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Lilja J, Kaivola J, Conway JRW, Vuorio J, Parkkola H, Roivas P, Dibus M, Chastney MR, Varila T, Jacquemet G, Peuhu E, Wang E, Pentikäinen U, Martinez D Posada I, Hamidi H, Najumudeen AK, Sansom OJ, Barsukov IL, Abankwa D, Vattulainen I, Salmi M, Ivaska J. SHANK3 depletion leads to ERK signalling overdose and cell death in KRAS-mutant cancers. Nat Commun 2024; 15:8002. [PMID: 39266533 PMCID: PMC11393128 DOI: 10.1038/s41467-024-52326-1] [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: 12/09/2022] [Accepted: 09/03/2024] [Indexed: 09/14/2024] Open
Abstract
The KRAS oncogene drives many common and highly fatal malignancies. These include pancreatic, lung, and colorectal cancer, where various activating KRAS mutations have made the development of KRAS inhibitors difficult. Here we identify the scaffold protein SH3 and multiple ankyrin repeat domain 3 (SHANK3) as a RAS interactor that binds active KRAS, including mutant forms, competes with RAF and limits oncogenic KRAS downstream signalling, maintaining mitogen-activated protein kinase/extracellular signal-regulated kinase (MAPK/ERK) activity at an optimal level. SHANK3 depletion breaches this threshold, triggering MAPK/ERK signalling hyperactivation and MAPK/ERK-dependent cell death in KRAS-mutant cancers. Targeting this vulnerability through RNA interference or nanobody-mediated disruption of the SHANK3-KRAS interaction constrains tumour growth in vivo in female mice. Thus, inhibition of SHANK3-KRAS interaction represents an alternative strategy for selective killing of KRAS-mutant cancer cells through excessive signalling.
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Affiliation(s)
- Johanna Lilja
- Turku Bioscience Centre, University of Turku, FI-20520, Turku, Finland
| | - Jasmin Kaivola
- Turku Bioscience Centre, University of Turku, FI-20520, Turku, Finland
| | - James R W Conway
- Turku Bioscience Centre, University of Turku, FI-20520, Turku, Finland
| | - Joni Vuorio
- Department of Physics, University of Helsinki, Helsinki, Finland
| | - Hanna Parkkola
- Turku Bioscience Centre, University of Turku, FI-20520, Turku, Finland
| | - Pekka Roivas
- Turku Bioscience Centre, University of Turku, FI-20520, Turku, Finland
- Institute of Biomedicine, University of Turku, FI-20520, Turku, Finland
| | - Michal Dibus
- Turku Bioscience Centre, University of Turku, FI-20520, Turku, Finland
| | - Megan R Chastney
- Turku Bioscience Centre, University of Turku, FI-20520, Turku, Finland
| | - Taru Varila
- Turku Bioscience Centre, University of Turku, FI-20520, Turku, Finland
| | - Guillaume Jacquemet
- Turku Bioscience Centre, University of Turku, FI-20520, Turku, Finland
- Faculty of Science and Engineering, Cell Biology, Åbo Akademi University, FI-20520, Turku, Finland
- Turku Bioimaging, University of Turku and Åbo Akademi University, FI-20520, Turku, Finland
- InFLAMES Research Flagship Center, Åbo Akademi University, FI-20520, Turku, Finland
| | - Emilia Peuhu
- Turku Bioscience Centre, University of Turku, FI-20520, Turku, Finland
- Institute of Biomedicine, Cancer Research Laboratory FICAN West, University of Turku, FI-20520, Turku, Finland
| | - Emily Wang
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK
| | - Ulla Pentikäinen
- Turku Bioscience Centre, University of Turku, FI-20520, Turku, Finland
- Institute of Biomedicine, University of Turku, FI-20520, Turku, Finland
| | | | - Hellyeh Hamidi
- Turku Bioscience Centre, University of Turku, FI-20520, Turku, Finland
| | - Arafath K Najumudeen
- Institute of Biotechnology, HiLIFE, University of Helsinki, Helsinki, Finland
- CRUK Scotland Institute, Garscube Estate, Switchback Road, Glasgow, G61 1BD, UK
| | - Owen J Sansom
- CRUK Scotland Institute, Garscube Estate, Switchback Road, Glasgow, G61 1BD, UK
- Institute of Cancer Sciences, University of Glasgow, Garscube Estate, Switchback Road, Glasgow, G61 1QH, UK
| | - Igor L Barsukov
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK
| | - Daniel Abankwa
- Turku Bioscience Centre, University of Turku, FI-20520, Turku, Finland
- Department of Life Sciences and Medicine, University of Luxembourg, 4365, Esch- sur-Alzette, Luxembourg
| | - Ilpo Vattulainen
- Department of Physics, University of Helsinki, Helsinki, Finland
| | - Marko Salmi
- Institute of Biomedicine, University of Turku, FI-20520, Turku, Finland
- MediCity Research Laboratory, University of Turku, FI-20520, Turku, Finland
- InFLAMES Research Flagship Center, University of Turku, FI-20520, Turku, Finland
| | - Johanna Ivaska
- Turku Bioscience Centre, University of Turku, FI-20520, Turku, Finland.
- InFLAMES Research Flagship Center, University of Turku, FI-20520, Turku, Finland.
- Department of Life Technologies, University of Turku, Turku, Finland.
- Foundation for the Finnish Cancer Institute, Tukholmankatu 8, FI-00014, Helsinki, Finland.
- Western Finnish Cancer Center, University of Turku, Turku, FI-20520, Finland.
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Chou J, Anvar NE, Elghaish R, Chen J, Hart T. Optimal methods for analyzing targeted pairwise knockout screens. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.08.19.608665. [PMID: 39229040 PMCID: PMC11370406 DOI: 10.1101/2024.08.19.608665] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/05/2024]
Abstract
Background Synthetic lethality offers a promising strategy for cancer treatment by targeting genetic vulnerabilities unique to tumor cells, leading to selective tumor cell death. However, single-gene knockout screens often miss functional redundancy due to paralog genes. Multiplex CRISPR systems, including various Cas9 and Cas12a platforms, have been developed to assay genetic interactions, yet no systematic comparison of method to identify synthetic lethality from CRISPR screens has been conducted. Results We evaluated data from four in4mer CRISPR/Cas12a screens in cancer cell lines, using three bioinformatic approaches to identify synthetic lethal interactions: delta log fold change (dLFC), Z-transformed dLFC (ZdLFC), and rescaled dLFC (RdLFC). Both ZdLFC and RdLFC provided more consistent identification of synthetic lethal pairs across cell lines compared to the unscaled dLFC method. Conclusions The ZdLFC method offers a robust framework for scoring synthetic lethal interactions from paralog screens, providing consistent results across different cell lines without requiring a training set of known positive interactors.
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Affiliation(s)
- Juihsuan Chou
- Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas
- The UT Health/MD Anderson Graduate School of Biological Sciences, Houston, Texas
| | - Nazanin Esmaeili Anvar
- Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Reem Elghaish
- Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas
- The UT Health/MD Anderson Graduate School of Biological Sciences, Houston, Texas
| | - Junjie Chen
- Department of Experimental Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Traver Hart
- Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas
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Mellis IA, Melzer ME, Bodkin N, Goyal Y. Prevalence of and gene regulatory constraints on transcriptional adaptation in single cells. Genome Biol 2024; 25:217. [PMID: 39135102 PMCID: PMC11320884 DOI: 10.1186/s13059-024-03351-2] [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: 12/13/2023] [Accepted: 07/25/2024] [Indexed: 08/15/2024] Open
Abstract
BACKGROUND Cells and tissues have a remarkable ability to adapt to genetic perturbations via a variety of molecular mechanisms. Nonsense-induced transcriptional compensation, a form of transcriptional adaptation, has recently emerged as one such mechanism, in which nonsense mutations in a gene trigger upregulation of related genes, possibly conferring robustness at cellular and organismal levels. However, beyond a handful of developmental contexts and curated sets of genes, no comprehensive genome-wide investigation of this behavior has been undertaken for mammalian cell types and conditions. How the regulatory-level effects of inherently stochastic compensatory gene networks contribute to phenotypic penetrance in single cells remains unclear. RESULTS We analyze existing bulk and single-cell transcriptomic datasets to uncover the prevalence of transcriptional adaptation in mammalian systems across diverse contexts and cell types. We perform regulon gene expression analyses of transcription factor target sets in both bulk and pooled single-cell genetic perturbation datasets. Our results reveal greater robustness in expression of regulons of transcription factors exhibiting transcriptional adaptation compared to those of transcription factors that do not. Stochastic mathematical modeling of minimal compensatory gene networks qualitatively recapitulates several aspects of transcriptional adaptation, including paralog upregulation and robustness to mutation. Combined with machine learning analysis of network features of interest, our framework offers potential explanations for which regulatory steps are most important for transcriptional adaptation. CONCLUSIONS Our integrative approach identifies several putative hits-genes demonstrating possible transcriptional adaptation-to follow-up on experimentally and provides a formal quantitative framework to test and refine models of transcriptional adaptation.
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Affiliation(s)
- Ian A Mellis
- Department of Pathology and Cell Biology, Columbia University Vagelos College of Physicians and Surgeons, New York, NY, USA.
- Aaron Diamond AIDS Research Center, Columbia University Vagelos College of Physicians and Surgeons, New York, NY, USA.
| | - Madeline E Melzer
- Department of Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
- Center for Synthetic Biology, Northwestern University, Chicago, IL, USA
- Robert H. Lurie Comprehensive Cancer Center, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Nicholas Bodkin
- Department of Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
- Center for Synthetic Biology, Northwestern University, Chicago, IL, USA
- Robert H. Lurie Comprehensive Cancer Center, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Yogesh Goyal
- Department of Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
- Center for Synthetic Biology, Northwestern University, Chicago, IL, USA.
- Robert H. Lurie Comprehensive Cancer Center, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
- CZ Biohub Chicago, LLC, Chicago, IL, USA.
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Wang X, Chi W, Ma Y, Zhang Q, Xue J, Shao ZM, Xiu B, Wu J, Chi Y. DUSP4 enhances therapeutic sensitivity in HER2-positive breast cancer by inhibiting the G6PD pathway and ROS metabolism by interacting with ALDOB. Transl Oncol 2024; 46:102016. [PMID: 38843658 PMCID: PMC11214528 DOI: 10.1016/j.tranon.2024.102016] [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: 01/30/2024] [Revised: 05/15/2024] [Accepted: 05/27/2024] [Indexed: 06/19/2024] Open
Abstract
BACKGROUND Breast cancer (BC) poses a global threat, with HER2-positive BC being a particularly hazardous subtype. Despite the promise shown by neoadjuvant therapy (NAT) in improving prognosis, resistance in HER2-positive BC persists despite emerging targeted therapies. The objective of this study is to identify markers that promote therapeutic sensitivity and unravel the underlying mechanisms. METHODS We conducted an analysis of 86 HER2-positive BC biopsy samples pre-NAT using RNA-seq. Validation was carried out using TCGA, Kaplan‒Meier Plotter, and Oncomine databases. Phenotype verification utilized IC50 assays, and prognostic validation involved IHC on tissue microarrays. RNA-seq was performed on wild-type/DUSP4-KO cells, while RT‒qPCR assessed ROS pathway regulation. Mechanistic insights were obtained through IP and MS assays. RESULTS Our findings reveal that DUSP4 enhances therapeutic efficacy in HER2-positive BC by inhibiting the ROS pathway. Elevated DUSP4 levels correlate with increased sensitivity to HER2-targeted therapies and improved clinical outcomes. DUSP4 independently predicts disease-free survival (DFS) and overall survival (OS) in HER2-positive BC. Moreover, DUSP4 hinders G6PD activity via ALDOB dephosphorylation, with a noteworthy association with heightened ROS levels. CONCLUSIONS In summary, our study unveils a metabolic reprogramming paradigm in BC, highlighting DUSP4's role in enhancing therapeutic sensitivity in HER2-positive BC cells. DUSP4 interacts with ALDOB, inhibiting G6PD activity and the ROS pathway, establishing it as an independent prognostic predictor for HER2-positive BC patients.
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Affiliation(s)
- Xuliren Wang
- Department of Breast Surgery, Key Laboratory of Breast Cancer in Shanghai, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Weiru Chi
- Department of Breast Surgery, Key Laboratory of Breast Cancer in Shanghai, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Yuwei Ma
- Department of Breast Surgery, Key Laboratory of Breast Cancer in Shanghai, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Qi Zhang
- Department of Breast Surgery, Key Laboratory of Breast Cancer in Shanghai, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Jingyan Xue
- Department of Breast Surgery, Key Laboratory of Breast Cancer in Shanghai, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Zhi-Ming Shao
- Department of Breast Surgery, Key Laboratory of Breast Cancer in Shanghai, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Bingqiu Xiu
- Department of Breast Surgery, Key Laboratory of Breast Cancer in Shanghai, Fudan University Shanghai Cancer Center, Shanghai, China.
| | - Jiong Wu
- Department of Breast Surgery, Key Laboratory of Breast Cancer in Shanghai, Fudan University Shanghai Cancer Center, Shanghai, China.
| | - Yayun Chi
- Department of Breast Surgery, Key Laboratory of Breast Cancer in Shanghai, Fudan University Shanghai Cancer Center, Shanghai, China.
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5
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Pei W, Yin W, Yu T, Zhang X, Zhang Q, Yang X, Shi C, Shen W, Liu G. Dual-Specificity Phosphatase 4 Promotes Malignant Features in Colorectal Cancer Through Cyclic-AMP Response Element Binding Protein/Protein Kinase CAMP-Activated Catalytic Subunit Beta Activation. Dig Dis Sci 2024; 69:2856-2874. [PMID: 38824257 DOI: 10.1007/s10620-024-08481-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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Accepted: 05/06/2024] [Indexed: 06/03/2024]
Abstract
INTRODUCTION Previous studies have demonstrated that Dual-specificity phosphatase 4 (DUSP4) plays an important role in the progression of different tumor types. However, the role and mechanism of DUSP4 in colorectal cancer (CRC) remain unclear. AIMS We investigate the role and mechanisms of DUSP4 in CRC. METHODS Immunohistochemistry was used to investigate DUSP4 expression in CRC tissues. Cell proliferation, apoptosis and migration assays were used to validate DUSP4 function in vitro and in vivo. RNA-sequence assay was used to identify the target genes of DUSP4. Human phosphokinase array and inhibitor assays were used to explore the downstream signaling of DUSP4. RESULTS DUSP4 expression was upregulated in CRC tissues relative to normal colorectal tissues, and DUSP4 expression showed a significant positive correlation with CRC stage. Consistently, we found that DUSP4 was highly expressed in colorectal cancer cells compared to normal cells. DUSP4 knockdown inhibits CRC cell proliferation, migration and promotes apoptosis. Furthermore, the ectopic expression of DUSP4 enhanced CRC cell proliferation, migration and diminished apoptosis in vitro and in vivo. Human phosphokinase array data showed that ectopic expression of DUSP4 promotes CREB activation. RNA-sequencing data showed that PRKACB acts as a downstream target gene of DUSP4/CREB and enhances CREB activation through PKA/cAMP signaling. In addition, xenograft model results demonstrated that DUSP4 promotes colorectal tumor progression via PRKACB/CREB activation in vivo. CONCLUSION These findings suggest that DUSP4 promotes CRC progression. Therefore, it may be a promising therapeutic target for CRC.
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Affiliation(s)
- Wenju Pei
- Department of General Surgery, Tianjin Medical University General Hospital, Tianjin, 300052, China
- Department of General Surgery, Affiliated Hospital of Jining Medical University, Jining Medical University, Jining, 272067, China
- Key Laboratory of Precision Oncology in Universities of Shandong, Institute of Precision Medicine, Jining Medical University, Jining, 272067, China
| | - Wanbin Yin
- Department of General Surgery, Tianjin Medical University General Hospital, Tianjin, 300052, China
- Department of General Surgery, Affiliated Hospital of Jining Medical University, Jining Medical University, Jining, 272067, China
| | - Tao Yu
- Department of Medical Oncology, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Xiaoyuan Zhang
- Key Laboratory of Precision Oncology in Universities of Shandong, Institute of Precision Medicine, Jining Medical University, Jining, 272067, China
| | - Qi Zhang
- Department of General Surgery, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Xiaowen Yang
- Key Laboratory of Precision Oncology in Universities of Shandong, Institute of Precision Medicine, Jining Medical University, Jining, 272067, China
| | - Chunlei Shi
- Department of General Surgery, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Wenzhi Shen
- Key Laboratory of Precision Oncology in Universities of Shandong, Institute of Precision Medicine, Jining Medical University, Jining, 272067, China.
| | - Gang Liu
- Department of General Surgery, Tianjin Medical University General Hospital, Tianjin, 300052, China
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6
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Wu MJ, Kondo H, Kammula AV, Shi L, Xiao Y, Dhiab S, Xu Q, Slater CJ, Avila OI, Merritt J, Kato H, Kattel P, Sussman J, Gritti I, Eccleston J, Sun Y, Cho HM, Olander K, Katsuda T, Shi DD, Savani MR, Smith BC, Cleary JM, Mostoslavsky R, Vijay V, Kitagawa Y, Wakimoto H, Jenkins RW, Yates KB, Paik J, Tassinari A, Saatcioglu DH, Tron AE, Haas W, Cahill D, McBrayer SK, Manguso RT, Bardeesy N. Mutant IDH1 inhibition induces dsDNA sensing to activate tumor immunity. Science 2024; 385:eadl6173. [PMID: 38991060 DOI: 10.1126/science.adl6173] [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: 11/17/2023] [Accepted: 05/09/2024] [Indexed: 07/13/2024]
Abstract
Isocitrate dehydrogenase 1 (IDH1) is the most commonly mutated metabolic gene across human cancers. Mutant IDH1 (mIDH1) generates the oncometabolite (R)-2-hydroxyglutarate, disrupting enzymes involved in epigenetics and other processes. A hallmark of IDH1-mutant solid tumors is T cell exclusion, whereas mIDH1 inhibition in preclinical models restores antitumor immunity. Here, we define a cell-autonomous mechanism of mIDH1-driven immune evasion. IDH1-mutant solid tumors show selective hypermethylation and silencing of the cytoplasmic double-stranded DNA (dsDNA) sensor CGAS, compromising innate immune signaling. mIDH1 inhibition restores DNA demethylation, derepressing CGAS and transposable element (TE) subclasses. dsDNA produced by TE-reverse transcriptase (TE-RT) activates cGAS, triggering viral mimicry and stimulating antitumor immunity. In summary, we demonstrate that mIDH1 epigenetically suppresses innate immunity and link endogenous RT activity to the mechanism of action of a US Food and Drug Administration-approved oncology drug.
