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Picco G, Rao Y, Al Saedi A, Lee Y, Vieira SF, Bhosle S, May K, Herranz-Ors C, Walker SJ, Shenje R, Dincer C, Gibson F, Banerjee R, Hewitson Z, Werner T, Cottom JE, Peng Y, Deng N, Zhang Y, Nartey EN, Nickels L, Landis P, Conticelli D, McCarten K, Bush J, Sharma M, Lightfoot H, House D, Milford E, Grant EK, Glogowski MP, Wagner CD, Bantscheff M, Rutkowska-Klute A, Zappacosta F, Pettinger J, Barthorpe S, Eberl HC, Jones BT, Schneck JL, Murphy DJ, Voest EE, Taygerly JP, DeMartino MP, Coelho MA, Houseley J, Sharma G, Schwartz B, Garnett MJ. Novel WRN Helicase Inhibitors Selectively Target Microsatellite-Unstable Cancer Cells. Cancer Discov 2024; 14:1457-1475. [PMID: 38587317 DOI: 10.1158/2159-8290.cd-24-0052] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2024] [Revised: 03/26/2024] [Accepted: 04/05/2024] [Indexed: 04/09/2024]
Abstract
Microsatellite-unstable (MSI) cancers require WRN helicase to resolve replication stress due to expanded DNA (TA)n dinucleotide repeats. WRN is a promising synthetic lethal target for MSI tumors, and WRN inhibitors are in development. In this study, we used CRISPR-Cas9 base editing to map WRN residues critical for MSI cells, validating the helicase domain as the primary drug target. Fragment-based screening led to the development of potent and highly selective WRN helicase covalent inhibitors. These compounds selectively suppressed MSI model growth in vitro and in vivo by mimicking WRN loss, inducing DNA double-strand breaks at expanded TA repeats and DNA damage. Assessment of biomarkers in preclinical models linked TA-repeat expansions and mismatch repair alterations to compound activity. Efficacy was confirmed in immunotherapy-resistant organoids and patient-derived xenograft models. The discovery of potent, selective covalent WRN inhibitors provides proof of concept for synthetic lethal targeting of WRN in MSI cancer and tools to dissect WRN biology. Significance: We report the discovery and characterization of potent, selective WRN helicase inhibitors for MSI cancer treatment, with biomarker analysis and evaluation of efficacy in vivo and in immunotherapy-refractory preclinical models. These findings pave the way to translate WRN inhibition into MSI cancer therapies and provide tools to investigate WRN biology. See related commentary by Wainberg, p. 1369.
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Affiliation(s)
| | | | | | - Yang Lee
- GSK, Upper Providence, Pennsylvania
| | | | | | - Kieron May
- Epigenetics Programme, Babraham Institute, Cambridge, UK
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Emile E Voest
- Netherlands Cancer Institute, Amsterdam, the Netherlands
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2
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Huseman ED, Lo A, Fedorova O, Elia JL, Gueble SE, Lin K, Sundaram RK, Oh J, Liu J, Menges F, Rees MG, Ronan MM, Roth JA, Batista VS, Crawford JM, Pyle AM, Bindra RS, Herzon SB. Mechanism of Action of KL-50, a Candidate Imidazotetrazine for the Treatment of Drug-Resistant Brain Cancers. J Am Chem Soc 2024; 146:18241-18252. [PMID: 38815248 DOI: 10.1021/jacs.3c06483] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/01/2024]
Abstract
Aberrant DNA repair is a hallmark of cancer, and many tumors display reduced DNA repair capacities that sensitize them to genotoxins. Here, we demonstrate that the differential DNA repair capacities of healthy and transformed tissue may be exploited to obtain highly selective chemotherapies. We show that the novel N3-(2-fluoroethyl)imidazotetrazine "KL-50" is a selective toxin toward tumors that lack the DNA repair protein O6-methylguanine-DNA-methyltransferase (MGMT), which reverses the formation of O6-alkylguanine lesions. We establish that KL-50 generates DNA interstrand cross-links (ICLs) by a multistep process comprising DNA alkylation to generate an O6-(2-fluoroethyl)guanine (O6FEtG) lesion, slow unimolecular displacement of fluoride to form an N1,O6-ethanoguanine (N1,O6EtG) intermediate, and ring-opening by the adjacent cytidine. The slow rate of N1,O6EtG formation allows healthy cells expressing MGMT to reverse the initial O6FEtG lesion before it evolves to N1,O6EtG, thereby suppressing the formation of toxic DNA-MGMT cross-links and reducing the amount of DNA ICLs generated in healthy cells. In contrast, O6-(2-chloroethyl)guanine lesions produced by agents such as lomustine and the N3-(2-chloroethyl)imidazotetrazine mitozolomide rapidly evolve to N1,O6EtG, resulting in the formation of DNA-MGMT cross-links and DNA ICLs in healthy tissue. These studies suggest that careful consideration of the rates of chemical DNA modification and biochemical DNA repair may lead to the identification of other tumor-specific genotoxic agents.
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Affiliation(s)
- Eric D Huseman
- Department of Chemistry, Yale University, New Haven, Connecticut 06520, United States
| | - Anna Lo
- Department of Chemistry, Yale University, New Haven, Connecticut 06520, United States
| | - Olga Fedorova
- Department of Molecular, Cellular, and Developmental Biology, Yale University, New Haven, Connecticut 06520, United States
- Howard Hughes Medical Institute, New Haven, Connecticut 06520, United States
| | - James L Elia
- Department of Pathology, Yale School of Medicine, New Haven, Connecticut 06520, United States
| | - Susan E Gueble
- Department of Therapeutic Radiology, Yale School of Medicine, New Haven, Connecticut 06520, United States
| | - Kingson Lin
- Department of Chemistry, Yale University, New Haven, Connecticut 06520, United States
- Department of Pathology, Yale School of Medicine, New Haven, Connecticut 06520, United States
- Department of Therapeutic Radiology, Yale School of Medicine, New Haven, Connecticut 06520, United States
| | - Ranjini K Sundaram
- Department of Therapeutic Radiology, Yale School of Medicine, New Haven, Connecticut 06520, United States
| | - Joonseok Oh
- Department of Chemistry, Yale University, New Haven, Connecticut 06520, United States
- Institute of Biomolecular Design & Discovery, Yale University, West Haven, Connecticut 06516, United States
| | - Jinchan Liu
- Department of Chemistry, Yale University, New Haven, Connecticut 06520, United States
| | - Fabian Menges
- Department of Chemistry, Yale University, New Haven, Connecticut 06520, United States
- Department of Chemistry, Chemical and Biophysical Instrumentation Center, Yale University, New Haven, Connecticut 06520, United States
| | - Matthew G Rees
- Broad Institute of MIT and Harvard; Cambridge, Massachusetts 02142, United States
| | - Melissa M Ronan
- Broad Institute of MIT and Harvard; Cambridge, Massachusetts 02142, United States
| | - Jennifer A Roth
- Broad Institute of MIT and Harvard; Cambridge, Massachusetts 02142, United States
| | - Victor S Batista
- Department of Chemistry, Yale University, New Haven, Connecticut 06520, United States
| | - Jason M Crawford
- Department of Chemistry, Yale University, New Haven, Connecticut 06520, United States
- Department of Chemistry, Chemical and Biophysical Instrumentation Center, Yale University, New Haven, Connecticut 06520, United States
- Department of Microbial Pathogenesis, Yale School of Medicine; New Haven, Connecticut 06520, United States
| | - Anna M Pyle
- Department of Chemistry, Yale University, New Haven, Connecticut 06520, United States
- Department of Molecular, Cellular, and Developmental Biology, Yale University, New Haven, Connecticut 06520, United States
- Howard Hughes Medical Institute, New Haven, Connecticut 06520, United States
| | - Ranjit S Bindra
- Department of Pathology, Yale School of Medicine, New Haven, Connecticut 06520, United States
- Department of Therapeutic Radiology, Yale School of Medicine, New Haven, Connecticut 06520, United States
| | - Seth B Herzon
- Department of Chemistry, Yale University, New Haven, Connecticut 06520, United States
- Department of Therapeutic Radiology, Yale School of Medicine, New Haven, Connecticut 06520, United States
- Department of Pharmacology, Yale School of Medicine; New Haven, Connecticut 06520, United States
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3
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Li X, González-Maroto C, Tavassoli M. Crosstalk between CAFs and tumour cells in head and neck cancer. Cell Death Discov 2024; 10:303. [PMID: 38926351 PMCID: PMC11208506 DOI: 10.1038/s41420-024-02053-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Revised: 05/30/2024] [Accepted: 05/31/2024] [Indexed: 06/28/2024] Open
Abstract
Head and neck squamous cell carcinomas (HNSCCs) are amongst the most aggressive, complex, and heterogeneous malignancies. The standard of care treatments for HNC patients include surgery, radiotherapy, chemotherapy, or their combination. However, around 50% do not benefit while suffering severe toxic side effects, costing the individuals and society. Decades have been spent to improve HNSCC treatment outcomes with only limited success. Much of the research in HNSCC treatment has focused on understanding the genetics of the HNSCC malignant cells, but it has become clear that tumour microenvironment (TME) plays an important role in the progression as well as treatment response in HNSCC. Understanding the crosstalk between cancer cells and TME is crucial for inhibiting progression and treatment resistance. Cancer-associated fibroblasts (CAFs), the predominant component of stroma in HNSCC, serve as the primary source of extra-cellular matrix (ECM) and various pro-tumoral composites in TME. The activation of CAFs in HNSCC is primarily driven by cancer cell-secreted molecules, which in turn induce phenotypic changes, elevated secretive status, and altered ECM production profile. Concurrently, CAFs play a pivotal role in modulating the cell cycle, stemness, epithelial-mesenchymal transition (EMT), and resistance to targeted and chemoradiotherapy in HNSCC cells. This modulation occurs through interactions with secreted molecules or direct contact with the ECM or CAF. Co-culture and 3D models of tumour cells and other TME cell types allows to mimic the HNSCC tumour milieu and enable modulating tumour hypoxia and reprograming cancer stem cells (CSC). This review aims to provide an update on the development of HNSCC tumour models comprising CAFs to obtain better understanding of the interaction between CAFs and tumour cells, and for providing preclinical testing platforms of current and combination with emerging therapeutics.
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Affiliation(s)
- Xinyang Li
- Head and Neck Oncology Group, Centre for Host Microbiome Interaction, King's College London, Hodgkin Building, London, SE1 1UL, UK
| | - Celia González-Maroto
- Head and Neck Oncology Group, Centre for Host Microbiome Interaction, King's College London, Hodgkin Building, London, SE1 1UL, UK
- Blizard Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Mahvash Tavassoli
- Head and Neck Oncology Group, Centre for Host Microbiome Interaction, King's College London, Hodgkin Building, London, SE1 1UL, UK.
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4
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Walpole IR, Zaman FY, Zhao P, Marshall VM, Lin FP, Thomas DM, Shackleton M, Antolin AA, Ameratunga M. Computational repurposing of oncology drugs through off-target drug binding interactions from pharmacological databases. Clin Transl Med 2024; 14:e1657. [PMID: 38629623 PMCID: PMC11022299 DOI: 10.1002/ctm2.1657] [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: 11/09/2023] [Revised: 03/25/2024] [Accepted: 03/30/2024] [Indexed: 04/19/2024] Open
Abstract
PURPOSE Systematic repurposing of approved medicines for another indication may accelerate drug development in oncology. We present a strategy combining biomarker testing with drug repurposing to identify new treatments for patients with advanced cancer. METHODS Tumours were sequenced with the Illumina TruSight Oncology 500 (TSO-500) platform or the FoundationOne CDx panel. Mutations were screened by two medical oncologists and pathogenic mutations were categorised referencing literature. Variants of unknown significance were classified as potentially pathogenic using plausible mechanisms and computational prediction of pathogenicity. Gain of function (GOF) mutations were evaluated through repurposing databases Probe Miner (PM), Broad Institute Drug Repurposing Hub (Broad Institute DRH) and TOPOGRAPH. GOF mutations were repurposing events if identified in PM, not indexed in TOPOGRAPH and excluding mutations with a known Food and Drug Administration (FDA)-approved biomarker. The computational repurposing approach was validated by evaluating its ability to identify FDA-approved biomarkers. The total repurposable genome was identified by evaluating all possible gene-FDA drug-approved combinations in the PM dataset. RESULTS The computational repurposing approach was accurate at identifying FDA therapies with known biomarkers (94%). Using next-generation sequencing molecular reports (n = 94), a meaningful percentage of patients (14%) could have an off-label therapeutic identified. The frequency of theoretical drug repurposing events in The Cancer Genome Atlas pan-cancer dataset was 73% of the samples in the cohort. CONCLUSION A computational drug repurposing approach may assist in identifying novel repurposing events in cancer patients with no access to standard therapies. Further validation is needed to confirm a precision oncology approach using drug repurposing.
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Affiliation(s)
| | - Farzana Y Zaman
- Department of Medical OncologyThe Alfred HospitalMelbourneAustralia
| | - Peinan Zhao
- School of Translational MedicineMonash UniversityMelbourneAustralia
| | | | - Frank P. Lin
- NHMRC Clinical Trials CentreUniversity of SydneySydneyAustralia
- Garvan Institute of Medical ResearchSt Vincent's Clinical SchoolFaculty of MedicineUNSWDarlinghurstAustralia
| | - David M. Thomas
- Garvan Institute of Medical ResearchSt Vincent's Clinical SchoolFaculty of MedicineUNSWDarlinghurstAustralia
| | - Mark Shackleton
- Department of Medical OncologyThe Alfred HospitalMelbourneAustralia
- School of Translational MedicineMonash UniversityMelbourneAustralia
| | - Albert A. Antolin
- ProCURE, Catalan Institute of Oncology (ICO)Oncobell, Bellvitge Institute for Biomedical Research (IDIBELL)BarcelonaSpain
- The Division of Cancer TherapeuticsCenter for Cancer Drug DiscoveryThe Institute of Cancer ResearchLondonUK
| | - Malaka Ameratunga
- Department of Medical OncologyThe Alfred HospitalMelbourneAustralia
- School of Translational MedicineMonash UniversityMelbourneAustralia
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5
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Deben C, Boullosa LF, Fortes FR, De La Hoz EC, Le Compte M, Seghers S, Peeters M, Vanlanduit S, Lin A, Dijkstra KK, Van Schil P, Hendriks JMH, Prenen H, Roeyen G, Lardon F, Smits E. Auranofin repurposing for lung and pancreatic cancer: low CA12 expression as a marker of sensitivity in patient-derived organoids, with potentiated efficacy by AKT inhibition. J Exp Clin Cancer Res 2024; 43:88. [PMID: 38515178 PMCID: PMC10958863 DOI: 10.1186/s13046-024-03012-z] [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: 01/02/2024] [Accepted: 03/14/2024] [Indexed: 03/23/2024] Open
Abstract
BACKGROUND This study explores the repurposing of Auranofin (AF), an anti-rheumatic drug, for treating non-small cell lung cancer (NSCLC) adenocarcinoma and pancreatic ductal adenocarcinoma (PDAC). Drug repurposing in oncology offers a cost-effective and time-efficient approach to developing new cancer therapies. Our research focuses on evaluating AF's selective cytotoxicity against cancer cells, identifying RNAseq-based biomarkers to predict AF response, and finding the most effective co-therapeutic agents for combination with AF. METHODS Our investigation employed a comprehensive drug screening of AF in combination with eleven anticancer agents in cancerous PDAC and NSCLC patient-derived organoids (n = 7), and non-cancerous pulmonary organoids (n = 2). Additionally, we conducted RNA sequencing to identify potential biomarkers for AF sensitivity and experimented with various drug combinations to optimize AF's therapeutic efficacy. RESULTS The results revealed that AF demonstrates a preferential cytotoxic effect on NSCLC and PDAC cancer cells at clinically relevant concentrations below 1 µM, sparing normal epithelial cells. We identified Carbonic Anhydrase 12 (CA12) as a significant RNAseq-based biomarker, closely associated with the NF-κB survival signaling pathway, which is crucial in cancer cell response to oxidative stress. Our findings suggest that cancer cells with low CA12 expression are more susceptible to AF treatment. Furthermore, the combination of AF with the AKT inhibitor MK2206 was found to be particularly effective, exhibiting potent and selective cytotoxic synergy, especially in tumor organoid models classified as intermediate responders to AF, without adverse effects on healthy organoids. CONCLUSION Our research offers valuable insights into the use of AF for treating NSCLC and PDAC. It highlights AF's cancer cell selectivity, establishes CA12 as a predictive biomarker for AF sensitivity, and underscores the enhanced efficacy of AF when combined with MK2206 and other therapeutics. These findings pave the way for further exploration of AF in cancer treatment, particularly in identifying patient populations most likely to benefit from its use and in optimizing combination therapies for improved patient outcomes.
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Affiliation(s)
- Christophe Deben
- Center for Oncological Research (CORE), Integrated Personalized & Precision Oncology Network (IPPON), University of Antwerp, Wilrijk, Belgium.
| | - Laurie Freire Boullosa
- Center for Oncological Research (CORE), Integrated Personalized & Precision Oncology Network (IPPON), University of Antwerp, Wilrijk, Belgium
| | - Felicia Rodrigues Fortes
- Center for Oncological Research (CORE), Integrated Personalized & Precision Oncology Network (IPPON), University of Antwerp, Wilrijk, Belgium
| | | | - Maxim Le Compte
- Center for Oncological Research (CORE), Integrated Personalized & Precision Oncology Network (IPPON), University of Antwerp, Wilrijk, Belgium
| | - Sofie Seghers
- Center for Oncological Research (CORE), Integrated Personalized & Precision Oncology Network (IPPON), University of Antwerp, Wilrijk, Belgium
| | - Marc Peeters
- Center for Oncological Research (CORE), Integrated Personalized & Precision Oncology Network (IPPON), University of Antwerp, Wilrijk, Belgium
| | | | - Abraham Lin
- Center for Oncological Research (CORE), Integrated Personalized & Precision Oncology Network (IPPON), University of Antwerp, Wilrijk, Belgium
- Plasma Lab for Applications in Sustainability and Medicine ANTwerp (PLASMANT), University of Antwerp, Wilrijk, Belgium
| | - Krijn K Dijkstra
- Department of Molecular Oncology and Immunology, the Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands
- Oncode Institute, Utrecht, The Netherlands
| | - Paul Van Schil
- Center for Oncological Research (CORE), Integrated Personalized & Precision Oncology Network (IPPON), University of Antwerp, Wilrijk, Belgium
- Department of Thoracic and Vascular Surgery, Antwerp University Hospital, Edegem, Belgium
| | - Jeroen M H Hendriks
- Center for Oncological Research (CORE), Integrated Personalized & Precision Oncology Network (IPPON), University of Antwerp, Wilrijk, Belgium
- Department of Thoracic and Vascular Surgery, Antwerp University Hospital, Edegem, Belgium
| | - Hans Prenen
- Center for Oncological Research (CORE), Integrated Personalized & Precision Oncology Network (IPPON), University of Antwerp, Wilrijk, Belgium
- Department of Oncology, Multidisciplinary Oncological Center Antwerp, Antwerp University Hospital, Antwerp, Belgium
| | - Geert Roeyen
- Center for Oncological Research (CORE), Integrated Personalized & Precision Oncology Network (IPPON), University of Antwerp, Wilrijk, Belgium
- Department of Hepatobiliary Transplantation and Endocrine Surgery, University Hospital Antwerp (UZA), Edegem, Belgium
| | - Filip Lardon
- Center for Oncological Research (CORE), Integrated Personalized & Precision Oncology Network (IPPON), University of Antwerp, Wilrijk, Belgium
| | - Evelien Smits
- Center for Oncological Research (CORE), Integrated Personalized & Precision Oncology Network (IPPON), University of Antwerp, Wilrijk, Belgium
- Center for Cell Therapy and Regenerative Medicine, Antwerp University Hospital, Edegem, Belgium
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6
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Tomasi F, Pozzi M, Lauria M. Investigating the mechanisms underlying resistance to chemoterapy and to CRISPR-Cas9 in cancer cell lines. Sci Rep 2024; 14:5402. [PMID: 38443409 PMCID: PMC10915165 DOI: 10.1038/s41598-024-55138-x] [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: 07/03/2023] [Accepted: 02/20/2024] [Indexed: 03/07/2024] Open
Abstract
Cancer is one of the major causes of death worldwide and the development of multidrug resistance (MDR) in cancer cells is the principal cause of chemotherapy failure. To gain insights into the specific mechanisms of MDR in cancer cell lines, we developed a novel method for the combined analysis of recently published datasets on drug sensitivity and CRISPR loss-of-function screens for the same set of cancer cell lines. For our analysis, we first selected cell lines that consistently exhibit drug resistance across several classes of compounds. We then identified putative resistance genes for each class of compound and used inferred gene regulatory networks (GRNs) to study possible mechanisms underlying the development of MDR in the identified cancer cell lines. We show that the same method of analysis can also be used to identify cell lines that consistently exhibit resistance to the gene knockout effect of the CRISPR-Cas9 technique and to study the possible underlying mechanisms. In the GRN associated to the drug resistant cell lines, we identify genes previously associated with resistance (UHMK1, RALYL, MGST3, USP9X, and ESRG), genes for which an indirect association can be identified (SPINK13, LINC00664, MRPL38, and EMILIN3), and genes that are found to be overexpressed in non-resistant cancer cell lines (MRPL38, EMILIN3 and RALYL). In the GRNs associated to the CRISPR-Cas9 resistance mechanism, none of the identified genes has been previously reported in the admittedly sparse literature on the subject. However, some of these genes have a common role: APBB2, RUNX1T1, ZBTB7C, and ISX regulate transcription, while APBB2, BTG3, ZBTB7C, SZRD1 and LEF1 have a function in regulating proliferation, suggesting a role for these two pathways. While our results are specific for the lung cancer cell lines we selected for this work, our method of analysis can be applied to cell lines from other tissues and for which the required data is available.
