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Subbalakshmi AR, Ramisetty S, Mohanty A, Pareek S, Do D, Shrestha S, Khan A, Talwar N, Tan T, Vishnubhotla P, Singhal SS, Salgia R, Kulkarni P. Phenotypic Plasticity and Cancer: A System Biology Perspective. J Clin Med 2024; 13:4302. [PMID: 39124569 PMCID: PMC11313222 DOI: 10.3390/jcm13154302] [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: 05/20/2024] [Revised: 07/01/2024] [Accepted: 07/18/2024] [Indexed: 08/12/2024] Open
Abstract
Epithelial-to-mesenchymal transition (EMT) is a major axis of phenotypic plasticity not only in diseased conditions such as cancer metastasis and fibrosis but also during normal development and wound healing. Yet-another important axis of plasticity with metastatic implications includes the cancer stem cell (CSCs) and non-CSC transitions. However, in both processes, epithelial (E) and mesenchymal (M) phenotypes are not merely binary states. Cancer cells acquire a spectrum of phenotypes with traits, properties, and markers of both E and M phenotypes, giving rise to intermediary hybrid (E/M) phenotypes. E/M cells play an important role in tumor initiation, metastasis, and disease progression in multiple cancers. Furthermore, the hybrid phenotypes also play a major role in causing therapeutic resistance in cancer. Here, we discuss how a systems biology perspective on the problem, which is implicit in the 'Team Medicine' approach outlined in the theme of this Special Issue of The Journal of Clinical Medicine and includes an interdisciplinary team of experts, is more likely to shed new light on EMT in cancer and help us to identify novel therapeutics and strategies to target phenotypic plasticity in cancer.
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Affiliation(s)
- Ayalur Raghu Subbalakshmi
- Department of Medical Oncology and Therapeutics Research, City of Hope National Medical Center, Duarte, CA 91010, USA; (A.R.S.)
| | - Sravani Ramisetty
- Department of Medical Oncology and Therapeutics Research, City of Hope National Medical Center, Duarte, CA 91010, USA; (A.R.S.)
| | - Atish Mohanty
- Department of Medical Oncology and Therapeutics Research, City of Hope National Medical Center, Duarte, CA 91010, USA; (A.R.S.)
| | - Siddhika Pareek
- Department of Medical Oncology and Therapeutics Research, City of Hope National Medical Center, Duarte, CA 91010, USA; (A.R.S.)
| | - Dana Do
- Department of Medical Oncology and Therapeutics Research, City of Hope National Medical Center, Duarte, CA 91010, USA; (A.R.S.)
| | - Sagun Shrestha
- Department of Medical Oncology and Therapeutics Research, City of Hope Phoenix, Goodyear, AZ 85338, USA
| | - Ajaz Khan
- Department of Medical Oncology and Therapeutics Research, City of Hope Chicago, Zion, IL 60099, USA
| | - Neel Talwar
- Department of Medical Oncology and Therapeutics Research, City of Hope San Bernardino Road, Upland, CA 91786, USA
| | - Tingting Tan
- Department of Medical Oncology and Therapeutics Research, City of Hope Avocado Avenue, Newport Beach, CA 92660, USA
| | - Priya Vishnubhotla
- Department of Medical Oncology and Therapeutics Research, City of Hope Atlanta, Newnan, GA 30265, USA
| | - Sharad S. Singhal
- Department of Medical Oncology and Therapeutics Research, City of Hope National Medical Center, Duarte, CA 91010, USA; (A.R.S.)
| | - Ravi Salgia
- Department of Medical Oncology and Therapeutics Research, City of Hope National Medical Center, Duarte, CA 91010, USA; (A.R.S.)
| | - Prakash Kulkarni
- Department of Medical Oncology and Therapeutics Research, City of Hope National Medical Center, Duarte, CA 91010, USA; (A.R.S.)
- Department of Systems Biology, City of Hope National Medical Center, Duarte, CA 91010, USA
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2
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Li J, Hilimire TA, Liu Y, Wang L, Liang J, Gyorffy B, Sikirzhytski V, Ji H, Zhang L, Cheng C, Ding X, Kerr KR, Dowling CE, Chumanevich AA, Mack ZT, Schools GP, Lim CU, Ellis L, Zi X, Porter DC, Broude EV, McInnes C, Wilding G, Lilly MB, Roninson IB, Chen M. Mediator kinase inhibition reverses castration resistance of advanced prostate cancer. J Clin Invest 2024; 134:e176709. [PMID: 38546787 DOI: 10.1172/jci176709] [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: 10/24/2023] [Accepted: 03/22/2024] [Indexed: 04/17/2024] Open
Abstract
Mediator kinases CDK19 and CDK8, pleiotropic regulators of transcriptional reprogramming, are differentially regulated by androgen signaling, but both kinases are upregulated in castration-resistant prostate cancer (CRPC). Genetic or pharmacological inhibition of CDK8 and CDK19 reverses the castration-resistant phenotype and restores the sensitivity of CRPC xenografts to androgen deprivation in vivo. Prolonged CDK8/19 inhibitor treatment combined with castration not only suppressed the growth of CRPC xenografts but also induced tumor regression and cures. Transcriptomic analysis revealed that Mediator kinase inhibition amplified and modulated the effects of castration on gene expression, disrupting CRPC adaptation to androgen deprivation. Mediator kinase inactivation in tumor cells also affected stromal gene expression, indicating that Mediator kinase activity in CRPC molded the tumor microenvironment. The combination of castration and Mediator kinase inhibition downregulated the MYC pathway, and Mediator kinase inhibition suppressed a MYC-driven CRPC tumor model even without castration. CDK8/19 inhibitors showed efficacy in patient-derived xenograft models of CRPC, and a gene signature of Mediator kinase activity correlated with tumor progression and overall survival in clinical samples of metastatic CRPC. These results indicate that Mediator kinases mediated androgen-independent in vivo growth of CRPC, supporting the development of CDK8/19 inhibitors for the treatment of this presently incurable disease.
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Affiliation(s)
- Jing Li
- Department of Drug Discovery and Biomedical Sciences, College of Pharmacy, University of South Carolina, Columbia, South Carolina, USA
| | - Thomas A Hilimire
- Department of Drug Discovery and Biomedical Sciences, College of Pharmacy, University of South Carolina, Columbia, South Carolina, USA
- Senex Biotechnology Inc., Columbia, South Carolina, USA
| | - Yueying Liu
- Division of Hematology-Oncology, Medical University of South Carolina, Charleston, South Carolina, USA
| | - Lili Wang
- Department of Drug Discovery and Biomedical Sciences, College of Pharmacy, University of South Carolina, Columbia, South Carolina, USA
| | - Jiaxin Liang
- Department of Drug Discovery and Biomedical Sciences, College of Pharmacy, University of South Carolina, Columbia, South Carolina, USA
| | - Balazs Gyorffy
- Department of Bioinformatics, Semmelweis University, Budapest, Hungary
- Department of Biophysics, Medical School, University of Pecs, Pecs, Hungary
| | - Vitali Sikirzhytski
- Department of Drug Discovery and Biomedical Sciences, College of Pharmacy, University of South Carolina, Columbia, South Carolina, USA
| | - Hao Ji
- Department of Drug Discovery and Biomedical Sciences, College of Pharmacy, University of South Carolina, Columbia, South Carolina, USA
| | - Li Zhang
- Department of Drug Discovery and Biomedical Sciences, College of Pharmacy, University of South Carolina, Columbia, South Carolina, USA
| | - Chen Cheng
- Department of Drug Discovery and Biomedical Sciences, College of Pharmacy, University of South Carolina, Columbia, South Carolina, USA
| | - Xiaokai Ding
- Department of Drug Discovery and Biomedical Sciences, College of Pharmacy, University of South Carolina, Columbia, South Carolina, USA
| | - Kendall R Kerr
- Department of Drug Discovery and Biomedical Sciences, College of Pharmacy, University of South Carolina, Columbia, South Carolina, USA
| | - Charles E Dowling
- Department of Drug Discovery and Biomedical Sciences, College of Pharmacy, University of South Carolina, Columbia, South Carolina, USA
| | - Alexander A Chumanevich
- Department of Drug Discovery and Biomedical Sciences, College of Pharmacy, University of South Carolina, Columbia, South Carolina, USA
| | - Zachary T Mack
- Department of Drug Discovery and Biomedical Sciences, College of Pharmacy, University of South Carolina, Columbia, South Carolina, USA
| | - Gary P Schools
- Department of Drug Discovery and Biomedical Sciences, College of Pharmacy, University of South Carolina, Columbia, South Carolina, USA
| | - Chang-Uk Lim
- Department of Drug Discovery and Biomedical Sciences, College of Pharmacy, University of South Carolina, Columbia, South Carolina, USA
| | - Leigh Ellis
- Center for Prostate Disease Research, Murtha Cancer Center Research Program, Department of Surgery, Uniformed Services University of the Health Sciences; Walter Reed National Military Medical Center; Henry M. Jackson Foundation for the Advancement of Military Medicine Inc.; Bethesda, Maryland, USA
- Genitourinary Malignancies Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Xiaolin Zi
- Departments of Urology and Pharmaceutical Sciences, University of California, Irvine, California, USA
| | | | - Eugenia V Broude
- Department of Drug Discovery and Biomedical Sciences, College of Pharmacy, University of South Carolina, Columbia, South Carolina, USA
| | - Campbell McInnes
- Department of Drug Discovery and Biomedical Sciences, College of Pharmacy, University of South Carolina, Columbia, South Carolina, USA
| | | | - Michael B Lilly
- Division of Hematology-Oncology, Medical University of South Carolina, Charleston, South Carolina, USA
| | - Igor B Roninson
- Department of Drug Discovery and Biomedical Sciences, College of Pharmacy, University of South Carolina, Columbia, South Carolina, USA
| | - Mengqian Chen
- Department of Drug Discovery and Biomedical Sciences, College of Pharmacy, University of South Carolina, Columbia, South Carolina, USA
- Senex Biotechnology Inc., Columbia, South Carolina, USA
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3
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Schultz L, Gondim A, Ruan S. Gompertz models with periodical treatment and applications to prostate cancer. MATHEMATICAL BIOSCIENCES AND ENGINEERING : MBE 2024; 21:4104-4116. [PMID: 38549320 DOI: 10.3934/mbe.2024181] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/02/2024]
Abstract
In this paper, Gompertz type models are proposed to understand the temporal tumor volume behavior of prostate cancer when a periodical treatment is provided. Existence, uniqueness, and stability of periodic solutions are established. The models are used to fit the data and to forecast the tumor growth behavior based on prostate cancer treatments using capsaicin and docetaxel anticancer drugs. Numerical simulations show that the combination of capsaicin and docetaxel is the most efficient treatment of prostate cancer.
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Affiliation(s)
- Leonardo Schultz
- Department of Mathematics, University of Miami, 1365 Memorial Drive, Coral Gables, FL 33146, USA
| | - Antonio Gondim
- Department of Mathematics, University of Miami, 1365 Memorial Drive, Coral Gables, FL 33146, USA
| | - Shigui Ruan
- Department of Mathematics, University of Miami, 1365 Memorial Drive, Coral Gables, FL 33146, USA
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Naponelli V, Bettuzzi S, Venerando A. Editorial: Challenges in the prevention of prostate cancer. Front Oncol 2023; 13:1342733. [PMID: 38125941 PMCID: PMC10731738 DOI: 10.3389/fonc.2023.1342733] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Accepted: 11/24/2023] [Indexed: 12/23/2023] Open
Affiliation(s)
- Valeria Naponelli
- Department of Medicine and Surgery, University of Parma, Plesso Biotecnologico Integrato, Parma, Italy
| | - Saverio Bettuzzi
- Department of Medicine and Surgery, University of Parma, Plesso Biotecnologico Integrato, Parma, Italy
| | - Andrea Venerando
- Department of Agricultural, Food, Environmental and Animal Sciences, University of Udine, Udine, Italy
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5
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Hodara E, Mades A, Swartz L, Iqbal M, Xu T, Bsteh D, Farnham P, Rhie S, Goldkorn A. m 6A epitranscriptome analysis reveals differentially methylated transcripts that drive early chemoresistance in bladder cancer. NAR Cancer 2023; 5:zcad054. [PMID: 38023731 PMCID: PMC10653028 DOI: 10.1093/narcan/zcad054] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Revised: 10/24/2023] [Accepted: 11/07/2023] [Indexed: 12/01/2023] Open
Abstract
N 6-Methyladenosine (m6A) RNA modifications dynamically regulate messenger RNA processing, differentiation and cell fate. Given these functions, we hypothesized that m6A modifications play a role in the transition to chemoresistance. To test this, we took an agnostic discovery approach anchored directly to chemoresistance rather than to any particular m6A effector protein. Specifically, we used methyl-RNA immunoprecipitation followed by sequencing (MeRIP-seq) in parallel with RNA sequencing to identify gene transcripts that were both differentially methylated and differentially expressed between cisplatin-sensitive and cisplatin-resistant bladder cancer (BC) cells. We filtered and prioritized these genes using clinical and functional database tools, and then validated several of the top candidates via targeted quantitative polymerase chain reaction (qPCR) and MeRIP-PCR. In cisplatin-resistant cells, SLC7A11 transcripts had decreased methylation associated with decreased m6A reader YTHDF3 binding, prolonged RNA stability, and increased RNA and protein levels, leading to reduced ferroptosis and increased survival. Consistent with this, cisplatin-sensitive BC cell lines and patient-derived organoids exposed to cisplatin for as little as 48 h exhibited similar mechanisms of SLC7A11 upregulation and chemoresistance, trends that were also reflected in public cancer survival databases. Collectively, these findings highlight epitranscriptomic plasticity as a mechanism of rapid chemoresistance and a potential therapeutic target.