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Affiliation(s)
- Meng-Ju Wu
- Krantz Family Center for Cancer Research, Massachusetts General Hospital, Boston MA, USA
- Center for Regenerative Medicine, Massachusetts General Hospital, Boston MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA
| | - Hiroshi Kondo
- Krantz Family Center for Cancer Research, Massachusetts General Hospital, Boston MA, USA
- Center for Regenerative Medicine, Massachusetts General Hospital, Boston MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA
| | - Ashwin V Kammula
- Krantz Family Center for Cancer Research, Massachusetts General Hospital, Boston MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA
| | - Lei Shi
- Krantz Family Center for Cancer Research, Massachusetts General Hospital, Boston MA, USA
- Center for Regenerative Medicine, Massachusetts General Hospital, Boston MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA
| | - Yi Xiao
- Children's Medical Center Research Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Sofiene Dhiab
- Krantz Family Center for Cancer Research, Massachusetts General Hospital, Boston MA, USA
- Center for Regenerative Medicine, Massachusetts General Hospital, Boston MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA
| | - Qin Xu
- Krantz Family Center for Cancer Research, Massachusetts General Hospital, Boston MA, USA
- Center for Regenerative Medicine, Massachusetts General Hospital, Boston MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA
| | - Chloe J Slater
- Krantz Family Center for Cancer Research, Massachusetts General Hospital, Boston MA, USA
- Center for Regenerative Medicine, Massachusetts General Hospital, Boston MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Universite Paris-Saclay, Institut Gustave Roussy, INSERM U1015, Villejuif, France
- Servier Pharmaceuticals LLC, Boston, MA, USA
| | - Omar I Avila
- Krantz Family Center for Cancer Research, Massachusetts General Hospital, Boston MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA
| | - Joshua Merritt
- Krantz Family Center for Cancer Research, Massachusetts General Hospital, Boston MA, USA
- Center for Regenerative Medicine, Massachusetts General Hospital, Boston MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA
| | - Hiroyuki Kato
- Krantz Family Center for Cancer Research, Massachusetts General Hospital, Boston MA, USA
- Center for Regenerative Medicine, Massachusetts General Hospital, Boston MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA
| | - Prabhat Kattel
- Krantz Family Center for Cancer Research, Massachusetts General Hospital, Boston MA, USA
- Center for Regenerative Medicine, Massachusetts General Hospital, Boston MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA
| | - Jonathan Sussman
- Abramson Family Cancer Research Institute and Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Graduate Group in Genomics and Computational Biology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Ilaria Gritti
- Krantz Family Center for Cancer Research, Massachusetts General Hospital, Boston MA, USA
- Center for Regenerative Medicine, Massachusetts General Hospital, Boston MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA
| | - Jason Eccleston
- Abramson Family Cancer Research Institute and Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Yi Sun
- Krantz Family Center for Cancer Research, Massachusetts General Hospital, Boston MA, USA
| | - Hyo Min Cho
- Krantz Family Center for Cancer Research, Massachusetts General Hospital, Boston MA, USA
- Center for Regenerative Medicine, Massachusetts General Hospital, Boston MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA
| | - Kira Olander
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA
| | - Takeshi Katsuda
- Abramson Family Cancer Research Institute and Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Diana D Shi
- Children's Medical Center Research Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Department of Radiation Oncology, Dana-Farber/Brigham and Women's Cancer Center, Harvard Medical School, Boston, MA, USA
| | - Milan R Savani
- Children's Medical Center Research Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Medical Scientist Training Program, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Bailey C Smith
- Children's Medical Center Research Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | | | - Raul Mostoslavsky
- Krantz Family Center for Cancer Research, Massachusetts General Hospital, Boston MA, USA
- Center for Regenerative Medicine, Massachusetts General Hospital, Boston MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA
| | - Vindhya Vijay
- Krantz Family Center for Cancer Research, Massachusetts General Hospital, Boston MA, USA
- Center for Regenerative Medicine, Massachusetts General Hospital, Boston MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA
| | - Yosuke Kitagawa
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Hiroaki Wakimoto
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Russell W Jenkins
- Krantz Family Center for Cancer Research, Massachusetts General Hospital, Boston MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA
- Laboratory of Systems Pharmacology, Harvard Program in Therapeutic Sciences, Harvard Medical School, Boston, MA, USA
| | - Kathleen B Yates
- Krantz Family Center for Cancer Research, Massachusetts General Hospital, Boston MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA
| | - Jihye Paik
- Department of Pathology and Laboratory Medicine, Sandra and Edward Meyer Cancer Center, Weill Medical College of Cornell University, New York, NY, USA
| | | | | | | | - Wilhelm Haas
- Krantz Family Center for Cancer Research, Massachusetts General Hospital, Boston MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Daniel Cahill
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Samuel K McBrayer
- Children's Medical Center Research Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Department of Pediatrics, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Robert T Manguso
- Krantz Family Center for Cancer Research, Massachusetts General Hospital, Boston MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA
| | - Nabeel Bardeesy
- Krantz Family Center for Cancer Research, Massachusetts General Hospital, Boston MA, USA
- Center for Regenerative Medicine, Massachusetts General Hospital, Boston MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA
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7
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Dong C, Zhang F, He E, Ren P, Verma N, Zhu X, Feng D, Zhao H, Chen S. Sensitive detection of synthetic response to cancer immunotherapy driven by gene paralog pairs. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.02.601809. [PMID: 39005443 PMCID: PMC11245041 DOI: 10.1101/2024.07.02.601809] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/16/2024]
Abstract
Emerging immunotherapies such as immune checkpoint blockade (ICB) and chimeric antigen receptor T-cell (CAR-T) therapy have revolutionized cancer treatment and have improved the survival of patients with multiple cancer types. Despite this success many patients are unresponsive to these treatments or relapse following treatment. CRISPR activation and knockout (KO) screens have been used to identify novel single gene targets that can enhance effector T cell function and promote immune cell targeting and eradication of tumors. However, cancer cells often employ multiple genes to promote an immunosuppressive pathway and thus modulating individual genes often has a limited effect. Paralogs are genes that originate from common ancestors and retain similar functions. They often have complex effects on a particular phenotype depending on factors like gene family similarity, each individual gene's expression and the physiological or pathological context. Some paralogs exhibit synthetic lethal interactions in cancer cell survival; however, a thorough investigation of paralog pairs that could enhance the efficacy of cancer immunotherapy is lacking. Here we introduce a sensitive computational approach that uses sgRNA sets enrichment analysis to identify cancer-intrinsic paralog pairs which have the potential to synergistically enhance T cell-mediated tumor destruction. We have further developed an ensemble learning model that uses an XGBoost classifier and incorporates features such as gene characteristics, sequence and structural similarities, protein-protein interaction (PPI) networks, and gene coevolution data to predict paralog pairs that are likely to enhance immunotherapy efficacy. We experimentally validated the functional significance of these predicted paralog pairs using double knockout (DKO) of identified paralog gene pairs as compared to single gene knockouts (SKOs). These data and analyses collectively provide a sensitive approach to identify previously undetected paralog pairs that can enhance cancer immunotherapy even when individual genes within the pair has a limited effect.
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Affiliation(s)
- Chuanpeng Dong
- Department of Genetics, Yale University School of Medicine, New Haven, CT, USA
- System Biology Institute, Yale University, West Haven, CT, USA
- Center for Cancer Systems Biology, Yale University, West Haven, CT, USA
- Center for Biomedical Data Science, Yale University School of Medicine, New Haven, CT, USA
- Yale-Boehringer Ingelheim Biomedical Data Science Fellowship Program
| | - Feifei Zhang
- Department of Genetics, Yale University School of Medicine, New Haven, CT, USA
- System Biology Institute, Yale University, West Haven, CT, USA
- Center for Cancer Systems Biology, Yale University, West Haven, CT, USA
| | - Emily He
- Department of Genetics, Yale University School of Medicine, New Haven, CT, USA
- System Biology Institute, Yale University, West Haven, CT, USA
- Center for Cancer Systems Biology, Yale University, West Haven, CT, USA
- Yale College, Yale University, New Haven, Connecticut, USA
| | - Ping Ren
- Department of Genetics, Yale University School of Medicine, New Haven, CT, USA
- System Biology Institute, Yale University, West Haven, CT, USA
- Center for Cancer Systems Biology, Yale University, West Haven, CT, USA
| | - Nipun Verma
- Department of Genetics, Yale University School of Medicine, New Haven, CT, USA
- System Biology Institute, Yale University, West Haven, CT, USA
- Center for Cancer Systems Biology, Yale University, West Haven, CT, USA
| | - Xinxin Zhu
- Center for Biomedical Data Science, Yale University School of Medicine, New Haven, CT, USA
- Yale-Boehringer Ingelheim Biomedical Data Science Fellowship Program
| | - Di Feng
- Yale-Boehringer Ingelheim Biomedical Data Science Fellowship Program
- Computational Biology, Boehringer Ingelheim Pharmaceuticals, Inc., Ridgefield, CT, USA
| | - Hongyu Zhao
- Department of Genetics, Yale University School of Medicine, New Haven, CT, USA
- Center for Biomedical Data Science, Yale University School of Medicine, New Haven, CT, USA
- Yale-Boehringer Ingelheim Biomedical Data Science Fellowship Program
- Department of Biostatistics, Yale University School of Public Health, New Haven, CT, USA
| | - Sidi Chen
- Department of Genetics, Yale University School of Medicine, New Haven, CT, USA
- System Biology Institute, Yale University, West Haven, CT, USA
- Center for Cancer Systems Biology, Yale University, West Haven, CT, USA
- Center for Biomedical Data Science, Yale University School of Medicine, New Haven, CT, USA
- Yale-Boehringer Ingelheim Biomedical Data Science Fellowship Program
- Yale Comprehensive Cancer Center, Yale University School of Medicine, New Haven, CT, USA
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8
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Dias MH, Friskes A, Wang S, Fernandes Neto JM, van Gemert F, Mourragui S, Papagianni C, Kuiken HJ, Mainardi S, Alvarez-Villanueva D, Lieftink C, Morris B, Dekker A, van Dijk E, Wilms LH, da Silva MS, Jansen RA, Mulero-Sánchez A, Malzer E, Vidal A, Santos C, Salazar R, Wailemann RA, Torres TE, De Conti G, Raaijmakers JA, Snaebjornsson P, Yuan S, Qin W, Kovach JS, Armelin HA, te Riele H, van Oudenaarden A, Jin H, Beijersbergen RL, Villanueva A, Medema RH, Bernards R. Paradoxical Activation of Oncogenic Signaling as a Cancer Treatment Strategy. Cancer Discov 2024; 14:1276-1301. [PMID: 38533987 PMCID: PMC11215412 DOI: 10.1158/2159-8290.cd-23-0216] [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: 02/21/2023] [Revised: 12/06/2023] [Accepted: 03/19/2024] [Indexed: 03/28/2024]
Abstract
Cancer homeostasis depends on a balance between activated oncogenic pathways driving tumorigenesis and engagement of stress response programs that counteract the inherent toxicity of such aberrant signaling. Although inhibition of oncogenic signaling pathways has been explored extensively, there is increasing evidence that overactivation of the same pathways can also disrupt cancer homeostasis and cause lethality. We show here that inhibition of protein phosphatase 2A (PP2A) hyperactivates multiple oncogenic pathways and engages stress responses in colon cancer cells. Genetic and compound screens identify combined inhibition of PP2A and WEE1 as synergistic in multiple cancer models by collapsing DNA replication and triggering premature mitosis followed by cell death. This combination also suppressed the growth of patient-derived tumors in vivo. Remarkably, acquired resistance to this drug combination suppressed the ability of colon cancer cells to form tumors in vivo. Our data suggest that paradoxical activation of oncogenic signaling can result in tumor-suppressive resistance. Significance: A therapy consisting of deliberate hyperactivation of oncogenic signaling combined with perturbation of the stress responses that result from this is very effective in animal models of colon cancer. Resistance to this therapy is associated with loss of oncogenic signaling and reduced oncogenic capacity, indicative of tumor-suppressive drug resistance.
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Affiliation(s)
- Matheus Henrique Dias
- Division of Molecular Carcinogenesis, Oncode Institute, The Netherlands Cancer Institute, Amsterdam, the Netherlands.
| | - Anoek Friskes
- Division of Cell Biology, Oncode Institute, The Netherlands Cancer Institute, Amsterdam, the Netherlands.
| | - Siying Wang
- State Key Laboratory of Oncogenes and Related Genes, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Joao M. Fernandes Neto
- Division of Molecular Carcinogenesis, Oncode Institute, The Netherlands Cancer Institute, Amsterdam, the Netherlands.
| | - Frank van Gemert
- Division of Tumor Biology and Immunology, The Netherlands Cancer Institute, Amsterdam, the Netherlands.
| | - Soufiane Mourragui
- Hubrecht Institute-KNAW (Royal Netherlands Academy of Arts and Sciences) and University Medical Center, Utrecht, the Netherlands.
| | - Chrysa Papagianni
- Division of Molecular Carcinogenesis, Oncode Institute, The Netherlands Cancer Institute, Amsterdam, the Netherlands.
| | - Hendrik J. Kuiken
- Division of Molecular Carcinogenesis, The Netherlands Cancer Institute, Amsterdam, the Netherlands.
| | - Sara Mainardi
- Division of Molecular Carcinogenesis, Oncode Institute, The Netherlands Cancer Institute, Amsterdam, the Netherlands.
| | - Daniel Alvarez-Villanueva
- Chemoresistance and Predictive Factors Group, Program Against Cancer Therapeutic Resistance (ProCURE), Catalan Institute of Oncology (ICO), Oncobell Program, Bellvitge Biomedical Research Institute (IDIBELL), L’Hospitalet del Llobregat, Barcelona, Spain.
| | - Cor Lieftink
- Division of Molecular Carcinogenesis, NKI Robotic and Screening Center, The Netherlands Cancer Institute, Amsterdam, the Netherlands.
| | - Ben Morris
- Division of Molecular Carcinogenesis, NKI Robotic and Screening Center, The Netherlands Cancer Institute, Amsterdam, the Netherlands.
| | - Anna Dekker
- Division of Molecular Carcinogenesis, Oncode Institute, The Netherlands Cancer Institute, Amsterdam, the Netherlands.
| | - Emma van Dijk
- Division of Molecular Carcinogenesis, Oncode Institute, The Netherlands Cancer Institute, Amsterdam, the Netherlands.
| | - Lieke H.S. Wilms
- Division of Molecular Carcinogenesis, Oncode Institute, The Netherlands Cancer Institute, Amsterdam, the Netherlands.
| | - Marcelo S. da Silva
- Department of Biochemistry, Institute of Chemistry, University of São Paulo, São Paulo, SP, Brazil.
- Department of Chemical and Biological Sciences, Institute of Biosciences, São Paulo State University (UNESP), Botucatu, SP, Brazil.
| | - Robin A. Jansen
- Division of Molecular Carcinogenesis, Oncode Institute, The Netherlands Cancer Institute, Amsterdam, the Netherlands.
| | - Antonio Mulero-Sánchez
- Division of Molecular Carcinogenesis, Oncode Institute, The Netherlands Cancer Institute, Amsterdam, the Netherlands.
| | - Elke Malzer
- Division of Molecular Carcinogenesis, The Netherlands Cancer Institute, Amsterdam, the Netherlands.
| | - August Vidal
- Department of Pathology, University Hospital of Bellvitge, Bellvitge Biomedical Research Institute (IDIBELL), L’Hospitalet de Llobregat, Barcelona, Spain.
- Xenopat S.L., Parc Cientific de Barcelona (PCB), Barcelona, Spain.
| | - Cristina Santos
- Department of Medical Oncology, Catalan Institute of Oncology (ICO), Oncobell Program, Bellvitge Biomedical Research Institute (IDIBELL), CIBERONC, Barcelona, Spain.
| | - Ramón Salazar
- Department of Medical Oncology, Catalan Institute of Oncology (ICO), Oncobell Program, Bellvitge Biomedical Research Institute (IDIBELL), CIBERONC, Barcelona, Spain.
| | | | - Thompson E.P. Torres
- Center of Toxins, Immune-response and Cell Signaling, Instituto Butantan, São Paulo, Brazil.
- Department of Clinical and Experimental Oncology, Federal University of São Paulo (UNIFESP), São Paulo, Brazil.
| | - Giulia De Conti
- Division of Molecular Carcinogenesis, Oncode Institute, The Netherlands Cancer Institute, Amsterdam, the Netherlands.
| | - Jonne A. Raaijmakers
- Division of Cell Biology, Oncode Institute, The Netherlands Cancer Institute, Amsterdam, the Netherlands.
| | - Petur Snaebjornsson
- Department of Pathology, The Netherlands Cancer Institute, Amsterdam, the Netherlands.
- University of Iceland, Faculty of Medicine, Reykjavik, Iceland.
| | - Shengxian Yuan
- The Third Department of Hepatic Surgery, Eastern Hepatobiliary Surgery Hospital, Shanghai, China.
| | - Wenxin Qin
- State Key Laboratory of Oncogenes and Related Genes, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - John S. Kovach
- Lixte Biotechnology Holdings, Inc., Pasadena, California.
| | - Hugo A. Armelin
- Center of Toxins, Immune-response and Cell Signaling, Instituto Butantan, São Paulo, Brazil.
| | - Hein te Riele
- Division of Tumor Biology and Immunology, The Netherlands Cancer Institute, Amsterdam, the Netherlands.
| | - Alexander van Oudenaarden
- Hubrecht Institute-KNAW (Royal Netherlands Academy of Arts and Sciences) and University Medical Center, Utrecht, the Netherlands.
| | - Haojie Jin
- Division of Molecular Carcinogenesis, Oncode Institute, The Netherlands Cancer Institute, Amsterdam, the Netherlands.
- State Key Laboratory of Oncogenes and Related Genes, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Roderick L. Beijersbergen
- Division of Molecular Carcinogenesis, The Netherlands Cancer Institute, Amsterdam, the Netherlands.
- Division of Molecular Carcinogenesis, NKI Robotic and Screening Center, The Netherlands Cancer Institute, Amsterdam, the Netherlands.
| | - Alberto Villanueva
- Chemoresistance and Predictive Factors Group, Program Against Cancer Therapeutic Resistance (ProCURE), Catalan Institute of Oncology (ICO), Oncobell Program, Bellvitge Biomedical Research Institute (IDIBELL), L’Hospitalet del Llobregat, Barcelona, Spain.
- Xenopat S.L., Parc Cientific de Barcelona (PCB), Barcelona, Spain.
| | - Rene H. Medema
- Division of Cell Biology, Oncode Institute, The Netherlands Cancer Institute, Amsterdam, the Netherlands.
| | - Rene Bernards
- Division of Molecular Carcinogenesis, Oncode Institute, The Netherlands Cancer Institute, Amsterdam, the Netherlands.
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9
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Kocher D, Cao L, Guiho R, Langhammer M, Lai YL, Becker P, Hamdi H, Friedel D, Selt F, Vonhören D, Zaman J, Valinciute G, Herter S, Picard D, Rettenmeier J, Maass KK, Pajtler KW, Remke M, von Deimling A, Pusch S, Pfister SM, Oehme I, Jones DTW, Halbach S, Brummer T, Martinez-Barbera JP, Witt O, Milde T, Sigaud R. Rebound growth of BRAF mutant pediatric glioma cells after MAPKi withdrawal is associated with MAPK reactivation and secretion of microglia-recruiting cytokines. J Neurooncol 2024; 168:317-332. [PMID: 38630384 PMCID: PMC11147834 DOI: 10.1007/s11060-024-04672-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2024] [Accepted: 03/28/2024] [Indexed: 06/04/2024]
Abstract
INTRODUCTION Patients with pediatric low-grade gliomas (pLGGs), the most common primary brain tumors in children, can often benefit from MAPK inhibitor (MAPKi) treatment. However, rapid tumor regrowth, also referred to as rebound growth, may occur once treatment is stopped, constituting a significant clinical challenge. METHODS Four patient-derived pediatric glioma models were investigated to model rebound growth in vitro based on viable cell counts in response to MAPKi treatment and withdrawal. A multi-omics dataset (RNA sequencing and LC-MS/MS based phospho-/proteomics) was generated to investigate possible rebound-driving mechanisms. Following in vitro validation, putative rebound-driving mechanisms were validated in vivo using the BT-40 orthotopic xenograft model. RESULTS Of the tested models, only a BRAFV600E-driven model (BT-40, with additional CDKN2A/Bdel) showed rebound growth upon MAPKi withdrawal. Using this model, we identified a rapid reactivation of the MAPK pathway upon MAPKi withdrawal in vitro, also confirmed in vivo. Furthermore, transient overactivation of key MAPK molecules at transcriptional (e.g. FOS) and phosphorylation (e.g. pMEK) levels, was observed in vitro. Additionally, we detected increased expression and secretion of cytokines (CCL2, CX3CL1, CXCL10 and CCL7) upon MAPKi treatment, maintained during early withdrawal. While increased cytokine expression did not have tumor cell intrinsic effects, presence of these cytokines in conditioned media led to increased attraction of microglia cells in vitro. CONCLUSION Taken together, these data indicate rapid MAPK reactivation upon MAPKi withdrawal as a tumor cell intrinsic rebound-driving mechanism. Furthermore, increased secretion of microglia-recruiting cytokines may play a role in treatment response and rebound growth upon withdrawal, warranting further evaluation.