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Affiliation(s)
| | - Matteo Pozzi
- CIBIO Department, University of Trento, Povo, Italy
- Fondazione Bruno Kessler, Povo, Italy
| | - Mario Lauria
- Department of Mathematics, University of Trento, Povo, Italy.
- Fondazione The Microsoft Research - University of Trento Centre for Computational and Systems Biology, Rovereto, Italy.
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7
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Matthews ER, Johnson OD, Horn KJ, Gutiérrez JA, Powell SR, Ward MC. Anthracyclines induce cardiotoxicity through a shared gene expression response signature. PLoS Genet 2024; 20:e1011164. [PMID: 38416769 PMCID: PMC10927150 DOI: 10.1371/journal.pgen.1011164] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2023] [Revised: 03/11/2024] [Accepted: 01/31/2024] [Indexed: 03/01/2024] Open
Abstract
TOP2 inhibitors (TOP2i) are effective drugs for breast cancer treatment. However, they can cause cardiotoxicity in some women. The most widely used TOP2i include anthracyclines (AC) Doxorubicin (DOX), Daunorubicin (DNR), Epirubicin (EPI), and the anthraquinone Mitoxantrone (MTX). It is unclear whether women would experience the same adverse effects from all drugs in this class, or if specific drugs would be preferable for certain individuals based on their cardiotoxicity risk profile. To investigate this, we studied the effects of treatment of DOX, DNR, EPI, MTX, and an unrelated monoclonal antibody Trastuzumab (TRZ) on iPSC-derived cardiomyocytes (iPSC-CMs) from six healthy females. All TOP2i induce cell death at concentrations observed in cancer patient serum, while TRZ does not. A sub-lethal dose of all TOP2i induces limited cellular stress but affects calcium handling, a function critical for cardiomyocyte contraction. TOP2i induce thousands of gene expression changes over time, giving rise to four distinct gene expression response signatures, denoted as TOP2i early-acute, early-sustained, and late response genes, and non-response genes. There is no drug- or AC-specific signature. TOP2i early response genes are enriched in chromatin regulators, which mediate AC sensitivity across breast cancer patients. However, there is increased transcriptional variability between individuals following AC treatments. To investigate potential genetic effects on response variability, we first identified a reported set of expression quantitative trait loci (eQTLs) uncovered following DOX treatment in iPSC-CMs. Indeed, DOX response eQTLs are enriched in genes that respond to all TOP2i. Next, we identified 38 genes in loci associated with AC toxicity by GWAS or TWAS. Two thirds of the genes that respond to at least one TOP2i, respond to all ACs with the same direction of effect. Our data demonstrate that TOP2i induce thousands of shared gene expression changes in cardiomyocytes, including genes near SNPs associated with inter-individual variation in response to DOX treatment and AC-induced cardiotoxicity.
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Affiliation(s)
- E. Renee Matthews
- Department of Biochemistry and Molecular Biology, University of Texas Medical Branch, Galveston, Texas, United States of America
| | - Omar D. Johnson
- Biochemistry, Cellular and Molecular Biology Graduate Program, University of Texas Medical Branch, Galveston, Texas, United States of America
| | - Kandace J. Horn
- John Sealy School of Medicine, University of Texas Medical Branch, Galveston, Texas, United States of America
| | - José A. Gutiérrez
- Department of Biochemistry and Molecular Biology, University of Texas Medical Branch, Galveston, Texas, United States of America
| | - Simon R. Powell
- Neuroscience Graduate Program, University of Texas Medical Branch, Galveston, Texas, United States of America
| | - Michelle C. Ward
- Department of Biochemistry and Molecular Biology, University of Texas Medical Branch, Galveston, Texas, United States of America
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8
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Yang Z, Shi M, Liang Y, Zhang F, Li C, Lu Y, Yin T, Wang Z, Li Y, Hao M, Guo R, Yang H, Lei G, Sun F, Zhang Y, Deng Z, Tian Y, Yu L, Bai C, Wang L, Wan C, Wang H, Yang P. Three-dimensional chromatin landscapes in hepatocellular carcinoma associated with hepatitis B virus. J Gastroenterol 2024; 59:119-137. [PMID: 37925679 DOI: 10.1007/s00535-023-02053-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Accepted: 10/11/2023] [Indexed: 11/07/2023]
Abstract
BACKGROUND Three-dimensional (3D) chromatin architecture frequently altered in cancer. However, its changes during the pathogenesis of hepatocellular carcinoma (HCC) remained elusive. METHODS Hi-C and RNA-seq were applied to study the 3D chromatin landscapes and gene expression of HCC and ANHT. Hi-C Pro was used to generate genome-wide raw interaction matrices, which were normalized via iterative correction (ICE). Moreover, the chromosomes were divided into different compartments according to the first principal component (E1). Furthermore, topologically associated domains (TADs) were visualized via WashU Epigenome Browser. Furthermore, differential expression analysis of ANHT and HCC was performed using the DESeq2 R package. Additionally, dysregulated genes associated with 3D genome architecture altered were confirmed using TCGA, qRT-PCR, immunohistochemistry (IHC), etc. RESULTS: First, the intrachromosomal interactions of chr1, chr2, chr5, and chr11 were significantly different, and the interchromosomal interactions of chr4-chr10, chr13-chr21, chr15-chr22, and chr16-chr19 are remarkably different between ANHT and HCC, which resulted in the up-regulation of TP53I3 and ZNF738 and the down-regulation of APOC3 and APOA5 in HCC. Second, 49 compartment regions on 18 chromosomes have significantly switched (A-B or B-A) during HCC tumorigenesis, contributing to up-regulation of RAP2A. Finally, a tumor-specific TAD boundary located on chr5: 6271000-6478000 and enhancer hijacking were identified in HCC tissues, potentially associated with the elevated expression of MED10, whose expression were associated with poor prognosis of HCC patients. CONCLUSION This study demonstrates the crucial role of chromosomal structure variation in HCC oncogenesis and potential novel biomarkers of HCC, laying a foundation for cancer precision medicine development.
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Affiliation(s)
- Zhao Yang
- College of Life Science and Technology, Innovation Center of Molecular Diagnostics, Beijing University of Chemical Technology, Beijing, 100029, China.
- The First Medical Center, Chinese PLA General Hospital, Beijing, 100853, China.
- College of Life Science and Technology, Key Laboratory of Protection and Utilization of Biological Resources in Tarim Basin of Xinjiang Production and Construction Corps, Tarim University, Alar, 843300, Xinjiang, China.
| | - Mengran Shi
- College of Life Science and Technology, Innovation Center of Molecular Diagnostics, Beijing University of Chemical Technology, Beijing, 100029, China
| | - Youfeng Liang
- College of Life Science and Technology, Innovation Center of Molecular Diagnostics, Beijing University of Chemical Technology, Beijing, 100029, China
| | - Fuhan Zhang
- College of Life Science and Technology, Innovation Center of Molecular Diagnostics, Beijing University of Chemical Technology, Beijing, 100029, China
| | - Cong Li
- The First Medical Center, Chinese PLA General Hospital, Beijing, 100853, China
| | - Yinying Lu
- The Fifth Medical Center, Chinese PLA General Hospital, Beijing, 100039, China
| | - Taian Yin
- College of Life Science and Technology, Innovation Center of Molecular Diagnostics, Beijing University of Chemical Technology, Beijing, 100029, China
| | - Zhaohai Wang
- The First Medical Center, Chinese PLA General Hospital, Beijing, 100853, China
| | - Yongchao Li
- College of Life Science and Technology, Innovation Center of Molecular Diagnostics, Beijing University of Chemical Technology, Beijing, 100029, China
- College of Life Science and Technology, Key Laboratory of Protection and Utilization of Biological Resources in Tarim Basin of Xinjiang Production and Construction Corps, Tarim University, Alar, 843300, Xinjiang, China
| | - Mingxuan Hao
- College of Life Science and Technology, Innovation Center of Molecular Diagnostics, Beijing University of Chemical Technology, Beijing, 100029, China
| | - Rui Guo
- College of Life Science and Technology, Innovation Center of Molecular Diagnostics, Beijing University of Chemical Technology, Beijing, 100029, China
| | - Hao Yang
- The First Medical Center, Chinese PLA General Hospital, Beijing, 100853, China
| | - Guanglin Lei
- The Fifth Medical Center, Chinese PLA General Hospital, Beijing, 100039, China
| | - Fang Sun
- The Fifth Medical Center, Chinese PLA General Hospital, Beijing, 100039, China
| | - Yu Zhang
- The Fifth Medical Center, Chinese PLA General Hospital, Beijing, 100039, China
| | - Zhuoya Deng
- The First Medical Center, Chinese PLA General Hospital, Beijing, 100853, China
| | - Yuying Tian
- The First Medical Center, Chinese PLA General Hospital, Beijing, 100853, China
| | - Linxiang Yu
- The Fifth Medical Center, Chinese PLA General Hospital, Beijing, 100039, China
| | - Changqing Bai
- Department of Respiratory, Shenzhen University General Hospital, Shenzhen, 518055, China
| | - Lei Wang
- College of Life Science and Technology, Innovation Center of Molecular Diagnostics, Beijing University of Chemical Technology, Beijing, 100029, China
| | - Chuanxing Wan
- College of Life Science and Technology, Key Laboratory of Protection and Utilization of Biological Resources in Tarim Basin of Xinjiang Production and Construction Corps, Tarim University, Alar, 843300, Xinjiang, China
| | - Haifeng Wang
- Department of Urology, Second Affiliated Hospital of Kunming Medical University, Kunming, 650504, China.
| | - Penghui Yang
- The First Medical Center, Chinese PLA General Hospital, Beijing, 100853, China.
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9
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Kervarrec T, Pissaloux D, Tirode F, de la Fouchardière A, Sohier P, Frouin E, Hamard A, Houben R, Schrama D, Barlier A, Cribier B, Battistella M, Macagno N. Gene fusions in poroma, porocarcinoma and related adnexal skin tumours: An update. Histopathology 2024; 84:266-278. [PMID: 37609771 DOI: 10.1111/his.15023] [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: 06/14/2023] [Revised: 07/24/2023] [Accepted: 07/25/2023] [Indexed: 08/24/2023]
Abstract
Poroma is a benign sweat gland tumour showing morphological features recapitulating the superficial portion of the eccrine sweat coil. A subset of poromas may transform into porocarcinoma, its malignant counterpart. Poroma and porocarcinoma are characterised by recurrent gene fusions involving YAP1, a transcriptional co-activator, which is controlled by the Hippo signalling pathway. The fusion genes frequently involve MAML2 and NUTM1, which are also rearranged in other cutaneous and extracutaneous neoplasms. We aimed to review the clinical, morphological and molecular features of this category of adnexal neoplasms with a special focus upon emerging differential diagnoses, and discuss how their systematic molecular characterisation may contribute to a standardisation of diagnosis, more accurate classification and, ultimately, refinement of their prognosis and therapeutic modalities.
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Affiliation(s)
- Thibault Kervarrec
- CARADERM, French Network of Rare Cutaneous Cancer, Lille, France
- Department of Pathology, University Hospital of Tours, Tours, France
- 'Biologie des infections à polyomavirus' Team, UMR1282 INRAE, University of Tours, Tours, France
| | | | - Franck Tirode
- Department of Biopathology, Center Léon Bérard, Lyon, France
- Centre Léon Bérard, Cancer Research Center of Lyon, Equipe Labellisée, University of Lyon, Université Claude Bernard Lyon 1, INSERM 1052, CNRS 5286, Lyon, France
| | - Arnaud de la Fouchardière
- CARADERM, French Network of Rare Cutaneous Cancer, Lille, France
- Department of Biopathology, Center Léon Bérard, Lyon, France
- Centre Léon Bérard, Cancer Research Center of Lyon, Equipe Labellisée, University of Lyon, Université Claude Bernard Lyon 1, INSERM 1052, CNRS 5286, Lyon, France
| | - Pierre Sohier
- CARADERM, French Network of Rare Cutaneous Cancer, Lille, France
- Department of Pathology, Hôpital Cochin, AP-HP, AP-HP Centre - Université Paris Cité, Paris, France
- Faculté de Médecine, University Paris Cité, Paris, France
| | - Eric Frouin
- CARADERM, French Network of Rare Cutaneous Cancer, Lille, France
- Department of Pathology, University Hospital of Poitiers, University of Poitiers, LITEC, Poitiers, France
| | - Aymeric Hamard
- Department of Pathology, University Hospital of Tours, Tours, France
| | - Roland Houben
- Department of Dermatology, Venereology and Allergology, University Hospital Würzburg, Würzburg, Germany
| | - David Schrama
- Department of Dermatology, Venereology and Allergology, University Hospital Würzburg, Würzburg, Germany
| | - Anne Barlier
- Aix-Marseille Univ, INSERM, MMG, U1251, Marmara Institute, Marseille, France
- Laboratory of Molecular Biology, La Conception Hospital, Marseille, France
| | - Bernard Cribier
- CARADERM, French Network of Rare Cutaneous Cancer, Lille, France
- Clinique Dermatologique, Hôpital Civil, Hôpitaux Universitaires, Université de Strasbourg, Strasbourg, France
| | - Maxime Battistella
- CARADERM, French Network of Rare Cutaneous Cancer, Lille, France
- Department of Pathology, Hospital Saint-Louis, AP-HP, Université Paris Cité, INSERM U976, Paris, France
| | - Nicolas Macagno
- CARADERM, French Network of Rare Cutaneous Cancer, Lille, France
- Aix-Marseille Univ, INSERM, MMG, U1251, Marmara Institute, Marseille, France
- Department of Pathology, APHM, Timone University Hospital, Marseille, France
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10
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MacKeracher A, Arnoldo A, Siddaway R, Surrey LF, Somers GR. The Incidence of Multiple Fusions in a Series of Pediatric Soft Tissue and Bone Tumors. Pediatr Dev Pathol 2024; 27:3-12. [PMID: 37771132 PMCID: PMC10800079 DOI: 10.1177/10935266231199928] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 09/30/2023]
Abstract
BACKGROUND Next generation sequencing (NGS) has increased the detection of fusion genes in cancer. NGS has found multiple fusions in single tumor samples; however, the incidence of this in pediatric soft tissue and bone tumors (PSTBTs) is not well documented. The aim of this study is to catalogue the incidence of multiple fusions in a series of PSTBTs, and apply a modified gene fusion classification system to determine clinical relevance. METHODOLOGY RNA from 78 bone and soft tissue tumors and 7 external quality assessment samples were sequenced and analyzed using recently-described Metafusion (MF) software and classified using a modification of previously-published schema for fusion classification into 3 tiers: 1, strong clinical significance; 2, potential clinical significance; and 3, unknown clinical significance. RESULTS One-hundred forty-five fusions were detected in 85 samples. Fifty-five samples (65%) had a single fusion and 30 (35%) had more than 1 fusion. No samples contained more than 1 tier 1 fusion. There were 40 tier 1 (28%), 36 tier 2 (24%), and 69 (48%) tier 3 fusions. CONCLUSIONS A significant percentage of PSTBTs harbor more than 1 fusion, and by applying a modified fusion classification scheme, the potential clinical relevance of such fusions can be determined.
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Affiliation(s)
- Anastasia MacKeracher
- Department of Paediatric Laboratory Medicine, Hospital for Sick Children, Toronto, ON, Canada
| | - Anthony Arnoldo
- Department of Paediatric Laboratory Medicine, Hospital for Sick Children, Toronto, ON, Canada
| | - Robert Siddaway
- Department of Paediatric Laboratory Medicine, Hospital for Sick Children, Toronto, ON, Canada
| | - Lea F. Surrey
- Department of Pathology and Laboratory Medicine, Children’s Hospital of Philadelphia, University of Pennsylvania, Philadelphia, PA, USA
| | - Gino R. Somers
- Department of Paediatric Laboratory Medicine, Hospital for Sick Children, Toronto, ON, Canada
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada
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11
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Welch DL, Fridley BL, Cen L, Teer JK, Yoder SJ, Pettersson F, Xu L, Cheng CH, Zhang Y, Alexandrow MG, Xiang S, Robertson-Tessi M, Brown JS, Metts J, Brohl AS, Reed DR. Modeling phenotypic heterogeneity towards evolutionarily inspired osteosarcoma therapy. Sci Rep 2023; 13:20125. [PMID: 37978271 PMCID: PMC10656496 DOI: 10.1038/s41598-023-47412-1] [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: 08/10/2023] [Accepted: 11/10/2023] [Indexed: 11/19/2023] Open
Abstract
Osteosarcoma is the most common bone sarcoma in children and young adults. While universally delivered, chemotherapy only benefits roughly half of patients with localized disease. Increasingly, intratumoral heterogeneity is recognized as a source of therapeutic resistance. In this study, we develop and evaluate an in vitro model of osteosarcoma heterogeneity based on phenotype and genotype. Cancer cell populations vary in their environment-specific growth rates and in their sensitivity to chemotherapy. We present the genotypic and phenotypic characterization of an osteosarcoma cell line panel with a focus on co-cultures of the most phenotypically divergent cell lines, 143B and SAOS2. Modest environmental (pH, glutamine) or chemical perturbations dramatically shift the success and composition of cell lines. We demonstrate that in nutrient rich culture conditions 143B outcompetes SAOS2. But, under nutrient deprivation or conventional chemotherapy, SAOS2 growth can be favored in spheroids. Importantly, when the simplest heterogeneity state is evaluated, a two-cell line coculture, perturbations that affect the faster growing cell line have only a modest effect on final spheroid size. Thus the only evaluated therapies to eliminate the spheroids were by switching therapies from a first strike to a second strike. This extensively characterized, widely available system, can be modeled and scaled to allow for improved strategies to anticipate resistance in osteosarcoma due to heterogeneity.