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Affiliation(s)
- Emmanuelle Hodara
- Division of Medical Oncology, Department of Medicine, Keck School of Medicine of USC and Norris Comprehensive Cancer Center, Los Angeles, CA 90033, USA
| | - Aubree Mades
- Division of Medical Oncology, Department of Medicine, Keck School of Medicine of USC and Norris Comprehensive Cancer Center, Los Angeles, CA 90033, USA
| | - Lisa Swartz
- Division of Medical Oncology, Department of Medicine, Keck School of Medicine of USC and Norris Comprehensive Cancer Center, Los Angeles, CA 90033, USA
| | - Maheen Iqbal
- Division of Medical Oncology, Department of Medicine, Keck School of Medicine of USC and Norris Comprehensive Cancer Center, Los Angeles, CA 90033, USA
| | - Tong Xu
- Division of Medical Oncology, Department of Medicine, Keck School of Medicine of USC and Norris Comprehensive Cancer Center, Los Angeles, CA 90033, USA
| | - Daniel Bsteh
- Division of Medical Oncology, Department of Medicine, Keck School of Medicine of USC and Norris Comprehensive Cancer Center, Los Angeles, CA 90033, USA
| | - Peggy J Farnham
- Department of Biochemistry and Molecular Medicine, Keck School of Medicine of USC, Los Angeles, CA 90033, USA
| | - Suhn K Rhie
- Department of Biochemistry and Molecular Medicine, Keck School of Medicine of USC, Los Angeles, CA 90033, USA
| | - Amir Goldkorn
- Division of Medical Oncology, Department of Medicine, Keck School of Medicine of USC and Norris Comprehensive Cancer Center, Los Angeles, CA 90033, USA
- Department of Biochemistry and Molecular Medicine, Keck School of Medicine of USC, Los Angeles, CA 90033, USA
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Modanwal S, Mishra A, Mishra N. An integrative analysis of GEO data to identify possible therapeutic biomarkers of prostate cancer and targeting potential protein through Zea mays phytochemicals by virtual screening approaches. J Biomol Struct Dyn 2023:1-21. [PMID: 38217083 DOI: 10.1080/07391102.2023.2283163] [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: 08/01/2023] [Accepted: 11/08/2023] [Indexed: 01/14/2024]
Abstract
Prostate cancer (PC) is a prevalent type of cancer among men. Delaying the treatment of patients with upgraded or upstaged cancer may lead to unmanageable circumstances. The aim of this study is to contribute to the finding of biomarkers that are specific to PC and identify drug candidates derived from plants. The information about cancer is critical for clinicians to make decisions about patient treatment in the era of precision medicine. Advances in genomics technology have opened up new possibilities for identifying genes that are associated with cancer, including PC. This study identifies novel differentially expressed genes for PC. The seven PC microarray datasets were selected from the National Center for Biotechnology Information (NCBI)/Gene Expression Omnibus (GEO). The differentially expressed genes (DEGs) were found based on a fold change of |logFC| ≥ 1 and an adjusted p-value of <0.05. The DEGs were further studied using several bioinformatics tools, including STRING, CytoHubba, SRplot, Coremine Medical database, FunRich and GeneMANIA, cBioPortal. The six new potential biomarkers, GAGE2A, GAGE12G, GAGE2E, GAGE13, GAGE12F and CSAG1 were identified. These biomarkers are associated with biological processes (BPs) such as cell division, and gene expression regulation, so these genes may have a crucial role in PC progression and may serve as potential biomarkers for PC. A total of 497 phytochemicals from corn plants have been screened against the target protein and found LTS0176591 as the best lead molecule with docking score of -6.31 kcal/mol. Further, molecular mechanics-generalized born surface area (MM-GBSA), molecular dynamics simulation, principal component analysis (PCA), free energy landscape (FEL) and molecular mechanics-Poisson-Boltzmann surface area (MM-PBSA) were carried out to validate the findings.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Shristi Modanwal
- Department of Applied Science, Indian Institute of Information Technology Allahabad, Prayagraj, India
| | - Ashutosh Mishra
- Department of Applied Science, Indian Institute of Information Technology Allahabad, Prayagraj, India
| | - Nidhi Mishra
- Department of Applied Science, Indian Institute of Information Technology Allahabad, Prayagraj, India
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7
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Jain P, Pillai M, Duddu AS, Somarelli JA, Goyal Y, Jolly MK. Dynamical hallmarks of cancer: Phenotypic switching in melanoma and epithelial-mesenchymal plasticity. Semin Cancer Biol 2023; 96:48-63. [PMID: 37788736 DOI: 10.1016/j.semcancer.2023.09.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Revised: 09/24/2023] [Accepted: 09/28/2023] [Indexed: 10/05/2023]
Abstract
Phenotypic plasticity was recently incorporated as a hallmark of cancer. This plasticity can manifest along many interconnected axes, such as stemness and differentiation, drug-sensitive and drug-resistant states, and between epithelial and mesenchymal cell-states. Despite growing acceptance for phenotypic plasticity as a hallmark of cancer, the dynamics of this process remains poorly understood. In particular, the knowledge necessary for a predictive understanding of how individual cancer cells and populations of cells dynamically switch their phenotypes in response to the intensity and/or duration of their current and past environmental stimuli remains far from complete. Here, we present recent investigations of phenotypic plasticity from a systems-level perspective using two exemplars: epithelial-mesenchymal plasticity in carcinomas and phenotypic switching in melanoma. We highlight how an integrated computational-experimental approach has helped unravel insights into specific dynamical hallmarks of phenotypic plasticity in different cancers to address the following questions: a) how many distinct cell-states or phenotypes exist?; b) how reversible are transitions among these cell-states, and what factors control the extent of reversibility?; and c) how might cell-cell communication be able to alter rates of cell-state switching and enable diverse patterns of phenotypic heterogeneity? Understanding these dynamic features of phenotypic plasticity may be a key component in shifting the paradigm of cancer treatment from reactionary to a more predictive, proactive approach.
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Affiliation(s)
- Paras Jain
- Department of Bioengineering, Indian Institute of Science, Bangalore 560012, India
| | - Maalavika Pillai
- Department of Bioengineering, Indian Institute of Science, Bangalore 560012, India; Department of Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA; Center for Synthetic Biology, Northwestern University, Chicago, IL 60611, USA
| | | | - Jason A Somarelli
- Department of Medicine, Duke Cancer Institute, Duke University, Durham, NC 27710, USA
| | - Yogesh Goyal
- Department of Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA; Center for Synthetic Biology, Northwestern University, Chicago, IL 60611, USA; Robert H. Lurie Comprehensive Cancer Center, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Mohit Kumar Jolly
- Department of Bioengineering, Indian Institute of Science, Bangalore 560012, India.
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Kulkarni P, Mohanty A, Ramisetty S, Duvivier H, Khan A, Shrestha S, Tan T, Merla A, El-Hajjaoui M, Malhotra J, Singhal S, Salgia R. A Nexus between Genetic and Non-Genetic Mechanisms Guides KRAS Inhibitor Resistance in Lung Cancer. Biomolecules 2023; 13:1587. [PMID: 38002269 PMCID: PMC10668935 DOI: 10.3390/biom13111587] [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: 09/11/2023] [Revised: 10/16/2023] [Accepted: 10/24/2023] [Indexed: 11/26/2023] Open
Abstract
Several studies in the last few years have determined that, in contrast to the prevailing dogma that drug resistance is simply due to Darwinian evolution-the selection of mutant clones in response to drug treatment-non-genetic changes can also lead to drug resistance whereby tolerant, reversible phenotypes are eventually relinquished by resistant, irreversible phenotypes. Here, using KRAS as a paradigm, we illustrate how this nexus between genetic and non-genetic mechanisms enables cancer cells to evade the harmful effects of drug treatment. We discuss how the conformational dynamics of the KRAS molecule, that includes intrinsically disordered regions, is influenced by the binding of the targeted therapies contributing to conformational noise and how this noise impacts the interaction of KRAS with partner proteins to rewire the protein interaction network. Thus, in response to drug treatment, reversible drug-tolerant phenotypes emerge via non-genetic mechanisms that eventually enable the emergence of irreversible resistant clones via genetic mutations. Furthermore, we also discuss the recent data demonstrating how combination therapy can help alleviate KRAS drug resistance in lung cancer, and how new treatment strategies based on evolutionary principles may help minimize or even preclude the emergence of drug resistance.
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Affiliation(s)
- Prakash Kulkarni
- Department of Medical Oncology and Experimental Therapeutics, City of Hope National Medical Center, 1500 Duarte Rd., Duarte, CA 91010, USA; (A.M.); (S.R.); (J.M.); (S.S.)
- Department of Systems Biology, City of Hope National Medical Center, 1500 Duarte Rd., Duarte, CA 91010, USA
| | - Atish Mohanty
- Department of Medical Oncology and Experimental Therapeutics, City of Hope National Medical Center, 1500 Duarte Rd., Duarte, CA 91010, USA; (A.M.); (S.R.); (J.M.); (S.S.)
| | - Sravani Ramisetty
- Department of Medical Oncology and Experimental Therapeutics, City of Hope National Medical Center, 1500 Duarte Rd., Duarte, CA 91010, USA; (A.M.); (S.R.); (J.M.); (S.S.)
| | - Herbert Duvivier
- Department of Medical Oncology, City of Hope Atlanta, 600 Celebrate Life Parkway, Newnan, GA 30265, USA;
| | - Ajaz Khan
- Department of Medical Oncology, City of Hope Chicago, 2520 Elisha Avenue, Zion, IL 60099, USA;
| | - Sagun Shrestha
- Department of Medical Oncology, City of Hope Phoenix, 14200 West Celebrate Life Way, Goodyear, AZ 85338, USA;
| | - Tingting Tan
- Department of Medical Oncology, City of Hope National Medical Center, Newport Beach Fashion Island, Duarte, CA 92660, USA;
| | - Amartej Merla
- Department of Medical Oncology, City of Hope, Lancaster, CA 93534, USA;
| | - Michelle El-Hajjaoui
- Department of Medical Oncology, City of Hope Medical Center, West Covina, CA 91790, USA;
| | - Jyoti Malhotra
- Department of Medical Oncology and Experimental Therapeutics, City of Hope National Medical Center, 1500 Duarte Rd., Duarte, CA 91010, USA; (A.M.); (S.R.); (J.M.); (S.S.)
| | - Sharad Singhal
- Department of Medical Oncology and Experimental Therapeutics, City of Hope National Medical Center, 1500 Duarte Rd., Duarte, CA 91010, USA; (A.M.); (S.R.); (J.M.); (S.S.)
| | - Ravi Salgia
- Department of Medical Oncology and Experimental Therapeutics, City of Hope National Medical Center, 1500 Duarte Rd., Duarte, CA 91010, USA; (A.M.); (S.R.); (J.M.); (S.S.)
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9
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Mohanty A, Nam A, Srivastava S, Jones J, Lomenick B, Singhal SS, Guo L, Cho H, Li A, Behal A, Mirzapoiazova T, Massarelli E, Koczywas M, Arvanitis LD, Walser T, Villaflor V, Hamilton S, Mambetsariev I, Sattler M, Nasser MW, Jain M, Batra SK, Soldi R, Sharma S, Fakih M, Mohanty SK, Mainan A, Wu X, Chen Y, He Y, Chou TF, Roy S, Orban J, Kulkarni P, Salgia R. Acquired resistance to KRAS G12C small-molecule inhibitors via genetic/nongenetic mechanisms in lung cancer. SCIENCE ADVANCES 2023; 9:eade3816. [PMID: 37831779 PMCID: PMC10575592 DOI: 10.1126/sciadv.ade3816] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Accepted: 09/08/2023] [Indexed: 10/15/2023]
Abstract
Inherent or acquired resistance to sotorasib poses a substantialt challenge for NSCLC treatment. Here, we demonstrate that acquired resistance to sotorasib in isogenic cells correlated with increased expression of integrin β4 (ITGB4), a component of the focal adhesion complex. Silencing ITGB4 in tolerant cells improved sotorasib sensitivity, while overexpressing ITGB4 enhanced tolerance to sotorasib by supporting AKT-mTOR bypass signaling. Chronic treatment with sotorasib induced WNT expression and activated the WNT/β-catenin signaling pathway. Thus, silencing both ITGB4 and β-catenin significantly improved sotorasib sensitivity in tolerant, acquired, and inherently resistant cells. In addition, the proteasome inhibitor carfilzomib (CFZ) exhibited synergism with sotorasib by down-regulating ITGB4 and β-catenin expression. Furthermore, adagrasib phenocopies the combination effect of sotorasib and CFZ by suppressing KRAS activity and inhibiting cell cycle progression in inherently resistant cells. Overall, our findings unveil previously unrecognized nongenetic mechanisms underlying resistance to sotorasib and propose a promising treatment strategy to overcome resistance.
