developed leukemia. Interestingly, comprehensive molecular characterization of NBDG-low and NBDG-med cells from patient-derived xenograft (PDX) models using RNA-Seq revealed a distinct profile of 2,162 differentially-expressed transcripts (DETs) (p<0.05) with 70.6% down-regulated in NBDG-low cells. Hierarchical clustering of DETs showed distinct segregation of NBDG-low from NBDG-med and NBDG-high groups with marked transcription expression alterations in the NBDG-low group consistent with cancer survival. In conclusion, A unique subpopulation of cells with low glucose uptake (NBDG-low) in B-ALL was discovered. These cells, despite their quiescence characteristics, once transplanted in mice, showed potent leukemia initiating capacity. Although NBDG-med cells also initiated leukemia, gene expression profiling revealed a distinct signature that clearly distinguishes NBDG-low cells from NBDG-med and the rest of the leukemia populations. These results suggest that NBDG-low cells may represent quiescent LSCs. These cells can be activated in the appropriate environment in vivo, showing leukemia initiating capacity. Our study provides insight into the biologic mechanisms of B-ALL initiation and survival.
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Affiliation(s)
- Alex Q. Lee
- Department of Pediatrics, University of California (UC) Davis School of Medicine, Sacramento, CA, United States
| | - Hiroaki Konishi
- Department of Pediatrics, University of California (UC) Davis School of Medicine, Sacramento, CA, United States
| | - Connie Duong
- Department of Pediatrics, University of California (UC) Davis School of Medicine, Sacramento, CA, United States
| | - Sakiko Yoshida
- Department of Pediatrics, University of California (UC) Davis School of Medicine, Sacramento, CA, United States
| | - Ryan R. Davis
- Genomics Shared Resource, University of California (UC) Davis Comprehensive Cancer Center, Sacramento, CA, United States
| | - Jonathan E. Van Dyke
- Flow Cytometry Shared Resource, University of California (UC) Davis Comprehensive Cancer Center, Sacramento, CA, United States
| | - Masami Ijiri
- Department of Pediatrics, University of California (UC) Davis School of Medicine, Sacramento, CA, United States
| | - Bridget McLaughlin
- Flow Cytometry Shared Resource, University of California (UC) Davis Comprehensive Cancer Center, Sacramento, CA, United States
| | - Kyoungmi Kim
- Department of Public Health Sciences, Division of Biostatistics, University of California (UC) Davis, Davis, CA, United States
| | - Yueju Li
- Department of Public Health Sciences, Division of Biostatistics, University of California (UC) Davis, Davis, CA, United States
| | - Laurel Beckett
- Department of Public Health Sciences, Division of Biostatistics, University of California (UC) Davis, Davis, CA, United States
| | - Nitin Nitin
- Departments of Food Science & Technology and Biological & Agricultural Engineering, University of California (UC) Davis, Davis, CA, United States
| | - John D. McPherson
- Genomics Shared Resource, University of California (UC) Davis Comprehensive Cancer Center, Sacramento, CA, United States,Department of Biochemistry and Molecular Medicine, University of California (UC) Davis School of Medicine, Sacramento, CA, United States
| | - Clifford G. Tepper
- Genomics Shared Resource, University of California (UC) Davis Comprehensive Cancer Center, Sacramento, CA, United States,Department of Biochemistry and Molecular Medicine, University of California (UC) Davis School of Medicine, Sacramento, CA, United States,*Correspondence: Noriko Satake, ; Clifford G. Tepper,
| | - Noriko Satake
- Department of Pediatrics, University of California (UC) Davis School of Medicine, Sacramento, CA, United States,*Correspondence: Noriko Satake, ; Clifford G. Tepper,
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Xu Y, Zhao J, Ren Y, Wang X, Lyu Y, Xie B, Sun Y, Yuan X, Liu H, Yang W, Fu Y, Yu Y, Liu Y, Mu R, Li C, Xu J, Deng H. Derivation of totipotent-like stem cells with blastocyst-like structure forming potential. Cell Res 2022; 32:513-529. [PMID: 35508506 PMCID: PMC9160264 DOI: 10.1038/s41422-022-00668-0] [Citation(s) in RCA: 50] [Impact Index Per Article: 25.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2022] [Accepted: 04/08/2022] [Indexed: 12/27/2022] Open
Abstract
It is challenging to derive totipotent stem cells in vitro that functionally and molecularly resemble cells from totipotent embryos. Here, we report that a chemical cocktail enables the derivation of totipotent-like stem cells, designated as totipotent potential stem (TPS) cells, from 2-cell mouse embryos and extended pluripotent stem cells, and that these TPS cells can be stably maintained long term in vitro. TPS cells shared features with 2-cell mouse embryos in terms of totipotency markers, transcriptome, chromatin accessibility and DNA methylation patterns. In vivo chimera formation assays show that these cells have embryonic and extraembryonic developmental potentials at the single-cell level. Moreover, TPS cells can be induced into blastocyst-like structures resembling preimplantation mouse blastocysts. Mechanistically, inhibition of HDAC1/2 and DOT1L activity and activation of RARγ signaling are important for inducing and maintaining totipotent features of TPS cells. Our study opens up a new path toward fully capturing totipotent stem cells in vitro.