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Affiliation(s)
- Darcy L Welch
- Adolescent and Young Adult Program, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
- Department of Individualized Cancer Management, H. Lee Moffitt Cancer Center and Research Institute, 12902 Magnolia Drive, Tampa, FL, 33612, USA
| | - Brooke L Fridley
- Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Ling Cen
- Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Jamie K Teer
- Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Sean J Yoder
- Molecular Genomics Core Facility, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Fredrik Pettersson
- Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Liping Xu
- Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Chia-Ho Cheng
- Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Yonghong Zhang
- Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Mark G Alexandrow
- Molecular Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Shengyan Xiang
- Molecular Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Mark Robertson-Tessi
- Integrative Mathematical Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
- Cancer Biology and Evolution, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Joel S Brown
- Integrative Mathematical Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
- Cancer Biology and Evolution, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Jonathan Metts
- Sarcoma Department, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Andrew S Brohl
- Sarcoma Department, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
- Molecular Medicine Program, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Damon R Reed
- Adolescent and Young Adult Program, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA.
- Department of Individualized Cancer Management, H. Lee Moffitt Cancer Center and Research Institute, 12902 Magnolia Drive, Tampa, FL, 33612, USA.
- Integrative Mathematical Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA.
- Cancer Biology and Evolution, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA.
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12
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Ploenzke M, Irizarry R. Reassessing pharmacogenomic cell sensitivity with multilevel statistical models. Biostatistics 2023; 24:901-921. [PMID: 35277956 PMCID: PMC10583722 DOI: 10.1093/biostatistics/kxac010] [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: 08/15/2021] [Revised: 02/04/2022] [Accepted: 02/14/2022] [Indexed: 10/19/2023] Open
Abstract
Pharmacogenomic experiments allow for the systematic testing of drugs, at varying dosage concentrations, to study how genomic markers correlate with cell sensitivity to treatment. The first step in the analysis is to quantify the response of cell lines to variable dosage concentrations of the drugs being tested. The signal to noise in these measurements can be low due to biological and experimental variability. However, the increasing availability of pharmacogenomic studies provides replicated data sets that can be leveraged to gain power. To do this, we formulate a hierarchical mixture model to estimate the drug-specific mixture distributions for estimating cell sensitivity and for assessing drug effect type as either broad or targeted effect. We use this formulation to propose a unified approach that can yield posterior probability of a cell being susceptible to a drug conditional on being a targeted effect or relative effect sizes conditioned on the cell being broad. We demonstrate the usefulness of our approach via case studies. First, we assess pairwise agreements for cell lines/drugs within the intersection of two data sets and confirm the moderate pairwise agreement between many publicly available pharmacogenomic data sets. We then present an analysis that identifies sensitivity to the drug crizotinib for cells harboring EML4-ALK or NPM1-ALK gene fusions, as well as significantly down-regulated cell-matrix pathways associated with crizotinib sensitivity.
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Affiliation(s)
- Matt Ploenzke
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, 655 Huntington Ave, Building 2, 4th Floor, Boston, MA 02115
| | - Rafael Irizarry
- Department of Data Science, Dana Farber Cancer Institute, 450 Brookline Ave, CLSB 11007, Boston, MA 02215
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13
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Krill-Burger JM, Dempster JM, Borah AA, Paolella BR, Root DE, Golub TR, Boehm JS, Hahn WC, McFarland JM, Vazquez F, Tsherniak A. Partial gene suppression improves identification of cancer vulnerabilities when CRISPR-Cas9 knockout is pan-lethal. Genome Biol 2023; 24:192. [PMID: 37612728 PMCID: PMC10464129 DOI: 10.1186/s13059-023-03020-w] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Accepted: 07/21/2023] [Indexed: 08/25/2023] Open
Abstract
BACKGROUND Hundreds of functional genomic screens have been performed across a diverse set of cancer contexts, as part of efforts such as the Cancer Dependency Map, to identify gene dependencies-genes whose loss of function reduces cell viability or fitness. Recently, large-scale screening efforts have shifted from RNAi to CRISPR-Cas9, due to superior efficacy and specificity. However, many effective oncology drugs only partially inhibit their protein targets, leading us to question whether partial suppression of genes using RNAi could reveal cancer vulnerabilities that are missed by complete knockout using CRISPR-Cas9. Here, we compare CRISPR-Cas9 and RNAi dependency profiles of genes across approximately 400 matched cancer cell lines. RESULTS We find that CRISPR screens accurately identify more gene dependencies per cell line, but the majority of each cell line's dependencies are part of a set of 1867 genes that are shared dependencies across the entire collection (pan-lethals). While RNAi knockdown of about 30% of these genes is also pan-lethal, approximately 50% have selective dependency patterns across cell lines, suggesting they could still be cancer vulnerabilities. The accuracy of the unique RNAi selectivity is supported by associations to multi-omics profiles, drug sensitivity, and other expected co-dependencies. CONCLUSIONS Incorporating RNAi data for genes that are pan-lethal knockouts facilitates the discovery of a wider range of gene targets than could be detected using the CRISPR dataset alone. This can aid in the interpretation of contrasting results obtained from CRISPR and RNAi screens and reinforce the importance of partial gene suppression methods in building a cancer dependency map.
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Affiliation(s)
| | | | - Ashir A Borah
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | | | - David E Root
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Todd R Golub
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Dana-Farber Cancer Institute, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Jesse S Boehm
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - William C Hahn
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Dana-Farber Cancer Institute, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | | | - Francisca Vazquez
- Broad Institute of Harvard and MIT, Cambridge, MA, USA.
- Dana-Farber Cancer Institute, Boston, MA, USA.
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14
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Mayoh C, Mao J, Xie J, Tax G, Chow SO, Cadiz R, Pazaky K, Barahona P, Ajuyah P, Trebilcock P, Malquori A, Gunther K, Avila A, Yun DY, Alfred S, Gopalakrishnan A, Kamili A, Wong M, Cowley MJ, Jessop S, Lau LM, Trahair TN, Ziegler DS, Fletcher JI, Gifford AJ, Tsoli M, Marshall GM, Haber M, Tyrrell V, Failes TW, Arndt GM, Lock RB, Ekert PG, Dolman MEM. High-Throughput Drug Screening of Primary Tumor Cells Identifies Therapeutic Strategies for Treating Children with High-Risk Cancer. Cancer Res 2023; 83:2716-2732. [PMID: 37523146 PMCID: PMC10425737 DOI: 10.1158/0008-5472.can-22-3702] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Revised: 04/10/2023] [Accepted: 06/02/2023] [Indexed: 08/01/2023]
Abstract
For one-third of patients with pediatric cancer enrolled in precision medicine programs, molecular profiling does not result in a therapeutic recommendation. To identify potential strategies for treating these high-risk pediatric patients, we performed in vitro screening of 125 patient-derived samples against a library of 126 anticancer drugs. Tumor cell expansion did not influence drug responses, and 82% of the screens on expanded tumor cells were completed while the patients were still under clinical care. High-throughput drug screening (HTS) confirmed known associations between activating genomic alterations in NTRK, BRAF, and ALK and responses to matching targeted drugs. The in vitro results were further validated in patient-derived xenograft models in vivo and were consistent with clinical responses in treated patients. In addition, effective combinations could be predicted by correlating sensitivity profiles between drugs. Furthermore, molecular integration with HTS identified biomarkers of sensitivity to WEE1 and MEK inhibition. Incorporating HTS into precision medicine programs is a powerful tool to accelerate the improved identification of effective biomarker-driven therapeutic strategies for treating high-risk pediatric cancers. SIGNIFICANCE Integrating HTS with molecular profiling is a powerful tool for expanding precision medicine to support drug treatment recommendations and broaden the therapeutic options available to high-risk pediatric cancers.
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Affiliation(s)
- Chelsea Mayoh
- Children's Cancer Institute, Lowy Cancer Research Centre, UNSW Sydney, Kensington, New South Wales, Australia
- School of Clinical Medicine, UNSW Medicine & Health, UNSW Sydney, Kensington, New South Wales, Australia
| | - Jie Mao
- Children's Cancer Institute, Lowy Cancer Research Centre, UNSW Sydney, Kensington, New South Wales, Australia
| | - Jinhan Xie
- Children's Cancer Institute, Lowy Cancer Research Centre, UNSW Sydney, Kensington, New South Wales, Australia
- School of Clinical Medicine, UNSW Medicine & Health, UNSW Sydney, Kensington, New South Wales, Australia
| | - Gabor Tax
- Children's Cancer Institute, Lowy Cancer Research Centre, UNSW Sydney, Kensington, New South Wales, Australia
- School of Clinical Medicine, UNSW Medicine & Health, UNSW Sydney, Kensington, New South Wales, Australia
| | - Shu-Oi Chow
- Children's Cancer Institute, Lowy Cancer Research Centre, UNSW Sydney, Kensington, New South Wales, Australia
- ACRF Drug Discovery Centre for Childhood Cancer, Children's Cancer Institute, Lowy Cancer Research Centre, UNSW Sydney, Sydney, New South Wales, Australia
| | - Roxanne Cadiz
- Children's Cancer Institute, Lowy Cancer Research Centre, UNSW Sydney, Kensington, New South Wales, Australia
| | - Karina Pazaky
- Children's Cancer Institute, Lowy Cancer Research Centre, UNSW Sydney, Kensington, New South Wales, Australia
| | - Paulette Barahona
- Children's Cancer Institute, Lowy Cancer Research Centre, UNSW Sydney, Kensington, New South Wales, Australia
| | - Pamela Ajuyah
- Children's Cancer Institute, Lowy Cancer Research Centre, UNSW Sydney, Kensington, New South Wales, Australia
| | - Peter Trebilcock
- Children's Cancer Institute, Lowy Cancer Research Centre, UNSW Sydney, Kensington, New South Wales, Australia
| | - Angela Malquori
- Children's Cancer Institute, Lowy Cancer Research Centre, UNSW Sydney, Kensington, New South Wales, Australia
| | - Kate Gunther
- Children's Cancer Institute, Lowy Cancer Research Centre, UNSW Sydney, Kensington, New South Wales, Australia
| | - Anica Avila
- Children's Cancer Institute, Lowy Cancer Research Centre, UNSW Sydney, Kensington, New South Wales, Australia
| | - Doo Young Yun
- Children's Cancer Institute, Lowy Cancer Research Centre, UNSW Sydney, Kensington, New South Wales, Australia
| | - Stephanie Alfred
- Children's Cancer Institute, Lowy Cancer Research Centre, UNSW Sydney, Kensington, New South Wales, Australia
| | - Anjana Gopalakrishnan
- Children's Cancer Institute, Lowy Cancer Research Centre, UNSW Sydney, Kensington, New South Wales, Australia
| | - Alvin Kamili
- Children's Cancer Institute, Lowy Cancer Research Centre, UNSW Sydney, Kensington, New South Wales, Australia
- School of Clinical Medicine, UNSW Medicine & Health, UNSW Sydney, Kensington, New South Wales, Australia
| | - Marie Wong
- Children's Cancer Institute, Lowy Cancer Research Centre, UNSW Sydney, Kensington, New South Wales, Australia
| | - Mark J. Cowley
- Children's Cancer Institute, Lowy Cancer Research Centre, UNSW Sydney, Kensington, New South Wales, Australia
- School of Clinical Medicine, UNSW Medicine & Health, UNSW Sydney, Kensington, New South Wales, Australia
| | - Sophie Jessop
- Children's Cancer Institute, Lowy Cancer Research Centre, UNSW Sydney, Kensington, New South Wales, Australia
- Kids Cancer Centre, Sydney Children's Hospital, Randwick, New South Wales, Australia
| | - Loretta M.S. Lau
- Children's Cancer Institute, Lowy Cancer Research Centre, UNSW Sydney, Kensington, New South Wales, Australia
- School of Clinical Medicine, UNSW Medicine & Health, UNSW Sydney, Kensington, New South Wales, Australia
- Kids Cancer Centre, Sydney Children's Hospital, Randwick, New South Wales, Australia
| | - Toby N. Trahair
- Children's Cancer Institute, Lowy Cancer Research Centre, UNSW Sydney, Kensington, New South Wales, Australia
- School of Clinical Medicine, UNSW Medicine & Health, UNSW Sydney, Kensington, New South Wales, Australia
- Kids Cancer Centre, Sydney Children's Hospital, Randwick, New South Wales, Australia
| | - David S. Ziegler
- Children's Cancer Institute, Lowy Cancer Research Centre, UNSW Sydney, Kensington, New South Wales, Australia
- School of Clinical Medicine, UNSW Medicine & Health, UNSW Sydney, Kensington, New South Wales, Australia
- Kids Cancer Centre, Sydney Children's Hospital, Randwick, New South Wales, Australia
| | - Jamie I. Fletcher
- Children's Cancer Institute, Lowy Cancer Research Centre, UNSW Sydney, Kensington, New South Wales, Australia
- School of Clinical Medicine, UNSW Medicine & Health, UNSW Sydney, Kensington, New South Wales, Australia
| | - Andrew J. Gifford
- Children's Cancer Institute, Lowy Cancer Research Centre, UNSW Sydney, Kensington, New South Wales, Australia
- School of Clinical Medicine, UNSW Medicine & Health, UNSW Sydney, Kensington, New South Wales, Australia
- Anatomical Pathology, NSW Health Pathology, Prince of Wales Hospital, Randwick, New South Wales, Australia
| | - Maria Tsoli
- Children's Cancer Institute, Lowy Cancer Research Centre, UNSW Sydney, Kensington, New South Wales, Australia
- School of Clinical Medicine, UNSW Medicine & Health, UNSW Sydney, Kensington, New South Wales, Australia
| | - Glenn M. Marshall
- Children's Cancer Institute, Lowy Cancer Research Centre, UNSW Sydney, Kensington, New South Wales, Australia
- School of Clinical Medicine, UNSW Medicine & Health, UNSW Sydney, Kensington, New South Wales, Australia
- Kids Cancer Centre, Sydney Children's Hospital, Randwick, New South Wales, Australia
| | - Michelle Haber
- Children's Cancer Institute, Lowy Cancer Research Centre, UNSW Sydney, Kensington, New South Wales, Australia
- School of Clinical Medicine, UNSW Medicine & Health, UNSW Sydney, Kensington, New South Wales, Australia
| | - Vanessa Tyrrell
- Children's Cancer Institute, Lowy Cancer Research Centre, UNSW Sydney, Kensington, New South Wales, Australia
- School of Clinical Medicine, UNSW Medicine & Health, UNSW Sydney, Kensington, New South Wales, Australia
| | - Timothy W. Failes
- Children's Cancer Institute, Lowy Cancer Research Centre, UNSW Sydney, Kensington, New South Wales, Australia
- ACRF Drug Discovery Centre for Childhood Cancer, Children's Cancer Institute, Lowy Cancer Research Centre, UNSW Sydney, Sydney, New South Wales, Australia
| | - Greg M. Arndt
- Children's Cancer Institute, Lowy Cancer Research Centre, UNSW Sydney, Kensington, New South Wales, Australia
- School of Clinical Medicine, UNSW Medicine & Health, UNSW Sydney, Kensington, New South Wales, Australia
- ACRF Drug Discovery Centre for Childhood Cancer, Children's Cancer Institute, Lowy Cancer Research Centre, UNSW Sydney, Sydney, New South Wales, Australia
| | - Richard B. Lock
- Children's Cancer Institute, Lowy Cancer Research Centre, UNSW Sydney, Kensington, New South Wales, Australia
- School of Clinical Medicine, UNSW Medicine & Health, UNSW Sydney, Kensington, New South Wales, Australia
| | - Paul G. Ekert
- Children's Cancer Institute, Lowy Cancer Research Centre, UNSW Sydney, Kensington, New South Wales, Australia
- School of Clinical Medicine, UNSW Medicine & Health, UNSW Sydney, Kensington, New South Wales, Australia
- Murdoch Children's Research Institute, Royal Children's Hospital, Parkville, Victoria, Australia
- Cancer Immunology Program, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
- The Sir Peter MacCallum Department of Oncology, The University of Melbourne, Victoria, Australia
| | - M. Emmy M. Dolman
- Children's Cancer Institute, Lowy Cancer Research Centre, UNSW Sydney, Kensington, New South Wales, Australia
- School of Clinical Medicine, UNSW Medicine & Health, UNSW Sydney, Kensington, New South Wales, Australia
- Princess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands
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15
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Ohnmacht AJ, Rajamani A, Avar G, Kutkaite G, Gonçalves E, Saur D, Menden MP. The pharmacoepigenomic landscape of cancer cell lines reveals the epigenetic component of drug sensitivity. Commun Biol 2023; 6:825. [PMID: 37558831 PMCID: PMC10412573 DOI: 10.1038/s42003-023-05198-y] [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: 01/14/2023] [Accepted: 08/01/2023] [Indexed: 08/11/2023] Open
Abstract
Aberrant DNA methylation accompanies genetic alterations during oncogenesis and tumour homeostasis and contributes to the transcriptional deregulation of key signalling pathways in cancer. Despite increasing efforts in DNA methylation profiling of cancer patients, there is still a lack of epigenetic biomarkers to predict treatment efficacy. To address this, we analyse 721 cancer cell lines across 22 cancer types treated with 453 anti-cancer compounds. We systematically detect the predictive component of DNA methylation in the context of transcriptional and mutational patterns, i.e., in total 19 DNA methylation biomarkers across 17 drugs and five cancer types. DNA methylation constitutes drug sensitivity biomarkers by mediating the expression of proximal genes, thereby enhancing biological signals across multi-omics data modalities. Our method reproduces anticipated associations, and in addition, we find that the NEK9 promoter hypermethylation may confer sensitivity to the NEDD8-activating enzyme (NAE) inhibitor pevonedistat in melanoma through downregulation of NEK9. In summary, we envision that epigenomics will refine existing patient stratification, thus empowering the next generation of precision oncology.
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Affiliation(s)
- Alexander Joschua Ohnmacht
- Computational Health Center, Helmholtz Munich, 85764, Neuherberg, Germany
- Department of Biology, Ludwig-Maximilians University Munich, 82152, Martinsried, Germany
| | - Anantharamanan Rajamani
- Division of Translational Cancer Research, German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK), Im Neuenheimer Feld 280, 69120, Heidelberg, Germany
- Chair of Translational Cancer Research and Institute of Experimental Cancer Therapy, Klinikum rechts der Isar, School of Medicine, Technische Universität München, Ismaninger Str. 22, 81675, Munich, Germany
- Center for Translational Cancer Research (TranslaTUM), School of Medicine, Technical University of Munich, Ismaninger Str. 22, 81675, Munich, Germany
| | - Göksu Avar
- Computational Health Center, Helmholtz Munich, 85764, Neuherberg, Germany
- Department of Biology, Ludwig-Maximilians University Munich, 82152, Martinsried, Germany
| | - Ginte Kutkaite
- Computational Health Center, Helmholtz Munich, 85764, Neuherberg, Germany
- Department of Biology, Ludwig-Maximilians University Munich, 82152, Martinsried, Germany
| | - Emanuel Gonçalves
- Instituto Superior Técnico (IST), Universidade de Lisboa, 1049-001, Lisbon, Portugal
- INESC-ID, 1000-029, Lisbon, Portugal
| | - Dieter Saur
- Division of Translational Cancer Research, German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK), Im Neuenheimer Feld 280, 69120, Heidelberg, Germany
- Chair of Translational Cancer Research and Institute of Experimental Cancer Therapy, Klinikum rechts der Isar, School of Medicine, Technische Universität München, Ismaninger Str. 22, 81675, Munich, Germany
- Center for Translational Cancer Research (TranslaTUM), School of Medicine, Technical University of Munich, Ismaninger Str. 22, 81675, Munich, Germany
| | - Michael Patrick Menden
- Computational Health Center, Helmholtz Munich, 85764, Neuherberg, Germany.