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Affiliation(s)
- Atish Mohanty
- Department of Medical Oncology and Experimental Therapeutics, City of Hope National Medical Center, Duarte, CA 91010, USA
| | - Arin Nam
- Department of Medical Oncology and Experimental Therapeutics, City of Hope National Medical Center, Duarte, CA 91010, USA
| | - Saumya Srivastava
- Department of Medical Oncology and Experimental Therapeutics, City of Hope National Medical Center, Duarte, CA 91010, USA
| | - Jeff Jones
- Proteome Exploration Laboratory, California Institute of Technology, Pasadena, CA 91125, USA
| | - Brett Lomenick
- Proteome Exploration Laboratory, California Institute of Technology, Pasadena, CA 91125, USA
| | - Sharad S. Singhal
- Department of Medical Oncology and Experimental Therapeutics, City of Hope National Medical Center, Duarte, CA 91010, USA
| | - Linlin Guo
- Department of Medical Oncology and Experimental Therapeutics, City of Hope National Medical Center, Duarte, CA 91010, USA
| | - Hyejin Cho
- Integrative Genomics Core, Beckman Research Institute, City of Hope, Monrovia, CA 91016, USA
| | - Aimin Li
- Department of Pathology, City of Hope National Medical Center, Duarte, CA 91010,USA
| | - Amita Behal
- Department of Medical Oncology and Experimental Therapeutics, City of Hope National Medical Center, Duarte, CA 91010, USA
| | - Tamara Mirzapoiazova
- Department of Medical Oncology and Experimental Therapeutics, City of Hope National Medical Center, Duarte, CA 91010, USA
| | - Erminia Massarelli
- Department of Medical Oncology and Experimental Therapeutics, City of Hope National Medical Center, Duarte, CA 91010, USA
| | - Marianna Koczywas
- Department of Medical Oncology and Experimental Therapeutics, City of Hope National Medical Center, Duarte, CA 91010, USA
| | | | - Tonya Walser
- Department of Medical Oncology and Experimental Therapeutics, City of Hope National Medical Center, Duarte, CA 91010, USA
| | - Victoria Villaflor
- Department of Medical Oncology and Experimental Therapeutics, City of Hope National Medical Center, Duarte, CA 91010, USA
| | - Stanley Hamilton
- Department of Pathology, City of Hope National Medical Center, Duarte, CA 91010,USA
| | - Isa Mambetsariev
- Department of Medical Oncology and Experimental Therapeutics, City of Hope National Medical Center, Duarte, CA 91010, USA
| | - Martin Sattler
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA
| | - Mohd W. Nasser
- Biochemistry and Molecular Biology, University of Nebraska Medical Center, Omaha, NE 68198, USA
| | - Maneesh Jain
- Biochemistry and Molecular Biology, University of Nebraska Medical Center, Omaha, NE 68198, USA
| | - Surinder K. Batra
- Biochemistry and Molecular Biology, University of Nebraska Medical Center, Omaha, NE 68198, USA
| | - Raffaella Soldi
- Applied Cancer Research and Drug Discovery Division, Translational Genomics Research Institute (TGen) of City of Hope, Phoenix, AZ 850043, USA
| | - Sunil Sharma
- Applied Cancer Research and Drug Discovery Division, Translational Genomics Research Institute (TGen) of City of Hope, Phoenix, AZ 850043, USA
| | - Marwan Fakih
- Department of Medical Oncology and Experimental Therapeutics, City of Hope National Medical Center, Duarte, CA 91010, USA
| | - Saswat Kumar Mohanty
- Department of Chemical Sciences, Indian Institute of Science Education and Research Kolkata, Mohanpur, West Bengal 741246, India
| | - Avijit Mainan
- Department of Chemical Sciences, Indian Institute of Science Education and Research Kolkata, Mohanpur, West Bengal 741246, India
| | - Xiwei Wu
- Integrative Genomics Core, Beckman Research Institute, City of Hope, Monrovia, CA 91016, USA
| | - Yihong Chen
- W. M. Keck Laboratory for Structural Biology, University of Maryland Institute for Bioscience and Biotechnology Research, Rockville, MD 20850, USA
| | - Yanan He
- W. M. Keck Laboratory for Structural Biology, University of Maryland Institute for Bioscience and Biotechnology Research, Rockville, MD 20850, USA
| | - Tsui-Fen Chou
- Proteome Exploration Laboratory, California Institute of Technology, Pasadena, CA 91125, USA
| | - Susmita Roy
- Department of Chemical Sciences, Indian Institute of Science Education and Research Kolkata, Mohanpur, West Bengal 741246, India
| | - John Orban
- W. M. Keck Laboratory for Structural Biology, University of Maryland Institute for Bioscience and Biotechnology Research, Rockville, MD 20850, USA
- Department of Chemistry and Biochemistry, University of Maryland, College Park, MD 20742, USA
| | - Prakash Kulkarni
- Department of Medical Oncology and Experimental Therapeutics, City of Hope National Medical Center, Duarte, CA 91010, USA
| | - Ravi Salgia
- Department of Medical Oncology and Experimental Therapeutics, City of Hope National Medical Center, Duarte, CA 91010, USA
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10
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Burggren WW, Mendez-Sanchez JF. "Bet hedging" against climate change in developing and adult animals: roles for stochastic gene expression, phenotypic plasticity, epigenetic inheritance and adaptation. Front Physiol 2023; 14:1245875. [PMID: 37869716 PMCID: PMC10588650 DOI: 10.3389/fphys.2023.1245875] [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: 06/23/2023] [Accepted: 09/12/2023] [Indexed: 10/24/2023] Open
Abstract
Animals from embryos to adults experiencing stress from climate change have numerous mechanisms available for enhancing their long-term survival. In this review we consider these options, and how viable they are in a world increasingly experiencing extreme weather associated with climate change. A deeply understood mechanism involves natural selection, leading to evolution of new adaptations that help cope with extreme and stochastic weather events associated with climate change. While potentially effective at staving off environmental challenges, such adaptations typically occur very slowly and incrementally over evolutionary time. Consequently, adaptation through natural selection is in most instances regarded as too slow to aid survival in rapidly changing environments, especially when considering the stochastic nature of extreme weather events associated with climate change. Alternative mechanisms operating in a much shorter time frame than adaptation involve the rapid creation of alternate phenotypes within a life cycle or a few generations. Stochastic gene expression creates multiple phenotypes from the same genotype even in the absence of environmental cues. In contrast, other mechanisms for phenotype change that are externally driven by environmental clues include well-understood developmental phenotypic plasticity (variation, flexibility), which can enable rapid, within-generation changes. Increasingly appreciated are epigenetic influences during development leading to rapid phenotypic changes that can also immediately be very widespread throughout a population, rather than confined to a few individuals as in the case of favorable gene mutations. Such epigenetically-induced phenotypic plasticity can arise rapidly in response to stressors within a generation or across a few generations and just as rapidly be "sunsetted" when the stressor dissipates, providing some capability to withstand environmental stressors emerging from climate change. Importantly, survival mechanisms resulting from adaptations and developmental phenotypic plasticity are not necessarily mutually exclusive, allowing for classic "bet hedging". Thus, the appearance of multiple phenotypes within a single population provides for a phenotype potentially optimal for some future environment. This enhances survival during stochastic extreme weather events associated with climate change. Finally, we end with recommendations for future physiological experiments, recommending in particular that experiments investigating phenotypic flexibility adopt more realistic protocols that reflect the stochastic nature of weather.
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Affiliation(s)
- Warren W. Burggren
- Developmental Integrative Biology Group, Department of Biological Sciences, University of North Texas, Denton, TX, United States
| | - Jose Fernando Mendez-Sanchez
- Laboratorio de Ecofisiología Animal, Departamento de Biología, Facultad de Ciencias, Universidad Autónoma del Estado de México, Toluca, Mexico
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11
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Groves SM, Quaranta V. Quantifying cancer cell plasticity with gene regulatory networks and single-cell dynamics. FRONTIERS IN NETWORK PHYSIOLOGY 2023; 3:1225736. [PMID: 37731743 PMCID: PMC10507267 DOI: 10.3389/fnetp.2023.1225736] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Accepted: 08/25/2023] [Indexed: 09/22/2023]
Abstract
Phenotypic plasticity of cancer cells can lead to complex cell state dynamics during tumor progression and acquired resistance. Highly plastic stem-like states may be inherently drug-resistant. Moreover, cell state dynamics in response to therapy allow a tumor to evade treatment. In both scenarios, quantifying plasticity is essential for identifying high-plasticity states or elucidating transition paths between states. Currently, methods to quantify plasticity tend to focus on 1) quantification of quasi-potential based on the underlying gene regulatory network dynamics of the system; or 2) inference of cell potency based on trajectory inference or lineage tracing in single-cell dynamics. Here, we explore both of these approaches and associated computational tools. We then discuss implications of each approach to plasticity metrics, and relevance to cancer treatment strategies.
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Affiliation(s)
- Sarah M. Groves
- Department of Pharmacology, Vanderbilt University, Nashville, TN, United States
| | - Vito Quaranta
- Department of Pharmacology, Vanderbilt University, Nashville, TN, United States
- Department of Biochemistry, Vanderbilt University, Nashville, TN, United States
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12
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Cassidy T. A Continuation Technique for Maximum Likelihood Estimators in Biological Models. Bull Math Biol 2023; 85:90. [PMID: 37650951 PMCID: PMC10471725 DOI: 10.1007/s11538-023-01200-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Accepted: 08/14/2023] [Indexed: 09/01/2023]
Abstract
Estimating model parameters is a crucial step in mathematical modelling and typically involves minimizing the disagreement between model predictions and experimental data. This calibration data can change throughout a study, particularly if modelling is performed simultaneously with the calibration experiments, or during an on-going public health crisis as in the case of the COVID-19 pandemic. Consequently, the optimal parameter set, or maximal likelihood estimator (MLE), is a function of the experimental data set. Here, we develop a numerical technique to predict the evolution of the MLE as a function of the experimental data. We show that, when considering perturbations from an initial data set, our approach is significantly more computationally efficient that re-fitting model parameters while producing acceptable model fits to the updated data. We use the continuation technique to develop an explicit functional relationship between fit model parameters and experimental data that can be used to measure the sensitivity of the MLE to experimental data. We then leverage this technique to select between model fits with similar information criteria, a priori determine the experimental measurements to which the MLE is most sensitive, and suggest additional experiment measurements that can resolve parameter uncertainty.
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Affiliation(s)
- Tyler Cassidy
- School of Mathematics, University of Leeds, Leeds, LS2 9JT, UK.
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13
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Kulkarni P, Salgia R, Rangarajan G. Intrinsically disordered proteins and conformational noise: The hypothesis a decade later. iScience 2023; 26:107109. [PMID: 37408690 PMCID: PMC10319216 DOI: 10.1016/j.isci.2023.107109] [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] [Indexed: 07/07/2023] Open
Abstract
Phenotypic plasticity is the ability of individual genotypes to produce different phenotypes in response to environmental perturbations. We previously postulated how conformational noise emanating from conformational dynamics of intrinsically disordered proteins (IDPs) which is distinct from transcriptional noise, can contribute to phenotypic switching by rewiring the cellular protein interaction network. Since most transcription factors are IDPs, we posited that conformational noise is an integral component of transcriptional noise implying that IDPs may amplify total noise in the system either stochastically or in response to environmental changes. Here, we review progress in elucidating the details of the hypothesis. We highlight empirical evidence supporting the hypothesis, discuss conceptual advances that underscore its fundamental importance and implications, and identify areas for future investigations.
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Affiliation(s)
- Prakash Kulkarni
- Department of Medical Oncology and Therapeutics Research, City of Hope National Medical Center, Duarte, CA, USA
- Department of Systems Biology, City of Hope National Medical Center, Duarte, CA, USA
| | - Ravi Salgia
- Department of Medical Oncology and Therapeutics Research, City of Hope National Medical Center, Duarte, CA, USA
| | - Govindan Rangarajan
- Department of Mathematics, Indian Institute of Science, Bangalore 560012, India
- Center for Neuroscience, Indian Institute of Science, Bangalore 560012, India
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14
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Phua TJ. Understanding human aging and the fundamental cell signaling link in age-related diseases: the middle-aging hypovascularity hypoxia hypothesis. FRONTIERS IN AGING 2023; 4:1196648. [PMID: 37384143 PMCID: PMC10293850 DOI: 10.3389/fragi.2023.1196648] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Accepted: 05/23/2023] [Indexed: 06/30/2023]
Abstract
Aging-related hypoxia, oxidative stress, and inflammation pathophysiology are closely associated with human age-related carcinogenesis and chronic diseases. However, the connection between hypoxia and hormonal cell signaling pathways is unclear, but such human age-related comorbid diseases do coincide with the middle-aging period of declining sex hormonal signaling. This scoping review evaluates the relevant interdisciplinary evidence to assess the systems biology of function, regulation, and homeostasis in order to discern and decipher the etiology of the connection between hypoxia and hormonal signaling in human age-related comorbid diseases. The hypothesis charts the accumulating evidence to support the development of a hypoxic milieu and oxidative stress-inflammation pathophysiology in middle-aged individuals, as well as the induction of amyloidosis, autophagy, and epithelial-to-mesenchymal transition in aging-related degeneration. Taken together, this new approach and strategy can provide the clarity of concepts and patterns to determine the causes of declining vascularity hemodynamics (blood flow) and physiological oxygenation perfusion (oxygen bioavailability) in relation to oxygen homeostasis and vascularity that cause hypoxia (hypovascularity hypoxia). The middle-aging hypovascularity hypoxia hypothesis could provide the mechanistic interface connecting the endocrine, nitric oxide, and oxygen homeostasis signaling that is closely linked to the progressive conditions of degenerative hypertrophy, atrophy, fibrosis, and neoplasm. An in-depth understanding of these intrinsic biological processes of the developing middle-aged hypoxia could provide potential new strategies for time-dependent therapies in maintaining healthspan for healthy lifestyle aging, medical cost savings, and health system sustainability.
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Affiliation(s)
- Teow J. Phua
- Molecular Medicine, NSW Health Pathology, John Hunter Hospital, Newcastle, NSW, Australia
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15
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Gromova T, Gehred ND, Vondriska TM. Single-cell transcriptomes in the heart: when every epigenome counts. Cardiovasc Res 2023; 119:64-78. [PMID: 35325060 DOI: 10.1093/cvr/cvac040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/06/2021] [Revised: 02/03/2022] [Accepted: 02/14/2022] [Indexed: 11/13/2022] Open
Abstract
The response of an organ to stimuli emerges from the actions of individual cells. Recent cardiac single-cell RNA-sequencing studies of development, injury, and reprogramming have uncovered heterogeneous populations even among previously well-defined cell types, raising questions about what level of experimental resolution corresponds to disease-relevant, tissue-level phenotypes. In this review, we explore the biological meaning behind this cellular heterogeneity by undertaking an exhaustive analysis of single-cell transcriptomics in the heart (including a comprehensive, annotated compendium of studies published to date) and evaluating new models for the cardiac function that have emerged from these studies (including discussion and schematics that depict new hypotheses in the field). We evaluate the evidence to support the biological actions of newly identified cell populations and debate questions related to the role of cell-to-cell variability in development and disease. Finally, we present emerging epigenomic approaches that, when combined with single-cell RNA-sequencing, can resolve basic mechanisms of gene regulation and variability in cell phenotype.
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Affiliation(s)
- Tatiana Gromova
- Department of Anesthesiology & Perioperative Medicine, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
- Department of Medicine/Cardiology, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
- Department of Physiology, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
| | - Natalie D Gehred
- Department of Anesthesiology & Perioperative Medicine, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
- Department of Medicine/Cardiology, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
- Department of Physiology, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
| | - Thomas M Vondriska
- Department of Anesthesiology & Perioperative Medicine, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
- Department of Medicine/Cardiology, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
- Department of Physiology, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
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16
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Evans R, Ramisetty S, Kulkarni P, Weninger K. Illuminating Intrinsically Disordered Proteins with Integrative Structural Biology. Biomolecules 2023; 13:124. [PMID: 36671509 PMCID: PMC9856150 DOI: 10.3390/biom13010124] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Revised: 01/01/2023] [Accepted: 01/04/2023] [Indexed: 01/11/2023] Open
Abstract
Intense study of intrinsically disordered proteins (IDPs) did not begin in earnest until the late 1990s when a few groups, working independently, convinced the community that these 'weird' proteins could have important functions. Over the past two decades, it has become clear that IDPs play critical roles in a multitude of biological phenomena with prominent examples including coordination in signaling hubs, enabling gene regulation, and regulating ion channels, just to name a few. One contributing factor that delayed appreciation of IDP functional significance is the experimental difficulty in characterizing their dynamic conformations. The combined application of multiple methods, termed integrative structural biology, has emerged as an essential approach to understanding IDP phenomena. Here, we review some of the recent applications of the integrative structural biology philosophy to study IDPs.
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Affiliation(s)
- Rachel Evans
- Department of Physics, North Carolina State University, Raleigh, NC 27695, USA
| | - Sravani Ramisetty
- Department of Medical Oncology and Therapeutics Research, City of Hope National Medical Center, Duarte, CA 91010, USA
| | - Prakash Kulkarni
- Department of Medical Oncology and Therapeutics Research, City of Hope National Medical Center, Duarte, CA 91010, USA
- Department of Systems Biology, City of Hope National Medical Center, Duarte, CA 91010, USA
| | - Keith Weninger
- Department of Physics, North Carolina State University, Raleigh, NC 27695, USA
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17
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Bryl R, Piwocka O, Kawka E, Mozdziak P, Kempisty B, Knopik-Skrocka A. Cancer Stem Cells-The Insight into Non-Coding RNAs. Cells 2022; 11:cells11223699. [PMID: 36429127 PMCID: PMC9688207 DOI: 10.3390/cells11223699] [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] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Revised: 11/11/2022] [Accepted: 11/15/2022] [Indexed: 11/23/2022] Open
Abstract
Since their initial identification three decades ago, there has been extensive research regarding cancer stem cells (CSCs). It is important to consider the biology of cancer stem cells with a particular focus on their phenotypic and metabolic plasticity, the most important signaling pathways, and non-coding RNAs (ncRNAs) regulating these cellular entities. Furthermore, the current status of therapeutic approaches against CSCs is an important consideration regarding employing the technology to improve human health. Cancer stem cells have claimed to be one of the most important group of cells for the development of several common cancers as they dictate features, such as resistance to radio- and chemotherapy, metastasis, and secondary tumor formation. Therapies which could target these cells may develop into an effective strategy for tumor eradication and a hope for patients for whom this disease remains uncurable.