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Affiliation(s)
- Daniela Kocher
- Hopp Children's Cancer Center Heidelberg (KiTZ), Heidelberg, Germany
- National Center for Tumor Diseases (NCT), NCT Heidelberg, a partnership between DKFZ and Heidelberg University Hospital, Heidelberg, Germany
- German Cancer Research Center (DKFZ) Heidelberg, Clinical Cooperation Unit Pediatric Oncology, Heidelberg, Germany
- Faculty of Biosciences, Heidelberg University, Heidelberg, Germany
| | - Lei Cao
- Developmental Biology and Cancer Programme, Birth Defects Research Centre, Great Ormond Street Institute of Child Health, University College London, 30 Guilford Street, WC1N 1EH, London, UK
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Romain Guiho
- Developmental Biology and Cancer Programme, Birth Defects Research Centre, Great Ormond Street Institute of Child Health, University College London, 30 Guilford Street, WC1N 1EH, London, UK
- Nantes Université, Oniris, INSERM, Regenerative Medicine and Skeleton, RMeS, UMR 1229, F-44000 Nantes, France
| | - Melanie Langhammer
- Institute of Molecular Medicine and Cell Research (IMMZ), Faculty of Medicine, University of Freiburg, Freiburg, Germany
- Faculty of Biology, University of Freiburg, Freiburg, Germany
| | - Yun-Lu Lai
- Hopp Children's Cancer Center Heidelberg (KiTZ), Heidelberg, Germany
- National Center for Tumor Diseases (NCT), NCT Heidelberg, a partnership between DKFZ and Heidelberg University Hospital, Heidelberg, Germany
- German Cancer Research Center (DKFZ) Heidelberg, Clinical Cooperation Unit Pediatric Oncology, Heidelberg, Germany
| | - Pauline Becker
- Hopp Children's Cancer Center Heidelberg (KiTZ), Heidelberg, Germany
- National Center for Tumor Diseases (NCT), NCT Heidelberg, a partnership between DKFZ and Heidelberg University Hospital, Heidelberg, Germany
- German Cancer Research Center (DKFZ) Heidelberg, Clinical Cooperation Unit Pediatric Oncology, Heidelberg, Germany
- Faculty of Medicine, Heidelberg University, Heidelberg, Germany
| | - Hiba Hamdi
- Developmental Biology and Cancer Programme, Birth Defects Research Centre, Great Ormond Street Institute of Child Health, University College London, 30 Guilford Street, WC1N 1EH, London, UK
| | - Dennis Friedel
- Faculty of Biosciences, Heidelberg University, Heidelberg, Germany
- Department of Neuropathology, Heidelberg University Hospital, Heidelberg, Germany
- German Cancer Research Center (DKFZ), Clinical Cooperation Unit Neuropathology, Heidelberg, Germany
| | - Florian Selt
- Hopp Children's Cancer Center Heidelberg (KiTZ), Heidelberg, Germany
- National Center for Tumor Diseases (NCT), NCT Heidelberg, a partnership between DKFZ and Heidelberg University Hospital, Heidelberg, Germany
- German Cancer Research Center (DKFZ) Heidelberg, Clinical Cooperation Unit Pediatric Oncology, Heidelberg, Germany
- KiTZ Clinical Trial Unit (ZIPO), Department of Pediatric Hematology and Oncology, Heidelberg University Hospital, Heidelberg, Germany
| | - David Vonhören
- Faculty of Biosciences, Heidelberg University, Heidelberg, Germany
- Department of Neuropathology, Heidelberg University Hospital, Heidelberg, Germany
- German Cancer Research Center (DKFZ), Clinical Cooperation Unit Neuropathology, Heidelberg, Germany
| | - Julia Zaman
- Faculty of Biosciences, Heidelberg University, Heidelberg, Germany
- Department of Neuropathology, Heidelberg University Hospital, Heidelberg, Germany
- German Cancer Research Center (DKFZ), Clinical Cooperation Unit Neuropathology, Heidelberg, Germany
| | - Gintvile Valinciute
- Hopp Children's Cancer Center Heidelberg (KiTZ), Heidelberg, Germany
- National Center for Tumor Diseases (NCT), NCT Heidelberg, a partnership between DKFZ and Heidelberg University Hospital, Heidelberg, Germany
- German Cancer Research Center (DKFZ) Heidelberg, Clinical Cooperation Unit Pediatric Oncology, Heidelberg, Germany
| | - Sonja Herter
- Hopp Children's Cancer Center Heidelberg (KiTZ), Heidelberg, Germany
- National Center for Tumor Diseases (NCT), NCT Heidelberg, a partnership between DKFZ and Heidelberg University Hospital, Heidelberg, Germany
- German Cancer Research Center (DKFZ) Heidelberg, Clinical Cooperation Unit Pediatric Oncology, Heidelberg, Germany
- Faculty of Biosciences, Heidelberg University, Heidelberg, Germany
| | - Daniel Picard
- Department of Pediatric Oncology, Hematology, and Clinical Immunology, Medical Faculty, and University Hospital Düsseldorf, Heinrich Heine University, Düsseldorf, Germany
- German Cancer Consortium (DKTK), Partner site Essen/Düsseldorf, Düsseldorf, Germany
- Institute of Neuropathology, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University, Düsseldorf, Germany
| | - Johanna Rettenmeier
- Hopp Children's Cancer Center Heidelberg (KiTZ), Heidelberg, Germany
- National Center for Tumor Diseases (NCT), NCT Heidelberg, a partnership between DKFZ and Heidelberg University Hospital, Heidelberg, Germany
- Faculty of Medicine, Heidelberg University, Heidelberg, Germany
- German Cancer Research Center (DKFZ), Division of Pediatric Neurooncology, Heidelberg, Germany
- Department of Pediatric Oncology, Hematology, Immunology and Pulmonology, Heidelberg University Hospital, Heidelberg, Germany
| | - Kendra K Maass
- Hopp Children's Cancer Center Heidelberg (KiTZ), Heidelberg, Germany
- National Center for Tumor Diseases (NCT), NCT Heidelberg, a partnership between DKFZ and Heidelberg University Hospital, Heidelberg, Germany
- German Cancer Research Center (DKFZ), Division of Pediatric Neurooncology, Heidelberg, Germany
- Department of Pediatric Oncology, Hematology, Immunology and Pulmonology, Heidelberg University Hospital, Heidelberg, Germany
| | - Kristian W Pajtler
- Hopp Children's Cancer Center Heidelberg (KiTZ), Heidelberg, Germany
- National Center for Tumor Diseases (NCT), NCT Heidelberg, a partnership between DKFZ and Heidelberg University Hospital, Heidelberg, Germany
- KiTZ Clinical Trial Unit (ZIPO), Department of Pediatric Hematology and Oncology, Heidelberg University Hospital, Heidelberg, Germany
- German Cancer Research Center (DKFZ), Division of Pediatric Neurooncology, Heidelberg, Germany
- Department of Pediatric Oncology, Hematology, Immunology and Pulmonology, Heidelberg University Hospital, Heidelberg, Germany
| | - Marc Remke
- Pediatric Hematology and Oncology, University Children's Hospital, Saarland University, Homburg, Germany
| | - Andreas von Deimling
- Department of Neuropathology, Heidelberg University Hospital, Heidelberg, Germany
- German Cancer Research Center (DKFZ), Clinical Cooperation Unit Neuropathology, Heidelberg, Germany
| | - Stefan Pusch
- Department of Neuropathology, Heidelberg University Hospital, Heidelberg, Germany
- German Cancer Research Center (DKFZ), Clinical Cooperation Unit Neuropathology, Heidelberg, Germany
| | - Stefan M Pfister
- Hopp Children's Cancer Center Heidelberg (KiTZ), Heidelberg, Germany
- National Center for Tumor Diseases (NCT), NCT Heidelberg, a partnership between DKFZ and Heidelberg University Hospital, Heidelberg, Germany
- KiTZ Clinical Trial Unit (ZIPO), Department of Pediatric Hematology and Oncology, Heidelberg University Hospital, Heidelberg, Germany
- German Cancer Research Center (DKFZ), Division of Pediatric Neurooncology, Heidelberg, Germany
| | - Ina Oehme
- Hopp Children's Cancer Center Heidelberg (KiTZ), Heidelberg, Germany
- National Center for Tumor Diseases (NCT), NCT Heidelberg, a partnership between DKFZ and Heidelberg University Hospital, Heidelberg, Germany
- German Cancer Research Center (DKFZ) Heidelberg, Clinical Cooperation Unit Pediatric Oncology, Heidelberg, Germany
| | - David T W Jones
- Hopp Children's Cancer Center Heidelberg (KiTZ), Heidelberg, Germany
- National Center for Tumor Diseases (NCT), NCT Heidelberg, a partnership between DKFZ and Heidelberg University Hospital, Heidelberg, Germany
- German Cancer Research Center (DKFZ) Heidelberg, Division of Pediatric Glioma Research, Heidelberg, Germany
| | - Sebastian Halbach
- Institute of Molecular Medicine and Cell Research (IMMZ), Faculty of Medicine, University of Freiburg, Freiburg, Germany
- German Consortium for Translational Cancer Research (DKTK), Freiburg, Germany, German Cancer Research Center (DKFZ), Heidelberg, Germany
- German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Tilman Brummer
- Institute of Molecular Medicine and Cell Research (IMMZ), Faculty of Medicine, University of Freiburg, Freiburg, Germany
- German Consortium for Translational Cancer Research (DKTK), Freiburg, Germany, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Centre for Biological Signaling Studies BIOSS, University of Freiburg, Freiburg, Germany
| | - Juan Pedro Martinez-Barbera
- Developmental Biology and Cancer Programme, Birth Defects Research Centre, Great Ormond Street Institute of Child Health, University College London, 30 Guilford Street, WC1N 1EH, London, UK
| | - Olaf Witt
- Hopp Children's Cancer Center Heidelberg (KiTZ), Heidelberg, Germany
- National Center for Tumor Diseases (NCT), NCT Heidelberg, a partnership between DKFZ and Heidelberg University Hospital, Heidelberg, Germany
- German Cancer Research Center (DKFZ) Heidelberg, Clinical Cooperation Unit Pediatric Oncology, Heidelberg, Germany
- KiTZ Clinical Trial Unit (ZIPO), Department of Pediatric Hematology and Oncology, Heidelberg University Hospital, Heidelberg, Germany
| | - Till Milde
- Hopp Children's Cancer Center Heidelberg (KiTZ), Heidelberg, Germany.
- National Center for Tumor Diseases (NCT), NCT Heidelberg, a partnership between DKFZ and Heidelberg University Hospital, Heidelberg, Germany.
- German Cancer Research Center (DKFZ) Heidelberg, Clinical Cooperation Unit Pediatric Oncology, Heidelberg, Germany.
- KiTZ Clinical Trial Unit (ZIPO), Department of Pediatric Hematology and Oncology, Heidelberg University Hospital, Heidelberg, Germany.
| | - Romain Sigaud
- Hopp Children's Cancer Center Heidelberg (KiTZ), Heidelberg, Germany.
- National Center for Tumor Diseases (NCT), NCT Heidelberg, a partnership between DKFZ and Heidelberg University Hospital, Heidelberg, Germany.
- German Cancer Research Center (DKFZ) Heidelberg, Clinical Cooperation Unit Pediatric Oncology, Heidelberg, Germany.
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10
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Zhao M, Shuai W, Su Z, Xu P, Wang A, Sun Q, Wang G. Protein tyrosine phosphatases: emerging role in cancer therapy resistance. Cancer Commun (Lond) 2024; 44:637-653. [PMID: 38741380 PMCID: PMC11194456 DOI: 10.1002/cac2.12548] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Revised: 04/14/2024] [Accepted: 04/23/2024] [Indexed: 05/16/2024] Open
Abstract
BACKGROUND Tyrosine phosphorylation of intracellular proteins is a post-translational modification that plays a regulatory role in signal transduction during cellular events. Dephosphorylation of signal transduction proteins caused by protein tyrosine phosphatases (PTPs) contributed their role as a convergent node to mediate cross-talk between signaling pathways. In the context of cancer, PTP-mediated pathways have been identified as signaling hubs that enabled cancer cells to mitigate stress induced by clinical therapy. This is achieved by the promotion of constitutive activation of growth-stimulatory signaling pathways or modulation of the immune-suppressive tumor microenvironment. Preclinical evidences suggested that anticancer drugs will release their greatest therapeutic potency when combined with PTP inhibitors, reversing drug resistance that was responsible for clinical failures during cancer therapy. AREAS COVERED This review aimed to elaborate recent insights that supported the involvement of PTP-mediated pathways in the development of resistance to targeted therapy and immune-checkpoint therapy. EXPERT OPINION This review proposed the notion of PTP inhibition in anticancer combination therapy as a potential strategy in clinic to achieve long-term tumor regression. Ongoing clinical trials are currently underway to assess the safety and efficacy of combination therapy in advanced-stage tumors.
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Affiliation(s)
- Min Zhao
- Innovation Center of Nursing ResearchNursing Key Laboratory of Sichuan ProvinceDepartment of BiotherapyCancer Center and State Key Laboratory of BiotherapyNational Clinical Research Center for GeriatricsWest China Hospital, West China School of Nursing, Sichuan UniversityChengduSichuanP. R. China
| | - Wen Shuai
- Innovation Center of Nursing ResearchNursing Key Laboratory of Sichuan ProvinceDepartment of BiotherapyCancer Center and State Key Laboratory of BiotherapyNational Clinical Research Center for GeriatricsWest China Hospital, West China School of Nursing, Sichuan UniversityChengduSichuanP. R. China
| | - Zehao Su
- Innovation Center of Nursing ResearchNursing Key Laboratory of Sichuan ProvinceDepartment of BiotherapyCancer Center and State Key Laboratory of BiotherapyNational Clinical Research Center for GeriatricsWest China Hospital, West China School of Nursing, Sichuan UniversityChengduSichuanP. R. China
- West China Biomedical Big Data CenterMed‐X Center for InformaticsSichuan UniversityChengduSichuanP. R. China
| | - Ping Xu
- Emergency DepartmentZigong Fourth People's HospitalChengduSichuanP. R. China
| | - Aoxue Wang
- Innovation Center of Nursing ResearchNursing Key Laboratory of Sichuan ProvinceDepartment of BiotherapyCancer Center and State Key Laboratory of BiotherapyNational Clinical Research Center for GeriatricsWest China Hospital, West China School of Nursing, Sichuan UniversityChengduSichuanP. R. China
| | - Qiu Sun
- Innovation Center of Nursing ResearchNursing Key Laboratory of Sichuan ProvinceDepartment of BiotherapyCancer Center and State Key Laboratory of BiotherapyNational Clinical Research Center for GeriatricsWest China Hospital, West China School of Nursing, Sichuan UniversityChengduSichuanP. R. China
| | - Guan Wang
- Innovation Center of Nursing ResearchNursing Key Laboratory of Sichuan ProvinceDepartment of BiotherapyCancer Center and State Key Laboratory of BiotherapyNational Clinical Research Center for GeriatricsWest China Hospital, West China School of Nursing, Sichuan UniversityChengduSichuanP. R. China
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11
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Thatikonda V, Supper V, Wachter J, Kaya O, Kombara A, Bilgilier C, Ravichandran MC, Lipp JJ, Sharma R, Badertscher L, Boghossian AS, Rees MG, Ronan MM, Roth JA, Grosche S, Neumüller RA, Mair B, Mauri F, Popa A. Genetic dependencies associated with transcription factor activities in human cancer cell lines. Cell Rep 2024; 43:114175. [PMID: 38691456 DOI: 10.1016/j.celrep.2024.114175] [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: 03/14/2023] [Revised: 02/02/2024] [Accepted: 04/16/2024] [Indexed: 05/03/2024] Open
Abstract
Transcription factors (TFs) are important mediators of aberrant transcriptional programs in cancer cells. In this study, we focus on TF activity (TFa) as a biomarker for cell-line-selective anti-proliferative effects, in that high TFa predicts sensitivity to loss of function of a given gene (i.e., genetic dependencies [GDs]). Our linear-regression-based framework identifies 3,047 pan-cancer and 3,952 cancer-type-specific candidate TFa-GD associations from cell line data, which are then cross-examined for impact on survival in patient cohorts. One of the most prominent biomarkers is TEAD1 activity, whose associations with its predicted GDs are validated through experimental evidence as proof of concept. Overall, these TFa-GD associations represent an attractive resource for identifying innovative, biomarker-driven hypotheses for drug discovery programs in oncology.
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Affiliation(s)
- Venu Thatikonda
- Boehringer Ingelheim RCV GmbH & Co KG, Doktor-Boehringer-Gasse 5-11, Vienna 1120, Austria.
| | - Verena Supper
- Boehringer Ingelheim RCV GmbH & Co KG, Doktor-Boehringer-Gasse 5-11, Vienna 1120, Austria
| | - Johannes Wachter
- Boehringer Ingelheim RCV GmbH & Co KG, Doktor-Boehringer-Gasse 5-11, Vienna 1120, Austria
| | - Onur Kaya
- Boehringer Ingelheim RCV GmbH & Co KG, Doktor-Boehringer-Gasse 5-11, Vienna 1120, Austria
| | - Anju Kombara
- Boehringer Ingelheim RCV GmbH & Co KG, Doktor-Boehringer-Gasse 5-11, Vienna 1120, Austria
| | - Ceren Bilgilier
- Boehringer Ingelheim RCV GmbH & Co KG, Doktor-Boehringer-Gasse 5-11, Vienna 1120, Austria
| | | | - Jesse J Lipp
- Boehringer Ingelheim RCV GmbH & Co KG, Doktor-Boehringer-Gasse 5-11, Vienna 1120, Austria
| | - Rahul Sharma
- Myllia Biotechnology GmbH, Am Kanal 27, Vienna 1110, Austria
| | | | | | - Matthew G Rees
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Melissa M Ronan
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Jennifer A Roth
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Sarah Grosche
- Boehringer Ingelheim RCV GmbH & Co KG, Doktor-Boehringer-Gasse 5-11, Vienna 1120, Austria
| | - Ralph A Neumüller
- Boehringer Ingelheim RCV GmbH & Co KG, Doktor-Boehringer-Gasse 5-11, Vienna 1120, Austria
| | - Barbara Mair
- Boehringer Ingelheim RCV GmbH & Co KG, Doktor-Boehringer-Gasse 5-11, Vienna 1120, Austria
| | - Federico Mauri
- Boehringer Ingelheim RCV GmbH & Co KG, Doktor-Boehringer-Gasse 5-11, Vienna 1120, Austria
| | - Alexandra Popa
- Boehringer Ingelheim RCV GmbH & Co KG, Doktor-Boehringer-Gasse 5-11, Vienna 1120, Austria.
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12
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Esmaeili Anvar N, Lin C, Ma X, Wilson LL, Steger R, Sangree AK, Colic M, Wang SH, Doench JG, Hart T. Efficient gene knockout and genetic interaction screening using the in4mer CRISPR/Cas12a multiplex knockout platform. Nat Commun 2024; 15:3577. [PMID: 38678031 PMCID: PMC11055879 DOI: 10.1038/s41467-024-47795-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Accepted: 04/12/2024] [Indexed: 04/29/2024] Open
Abstract
Genetic interactions mediate the emergence of phenotype from genotype, but technologies for combinatorial genetic perturbation in mammalian cells are challenging to scale. Here, we identify background-independent paralog synthetic lethals from previous CRISPR genetic interaction screens, and find that the Cas12a platform provides superior sensitivity and assay replicability. We develop the in4mer Cas12a platform that uses arrays of four independent guide RNAs targeting the same or different genes. We construct a genome-scale library, Inzolia, that is ~30% smaller than a typical CRISPR/Cas9 library while also targeting ~4000 paralog pairs. Screens in cancer cells demonstrate discrimination of core and context-dependent essential genes similar to that of CRISPR/Cas9 libraries, as well as detection of synthetic lethal and masking/buffering genetic interactions between paralogs of various family sizes. Importantly, the in4mer platform offers a fivefold reduction in library size compared to other genetic interaction methods, substantially reducing the cost and effort required for these assays.