- Department of Biology, Ludwig-Maximilians University Munich, 82152, Martinsried, Germany.
- Department of Biochemistry and Pharmacology, University of Melbourne, Victoria, VIC, 3010, Australia.
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16
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Trastulla L, Savino A, Beltrao P, Ciriano IC, Fenici P, Garnett MJ, Guerini I, Bigas NL, Mattaj I, Petsalaki E, Riva L, Tape CJ, Leeuwen JV, Sharma S, Vazquez F, Iorio F. Highlights from the 1st European cancer dependency map symposium and workshop. FEBS Lett 2023; 597:1921-1927. [PMID: 37487655 DOI: 10.1002/1873-3468.14699] [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: 07/06/2023] [Revised: 07/10/2023] [Accepted: 07/13/2023] [Indexed: 07/26/2023]
Abstract
The systematic identification of tumour vulnerabilities through perturbational experiments on cancer models, including genome editing and drug screens, is playing a crucial role in combating cancer. This collective effort is known as the Cancer Dependency Map (DepMap). The 1st European Cancer Dependency Map Symposium (EuroDepMap), held in Milan last May, featured talks, a roundtable discussion, and a poster session, showcasing the latest discoveries and future challenges related to the DepMap. The symposium aimed to facilitate interactions among participants across Europe, encourage idea exchange with leading experts, and present their work and future projects. Importantly, it sparked discussions on future endeavours, such as screening more complex cancer models and accounting for tumour evolution.
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Affiliation(s)
| | | | - Pedro Beltrao
- Institute of Molecular Systems Biology, ETH Zürich, Zurich, Switzerland
| | | | | | | | | | | | | | | | | | | | | | | | - Francisca Vazquez
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA
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17
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Kumar-Sinha C, Vats P, Tran N, Robinson DR, Gunchick V, Wu YM, Cao X, Ning Y, Wang R, Rabban E, Bell J, Shankar S, Mannan R, Zhang Y, Zalupski MM, Chinnaiyan AM, Sahai V. Genomics driven precision oncology in advanced biliary tract cancer improves survival. Neoplasia 2023; 42:100910. [PMID: 37267699 PMCID: PMC10245336 DOI: 10.1016/j.neo.2023.100910] [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: 05/11/2023] [Accepted: 05/12/2023] [Indexed: 06/04/2023]
Abstract
BACKGROUND Biliary tract cancers (BTCs) including intrahepatic, perihilar, and distal cholangiocarcinoma as well as gallbladder cancer, are rare but aggressive malignancies with few effective standard of care therapies. METHODS We implemented integrative clinical sequencing of advanced BTC tumors from 124 consecutive patients who progressed on standard therapies (N=92 with MI-ONCOSEQ and N=32 with commercial gene panels) enrolled between 2011-2020. RESULTS Genomic profiling of paired tumor and normal DNA and tumor transcriptome (RNA) sequencing identified actionable somatic and germline genomic alterations in 54 patients (43.5%), and potentially actionable alterations in 79 (63.7%) of the cohort. Of these, patients who received matched targeted therapy (22; 40.7%) had a median overall survival of 28.1 months compared to 13.3 months in those who did not receive matched targeted therapy (32; P < 0.01), or 13.9 months in those without actionable mutations (70; P < 0.01). Additionally, we discovered recurrent activating mutations in FGFR2, and a novel association between KRAS and BRAF mutant tumors with high expression of immune modulatory protein NT5E (CD73) that may represent novel therapeutic avenues. CONCLUSIONS Overall, the identification of actionable/ potentially actionable aberrations in a large proportion of cases, and improvement in survival with precision oncology supports molecular analysis and clinical sequencing for all patients with advanced BTC.
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Affiliation(s)
- Chandan Kumar-Sinha
- Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI 48109, USA; Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Pankaj Vats
- Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI 48109, USA; Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Nguyen Tran
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI 48109, USA
| | - Dan R Robinson
- Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI 48109, USA; Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Valerie Gunchick
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI 48109, USA
| | - Yi-Mi Wu
- Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI 48109, USA; Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Xuhong Cao
- Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI 48109, USA; Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Yu Ning
- Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Rui Wang
- Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Erica Rabban
- Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Janice Bell
- Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Sunita Shankar
- Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Rahul Mannan
- Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Yuping Zhang
- Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Mark M Zalupski
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI 48109, USA; Rogel Cancer Center, University of Michigan, Ann Arbor, MI 48109, USA
| | - Arul M Chinnaiyan
- Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI 48109, USA; Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA; Rogel Cancer Center, University of Michigan, Ann Arbor, MI 48109, USA; Howard Hughes Medical Institute, Chevy Chase, MD 20815, USA.
| | - Vaibhav Sahai
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI 48109, USA; Rogel Cancer Center, University of Michigan, Ann Arbor, MI 48109, USA.
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18
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van Belzen IAEM, Cai C, van Tuil M, Badloe S, Strengman E, Janse A, Verwiel ETP, van der Leest DFM, Kester L, Molenaar JJ, Meijerink J, Drost J, Peng WC, Kerstens HHD, Tops BBJ, Holstege FCP, Kemmeren P, Hehir-Kwa JY. Systematic discovery of gene fusions in pediatric cancer by integrating RNA-seq and WGS. BMC Cancer 2023; 23:618. [PMID: 37400763 DOI: 10.1186/s12885-023-11054-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Accepted: 03/08/2023] [Indexed: 07/05/2023] Open
Abstract
BACKGROUND Gene fusions are important cancer drivers in pediatric cancer and their accurate detection is essential for diagnosis and treatment. Clinical decision-making requires high confidence and precision of detection. Recent developments show RNA sequencing (RNA-seq) is promising for genome-wide detection of fusion products but hindered by many false positives that require extensive manual curation and impede discovery of pathogenic fusions. METHODS We developed Fusion-sq to overcome existing disadvantages of detecting gene fusions. Fusion-sq integrates and "fuses" evidence from RNA-seq and whole genome sequencing (WGS) using intron-exon gene structure to identify tumor-specific protein coding gene fusions. Fusion-sq was then applied to the data generated from a pediatric pan-cancer cohort of 128 patients by WGS and RNA sequencing. RESULTS In a pediatric pan-cancer cohort of 128 patients, we identified 155 high confidence tumor-specific gene fusions and their underlying structural variants (SVs). This includes all clinically relevant fusions known to be present in this cohort (30 patients). Fusion-sq distinguishes healthy-occurring from tumor-specific fusions and resolves fusions in amplified regions and copy number unstable genomes. A high gene fusion burden is associated with copy number instability. We identified 27 potentially pathogenic fusions involving oncogenes or tumor-suppressor genes characterized by underlying SVs, in some cases leading to expression changes indicative of activating or disruptive effects. CONCLUSIONS Our results indicate how clinically relevant and potentially pathogenic gene fusions can be identified and their functional effects investigated by combining WGS and RNA-seq. Integrating RNA fusion predictions with underlying SVs advances fusion detection beyond extensive manual filtering. Taken together, we developed a method for identifying candidate gene fusions that is suitable for precision oncology applications. Our method provides multi-omics evidence for assessing the pathogenicity of tumor-specific gene fusions for future clinical decision making.
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Affiliation(s)
| | - Casey Cai
- Princess Máxima Center for Pediatric Oncology, Utrecht, The Netherlands
| | - Marc van Tuil
- Princess Máxima Center for Pediatric Oncology, Utrecht, The Netherlands
| | - Shashi Badloe
- Princess Máxima Center for Pediatric Oncology, Utrecht, The Netherlands
| | - Eric Strengman
- Princess Máxima Center for Pediatric Oncology, Utrecht, The Netherlands
| | - Alex Janse
- Princess Máxima Center for Pediatric Oncology, Utrecht, The Netherlands
| | | | | | - Lennart Kester
- Princess Máxima Center for Pediatric Oncology, Utrecht, The Netherlands
| | - Jan J Molenaar
- Princess Máxima Center for Pediatric Oncology, Utrecht, The Netherlands
- Department of Pharmaceutical Sciences, Utrecht University, Utrecht, The Netherlands
| | - Jules Meijerink
- Princess Máxima Center for Pediatric Oncology, Utrecht, The Netherlands
| | - Jarno Drost
- Princess Máxima Center for Pediatric Oncology, Utrecht, The Netherlands
- Oncode Institute, Utrecht, The Netherlands
| | - Weng Chuan Peng
- Princess Máxima Center for Pediatric Oncology, Utrecht, The Netherlands
| | | | - Bastiaan B J Tops
- Princess Máxima Center for Pediatric Oncology, Utrecht, The Netherlands
| | | | - Patrick Kemmeren
- Princess Máxima Center for Pediatric Oncology, Utrecht, The Netherlands.
- Center for Molecular Medicine, UMC Utrecht and Utrecht University, Utrecht, The Netherlands.
| | - Jayne Y Hehir-Kwa
- Princess Máxima Center for Pediatric Oncology, Utrecht, The Netherlands.
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19
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Nair NU, Greninger P, Zhang X, Friedman AA, Amzallag A, Cortez E, Sahu AD, Lee JS, Dastur A, Egan RK, Murchie E, Ceribelli M, Crowther GS, Beck E, McClanaghan J, Klump-Thomas C, Boisvert JL, Damon LJ, Wilson KM, Ho J, Tam A, McKnight C, Michael S, Itkin Z, Garnett MJ, Engelman JA, Haber DA, Thomas CJ, Ruppin E, Benes CH. A landscape of response to drug combinations in non-small cell lung cancer. Nat Commun 2023; 14:3830. [PMID: 37380628 PMCID: PMC10307832 DOI: 10.1038/s41467-023-39528-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Accepted: 06/14/2023] [Indexed: 06/30/2023] Open
Abstract
Combination of anti-cancer drugs is broadly seen as way to overcome the often-limited efficacy of single agents. The design and testing of combinations are however very challenging. Here we present a uniquely large dataset screening over 5000 targeted agent combinations across 81 non-small cell lung cancer cell lines. Our analysis reveals a profound heterogeneity of response across the tumor models. Notably, combinations very rarely result in a strong gain in efficacy over the range of response observable with single agents. Importantly, gain of activity over single agents is more often seen when co-targeting functionally proximal genes, offering a strategy for designing more efficient combinations. Because combinatorial effect is strongly context specific, tumor specificity should be achievable. The resource provided, together with an additional validation screen sheds light on major challenges and opportunities in building efficacious combinations against cancer and provides an opportunity for training computational models for synergy prediction.
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Affiliation(s)
- Nishanth Ulhas Nair
- Cancer Data Science Laboratory, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | | | - Xiaohu Zhang
- Howard Hughes Medical Institute, Bethesda, MD, USA
| | - Adam A Friedman
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Arnaud Amzallag
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Eliane Cortez
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Avinash Das Sahu
- University of New Mexico, Comprehensive Cancer Center, Albuquerque, NM, USA
| | - Joo Sang Lee
- Samsung Medical Center, Sungkyunkwan University School of Medicine, Suwon, 16419, Republic of Korea
| | - Anahita Dastur
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Regina K Egan
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Ellen Murchie
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | | | | | - Erin Beck
- Howard Hughes Medical Institute, Bethesda, MD, USA
| | | | | | | | - Leah J Damon
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | | | - Jeffrey Ho
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Angela Tam
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | | | - Sam Michael
- Howard Hughes Medical Institute, Bethesda, MD, USA
| | - Zina Itkin
- Howard Hughes Medical Institute, Bethesda, MD, USA
| | - Mathew J Garnett
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Cambridge, CB10 1SA, UK
| | | | - Daniel A Haber
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Howard Hughes Medical Institute, Bethesda, MD, USA
| | - Craig J Thomas
- Division of Preclinical Innovation, National Center for Advancing Translational Sciences, National Institute of Health, Rockville, MD, 20850, USA
- Lymphoid Malignancies Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Eytan Ruppin
- Cancer Data Science Laboratory, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
| | - Cyril H Benes
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
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20
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Zheng C, Zhang B, Li Y, Liu K, Wei W, Liang S, Guo H, Ma K, Liu Y, Wang J, Liu L. Donafenib and GSK-J4 Synergistically Induce Ferroptosis in Liver Cancer by Upregulating HMOX1 Expression. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2023:e2206798. [PMID: 37330650 PMCID: PMC10401117 DOI: 10.1002/advs.202206798] [Citation(s) in RCA: 17] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/19/2022] [Revised: 04/06/2023] [Indexed: 06/19/2023]
Abstract
Hepatocellular carcinoma (HCC) is one of the most lethal cancers worldwide. Donafenib is a multi-receptor tyrosine kinase inhibitor approved for the treatment of patients with advanced HCC, but its clinical effect is very limited. Here, through integrated screening of a small-molecule inhibitor library and a druggable CRISPR library, that GSK-J4 is synthetically lethal with donafenib in liver cancer is shown. This synergistic lethality is validated in multiple HCC models, including xenograft, orthotopically induced HCC, patient-derived xenograft, and organoid models. Furthermore, co-treatment with donafenib and GSK-J4 resulted in cell death mainly via ferroptosis. Mechanistically, through integrated RNA sequencing (RNA-seq) and assay for transposase-accessible chromatin with high throughput sequencing (ATAC-seq) analyses, that donafenib and GSK-J4 synergistically promoted the expression of HMOX1 and increased the intracellular Fe2+ level is found, eventually leading to ferroptosis. Additionally, through cleavage under targets & tagmentation followed by sequencing (CUT&Tag-seq), it is found that the enhancer regions upstream of HMOX1 promoter significantly increased under donafenib and GSK-J4 co-treatment. A chromosome conformation capture assay confirmed that the increased expression of HMOX1 is caused by the significantly enhanced interaction between the promoter and upstream enhancer under dual-drug combination. Taken together, this study elucidates a new synergistic lethal interaction in liver cancer.
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Affiliation(s)
- Chenyang Zheng
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, 230001, China
- Anhui Province Key Laboratory of Hepatopancreatobiliary Surgery, Hefei, Anhui, 230001, China
- Anhui Provincial Clinical Research Center for Hepatobiliary Diseases, Hefei, Anhui, 230001, China
| | - Bo Zhang
- Anhui Province Key Laboratory of Hepatopancreatobiliary Surgery, Hefei, Anhui, 230001, China
- Anhui Provincial Clinical Research Center for Hepatobiliary Diseases, Hefei, Anhui, 230001, China
- Department of Gastrointestinal Surgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, 230001, China
| | - Yunyun Li
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, 230001, China
- Anhui Province Key Laboratory of Hepatopancreatobiliary Surgery, Hefei, Anhui, 230001, China
- Anhui Provincial Clinical Research Center for Hepatobiliary Diseases, Hefei, Anhui, 230001, China
| | - Kejia Liu
- Hefei National Laboratory for Physical Sciences at the Microscale, Division of Life Sciences and Medicine, CAS Centre for Excellence in Molecular Cell Science, University of Science and Technology of China, Hefei, Anhui, 230001, China
| | - Wei Wei
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, 230001, China
- Anhui Province Key Laboratory of Hepatopancreatobiliary Surgery, Hefei, Anhui, 230001, China
- Anhui Provincial Clinical Research Center for Hepatobiliary Diseases, Hefei, Anhui, 230001, China
| | - Shuhang Liang
- Anhui Province Key Laboratory of Hepatopancreatobiliary Surgery, Hefei, Anhui, 230001, China
- Anhui Provincial Clinical Research Center for Hepatobiliary Diseases, Hefei, Anhui, 230001, China
- Department of Gastrointestinal Surgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, 230001, China
| | - Hongrui Guo
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, 230001, China
- Anhui Province Key Laboratory of Hepatopancreatobiliary Surgery, Hefei, Anhui, 230001, China
- Anhui Provincial Clinical Research Center for Hepatobiliary Diseases, Hefei, Anhui, 230001, China
| | - Kun Ma
- Department of Hepatic Surgery, Key Laboratory of Hepatosplenic Surgery, Ministry of Education, The First Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, 150007, China
| | - Yao Liu
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, 230001, China
- Anhui Province Key Laboratory of Hepatopancreatobiliary Surgery, Hefei, Anhui, 230001, China
- Anhui Provincial Clinical Research Center for Hepatobiliary Diseases, Hefei, Anhui, 230001, China
| | - Jiabei Wang
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, 230001, China
- Anhui Province Key Laboratory of Hepatopancreatobiliary Surgery, Hefei, Anhui, 230001, China
- Anhui Provincial Clinical Research Center for Hepatobiliary Diseases, Hefei, Anhui, 230001, China
| | - Lianxin Liu
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, 230001, China
- Anhui Province Key Laboratory of Hepatopancreatobiliary Surgery, Hefei, Anhui, 230001, China
- Anhui Provincial Clinical Research Center for Hepatobiliary Diseases, Hefei, Anhui, 230001, China
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21
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Franklin JM, Wu Z, Guan KL. Insights into recent findings and clinical application of YAP and TAZ in cancer. Nat Rev Cancer 2023:10.1038/s41568-023-00579-1. [PMID: 37308716 DOI: 10.1038/s41568-023-00579-1] [Citation(s) in RCA: 40] [Impact Index Per Article: 40.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 04/19/2023] [Indexed: 06/14/2023]
Abstract
Decades of research have mapped out the basic mechanics of the Hippo pathway. The paralogues Yes-associated protein (YAP) and transcriptional co-activator with PDZ-binding motif (TAZ), as the central transcription control module of the Hippo pathway, have long been implicated in the progression of various human cancers. The current literature regarding oncogenic YAP and TAZ activities consists mostly of context-specific mechanisms and treatments of human cancers. Furthermore, a growing number of studies demonstrate tumour-suppressor functions of YAP and TAZ. In this Review we aim to synthesize an integrated perspective of the many disparate findings regarding YAP and TAZ in cancer. We then conclude with the various strategies for targeting and treating YAP- and TAZ-dependent cancers.
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Affiliation(s)
- J Matthew Franklin
- Department of Pharmacology and Moores Cancer Center, University of California San Diego, La Jolla, CA, USA
| | - Zhengming Wu
- Department of Pharmacology and Moores Cancer Center, University of California San Diego, La Jolla, CA, USA
| | - Kun-Liang Guan
- Department of Pharmacology and Moores Cancer Center, University of California San Diego, La Jolla, CA, USA.