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Affiliation(s)
- Rut Bryl
- Section of Regenerative Medicine and Cancer Research, Natural Sciences Club, Faculty of Biology, Adam Mickiewicz University, 61-614 Poznań, Poland
| | - Oliwia Piwocka
- Section of Regenerative Medicine and Cancer Research, Natural Sciences Club, Faculty of Biology, Adam Mickiewicz University, 61-614 Poznań, Poland
- Department of Electroradiology, Poznan University of Medical Sciences, 61-701 Poznań, Poland
- Doctoral School, Poznan University of Medical Sciences, 61-701 Poznań, Poland
| | - Emilia Kawka
- Section of Regenerative Medicine and Cancer Research, Natural Sciences Club, Faculty of Biology, Adam Mickiewicz University, 61-614 Poznań, Poland
| | - Paul Mozdziak
- Prestage Department of Poultry Science, North Carolina State University, Raleigh, NC 27695, USA
| | - Bartosz Kempisty
- Prestage Department of Poultry Science, North Carolina State University, Raleigh, NC 27695, USA
- Department of Human Morphology and Embryology, Division of Anatomy, Medical University of Wrocław, 50-367 Wroclaw, Poland
- Department of Veterinary Surgery, Institute of Veterinary Medicine, Nicolaus Copernicus University, 87-100 Torun, Poland
- Correspondence: or
| | - Agnieszka Knopik-Skrocka
- Section of Regenerative Medicine and Cancer Research, Natural Sciences Club, Faculty of Biology, Adam Mickiewicz University, 61-614 Poznań, Poland
- Department of Cell Biology, Faculty of Biology, Adam Mickiewicz University, 61-614 Poznań, Poland
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18
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Allard P, Papazotos F, Potvin-Trottier L. Microfluidics for long-term single-cell time-lapse microscopy: Advances and applications. Front Bioeng Biotechnol 2022; 10:968342. [PMID: 36312536 PMCID: PMC9597311 DOI: 10.3389/fbioe.2022.968342] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Accepted: 09/21/2022] [Indexed: 11/13/2022] Open
Abstract
Cells are inherently dynamic, whether they are responding to environmental conditions or simply at equilibrium, with biomolecules constantly being made and destroyed. Due to their small volumes, the chemical reactions inside cells are stochastic, such that genetically identical cells display heterogeneous behaviors and gene expression profiles. Studying these dynamic processes is challenging, but the development of microfluidic methods enabling the tracking of individual prokaryotic cells with microscopy over long time periods under controlled growth conditions has led to many discoveries. This review focuses on the recent developments of one such microfluidic device nicknamed the mother machine. We overview the original device design, experimental setup, and challenges associated with this platform. We then describe recent methods for analyzing experiments using automated image segmentation and tracking. We further discuss modifications to the experimental setup that allow for time-varying environmental control, replicating batch culture conditions, cell screening based on their dynamic behaviors, and to accommodate a variety of microbial species. Finally, this review highlights the discoveries enabled by this technology in diverse fields, such as cell-size control, genetic mutations, cellular aging, and synthetic biology.
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Affiliation(s)
- Paige Allard
- Department of Biology, Concordia University, Montréal, QC, Canada
| | - Fotini Papazotos
- Department of Biology, Concordia University, Montréal, QC, Canada
| | - Laurent Potvin-Trottier
- Department of Biology, Concordia University, Montréal, QC, Canada
- Department of Physics, Concordia University, Montréal, QC, Canada
- Centre for Applied Synthetic Biology, Concordia University, Montréal, QC, Canada
- *Correspondence: Laurent Potvin-Trottier,
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19
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Addressing Drug Resistance in Cancer: A Team Medicine Approach. J Clin Med 2022; 11:jcm11195701. [PMID: 36233569 PMCID: PMC9572909 DOI: 10.3390/jcm11195701] [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: 08/30/2022] [Revised: 09/16/2022] [Accepted: 09/23/2022] [Indexed: 12/04/2022] Open
Abstract
Drug resistance remains one of the major impediments to treating cancer. Although many patients respond well initially, resistance to therapy typically ensues. Several confounding factors appear to contribute to this challenge. Here, we first discuss some of the challenges associated with drug resistance. We then discuss how a ‘Team Medicine’ approach, involving an interdisciplinary team of basic scientists working together with clinicians, has uncovered new therapeutic strategies. These strategies, referred to as intermittent or ‘adaptive’ therapy, which are based on eco-evolutionary principles, have met with remarkable success in potentially precluding or delaying the emergence of drug resistance in several cancers. Incorporating such treatment strategies into clinical protocols could potentially enhance the precision of delivering personalized medicine to patients. Furthermore, reaching out to patients in the network of hospitals affiliated with leading academic centers could help them benefit from such innovative treatment options. Finally, lowering the dose of the drug and its frequency (because of intermittent rather than continuous therapy) can also have a significant impact on lowering the toxicity and undesirable side effects of the drugs while lowering the financial burden carried by the patient and insurance providers.
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20
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Cárdenas SD, Reznik CJ, Ranaweera R, Song F, Chung CH, Fertig EJ, Gevertz JL. Model-informed experimental design recommendations for distinguishing intrinsic and acquired targeted therapeutic resistance in head and neck cancer. NPJ Syst Biol Appl 2022; 8:32. [PMID: 36075912 PMCID: PMC9458753 DOI: 10.1038/s41540-022-00244-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2022] [Accepted: 08/05/2022] [Indexed: 11/09/2022] Open
Abstract
The promise of precision medicine has been limited by the pervasive resistance to many targeted therapies for cancer. Inferring the timing (i.e., pre-existing or acquired) and mechanism (i.e., drug-induced) of such resistance is crucial for designing effective new therapeutics. This paper studies cetuximab resistance in head and neck squamous cell carcinoma (HNSCC) using tumor volume data obtained from patient-derived tumor xenografts. We ask if resistance mechanisms can be determined from this data alone, and if not, what data would be needed to deduce the underlying mode(s) of resistance. To answer these questions, we propose a family of mathematical models, with each member of the family assuming a different timing and mechanism of resistance. We present a method for fitting these models to individual volumetric data, and utilize model selection and parameter sensitivity analyses to ask: which member(s) of the family of models best describes HNSCC response to cetuximab, and what does that tell us about the timing and mechanisms driving resistance? We find that along with time-course volumetric data to a single dose of cetuximab, the initial resistance fraction and, in some instances, dose escalation volumetric data are required to distinguish among the family of models and thereby infer the mechanisms of resistance. These findings can inform future experimental design so that we can best leverage the synergy of wet laboratory experimentation and mathematical modeling in the study of novel targeted cancer therapeutics.
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Affiliation(s)
- Santiago D Cárdenas
- Department of Mathematics and Statistics, The College of New Jersey, Ewing, NJ, USA
| | - Constance J Reznik
- Department of Mathematics and Statistics, The College of New Jersey, Ewing, NJ, USA.,Datacor, Inc., Florham Park, NJ, USA
| | - Ruchira Ranaweera
- Department of Head and Neck-Endocrine Oncology, Moffitt Cancer Center, Tampa, FL, USA
| | - Feifei Song
- Department of Head and Neck-Endocrine Oncology, Moffitt Cancer Center, Tampa, FL, USA
| | - Christine H Chung
- Department of Head and Neck-Endocrine Oncology, Moffitt Cancer Center, Tampa, FL, USA
| | - Elana J Fertig
- Convergence Institute, Department of Oncology, Department of Biomedical Engineering, Department of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, MD, USA.
| | - Jana L Gevertz
- Department of Mathematics and Statistics, The College of New Jersey, Ewing, NJ, USA.
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21
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Stochastic population dynamics of cancer stemness and adaptive response to therapies. Essays Biochem 2022; 66:387-398. [PMID: 36073715 DOI: 10.1042/ebc20220038] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Revised: 08/19/2022] [Accepted: 08/22/2022] [Indexed: 02/07/2023]
Abstract
Intratumoral heterogeneity can exist along multiple axes: Cancer stem cells (CSCs)/non-CSCs, drug-sensitive/drug-tolerant states, and a spectrum of epithelial-hybrid-mesenchymal phenotypes. Further, these diverse cell-states can switch reversibly among one another, thereby posing a major challenge to therapeutic efficacy. Therefore, understanding the origins of phenotypic plasticity and heterogeneity remains an active area of investigation. While genomic components (mutations, chromosomal instability) driving heterogeneity have been well-studied, recent reports highlight the role of non-genetic mechanisms in enabling both phenotypic plasticity and heterogeneity. Here, we discuss various processes underlying phenotypic plasticity such as stochastic gene expression, chromatin reprogramming, asymmetric cell division and the presence of multiple stable gene expression patterns ('attractors'). These processes can facilitate a dynamically evolving cell population such that a subpopulation of (drug-tolerant) cells can survive lethal drug exposure and recapitulate population heterogeneity on drug withdrawal, leading to relapse. These drug-tolerant cells can be both pre-existing and also induced by the drug itself through cell-state reprogramming. The dynamics of cell-state transitions both in absence and presence of the drug can be quantified through mathematical models. Such a dynamical systems approach to elucidating patterns of intratumoral heterogeneity by integrating longitudinal experimental data with mathematical models can help design effective combinatorial and/or sequential therapies for better clinical outcomes.
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22
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Islam R, Mishra J, Polavaram NS, Bhattacharya S, Hong Z, Bodas S, Sharma S, Bouska A, Gilbreath T, Said AM, Smith LM, Teply BA, Muders MH, Batra SK, Datta K, Dutta S. Neuropilin-2 axis in regulating secretory phenotype of neuroendocrine-like prostate cancer cells and its implication in therapy resistance. Cell Rep 2022; 40:111097. [PMID: 35858551 PMCID: PMC9362995 DOI: 10.1016/j.celrep.2022.111097] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Revised: 04/06/2022] [Accepted: 06/23/2022] [Indexed: 12/25/2022] Open
Abstract
Neuroendocrine (NE)-like tumors secrete various signaling molecules to establish paracrine communication within the tumor milieu and to create a therapy-resistant environment. It is important to identify molecular mediators that regulate this secretory phenotype in NE-like cancer. The current study highlights the importance of a cell surface molecule, Neuropilin-2 (NRP2), for the secretory function of NE-like prostate cancer (PCa). Our analysis on different patient cohorts suggests that NRP2 is high in NE-like PCa. We have developed cell line models to investigate NRP2's role in NE-like PCa. Our bioinformatics, mass spectrometry, cytokine array, and other supporting experiments reveal that NRP2 regulates robust secretory phenotype in NE-like PCa and controls the secretion of factors promoting cancer cell survival. Depletion of NRP2 reduces the secretion of these factors and makes resistant cancer cells sensitive to chemotherapy in vitro and in vivo. Therefore, targeting NRP2 can revert cellular secretion and sensitize PCa cells toward therapy.
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Affiliation(s)
- Ridwan Islam
- Department of Biochemistry and Molecular Biology, University of Nebraska Medical Center, BCC, Omaha, NE 68198, USA
| | - Juhi Mishra
- Department of Biochemistry and Molecular Biology, University of Nebraska Medical Center, BCC, Omaha, NE 68198, USA
| | - Navatha Shree Polavaram
- Department of Biochemistry and Molecular Biology, University of Nebraska Medical Center, BCC, Omaha, NE 68198, USA
| | - Sreyashi Bhattacharya
- Department of Biochemistry and Molecular Biology, University of Nebraska Medical Center, BCC, Omaha, NE 68198, USA
| | - Zhengdong Hong
- Department of Biochemistry and Molecular Biology, University of Nebraska Medical Center, BCC, Omaha, NE 68198, USA
| | - Sanika Bodas
- Department of Biochemistry and Molecular Biology, University of Nebraska Medical Center, BCC, Omaha, NE 68198, USA
| | - Sunandini Sharma
- Department of Biochemistry and Molecular Biology, University of Nebraska Medical Center, BCC, Omaha, NE 68198, USA
| | - Alyssa Bouska
- Department of Biochemistry and Molecular Biology, University of Nebraska Medical Center, BCC, Omaha, NE 68198, USA
| | - Tyler Gilbreath
- Department of Biochemistry and Molecular Biology, University of Nebraska Medical Center, BCC, Omaha, NE 68198, USA
| | - Ahmed M Said
- Department of Pharmaceutical Organic Chemistry, Faculty of Pharmacy, Helwan University, Ein-Helwan, Helwan, Cairo, Egypt
| | - Lynette M Smith
- Department of Biochemistry and Molecular Biology, University of Nebraska Medical Center, BCC, Omaha, NE 68198, USA
| | - Benjamin A Teply
- Department of Biochemistry and Molecular Biology, University of Nebraska Medical Center, BCC, Omaha, NE 68198, USA
| | - Michael H Muders
- Department of Prostate Cancer Research, Center for Pathology, University of Bonn Medical Center, Bonn, Germany
| | - Surinder K Batra
- Department of Biochemistry and Molecular Biology, University of Nebraska Medical Center, BCC, Omaha, NE 68198, USA
| | - Kaustubh Datta
- Department of Biochemistry and Molecular Biology, University of Nebraska Medical Center, BCC, Omaha, NE 68198, USA.
| | - Samikshan Dutta
- Department of Biochemistry and Molecular Biology, University of Nebraska Medical Center, BCC, Omaha, NE 68198, USA.
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23
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Capp JP, Thomas F. From developmental to atavistic bet-hedging: How cancer cells pervert the exploitation of random single-cell phenotypic fluctuations. Bioessays 2022; 44:e2200048. [PMID: 35839471 DOI: 10.1002/bies.202200048] [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: 02/28/2022] [Revised: 07/05/2022] [Accepted: 07/05/2022] [Indexed: 11/08/2022]
Abstract
Stochastic gene expression plays a leading developmental role through its contribution to cell differentiation. It is also proposed to promote phenotypic diversification in malignant cells. However, it remains unclear if these two forms of cellular bet-hedging are identical or rather display distinct features. Here we argue that bet-hedging phenomena in cancer cells are more similar to those occurring in unicellular organisms than to those of normal metazoan cells. We further propose that the atavistic bet-hedging strategies in cancer originate from a hijacking of the normal developmental bet-hedging of metazoans. Finally, we discuss the constraints that may shape the atavistic bet-hedging strategies of cancer cells.