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Affiliation(s)
- Nazanin Esmaeili Anvar
- Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
- Graduate School of Biomedical Sciences, The University of Texas MD Anderson Cancer Center UTHealth, Houston, TX, USA
| | - Chenchu Lin
- Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Xingdi Ma
- Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
- Graduate School of Biomedical Sciences, The University of Texas MD Anderson Cancer Center UTHealth, Houston, TX, USA
| | - Lori L Wilson
- Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Ryan Steger
- Genetic Perturbation Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Annabel K Sangree
- Genetic Perturbation Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Medina Colic
- Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Sidney H Wang
- Center for Human Genetics, The Brown foundation Institute of Molecular Medicine, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - John G Doench
- Genetic Perturbation Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Traver Hart
- Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
- Department of Cancer Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
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13
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Jubran J, Slutsky R, Rozenblum N, Rokach L, Ben-David U, Yeger-Lotem E. Machine-learning analysis reveals an important role for negative selection in shaping cancer aneuploidy landscapes. Genome Biol 2024; 25:95. [PMID: 38622679 PMCID: PMC11020441 DOI: 10.1186/s13059-024-03225-7] [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: 07/05/2023] [Accepted: 03/26/2024] [Indexed: 04/17/2024] Open
Abstract
BACKGROUND Aneuploidy, an abnormal number of chromosomes within a cell, is a hallmark of cancer. Patterns of aneuploidy differ across cancers, yet are similar in cancers affecting closely related tissues. The selection pressures underlying aneuploidy patterns are not fully understood, hindering our understanding of cancer development and progression. RESULTS Here, we apply interpretable machine learning methods to study tissue-selective aneuploidy patterns. We define 20 types of features corresponding to genomic attributes of chromosome-arms, normal tissues, primary tumors, and cancer cell lines (CCLs), and use them to model gains and losses of chromosome arms in 24 cancer types. To reveal the factors that shape the tissue-specific cancer aneuploidy landscapes, we interpret the machine learning models by estimating the relative contribution of each feature to the models. While confirming known drivers of positive selection, our quantitative analysis highlights the importance of negative selection for shaping aneuploidy landscapes. This is exemplified by tumor suppressor gene density being a better predictor of gain patterns than oncogene density, and vice versa for loss patterns. We also identify the importance of tissue-selective features and demonstrate them experimentally, revealing KLF5 as an important driver for chr13q gain in colon cancer. Further supporting an important role for negative selection in shaping the aneuploidy landscapes, we find compensation by paralogs to be among the top predictors of chromosome arm loss prevalence and demonstrate this relationship for one paralog interaction. Similar factors shape aneuploidy patterns in human CCLs, demonstrating their relevance for aneuploidy research. CONCLUSIONS Our quantitative, interpretable machine learning models improve the understanding of the genomic properties that shape cancer aneuploidy landscapes.
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Affiliation(s)
- Juman Jubran
- Department of Clinical Biochemistry and Pharmacology, Ben-Gurion University of the Negev, 84105, Beer Sheva, Israel
| | - Rachel Slutsky
- Department of Human Molecular Genetics and Biochemistry, Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Nir Rozenblum
- Department of Human Molecular Genetics and Biochemistry, Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Lior Rokach
- Department of Software & Information Systems Engineering, Ben-Gurion University of the Negev, 84105, Beer Sheva, Israel
| | - Uri Ben-David
- Department of Human Molecular Genetics and Biochemistry, Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.
| | - Esti Yeger-Lotem
- Department of Clinical Biochemistry and Pharmacology, Ben-Gurion University of the Negev, 84105, Beer Sheva, Israel.
- The National Institute for Biotechnology in the Negev, Ben-Gurion University of the Negev, 84105, Beer Sheva, Israel.
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14
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White J, Derheimer FA, Jensen-Pergakes K, O'Connell S, Sharma S, Spiegel N, Paul TA. Histone lysine acetyltransferase inhibitors: an emerging class of drugs for cancer therapy. Trends Pharmacol Sci 2024; 45:243-254. [PMID: 38383216 DOI: 10.1016/j.tips.2024.01.010] [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: 01/05/2024] [Revised: 01/20/2024] [Accepted: 01/22/2024] [Indexed: 02/23/2024]
Abstract
Lysine acetyltransferases (KATs) are a family of epigenetic enzymes involved in the regulation of gene expression; they represent a promising class of emerging drug targets. The frequent molecular dysregulation of these enzymes, as well as their mechanistic links to biological functions that are crucial to cancer, have led to exploration around the development of small-molecule inhibitors against KATs. Despite early challenges, recent advances have led to the development of potent and selective enzymatic and bromodomain (BRD) KAT inhibitors. In this review we discuss the discovery and development of new KAT inhibitors and their application as oncology therapeutics. Additionally, new chemically induced proximity approaches are presented, offering opportunities for unique target selectivity profiles and tissue-specific targeting of KATs. Emerging clinical data for CREB binding protein (CREBBP)/EP300 BRD inhibitors and KAT6 catalytic inhibitors indicate the promise of this target class in cancer therapeutics.
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Affiliation(s)
- Jeffrey White
- Pfizer Inc., Oncology Research Unit, San Diego, CA 92121, USA
| | | | | | - Shawn O'Connell
- Pfizer Inc., Oncology Research Unit, San Diego, CA 92121, USA
| | - Shikhar Sharma
- Pfizer Inc., Oncology Research Unit, San Diego, CA 92121, USA
| | - Noah Spiegel
- Pfizer Inc., Oncology Research Unit, San Diego, CA 92121, USA
| | - Thomas A Paul
- Pfizer Inc., Oncology Research Unit, San Diego, CA 92121, USA.
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15
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Pacini C, Duncan E, Gonçalves E, Gilbert J, Bhosle S, Horswell S, Karakoc E, Lightfoot H, Curry E, Muyas F, Bouaboula M, Pedamallu CS, Cortes-Ciriano I, Behan FM, Zalmas LP, Barthorpe A, Francies H, Rowley S, Pollard J, Beltrao P, Parts L, Iorio F, Garnett MJ. A comprehensive clinically informed map of dependencies in cancer cells and framework for target prioritization. Cancer Cell 2024; 42:301-316.e9. [PMID: 38215750 DOI: 10.1016/j.ccell.2023.12.016] [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: 07/05/2023] [Revised: 10/20/2023] [Accepted: 12/15/2023] [Indexed: 01/14/2024]
Abstract
Genetic screens in cancer cell lines inform gene function and drug discovery. More comprehensive screen datasets with multi-omics data are needed to enhance opportunities to functionally map genetic vulnerabilities. Here, we construct a second-generation map of cancer dependencies by annotating 930 cancer cell lines with multi-omic data and analyze relationships between molecular markers and cancer dependencies derived from CRISPR-Cas9 screens. We identify dependency-associated gene expression markers beyond driver genes, and observe many gene addiction relationships driven by gain of function rather than synthetic lethal effects. By combining clinically informed dependency-marker associations with protein-protein interaction networks, we identify 370 anti-cancer priority targets for 27 cancer types, many of which have network-based evidence of a functional link with a marker in a cancer type. Mapping these targets to sequenced tumor cohorts identifies tractable targets in different cancer types. This target prioritization map enhances understanding of gene dependencies and identifies candidate anti-cancer targets for drug development.
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Affiliation(s)
- Clare Pacini
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK; Open Targets, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Emma Duncan
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK; Open Targets, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Emanuel Gonçalves
- Instituto Superior Técnico (IST), Universidade de Lisboa, 1049-001 Lisboa, Portugal; INESC-ID, 1000-029 Lisboa, Portugal
| | - James Gilbert
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Shriram Bhosle
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Stuart Horswell
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK; Open Targets, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Emre Karakoc
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK; Open Targets, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Howard Lightfoot
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Ed Curry
- Genome Biology, Genomic Sciences, GSK, Stevenage, UK
| | - Francesc Muyas
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, Cambridge CB10 1SD, UK
| | | | | | - Isidro Cortes-Ciriano
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, Cambridge CB10 1SD, UK
| | - Fiona M Behan
- Genome Biology, Genomic Sciences, GSK, Stevenage, UK
| | - Lykourgos-Panagiotis Zalmas
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK; Open Targets, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Andrew Barthorpe
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Hayley Francies
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK; Genome Biology, Genomic Sciences, GSK, Stevenage, UK
| | - Steve Rowley
- Sanofi Research and Development, Cambridge, MA, USA
| | - Jack Pollard
- Sanofi Research and Development, Cambridge, MA, USA
| | - Pedro Beltrao
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK; European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, Cambridge CB10 1SD, UK
| | - Leopold Parts
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK; Open Targets, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Francesco Iorio
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK; Open Targets, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK; Human Technopole, V.le Rita Levi-Montalcini, 1, 20157 Milano, Italy.
| | - Mathew J Garnett
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK; Open Targets, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK.
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16
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Gökbağ B, Tang S, Fan K, Cheng L, Yu L, Zhao Y, Li L. SLKB: synthetic lethality knowledge base. Nucleic Acids Res 2024; 52:D1418-D1428. [PMID: 37889037 PMCID: PMC10767912 DOI: 10.1093/nar/gkad806] [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: 06/04/2023] [Revised: 08/16/2023] [Accepted: 09/27/2023] [Indexed: 10/28/2023] Open
Abstract
Emerging CRISPR-Cas9 technology permits synthetic lethality (SL) screening of large number of gene pairs from gene combination double knockout (CDKO) experiments. However, the poor integration and annotation of CDKO SL data in current SL databases limit their utility, and diverse methods of calculating SL scores prohibit their comparison. To overcome these shortcomings, we have developed SL knowledge base (SLKB) that incorporates data of 11 CDKO experiments in 22 cell lines, 16,059 SL gene pairs and 264,424 non-SL gene pairs. Additionally, within SLKB, we have implemented five SL calculation methods: median score with and without background control normalization (Median-B/NB), sgRNA-derived score (sgRNA-B/NB), Horlbeck score, GEMINI score and MAGeCK score. The five scores have demonstrated a mere 1.21% overlap among their top 10% SL gene pairs, reflecting high diversity. Users can browse SL networks and assess the impact of scoring methods using Venn diagrams. The SL network generated from all data in SLKB shows a greater likelihood of SL gene pair connectivity with other SL gene pairs than non-SL pairs. Comparison of SL networks between two cell lines demonstrated greater likelihood to share SL hub genes than SL gene pairs. SLKB website and pipeline can be freely accessed at https://slkb.osubmi.org and https://slkb.docs.osubmi.org/, respectively.
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Affiliation(s)
- Birkan Gökbağ
- Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH 43210, USA
| | - Shan Tang
- College of Pharmacy, The Ohio State University, Columbus, OH 43210, USA
| | - Kunjie Fan
- Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH 43210, USA
| | - Lijun Cheng
- Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH 43210, USA
| | - Lianbo Yu
- Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH 43210, USA
| | - Yue Zhao
- Department of Computational Medicine and Bioinformatics, College of Medicine, University of Michigan, Ann Arbor, MI 48104, USA
| | - Lang Li
- Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH 43210, USA
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17
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Maltas J, Killarney ST, Singleton KR, Strobl MAR, Washart R, Wood KC, Wood KB. Drug dependence in cancer is exploitable by optimally constructed treatment holidays. Nat Ecol Evol 2024; 8:147-162. [PMID: 38012363 PMCID: PMC10918730 DOI: 10.1038/s41559-023-02255-x] [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: 07/06/2022] [Accepted: 10/19/2023] [Indexed: 11/29/2023]
Abstract
Cancers with acquired resistance to targeted therapy can become simultaneously dependent on the presence of the targeted therapy drug for survival, suggesting that intermittent therapy may slow resistance. However, relatively little is known about which tumours are likely to become dependent and how to schedule intermittent therapy optimally. Here we characterized drug dependence across a panel of over 75 MAPK-inhibitor-resistant BRAFV600E mutant melanoma models at the population and single-clone levels. Melanocytic differentiated models exhibited a much greater tendency to give rise to drug-dependent progeny than their dedifferentiated counterparts. Mechanistically, acquired loss of microphthalmia-associated transcription factor in differentiated melanoma models drives ERK-JunB-p21 signalling to enforce drug dependence. We identified the optimal scheduling of 'drug holidays' using simple mathematical models that we validated across short and long timescales. Without detailed knowledge of tumour characteristics, we found that a simple adaptive therapy protocol can produce near-optimal outcomes using only measurements of total population size. Finally, a spatial agent-based model showed that optimal schedules derived from exponentially growing cells in culture remain nearly optimal in the context of tumour cell turnover and limited environmental carrying capacity. These findings may guide the implementation of improved evolution-inspired treatment strategies for drug-dependent cancers.
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Affiliation(s)
- Jeff Maltas
- Department of Biophysics, University of Michigan, Ann Arbor, MI, USA
| | - Shane T Killarney
- Department of Pharmacology and Cancer Biology, Duke University, Durham, NC, USA
| | | | - Maximilian A R Strobl
- Department of Translational Hematology and Oncology Research, Cleveland Clinic, Cleveland, OH, USA
| | - Rachel Washart
- Department of Pharmacology and Cancer Biology, Duke University, Durham, NC, USA
| | - Kris C Wood
- Department of Pharmacology and Cancer Biology, Duke University, Durham, NC, USA.
| | - Kevin B Wood
- Department of Biophysics, University of Michigan, Ann Arbor, MI, USA.
- Department of Physics, University of Michigan, Ann Arbor, MI, USA.
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18
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Layden HM, Johnson AE, Hiebert SW. Chemical-genetics refines transcription factor regulatory circuits. Trends Cancer 2024; 10:65-75. [PMID: 37722945 PMCID: PMC10840957 DOI: 10.1016/j.trecan.2023.08.012] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Revised: 08/14/2023] [Accepted: 08/25/2023] [Indexed: 09/20/2023]
Abstract
Transcriptional dysregulation is a key step in oncogenesis, but our understanding of transcriptional control has relied on genetic approaches that are slow and allow for compensation. Chemical-genetic approaches have shortened the time frame for the analysis of transcription factors from days or weeks to minutes. These studies show that while DNA-binding proteins bind to thousands of sites, they are directly required to regulate only a small cadre of genes. Moreover, these transcriptional control networks are far more distinct, with much less overlap and interconnectivity than predicted from DNA binding. The identified direct targets can then be used to dissect the mechanism of action of these factors, which could identify ways to therapeutically manipulate these oncogenic transcriptional control networks.
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Affiliation(s)
- Hillary M Layden
- Department of Biochemistry, Vanderbilt University School of Medicine, Nashville, TN 37232, USA
| | - Anna E Johnson
- Department of Biochemistry, Vanderbilt University School of Medicine, Nashville, TN 37232, USA
| | - Scott W Hiebert
- Department of Biochemistry, Vanderbilt University School of Medicine, Nashville, TN 37232, USA; Vanderbilt-Ingram Cancer Center, Nashville, TN 37027, USA.
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19
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Deschênes-Simard X, Malleshaiah M, Ferbeyre G. Extracellular Signal-Regulated Kinases: One Pathway, Multiple Fates. Cancers (Basel) 2023; 16:95. [PMID: 38201521 PMCID: PMC10778234 DOI: 10.3390/cancers16010095] [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: 11/23/2023] [Revised: 12/20/2023] [Accepted: 12/22/2023] [Indexed: 01/12/2024] Open
Abstract
This comprehensive review delves into the multifaceted aspects of ERK signaling and the intricate mechanisms underlying distinct cellular fates. ERK1 and ERK2 (ERK) govern proliferation, transformation, epithelial-mesenchymal transition, differentiation, senescence, or cell death, contingent upon activation strength, duration, and context. The biochemical mechanisms underlying these outcomes are inadequately understood, shaped by signaling feedback and the spatial localization of ERK activation. Generally, ERK activation aligns with the Goldilocks principle in cell fate determination. Inadequate or excessive ERK activity hinders cell proliferation, while balanced activation promotes both cell proliferation and survival. Unraveling the intricacies of how the degree of ERK activation dictates cell fate requires deciphering mechanisms encompassing protein stability, transcription factors downstream of ERK, and the chromatin landscape.
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Affiliation(s)
- Xavier Deschênes-Simard
- Montreal University Hospital Center (CHUM), Université de Montréal, Montréal, QC H3T 1J4, Canada;
| | - Mohan Malleshaiah
- Department of Biochemistry and Molecular Medicine, Université de Montréal, Montréal, QC H3T 1J4, Canada;
- Montreal Clinical Research Institute (IRCM), Montréal, QC H2W 1R7, Canada
| | - Gerardo Ferbeyre
- Montreal Clinical Research Institute (IRCM), Montréal, QC H2W 1R7, Canada
- Montreal Cancer Institute, CR-CHUM, Université de Montréal, Montréal, QC H3T 1J4, Canada
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20
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Mandal J, Yu ZC, Shih IM, Wang TL. ARID1A loss activates MAPK signaling via DUSP4 downregulation. J Biomed Sci 2023; 30:94. [PMID: 38071325 PMCID: PMC10709884 DOI: 10.1186/s12929-023-00985-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Accepted: 11/12/2023] [Indexed: 12/18/2023] Open
Abstract
BACKGROUND ARID1A, a tumor suppressor gene encoding BAF250, a protein participating in chromatin remodeling, is frequently mutated in endometrium-related malignancies, including ovarian or uterine clear cell carcinoma (CCC) and endometrioid carcinoma (EMCA). However, how ARID1A mutations alter downstream signaling to promote tumor development is yet to be established. METHODS We used RNA-sequencing (RNA-seq) to explore transcriptomic changes in isogenic human endometrial epithelial cells after deleting ARID1A. Chromatin immunoprecipitation sequencing (ChIP-seq) was employed to assess the active or repressive histone marks on DUSP4 promoter and regulatory regions. We validated our findings using genetically engineered murine endometroid carcinoma models, human endometroid carcinoma tissues, and in silico approaches. RESULTS RNA-seq revealed the downregulation of the MAPK phosphatase dual-specificity phosphatase 4 (DUSP4) in ARID1A-deficient cells. ChIP-seq demonstrated decreased histone acetylation marks (H3K27Ac, H3K9Ac) on DUSP4 regulatory regions as one of the causes for DUSP4 downregulation in ARID1A-deficient cells. Ectopic DUSP4 expression decreased cell proliferation, and pharmacologically inhibiting the MAPK pathway significantly mitigated tumor formation in vivo. CONCLUSIONS Our findings suggest that ARID1A protein transcriptionally modulates DUSP4 expression by remodeling chromatin, subsequently inactivating the MAPK pathway, leading to tumor suppression. The ARID1A-DUSP4-MAPK axis may be further considered for developing targeted therapies against ARID1A-mutated cancers.
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Affiliation(s)
- Jayaprakash Mandal
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Gynecology and Obstetrics, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Zheng-Cheng Yu
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Gynecology and Obstetrics, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Ie-Ming Shih
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
- Department of Gynecology and Obstetrics, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
- Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
| | - Tian-Li Wang
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
- Department of Gynecology and Obstetrics, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
- Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
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21
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Ryan CJ, Devakumar LPS, Pettitt SJ, Lord CJ. Complex synthetic lethality in cancer. Nat Genet 2023; 55:2039-2048. [PMID: 38036785 DOI: 10.1038/s41588-023-01557-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Accepted: 10/04/2023] [Indexed: 12/02/2023]
Abstract
The concept of synthetic lethality has been widely applied to identify therapeutic targets in cancer, with varying degrees of success. The standard approach normally involves identifying genetic interactions between two genes, a driver and a target. In reality, however, most cancer synthetic lethal effects are likely complex and also polygenic, being influenced by the environment in addition to involving contributions from multiple genes. By acknowledging and delineating this complexity, we describe in this article how the success rate in cancer drug discovery and development could be improved.
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Affiliation(s)
- Colm J Ryan
- Conway Institute and School of Computer Science, University College Dublin, Dublin, Ireland.
| | - Lovely Paul Solomon Devakumar
- The CRUK Gene Function Laboratory and Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, UK.
| | - Stephen J Pettitt
- The CRUK Gene Function Laboratory and Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, UK.
| | - Christopher J Lord
- The CRUK Gene Function Laboratory and Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, UK.