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22
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Cheng X, Song H, Ren D, Gao M, Xia X, Yu P, Bian X. Rolling circle transcription and CRISPR/Cas12a-assisted versatile bicyclic cascade amplification assay for sensitive uracil-DNA glycosylase detection. Talanta 2023; 262:124684. [PMID: 37220689 DOI: 10.1016/j.talanta.2023.124684] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Revised: 05/14/2023] [Accepted: 05/17/2023] [Indexed: 05/25/2023]
Abstract
Uracil-DNA glycosylase (UDG) is pivotal in maintaining genome integrity and aberrant expressed UDG is highly relevant to numerous diseases. Sensitive and accurate detecting UDG is critically significant for early clinical diagnosis. In this research, we demonstrated a sensitive UDG fluorescent assay based on rolling circle transcription (RCT)/CRISPR/Cas12a-assisted bicyclic cascade amplification strategy. Target UDG catalyzed to remove uracil base of DNA dumbbell-shape substrate probe (SubUDG) to produce an apurinic/apyrimidinic (AP) site, at which SubUDG was cleaved by apurinic/apyrimidinic endonuclease (APE1) subsequently. The exposed 5'-PO4 was ligated with the free 3'-OH terminus to form an enclosed DNA dumbbell-shape substrate probe (E-SubUDG). E-SubUDG functioned as a template can actuate T7 RNA polymerase-mediated RCT signal amplification, generating multitudes of crRNA repeats. The resultant Cas12a/crRNA/activator ternary complex activated the activity of Cas12a, causing a significantly enhanced fluorescence output. In this bicyclic cascade strategy, target UDG was amplified via RCT and CRISPR/Cas12a, and the whole reaction was completed without complex procedures. This method enabled sensitive and specific monitor UDG down to 0.0005 U/mL, screen corresponding inhibitors, and analyze endogenous UDG in A549 cells at single-cell level. Importantly, this assay can be extended to analyze other DNA glycosylase (hAAG and Fpg) by altering the recognition site in DNA substrates probe rationally, thereby offering a potent tool for DNA glycosylase-associated clinical diagnosis and biomedical research.
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Affiliation(s)
- Xia Cheng
- Department of Pharmacy, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Huahua Song
- Experimental Nuclear Medicine Laboratory, Core Facility of Basic Medical Sciences, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Dandan Ren
- School of Pharmacy, Nanjing Medical University, Nanjing, Jiangsu, 211166, PR China
| | - Mingcong Gao
- School of Pharmacy, Nanjing Medical University, Nanjing, Jiangsu, 211166, PR China
| | - Xinyi Xia
- School of Pharmacy, Nanjing Medical University, Nanjing, Jiangsu, 211166, PR China
| | - Ping Yu
- Department of Pharmacy, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Xiaolan Bian
- Department of Pharmacy, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
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23
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Naineni SK, Robert F, Nagar B, Pelletier J. Targeting DEAD-box RNA helicases: The emergence of molecular staples. WILEY INTERDISCIPLINARY REVIEWS. RNA 2023; 14:e1738. [PMID: 35581936 DOI: 10.1002/wrna.1738] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Revised: 04/13/2022] [Accepted: 04/16/2022] [Indexed: 12/29/2022]
Abstract
RNA helicases constitute a large family of proteins that play critical roles in mediating RNA function. They have been implicated in all facets of gene expression pathways involving RNA, from transcription to processing, transport and translation, and storage and decay. There is significant interest in developing small molecule inhibitors to RNA helicases as some family members have been documented to be dysregulated in neurological and neurodevelopment disorders, as well as in cancers. Although different functional properties of RNA helicases offer multiple opportunities for small molecule development, molecular staples have recently come to the forefront. These bifunctional molecules interact with both protein and RNA components to lock them together, thereby imparting novel gain-of-function properties to their targets. This article is categorized under: RNA Interactions with Proteins and Other Molecules > Small Molecule-RNA Interactions RNA Interactions with Proteins and Other Molecules > Protein-RNA Interactions: Functional Implications.
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Affiliation(s)
- Sai Kiran Naineni
- Department of Biochemistry, McGill University, Montreal, Quebec, Canada
| | - Francis Robert
- Department of Biochemistry, McGill University, Montreal, Quebec, Canada
| | - Bhushan Nagar
- Department of Biochemistry, McGill University, Montreal, Quebec, Canada
| | - Jerry Pelletier
- Department of Biochemistry, McGill University, Montreal, Quebec, Canada.,Department of Oncology, McGill University, Montreal, Quebec, Canada.,Rosalind and Morris Goodman Cancer Institute, McGill University, Montreal, Quebec, Canada
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24
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Wild AR, Hogg PW, Flibotte S, Kochhar S, Hollman RB, Haas K, Bamji SX. CellPalmSeq: A curated RNAseq database of palmitoylating and de-palmitoylating enzyme expression in human cell types and laboratory cell lines. Front Physiol 2023; 14:1110550. [PMID: 36760531 PMCID: PMC9904442 DOI: 10.3389/fphys.2023.1110550] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Accepted: 01/09/2023] [Indexed: 01/25/2023] Open
Abstract
The reversible lipid modification protein S-palmitoylation can dynamically modify the localization, diffusion, function, conformation and physical interactions of substrate proteins. Dysregulated S-palmitoylation is associated with a multitude of human diseases including brain and metabolic disorders, viral infection and cancer. However, the diverse expression patterns of the genes that regulate palmitoylation in the broad range of human cell types are currently unexplored, and their expression in commonly used cell lines that are the workhorse of basic and preclinical research are often overlooked when studying palmitoylation dependent processes. We therefore created CellPalmSeq (https://cellpalmseq.med.ubc.ca), a curated RNAseq database and interactive webtool for visualization of the expression patterns of the genes that regulate palmitoylation across human single cell types, bulk tissue, cancer cell lines and commonly used laboratory non-human cell lines. This resource will allow exploration of these expression patterns, revealing important insights into cellular physiology and disease, and will aid with cell line selection and the interpretation of results when studying important cellular processes that depend on protein S-palmitoylation.
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Affiliation(s)
- Angela R. Wild
- Bamji Lab, Department of Cellular and Physiological Sciences, Life Sciences Institute and Djavad Mowafaghian Centre for Brain Health, Vancouver, BC, Canada
| | - Peter W. Hogg
- Bamji Lab, Department of Cellular and Physiological Sciences, Life Sciences Institute and Djavad Mowafaghian Centre for Brain Health, Vancouver, BC, Canada
| | - Stephane Flibotte
- Life Sciences Institute Bioinformatics Facility, University of British Columbia, Vancouver, BC, Canada
| | - Shruti Kochhar
- Bamji Lab, Department of Cellular and Physiological Sciences, Life Sciences Institute and Djavad Mowafaghian Centre for Brain Health, Vancouver, BC, Canada
| | - Rocio B. Hollman
- Bamji Lab, Department of Cellular and Physiological Sciences, Life Sciences Institute and Djavad Mowafaghian Centre for Brain Health, Vancouver, BC, Canada
| | - Kurt Haas
- Bamji Lab, Department of Cellular and Physiological Sciences, Life Sciences Institute and Djavad Mowafaghian Centre for Brain Health, Vancouver, BC, Canada
| | - Shernaz X. Bamji
- Bamji Lab, Department of Cellular and Physiological Sciences, Life Sciences Institute and Djavad Mowafaghian Centre for Brain Health, Vancouver, BC, Canada,*Correspondence: Shernaz X. Bamji,
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25
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Wang M, Xu H, Han Q, Wang L. Significance of YAP1-MAML2 rearrangement and GTF2I mutation in the diagnosis and differential diagnosis of metaplastic thymoma. Ann Med 2023; 55:2237040. [PMID: 37489594 PMCID: PMC10392284 DOI: 10.1080/07853890.2023.2237040] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/18/2023] [Revised: 07/10/2023] [Accepted: 07/11/2023] [Indexed: 07/26/2023] Open
Abstract
BACKGROUND Metaplastic thymoma (MT) is a very uncommon thymoma type, with biphasic differentiation as one of its histological characteristics. This histological pattern, however, can also be mistaken for type A thymoma and the A component in type AB thymoma. METHODS Postoperative specimens were collected from five MT and four type A thymomas with a retrospective analysis involving immunohistochemistry, fluorescence in situ hybridization (FISH) and next-generation sequencing (NGS). RESULTS The histological morphology of the MT overlapped with that of the type A thymoma. With immunostains, the former's spindle cell components expressed vimentin and EMA, but not CD20. In MT, 3/5 cases had the nuclear expression of YAP1. The spindle cell component of the type A thymoma was found to express CD20. In all five cases of MT, FISH detection revealed YAP1-MAML2 fusion, which was not found in any type A thymoma cases. NGS sequencing confirmed YAP1-MAML2 rearrangement in all five cases of MT, and mutations in POLE and HRAS were also found in two cases, respectively. GTF2I c.74146970 T > A mutations were found in all cases of type A thymoma, and HRAS and NRAS mutations were found in two cases, but no YAP1-MAML2 rearrangement was evident. CONCLUSIONS For the diagnosis and differential diagnosis of challenging cases, the YAP1-MAML2 rearrangement and GTF2I mutation were both significant molecular events specific to MT and type A thymoma, respectively.
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Affiliation(s)
- Minghao Wang
- Department of Neurosurgery, First Hospital of China Medical University, Shenyang, China
| | - Hongtao Xu
- Department of Pathology, First Hospital of China Medical University, Shenyang, China
| | - Qiang Han
- Department of Pathology, First Hospital of China Medical University, Shenyang, China
| | - Liang Wang
- Department of Pathology, First Hospital of China Medical University, Shenyang, China
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26
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Ulgen E, Ozisik O, Sezerman OU. PANACEA: network-based methods for pharmacotherapy prioritization in personalized oncology. Bioinformatics 2023; 39:btad022. [PMID: 36689556 PMCID: PMC9869653 DOI: 10.1093/bioinformatics/btad022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Revised: 12/09/2022] [Accepted: 01/11/2023] [Indexed: 01/13/2023] Open
Abstract
MOTIVATION Identifying appropriate pharmacotherapy options from genomics results is a significant challenge in personalized oncology. However, computational methods for prioritizing drugs are underdeveloped. With the hypothesis that network-based approaches can improve the performance by extending the use of potential drug targets beyond direct interactions, we devised two network-based methods for personalized pharmacotherapy prioritization in cancer. RESULTS We developed novel personalized drug prioritization approaches, PANACEA: PersonAlized Network-based Anti-Cancer therapy EvaluAtion. In PANACEA, initially, the protein interaction network is extended with drugs, and a driverness score is assigned to each altered gene. For scoring drugs, either (i) the 'distance-based' method, incorporating the shortest distance between drugs and altered genes, and driverness scores, or (ii) the 'propagation' method involving the propagation of driverness scores via a random walk with restart framework is performed. We evaluated PANACEA using multiple datasets, and demonstrated that (i) the top-ranking drugs are relevant for cancer pharmacotherapy using TCGA data; (ii) drugs that cancer cell lines are sensitive to are identified using GDSC data; and (iii) PANACEA can perform adequately in the clinical setting using cases with known drug responses. We also illustrate that the proposed methods outperform iCAGES and PanDrugs, two previous personalized drug prioritization approaches. AVAILABILITY AND IMPLEMENTATION The corresponding R package is available on GitHub. (https://github.com/egeulgen/PANACEA.git). SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Ege Ulgen
- Department of Biostatistics and Medical Informatics, School of Medicine, Acibadem Mehmet Ali Aydinlar University, Istanbul 34752, Turkey
| | - Ozan Ozisik
- Aix Marseille University, Inserm, MMG, Marseille 13385, France
| | - Osman Ugur Sezerman
- Department of Biostatistics and Medical Informatics, School of Medicine, Acibadem Mehmet Ali Aydinlar University, Istanbul 34752, Turkey
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27
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Banerjee R, Sotero-Caio CG, Fu B, Yang F. Chromosomal instability (CIN) in HAP1 cell lines revealed by multiplex fluorescence in situ hybridisation (M-FISH). Mol Cytogenet 2022; 15:46. [PMID: 36289492 PMCID: PMC9609465 DOI: 10.1186/s13039-022-00625-x] [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: 08/17/2022] [Accepted: 10/13/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND HAP1, a near-haploid human leukemic cancer cell line is often used in combination with CRISPR-Cas9 gene editing technology for genetic screens. HAP1 carries the Philadelphia chromosome (Ph) and an additional ~ 30 Mb fragment of chromosome 15 inserted into chromosome 19. The potential use of an in vitro cell line as a model system in biomedical research studies depends on its ability to maintain genome stability. Being a cancer cell line with a near-haploid genome, HAP1 is prone to genetic instability, which is further compounded by its tendency to diploidise in culture spontaneously. Moreover, CRISPR-Cas9 gene editing coupled with prolonged in-vitro cell culturing has the potential to induce unintended 'off-target' cytogenetic mutations. To gain an insight into chromosomal instability (CIN) and karyotype heterogeneity, 19 HAP1 cell lines were cytogenetically characterised, 17 of which were near-haploids and two double-haploids, using multiplex fluorescence in situ hybridisation (M-FISH), at single cell resolution. We focused on novel numerical (N) and structural (S) CIN and discussed the potential causal factors for the observed instability. For each cell line we examined its ploidy, gene editing status and its length of in-vitro cell culturing. RESULTS Sixteen of the 19 cell lines had been gene edited with passage numbers ranging from 10 to 35. Diploidisation in 17 near-haploid cell lines ranged from 4 to 35% and percentage of N- and S-CIN in [1n] and [2n] metaphases ranged from 7 to 50% with two cell lines showing no CIN. Percentage of cells with CIN in the two double-haploid cell lines were 96% and 100% respectively. The most common S-CIN observed was deletion followed by translocation of both types, non-reciprocal and Robertsonian. Interestingly, we observed a prevalence of S-CIN associated with chromosome 13 in both near-and double-haploid cell lines, with a high incidence of Robertsonian translocation involving chromosome 13. Furthermore, locus-specific BAC (bacterial artificial chromosome) FISH enabled us to show for the first time that the additional chromosome 15 fragment is inserted into the p-arm rather than the q-arm of chromosome 19 of the HAP1 genome. CONCLUSION Our study revealed a high incidence of CIN leading to karyotype heterogeneity in majority of the HAP1 cell lines with the number of chromosomal aberrations varying between cell lines. A noteworthy observation was the high frequency of structural chromosomal aberrations associated with chromosome 13. We showed that CRISPR-Cas9 gene editing technology in combination with spontaneous diploidisation and prolonged in-vitro cell culturing is potentially instrumental in inducing further chromosomal rearrangements in the HAP1 cell lines with existing CIN. We highlight the importance of maintaining cell lines at low passage and the need for regular monitoring to prevent implications in downstream applications. Our study also established that the additional fragment of chromosome 15 in the HAP1 genome is inserted into chromosome 19p rather than 19q.
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Affiliation(s)
- Ruby Banerjee
- grid.10306.340000 0004 0606 5382Molecular Cytogenetics Core Facility, Wellcome Sanger Institute, Cambridge, CB10 1SA UK
| | - Cibele G. Sotero-Caio
- grid.10306.340000 0004 0606 5382Molecular Cytogenetics Core Facility, Wellcome Sanger Institute, Cambridge, CB10 1SA UK
| | - Beiyuan Fu
- grid.10306.340000 0004 0606 5382Molecular Cytogenetics Core Facility, Wellcome Sanger Institute, Cambridge, CB10 1SA UK
| | - Fengtang Yang
- grid.10306.340000 0004 0606 5382Molecular Cytogenetics Core Facility, Wellcome Sanger Institute, Cambridge, CB10 1SA UK ,grid.412509.b0000 0004 1808 3414School of Life Sciences and Medicine, Shandong University of Technology, Zibo, Shandong People’s Republic of China
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28
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Single-cell profiling reveals molecular basis of malignant phenotypes and tumor microenvironments in small bowel adenocarcinomas. Cell Discov 2022; 8:92. [PMID: 36104333 PMCID: PMC9475032 DOI: 10.1038/s41421-022-00434-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2022] [Accepted: 06/06/2022] [Indexed: 11/08/2022] Open
Abstract
AbstractSmall bowel adenocarcinomas (SBAs) are rare malignant tumors with a high mortality rate, and their molecular characteristics are still largely unexplored. Here we performed single-cell RNA sequencing for tumor samples from 12 SBA patients and predicted drug candidates for SBA. We identified four prevalent subtypes of malignant cells with distinct signatures including cell cycle program, mitochondria program, metabolism program and epithelial–mesenchymal transition (EMT) program. The progression relationships of these four subtypes of malignant cells were also revealed, which started from the cell cycle program, through the mitochondria program and then progressing into either the metabolism program or the EMT program. Importantly, ligand–receptor interaction pairs were found to be specifically enriched in pairs of EMT-program malignant cells and highly exhausted CD8+ T cells, suggesting that cancer cell subpopulations with EMT features may contribute most to the exhaustion of T cells. We also showed that the duodenal subtype of SBA exhibited molecular features more similar to gastric cancer whereas jejunal subtype of SBA more similar to colorectal cancer. Especially, we predicted specific drugs for SBA based on differential gene expression signatures between malignant cells and normal epithelial cells of SBA, and verified more potent inhibitory effects of volasertib and tozasertib for SBA cancer cells than conventional drugs of SBA at the same concentration, which provides new clues for treatments of SBA. In summary, our study provides a blueprint of the molecular signatures of both tumor cells and tumor microenvironment cells in SBA and reveals potential targets and drug candidates for its clinical treatments.
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29
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Leskoske K, Garcia-Mansfield K, Sharma R, Krishnan A, Rusert JM, Mesirov JP, Wechsler-Reya RJ, Pirrotte P. Subgroup-Enriched Pathways and Kinase Signatures in Medulloblastoma Patient-Derived Xenografts. J Proteome Res 2022; 21:2124-2136. [PMID: 35977718 PMCID: PMC9442791 DOI: 10.1021/acs.jproteome.2c00203] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Indexed: 11/30/2022]
Abstract
Medulloblastoma (MB) is the most common malignant pediatric brain tumor. MB is classified into four primary molecular subgroups: wingless (WNT), sonic hedgehog (SHH), Group 3 (G3), and Group 4 (G4), and further genomic and proteomic subtypes have been reported. Subgroup heterogeneity and few actionable mutations have hindered the development of targeted therapies, especially for G3 MB, which has a particularly poor prognosis. To identify novel therapeutic targets for MB, we performed mass spectrometry-based deep expression proteomics and phosphoproteomics in 20 orthotopic patient-derived xenograft (PDX) models of MB comprising SHH, G3, and G4 subgroups. We found that the proteomic profiles of MB PDX tumors are closely aligned with those of primary human MB tumors illustrating the utility of PDX models. SHH PDXs were enriched for NFκB and p38 MAPK signaling, while G3 PDXs were characterized by MYC activity. Additionally, we found a significant association between actinomycin D sensitivity and increased abundance of MYC and MYC target genes. Our results highlight several candidate pathways that may serve as targets for new MB therapies. Mass spectrometry data are available via ProteomeXchange with identifier PXD035070.