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Affiliation(s)
- Jean-Pascal Capp
- Toulouse Biotechnology Institute, INSA / University of Toulouse, CNRS, INRAE, Toulouse, France
| | - Frédéric Thomas
- CREEC, UMR IRD 224-CNRS 5290-University of Montpellier, Montpellier, France
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24
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Vipparthi K, Hari K, Chakraborty P, Ghosh S, Patel AK, Ghosh A, Biswas NK, Sharan R, Arun P, Jolly MK, Singh S. Emergence of hybrid states of stem-like cancer cells correlates with poor prognosis in oral cancer. iScience 2022; 25:104317. [PMID: 35602941 PMCID: PMC9114525 DOI: 10.1016/j.isci.2022.104317] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Revised: 03/14/2022] [Accepted: 04/22/2022] [Indexed: 12/26/2022] Open
Abstract
Cancer cell state transitions emerged as powerful mechanisms responsible for drug tolerance and overall poor prognosis; however, evidences were largely missing in oral cancer. Here, by multiplexing phenotypic markers of stem-like cancer cells (SLCCs); CD44, CD24 and aldehyde dehydrogenase (ALDH), we characterized diversity among multiple oral tumor tissues and cell lines. Two distinct patterns of spontaneous transitions with stochastic bidirectional interconversions on ‘ALDH-axis’, and unidirectional non-interconvertible transitions on ‘CD24-axis’ were observed. Interestingly, plastic ‘ALDH-axis’ was harnessed by cells to adapt to a Cisplatin tolerant state. Furthermore, phenotype-specific RNA sequencing suggested the possible maintenance of intermediate hybrid cell states maintaining stemness within the differentiating subpopulations. Importantly, survival analysis with subpopulation-specific gene sets strongly suggested that cell-state transitions may drive non-genetic heterogeneity, resulting in poor prognosis. Therefore, we have described the phenotypic-composition of heterogeneous subpopulations critical for global tumor behavior in oral cancer; which may provide prerequisite knowledge for treatment strategies. Demonstrated population trajectory driven non-genetic heterogeneity in oral cancer Created transition maps for subpopulations using discrete time Markov chain model Demonstrated maintenance of stemness in cells undergoing differentiation Uniquely expressed genes of these subpopulations associated with disease prognosis
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Affiliation(s)
- Kavya Vipparthi
- National Institute of Biomedical Genomics, Kalyani, West Bengal 741251, India
| | - Kishore Hari
- Centre for BioSystems Science and Engineering, India Institute of Science, Bengaluru, Karnataka 560012, India
| | - Priyanka Chakraborty
- Centre for BioSystems Science and Engineering, India Institute of Science, Bengaluru, Karnataka 560012, India
| | - Subhashis Ghosh
- National Institute of Biomedical Genomics, Kalyani, West Bengal 741251, India
| | - Ankit Kumar Patel
- National Institute of Biomedical Genomics, Kalyani, West Bengal 741251, India
| | - Arnab Ghosh
- National Institute of Biomedical Genomics, Kalyani, West Bengal 741251, India
| | - Nidhan Kumar Biswas
- National Institute of Biomedical Genomics, Kalyani, West Bengal 741251, India
| | - Rajeev Sharan
- Head and Neck Surgery, Tata Medical Center, Kolkata, West Bengal 700160, India
| | - Pattatheyil Arun
- Head and Neck Surgery, Tata Medical Center, Kolkata, West Bengal 700160, India
| | - Mohit Kumar Jolly
- Centre for BioSystems Science and Engineering, India Institute of Science, Bengaluru, Karnataka 560012, India
| | - Sandeep Singh
- National Institute of Biomedical Genomics, Kalyani, West Bengal 741251, India
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25
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Ibragimova M, Tsyganov M, Litviakov N. Tumour Stem Cells in Breast Cancer. Int J Mol Sci 2022; 23:ijms23095058. [PMID: 35563449 PMCID: PMC9099719 DOI: 10.3390/ijms23095058] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Revised: 04/27/2022] [Accepted: 04/30/2022] [Indexed: 12/12/2022] Open
Abstract
Tumour stem cells (CSCs) are a self-renewing population that plays important roles in tumour initiation, recurrence, and metastasis. Although the medical literature is extensive, problems with CSC identification and cancer therapy remain. This review provides the main mechanisms of CSC action in breast cancer (BC): CSC markers and signalling pathways, heterogeneity, plasticity, and ecological behaviour. The dynamic heterogeneity of CSCs and the dynamic transitions of CSC− non-CSCs and their significance for metastasis are considered.
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Affiliation(s)
- Marina Ibragimova
- Cancer Research Institute, Tomsk National Research Medical Center, Russian Academy of Sciences, 5, Kooperativny Street, 634050 Tomsk, Russia; (M.T.); (N.L.)
- Laboratory of Genetic Technologies, Siberian State Medical University, 2, Moscow Tract, 634050 Tomsk, Russia
- Biological Institute, National Research Tomsk State University, 36, Lenin, 634050 Tomsk, Russia
- Correspondence:
| | - Matvey Tsyganov
- Cancer Research Institute, Tomsk National Research Medical Center, Russian Academy of Sciences, 5, Kooperativny Street, 634050 Tomsk, Russia; (M.T.); (N.L.)
| | - Nikolai Litviakov
- Cancer Research Institute, Tomsk National Research Medical Center, Russian Academy of Sciences, 5, Kooperativny Street, 634050 Tomsk, Russia; (M.T.); (N.L.)
- Laboratory of Genetic Technologies, Siberian State Medical University, 2, Moscow Tract, 634050 Tomsk, Russia
- Biological Institute, National Research Tomsk State University, 36, Lenin, 634050 Tomsk, Russia
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26
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EMT, Stemness, and Drug Resistance in Biological Context: A 3D Tumor Tissue/In Silico Platform for Analysis of Combinatorial Treatment in NSCLC with Aggressive KRAS-Biomarker Signatures. Cancers (Basel) 2022; 14:cancers14092176. [PMID: 35565305 PMCID: PMC9099837 DOI: 10.3390/cancers14092176] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2022] [Revised: 04/09/2022] [Accepted: 04/15/2022] [Indexed: 11/17/2022] Open
Abstract
Simple Summary The phenotypic transition of tumor cells from epithelial to mesenchymal characteristics is called EMT and is widely discussed in the scientific community as a game changer in drug resistance and metastasis formation. However, clinical studies could not prove the efficacy of EMT-interfering treatments, and in clinical routine, EMT is not investigated to assess invasion. To fill this gap between bench and bedside, we use in this study a lung tumor tissue model with a preserved basement membrane for investigation of EMT functions with respect to invasion across this membrane and drug resistance. Our results suggest EMT is more a marker of drug resistance than a maker. Invasion is enhanced by EMT but more dependent on intrinsic factors, and EMT is not detected in the center of invasive tumor nodules. An in silico signaling network model is used to integrate these in vitro results and to reveal determinants for drug response. Abstract Epithelial-to-mesenchymal transition (EMT) is discussed to be centrally involved in invasion, stemness, and drug resistance. Experimental models to evaluate this process in its biological complexity are limited. To shed light on EMT impact and test drug response more reliably, we use a lung tumor test system based on a decellularized intestinal matrix showing more in vivo-like proliferation levels and enhanced expression of clinical markers and carcinogenesis-related genes. In our models, we found evidence for a correlation of EMT with drug resistance in primary and secondary resistant cells harboring KRASG12C or EGFR mutations, which was simulated in silico based on an optimized signaling network topology. Notably, drug resistance did not correlate with EMT status in KRAS-mutated patient-derived xenograft (PDX) cell lines, and drug efficacy was not affected by EMT induction via TGF-β. To investigate further determinants of drug response, we tested several drugs in combination with a KRASG12C inhibitor in KRASG12C mutant HCC44 models, which, besides EMT, display mutations in P53, LKB1, KEAP1, and high c-MYC expression. We identified an aurora-kinase A (AURKA) inhibitor as the most promising candidate. In our network, AURKA is a centrally linked hub to EMT, proliferation, apoptosis, LKB1, and c-MYC. This exemplifies our systemic analysis approach for clinical translation of biomarker signatures.
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27
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Cancer: More than a geneticist’s Pandora’s box. J Biosci 2022. [DOI: 10.1007/s12038-022-00254-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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28
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Bladder cancer cells shift rapidly and spontaneously to cisplatin-resistant oxidative phosphorylation that is trackable in real time. Sci Rep 2022; 12:5518. [PMID: 35365706 PMCID: PMC8976067 DOI: 10.1038/s41598-022-09438-9] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Accepted: 03/23/2022] [Indexed: 12/26/2022] Open
Abstract
Genetic mutations have long been recognized as drivers of cancer drug resistance, but recent work has defined additional non-genetic mechanisms of plasticity, wherein cancer cells assume a drug resistant phenotype marked by altered epigenetic and transcriptional states. Currently, little is known about the real-time, dynamic nature of this phenotypic shift. Using a bladder cancer model of nongenetic plasticity, we discovered that rapid transition to drug resistance entails upregulation of mitochondrial gene expression and a corresponding metabolic shift towards the tricarboxylic acid cycle and oxidative phosphorylation. Based on this distinction, we were able to track cancer cell metabolic profiles in real time using fluorescence lifetime microscopy (FLIM). We observed single cells transitioning spontaneously to an oxidative phosphorylation state over hours to days, a trend that intensified with exposure to cisplatin chemotherapy. Conversely, pharmacological inhibition of oxidative phosphorylation significantly reversed the FLIM metabolic signature and reduced cisplatin resistance. These rapid, spontaneous metabolic shifts offer a new means of tracking nongenetic cancer plasticity and forestalling the emergence of drug resistance.
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29
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Radfar P, Aboulkheyr Es H, Salomon R, Kulasinghe A, Ramalingam N, Sarafraz-Yazdi E, Thiery JP, Warkiani ME. Single-cell analysis of circulating tumour cells: enabling technologies and clinical applications. Trends Biotechnol 2022; 40:1041-1060. [DOI: 10.1016/j.tibtech.2022.02.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Revised: 02/15/2022] [Accepted: 02/16/2022] [Indexed: 11/26/2022]
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30
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Howard GR, Jost TA, Yankeelov TE, Brock A. Quantification of long-term doxorubicin response dynamics in breast cancer cell lines to direct treatment schedules. PLoS Comput Biol 2022; 18:e1009104. [PMID: 35358172 PMCID: PMC9004764 DOI: 10.1371/journal.pcbi.1009104] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2021] [Revised: 04/12/2022] [Accepted: 02/07/2022] [Indexed: 01/05/2023] Open
Abstract
While acquired chemoresistance is recognized as a key challenge to treating many types of cancer, the dynamics with which drug sensitivity changes after exposure are poorly characterized. Most chemotherapeutic regimens call for repeated dosing at regular intervals, and if drug sensitivity changes on a similar time scale then the treatment interval could be optimized to improve treatment performance. Theoretical work suggests that such optimal schedules exist, but experimental confirmation has been obstructed by the difficulty of deconvolving the simultaneous processes of death, adaptation, and regrowth taking place in cancer cell populations. Here we present a method of optimizing drug schedules in vitro through iterative application of experimentally calibrated models, and demonstrate its ability to characterize dynamic changes in sensitivity to the chemotherapeutic doxorubicin in three breast cancer cell lines subjected to treatment schedules varying in concentration, interval between pulse treatments, and number of sequential pulse treatments. Cell populations are monitored longitudinally through automated imaging for 600–800 hours, and this data is used to calibrate a family of cancer growth models, each consisting of a system of ordinary differential equations, derived from the bi-exponential model which characterizes resistant and sensitive subpopulations. We identify a model incorporating both a period of growth arrest in surviving cells and a delay in the death of chemosensitive cells which outperforms the original bi-exponential growth model in Akaike Information Criterion based model selection, and use the calibrated model to quantify the performance of each drug schedule. We find that the inter-treatment interval is a key variable in determining the performance of sequential dosing schedules and identify an optimal retreatment time for each cell line which extends regrowth time by 40%-239%, demonstrating that the time scale of changes in chemosensitivity following doxorubicin exposure allows optimization of drug scheduling by varying this inter-treatment interval. Acquired chemoresistance is a common cause of treatment failure in cancer. The scheduling of a multi-dose course of chemotherapeutic treatment may influence the dynamics of acquired chemoresistance, and drug schedule optimization may increase the duration of effectiveness of a particular chemotherapeutic agent for a particular patient. Here we present a method for experimentally optimizing an in vitro drug schedule through iterative rounds of experimentation and computational analysis, and demonstrate the method’s ability to improve the performance of doxorubicin treatment in three breast carcinoma cell lines. Specifically, we find that the interval between drug exposures can be optimized while holding drug concentration and number of treatments constant, suggesting that this may be a key variable to explore in future drug schedule optimization efforts. We further use this method’s model calibration and selection process to extract information about the underlying biology of the doxorubicin response, and find that the incorporation of delays on both cell death and regrowth are necessary for accurate parameterization of cell growth data.
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Affiliation(s)
- Grant R. Howard
- Department of Biomedical Engineering, The University of Texas at Austin, Austin, Texas, United States of America
| | - Tyler A. Jost
- Department of Biomedical Engineering, The University of Texas at Austin, Austin, Texas, United States of America
| | - Thomas E. Yankeelov
- Department of Biomedical Engineering, The University of Texas at Austin, Austin, Texas, United States of America
- Department of Diagnostic Medicine, The University of Texas at Austin, Austin, Texas, United States of America
- Department of Oncology, The University of Texas at Austin, Austin, Texas, United States of America
- Oden Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, Texas, United States of America
- Livestrong Cancer Institutes, The University of Texas at Austin, Austin, Texas, United States of America
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America
| | - Amy Brock
- Department of Biomedical Engineering, The University of Texas at Austin, Austin, Texas, United States of America
- Department of Cell and Molecular Biology, The University of Texas at Austin, Austin, Texas, United States of America
- * E-mail:
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31
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Kulkarni P, Leite VBP, Roy S, Bhattacharyya S, Mohanty A, Achuthan S, Singh D, Appadurai R, Rangarajan G, Weninger K, Orban J, Srivastava A, Jolly MK, Onuchic JN, Uversky VN, Salgia R. Intrinsically disordered proteins: Ensembles at the limits of Anfinsen's dogma. BIOPHYSICS REVIEWS 2022; 3:011306. [PMID: 38505224 PMCID: PMC10903413 DOI: 10.1063/5.0080512] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Accepted: 02/17/2022] [Indexed: 03/21/2024]
Abstract
Intrinsically disordered proteins (IDPs) are proteins that lack rigid 3D structure. Hence, they are often misconceived to present a challenge to Anfinsen's dogma. However, IDPs exist as ensembles that sample a quasi-continuum of rapidly interconverting conformations and, as such, may represent proteins at the extreme limit of the Anfinsen postulate. IDPs play important biological roles and are key components of the cellular protein interaction network (PIN). Many IDPs can interconvert between disordered and ordered states as they bind to appropriate partners. Conformational dynamics of IDPs contribute to conformational noise in the cell. Thus, the dysregulation of IDPs contributes to increased noise and "promiscuous" interactions. This leads to PIN rewiring to output an appropriate response underscoring the critical role of IDPs in cellular decision making. Nonetheless, IDPs are not easily tractable experimentally. Furthermore, in the absence of a reference conformation, discerning the energy landscape representation of the weakly funneled IDPs in terms of reaction coordinates is challenging. To understand conformational dynamics in real time and decipher how IDPs recognize multiple binding partners with high specificity, several sophisticated knowledge-based and physics-based in silico sampling techniques have been developed. Here, using specific examples, we highlight recent advances in energy landscape visualization and molecular dynamics simulations to discern conformational dynamics and discuss how the conformational preferences of IDPs modulate their function, especially in phenotypic switching. Finally, we discuss recent progress in identifying small molecules targeting IDPs underscoring the potential therapeutic value of IDPs. Understanding structure and function of IDPs can not only provide new insight on cellular decision making but may also help to refine and extend Anfinsen's structure/function paradigm.