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22
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Wu X, Wang J, Kang Y, Wang Q, Qu J, Sun X, Ji D, Li Y. miR-133a-3p regulates the growth of hair follicle stem cells in white goats from the Yangtze River Delta. Anim Biotechnol 2023; 34:4559-4568. [PMID: 36752211 DOI: 10.1080/10495398.2023.2172422] [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] [Indexed: 02/09/2023]
Abstract
The Yangtze River Delta white goats are the sole goat breed producing brush hair of high quality. Owing to the particularities of its wool production, a higher demand is placed on breeding efforts for this animal. Studies on the developmental mechanisms of the aligned hair follicle stem cells (HFSCs) provide a theoretical basis for molecular breeding. In the present study, HFSCs were isolated using the technique of immunohistochemistry from the cervical spinal skin tissue samples from the fetal sheep, and the miR-133a-3p expression was confirmed using quantitative reverse-transcription PCR (RT-qPCR) and western blotting experiments from the isolated HFSCs. Additionally, the effects on the proliferation and apoptosis of HFSCs were detected using flow cytometry and 5-ethynyl-2'-deoxyuridine assays, along with other methods, following the overexpression of miR-133a-3p or its inhibition. The experimental results revealed that miR-133a-3p overexpressed could inhibit the proliferation of HFSCs and promote apoptosis by specifically targeting DUSP6. While the miR-133a-3p knockdown could promote the proliferation but inhibit the apoptosis of the HFSCs. Meanwhile, the miR-133a-3p knockdown experiments showed opposite outcomes. These results illustrate the presence of a relevant network between DUSP6 and miR-133a-3p, which regulates the production of superior-quality brush hair.
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Affiliation(s)
- Xi Wu
- Key Laboratory for Animal Genetics & Molecular Breeding of Jiangsu Province, College of Animal Science and Technology, Yangzhou University, Yangzhou, China
| | - Jian Wang
- Key Laboratory for Animal Genetics & Molecular Breeding of Jiangsu Province, College of Animal Science and Technology, Yangzhou University, Yangzhou, China
- International Joint Research Laboratory in Universities of Jiangsu Province of China for Domestic Animal Germplasm Resources and Genetic Improvement, Yangzhou University, Yangzhou, China
| | - Yan Kang
- Key Laboratory for Animal Genetics & Molecular Breeding of Jiangsu Province, College of Animal Science and Technology, Yangzhou University, Yangzhou, China
| | - Qiang Wang
- Key Laboratory for Animal Genetics & Molecular Breeding of Jiangsu Province, College of Animal Science and Technology, Yangzhou University, Yangzhou, China
| | - Jingwen Qu
- Key Laboratory for Animal Genetics & Molecular Breeding of Jiangsu Province, College of Animal Science and Technology, Yangzhou University, Yangzhou, China
| | - Xiaomei Sun
- Key Laboratory for Animal Genetics & Molecular Breeding of Jiangsu Province, College of Animal Science and Technology, Yangzhou University, Yangzhou, China
| | - Dejun Ji
- Key Laboratory for Animal Genetics & Molecular Breeding of Jiangsu Province, College of Animal Science and Technology, Yangzhou University, Yangzhou, China
| | - Yongjun Li
- Key Laboratory for Animal Genetics & Molecular Breeding of Jiangsu Province, College of Animal Science and Technology, Yangzhou University, Yangzhou, China
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23
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Mellis IA, Bodkin N, Melzer ME, Goyal Y. Prevalence of and gene regulatory constraints on transcriptional adaptation in single cells. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.14.553318. [PMID: 37645989 PMCID: PMC10462021 DOI: 10.1101/2023.08.14.553318] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/01/2023]
Abstract
Cells and tissues have a remarkable ability to adapt to genetic perturbations via a variety of molecular mechanisms. Nonsense-induced transcriptional compensation, a form of transcriptional adaptation, has recently emerged as one such mechanism, in which nonsense mutations in a gene can trigger upregulation of related genes, possibly conferring robustness at cellular and organismal levels. However, beyond a handful of developmental contexts and curated sets of genes, to date, no comprehensive genome-wide investigation of this behavior has been undertaken for mammalian cell types and contexts. Moreover, how the regulatory-level effects of inherently stochastic compensatory gene networks contribute to phenotypic penetrance in single cells remains unclear. Here we combine computational analysis of existing datasets with stochastic mathematical modeling and machine learning to uncover the widespread prevalence of transcriptional adaptation in mammalian systems and the diverse single-cell manifestations of minimal compensatory gene networks. Regulon gene expression analysis of a pooled single-cell genetic perturbation dataset recapitulates important model predictions. Our integrative approach uncovers several putative hits-genes demonstrating possible transcriptional adaptation-to follow up on experimentally, and provides a formal quantitative framework to test and refine models of transcriptional adaptation.
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Affiliation(s)
- Ian A. Mellis
- Department of Pathology and Cell Biology, Columbia University Vagelos College of Physicians and Surgeons, New York, NY, USA
- Aaron Diamond AIDS Research Center, Columbia University Vagelos College of Physicians and Surgeons, New York, NY, USA
| | - Nicholas Bodkin
- Department of Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
- Center for Synthetic Biology, Northwestern University, Chicago, IL, USA
- Robert H. Lurie Comprehensive Cancer Center, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Madeline E. Melzer
- Department of Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
- Center for Synthetic Biology, Northwestern University, Chicago, IL, USA
- Robert H. Lurie Comprehensive Cancer Center, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Yogesh Goyal
- Department of Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
- Center for Synthetic Biology, Northwestern University, Chicago, IL, USA
- Robert H. Lurie Comprehensive Cancer Center, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
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24
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Klemm S, Evert K, Utpatel K, Muggli A, Simile MM, Chen X, Evert M, Calvisi DF, Scheiter A. Identification of DUSP4/6 overexpression as a potential rheostat to NRAS-induced hepatocarcinogenesis. BMC Cancer 2023; 23:1086. [PMID: 37946160 PMCID: PMC10636894 DOI: 10.1186/s12885-023-11577-9] [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: 04/10/2023] [Accepted: 10/27/2023] [Indexed: 11/12/2023] Open
Abstract
BACKGROUND Upregulation of the mitogen-activated protein kinase (MAPK) cascade is common in hepatocellular carcinoma (HCC). Neuroblastoma RAS viral oncogene homolog (NRAS) is mutated in a small percentage of HCC and is hitherto considered insufficient for hepatocarcinogenesis. We aimed to characterize the process of N-Ras-dependent carcinogenesis in the liver and to identify potential therapeutic vulnerabilities. METHODS NRAS V12 plasmid was delivered into the mouse liver via hydrodynamic tail vein injection (HTVI). The resulting tumours, preneoplastic lesions, and normal tissue were characterized by NanoString® gene expression analysis, Western Blot, and Immunohistochemistry (IHC). The results were further confirmed by in vitro analyses of HCC cell lines. RESULTS HTVI with NRAS V12 plasmid resulted in the gradual formation of preneoplastic and neoplastic lesions in the liver three months post-injection. These lesions mostly showed characteristics of HCC, with some exceptions of spindle cell/ cholangiocellular differentiation. Progressive upregulation of the RAS/RAF/MEK/ERK signalling was detectable in the lesions by Western Blot and IHC. NanoString® gene expression analysis of preneoplastic and tumorous tissue revealed a gradual overexpression of the cancer stem cell marker CD133 and Dual Specificity Phosphatases 4 and 6 (DUSP4/6). In vitro, transfection of HCC cell lines with NRAS V12 plasmid resulted in a coherent upregulation of DUSP4 and DUSP6. Paradoxically, this upregulation in PLC/PRF/5 cells was accompanied by a downregulation of phosphorylated extracellular-signal-regulated kinase (pERK), suggesting an overshooting compensation. Silencing of DUSP4 and DUSP6 increased proliferation in HCC cell lines. CONCLUSIONS Contrary to prior assumptions, the G12V NRAS mutant form is sufficient to elicit hepatocarcinogenesis in the mouse. Furthermore, the upregulation of the MAPK cascade was paralleled by the overexpression of DUSP4, DUSP6, and CD133 in vivo and in vitro. Therefore, DUSP4 and DUSP6 might fine-tune the excessive MAPK activation, a mechanism that can potentially be harnessed therapeutically.
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Affiliation(s)
- Sophie Klemm
- Institute of Pathology, University of Regensburg, Regensburg, Germany
| | - Katja Evert
- Institute of Pathology, University of Regensburg, Regensburg, Germany
| | - Kirsten Utpatel
- Institute of Pathology, University of Regensburg, Regensburg, Germany
| | - Alexandra Muggli
- Institute of Pathology, University of Regensburg, Regensburg, Germany
| | - Maria M Simile
- Department of Medicine, Surgery, and Pharmacy, University of Sassari, Sassari, Italy
| | - Xin Chen
- Cancer Biology Program, University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Matthias Evert
- Institute of Pathology, University of Regensburg, Regensburg, Germany
| | - Diego F Calvisi
- Institute of Pathology, University of Regensburg, Regensburg, Germany
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25
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Huang X, Zhu H, Lu W, Cao L, Fang Z, Che L, Lin Y, Xu S, Zhuo Y, Hua L, Jiang X, Sun M, Wu D, Feng B. Acute Endoplasmic Reticulum Stress Suppresses Hepatic Gluconeogenesis by Stimulating MAPK Phosphatase 3 Degradation. Int J Mol Sci 2023; 24:15561. [PMID: 37958545 PMCID: PMC10647389 DOI: 10.3390/ijms242115561] [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: 08/30/2023] [Revised: 10/10/2023] [Accepted: 10/23/2023] [Indexed: 11/15/2023] Open
Abstract
Drug-induced liver injury (DILI) is a widespread and harmful disease, and is closely linked to acute endoplasmic reticulum (ER) stress. Previous reports have shown that acute ER stress can suppress hepatic gluconeogenesis and even leads to hypoglycemia. However, the mechanism is still unclear. MAPK phosphatase 3 (MKP-3) is a positive regulator for gluconeogenesis. Thus, this study was conducted to investigate the role of MKP-3 in the suppression of gluconeogenesis by acute ER stress, as well as the regulatory role of acute ER stress on the expression of MKP-3. Results showed that acute ER stress induced by tunicamycin significantly suppressed gluconeogenesis in both hepatocytes and mouse liver, reduced glucose production level in hepatocytes, and decreased fasting blood glucose level in mice. Additionally, the protein level of MKP-3 was reduced by acute ER stress in both hepatocytes and mouse liver. Mkp-3 deficiency eliminated the inhibitory effect of acute ER stress on gluconeogenesis in hepatocytes. Moreover, the reduction effect of acute ER stress on blood glucose level and hepatic glucose 6-phosphatase (G6pc) expression was not observed in the liver-specific Mkp-3 knockout mice. Furthermore, activation of protein kinase R-like ER kinase (PERK) decreased the MKP-3 protein level, while inactivation of PERK abolished the reduction effect of acute ER stress on the MKP-3 protein level in hepatocytes. Taken together, our study suggested that acute ER stress could suppress hepatic gluconeogenesis by stimulating MKP-3 degradation via PERK, at least partially. Thus, MKP-3 might be a therapeutic target for DILI-related hypoglycemia.
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Affiliation(s)
- Xiaohua Huang
- Animal Nutrition Institute, Sichuan Agricultural University, Chengdu 611130, China; (X.H.); (H.Z.); (W.L.); (L.C.); (Z.F.); (L.C.); (Y.L.); (S.X.); (Y.Z.); (L.H.); (X.J.)
- Key Laboratory of Animal Disease-Resistant Nutrition of Ministry of Education, Sichuan Agricultural University, Chengdu 611130, China
| | - Heng Zhu
- Animal Nutrition Institute, Sichuan Agricultural University, Chengdu 611130, China; (X.H.); (H.Z.); (W.L.); (L.C.); (Z.F.); (L.C.); (Y.L.); (S.X.); (Y.Z.); (L.H.); (X.J.)
- Key Laboratory of Animal Disease-Resistant Nutrition of Ministry of Education, Sichuan Agricultural University, Chengdu 611130, China
| | - Wei Lu
- Animal Nutrition Institute, Sichuan Agricultural University, Chengdu 611130, China; (X.H.); (H.Z.); (W.L.); (L.C.); (Z.F.); (L.C.); (Y.L.); (S.X.); (Y.Z.); (L.H.); (X.J.)
| | - Lei Cao
- Animal Nutrition Institute, Sichuan Agricultural University, Chengdu 611130, China; (X.H.); (H.Z.); (W.L.); (L.C.); (Z.F.); (L.C.); (Y.L.); (S.X.); (Y.Z.); (L.H.); (X.J.)
| | - Zhengfeng Fang
- Animal Nutrition Institute, Sichuan Agricultural University, Chengdu 611130, China; (X.H.); (H.Z.); (W.L.); (L.C.); (Z.F.); (L.C.); (Y.L.); (S.X.); (Y.Z.); (L.H.); (X.J.)
| | - Lianqiang Che
- Animal Nutrition Institute, Sichuan Agricultural University, Chengdu 611130, China; (X.H.); (H.Z.); (W.L.); (L.C.); (Z.F.); (L.C.); (Y.L.); (S.X.); (Y.Z.); (L.H.); (X.J.)
| | - Yan Lin
- Animal Nutrition Institute, Sichuan Agricultural University, Chengdu 611130, China; (X.H.); (H.Z.); (W.L.); (L.C.); (Z.F.); (L.C.); (Y.L.); (S.X.); (Y.Z.); (L.H.); (X.J.)
| | - Shengyu Xu
- Animal Nutrition Institute, Sichuan Agricultural University, Chengdu 611130, China; (X.H.); (H.Z.); (W.L.); (L.C.); (Z.F.); (L.C.); (Y.L.); (S.X.); (Y.Z.); (L.H.); (X.J.)
| | - Yong Zhuo
- Animal Nutrition Institute, Sichuan Agricultural University, Chengdu 611130, China; (X.H.); (H.Z.); (W.L.); (L.C.); (Z.F.); (L.C.); (Y.L.); (S.X.); (Y.Z.); (L.H.); (X.J.)
| | - Lun Hua
- Animal Nutrition Institute, Sichuan Agricultural University, Chengdu 611130, China; (X.H.); (H.Z.); (W.L.); (L.C.); (Z.F.); (L.C.); (Y.L.); (S.X.); (Y.Z.); (L.H.); (X.J.)
| | - Xuemei Jiang
- Animal Nutrition Institute, Sichuan Agricultural University, Chengdu 611130, China; (X.H.); (H.Z.); (W.L.); (L.C.); (Z.F.); (L.C.); (Y.L.); (S.X.); (Y.Z.); (L.H.); (X.J.)
| | - Mengmeng Sun
- College of Science, Sichuan Agricultural University, Chengdu 611130, China;
| | - De Wu
- Animal Nutrition Institute, Sichuan Agricultural University, Chengdu 611130, China; (X.H.); (H.Z.); (W.L.); (L.C.); (Z.F.); (L.C.); (Y.L.); (S.X.); (Y.Z.); (L.H.); (X.J.)
- Key Laboratory of Animal Disease-Resistant Nutrition of Ministry of Education, Sichuan Agricultural University, Chengdu 611130, China
| | - Bin Feng
- Animal Nutrition Institute, Sichuan Agricultural University, Chengdu 611130, China; (X.H.); (H.Z.); (W.L.); (L.C.); (Z.F.); (L.C.); (Y.L.); (S.X.); (Y.Z.); (L.H.); (X.J.)
- Key Laboratory of Animal Disease-Resistant Nutrition of Ministry of Education, Sichuan Agricultural University, Chengdu 611130, China
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26
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Sharma S, Chung CY, Uryu S, Petrovic J, Cao J, Rickard A, Nady N, Greasley S, Johnson E, Brodsky O, Khan S, Wang H, Wang Z, Zhang Y, Tsaparikos K, Chen L, Mazurek A, Lapek J, Kung PP, Sutton S, Richardson PF, Greenwald EC, Yamazaki S, Jones R, Maegley KA, Bingham P, Lam H, Stupple AE, Kamal A, Chueh A, Cuzzupe A, Morrow BJ, Ren B, Carrasco-Pozo C, Tan CW, Bhuva DD, Allan E, Surgenor E, Vaillant F, Pehlivanoglu H, Falk H, Whittle JR, Newman J, Cursons J, Doherty JP, White KL, MacPherson L, Devlin M, Dennis ML, Hattarki MK, De Silva M, Camerino MA, Butler MS, Dolezal O, Pilling P, Foitzik R, Stupple PA, Lagiakos HR, Walker SR, Hediyeh-Zadeh S, Nuttall S, Spall SK, Charman SA, Connor T, Peat TS, Avery VM, Bozikis YE, Yang Y, Zhang M, Monahan BJ, Voss AK, Thomas T, Street IP, Dawson SJ, Dawson MA, Lindeman GJ, Davis MJ, Visvader JE, Paul TA. Discovery of a highly potent, selective, orally bioavailable inhibitor of KAT6A/B histone acetyltransferases with efficacy against KAT6A-high ER+ breast cancer. Cell Chem Biol 2023; 30:1191-1210.e20. [PMID: 37557181 DOI: 10.1016/j.chembiol.2023.07.005] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Revised: 02/07/2023] [Accepted: 07/16/2023] [Indexed: 08/11/2023]
Abstract
KAT6A, and its paralog KAT6B, are histone lysine acetyltransferases (HAT) that acetylate histone H3K23 and exert an oncogenic role in several tumor types including breast cancer where KAT6A is frequently amplified/overexpressed. However, pharmacologic targeting of KAT6A to achieve therapeutic benefit has been a challenge. Here we describe identification of a highly potent, selective, and orally bioavailable KAT6A/KAT6B inhibitor CTx-648 (PF-9363), derived from a benzisoxazole series, which demonstrates anti-tumor activity in correlation with H3K23Ac inhibition in KAT6A over-expressing breast cancer. Transcriptional and epigenetic profiling studies show reduced RNA Pol II binding and downregulation of genes involved in estrogen signaling, cell cycle, Myc and stem cell pathways associated with CTx-648 anti-tumor activity in ER-positive (ER+) breast cancer. CTx-648 treatment leads to potent tumor growth inhibition in ER+ breast cancer in vivo models, including models refractory to endocrine therapy, highlighting the potential for targeting KAT6A in ER+ breast cancer.