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Affiliation(s)
- Kristin
L. Leskoske
- Cancer
and Cell Biology Division, Translational
Genomics Research Institute, Phoenix, Arizona 85004, United States
| | - Krystine Garcia-Mansfield
- Cancer
and Cell Biology Division, Translational
Genomics Research Institute, Phoenix, Arizona 85004, United States
- Integrated
Mass Spectrometry Shared Resource, City of Hope Comprehensive Cancer
Center, Duarte, California 91010, United States
| | - Ritin Sharma
- Cancer
and Cell Biology Division, Translational
Genomics Research Institute, Phoenix, Arizona 85004, United States
- Integrated
Mass Spectrometry Shared Resource, City of Hope Comprehensive Cancer
Center, Duarte, California 91010, United States
| | - Aparna Krishnan
- Cancer
and Cell Biology Division, Translational
Genomics Research Institute, Phoenix, Arizona 85004, United States
| | - Jessica M. Rusert
- Tumor
Initiation and Maintenance Program, NCI-Designated Cancer Center, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, California 92037, United States
| | - Jill P. Mesirov
- Department
of Medicine, University of California San
Diego, La Jolla, California 92093, United States
- Moores
Cancer Center, University of California
San Diego, La Jolla, California 92093, United States
| | - Robert J. Wechsler-Reya
- Tumor
Initiation and Maintenance Program, NCI-Designated Cancer Center, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, California 92037, United States
| | - Patrick Pirrotte
- Cancer
and Cell Biology Division, Translational
Genomics Research Institute, Phoenix, Arizona 85004, United States
- Integrated
Mass Spectrometry Shared Resource, City of Hope Comprehensive Cancer
Center, Duarte, California 91010, United States
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30
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Cancer cell histone density links global histone acetylation, mitochondrial proteome and histone acetylase inhibitor sensitivity. Commun Biol 2022; 5:882. [PMID: 36030322 PMCID: PMC9420116 DOI: 10.1038/s42003-022-03846-3] [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: 11/22/2021] [Accepted: 08/16/2022] [Indexed: 12/03/2022] Open
Abstract
Chromatin metabolism is frequently altered in cancer cells and facilitates cancer development. While cancer cells produce large amounts of histones, the protein component of chromatin packaging, during replication, the potential impact of histone density on cancer biology has not been studied systematically. Here, we show that altered histone density affects global histone acetylation, histone deactylase inhibitor sensitivity and altered mitochondrial proteome composition. We present estimates of nuclear histone densities in 373 cancer cell lines, based on Cancer Cell Line Encyclopedia data, and we show that a known histone regulator, HMGB1, is linked to histone density aberrations in many cancer cell lines. We further identify an E3 ubiquitin ligase interactor, DCAF6, and a mitochondrial respiratory chain assembly factor, CHCHD4, as histone modulators. As systematic characterization of histone density aberrations in cancer cell lines, this study provides approaches and resources to investigate the impact of histone density on cancer biology. Elevated histone density is associated with global histone acetylation, histone deacetylase inhibitor sensitivity and altered mitochondrial proteome composition, with histone regulator HMGB1 linked to histone density aberrations in many cancer cell lines.
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31
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Gonçalves E, Poulos RC, Cai Z, Barthorpe S, Manda SS, Lucas N, Beck A, Bucio-Noble D, Dausmann M, Hall C, Hecker M, Koh J, Lightfoot H, Mahboob S, Mali I, Morris J, Richardson L, Seneviratne AJ, Shepherd R, Sykes E, Thomas F, Valentini S, Williams SG, Wu Y, Xavier D, MacKenzie KL, Hains PG, Tully B, Robinson PJ, Zhong Q, Garnett MJ, Reddel RR. Pan-cancer proteomic map of 949 human cell lines. Cancer Cell 2022; 40:835-849.e8. [PMID: 35839778 PMCID: PMC9387775 DOI: 10.1016/j.ccell.2022.06.010] [Citation(s) in RCA: 57] [Impact Index Per Article: 28.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Revised: 03/29/2022] [Accepted: 06/21/2022] [Indexed: 12/12/2022]
Abstract
The proteome provides unique insights into disease biology beyond the genome and transcriptome. A lack of large proteomic datasets has restricted the identification of new cancer biomarkers. Here, proteomes of 949 cancer cell lines across 28 tissue types are analyzed by mass spectrometry. Deploying a workflow to quantify 8,498 proteins, these data capture evidence of cell-type and post-transcriptional modifications. Integrating multi-omics, drug response, and CRISPR-Cas9 gene essentiality screens with a deep learning-based pipeline reveals thousands of protein biomarkers of cancer vulnerabilities that are not significant at the transcript level. The power of the proteome to predict drug response is very similar to that of the transcriptome. Further, random downsampling to only 1,500 proteins has limited impact on predictive power, consistent with protein networks being highly connected and co-regulated. This pan-cancer proteomic map (ProCan-DepMapSanger) is a comprehensive resource available at https://cellmodelpassports.sanger.ac.uk.
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Affiliation(s)
- Emanuel Gonçalves
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge CB10 1SA, UK; Instituto Superior Técnico (IST), Universidade de Lisboa, 1049-001 Lisboa, Portugal; INESC-ID, 1000-029 Lisboa, Portugal
| | - Rebecca C Poulos
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
| | - Zhaoxiang Cai
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
| | - Syd Barthorpe
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge CB10 1SA, UK
| | - Srikanth S Manda
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
| | - Natasha Lucas
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
| | - Alexandra Beck
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge CB10 1SA, UK
| | - Daniel Bucio-Noble
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
| | - Michael Dausmann
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
| | - Caitlin Hall
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge CB10 1SA, UK
| | - Michael Hecker
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
| | - Jennifer Koh
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
| | - Howard Lightfoot
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge CB10 1SA, UK
| | - Sadia Mahboob
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
| | - Iman Mali
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge CB10 1SA, UK
| | - James Morris
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge CB10 1SA, UK
| | - Laura Richardson
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge CB10 1SA, UK
| | - Akila J Seneviratne
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
| | - Rebecca Shepherd
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge CB10 1SA, UK
| | - Erin Sykes
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
| | - Frances Thomas
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge CB10 1SA, UK
| | - Sara Valentini
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge CB10 1SA, UK
| | - Steven G Williams
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
| | - Yangxiu Wu
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
| | - Dylan Xavier
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
| | - Karen L MacKenzie
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
| | - Peter G Hains
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
| | - Brett Tully
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
| | - Phillip J Robinson
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia.
| | - Qing Zhong
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia.
| | - Mathew J Garnett
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge CB10 1SA, UK.
| | - Roger R Reddel
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia.
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32
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Wang ZY, Li DL, Tian X, Li Y, Zhang CY. Single-Molecule Counting of FTO in Human Breast Tissues Based on a Rolling Circle Transcription Amplification-Driven Clustered Regularly Interspaced Short Palindromic Repeat─Cas12a. Anal Chem 2022; 94:11425-11432. [PMID: 35916620 DOI: 10.1021/acs.analchem.2c02578] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
N6-methyladenosine modification as an mRNA modification in mammalian cells is dynamically reversible, regulated by RNA demethylase [e.g., fat mass and obesity-associated protein (FTO)]. The abnormal expression of FTO is closely related to numerous diseases (e.g., various cancers and obesity). Herein, we demonstrate the single-molecule counting of FTO in human cancer cells and breast tissues based on a T7 RNA polymerase-mediated rolling circle transcription (RCT) amplification-driven clustered regularly interspaced short palindromic repeat (CRISPR)─Cas12a. When FTO is present, it demethylates the DNA substrate, initiating the DpnII-mediated cleavage reaction. After magnetic separation, the cleaved DNA fragments trigger the T7 RNA polymerase-mediated RCT amplification, activating CRISPR-/Cas12a-mediated cleavage of signal probes and releasing abundant FAM molecules that are simply counted via single-molecule detection. In this assay, only target FTO can generate CRISPR RNAs, efficiently improving detection specificity. Moreover, the integration of single-molecule detection with magnetic separation achieves zero background and effectively enhances detection sensitivity. This method can specifically and sensitively monitor FTO activity with a limit of detection of 1.20 × 10-13 M, and it may measure FTO at the single-cell level. Furthermore, it may accurately discriminate the FTO expression level in breast tissues between healthy persons and breast cancer patients and screen the FTO inhibitors as well, with great potential in clinical diagnosis and drug discovery.
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Affiliation(s)
- Zi-Yue Wang
- College of Chemistry, Chemical Engineering and Materials Science, Shandong Normal University, Jinan 250014, China
| | - Dong-Ling Li
- College of Chemistry, Chemical Engineering and Materials Science, Shandong Normal University, Jinan 250014, China
| | - Xiaorui Tian
- College of Chemistry, Chemical Engineering and Materials Science, Shandong Normal University, Jinan 250014, China
| | - Yueying Li
- Institute of Immunity and Infectious Diseases, School of Medicine and Pharmaceutical Sciences, Zhengzhou University, Zhengzhou 450000, China
| | - Chun-Yang Zhang
- College of Chemistry, Chemical Engineering and Materials Science, Shandong Normal University, Jinan 250014, China
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33
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Gutierrez-Prat N, Zuberer HL, Mangano L, Karimaddini Z, Wolf L, Tyanova S, Wellinger LC, Marbach D, Griesser V, Pettazzoni P, Bischoff JR, Rohle D, Palladino C, Vivanco I. DUSP4 protects BRAF- and NRAS-mutant melanoma from oncogene overdose through modulation of MITF. Life Sci Alliance 2022; 5:5/9/e202101235. [PMID: 35580987 PMCID: PMC9113946 DOI: 10.26508/lsa.202101235] [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: 09/16/2021] [Revised: 05/04/2022] [Accepted: 05/05/2022] [Indexed: 11/24/2022] Open
Abstract
MAPK inhibitors (MAPKi) remain an important component of the standard of care for metastatic melanoma. However, acquired resistance to these drugs limits their therapeutic benefit. Tumor cells can become refractory to MAPKi by reactivation of ERK. When this happens, tumors often become sensitive to drug withdrawal. This drug addiction phenotype results from the hyperactivation of the oncogenic pathway, a phenomenon commonly referred to as oncogene overdose. Several feedback mechanisms are involved in regulating ERK signaling. However, the genes that serve as gatekeepers of oncogene overdose in mutant melanoma remain unknown. Here, we demonstrate that depletion of the ERK phosphatase, DUSP4, leads to toxic levels of MAPK activation in both drug-naive and drug-resistant mutant melanoma cells. Importantly, ERK hyperactivation is associated with down-regulation of lineage-defining genes including MITF Our results offer an alternative therapeutic strategy to treat mutant melanoma patients with acquired MAPKi resistance and those unable to tolerate MAPKi.
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Affiliation(s)
- Nuria Gutierrez-Prat
- Roche Pharma Research and Early Development, Oncology Discovery, Roche Innovation Center Basel, Basel, Switzerland
| | - Hedwig L Zuberer
- Roche Pharma Research and Early Development, Oncology Discovery, Roche Innovation Center Basel, Basel, Switzerland
| | - Luca Mangano
- Roche Pharma Research and Early Development, Oncology Discovery, Roche Innovation Center Basel, Basel, Switzerland
| | - Zahra Karimaddini
- Roche Pharma Research and Early Development, Informatics, Roche Innovation Center Basel, Basel, Switzerland
| | - Luise Wolf
- Roche Pharma Research and Early Development, Informatics, Roche Innovation Center Basel, Basel, Switzerland
| | - Stefka Tyanova
- Roche Pharma Research and Early Development, Informatics, Roche Innovation Center Basel, Basel, Switzerland
| | | | - Daniel Marbach
- Roche Pharma Research and Early Development, Pharmaceutical Sciences, Roche Innovation Center Basel, Basel, Switzerland
| | - Vera Griesser
- Roche Pharma Research and Early Development, Pharmaceutical Sciences, Roche Innovation Center Basel, Basel, Switzerland
| | - Piergiorgio Pettazzoni
- Roche Pharma Research and Early Development, Oncology Discovery, Roche Innovation Center Basel, Basel, Switzerland
| | - James R Bischoff
- Roche Pharma Research and Early Development, Oncology Discovery, Roche Innovation Center Basel, Basel, Switzerland
| | | | - Chiara Palladino
- Roche Pharma Research and Early Development, Oncology Discovery, Roche Innovation Center Basel, Basel, Switzerland
| | - Igor Vivanco
- Institute of Pharmaceutical Science, King's College London, London, UK
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34
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Abstract
Distilling biologically meaningful information from cancer genome sequencing data requires comprehensive identification of somatic alterations using rigorous computational methods. As the amount and complexity of sequencing data have increased, so has the number of tools for analysing them. Here, we describe the main steps involved in the bioinformatic analysis of cancer genomes, review key algorithmic developments and highlight popular tools and emerging technologies. These tools include those that identify point mutations, copy number alterations, structural variations and mutational signatures in cancer genomes. We also discuss issues in experimental design, the strengths and limitations of sequencing modalities and methodological challenges for the future.
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35
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Cruz-Duarte R, Rebelo de Almeida C, Negrão M, Fernandes A, Borralho P, Sobral D, Gallego-Paez LM, Machado D, Gramaça J, Vílchez J, Xavier AT, Ferreira MG, Miranda AR, Mansinho H, Brito MJ, Pacheco TR, Abreu C, Lucia-Costa A, Mansinho A, Fior R, Costa L, Martins M. Predictive and Therapeutic Implications of a Novel PLCγ1/SHP2-Driven Mechanism of Cetuximab Resistance in Metastatic Colorectal Cancer. Clin Cancer Res 2022; 28:1203-1216. [PMID: 34980600 PMCID: PMC9365369 DOI: 10.1158/1078-0432.ccr-21-1992] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Revised: 11/14/2021] [Accepted: 12/27/2021] [Indexed: 01/07/2023]
Abstract
PURPOSE Cetuximab is an EGFR-targeted therapy approved for the treatment of RAS wild-type (WT) metastatic colorectal cancer (mCRC). However, about 60% of these patients show innate resistance to cetuximab. To increase cetuximab efficacy, it is crucial to successfully identify responder patients, as well as to develop new therapeutic approaches to overcome cetuximab resistance. EXPERIMENTAL DESIGN We evaluated the value of EGFR effector phospholipase C gamma 1 (PLCγ1) in predicting cetuximab responses, by analyzing progression-free survival (PFS) of a multicentric retrospective cohort of 94 treated patients with mCRC (log-rank test and Cox regression model). Furthermore, we used in vitro and zebrafish xenotransplant models to identify and target the mechanism behind PLCγ1-mediated resistance to cetuximab. RESULTS In this study, levels of PLCγ1 were found increased in RAS WT tumors and were able to predict cetuximab responses in clinical samples and in vitro and in vivo models. Mechanistically, PLCγ1 expression was found to bypass cetuximab-dependent EGFR inhibition by activating ERK and AKT pathways. This novel resistance mechanism involves a noncatalytic role of PLCγ1 SH2 tandem domains in the propagation of downstream signaling via SH2-containing protein tyrosine phosphatase 2 (SHP2). Accordingly, SHP2 inhibition sensitizes PLCγ1-resistant cells to cetuximab. CONCLUSIONS Our discoveries reveal the potential of PLCγ1 as a predictive biomarker for cetuximab responses and suggest an alternative therapeutic approach to circumvent PLCγ1-mediated resistance to cetuximab in patients with RAS WT mCRC. In this way, this work contributes to the development of novel strategies in the medical management and treatment of patients with mCRC.
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Affiliation(s)
- Raquel Cruz-Duarte
- Instituto de Medicina Molecular - João Lobo Antunes, Faculdade de Medicina, Universidade de Lisboa, Lisbon, Portugal
| | | | - Magda Negrão
- Champalimaud Centre for the Unknown, Champalimaud Foundation, Lisbon, Portugal
| | - Afonso Fernandes
- Instituto de Medicina Molecular - João Lobo Antunes, Faculdade de Medicina, Universidade de Lisboa, Lisbon, Portugal
| | - Paula Borralho
- Institute of Pathology, Faculdade de Medicina, Universidade de Lisboa, Lisbon, Portugal
| | - Daniel Sobral
- Universidade Nova Lisboa, UCIBIO, Departamento de Ciências da Vida, Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, Caparica, Portugal
| | | | - Daniel Machado
- Oncology Division, Centro Hospitalar Barreiro-Montijo, Barreiro, Portugal
| | - João Gramaça
- Oncology Division, Centro Hospitalar Barreiro-Montijo, Barreiro, Portugal
| | - José Vílchez
- Oncology Division, Centro Hospitalar Barreiro-Montijo, Barreiro, Portugal
| | - Ana T. Xavier
- Oncology Division, Centro Hospitalar Barreiro-Montijo, Barreiro, Portugal
| | - Miguel Godinho Ferreira
- Champalimaud Centre for the Unknown, Champalimaud Foundation, Lisbon, Portugal.,Institute for Research on Cancer and Aging of Nice (IRCAN), UMR7284 U1081 UNS, Université Côte d'Azur, Nice, France
| | - Ana R. Miranda
- Hemato-Oncologia Division, Hospital Garcia de Orta, Almada, Portugal
| | - Helder Mansinho
- Hemato-Oncologia Division, Hospital Garcia de Orta, Almada, Portugal
| | - Maria J. Brito
- Pathology Division, Hospital Garcia de Orta, Almada, Portugal
| | - Teresa R. Pacheco
- Instituto de Medicina Molecular - João Lobo Antunes, Faculdade de Medicina, Universidade de Lisboa, Lisbon, Portugal.,Oncology Division, Hospital de Santa Maria, Centro Hospitalar Lisboa Norte, Lisbon, Portugal
| | - Catarina Abreu
- Oncology Division, Hospital de Santa Maria, Centro Hospitalar Lisboa Norte, Lisbon, Portugal
| | - Ana Lucia-Costa
- Oncology Division, Hospital de Santa Maria, Centro Hospitalar Lisboa Norte, Lisbon, Portugal
| | - André Mansinho
- Instituto de Medicina Molecular - João Lobo Antunes, Faculdade de Medicina, Universidade de Lisboa, Lisbon, Portugal.,Oncology Division, Hospital de Santa Maria, Centro Hospitalar Lisboa Norte, Lisbon, Portugal
| | - Rita Fior
- Champalimaud Centre for the Unknown, Champalimaud Foundation, Lisbon, Portugal
| | - Luís Costa
- Instituto de Medicina Molecular - João Lobo Antunes, Faculdade de Medicina, Universidade de Lisboa, Lisbon, Portugal.,Oncology Division, Hospital de Santa Maria, Centro Hospitalar Lisboa Norte, Lisbon, Portugal.,Corresponding Authors: Marta Martins, Translational Oncology, Instituto de Medicina Molecular - João Lobo Antunes, Lisbon 1649-028, Portugal. E-mail: ; and Luís Costa, Instituto de Medicina Molecular-João Lobo Antunes, Faculdade de Medicina, Universidade de Lisboa, Lisbon 1649-028, Portugal. E-mail:
| | - Marta Martins
- Instituto de Medicina Molecular - João Lobo Antunes, Faculdade de Medicina, Universidade de Lisboa, Lisbon, Portugal.,Corresponding Authors: Marta Martins, Translational Oncology, Instituto de Medicina Molecular - João Lobo Antunes, Lisbon 1649-028, Portugal. E-mail: ; and Luís Costa, Instituto de Medicina Molecular-João Lobo Antunes, Faculdade de Medicina, Universidade de Lisboa, Lisbon 1649-028, Portugal. E-mail:
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36
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Systematic illumination of druggable genes in cancer genomes. Cell Rep 2022; 38:110400. [PMID: 35196490 PMCID: PMC8919705 DOI: 10.1016/j.celrep.2022.110400] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2021] [Revised: 09/12/2021] [Accepted: 01/26/2022] [Indexed: 01/15/2023] Open
Abstract
By combining 6 druggable genome resources, we identify 6,083 genes as potential druggable genes (PDGs). We characterize their expression, recurrent genomic alterations, cancer dependencies, and therapeutic potentials by integrating genome, functionome, and druggome profiles across cancers. 81.5% of PDGs are reliably expressed in major adult cancers, 46.9% show selective expression patterns, and 39.1% exhibit at least one recurrent genomic alteration. We annotate a total of 784 PDGs as dependent genes for cancer cell growth. We further quantify 16 cancer-related features and estimate a PDG cancer drug target score (PCDT score). PDGs with higher PCDT scores are significantly enriched for genes encoding kinases and histone modification enzymes. Importantly, we find that a considerable portion of high PCDT score PDGs are understudied genes, providing unexplored opportunities for drug development in oncology. By integrating the druggable genome and the cancer genome, our study thus generates a comprehensive blueprint of potential druggable genes across cancers. Jiang et al. generate a comprehensive blueprint of potential druggable genes (PDGs) across cancers by a systematic integration of the druggable genome and the cancer genome. This resource is publicly available to the cancer research community in The Cancer Druggable Gene Atlas (TCDA) through the Functional Cancer Genome data portal.