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Affiliation(s)
- Yaxing Xu
- MOE Engineering Research Center of Regenerative Medicine, School of Basic Medical Sciences, State Key Laboratory of Natural and Biomimetic Drugs, Peking University Health Science Center and the MOE Key Laboratory of Cell Proliferation and Differentiation, College of Life Sciences, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China
| | - Jingru Zhao
- MOE Engineering Research Center of Regenerative Medicine, School of Basic Medical Sciences, State Key Laboratory of Natural and Biomimetic Drugs, Peking University Health Science Center and the MOE Key Laboratory of Cell Proliferation and Differentiation, College of Life Sciences, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China
| | - Yixuan Ren
- MOE Engineering Research Center of Regenerative Medicine, School of Basic Medical Sciences, State Key Laboratory of Natural and Biomimetic Drugs, Peking University Health Science Center and the MOE Key Laboratory of Cell Proliferation and Differentiation, College of Life Sciences, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China
| | - Xuyang Wang
- MOE Engineering Research Center of Regenerative Medicine, School of Basic Medical Sciences, State Key Laboratory of Natural and Biomimetic Drugs, Peking University Health Science Center and the MOE Key Laboratory of Cell Proliferation and Differentiation, College of Life Sciences, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China
| | - Yulin Lyu
- School of Life Sciences, Center for Bioinformatics, Center for Statistical Science, Peking University, Beijing, China
| | - Bingqing Xie
- MOE Engineering Research Center of Regenerative Medicine, School of Basic Medical Sciences, State Key Laboratory of Natural and Biomimetic Drugs, Peking University Health Science Center and the MOE Key Laboratory of Cell Proliferation and Differentiation, College of Life Sciences, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China
| | - Yiming Sun
- School of Life Sciences, Center for Bioinformatics, Center for Statistical Science, Peking University, Beijing, China
| | - Xiandun Yuan
- Department of Rheumatology and Immunology, Peking University Third Hospital, Beijing, China
| | - Haiyin Liu
- MOE Engineering Research Center of Regenerative Medicine, School of Basic Medical Sciences, State Key Laboratory of Natural and Biomimetic Drugs, Peking University Health Science Center and the MOE Key Laboratory of Cell Proliferation and Differentiation, College of Life Sciences, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China
| | - Weifeng Yang
- Beijing Vitalstar Biotechnology Co., Ltd, Beijing, China
| | - Yenan Fu
- Program for Cancer and Cell Biology, Department of Human Anatomy, Histology and Embryology, School of Basic Medical Sciences, PKU International Cancer Institute; MOE Key Laboratory of Carcinogenesis and Translational Research and State Key Laboratory of Natural and Biomimetic Drugs, Peking University Health Science Center, Beijing, China
| | - Yu Yu
- Program for Cancer and Cell Biology, Department of Human Anatomy, Histology and Embryology, School of Basic Medical Sciences, PKU International Cancer Institute; MOE Key Laboratory of Carcinogenesis and Translational Research and State Key Laboratory of Natural and Biomimetic Drugs, Peking University Health Science Center, Beijing, China
| | - Yinan Liu
- Department of Cell Biology, School of Basic Medical Sciences, Peking University Stem Cell Research Center, Peking University Health Science Center, Peking University, Beijing, China
| | - Rong Mu
- Department of Rheumatology and Immunology, Peking University Third Hospital, Beijing, China
| | - Cheng Li
- School of Life Sciences, Center for Bioinformatics, Center for Statistical Science, Peking University, Beijing, China.
| | - Jun Xu
- Department of Cell Biology, School of Basic Medical Sciences, Peking University Stem Cell Research Center, Peking University Health Science Center, Peking University, Beijing, China.
| | - Hongkui Deng
- MOE Engineering Research Center of Regenerative Medicine, School of Basic Medical Sciences, State Key Laboratory of Natural and Biomimetic Drugs, Peking University Health Science Center and the MOE Key Laboratory of Cell Proliferation and Differentiation, College of Life Sciences, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China.
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Genetic Drivers of Head and Neck Squamous Cell Carcinoma: Aberrant Splicing Events, Mutational Burden, HPV Infection and Future Targets. Genes (Basel) 2021; 12:genes12030422. [PMID: 33804181 PMCID: PMC7998272 DOI: 10.3390/genes12030422] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Revised: 02/16/2021] [Accepted: 03/11/2021] [Indexed: 12/15/2022] Open
Abstract
Head and neck cancers include cancers that originate from a variety of locations. These include the mouth, nasal cavity, throat, sinuses, and salivary glands. These cancers are the sixth most diagnosed cancers worldwide. Due to the tissues they arise from, they are collectively named head and neck squamous cell carcinomas (HNSCC). The most important risk factors for head and neck cancers are infection with human papillomavirus (HPV), tobacco use and alcohol consumption. The genetic basis behind the development and progression of HNSCC includes aberrant non-coding RNA levels. However, one of the most important differences between healthy tissue and HNSCC tissue is changes in the alternative splicing of genes that play a vital role in processes that can be described as the hallmarks of cancer. These changes in the expression profile of alternately spliced mRNA give rise to various protein isoforms. These protein isoforms, alternate methylation of proteins, and changes in the transcription of non-coding RNAs (ncRNA) can be used as diagnostic or prognostic markers and as targets for the development of new therapeutic agents. This review aims to describe changes in alternative splicing and ncRNA patterns that contribute to the development and progression of HNSCC. It will also review the use of the changes in gene expression as biomarkers or as the basis for the development of new therapies.
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