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Affiliation(s)
- Shikhar Sharma
- Pfizer, Oncology Research & Development, San Diego, CA 92121, USA.
| | - Chi-Yeh Chung
- Pfizer, Oncology Research & Development, San Diego, CA 92121, USA
| | - Sean Uryu
- Pfizer, Oncology Research & Development, San Diego, CA 92121, USA
| | - Jelena Petrovic
- Pfizer, Oncology Research & Development, San Diego, CA 92121, USA
| | - Joan Cao
- Pfizer, Oncology Research & Development, San Diego, CA 92121, USA
| | - Amanda Rickard
- Pfizer, Oncology Research & Development, San Diego, CA 92121, USA
| | - Nataliya Nady
- Pfizer, Oncology Research & Development, San Diego, CA 92121, USA
| | | | - Eric Johnson
- Pfizer, Oncology Research & Development, San Diego, CA 92121, USA
| | - Oleg Brodsky
- Pfizer, Oncology Research & Development, San Diego, CA 92121, USA
| | - Showkhin Khan
- Pfizer, Oncology Research & Development, San Diego, CA 92121, USA
| | - Hui Wang
- Pfizer, Oncology Research & Development, San Diego, CA 92121, USA
| | - Zhenxiong Wang
- Pfizer, Oncology Research & Development, San Diego, CA 92121, USA
| | - Yong Zhang
- Pfizer, Oncology Research & Development, San Diego, CA 92121, USA
| | | | - Lei Chen
- Pfizer, Oncology Research & Development, San Diego, CA 92121, USA
| | - Anthony Mazurek
- Pfizer, Oncology Research & Development, San Diego, CA 92121, USA
| | - John Lapek
- Pfizer, Oncology Research & Development, San Diego, CA 92121, USA
| | - Pei-Pei Kung
- Pfizer, Oncology Research & Development, San Diego, CA 92121, USA
| | - Scott Sutton
- Pfizer, Oncology Research & Development, San Diego, CA 92121, USA
| | | | - Eric C Greenwald
- Pfizer, Oncology Research & Development, San Diego, CA 92121, USA
| | - Shinji Yamazaki
- Pfizer, Oncology Research & Development, San Diego, CA 92121, USA
| | - Rhys Jones
- Pfizer, Oncology Research & Development, San Diego, CA 92121, USA
| | - Karen A Maegley
- Pfizer, Oncology Research & Development, San Diego, CA 92121, USA
| | - Patrick Bingham
- Pfizer, Oncology Research & Development, San Diego, CA 92121, USA
| | - Hieu Lam
- Pfizer, Oncology Research & Development, San Diego, CA 92121, USA
| | - Alexandra E Stupple
- Cancer Therapeutics CRC, Melbourne, VIC 3000, Australia; Medicinal Chemistry and Centre for Drug Candidate Optimisation, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, VIC 3052, Australia; CANThera Discovery, Melbourne, VIC 3000, Australia
| | - Aileen Kamal
- The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia
| | - Anderly Chueh
- Cancer Therapeutics CRC, Melbourne, VIC 3000, Australia; The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia
| | - Anthony Cuzzupe
- SYNthesis Med Chem (Australia) Pty Ltd, Bio21 Institute, 30 Flemington Road, Parkville, VIC 3052, Australia
| | - Benjamin J Morrow
- Medicinal Chemistry and Centre for Drug Candidate Optimisation, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, VIC 3052, Australia; Cancer Therapeutics CRC, Melbourne, VIC 3000, Australia
| | - Bin Ren
- Cancer Therapeutics CRC, Melbourne, VIC 3000, Australia; Commonwealth Scientific and Industrial Research Organisation (CSIRO), Parkville, VIC 3052, Australia
| | - Catalina Carrasco-Pozo
- Cancer Therapeutics CRC, Melbourne, VIC 3000, Australia; Discovery Biology, Centre for Cellular Phenomics, Griffith University, Brisbane QLD 4111, Australia
| | - Chin Wee Tan
- The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia; Department of Medical Biology, The University of Melbourne, Parkville, VIC 3052, Australia
| | - Dharmesh D Bhuva
- The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia; Department of Medical Biology, The University of Melbourne, Parkville, VIC 3052, Australia
| | - Elizabeth Allan
- Cancer Therapeutics CRC, Melbourne, VIC 3000, Australia; The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia
| | - Elliot Surgenor
- The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia
| | - François Vaillant
- The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia; Department of Medical Biology, The University of Melbourne, Parkville, VIC 3052, Australia
| | - Havva Pehlivanoglu
- The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia
| | - Hendrik Falk
- Cancer Therapeutics CRC, Melbourne, VIC 3000, Australia; The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia; Department of Medical Biology, The University of Melbourne, Parkville, VIC 3052, Australia; Commonwealth Scientific and Industrial Research Organisation (CSIRO), Parkville, VIC 3052, Australia
| | - James R Whittle
- The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia; Department of Medical Biology, The University of Melbourne, Parkville, VIC 3052, Australia
| | - Janet Newman
- Commonwealth Scientific and Industrial Research Organisation (CSIRO), Parkville, VIC 3052, Australia
| | - Joseph Cursons
- The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia
| | - Judy P Doherty
- Peter MacCallum Cancer Centre, Melbourne VIC 3000, Australia; Sir Peter MacCallum Department of Oncology, The University of Melbourne, Parkville, VIC 3052, Australia
| | - Karen L White
- Cancer Therapeutics CRC, Melbourne, VIC 3000, Australia; Medicinal Chemistry and Centre for Drug Candidate Optimisation, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, VIC 3052, Australia
| | - Laura MacPherson
- Peter MacCallum Cancer Centre, Melbourne VIC 3000, Australia; Sir Peter MacCallum Department of Oncology, The University of Melbourne, Parkville, VIC 3052, Australia
| | - Mark Devlin
- Cancer Therapeutics CRC, Melbourne, VIC 3000, Australia; Peter MacCallum Cancer Centre, Melbourne VIC 3000, Australia; Sir Peter MacCallum Department of Oncology, The University of Melbourne, Parkville, VIC 3052, Australia
| | - Matthew L Dennis
- Cancer Therapeutics CRC, Melbourne, VIC 3000, Australia; Commonwealth Scientific and Industrial Research Organisation (CSIRO), Parkville, VIC 3052, Australia
| | - Meghan K Hattarki
- Commonwealth Scientific and Industrial Research Organisation (CSIRO), Parkville, VIC 3052, Australia
| | - Melanie De Silva
- Cancer Therapeutics CRC, Melbourne, VIC 3000, Australia; The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia
| | - Michelle A Camerino
- Cancer Therapeutics CRC, Melbourne, VIC 3000, Australia; Medicinal Chemistry and Centre for Drug Candidate Optimisation, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, VIC 3052, Australia
| | - Miriam S Butler
- Cancer Therapeutics CRC, Melbourne, VIC 3000, Australia; Peter MacCallum Cancer Centre, Melbourne VIC 3000, Australia; Sir Peter MacCallum Department of Oncology, The University of Melbourne, Parkville, VIC 3052, Australia
| | - Olan Dolezal
- Cancer Therapeutics CRC, Melbourne, VIC 3000, Australia; Commonwealth Scientific and Industrial Research Organisation (CSIRO), Parkville, VIC 3052, Australia
| | - Patricia Pilling
- Commonwealth Scientific and Industrial Research Organisation (CSIRO), Parkville, VIC 3052, Australia
| | - Richard Foitzik
- Cancer Therapeutics CRC, Melbourne, VIC 3000, Australia; Medicinal Chemistry and Centre for Drug Candidate Optimisation, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, VIC 3052, Australia; OncologyOne Pty Ltd, Melbourne, VIC 3000, Australia
| | - Paul A Stupple
- Cancer Therapeutics CRC, Melbourne, VIC 3000, Australia; Medicinal Chemistry and Centre for Drug Candidate Optimisation, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, VIC 3052, Australia; CANThera Discovery, Melbourne, VIC 3000, Australia
| | - H Rachel Lagiakos
- Cancer Therapeutics CRC, Melbourne, VIC 3000, Australia; Medicinal Chemistry and Centre for Drug Candidate Optimisation, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, VIC 3052, Australia
| | - Scott R Walker
- Cancer Therapeutics CRC, Melbourne, VIC 3000, Australia; Medicinal Chemistry and Centre for Drug Candidate Optimisation, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, VIC 3052, Australia; Commonwealth Scientific and Industrial Research Organisation (CSIRO), Parkville, VIC 3052, Australia
| | - Soroor Hediyeh-Zadeh
- The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia; Department of Medical Biology, The University of Melbourne, Parkville, VIC 3052, Australia
| | - Stewart Nuttall
- Cancer Therapeutics CRC, Melbourne, VIC 3000, Australia; Commonwealth Scientific and Industrial Research Organisation (CSIRO), Parkville, VIC 3052, Australia
| | - Sukhdeep K Spall
- Cancer Therapeutics CRC, Melbourne, VIC 3000, Australia; The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia
| | - Susan A Charman
- Cancer Therapeutics CRC, Melbourne, VIC 3000, Australia; Medicinal Chemistry and Centre for Drug Candidate Optimisation, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, VIC 3052, Australia
| | - Theresa Connor
- Cancer Therapeutics CRC, Melbourne, VIC 3000, Australia; Peter MacCallum Cancer Centre, Melbourne VIC 3000, Australia; Sir Peter MacCallum Department of Oncology, The University of Melbourne, Parkville, VIC 3052, Australia
| | - Thomas S Peat
- Cancer Therapeutics CRC, Melbourne, VIC 3000, Australia; Commonwealth Scientific and Industrial Research Organisation (CSIRO), Parkville, VIC 3052, Australia
| | - Vicky M Avery
- Cancer Therapeutics CRC, Melbourne, VIC 3000, Australia; Discovery Biology, Centre for Cellular Phenomics, Griffith University, Brisbane QLD 4111, Australia
| | - Ylva E Bozikis
- Cancer Therapeutics CRC, Melbourne, VIC 3000, Australia; Medicinal Chemistry and Centre for Drug Candidate Optimisation, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, VIC 3052, Australia
| | - Yuqing Yang
- The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia; Department of Medical Biology, The University of Melbourne, Parkville, VIC 3052, Australia
| | - Ming Zhang
- Cancer Therapeutics CRC, Melbourne, VIC 3000, Australia; The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia
| | - Brendon J Monahan
- Cancer Therapeutics CRC, Melbourne, VIC 3000, Australia; The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia; Department of Medical Biology, The University of Melbourne, Parkville, VIC 3052, Australia; CANThera Discovery, Melbourne, VIC 3000, Australia
| | - Anne K Voss
- The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia; Department of Medical Biology, The University of Melbourne, Parkville, VIC 3052, Australia
| | - Tim Thomas
- The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia; Department of Medical Biology, The University of Melbourne, Parkville, VIC 3052, Australia
| | - Ian P Street
- Cancer Therapeutics CRC, Melbourne, VIC 3000, Australia; The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia; Department of Medical Biology, The University of Melbourne, Parkville, VIC 3052, Australia; OncologyOne Pty Ltd, Melbourne, VIC 3000, Australia; Children's Cancer Institute, Randwick, NSW 2031, Australia; University of New South Wales, Randwick, NSW 2021, Australia
| | - Sarah-Jane Dawson
- Peter MacCallum Cancer Centre, Melbourne VIC 3000, Australia; Sir Peter MacCallum Department of Oncology, The University of Melbourne, Parkville, VIC 3052, Australia
| | - Mark A Dawson
- Peter MacCallum Cancer Centre, Melbourne VIC 3000, Australia; Sir Peter MacCallum Department of Oncology, The University of Melbourne, Parkville, VIC 3052, Australia
| | - Geoffrey J Lindeman
- The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia; Department of Medicine, Royal Melbourne Hospital, The University of Melbourne, Parkville, VIC 3010, Australia; Parkville Familial Cancer Centre and Department of Medical Oncology, The Royal Melbourne Hospital and Peter MacCallum Cancer Centre, Parkville, VIC 3050, Australia
| | - Melissa J Davis
- The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia; Department of Medical Biology, The University of Melbourne, Parkville, VIC 3052, Australia; Department of Clinical Pathology, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Parkville, VIC 3010, Australia
| | - Jane E Visvader
- The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia; Department of Medical Biology, The University of Melbourne, Parkville, VIC 3052, Australia
| | - Thomas A Paul
- Pfizer, Oncology Research & Development, San Diego, CA 92121, USA.
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27
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Pu M, Cheng K, Li X, Xin Y, Wei L, Jin S, Zheng W, Peng G, Tang Q, Zhou J, Zhang Y. Using graph-based model to identify cell specific synthetic lethal effects. Comput Struct Biotechnol J 2023; 21:5099-5110. [PMID: 37920819 PMCID: PMC10618116 DOI: 10.1016/j.csbj.2023.10.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Revised: 10/05/2023] [Accepted: 10/06/2023] [Indexed: 11/04/2023] Open
Abstract
Synthetic lethal (SL) pairs are pairs of genes whose simultaneous loss-of-function results in cell death, while a damaging mutation of either gene alone does not affect the cell's survival. This makes SL pairs attractive targets for precision cancer therapies, as targeting the unimpaired gene of the SL pair can selectively kill cancer cells that already harbor the impaired gene. Limited by the difficulty of finding true SL pairs, especially on specific cell types, current computational approaches provide only limited insights because of overlooking the crucial aspects of cellular context dependency and mechanistic understanding of SL pairs. As a result, the identification of SL targets still relies on expensive, time-consuming experimental approaches. In this work, we applied cell-line specific multi-omics data to a specially designed deep learning model to predict cell-line specific SL pairs. Through incorporating multiple types of cell-specific omics data with a self-attention module, we represent gene relationships as graphs. Our approach achieves the prediction of SL pairs in a cell-specific manner and demonstrates the potential to facilitate the discovery of cell-specific SL targets for cancer therapeutics, providing a tool to unearth mechanisms underlying the origin of SL in cancer biology. The code and data of our approach can be found at https://github.com/promethiume/SLwise.
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Affiliation(s)
| | - Kaiyang Cheng
- StoneWise, AI, Ltd., Beijing, China
- Nanjing University of Chinese Medicine, Shanghai, China
| | - Xiaorong Li
- StoneWise, AI, Ltd., Beijing, China
- Minzu University of China, Beijing, China
| | | | | | - Sutong Jin
- StoneWise, AI, Ltd., Beijing, China
- Harbin Institute of Technology, Weihai, China
| | | | | | - Qihong Tang
- StoneWise, AI, Ltd., Beijing, China
- Guilin University of Electronic Science and Technology, Guangxi, China
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28
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Champhekar A, Heymans R, Saco J, Turon Font G, Gonzalez C, Gao A, Pham J, Lee J, Maryoung R, Medina E, Campbell KM, Karin D, Austin D, Damioseaux R, Ribas A. ERK mediates interferon gamma-induced melanoma cell death. Mol Cancer 2023; 22:165. [PMID: 37803324 PMCID: PMC10557262 DOI: 10.1186/s12943-023-01868-x] [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: 08/22/2023] [Accepted: 09/25/2023] [Indexed: 10/08/2023] Open
Abstract
BACKGROUND Interferon-gamma (IFNγ) exerts potent growth inhibitory effects on a wide range of cancer cells through unknown signaling pathways. We pursued complementary screening approaches to characterize the growth inhibition pathway. METHODS We performed chemical genomics and whole genome targeting CRISPR/Cas9 screens using patient-derived melanoma lines to uncover essential nodes in the IFNγ-mediated growth inhibition pathway. We used transcriptomic profiling to identify cell death pathways activated upon IFNγ exposure. Live imaging experiments coupled with apoptosis assays confirmed the involvement of these pathways in IFNγ-mediated cell death. RESULTS We show that IFNγ signaling activated ERK. Blocking ERK activation rescued IFNγ-mediated apoptosis in 17 of 23 (~ 74%) cell lines representing BRAF, NRAS, NF1 mutant, and triple wild type subtypes of cutaneous melanoma. ERK signaling induced a stress response, ultimately leading to apoptosis through the activity of DR5 and NOXA proteins. CONCLUSIONS Our results provide a new understanding of the IFNγ growth inhibition pathway, which will be crucial in defining mechanisms of immunotherapy response and resistance.
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Affiliation(s)
- Ameya Champhekar
- Division of Hematology-Oncology, Department of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA.
| | - Rachel Heymans
- Division of Hematology-Oncology, Department of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Justin Saco
- Division of Hematology-Oncology, Department of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Department of Molecular and Medical Pharmacology, University of California, Los Angeles, CA, 90095, USA
| | - Guillem Turon Font
- Division of Hematology-Oncology, Department of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Cynthia Gonzalez
- Division of Hematology-Oncology, Department of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Anne Gao
- Division of Hematology-Oncology, Department of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - John Pham
- Division of Hematology-Oncology, Department of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - June Lee
- Division of Hematology-Oncology, Department of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Ryan Maryoung
- Division of Hematology-Oncology, Department of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Egmidio Medina
- Division of Hematology-Oncology, Department of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Katie M Campbell
- Division of Hematology-Oncology, Department of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Daniel Karin
- Division of Hematology-Oncology, Department of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Department of Molecular and Medical Pharmacology, University of California, Los Angeles, CA, 90095, USA
| | - David Austin
- California NanoSystems Institute, University of California, Los Angeles, CA, 90095, USA
| | - Robert Damioseaux
- Department of Molecular and Medical Pharmacology, University of California, Los Angeles, CA, 90095, USA
- California NanoSystems Institute, University of California, Los Angeles, CA, 90095, USA
- Jonsson Comprehensive Cancer Center, Los Angeles, CA, 90095, USA
- Department of Bioengineering, Samueli School of Engineering, University of California, Los Angeles, CA, 90095, USA
| | - Antoni Ribas
- Division of Hematology-Oncology, Department of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA.
- Jonsson Comprehensive Cancer Center, Los Angeles, CA, 90095, USA.
- Division of Surgical Oncology, Department of Surgery, University of California, Los Angeles, Los Angeles, CA, 90095, USA.
- Parker Institute for Cancer Immunotherapy, San Francisco, CA, 94129, USA.
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29
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Stuart DD, Guzman-Perez A, Brooijmans N, Jackson EL, Kryukov GV, Friedman AA, Hoos A. Precision Oncology Comes of Age: Designing Best-in-Class Small Molecules by Integrating Two Decades of Advances in Chemistry, Target Biology, and Data Science. Cancer Discov 2023; 13:2131-2149. [PMID: 37712571 PMCID: PMC10551669 DOI: 10.1158/2159-8290.cd-23-0280] [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: 03/06/2023] [Revised: 04/27/2023] [Accepted: 07/28/2023] [Indexed: 09/16/2023]
Abstract
Small-molecule drugs have enabled the practice of precision oncology for genetically defined patient populations since the first approval of imatinib in 2001. Scientific and technology advances over this 20-year period have driven the evolution of cancer biology, medicinal chemistry, and data science. Collectively, these advances provide tools to more consistently design best-in-class small-molecule drugs against known, previously undruggable, and novel cancer targets. The integration of these tools and their customization in the hands of skilled drug hunters will be necessary to enable the discovery of transformational therapies for patients across a wider spectrum of cancers. SIGNIFICANCE Target-centric small-molecule drug discovery necessitates the consideration of multiple approaches to identify chemical matter that can be optimized into drug candidates. To do this successfully and consistently, drug hunters require a comprehensive toolbox to avoid following the "law of instrument" or Maslow's hammer concept where only one tool is applied regardless of the requirements of the task. Combining our ever-increasing understanding of cancer and cancer targets with the technological advances in drug discovery described below will accelerate the next generation of small-molecule drugs in oncology.
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Affiliation(s)
| | | | | | | | | | | | - Axel Hoos
- Scorpion Therapeutics, Boston, Massachusetts
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30
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Wood KC. Hyperactivation of oncogenic driver pathways as a precision therapeutic strategy. Nat Genet 2023; 55:1613-1614. [PMID: 37749245 DOI: 10.1038/s41588-023-01493-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/27/2023]
Affiliation(s)
- Kris C Wood
- Department of Pharmacology and Cancer Biology, Duke University, Durham, NC, USA.
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31
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Chang L, Jung NY, Atari A, Rodriguez DJ, Kesar D, Song TY, Rees MG, Ronan M, Li R, Ruiz P, Chaturantabut S, Ito T, van Tienen LM, Tseng YY, Roth JA, Sellers WR. Systematic profiling of conditional pathway activation identifies context-dependent synthetic lethalities. Nat Genet 2023; 55:1709-1720. [PMID: 37749246 DOI: 10.1038/s41588-023-01515-7] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Accepted: 08/22/2023] [Indexed: 09/27/2023]
Abstract
The paradigm of cancer-targeted therapies has focused largely on inhibition of critical pathways in cancer. Conversely, conditional activation of signaling pathways as a new source of selective cancer vulnerabilities has not been deeply characterized. In this study, we sought to systematically identify context-specific gene-activation-induced lethalities in cancer. To this end, we developed a method for gain-of-function genetic perturbations simultaneously across ~500 barcoded cancer cell lines. Using this approach, we queried the pan-cancer vulnerability landscape upon activating ten key pathway nodes, revealing selective activation dependencies of MAPK and PI3K pathways associated with specific biomarkers. Notably, we discovered new pathway hyperactivation dependencies in subsets of APC-mutant colorectal cancers where further activation of the WNT pathway by APC knockdown or direct β-catenin overexpression led to robust antitumor effects in xenograft and patient-derived organoid models. Together, this study reveals a new class of conditional gene-activation dependencies in cancer.
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Affiliation(s)
- Liang Chang
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Nancy Y Jung
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Adel Atari
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | | | - Devishi Kesar
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Tian-Yu Song
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | | | - Melissa Ronan
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Ruitong Li
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Paloma Ruiz
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Saireudee Chaturantabut
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- Department of Biopharmacy, Faculty of Pharmacy, Silpakorn University, Nakhon Pathom, Thailand
| | - Takahiro Ito
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Laurens M van Tienen
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Yuen-Yi Tseng
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | | | - William R Sellers
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA.