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Affiliation(s)
- Prakash Kulkarni
- Department of Medical Oncology and Therapeutics Research, City of Hope National Medical Center, Duarte, California 91010, USA
| | - Vitor B. P. Leite
- Departamento de Física, Instituto de Biociências, Letras e Ciências Exatas, Universidade Estadual Paulista (UNESP), São José do Rio Preto, São Paulo 15054-000, Brazil
| | - Susmita Roy
- Department of Chemical Sciences, Indian Institute of Science Education and Research Kolkata, Mohanpur, West Bengal 741246, India
| | - Supriyo Bhattacharyya
- Translational Bioinformatics, Center for Informatics, Department of Computational and Quantitative Medicine, City of Hope National Medical Center, Duarte, California 91010, USA
| | - Atish Mohanty
- Department of Medical Oncology and Therapeutics Research, City of Hope National Medical Center, Duarte, California 91010, USA
| | - Srisairam Achuthan
- Center for Informatics, Division of Research Informatics, City of Hope National Medical Center, Duarte, California 91010, USA
| | - Divyoj Singh
- Center for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India
| | - Rajeswari Appadurai
- Molecular Biophysics Unit, Indian Institute of Science, Bangalore, Karnataka, India
| | - Govindan Rangarajan
- Department of Mathematics, Indian Institute of Science, Bangalore 560012, India
| | - Keith Weninger
- Department of Physics, North Carolina State University, Raleigh, North Carolina 27695, USA
| | | | - Anand Srivastava
- Molecular Biophysics Unit, Indian Institute of Science, Bangalore, Karnataka, India
| | - Mohit Kumar Jolly
- Center for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India
| | - Jose N. Onuchic
- Center for Theoretical Biological Physics, Rice University, Houston, Texas 77005-1892, USA
| | | | - Ravi Salgia
- Department of Medical Oncology and Therapeutics Research, City of Hope National Medical Center, Duarte, California 91010, USA
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32
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Jain P, Bhatia S, Thompson EW, Jolly MK. Population Dynamics of Epithelial-Mesenchymal Heterogeneity in Cancer Cells. Biomolecules 2022; 12:biom12030348. [PMID: 35327538 PMCID: PMC8945776 DOI: 10.3390/biom12030348] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Revised: 02/17/2022] [Accepted: 02/18/2022] [Indexed: 11/16/2022] Open
Abstract
Phenotypic heterogeneity is a hallmark of aggressive cancer behaviour and a clinical challenge. Despite much characterisation of this heterogeneity at a multi-omics level in many cancers, we have a limited understanding of how this heterogeneity emerges spontaneously in an isogenic cell population. Some longitudinal observations of dynamics in epithelial-mesenchymal heterogeneity, a canonical example of phenotypic heterogeneity, have offered us opportunities to quantify the rates of phenotypic switching that may drive such heterogeneity. Here, we offer a mathematical modeling framework that explains the salient features of population dynamics noted in PMC42-LA cells: (a) predominance of EpCAMhigh subpopulation, (b) re-establishment of parental distributions from the EpCAMhigh and EpCAMlow subpopulations, and (c) enhanced heterogeneity in clonal populations established from individual cells. Our framework proposes that fluctuations or noise in content duplication and partitioning of SNAIL—an EMT-inducing transcription factor—during cell division can explain spontaneous phenotypic switching and consequent dynamic heterogeneity in PMC42-LA cells observed experimentally at both single-cell and bulk level analysis. Together, we propose that asymmetric cell division can be a potential mechanism for phenotypic heterogeneity.
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Affiliation(s)
- Paras Jain
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India;
| | - Sugandha Bhatia
- School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Brisbane 4000, Australia;
- The University of Queensland Diamantina Institute, Faculty of Medicine, The University of Queensland, Woolloongabba 4102, Australia
- Translational Research Institute, Woolloongabba 4102, Australia
| | - Erik W. Thompson
- School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Brisbane 4000, Australia;
- Translational Research Institute, Woolloongabba 4102, Australia
- Correspondence: (E.W.T.); (M.K.J.)
| | - Mohit Kumar Jolly
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India;
- Correspondence: (E.W.T.); (M.K.J.)
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33
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Foo J, Basanta D, Rockne RC, Strelez C, Shah C, Ghaffarian K, Mumenthaler SM, Mitchell K, Lathia JD, Frankhouser D, Branciamore S, Kuo YH, Marcucci G, Vander Velde R, Marusyk A, Hang S, Hari K, Jolly MK, Hatzikirou H, Poels K, Spilker M, Shtylla B, Robertson-Tessi M, Anderson ARA. Roadmap on plasticity and epigenetics in cancer. Phys Biol 2022; 19. [PMID: 35078159 PMCID: PMC9190291 DOI: 10.1088/1478-3975/ac4ee2] [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: 08/20/2021] [Accepted: 01/25/2022] [Indexed: 11/22/2022]
Abstract
The role of plasticity and epigenetics in shaping cancer evolution and response to therapy has taken center stage with recent technological advances including single cell sequencing. This roadmap article is focused on state-of-the-art mathematical and experimental approaches to interrogate plasticity in cancer, and addresses the following themes and questions: is there a formal overarching framework that encompasses both non-genetic plasticity and mutation-driven somatic evolution? How do we measure and model the role of the microenvironment in influencing/controlling non-genetic plasticity? How can we experimentally study non-genetic plasticity? Which mathematical techniques are required or best suited? What are the clinical and practical applications and implications of these concepts?
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Affiliation(s)
- Jasmine Foo
- University of Minnesota System, School of Mathematics, Minneapolis, Minnesota, 55455-2020, UNITED STATES
| | - David Basanta
- Integrated Mathematical Oncology, H Lee Moffitt Cancer Center and Research Center Inc, H Lee Moffitt Cancer Center and Research Institute, 12902 Magnolia Drive, MRC-3 West/IMO, Tampa, Florida 33612USA, Tampa, Florida, 33612-9416, UNITED STATES
| | - Russell C Rockne
- Computational and Quantitative Medicine; Division of Mathematical Oncology, Beckman Research Institute, 1500 E Duarte Rd, Rose Vogel Building (74), Duarte, California, 91010, UNITED STATES
| | - Carly Strelez
- Lawrence J. Ellison Institute , Transformative Medicine, Los Angeles, CA 90064, UNITED STATES
| | - Curran Shah
- Lawrence J. Ellison Institute , Transformative Medicine, Los Angeles, CA 90064, UNITED STATES
| | - Kimya Ghaffarian
- Lawrence J. Ellison Institute , Transformative Medicine, Los Angeles, CA 90064, UNITED STATES
| | - Shannon M Mumenthaler
- Lawrence J. Ellison Institute , Transformative Medicine, Los Angeles, CA 90064, UNITED STATES
| | - Kelly Mitchell
- Department of Cardiovascular & Metabolic Sciences, Cleveland Clinic, Lerner Research Institute, Cleveland, Ohio, 44195-5243, UNITED STATES
| | - Justin D Lathia
- Department of Cardiovascular & Metabolic Sciences, Cleveland Clinic, Lerner Research Institute, Cleveland, Ohio, 44195-5243, UNITED STATES
| | - David Frankhouser
- Computational and Quantitative Medicine; Division of Mathematical Oncology, Beckman Research Institute, 1500 E Duarte Rd, Rose Vogel Building (74), Duarte, California, 91010, UNITED STATES
| | - Sergio Branciamore
- Computational and Quantitative Medicine; Division of Mathematical Oncology, Beckman Research Institute, 1500 E Duarte Rd, Rose Vogel Building (74), Duarte, California, 91010, UNITED STATES
| | - Ya-Huei Kuo
- Hematologic Malignancies Translational Science, City of Hope National Medical Center, Beckman Research Institute, 1500 E Duarte Rd, Rose Vogel Building (74), Duarte, California, 91010, UNITED STATES
| | - Guido Marcucci
- Hematologic Malignancies Translational Science, City of Hope National Medical Center, Beckman Research Institute, 1500 E Duarte Rd, Rose Vogel Building (74), Duarte, California, 91010, UNITED STATES
| | - Robert Vander Velde
- Department of Cancer Physiology, H Lee Moffitt Cancer Center and Research Center Inc, H Lee Moffitt Cancer Center and Research Institute, 12902 Magnolia Drive, MRC-3 West/IMO, Tampa, Florida 33612USA, Tampa, Florida, 33612-9416, UNITED STATES
| | - Andriy Marusyk
- Cancer Physiology, Moffitt Cancer Center, 12902 USF Magnolia Drive, Tampa, Florida, 33612, UNITED STATES
| | - Sui Hang
- Institute for Systems Biology, Systems Biology, WA , WA 98109, UNITED STATES
| | - Kishore Hari
- Indian Institute of Science, 560012 Bangalore, Bangalore, 560012, INDIA
| | - Mohit Kumar Jolly
- Centre for BioSystems Science and Engineering,, Indian Institute of Science, 560012 Bangalore, Bangalore, 560012, INDIA
| | - Haralampos Hatzikirou
- Khalifa University, P.O. Box: 127788, Abu Dhabi, Abu Dhabi, NA, UNITED ARAB EMIRATES
| | - Kamrine Poels
- Early Clinical Development, Pfizer Global Research and Development, Early Clinical Development, Groton, Connecticut, 06340, UNITED STATES
| | - Mary Spilker
- Medicine Design, Pfizer Global Research and Development, Medicine Design, Groton, Connecticut, 06340, UNITED STATES
| | - Blerta Shtylla
- Early Clinical Development, Pfizer Global Research and Development, Early Clinical Development, Groton, Connecticut, 06340, UNITED STATES
| | - Mark Robertson-Tessi
- Integrated Mathematical Oncology Department, Moffitt Cancer Center, 12902 USF Magnolia Drive, Tampa, Florida, 33612, UNITED STATES
| | - Alexander R A Anderson
- Integrated Mathematical Oncology, Moffitt Cancer Center, Co-Director of Integrated Mathematical Oncology, 12902 Magnolia Drive, SRB 4 Rm 24000H, Tampa, Florida 33612, Tampa, 33612, UNITED STATES
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34
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Gedye C, Navani V. Find the path of least resistance: Adaptive therapy to delay treatment failure and improve outcomes. Biochim Biophys Acta Rev Cancer 2022; 1877:188681. [PMID: 35051527 DOI: 10.1016/j.bbcan.2022.188681] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Revised: 01/01/2022] [Accepted: 01/11/2022] [Indexed: 11/15/2022]
Abstract
Cytotoxic chemotherapy and targeted therapies help people with advanced cancers, but for most, treatment fails. Cancer heterogeneity is one cause of treatment failure, but also suggests an opportunity to improve outcomes; reconceptualising cancer therapy as an ecological problem offers the strategy of adaptive therapy. If an agent is active against a patient's cancer, instead of traditional continuous dosing at the maximum tolerated dose until treatment failure, the patient and their oncologist may instead choose to pause treatment as soon as the cancer responds. When tumour burden increases, the cancer is rechallenged with the same agent in hope of delivering another response, ideally before symptoms occur or quality-of-life is impacted. These 'loops' of 'pause/restart' allows an active treatment to be used strategically, to delay the development of evolutionary selection within the cancer, delaying the onset of treatment resistance, controlling the cancer for longer. Modelling predicts patients can navigate several 'loops', potentially increasing the utility of an active treatment by multiples, and early trials suggest at least doubling of progression-free survival. In this narrative review we confront how cancer heterogeneity limits treatment effectiveness, re-examine cancer as an ecological problem, review the data supporting adaptive therapy and outline the challenges and opportunities faced in clinical practice to implement this evolutionary concept. In an era where multiple novel active anti-neoplastic agents are being used with ancient inflexibile maximum tolerated dose for maximum duration approaches, adaptive dosing offers a personalised, n = 1 approach to cancer therapy selection.
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Affiliation(s)
- Craig Gedye
- Calvary Mater Newcastle, Waratah 2298, NSW, Australia; Clinical Trial Unit, Hunter Medical Research Institute, New Lambton Heights, NSW, Australia; School of Medicine and Public Health University of Newcastle, NSW, Australia.
| | - Vishal Navani
- Tom Baker Cancer Centre, University of Calgary, Calgary, AB, Canada.
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Pryyma A, Matinkhoo K, Bu YJ, Merkens H, Zhang Z, Bénard F, Perrin DM. Synthesis and preliminary evaluation of octreotate conjugates of bioactive synthetic amatoxins for targeting somatostatin receptor (sstr2) expressing cells. RSC Chem Biol 2022; 3:69-78. [PMID: 35128410 PMCID: PMC8729174 DOI: 10.1039/d1cb00036e] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2021] [Accepted: 09/27/2021] [Indexed: 11/28/2022] Open
Abstract
Targeted cancer therapy represents a paradigm-shifting approach that aims to deliver a toxic payload selectively to target-expressing cells thereby sparing normal tissues the off-target effects associated with traditional chemotherapeutics. Since most targeted constructs rely on standard microtubule inhibitors or DNA-reactive molecules as payloads, new toxins that inhibit other intracellular targets are needed to realize the full potential of targeted therapy. Among these new payloads, α-amanitin has gained attraction as a payload in targeted therapy. Here, we conjugate two synthetic amanitins at different sites to demonstrate their utility as payloads in peptide drug conjugates (PDCs). As an exemplary targeting agent, we chose octreotate, a well-studied somatostatin receptor (sstr2) peptide agonist for the conjugation to synthetic amatoxins via three tailor-built linkers. The linker chemistry permitted the evaluation of one non-cleavable and two cleavable self-immolative conjugates. The immolating linkers were chosen to take advantage of either the reducing potential of the intracellular environment or the high levels of lysosomal proteases in tumor cells to trigger toxin release. Cell-based assays on target-positive Ar42J cells revealed target-specific reduction in viability with up to 1000-fold enhancement in bioactivity compared to the untargeted amatoxins. Altogether, this preliminary study enabled the development of a highly modular synthetic platform for the construction of amanitin-based conjugates that can be readily extended to various targeting moieties.