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37
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The Hippo pathway in cancer: YAP/TAZ and TEAD as therapeutic targets in cancer. Clin Sci (Lond) 2022; 136:197-222. [PMID: 35119068 PMCID: PMC8819670 DOI: 10.1042/cs20201474] [Citation(s) in RCA: 95] [Impact Index Per Article: 47.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Revised: 01/05/2022] [Accepted: 01/18/2022] [Indexed: 02/07/2023]
Abstract
Tumorigenesis is a highly complex process, involving many interrelated and cross-acting signalling pathways. One such pathway that has garnered much attention in the field of cancer research over the last decade is the Hippo signalling pathway. Consisting of two antagonistic modules, the pathway plays an integral role in both tumour suppressive and oncogenic processes, generally via regulation of a diverse set of genes involved in a range of biological functions. This review discusses the history of the pathway within the context of cancer and explores some of the most recent discoveries as to how this critical transducer of cellular signalling can influence cancer progression. A special focus is on the various recent efforts to therapeutically target the key effectors of the pathway in both preclinical and clinical settings.
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38
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de Nonneville A, Finetti P, Mamessier E, Bertucci F. RE: NDRG1 in Aggressive Breast Cancer Progression and Brain Metastasis. J Natl Cancer Inst 2022; 114:1046-1047. [PMID: 35148398 PMCID: PMC9275762 DOI: 10.1093/jnci/djac031] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2022] [Revised: 01/12/2022] [Accepted: 02/02/2022] [Indexed: 11/13/2022] Open
Affiliation(s)
- Alexandre de Nonneville
- Laboratory of Predictive Oncology, Equipe labellisée Ligue Nationale Contre Le Cancer, Centre de Recherche en Cancérologie de Marseille, Institut Paoli-Calmettes, INSERM UMR1068, CNRS UMR725, Marseille, France
| | - Pascal Finetti
- Laboratory of Predictive Oncology, Equipe labellisée Ligue Nationale Contre Le Cancer, Centre de Recherche en Cancérologie de Marseille, Institut Paoli-Calmettes, INSERM UMR1068, CNRS UMR725, Marseille, France
| | - Emilie Mamessier
- Laboratory of Predictive Oncology, Equipe labellisée Ligue Nationale Contre Le Cancer, Centre de Recherche en Cancérologie de Marseille, Institut Paoli-Calmettes, INSERM UMR1068, CNRS UMR725, Marseille, France
| | - François Bertucci
- Correspondence to: François Bertucci, MD, PhD, Department of Medical Oncology, Laboratory of Predictive Oncology, Institut Paoli-Calmettes, 232 Bd. Sainte-Marguerite, 13009 Marseille, France (e-mail: )
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39
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Feizi N, Nair SK, Smirnov P, Beri G, Eeles C, Esfahani PN, Nakano M, Tkachuk D, Mammoliti A, Gorobets E, Mer AS, Lin E, Yu Y, Martin S, Hafner M, Haibe-Kains B. PharmacoDB 2.0: improving scalability and transparency of in vitro pharmacogenomics analysis. Nucleic Acids Res 2022; 50:D1348-D1357. [PMID: 34850112 PMCID: PMC8728279 DOI: 10.1093/nar/gkab1084] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Revised: 10/15/2021] [Accepted: 10/20/2021] [Indexed: 11/14/2022] Open
Abstract
Cancer pharmacogenomics studies provide valuable insights into disease progression and associations between genomic features and drug response. PharmacoDB integrates multiple cancer pharmacogenomics datasets profiling approved and investigational drugs across cell lines from diverse tissue types. The web-application enables users to efficiently navigate across datasets, view and compare drug dose-response data for a specific drug-cell line pair. In the new version of PharmacoDB (version 2.0, https://pharmacodb.ca/), we present (i) new datasets such as NCI-60, the Profiling Relative Inhibition Simultaneously in Mixtures (PRISM) dataset, as well as updated data from the Genomics of Drug Sensitivity in Cancer (GDSC) and the Genentech Cell Line Screening Initiative (gCSI); (ii) implementation of FAIR data pipelines using ORCESTRA and PharmacoDI; (iii) enhancements to drug-response analysis such as tissue distribution of dose-response metrics and biomarker analysis; and (iv) improved connectivity to drug and cell line databases in the community. The web interface has been rewritten using a modern technology stack to ensure scalability and standardization to accommodate growing pharmacogenomics datasets. PharmacoDB 2.0 is a valuable tool for mining pharmacogenomics datasets, comparing and assessing drug-response phenotypes of cancer models.
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Affiliation(s)
- Nikta Feizi
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON M5G 2C1, Canada
| | - Sisira Kadambat Nair
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON M5G 2C1, Canada
| | - Petr Smirnov
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON M5G 2C1, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON M5G 1L7, Canada
| | - Gangesh Beri
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON M5G 2C1, Canada
| | - Christopher Eeles
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON M5G 2C1, Canada
| | - Parinaz Nasr Esfahani
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON M5G 2C1, Canada
| | - Minoru Nakano
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON M5G 2C1, Canada
| | - Denis Tkachuk
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON M5G 2C1, Canada
| | - Anthony Mammoliti
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON M5G 2C1, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON M5G 1L7, Canada
| | - Evgeniya Gorobets
- Department of Cell and Systems Biology, University of Toronto, Toronto, ON M5S 3G5, Canada
| | - Arvind Singh Mer
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON M5G 2C1, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON M5G 1L7, Canada
| | - Eva Lin
- Department of Discovery Oncology, Genentech Inc, South San Francisco, CA 94080, USA
| | - Yihong Yu
- Department of Discovery Oncology, Genentech Inc, South San Francisco, CA 94080, USA
| | - Scott Martin
- Department of Discovery Oncology, Genentech Inc, South San Francisco, CA 94080, USA
| | - Marc Hafner
- Department of Oncology Bioinformatics, Genentech Inc, South San Francisco, CA 94080, USA
| | - Benjamin Haibe-Kains
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON M5G 2C1, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON M5G 1L7, Canada
- Department of Computer Science, University of Toronto, Toronto, ON M5T 3A1, Canada
- Ontario Institute for Cancer Research, Toronto, ON M5G 0A3, Canada
- Vector Institute for Artificial Intelligence, Toronto, ON M5G 1M1, Canada
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40
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Creason A, Haan D, Dang K, Chiotti KE, Inkman M, Lamb A, Yu T, Hu Y, Norman TC, Buchanan A, van Baren MJ, Spangler R, Rollins MR, Spellman PT, Rozanov D, Zhang J, Maher CA, Caloian C, Watson JD, Uhrig S, Haas BJ, Jain M, Akeson M, Ahsen ME, Stolovitzky G, Guinney J, Boutros PC, Stuart JM, Ellrott K. A community challenge to evaluate RNA-seq, fusion detection, and isoform quantification methods for cancer discovery. Cell Syst 2021; 12:827-838.e5. [PMID: 34146471 PMCID: PMC8376800 DOI: 10.1016/j.cels.2021.05.021] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2019] [Revised: 09/15/2020] [Accepted: 05/25/2021] [Indexed: 02/03/2023]
Abstract
The accurate identification and quantitation of RNA isoforms present in the cancer transcriptome is key for analyses ranging from the inference of the impacts of somatic variants to pathway analysis to biomarker development and subtype discovery. The ICGC-TCGA DREAM Somatic Mutation Calling in RNA (SMC-RNA) challenge was a crowd-sourced effort to benchmark methods for RNA isoform quantification and fusion detection from bulk cancer RNA sequencing (RNA-seq) data. It concluded in 2018 with a comparison of 77 fusion detection entries and 65 isoform quantification entries on 51 synthetic tumors and 32 cell lines with spiked-in fusion constructs. We report the entries used to build this benchmark, the leaderboard results, and the experimental features associated with the accurate prediction of RNA species. This challenge required submissions to be in the form of containerized workflows, meaning each of the entries described is easily reusable through CWL and Docker containers at https://github.com/SMC-RNA-challenge. A record of this paper's transparent peer review process is included in the supplemental information.
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Affiliation(s)
- Allison Creason
- Biomedical Engineering, Oregon Health and Science University, Portland, OR 97239, USA
| | - David Haan
- Biomolecular Engineering and UC Santa Cruz Genome Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | | | - Kami E Chiotti
- Biomedical Engineering, Oregon Health and Science University, Portland, OR 97239, USA
| | - Matthew Inkman
- The Genome Institute, Washington University School of Medicine, 4444 Forest Park Avenue, St. Louis, MO 63110, USA
| | | | | | - Yin Hu
- Sage Bionetworks, Seattle, WA, USA
| | | | - Alex Buchanan
- Biomedical Engineering, Oregon Health and Science University, Portland, OR 97239, USA
| | - Marijke J van Baren
- Biomolecular Engineering and UC Santa Cruz Genome Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Ryan Spangler
- Biomedical Engineering, Oregon Health and Science University, Portland, OR 97239, USA
| | - M Rick Rollins
- Biomedical Engineering, Oregon Health and Science University, Portland, OR 97239, USA
| | - Paul T Spellman
- Biomedical Engineering, Oregon Health and Science University, Portland, OR 97239, USA
| | - Dmitri Rozanov
- Biomedical Engineering, Oregon Health and Science University, Portland, OR 97239, USA
| | - Jin Zhang
- The Genome Institute, Washington University School of Medicine, 4444 Forest Park Avenue, St. Louis, MO 63110, USA
| | - Christopher A Maher
- The Genome Institute, Washington University School of Medicine, 4444 Forest Park Avenue, St. Louis, MO 63110, USA
| | - Cristian Caloian
- Computational Biology, Ontario Institute for Cancer Research, Toronto, Canada
| | - John D Watson
- Computational Biology, Ontario Institute for Cancer Research, Toronto, Canada
| | - Sebastian Uhrig
- Division of Applied Bioinformatics, German Cancer Research Center (DKFZ) and Faculty of Biosciences, Heidelberg University, Heidelberg, Germany
| | - Brian J Haas
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Miten Jain
- Biomolecular Engineering and UC Santa Cruz Genome Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Mark Akeson
- Biomolecular Engineering and UC Santa Cruz Genome Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Mehmet Eren Ahsen
- Icahn School of Medicine at Mount Sinai, Department of Genetics and Genomic Sciences, One Gustave Levy Place, New York, NY 1498, USA
| | - Gustavo Stolovitzky
- Icahn School of Medicine at Mount Sinai, Department of Genetics and Genomic Sciences, One Gustave Levy Place, New York, NY 1498, USA; IBM T.J. Watson Research Center, 1101 Kitchawan Road, Route 134, Yorktown Heights, NY 10598, USA
| | | | - Paul C Boutros
- Computational Biology, Ontario Institute for Cancer Research, Toronto, Canada; Departments of Medical Biophysics and Pharmacology & Toxicology, University of Toronto, Toronto, Canada; Departments of Human Genetics and Urology, University of California, Los Angeles, Los Angeles, CA, USA
| | - Joshua M Stuart
- Biomolecular Engineering and UC Santa Cruz Genome Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Kyle Ellrott
- Biomedical Engineering, Oregon Health and Science University, Portland, OR 97239, USA.
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41
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Rosell R, Cardona AF, Arrieta O, Aguilar A, Ito M, Pedraz C, Codony-Servat J, Santarpia M. Coregulation of pathways in lung cancer patients with EGFR mutation: therapeutic opportunities. Br J Cancer 2021; 125:1602-1611. [PMID: 34373568 PMCID: PMC8351231 DOI: 10.1038/s41416-021-01519-2] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Revised: 06/18/2021] [Accepted: 07/26/2021] [Indexed: 12/15/2022] Open
Abstract
Epidermal growth factor receptor (EGFR) mutations in lung adenocarcinoma are a frequent class of driver mutations. Single EGFR tyrosine kinase inhibitor (TKI) provides substantial clinical benefit, but almost nil radiographic complete responses. Patients invariably progress, although survival can reach several years with post-treatment therapies, including EGFR TKIs, chemotherapy or other procedures. Endeavours have been clinically oriented to manage the acquisition of EGFR TKI-resistant mutations; however, basic principles on cancer evolution have not been considered in clinical trials. For years, evidence has displayed rapidly adaptive mechanisms of resistance to selective monotherapy, posing several dilemmas for the practitioner. Strict adherence to non-small cell lung cancer (NSCLC) guidelines is not always practical for addressing the clinical progression that EGFR-mutant lung adenocarcinoma patients suffer. The purpose of this review is to highlight regulatory mechanisms and signalling pathways that cause therapy-induced resistance to EGFR TKIs. It suggests combinatorial therapies that target EGFR, as well as potential mechanisms underlying EGFR-mutant NSCLC, alerting the reader to clinical opportunities that may lead to a deeper and more durable response. Molecular reprogramming contributes to EGFR TKI resistance, and the compiled information is relevant in understanding the development of new combined targeted strategies in EGFR-mutant NSCLC.
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Affiliation(s)
- Rafael Rosell
- Catalan Institute of Oncology, Badalona, Spain. .,Oncology Institute Dr Rosell, IOR, Barcelona, Spain.
| | - Andrés Felipe Cardona
- Clinical and Translational Oncology Group, Thoracic Oncology Unit, Institute of Oncologyt, Clínica del Country, Bogotá, Colombia
| | - Oscar Arrieta
- Personalized Medicine Laboratory, Instituto Nacional de Cancerología, México City, México.,Thoracic Oncology Unit, Instituto Nacional de Cancerología, México City, México
| | | | - Masaoki Ito
- Department of Surgical Oncology, Research Institute for Radiation Biology and Medicine, Hiroshima University, Hiroshima, Japan
| | - Carlos Pedraz
- Germans Trias i Pujol Research Institute, Badalona, Spain.,Biochemistry, Molecular Biology and Biomedicine Department, Universitat Autónoma de Barcelona, Bellaterra, Barcelona, Spain
| | | | - Mariacarmela Santarpia
- Medical Oncology Unit, Department of Human Pathology "G. Barresi", University of Messina, Messina, Italy
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42
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Gillani R, Seong BKA, Crowdis J, Conway JR, Dharia NV, Alimohamed S, Haas BJ, Han K, Park J, Dietlein F, He MX, Imamovic A, Ma C, Bassik MC, Boehm JS, Vazquez F, Gusev A, Liu D, Janeway KA, McFarland JM, Stegmaier K, Van Allen EM. Gene Fusions Create Partner and Collateral Dependencies Essential to Cancer Cell Survival. Cancer Res 2021; 81:3971-3984. [PMID: 34099491 PMCID: PMC8338889 DOI: 10.1158/0008-5472.can-21-0791] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2021] [Revised: 03/26/2021] [Accepted: 06/04/2021] [Indexed: 01/07/2023]
Abstract
Gene fusions frequently result from rearrangements in cancer genomes. In many instances, gene fusions play an important role in oncogenesis; in other instances, they are thought to be passenger events. Although regulatory element rearrangements and copy number alterations resulting from these structural variants are known to lead to transcriptional dysregulation across cancers, the extent to which these events result in functional dependencies with an impact on cancer cell survival is variable. Here we used CRISPR-Cas9 dependency screens to evaluate the fitness impact of 3,277 fusions across 645 cell lines from the Cancer Dependency Map. We found that 35% of cell lines harbored either a fusion partner dependency or a collateral dependency on a gene within the same topologically associating domain as a fusion partner. Fusion-associated dependencies revealed numerous novel oncogenic drivers and clinically translatable alterations. Broadly, fusions can result in partner and collateral dependencies that have biological and clinical relevance across cancer types. SIGNIFICANCE: This study provides insights into how fusions contribute to fitness in different cancer contexts beyond partner-gene activation events, identifying partner and collateral dependencies that may have direct implications for clinical care.
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Affiliation(s)
- Riaz Gillani
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts.,Broad Institute of Harvard and MIT, Cambridge, Massachusetts.,Department of Pediatrics, Harvard Medical School, Boston, Massachusetts.,Boston Children's Hospital, Boston, Massachusetts
| | - Bo Kyung A. Seong
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts.,Broad Institute of Harvard and MIT, Cambridge, Massachusetts
| | - Jett Crowdis
- Broad Institute of Harvard and MIT, Cambridge, Massachusetts.,Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Jake R. Conway
- Broad Institute of Harvard and MIT, Cambridge, Massachusetts.,Harvard Medical School, Boston, Massachusetts
| | - Neekesh V. Dharia
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts.,Broad Institute of Harvard and MIT, Cambridge, Massachusetts.,Department of Pediatrics, Harvard Medical School, Boston, Massachusetts.,Boston Children's Hospital, Boston, Massachusetts
| | - Saif Alimohamed
- Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, North Carolina
| | - Brian J. Haas
- Broad Institute of Harvard and MIT, Cambridge, Massachusetts
| | - Kyuho Han
- Department of Genetics, Stanford University School of Medicine, Stanford, California
| | - Jihye Park
- Broad Institute of Harvard and MIT, Cambridge, Massachusetts.,Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Felix Dietlein
- Broad Institute of Harvard and MIT, Cambridge, Massachusetts.,Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Meng Xiao He
- Broad Institute of Harvard and MIT, Cambridge, Massachusetts.,Harvard Medical School, Boston, Massachusetts
| | - Alma Imamovic
- Broad Institute of Harvard and MIT, Cambridge, Massachusetts.,Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Clement Ma
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Michael C. Bassik
- Department of Genetics, Stanford University School of Medicine, Stanford, California.,Program in Cancer Biology, Stanford University School of Medicine, Stanford, California.,Program in Chemistry, Engineering and Medicine for Human Health (ChEM-H), Stanford University, Stanford, California
| | - Jesse S. Boehm
- Broad Institute of Harvard and MIT, Cambridge, Massachusetts
| | | | - Alexander Gusev
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts.,Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - David Liu
- Broad Institute of Harvard and MIT, Cambridge, Massachusetts.,Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Katherine A. Janeway
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts.,Department of Pediatrics, Harvard Medical School, Boston, Massachusetts.,Boston Children's Hospital, Boston, Massachusetts
| | | | - Kimberly Stegmaier
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts.,Broad Institute of Harvard and MIT, Cambridge, Massachusetts.,Department of Pediatrics, Harvard Medical School, Boston, Massachusetts.,Boston Children's Hospital, Boston, Massachusetts
| | - Eliezer M. Van Allen
- Broad Institute of Harvard and MIT, Cambridge, Massachusetts.,Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts.,Center for Cancer Genomics, Dana-Farber Cancer Institute, Boston, Massachusetts.,Corresponding Author: Eliezer M. Van Allen, Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215. Phone: 617-632-6656; E-mail:
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43
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Zhao J, Zhao R, Xiang C, Shao J, Guo L, Han Y. YAP1-MAML2 Fusion as a Diagnostic Biomarker for Metaplastic Thymoma. Front Oncol 2021; 11:692283. [PMID: 34354947 PMCID: PMC8329546 DOI: 10.3389/fonc.2021.692283] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2021] [Accepted: 07/07/2021] [Indexed: 01/11/2023] Open
Abstract
BACKGROUND Metaplastic thymoma is a very rare tumor with only a few case reports documented in literature. Hence, its molecular features have not been well explored. MATERIAL AND METHODS Seventeen specimens of metaplastic thymoma were sequenced and retrospectively analyzed by fluorescence in situ hybridization (FISH) and immunohistochemistry in the study. In addition, seven cases of micronodular thymoma with lymphoid stroma and nine cases of type A thymoma were also investigated. RESULTS Among these metaplastic thymomas, fifteen cases showed classical histological features, and two cases displayed characteristic micronodular-like growth patterns. DNA and RNA based next-generation sequencing identified and confirmed highly recurrent Yes Associated Protein 1 (YAP1) - Mastermind Like Transcriptional Coactivator 2 (MAML2) translocation (13/17, 76.5%) in metaplastic thymoma but not in micronodular thymoma with lymphoid stroma (0/7, 0%) and type A thymoma (0/9, 0%). In addition, six nonsense mutations were also detected in the metaplastic thymoma. FISH in microdissection specimens indicated that both epithelioid and spindle cell components harbored YAP1-MAML2 gene rearrangements. CONCLUSIONS Our study explored the genetic alterations in epithelioid and spindle cell components in metaplastic thymoma. Furthermore, YAP1-MAML2 gene rearrangements emerged as a potential diagnostic biomarker helpful for distinguishing metaplastic thymoma from type A and micronodular thymoma with lymphoid stroma.