- Harvard Medical School, Boston, MA, USA.
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32
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Griffith AL, Zheng F, McGee AV, Miller NW, Szegletes ZM, Reint G, Gademann F, Nwolah I, Hegde M, Liu YV, Goodale A, Doench JG. Optimization of Cas12a for multiplexed genome-scale transcriptional activation. CELL GENOMICS 2023; 3:100387. [PMID: 37719144 PMCID: PMC10504673 DOI: 10.1016/j.xgen.2023.100387] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/10/2023] [Revised: 06/28/2023] [Accepted: 08/01/2023] [Indexed: 09/19/2023]
Abstract
Cas12a CRISPR technology, unlike Cas9, allows for facile multiplexing of guide RNAs from a single transcript, simplifying combinatorial perturbations. While Cas12a has been implemented for multiplexed knockout genetic screens, it has yet to be optimized for CRISPR activation (CRISPRa) screens in human cells. Here, we develop a new Cas12a-based transactivation domain (TAD) recruitment system using the ALFA nanobody and demonstrate simultaneous activation of up to four genes. We screen a genome-wide library to identify modulators of growth and MEK inhibition, and we compare these results with those obtained with open reading frame (ORF) overexpression and Cas9-based CRISPRa. We find that the activity of multiplexed arrays is largely predictable from the best-performing guide and provide criteria for selecting active guides. We anticipate that these results will greatly accelerate the exploration of gene function and combinatorial phenotypes at scale.
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Affiliation(s)
- Audrey L. Griffith
- Genetic Perturbation Platform, Broad Institute of MIT and Harvard, 75 Ames St., Cambridge, MA 02142, USA
| | - Fengyi Zheng
- Genetic Perturbation Platform, Broad Institute of MIT and Harvard, 75 Ames St., Cambridge, MA 02142, USA
| | - Abby V. McGee
- Genetic Perturbation Platform, Broad Institute of MIT and Harvard, 75 Ames St., Cambridge, MA 02142, USA
| | - Nathan W. Miller
- Genetic Perturbation Platform, Broad Institute of MIT and Harvard, 75 Ames St., Cambridge, MA 02142, USA
| | - Zsofia M. Szegletes
- Genetic Perturbation Platform, Broad Institute of MIT and Harvard, 75 Ames St., Cambridge, MA 02142, USA
| | - Ganna Reint
- Genetic Perturbation Platform, Broad Institute of MIT and Harvard, 75 Ames St., Cambridge, MA 02142, USA
| | - Fabian Gademann
- Genetic Perturbation Platform, Broad Institute of MIT and Harvard, 75 Ames St., Cambridge, MA 02142, USA
| | - Ifunanya Nwolah
- Genetic Perturbation Platform, Broad Institute of MIT and Harvard, 75 Ames St., Cambridge, MA 02142, USA
| | - Mudra Hegde
- Genetic Perturbation Platform, Broad Institute of MIT and Harvard, 75 Ames St., Cambridge, MA 02142, USA
| | - Yanjing V. Liu
- Genetic Perturbation Platform, Broad Institute of MIT and Harvard, 75 Ames St., Cambridge, MA 02142, USA
| | - Amy Goodale
- Genetic Perturbation Platform, Broad Institute of MIT and Harvard, 75 Ames St., Cambridge, MA 02142, USA
| | - John G. Doench
- Genetic Perturbation Platform, Broad Institute of MIT and Harvard, 75 Ames St., Cambridge, MA 02142, USA
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Anvar NE, Lin C, Ma X, Wilson LL, Steger R, Sangree AK, Colic M, Wang SH, Doench JG, Hart T. Efficient gene knockout and genetic interactions: the IN4MER CRISPR/Cas12a multiplex knockout platform. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.03.522655. [PMID: 36712129 PMCID: PMC9881895 DOI: 10.1101/2023.01.03.522655] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
Genetic interactions mediate the emergence of phenotype from genotype, but initial technologies for combinatorial genetic perturbation in mammalian cells suffer from inefficiency and are challenging to scale. Recent focus on paralog synthetic lethality in cancer cells offers an opportunity to evaluate different approaches and improve on the state of the art. Here we report a meta-analysis of CRISPR genetic interactions screens, identifying a candidate set of background-independent paralog synthetic lethals, and find that the Cas12a platform provides superior sensitivity and assay replicability. We demonstrate that Cas12a can independently target up to four genes from a single guide array, and we build on this knowledge by constructing a genome-scale library that expresses arrays of four guides per clone, a platform we call 'in4mer'. Our genome-scale human library, with only 49k clones, is substantially smaller than a typical CRISPR/Cas9 monogenic library while also targeting more than four thousand paralog pairs, triples, and quads. Proof of concept screens in four cell lines demonstrate discrimination of core and context-dependent essential genes similar to that of state-of-the-art CRISPR/Cas9 libraries, as well as detection of synthetic lethal and masking/buffering genetic interactions between paralogs of various family sizes, a capability not offered by any extant library. Importantly, the in4mer platform offers a fivefold reduction in the number of clones required to assay genetic interactions, dramatically improving the cost and effort required for these studies.
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Affiliation(s)
- Nazanin Esmaeili Anvar
- Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
- Graduate School of Biomedical Sciences, The University of Texas MD Anderson Cancer Center UTHealth, Houston, TX, USA
| | - Chenchu Lin
- Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Xingdi Ma
- Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
- Graduate School of Biomedical Sciences, The University of Texas MD Anderson Cancer Center UTHealth, Houston, TX, USA
| | - Lori L. Wilson
- Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Ryan Steger
- Genetic Perturbation Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Annabel K. Sangree
- Genetic Perturbation Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Medina Colic
- Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Sidney H. Wang
- Center for Human Genetics, The Brown foundation Institute of Molecular Medicine, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - John G. Doench
- Genetic Perturbation Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Traver Hart
- Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
- Department of Cancer Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
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Renaux A, Terwagne C, Cochez M, Tiddi I, Nowé A, Lenaerts T. A knowledge graph approach to predict and interpret disease-causing gene interactions. BMC Bioinformatics 2023; 24:324. [PMID: 37644440 PMCID: PMC10463539 DOI: 10.1186/s12859-023-05451-5] [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: 06/07/2023] [Accepted: 08/22/2023] [Indexed: 08/31/2023] Open
Abstract
BACKGROUND Understanding the impact of gene interactions on disease phenotypes is increasingly recognised as a crucial aspect of genetic disease research. This trend is reflected by the growing amount of clinical research on oligogenic diseases, where disease manifestations are influenced by combinations of variants on a few specific genes. Although statistical machine-learning methods have been developed to identify relevant genetic variant or gene combinations associated with oligogenic diseases, they rely on abstract features and black-box models, posing challenges to interpretability for medical experts and impeding their ability to comprehend and validate predictions. In this work, we present a novel, interpretable predictive approach based on a knowledge graph that not only provides accurate predictions of disease-causing gene interactions but also offers explanations for these results. RESULTS We introduce BOCK, a knowledge graph constructed to explore disease-causing genetic interactions, integrating curated information on oligogenic diseases from clinical cases with relevant biomedical networks and ontologies. Using this graph, we developed a novel predictive framework based on heterogenous paths connecting gene pairs. This method trains an interpretable decision set model that not only accurately predicts pathogenic gene interactions, but also unveils the patterns associated with these diseases. A unique aspect of our approach is its ability to offer, along with each positive prediction, explanations in the form of subgraphs, revealing the specific entities and relationships that led to each pathogenic prediction. CONCLUSION Our method, built with interpretability in mind, leverages heterogenous path information in knowledge graphs to predict pathogenic gene interactions and generate meaningful explanations. This not only broadens our understanding of the molecular mechanisms underlying oligogenic diseases, but also presents a novel application of knowledge graphs in creating more transparent and insightful predictors for genetic research.
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Affiliation(s)
- Alexandre Renaux
- Interuniversity Institute of Bioinformatics in Brussels, Université Libre de Bruxelles - Vrije Universiteit Brussel, Brussels, Belgium
- Machine Learning Group, Université Libre de Bruxelles, Brussels, Belgium
- Artificial Intelligence lab, Vrije Universiteit Brussel, Brussels, Belgium
| | - Chloé Terwagne
- Interuniversity Institute of Bioinformatics in Brussels, Université Libre de Bruxelles - Vrije Universiteit Brussel, Brussels, Belgium
- Machine Learning Group, Université Libre de Bruxelles, Brussels, Belgium
| | - Michael Cochez
- Computer Science, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Discovery Lab, Elsevier, Amsterdam, The Netherlands
| | - Ilaria Tiddi
- Computer Science, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Ann Nowé
- Interuniversity Institute of Bioinformatics in Brussels, Université Libre de Bruxelles - Vrije Universiteit Brussel, Brussels, Belgium
- Artificial Intelligence lab, Vrije Universiteit Brussel, Brussels, Belgium
| | - Tom Lenaerts
- Interuniversity Institute of Bioinformatics in Brussels, Université Libre de Bruxelles - Vrije Universiteit Brussel, Brussels, Belgium
- Machine Learning Group, Université Libre de Bruxelles, Brussels, Belgium
- Artificial Intelligence lab, Vrije Universiteit Brussel, Brussels, Belgium
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35
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Zhang Y, Remillard D, Onubogu U, Karakyriakou B, Asiaban JN, Ramos AR, Bowland K, Bishop TR, Barta PA, Nance S, Durbin AD, Ott CJ, Janiszewska M, Cravatt BF, Erb MA. Collateral lethality between HDAC1 and HDAC2 exploits cancer-specific NuRD complex vulnerabilities. Nat Struct Mol Biol 2023; 30:1160-1171. [PMID: 37488358 PMCID: PMC10529074 DOI: 10.1038/s41594-023-01041-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Accepted: 06/22/2023] [Indexed: 07/26/2023]
Abstract
Transcriptional co-regulators have been widely pursued as targets for disrupting oncogenic gene regulatory programs. However, many proteins in this target class are universally essential for cell survival, which limits their therapeutic window. Here we unveil a genetic interaction between histone deacetylase 1 (HDAC1) and HDAC2, wherein each paralog is synthetically lethal with hemizygous deletion of the other. This collateral synthetic lethality is caused by recurrent chromosomal deletions that occur in diverse solid and hematological malignancies, including neuroblastoma and multiple myeloma. Using genetic disruption or dTAG-mediated degradation, we show that targeting HDAC2 suppresses the growth of HDAC1-deficient neuroblastoma in vitro and in vivo. Mechanistically, we find that targeted degradation of HDAC2 in these cells prompts the degradation of several members of the nucleosome remodeling and deacetylase (NuRD) complex, leading to diminished chromatin accessibility at HDAC2-NuRD-bound sites of the genome and impaired control of enhancer-associated transcription. Furthermore, we reveal that several of the degraded NuRD complex subunits are dependencies in neuroblastoma and multiple myeloma, providing motivation to develop paralog-selective HDAC1 or HDAC2 degraders that could leverage HDAC1/2 synthetic lethality to target NuRD vulnerabilities. Altogether, we identify HDAC1/2 collateral synthetic lethality as a potential therapeutic target and reveal an unexplored mechanism for targeting NuRD-associated cancer dependencies.
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Affiliation(s)
- Yuxiang Zhang
- Department of Chemistry, The Scripps Research Institute, La Jolla, CA, USA
| | - David Remillard
- Department of Chemistry, The Scripps Research Institute, La Jolla, CA, USA
| | - Ugoma Onubogu
- Department of Molecular Medicine, The Herbert Wertheim UF Scripps Institute for Biomedical Innovation & Technology, Jupiter, FL, USA
| | | | - Joshua N Asiaban
- Department of Chemistry, The Scripps Research Institute, La Jolla, CA, USA
| | - Anissa R Ramos
- Department of Chemistry, The Scripps Research Institute, La Jolla, CA, USA
| | - Kirsten Bowland
- Department of Chemistry, The Scripps Research Institute, La Jolla, CA, USA
| | - Timothy R Bishop
- Department of Chemistry, The Scripps Research Institute, La Jolla, CA, USA
| | - Paige A Barta
- Department of Chemistry, The Scripps Research Institute, La Jolla, CA, USA
| | - Stephanie Nance
- Department of Oncology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Adam D Durbin
- Department of Oncology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Christopher J Ott
- Massachusetts General Hospital Cancer Center, Charlestown, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT & Harvard, Cambridge, MA, USA
| | - Michalina Janiszewska
- Department of Molecular Medicine, The Herbert Wertheim UF Scripps Institute for Biomedical Innovation & Technology, Jupiter, FL, USA
| | - Benjamin F Cravatt
- Department of Chemistry, The Scripps Research Institute, La Jolla, CA, USA
| | - Michael A Erb
- Department of Chemistry, The Scripps Research Institute, La Jolla, CA, USA.
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36
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Xin Y, Zhang Y. Paralog-based synthetic lethality: rationales and applications. Front Oncol 2023; 13:1168143. [PMID: 37350942 PMCID: PMC10282757 DOI: 10.3389/fonc.2023.1168143] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Accepted: 05/23/2023] [Indexed: 06/24/2023] Open
Abstract
Tumor cells can result from gene mutations and over-expression. Synthetic lethality (SL) offers a desirable setting where cancer cells bearing one mutated gene of an SL gene pair can be specifically targeted by disrupting the function of the other genes, while leaving wide-type normal cells unharmed. Paralogs, a set of homologous genes that have diverged from each other as a consequence of gene duplication, make the concept of SL feasible as the loss of one gene does not affect the cell's survival. Furthermore, homozygous loss of paralogs in tumor cells is more frequent than singletons, making them ideal SL targets. Although high-throughput CRISPR-Cas9 screenings have uncovered numerous paralog-based SL pairs, the unclear mechanisms of targeting these gene pairs and the difficulty in finding specific inhibitors that exclusively target a single but not both paralogs hinder further clinical development. Here, we review the potential mechanisms of paralog-based SL given their function and genetic combination, and discuss the challenge and application prospects of paralog-based SL in cancer therapeutic discovery.
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37
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Weiskittel TM, Cao A, Meng-Lin K, Lehmann Z, Feng B, Correia C, Zhang C, Wisniewski P, Zhu S, Yong Ung C, Li H. Network Biology-Inspired Machine Learning Features Predict Cancer Gene Targets and Reveal Target Coordinating Mechanisms. Pharmaceuticals (Basel) 2023; 16:752. [PMID: 37242535 PMCID: PMC10223789 DOI: 10.3390/ph16050752] [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: 04/03/2023] [Revised: 05/08/2023] [Accepted: 05/11/2023] [Indexed: 05/28/2023] Open
Abstract
Anticipating and understanding cancers' need for specific gene activities is key for novel therapeutic development. Here we utilized DepMap, a cancer gene dependency screen, to demonstrate that machine learning combined with network biology can produce robust algorithms that both predict what genes a cancer is dependent on and what network features coordinate such gene dependencies. Using network topology and biological annotations, we constructed four groups of novel engineered machine learning features that produced high accuracies when predicting binary gene dependencies. We found that in all examined cancer types, F1 scores were greater than 0.90, and model accuracy remained robust under multiple hyperparameter tests. We then deconstructed these models to identify tumor type-specific coordinators of gene dependency and identified that in certain cancers, such as thyroid and kidney, tumors' dependencies are highly predicted by gene connectivity. In contrast, other histologies relied on pathway-based features such as lung, where gene dependencies were highly predictive by associations with cell death pathway genes. In sum, we show that biologically informed network features can be a valuable and robust addition to predictive pharmacology models while simultaneously providing mechanistic insights.
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Affiliation(s)
- Taylor M Weiskittel
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic College of Medicine and Science, Rochester, MN 55905, USA
- Mayo Clinic Alix School of Medicine, Mayo Clinic College of Medicine and Science, Rochester, MN 55905, USA
| | - Andrew Cao
- Department of Computer Science, Duke University, Durham, NC 27708, USA
| | - Kevin Meng-Lin
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic College of Medicine and Science, Rochester, MN 55905, USA
| | - Zachary Lehmann
- Department of Chemistry, Biochemistry and Physics, South Dakota State University, Brookings, SD 57006, USA
| | - Benjamin Feng
- Department of Molecular Cell and Developmental Biology, University of California, Los Angeles, CA 90095, USA
| | - Cristina Correia
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic College of Medicine and Science, Rochester, MN 55905, USA
| | - Cheng Zhang
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic College of Medicine and Science, Rochester, MN 55905, USA
| | - Philip Wisniewski
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic College of Medicine and Science, Rochester, MN 55905, USA
| | - Shizhen Zhu
- Department of Biochemistry and Molecular Biology, Mayo Clinic College of Medicine and Science, Rochester, MN 55905, USA
| | - Choong Yong Ung
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic College of Medicine and Science, Rochester, MN 55905, USA
| | - Hu Li
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic College of Medicine and Science, Rochester, MN 55905, USA
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38
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Cetin R, Wegner M, Luwisch L, Saud S, Achmedov T, Süsser S, Vera-Guapi A, Müller K, Matthess Y, Quandt E, Schaubeck S, Beisel CL, Kaulich M. Optimized metrics for orthogonal combinatorial CRISPR screens. Sci Rep 2023; 13:7405. [PMID: 37149686 PMCID: PMC10164157 DOI: 10.1038/s41598-023-34597-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Accepted: 05/04/2023] [Indexed: 05/08/2023] Open
Abstract
CRISPR-based gene perturbation enables unbiased investigations of single and combinatorial genotype-to-phenotype associations. In light of efforts to map combinatorial gene dependencies at scale, choosing an efficient and robust CRISPR-associated (Cas) nuclease is of utmost importance. Even though SpCas9 and AsCas12a are widely used for single, combinatorial, and orthogonal screenings, side-by-side comparisons remain sparse. Here, we systematically compared combinatorial SpCas9, AsCas12a, and CHyMErA in hTERT-immortalized retinal pigment epithelial cells and extracted performance-critical parameters for combinatorial and orthogonal CRISPR screens. Our analyses identified SpCas9 to be superior to enhanced and optimized AsCas12a, with CHyMErA being largely inactive in the tested conditions. Since AsCas12a contains RNA processing activity, we used arrayed dual-gRNAs to improve AsCas12a and CHyMErA applications. While this negatively influenced the effect size range of combinatorial AsCas12a applications, it enhanced the performance of CHyMErA. This improved performance, however, was limited to AsCas12a dual-gRNAs, as SpCas9 gRNAs remained largely inactive. To avoid the use of hybrid gRNAs for orthogonal applications, we engineered the multiplex SpCas9-enAsCas12a approach (multiSPAS) that avoids RNA processing for efficient orthogonal gene editing.