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Affiliation(s)
- Alla Pryyma
- Department of Chemistry, University of British Columbia 2036 Main Mall Vancouver BC V6T 1Z1 Canada
| | - Kaveh Matinkhoo
- Department of Chemistry, University of British Columbia 2036 Main Mall Vancouver BC V6T 1Z1 Canada
| | - Yong Jia Bu
- Department of Chemistry, University of British Columbia 2036 Main Mall Vancouver BC V6T 1Z1 Canada
| | - Helen Merkens
- Department of Molecular Oncology, BC Cancer Vancouver BC V5Z 1L3 Canada
| | - Zhengxing Zhang
- Department of Molecular Oncology, BC Cancer Vancouver BC V5Z 1L3 Canada
| | - Francois Bénard
- Department of Molecular Oncology, BC Cancer Vancouver BC V5Z 1L3 Canada
| | - David M Perrin
- Department of Chemistry, University of British Columbia 2036 Main Mall Vancouver BC V6T 1Z1 Canada
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Aguadé-Gorgorió G, Kauffman S, Solé R. Transition Therapy: Tackling the Ecology of Tumor Phenotypic Plasticity. Bull Math Biol 2021; 84:24. [PMID: 34958403 PMCID: PMC8712307 DOI: 10.1007/s11538-021-00970-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2021] [Accepted: 11/15/2021] [Indexed: 11/17/2022]
Abstract
Phenotypic switching in cancer cells has been found to be present across tumor types. Recent studies on Glioblastoma report a remarkably common architecture of four well-defined phenotypes coexisting within high levels of intra-tumor genetic heterogeneity. Similar dynamics have been shown to occur in breast cancer and melanoma and are likely to be found across cancer types. Given the adaptive potential of phenotypic switching (PHS) strategies, understanding how it drives tumor evolution and therapy resistance is a major priority. Here we present a mathematical framework uncovering the ecological dynamics behind PHS. The model is able to reproduce experimental results, and mathematical conditions for cancer progression reveal PHS-specific features of tumors with direct consequences on therapy resistance. In particular, our model reveals a threshold for the resistant-to-sensitive phenotype transition rate, below which any cytotoxic or switch-inhibition therapy is likely to fail. The model is able to capture therapeutic success thresholds for cancers where nonlinear growth dynamics or larger PHS architectures are in place, such as glioblastoma or melanoma. By doing so, the model presents a novel set of conditions for the success of combination therapies able to target replication and phenotypic transitions at once. Following our results, we discuss transition therapy as a novel scheme to target not only combined cytotoxicity but also the rates of phenotypic switching.
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Affiliation(s)
- Guim Aguadé-Gorgorió
- ICREA-Complex Systems Lab, Universitat Pompeu Fabra, 08003, Barcelona, Spain
- Institut de Biologia Evolutiva, CSIC-UPF, 08003, Barcelona, Spain
| | | | - Ricard Solé
- ICREA-Complex Systems Lab, Universitat Pompeu Fabra, 08003, Barcelona, Spain.
- Institut de Biologia Evolutiva, CSIC-UPF, 08003, Barcelona, Spain.
- Santa Fe Institute, Santa Fe, NM, 87501, USA.
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Dynamic Phenotypic Switching and Group Behavior Help Non-Small Cell Lung Cancer Cells Evade Chemotherapy. Biomolecules 2021; 12:biom12010008. [PMID: 35053156 PMCID: PMC8773639 DOI: 10.3390/biom12010008] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Revised: 12/14/2021] [Accepted: 12/17/2021] [Indexed: 12/21/2022] Open
Abstract
Drug resistance, a major challenge in cancer therapy, is typically attributed to mutations and genetic heterogeneity. Emerging evidence suggests that dynamic cellular interactions and group behavior also contribute to drug resistance. However, the underlying mechanisms remain poorly understood. Here, we present a new mathematical approach with game theoretical underpinnings that we developed to model real-time growth data of non-small cell lung cancer (NSCLC) cells and discern patterns in response to treatment with cisplatin. We show that the cisplatin-sensitive and cisplatin-tolerant NSCLC cells, when co-cultured in the absence or presence of the drug, display dynamic group behavior strategies. Tolerant cells exhibit a 'persister-like' behavior and are attenuated by sensitive cells; they also appear to 'educate' sensitive cells to evade chemotherapy. Further, tolerant cells can switch phenotypes to become sensitive, especially at low cisplatin concentrations. Finally, switching treatment from continuous to an intermittent regimen can attenuate the emergence of tolerant cells, suggesting that intermittent chemotherapy may improve outcomes in lung cancer.
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Hare PJ, LaGree TJ, Byrd BA, DeMarco AM, Mok WWK. Single-Cell Technologies to Study Phenotypic Heterogeneity and Bacterial Persisters. Microorganisms 2021; 9:2277. [PMID: 34835403 PMCID: PMC8620850 DOI: 10.3390/microorganisms9112277] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2021] [Revised: 10/20/2021] [Accepted: 10/27/2021] [Indexed: 11/16/2022] Open
Abstract
Antibiotic persistence is a phenomenon in which rare cells of a clonal bacterial population can survive antibiotic doses that kill their kin, even though the entire population is genetically susceptible. With antibiotic treatment failure on the rise, there is growing interest in understanding the molecular mechanisms underlying bacterial phenotypic heterogeneity and antibiotic persistence. However, elucidating these rare cell states can be technically challenging. The advent of single-cell techniques has enabled us to observe and quantitatively investigate individual cells in complex, phenotypically heterogeneous populations. In this review, we will discuss current technologies for studying persister phenotypes, including fluorescent tags and biosensors used to elucidate cellular processes; advances in flow cytometry, mass spectrometry, Raman spectroscopy, and microfluidics that contribute high-throughput and high-content information; and next-generation sequencing for powerful insights into genetic and transcriptomic programs. We will further discuss existing knowledge gaps, cutting-edge technologies that can address them, and how advances in single-cell microbiology can potentially improve infectious disease treatment outcomes.
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Affiliation(s)
- Patricia J. Hare
- Department of Molecular Biology & Biophysics, UConn Health, Farmington, CT 06032, USA; (P.J.H.); (T.J.L.); (B.A.B.); (A.M.D.)
- School of Dental Medicine, University of Connecticut, Farmington, CT 06032, USA
| | - Travis J. LaGree
- Department of Molecular Biology & Biophysics, UConn Health, Farmington, CT 06032, USA; (P.J.H.); (T.J.L.); (B.A.B.); (A.M.D.)
| | - Brandon A. Byrd
- Department of Molecular Biology & Biophysics, UConn Health, Farmington, CT 06032, USA; (P.J.H.); (T.J.L.); (B.A.B.); (A.M.D.)
- School of Medicine, University of Connecticut, Farmington, CT 06032, USA
| | - Angela M. DeMarco
- Department of Molecular Biology & Biophysics, UConn Health, Farmington, CT 06032, USA; (P.J.H.); (T.J.L.); (B.A.B.); (A.M.D.)
| | - Wendy W. K. Mok
- Department of Molecular Biology & Biophysics, UConn Health, Farmington, CT 06032, USA; (P.J.H.); (T.J.L.); (B.A.B.); (A.M.D.)
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Catania F, Ujvari B, Roche B, Capp JP, Thomas F. Bridging Tumorigenesis and Therapy Resistance With a Non-Darwinian and Non-Lamarckian Mechanism of Adaptive Evolution. Front Oncol 2021; 11:732081. [PMID: 34568068 PMCID: PMC8462274 DOI: 10.3389/fonc.2021.732081] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Accepted: 08/25/2021] [Indexed: 12/13/2022] Open
Abstract
Although neo-Darwinian (and less often Lamarckian) dynamics are regularly invoked to interpret cancer's multifarious molecular profiles, they shine little light on how tumorigenesis unfolds and often fail to fully capture the frequency and breadth of resistance mechanisms. This uncertainty frames one of the most problematic gaps between science and practice in modern times. Here, we offer a theory of adaptive cancer evolution, which builds on a molecular mechanism that lies outside neo-Darwinian and Lamarckian schemes. This mechanism coherently integrates non-genetic and genetic changes, ecological and evolutionary time scales, and shifts the spotlight away from positive selection towards purifying selection, genetic drift, and the creative-disruptive power of environmental change. The surprisingly simple use-it or lose-it rationale of the proposed theory can help predict molecular dynamics during tumorigenesis. It also provides simple rules of thumb that should help improve therapeutic approaches in cancer.
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Affiliation(s)
- Francesco Catania
- Institute for Evolution and Biodiversity, University of Münster, Münster, Germany
| | - Beata Ujvari
- Centre for Integrative Ecology, School of Life and Environmental Sciences, Deakin University, Deakin, VIC, Australia
| | - Benjamin Roche
- CREEC/CANECEV, MIVEGEC (CREES), Centre de Recherches Ecologiques et Evolutives sur le Cancer, University of Montpellier, CNRS, IRD, Montpellier, France
| | - Jean-Pascal Capp
- Toulouse Biotechnology Institute, University of Toulouse, INSA, CNRS, INRAE, Toulouse, France
| | - Frédéric Thomas
- CREEC/CANECEV, MIVEGEC (CREES), Centre de Recherches Ecologiques et Evolutives sur le Cancer, University of Montpellier, CNRS, IRD, Montpellier, France
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Wrenn E, Huang Y, Cheung K. Collective metastasis: coordinating the multicellular voyage. Clin Exp Metastasis 2021; 38:373-399. [PMID: 34254215 PMCID: PMC8346286 DOI: 10.1007/s10585-021-10111-0] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2021] [Accepted: 06/14/2021] [Indexed: 12/16/2022]
Abstract
The metastatic process is arduous. Cancer cells must escape the confines of the primary tumor, make their way into and travel through the circulation, then survive and proliferate in unfavorable microenvironments. A key question is how cancer cells overcome these multiple barriers to orchestrate distant organ colonization. Accumulating evidence in human patients and animal models supports the hypothesis that clusters of tumor cells can complete the entire metastatic journey in a process referred to as collective metastasis. Here we highlight recent studies unraveling how multicellular coordination, via both physical and biochemical coupling of cells, induces cooperative properties advantageous for the completion of metastasis. We discuss conceptual challenges and unique mechanisms arising from collective dissemination that are distinct from single cell-based metastasis. Finally, we consider how the dissection of molecular transitions regulating collective metastasis could offer potential insight into cancer therapy.
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Affiliation(s)
- Emma Wrenn
- Translational Research Program, Public Health Sciences and Human Biology Divisions, Fred Hutchinson Cancer Research Center, Seattle, WA, 98109, USA
- Molecular and Cellular Biology Graduate Program, University of Washington, Seattle, WA, 98195, USA
| | - Yin Huang
- Translational Research Program, Public Health Sciences and Human Biology Divisions, Fred Hutchinson Cancer Research Center, Seattle, WA, 98109, USA
| | - Kevin Cheung
- Translational Research Program, Public Health Sciences and Human Biology Divisions, Fred Hutchinson Cancer Research Center, Seattle, WA, 98109, USA.
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Cassidy T, Nichol D, Robertson-Tessi M, Craig M, Anderson ARA. The role of memory in non-genetic inheritance and its impact on cancer treatment resistance. PLoS Comput Biol 2021; 17:e1009348. [PMID: 34460809 PMCID: PMC8432806 DOI: 10.1371/journal.pcbi.1009348] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Revised: 09/10/2021] [Accepted: 08/11/2021] [Indexed: 12/24/2022] Open
Abstract
Intra-tumour heterogeneity is a leading cause of treatment failure and disease progression in cancer. While genetic mutations have long been accepted as a primary mechanism of generating this heterogeneity, the role of phenotypic plasticity is becoming increasingly apparent as a driver of intra-tumour heterogeneity. Consequently, understanding the role of this plasticity in treatment resistance and failure is a key component of improving cancer therapy. We develop a mathematical model of stochastic phenotype switching that tracks the evolution of drug-sensitive and drug-tolerant subpopulations to clarify the role of phenotype switching on population growth rates and tumour persistence. By including cytotoxic therapy in the model, we show that, depending on the strategy of the drug-tolerant subpopulation, stochastic phenotype switching can lead to either transient or permanent drug resistance. We study the role of phenotypic heterogeneity in a drug-resistant, genetically homogeneous population of non-small cell lung cancer cells to derive a rational treatment schedule that drives population extinction and avoids competitive release of the drug-tolerant sub-population. This model-informed therapeutic schedule results in increased treatment efficacy when compared against periodic therapy, and, most importantly, sustained tumour decay without the development of resistance.
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Affiliation(s)
- Tyler Cassidy
- Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America
| | - Daniel Nichol
- Evolutionary Genomics and Modelling Lab, Centre for Evolution and Cancer, The Institute of Cancer Research, London, United Kingdom
| | - Mark Robertson-Tessi
- Department of Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center, Tampa, Florida, United States of America
| | - Morgan Craig
- Département de mathématiques et de statistique, Université de Montréal, Montreal, Canada
- CHU Sainte-Justine, Montreal, Canada
| | - Alexander R. A. Anderson
- Department of Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center, Tampa, Florida, United States of America
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Thankamony AP, Subbalakshmi AR, Jolly MK, Nair R. Lineage Plasticity in Cancer: The Tale of a Skin-Walker. Cancers (Basel) 2021; 13:3602. [PMID: 34298815 PMCID: PMC8306016 DOI: 10.3390/cancers13143602] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2021] [Revised: 07/04/2021] [Accepted: 07/14/2021] [Indexed: 12/11/2022] Open
Abstract
Lineage plasticity, the switching of cells from one lineage to another, has been recognized as a cardinal property essential for embryonic development, tissue repair and homeostasis. However, such a highly regulated process goes awry when cancer cells exploit this inherent ability to their advantage, resulting in tumorigenesis, relapse, metastasis and therapy resistance. In this review, we summarize our current understanding on the role of lineage plasticity in tumor progression and therapeutic resistance in multiple cancers. Lineage plasticity can be triggered by treatment itself and is reported across various solid as well as liquid tumors. Here, we focus on the importance of lineage switching in tumor progression and therapeutic resistance of solid tumors such as the prostate, lung, hepatocellular and colorectal carcinoma and the myeloid and lymphoid lineage switch observed in leukemias. Besides this, we also discuss the role of epithelial-mesenchymal transition (EMT) in facilitating the lineage switch in biphasic cancers such as aggressive carcinosarcomas. We also discuss the mechanisms involved, current therapeutic approaches and challenges that lie ahead in taming the scourge of lineage plasticity in cancer.