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Affiliation(s)
| | | | | | | | | | - Yuchen Han
- Department of Pathology, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China
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44
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Khorani K, Schwaerzler J, Burkart S, Kurth I, Holzinger D, Flechtenmacher C, Plinkert PK, Zaoui K, Hess J. Establishment of a Plasticity-Associated Risk Model Based on a SOX2- and SOX9-Related Gene Set in Head and Neck Squamous Cell Carcinoma. Mol Cancer Res 2021; 19:1676-1687. [PMID: 34285085 DOI: 10.1158/1541-7786.mcr-21-0066] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2021] [Revised: 05/26/2021] [Accepted: 07/12/2021] [Indexed: 11/16/2022]
Abstract
Recent studies highlighted SOX2 and SOX9 as key determinants for cancer-cell plasticity and demonstrated that cisplatin-induced adaptation in oral squamous cell carcinoma (SCC) is acquired by an inverse regulation of both transcription factors. However, the association between SOX2/SOX9-related genetic programs with risk factors and genetic or epigenetic alterations in primary head and neck SCC (HNSCC), and their prognostic value is largely unknown.Here, we identified differentially-expressed genes (DEG) related to SOX2 and SOX9 transcription in The Cancer Genome Atlas (TCGA)-HNSC, which enable clustering of patients into groups with distinct clinical features and survival. A prognostic risk model was established by LASSO Cox regression based on expression patterns of DEGs in TCGA-HNSC (training cohort), and was confirmed in independent HNSCC validation cohorts as well as other cancer cohorts from TCGA. Differences in the mutational landscape among risk groups of TCGA-HNSC demonstrated an enrichment of truncating NSD1 mutations for the low-risk group and elucidated DNA methylation as modulator of SOX2 expression. Gene set variation analysis (GSVA) revealed differences in several oncogenic pathways among risk groups, including upregulation of gene sets related to oncogenic KRAS signaling for the high-risk group. Finally, in silico drug screen analysis revealed numerous compounds targeting EGFR signaling with significantly lower efficacy for cancer cell lines with a higher risk phenotype, but also indicated potential vulnerabilities. IMPLICATIONS: The established risk model identifies patients with primary HNSCC, but also other cancers at a higher risk for treatment failure, who might benefit from a therapy targeting SOX2/SOX9-related gene regulatory and signaling networks.
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Affiliation(s)
- Karam Khorani
- Department of Otorhinolaryngology, Head and Neck Tumors, Heidelberg University Hospital, Heidelberg, Germany
| | - Julia Schwaerzler
- Department of Otorhinolaryngology, Head and Neck Tumors, Heidelberg University Hospital, Heidelberg, Germany
| | - Sebastian Burkart
- Department of Otorhinolaryngology, Head and Neck Tumors, Heidelberg University Hospital, Heidelberg, Germany
| | - Ina Kurth
- Division of Radiooncology/Radiobiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Dana Holzinger
- Department of Otorhinolaryngology, Head and Neck Tumors, Heidelberg University Hospital, Heidelberg, Germany.,Division of Molecular Diagnostics of Oncogenic Infections, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Christa Flechtenmacher
- Institute of Pathology, Heidelberg University Hospital, and NCT Tissue Bank, National Center for Tumor Diseases (NCT), Heidelberg, Germany
| | - Peter K Plinkert
- Department of Otorhinolaryngology, Head and Neck Tumors, Heidelberg University Hospital, Heidelberg, Germany
| | - Karim Zaoui
- Department of Otorhinolaryngology, Head and Neck Tumors, Heidelberg University Hospital, Heidelberg, Germany
| | - Jochen Hess
- Department of Otorhinolaryngology, Head and Neck Tumors, Heidelberg University Hospital, Heidelberg, Germany. .,Research Group Molecular Mechanisms of Head and Neck Tumors, German Cancer Research Center (DKFZ), Heidelberg, Germany
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45
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Zhao Z, Li C, Tong F, Deng J, Huang G, Sang Y. Review of applications of CRISPR-Cas9 gene-editing technology in cancer research. Biol Proced Online 2021; 23:14. [PMID: 34261433 PMCID: PMC8281662 DOI: 10.1186/s12575-021-00151-x] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2021] [Accepted: 05/24/2021] [Indexed: 12/11/2022] Open
Abstract
Characterized by multiple complex mutations, including activation by oncogenes and inhibition by tumor suppressors, cancer is one of the leading causes of death. Application of CRISPR-Cas9 gene-editing technology in cancer research has aroused great interest, promoting the exploration of the molecular mechanism of cancer progression and development of precise therapy. CRISPR-Cas9 gene-editing technology provides a solid basis for identifying driver and passenger mutations in cancer genomes, which is of great value in genetic screening and for developing cancer models and treatments. This article reviews the current applications of CRISPR-Cas9 gene-editing technology in various cancer studies, the challenges faced, and the existing solutions, highlighting the potential of this technology for cancer treatment.
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Affiliation(s)
- Ziyi Zhao
- The Third Affiliated Hospital of Nanchang University, Nanchang, 330008, China
| | - Chenxi Li
- The Third Affiliated Hospital of Nanchang University, Nanchang, 330008, China
| | - Fei Tong
- Orthodontic Department of Affiliated Stomatological Hospital of Nanchang University, Nanchang, 330008, China
| | - Jingkuang Deng
- The Third Affiliated Hospital of Nanchang University, Nanchang, 330008, China
| | - Guofu Huang
- The Third Affiliated Hospital of Nanchang University, Nanchang, 330008, China.
| | - Yi Sang
- The Third Affiliated Hospital of Nanchang University, Nanchang, 330008, China.
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46
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Najgebauer H, Yang M, Francies HE, Pacini C, Stronach EA, Garnett MJ, Saez-Rodriguez J, Iorio F. CELLector: Genomics-Guided Selection of Cancer In Vitro Models. Cell Syst 2021; 10:424-432.e6. [PMID: 32437684 DOI: 10.1016/j.cels.2020.04.007] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2018] [Revised: 03/05/2020] [Accepted: 04/21/2020] [Indexed: 12/20/2022]
Abstract
Selecting appropriate cancer models is a key prerequisite for maximizing translational potential and clinical relevance of in vitro oncology studies. We developed CELLector: an R package and R Shiny application allowing researchers to select the most relevant cancer cell lines in a patient-genomic-guided fashion. CELLector leverages tumor genomics to identify recurrent subtypes with associated genomic signatures. It then evaluates these signatures in cancer cell lines to prioritize their selection. This enables users to choose appropriate in vitro models for inclusion or exclusion in retrospective analyses and future studies. Moreover, this allows bridging outcomes from cancer cell line screens to precisely defined sub-cohorts of primary tumors. Here, we demonstrate the usefulness and applicability of CELLector, showing how it can aid prioritization of in vitro models for future development and unveil patient-derived multivariate prognostic and therapeutic markers. CELLector is freely available at https://ot-cellector.shinyapps.io/CELLector_App/ (code at https://github.com/francescojm/CELLector and https://github.com/francescojm/CELLector_App).
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Affiliation(s)
- Hanna Najgebauer
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK; European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Cambridge CB10 1SA, UK; Wellcome Trust Sanger Institute, Wellcome Genome Campus, Cambridge CB10 1SA, UK
| | - Mi Yang
- Faculty of Medicine, Joint Research Centre for Computational Biomedicine, RWTH Aachen University, Aachen 52057, Germany
| | - Hayley E Francies
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Cambridge CB10 1SA, UK
| | - Clare Pacini
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK; Wellcome Trust Sanger Institute, Wellcome Genome Campus, Cambridge CB10 1SA, UK
| | - Euan A Stronach
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK; Functional Genomics GlaxoSmithKline, Stevenage, UK
| | - Mathew J Garnett
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK; Wellcome Trust Sanger Institute, Wellcome Genome Campus, Cambridge CB10 1SA, UK
| | - Julio Saez-Rodriguez
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Cambridge CB10 1SA, UK; Faculty of Medicine, Joint Research Centre for Computational Biomedicine, RWTH Aachen University, Aachen 52057, Germany; Institute for Computational Biomedicine, Faculty of Medicine, BIOQUANT-Center, Heidelberg University, Heidelberg, Germany
| | - Francesco Iorio
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK; Wellcome Trust Sanger Institute, Wellcome Genome Campus, Cambridge CB10 1SA, UK; Human Technopole, 20157, Milano, Italy.
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47
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Chen BR, Deshpande A, Barbosa K, Kleppe M, Lei X, Yeddula N, Vela PS, Campos AR, Wechsler-Reya RJ, Bagchi A, Meshinchi S, Eaves C, Jeremias I, Haferlach T, Frank DA, Ronai Z, Chanda S, Armstrong SA, Adams PD, Levine RL, Deshpande AJ. A JAK/STAT-mediated inflammatory signaling cascade drives oncogenesis in AF10-rearranged AML. Blood 2021; 137:3403-3415. [PMID: 33690798 PMCID: PMC8212510 DOI: 10.1182/blood.2020009023] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2020] [Accepted: 02/11/2021] [Indexed: 12/18/2022] Open
Abstract
Leukemias bearing fusions of the AF10/MLLT10 gene are associated with poor prognosis, and therapies targeting these fusion proteins (FPs) are lacking. To understand mechanisms underlying AF10 fusion-mediated leukemogenesis, we generated inducible mouse models of acute myeloid leukemia (AML) driven by the most common AF10 FPs, PICALM/CALM-AF10 and KMT2A/MLL-AF10, and performed comprehensive characterization of the disease using transcriptomic, epigenomic, proteomic, and functional genomic approaches. Our studies provide a detailed map of gene networks and protein interactors associated with key AF10 fusions involved in leukemia. Specifically, we report that AF10 fusions activate a cascade of JAK/STAT-mediated inflammatory signaling through direct recruitment of JAK1 kinase. Inhibition of the JAK/STAT signaling by genetic Jak1 deletion or through pharmacological JAK/STAT inhibition elicited potent antioncogenic effects in mouse and human models of AF10 fusion AML. Collectively, our study identifies JAK1 as a tractable therapeutic target in AF10-rearranged leukemias.
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Affiliation(s)
- Bo-Rui Chen
- Tumor Initiation and Maintenance Program, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA
| | - Anagha Deshpande
- Tumor Initiation and Maintenance Program, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA
| | - Karina Barbosa
- Tumor Initiation and Maintenance Program, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA
| | - Maria Kleppe
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Xue Lei
- Tumor Initiation and Maintenance Program, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA
| | - Narayana Yeddula
- Immunity and Pathogenesis Program, Infectious and Inflammatory Disease Center and
| | - Pablo Sánchez Vela
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Alexandre Rosa Campos
- Proteomics Facility, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA
| | - Robert J Wechsler-Reya
- Tumor Initiation and Maintenance Program, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA
| | - Anindya Bagchi
- Tumor Initiation and Maintenance Program, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA
| | - Soheil Meshinchi
- Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA
| | - Connie Eaves
- Terry Fox Laboratory, British Columbia Cancer Agency, Vancouver, BC, Canada
| | - Irmela Jeremias
- Research Unit Apoptosis in Hematopoietic Stem Cells, Helmholtz Center Munich, German Center for Environmental Health, Munich, Germany
| | | | | | - Ze'ev Ronai
- Tumor Initiation and Maintenance Program, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA
| | - Sumit Chanda
- Immunity and Pathogenesis Program, Infectious and Inflammatory Disease Center and
| | - Scott A Armstrong
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Boston, MA
| | - Peter D Adams
- Tumor Initiation and Maintenance Program, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA
| | - Ross L Levine
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Aniruddha J Deshpande
- Tumor Initiation and Maintenance Program, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA
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48
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Durinikova E, Buzo K, Arena S. Preclinical models as patients' avatars for precision medicine in colorectal cancer: past and future challenges. J Exp Clin Cancer Res 2021; 40:185. [PMID: 34090508 PMCID: PMC8178911 DOI: 10.1186/s13046-021-01981-z] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2021] [Accepted: 05/13/2021] [Indexed: 02/06/2023] Open
Abstract
Colorectal cancer (CRC) is a complex and heterogeneous disease, characterized by dismal prognosis and low survival rate in the advanced (metastatic) stage. During the last decade, the establishment of novel preclinical models, leading to the generation of translational discovery and validation platforms, has opened up a new scenario for the clinical practice of CRC patients. To bridge the results developed at the bench with the medical decision process, the ideal model should be easily scalable, reliable to predict treatment responses, and flexibly adapted for various applications in the research. As such, the improved benefit of novel therapies being tested initially on valuable and reproducible preclinical models would lie in personalized treatment recommendations based on the biology and genomics of the patient's tumor with the overall aim to avoid overtreatment and unnecessary toxicity. In this review, we summarize different in vitro and in vivo models, which proved efficacy in detection of novel CRC culprits and shed light into the biology and therapy of this complex disease. Even though cell lines and patient-derived xenografts remain the mainstay of colorectal cancer research, the field has been confidently shifting to the use of organoids as the most relevant preclinical model. Prioritization of organoids is supported by increasing body of evidence that these represent excellent tools worth further therapeutic explorations. In addition, novel preclinical models such as zebrafish avatars are emerging as useful tools for pharmacological interrogation. Finally, all available models represent complementary tools that can be utilized for precision medicine applications.
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Affiliation(s)
- Erika Durinikova
- Candiolo Cancer Institute, FPO - IRCCS, Strada Provinciale 142, Km 3.95, 10060, Candiolo, TO, Italy
| | - Kristi Buzo
- Candiolo Cancer Institute, FPO - IRCCS, Strada Provinciale 142, Km 3.95, 10060, Candiolo, TO, Italy
| | - Sabrina Arena
- Candiolo Cancer Institute, FPO - IRCCS, Strada Provinciale 142, Km 3.95, 10060, Candiolo, TO, Italy.
- Department of Oncology, University of Torino, Strada Provinciale 142, Km 3.95, 10060, Candiolo, TO, Italy.
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49
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He Z, Li R, Jiang H. Mutations and Copy Number Abnormalities of Hippo Pathway Components in Human Cancers. Front Cell Dev Biol 2021; 9:661718. [PMID: 34150758 PMCID: PMC8209335 DOI: 10.3389/fcell.2021.661718] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2021] [Accepted: 04/12/2021] [Indexed: 12/13/2022] Open
Abstract
The Hippo pathway is highly conserved from Drosophila to mammals. As a key regulator of cell proliferation, the Hippo pathway controls tissue homeostasis and has a major impact on tumorigenesis. The originally defined core components of the Hippo pathway in mammals include STK3/4, LATS1/2, YAP1/TAZ, TEAD, VGLL4, and NF2. However, for most of these genes, mutations and copy number variations are relatively uncommon in human cancer. Several other recently identified upstream and downstream regulators of Hippo signaling, including FAT1, SHANK2, Gq/11, and SWI/SNF complex, are more commonly dysregulated in human cancer at the genomic level. This review will discuss major genomic events in human cancer that enable cancer cells to escape the tumor-suppressive effects of Hippo signaling.
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Affiliation(s)
- Zhengjin He
- State Key Laboratory of Cell Biology, CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, China
| | - Ruihan Li
- State Key Laboratory of Cell Biology, CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, China
| | - Hai Jiang
- State Key Laboratory of Cell Biology, CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, China
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50
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Cai L, Liu H, Minna JD, DeBerardinis RJ, Xiao G, Xie Y. Assessing Consistency Across Functional Screening Datasets in Cancer Cells. Bioinformatics 2021; 37:4540-4547. [PMID: 34081116 PMCID: PMC8652113 DOI: 10.1093/bioinformatics/btab423] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Revised: 04/16/2021] [Accepted: 06/02/2021] [Indexed: 12/26/2022] Open
Abstract
Motivation Many high-throughput screening studies have been carried out in cancer cell lines to identify therapeutic agents and targets. Existing consistency assessment studies only examined two datasets at a time, with conclusions based on a subset of carefully selected features rather than considering global consistency of all the data. However, poor concordance can still be observed for a large part of the data even when selected features are highly consistent. Results In this study, we assembled nine compound screening datasets and three functional genomics datasets. We derived direct measures of consistency as well as indirect measures of consistency based on association between functional data and copy number-adjusted gene expression data. These results have been integrated into a web application—the Functional Data Consistency Explorer (FDCE), to allow users to make queries and generate interactive visualizations so that functional data consistency can be assessed for individual features of interest. Availability and implementation The FDCE web tool and we have developed and the functional data consistency measures we have generated are available at https://lccl.shinyapps.io/FDCE/. Supplementary information Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Ling Cai
- Quantitative Biomedical Research Center, Department of Population and Data Sciences, UT Southwestern Medical Center, Dallas, TX 75390, USA.,Children's Research Institute, UT Southwestern Medical Center, Dallas, TX 75390, USA
| | - Hongyu Liu
- Quantitative Biomedical Research Center, Department of Population and Data Sciences, UT Southwestern Medical Center, Dallas, TX 75390, USA
| | - John D Minna
- Children's Research Institute, UT Southwestern Medical Center, Dallas, TX 75390, USA.,Hamon Center for Therapeutic Oncology Research, UT Southwestern Medical Center, Dallas, Dallas, TX 75390, USA.,Department of Pharmacology, UT Southwestern Medical Center, Dallas, TX 75390, USA.,Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Ralph J DeBerardinis
- Children's Research Institute, UT Southwestern Medical Center, Dallas, TX 75390, USA.,Howard Hughes Medical Institute, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Guanghua Xiao
- Quantitative Biomedical Research Center, Department of Population and Data Sciences, UT Southwestern Medical Center, Dallas, TX 75390, USA.,Children's Research Institute, UT Southwestern Medical Center, Dallas, TX 75390, USA.,Department of Bioinformatics, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Yang Xie
- Quantitative Biomedical Research Center, Department of Population and Data Sciences, UT Southwestern Medical Center, Dallas, TX 75390, USA.,Children's Research Institute, UT Southwestern Medical Center, Dallas, TX 75390, USA.,Department of Bioinformatics, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
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