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Affiliation(s)
- Archana P. Thankamony
- Cancer Research Program, Rajiv Gandhi Centre for Biotechnology, Kerala 695014, India;
- Manipal Academy of Higher Education (MAHE), Manipal 576104, India
| | - Ayalur Raghu Subbalakshmi
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India;
| | - Mohit Kumar Jolly
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India;
| | - Radhika Nair
- Cancer Research Program, Rajiv Gandhi Centre for Biotechnology, Kerala 695014, India;
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Sahoo S, Mishra A, Kaur H, Hari K, Muralidharan S, Mandal S, Jolly MK. A mechanistic model captures the emergence and implications of non-genetic heterogeneity and reversible drug resistance in ER+ breast cancer cells. NAR Cancer 2021; 3:zcab027. [PMID: 34316714 PMCID: PMC8271219 DOI: 10.1093/narcan/zcab027] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2021] [Revised: 06/02/2021] [Accepted: 06/18/2021] [Indexed: 02/07/2023] Open
Abstract
Resistance to anti-estrogen therapy is an unsolved clinical challenge in successfully treating ER+ breast cancer patients. Recent studies have demonstrated the role of non-genetic (i.e. phenotypic) adaptations in tolerating drug treatments; however, the mechanisms and dynamics of such non-genetic adaptation remain elusive. Here, we investigate coupled dynamics of epithelial–mesenchymal transition (EMT) in breast cancer cells and emergence of reversible drug resistance. Our mechanism-based model for underlying regulatory network reveals that these two axes can drive one another, thus enabling non-genetic heterogeneity in a cell population by allowing for six co-existing phenotypes: epithelial-sensitive, mesenchymal-resistant, hybrid E/M-sensitive, hybrid E/M-resistant, mesenchymal-sensitive and epithelial-resistant, with the first two ones being most dominant. Next, in a population dynamics framework, we exemplify the implications of phenotypic plasticity (both drug-induced and intrinsic stochastic switching) and/or non-genetic heterogeneity in promoting population survival in a mixture of sensitive and resistant cells, even in the absence of any cell–cell cooperation. Finally, we propose the potential therapeutic use of mesenchymal–epithelial transition inducers besides canonical anti-estrogen therapy to limit the emergence of reversible drug resistance. Our results offer mechanistic insights into empirical observations on EMT and drug resistance and illustrate how such dynamical insights can be exploited for better therapeutic designs.
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Affiliation(s)
- Sarthak Sahoo
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India
| | - Ashutosh Mishra
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India
| | - Harsimran Kaur
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India
| | - Kishore Hari
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India
| | - Srinath Muralidharan
- Department of Biotechnology, Indian Institute of Technology Madras, Chennai 600036, India
| | - Susmita Mandal
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India
| | - Mohit Kumar Jolly
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India
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45
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Khalaf K, Hana D, Chou JTT, Singh C, Mackiewicz A, Kaczmarek M. Aspects of the Tumor Microenvironment Involved in Immune Resistance and Drug Resistance. Front Immunol 2021; 12:656364. [PMID: 34122412 PMCID: PMC8190405 DOI: 10.3389/fimmu.2021.656364] [Citation(s) in RCA: 183] [Impact Index Per Article: 61.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2021] [Accepted: 04/27/2021] [Indexed: 12/11/2022] Open
Abstract
The tumor microenvironment (TME) is a complex and ever-changing "rogue organ" composed of its own blood supply, lymphatic and nervous systems, stroma, immune cells and extracellular matrix (ECM). These complex components, utilizing both benign and malignant cells, nurture the harsh, immunosuppressive and nutrient-deficient environment necessary for tumor cell growth, proliferation and phenotypic flexibility and variation. An important aspect of the TME is cellular crosstalk and cell-to-ECM communication. This interaction induces the release of soluble factors responsible for immune evasion and ECM remodeling, which further contribute to therapy resistance. Other aspects are the presence of exosomes contributed by both malignant and benign cells, circulating deregulated microRNAs and TME-specific metabolic patterns which further potentiate the progression and/or resistance to therapy. In addition to biochemical signaling, specific TME characteristics such as the hypoxic environment, metabolic derangements, and abnormal mechanical forces have been implicated in the development of treatment resistance. In this review, we will provide an overview of tumor microenvironmental composition, structure, and features that influence immune suppression and contribute to treatment resistance.
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Affiliation(s)
- Khalil Khalaf
- Department of Cancer Diagnostics and Immunology, Greater Poland Cancer Center, Poznań, Poland
- Department of Cancer Immunology, Poznan University of Medical Sciences, Poznań, Poland
| | - Doris Hana
- Department of Cancer Diagnostics and Immunology, Greater Poland Cancer Center, Poznań, Poland
- Department of Cancer Immunology, Poznan University of Medical Sciences, Poznań, Poland
| | - Jadzia Tin-Tsen Chou
- Department of Cancer Diagnostics and Immunology, Greater Poland Cancer Center, Poznań, Poland
- Department of Cancer Immunology, Poznan University of Medical Sciences, Poznań, Poland
| | - Chandpreet Singh
- Department of Cancer Diagnostics and Immunology, Greater Poland Cancer Center, Poznań, Poland
- Department of Cancer Immunology, Poznan University of Medical Sciences, Poznań, Poland
| | - Andrzej Mackiewicz
- Department of Cancer Diagnostics and Immunology, Greater Poland Cancer Center, Poznań, Poland
- Department of Cancer Immunology, Poznan University of Medical Sciences, Poznań, Poland
| | - Mariusz Kaczmarek
- Department of Cancer Diagnostics and Immunology, Greater Poland Cancer Center, Poznań, Poland
- Department of Cancer Immunology, Poznan University of Medical Sciences, Poznań, Poland
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Bhattacharya S, Mohanty A, Achuthan S, Kotnala S, Jolly MK, Kulkarni P, Salgia R. Group Behavior and Emergence of Cancer Drug Resistance. Trends Cancer 2021; 7:323-334. [PMID: 33622644 PMCID: PMC8500356 DOI: 10.1016/j.trecan.2021.01.009] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2020] [Revised: 01/25/2021] [Accepted: 01/26/2021] [Indexed: 02/06/2023]
Abstract
Drug resistance is a major impediment in cancer. Although it is generally thought that acquired drug resistance is due to genetic mutations, emerging evidence indicates that nongenetic mechanisms also play an important role. Resistance emerges through a complex interplay of clonal groups within a heterogeneous tumor and the surrounding microenvironment. Traits such as phenotypic plasticity, intercellular communication, and adaptive stress response, act in concert to ensure survival of intermediate reversible phenotypes, until permanent, resistant clones can emerge. Understanding the role of group behavior, and the underlying nongenetic mechanisms, can lead to more efficacious treatment designs and minimize or delay emergence of resistance.
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Affiliation(s)
- Supriyo Bhattacharya
- Translational Bioinformatics, Center for Informatics, Department of Computational and Quantitative Medicine, City of Hope National Medical Center, Duarte, CA 91010, USA
| | - Atish Mohanty
- Department of Medical Oncology and Therapeutics Research, City of Hope National Medical Center, Duarte, CA 91010, USA
| | - Srisairam Achuthan
- Center for Informatics, Division of Research Informatics, City of Hope National Medical Center, Duarte, CA 91010, USA
| | - Sourabh Kotnala
- Department of Medical Oncology and Therapeutics Research, City of Hope National Medical Center, Duarte, CA 91010, USA
| | - Mohit Kumar Jolly
- Center for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India
| | - Prakash Kulkarni
- Department of Medical Oncology and Therapeutics Research, City of Hope National Medical Center, Duarte, CA 91010, USA
| | - Ravi Salgia
- Department of Medical Oncology and Therapeutics Research, City of Hope National Medical Center, Duarte, CA 91010, USA.
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Chauhan L, Ram U, Hari K, Jolly MK. Topological signatures in regulatory network enable phenotypic heterogeneity in small cell lung cancer. eLife 2021; 10:e64522. [PMID: 33729159 PMCID: PMC8012062 DOI: 10.7554/elife.64522] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2020] [Accepted: 03/16/2021] [Indexed: 02/07/2023] Open
Abstract
Phenotypic (non-genetic) heterogeneity has significant implications for the development and evolution of organs, organisms, and populations. Recent observations in multiple cancers have unraveled the role of phenotypic heterogeneity in driving metastasis and therapy recalcitrance. However, the origins of such phenotypic heterogeneity are poorly understood in most cancers. Here, we investigate a regulatory network underlying phenotypic heterogeneity in small cell lung cancer, a devastating disease with no molecular targeted therapy. Discrete and continuous dynamical simulations of this network reveal its multistable behavior that can explain co-existence of four experimentally observed phenotypes. Analysis of the network topology uncovers that multistability emerges from two teams of players that mutually inhibit each other, but members of a team activate one another, forming a 'toggle switch' between the two teams. Deciphering these topological signatures in cancer-related regulatory networks can unravel their 'latent' design principles and offer a rational approach to characterize phenotypic heterogeneity in a tumor.
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Affiliation(s)
- Lakshya Chauhan
- Centre for BioSystems Science and Engineering, Indian Institute of ScienceBangaloreIndia
- Undergraduate Programme, Indian Institute of ScienceBangaloreIndia
| | - Uday Ram
- Centre for BioSystems Science and Engineering, Indian Institute of ScienceBangaloreIndia
- Undergraduate Programme, Indian Institute of ScienceBangaloreIndia
| | - Kishore Hari
- Centre for BioSystems Science and Engineering, Indian Institute of ScienceBangaloreIndia
| | - Mohit Kumar Jolly
- Centre for BioSystems Science and Engineering, Indian Institute of ScienceBangaloreIndia
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48
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Singh D, Bocci F, Kulkarni P, Jolly MK. Coupled Feedback Loops Involving PAGE4, EMT and Notch Signaling Can Give Rise to Non-genetic Heterogeneity in Prostate Cancer Cells. ENTROPY (BASEL, SWITZERLAND) 2021; 23:288. [PMID: 33652914 PMCID: PMC7996788 DOI: 10.3390/e23030288] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/29/2020] [Revised: 02/18/2021] [Accepted: 02/23/2021] [Indexed: 12/12/2022]
Abstract
Non-genetic heterogeneity is emerging as a crucial factor underlying therapy resistance in multiple cancers. However, the design principles of regulatory networks underlying non-genetic heterogeneity in cancer remain poorly understood. Here, we investigate the coupled dynamics of feedback loops involving (a) oscillations in androgen receptor (AR) signaling mediated through an intrinsically disordered protein PAGE4, (b) multistability in epithelial-mesenchymal transition (EMT), and c) Notch-Delta-Jagged signaling mediated cell-cell communication, each of which can generate non-genetic heterogeneity through multistability and/or oscillations. Our results show how different coupling strengths between AR and EMT signaling can lead to monostability, bistability, or oscillations in the levels of AR, as well as propagation of oscillations to EMT dynamics. These results reveal the emergent dynamics of coupled oscillatory and multi-stable systems and unravel mechanisms by which non-genetic heterogeneity in AR levels can be generated, which can act as a barrier to most existing therapies for prostate cancer patients.
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Affiliation(s)
- Divyoj Singh
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India;
- Undergraduate Programme, Indian Institute of Science, Bangalore 560012, India
| | - Federico Bocci
- Center for Theoretical Biological Physics, Rice University, Houston, TX 77005, USA;
- NSF-Simons Center for Multiscale Cell Fate Research, University of California, Irvine, CA 92697, USA
| | - Prakash Kulkarni
- Department of Medical Oncology and Experimental Therapeutics, City of Hope National Medical Center, Duarte, CA 91010, USA;
| | - Mohit Kumar Jolly
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India;
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49
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Berenguer J, Celià-Terrassa T. Cell memory of epithelial-mesenchymal plasticity in cancer. Curr Opin Cell Biol 2021; 69:103-110. [PMID: 33578288 DOI: 10.1016/j.ceb.2021.01.001] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2020] [Revised: 12/29/2020] [Accepted: 01/04/2021] [Indexed: 11/26/2022]
Abstract
Fundamental biological processes of cell identity and cell fate determination are controlled by complex regulatory networks. These processes require molecular mechanisms that confer cellular phenotypic memory and state persistence. In this minireview, we will summarize mechanisms of cell memory based on regulatory hysteretic feedback loops and explore epigenetic mechanisms widely represented in nature, with special focus on epithelial-to-mesenchymal plasticity. We will also discuss the functional consequences of cell memory and epithelial-to-mesenchymal plasticity dynamics during development and cancer metastasis.
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Affiliation(s)
- Jordi Berenguer
- Cancer Research Program, IMIM (Hospital del Mar Medical Research Institute), 08003 Barcelona, Spain
| | - Toni Celià-Terrassa
- Cancer Research Program, IMIM (Hospital del Mar Medical Research Institute), 08003 Barcelona, Spain.
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50
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Chedere A, Hari K, Kumar S, Rangarajan A, Jolly MK. Multi-Stability and Consequent Phenotypic Plasticity in AMPK-Akt Double Negative Feedback Loop in Cancer Cells. J Clin Med 2021; 10:jcm10030472. [PMID: 33530625 PMCID: PMC7865639 DOI: 10.3390/jcm10030472] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Revised: 01/07/2021] [Accepted: 01/21/2021] [Indexed: 12/23/2022] Open
Abstract
Adaptation and survival of cancer cells to various stress and growth factor conditions is crucial for successful metastasis. A double-negative feedback loop between two serine/threonine kinases AMPK (AMP-activated protein kinase) and Akt can regulate the adaptation of breast cancer cells to matrix-deprivation stress. This feedback loop can significantly generate two phenotypes or cell states: matrix detachment-triggered pAMPKhigh/ pAktlow state, and matrix (re)attachment-triggered pAkthigh/ pAMPKlow state. However, whether these two cell states can exhibit phenotypic plasticity and heterogeneity in a given cell population, i.e., whether they can co-exist and undergo spontaneous switching to generate the other subpopulation, remains unclear. Here, we develop a mechanism-based mathematical model that captures the set of experimentally reported interactions among AMPK and Akt. Our simulations suggest that the AMPK-Akt feedback loop can give rise to two co-existing phenotypes (pAkthigh/ pAMPKlow and pAMPKhigh/pAktlow) in specific parameter regimes. Next, to test the model predictions, we segregated these two subpopulations in MDA-MB-231 cells and observed that each of them was capable of switching to another in adherent conditions. Finally, the predicted trends are supported by clinical data analysis of The Cancer Genome Atlas (TCGA) breast cancer and pan-cancer cohorts that revealed negatively correlated pAMPK and pAkt protein levels. Overall, our integrated computational-experimental approach unravels that AMPK-Akt feedback loop can generate multi-stability and drive phenotypic switching and heterogeneity in a cancer cell population.
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Affiliation(s)
- Adithya Chedere
- Department of Molecular Reproduction, Development, and Genetics, Indian Institute of Science, Bangalore 560012, India; (A.C.); (S.K.)
| | - Kishore Hari
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India;
| | - Saurav Kumar
- Department of Molecular Reproduction, Development, and Genetics, Indian Institute of Science, Bangalore 560012, India; (A.C.); (S.K.)
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India;
- Basic Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Annapoorni Rangarajan
- Department of Molecular Reproduction, Development, and Genetics, Indian Institute of Science, Bangalore 560012, India; (A.C.); (S.K.)
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India;
- Correspondence: (A.R.); (M.K.J.)
| | - Mohit Kumar Jolly
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India;
- Correspondence: (A.R.); (M.K.J.)
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