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Affiliation(s)
- Ronay Cetin
- Institute of Biochemistry II, Faculty of Medicine, Goethe University Frankfurt, Theodor-Stern-Kai 7, 60590, Frankfurt am Main, Germany
| | - Martin Wegner
- Institute of Biochemistry II, Faculty of Medicine, Goethe University Frankfurt, Theodor-Stern-Kai 7, 60590, Frankfurt am Main, Germany
| | - Leah Luwisch
- Institute of Biochemistry II, Faculty of Medicine, Goethe University Frankfurt, Theodor-Stern-Kai 7, 60590, Frankfurt am Main, Germany
| | - Sarada Saud
- Institute of Biochemistry II, Faculty of Medicine, Goethe University Frankfurt, Theodor-Stern-Kai 7, 60590, Frankfurt am Main, Germany
| | - Tatjana Achmedov
- Helmholtz-Centre for Infection Research (HZI), Helmholtz Institute for RNA-Based Infection Research (HIRI), 97080, Würzburg, Germany
| | - Sebastian Süsser
- Institute of Biochemistry II, Faculty of Medicine, Goethe University Frankfurt, Theodor-Stern-Kai 7, 60590, Frankfurt am Main, Germany
| | - Antonella Vera-Guapi
- Institute of Biochemistry II, Faculty of Medicine, Goethe University Frankfurt, Theodor-Stern-Kai 7, 60590, Frankfurt am Main, Germany
| | - Konstantin Müller
- Institute of Biochemistry II, Faculty of Medicine, Goethe University Frankfurt, Theodor-Stern-Kai 7, 60590, Frankfurt am Main, Germany
| | - Yves Matthess
- Institute of Biochemistry II, Faculty of Medicine, Goethe University Frankfurt, Theodor-Stern-Kai 7, 60590, Frankfurt am Main, Germany
| | - Eva Quandt
- Institute of Biochemistry II, Faculty of Medicine, Goethe University Frankfurt, Theodor-Stern-Kai 7, 60590, Frankfurt am Main, Germany
- Faculty of Medicine and Health Sciences, Universitat Internacional de Catalunya, 08195, Barcelona, Spain
| | - Simone Schaubeck
- Institute of Biochemistry II, Faculty of Medicine, Goethe University Frankfurt, Theodor-Stern-Kai 7, 60590, Frankfurt am Main, Germany
| | - Chase L Beisel
- Helmholtz-Centre for Infection Research (HZI), Helmholtz Institute for RNA-Based Infection Research (HIRI), 97080, Würzburg, Germany
- Medical Faculty, University of Würzburg, 97080, Würzburg, Germany
| | - Manuel Kaulich
- Institute of Biochemistry II, Faculty of Medicine, Goethe University Frankfurt, Theodor-Stern-Kai 7, 60590, Frankfurt am Main, Germany.
- Frankfurt Cancer Institute, 60596, Frankfurt am Main, Germany.
- Cardio-Pulmonary Institute, 60590, Frankfurt am Main, Germany.
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39
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Ryan CJ, Mehta I, Kebabci N, Adams DJ. Targeting synthetic lethal paralogs in cancer. Trends Cancer 2023; 9:397-409. [PMID: 36890003 DOI: 10.1016/j.trecan.2023.02.002] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2022] [Revised: 02/02/2023] [Accepted: 02/07/2023] [Indexed: 03/08/2023]
Abstract
Synthetic lethal interactions, where mutation of one gene renders cells sensitive to inhibition of another gene, can be exploited for the development of targeted therapeutics in cancer. Pairs of duplicate genes (paralogs) often share common functionality and hence are a potentially rich source of synthetic lethal interactions. Because the majority of human genes have paralogs, exploiting such interactions could be a widely applicable approach for targeting gene loss in cancer. Moreover, existing small-molecule drugs may exploit synthetic lethal interactions by inhibiting multiple paralogs simultaneously. Consequently, the identification of synthetic lethal interactions between paralogs could be extremely informative for drug development. Here we review approaches to identify such interactions and discuss some of the challenges of exploiting them.
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Affiliation(s)
- Colm J Ryan
- Conway Institute and School of Computer Science, University College Dublin, Dublin, Ireland; Systems Biology Ireland, University College Dublin, Dublin, Ireland.
| | - Ishan Mehta
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, UK
| | - Narod Kebabci
- Conway Institute and School of Computer Science, University College Dublin, Dublin, Ireland; Science Foundation Ireland (SFI) Centre for Research Training in Genomics Data Science, University College Dublin, Dublin, Ireland
| | - David J Adams
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, UK
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Abstract
Over the past decade, melanoma has led the field in new cancer treatments, with impressive gains in on-treatment survival but more modest improvements in overall survival. Melanoma presents heterogeneity and transcriptional plasticity that recapitulates distinct melanocyte developmental states and phenotypes, allowing it to adapt to and eventually escape even the most advanced treatments. Despite remarkable advances in our understanding of melanoma biology and genetics, the melanoma cell of origin is still fiercely debated because both melanocyte stem cells and mature melanocytes can be transformed. Animal models and high-throughput single-cell sequencing approaches have opened new opportunities to address this question. Here, we discuss the melanocytic journey from the neural crest, where they emerge as melanoblasts, to the fully mature pigmented melanocytes resident in several tissues. We describe a new understanding of melanocyte biology and the different melanocyte subpopulations and microenvironments they inhabit, and how this provides unique insights into melanoma initiation and progression. We highlight recent findings on melanoma heterogeneity and transcriptional plasticity and their implications for exciting new research areas and treatment opportunities. The lessons from melanocyte biology reveal how cells that are present to protect us from the damaging effects of ultraviolet radiation reach back to their origins to become a potentially deadly cancer.
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Affiliation(s)
- Patricia P Centeno
- Molecular Oncology Group, Cancer Research UK Manchester Institute, The University of Manchester, Alderley Park, UK
| | - Valeria Pavet
- Molecular Oncology Group, Cancer Research UK Manchester Institute, The University of Manchester, Alderley Park, UK
| | - Richard Marais
- Molecular Oncology Group, Cancer Research UK Manchester Institute, The University of Manchester, Alderley Park, UK.
- Oncodrug Ltd, Alderly Park, Macclesfield, UK.
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Zhang X, Zhan S, Guan X, Zhang Y, Lu J, Yu Y, Jin Y, Yang Y, Chu P, Hong E, Yang H, Ren H, Geng D, Wang Y, Zhou P, Guo Y, Chang Y. TAF1D promotes proliferation by transcriptionally activating G2/M phase-related genes in MYCN-amplified neuroblastoma. Cancer Sci 2023. [PMID: 37094904 DOI: 10.1111/cas.15815] [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: 11/24/2022] [Revised: 03/18/2023] [Accepted: 04/05/2023] [Indexed: 04/26/2023] Open
Abstract
High-risk neuroblastoma (HR-NB) is an aggressive childhood cancer that responds poorly to currently available therapies and is associated with only about a 50% 5-year survival rate. MYCN amplification is a critical driver of these aggressive tumors, but so far there have not been any approved treatments to effectively treat HR-NB by targeting MYCN or its downstream effectors. Thus, the identification of novel molecular targets and therapeutic strategies to treat children diagnosed with HR-NB represents an urgent unmet medical need. Here, we conducted a targeted siRNA screening and identified TATA box-binding protein-associated factor RNA polymerase I subunit D, TAF1D, as a critical regulator of the cell cycle and proliferation in HR-NB cells. Analysis of three independent primary NB cohorts determined that high TAF1D expression correlated with MYCN-amplified, high-risk disease and poor clinical outcomes. TAF1D knockdown more robustly inhibited cell proliferation in MYCN-amplified NB cells compared with MYCN-non-amplified NB cells, as well as suppressed colony formation and inhibited tumor growth in a xenograft mouse model of MYCN-amplified NB. RNA-seq analysis revealed that TAF1D knockdown downregulates the expression of genes associated with the G2/M transition, including the master cell-cycle regulator, cell-cycle-dependent kinase 1 (CDK1), resulting in cell-cycle arrest at G2/M. Our findings demonstrate that TAF1D is a key oncogenic regulator of MYCN-amplified HR-NB and suggest that therapeutic targeting of TAF1D may be a viable strategy to treat HR-NB patients by blocking cell-cycle progression and the proliferation of tumor cells.
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Affiliation(s)
- Xuan Zhang
- Beijing Key Laboratory for Pediatric Diseases of Otolaryngology, Head and Neck Surgery, MOE Key Laboratory of Major Diseases in Children, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China
| | - Shijia Zhan
- Beijing Key Laboratory for Pediatric Diseases of Otolaryngology, Head and Neck Surgery, MOE Key Laboratory of Major Diseases in Children, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China
| | - Xiaoxing Guan
- Department of Pathology, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China
| | - Yanli Zhang
- Imaging Core Facility, Technology Center for Protein Science, Tsinghua University, Beijing, China
| | - Jie Lu
- Beijing Key Laboratory for Pediatric Diseases of Otolaryngology, Head and Neck Surgery, MOE Key Laboratory of Major Diseases in Children, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China
| | - Yongbo Yu
- Beijing Key Laboratory for Pediatric Diseases of Otolaryngology, Head and Neck Surgery, MOE Key Laboratory of Major Diseases in Children, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China
| | - Yaqiong Jin
- Beijing Key Laboratory for Pediatric Diseases of Otolaryngology, Head and Neck Surgery, MOE Key Laboratory of Major Diseases in Children, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China
| | - Yeran Yang
- Beijing Key Laboratory for Pediatric Diseases of Otolaryngology, Head and Neck Surgery, MOE Key Laboratory of Major Diseases in Children, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China
| | - Ping Chu
- Beijing Key Laboratory for Pediatric Diseases of Otolaryngology, Head and Neck Surgery, MOE Key Laboratory of Major Diseases in Children, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China
| | - Enyu Hong
- Beijing Key Laboratory for Pediatric Diseases of Otolaryngology, Head and Neck Surgery, MOE Key Laboratory of Major Diseases in Children, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China
| | - Hui Yang
- Beijing Key Laboratory for Pediatric Diseases of Otolaryngology, Head and Neck Surgery, MOE Key Laboratory of Major Diseases in Children, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China
| | - Huimin Ren
- Beijing Key Laboratory for Pediatric Diseases of Otolaryngology, Head and Neck Surgery, MOE Key Laboratory of Major Diseases in Children, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China
| | - Di Geng
- Beijing Key Laboratory for Pediatric Diseases of Otolaryngology, Head and Neck Surgery, MOE Key Laboratory of Major Diseases in Children, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China
| | - Yadi Wang
- Beijing Key Laboratory for Pediatric Diseases of Otolaryngology, Head and Neck Surgery, MOE Key Laboratory of Major Diseases in Children, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China
| | - Pingping Zhou
- Beijing Key Laboratory for Pediatric Diseases of Otolaryngology, Head and Neck Surgery, MOE Key Laboratory of Major Diseases in Children, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China
| | - Yongli Guo
- Beijing Key Laboratory for Pediatric Diseases of Otolaryngology, Head and Neck Surgery, MOE Key Laboratory of Major Diseases in Children, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China
| | - Yan Chang
- Beijing Key Laboratory for Pediatric Diseases of Otolaryngology, Head and Neck Surgery, MOE Key Laboratory of Major Diseases in Children, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China
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Palmerini E, Gambarotti M, Italiano A, Nathenson MJ, Ratan R, Dileo P, Provenzano S, Jones RL, DuBois SG, Martin-Broto J, de Alava E, Baldi GG, Grignani G, Ferraresi V, Brunello A, Paoluzzi L, Bertulli R, Hindi N, Montemurro M, Rothermundt C, Cocchi S, Salguero-Aranda C, Donati D, Martin JD, Abdelhamid Ahmed AH, Mazzocca A, Carretta E, Cesari M, Pierini M, Righi A, Sbaraglia M, Laginestra MA, Scotlandi K, Dei Tos AP, Ibrahim T, Stacchiotti S, Vincenzi B. A global collaboRAtive study of CIC-rearranged, BCOR::CCNB3-rearranged and other ultra-rare unclassified undifferentiated small round cell sarcomas (GRACefUl). Eur J Cancer 2023; 183:11-23. [PMID: 36791667 DOI: 10.1016/j.ejca.2023.01.003] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2022] [Revised: 12/16/2022] [Accepted: 01/04/2023] [Indexed: 01/19/2023]
Abstract
BACKGROUND Undifferentiated small round cell sarcomas (URCSs) represent a diagnostic challenge, and their optimal treatment is unknown. We aimed to define the clinical characteristics, treatment, and outcome of URCS patients. METHODS URCS patients treated from 1983 to 2019 at 21 worldwide sarcoma reference centres were retrospectively identified. Based on molecular assessment, cases were classified as follows: (1) CIC-rearranged round cell sarcomas, (2) BCOR::CCNB3-rearranged round cell sarcomas, (3) unclassified URCSs. Treatment, prognostic factors and outcome were reviewed. RESULTS In total, 148 patients were identified [88/148 (60%) CIC-rearranged sarcoma (median age 32 years, range 7-78), 33/148 (22%) BCOR::CCNB3-rearranged (median age 17 years, range 5-91), and 27/148 (18%) unclassified URCSs (median age 37 years, range 4-70)]. One hundred-one (68.2%) cases presented with localised disease; 47 (31.8%) had metastases at diagnosis. Male prevalence, younger age, bone primary site, and a low rate of synchronous metastases were observed in BCOR::CCNB3-rearranged cases. Local treatment was surgery in 67/148 (45%) patients, and surgery + radiotherapy in 52/148 (35%). Chemotherapy was given to 122/148 (82%) patients. At a 42.7-month median follow-up, the 3-year overall survival (OS) was 92.2% (95% CI 71.5-98.0) in BCOR::CCNB3 patients, 39.6% (95% CI 27.7-51.3) in CIC-rearranged sarcomas, and 78.7% in unclassified URCSs (95% CI 56.1-90.6; p < 0.0001). CONCLUSIONS This study is the largest conducted in URCS and confirms major differences in outcomes between URCS subtypes. A full molecular assessment should be undertaken when a diagnosis of URCS is suspected. Prospective studies are needed to better define the optimal treatment strategy in each URCS subtype.
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Affiliation(s)
- Emanuela Palmerini
- Osteoncology, Soft Tissue and Bone Sarcomas, Innovative Therapy Unit, IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy.
| | - Marco Gambarotti
- Department of Pathology, IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy
| | - Antoine Italiano
- Early Phase Trial and Sarcoma Unit, Institut Bergonié, Bordeaux, France; Faculty of Medicine, University of Bordeaux, Bordeaux, France
| | | | - Ravin Ratan
- Department of Sarcoma Medical Oncology, The University of Texas, MD Anderson Cancer Center, Houston, TX, USA
| | - Palma Dileo
- London Sarcoma Service, University College London Hospital, London, UK
| | - Salvatore Provenzano
- Adult mesenchymal tumours and rare cancers unit, Department of Medical Oncology, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - Robin L Jones
- Sarcoma Unit, The Royal Marsden and Institute of Cancer Research, London, UK
| | - Steven G DuBois
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Javier Martin-Broto
- Medical Oncology Department, University Hospital Fundación Jimenez Diaz, Madrid, Spain; University Hospital General de Villalba, Madrid, Spain; Instituto de Investigacion Sanitaria Fundacion Jimenez Diaz (IIS/FJD; UAM), Madrid, Spain
| | - Enrique de Alava
- IBIS Instituto de Biomedicina de Sevilla, Sevilla, Spain; Vigem Del Rocio University Hospital/CSIC/University of Seville/CIBERONC, Spain; Department of Normal and Pathological Cytology and Histology, School of Medicine, University of Seville, Spain
| | | | - Giovanni Grignani
- Candiolo Cancer Institute, FPO-IRCCS, Candiolo, Turin, Italy; Azienda Ospedaliero-Universitaria CItta della Scienza e della Salute di Torino, Torino, Italy
| | | | - Antonella Brunello
- Department of Oncology, Istituto Oncologico Veneto IOV-IRCCS, Padua, Italy
| | - Luca Paoluzzi
- Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Rossella Bertulli
- Adult mesenchymal tumours and rare cancers unit, Department of Medical Oncology, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - Nadia Hindi
- Medical Oncology Department, University Hospital Fundación Jimenez Diaz, Madrid, Spain; University Hospital General de Villalba, Madrid, Spain; Instituto de Investigacion Sanitaria Fundacion Jimenez Diaz (IIS/FJD; UAM), Madrid, Spain
| | - Michael Montemurro
- Department of Oncology, Centre Hospitalier Universitaire Vaudois, Lausanne, Switzerland
| | - Christian Rothermundt
- Department of Medical Oncology and Haematology Kantonsspital St.Gallen, St. Gallen, Switzerland
| | - Stefania Cocchi
- Department of Pathology, IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy
| | - Carmen Salguero-Aranda
- IBIS Instituto de Biomedicina de Sevilla, Sevilla, Spain; Vigem Del Rocio University Hospital/CSIC/University of Seville/CIBERONC, Spain; Department of Normal and Pathological Cytology and Histology, School of Medicine, University of Seville, Spain
| | - Davide Donati
- Department of Orthopaedic Surgery, IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy
| | - Juan D Martin
- IBIS Instituto de Biomedicina de Sevilla, Sevilla, Spain; Vigem Del Rocio University Hospital/CSIC/University of Seville/CIBERONC, Spain; Department of Normal and Pathological Cytology and Histology, School of Medicine, University of Seville, Spain
| | | | - Alessandro Mazzocca
- Department of Medical Oncology, Università Campus Bio-medico di Roma, Rome, Italy
| | - Elisa Carretta
- Department of Medicine, University of Padua, Padua, Italy
| | - Marilena Cesari
- Osteoncology, Soft Tissue and Bone Sarcomas, Innovative Therapy Unit, IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy
| | - Michela Pierini
- Osteoncology, Soft Tissue and Bone Sarcomas, Innovative Therapy Unit, IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy
| | - Alberto Righi
- Department of Pathology, IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy
| | | | - Maria A Laginestra
- Laboratory of Experimental Oncology, IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy
| | - Katia Scotlandi
- Laboratory of Experimental Oncology, IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy
| | | | - Toni Ibrahim
- Osteoncology, Soft Tissue and Bone Sarcomas, Innovative Therapy Unit, IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy
| | - Silvia Stacchiotti
- Adult mesenchymal tumours and rare cancers unit, Department of Medical Oncology, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - Bruno Vincenzi
- Department of Medical Oncology, Università Campus Bio-medico di Roma, Rome, Italy
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Ben Guebila M, Wang T, Lopes-Ramos CM, Fanfani V, Weighill D, Burkholz R, Schlauch D, Paulson JN, Altenbuchinger M, Shutta KH, Sonawane AR, Lim J, Calderer G, van IJzendoorn DGP, Morgan D, Marin A, Chen CY, Song Q, Saha E, DeMeo DL, Padi M, Platig J, Kuijjer ML, Glass K, Quackenbush J. The Network Zoo: a multilingual package for the inference and analysis of gene regulatory networks. Genome Biol 2023; 24:45. [PMID: 36894939 PMCID: PMC9999668 DOI: 10.1186/s13059-023-02877-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Accepted: 02/15/2023] [Indexed: 03/11/2023] Open
Abstract
Inference and analysis of gene regulatory networks (GRNs) require software that integrates multi-omic data from various sources. The Network Zoo (netZoo; netzoo.github.io) is a collection of open-source methods to infer GRNs, conduct differential network analyses, estimate community structure, and explore the transitions between biological states. The netZoo builds on our ongoing development of network methods, harmonizing the implementations in various computing languages and between methods to allow better integration of these tools into analytical pipelines. We demonstrate the utility using multi-omic data from the Cancer Cell Line Encyclopedia. We will continue to expand the netZoo to incorporate additional methods.
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Affiliation(s)
- Marouen Ben Guebila
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Tian Wang
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Present Address: Biology Department, Boston College, Chestnut Hill, MA, USA
| | - Camila M Lopes-Ramos
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Viola Fanfani
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Des Weighill
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Present Address: Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Rebekka Burkholz
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Present Address: CISPA Helmholtz Center for Information Security, Saarbrücken, Germany
| | - Daniel Schlauch
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Present Address: Genospace, LLC, Boston, MA, USA
| | - Joseph N Paulson
- Department of Biochemistry and Molecular Biology, Pennsylvania State University College of Medicine, Hershey, PA, USA
| | - Michael Altenbuchinger
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Present Address: Department of Medical Bioinformatics, University Medical Center Göttingen, Göttingen, Germany
| | - Katherine H Shutta
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Abhijeet R Sonawane
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Present Address: Center for Interdisciplinary Cardiovascular Sciences, Division of Cardiovascular Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - James Lim
- Department of Molecular and Cellular Biology, University of Arizona, Tucson, AZ, USA
- Present Address: Monoceros Biosystems, LLC, San Diego, CA, USA
| | - Genis Calderer
- Center for Molecular Medicine Norway, Nordic EMBL Partnership, University of Oslo, Oslo, Norway
| | - David G P van IJzendoorn
- Department of Pathology, Leiden University Medical Center, Leiden, The Netherlands
- Present Address: Department of Pathology, Stanford University School of Medicine, Palo Alto, CA, USA
| | - Daniel Morgan
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Present Address: School of Biomedical Sciences, Hong Kong University, Pokfulam, Hong Kong
| | | | - Cho-Yi Chen
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Dana-Farber Cancer Institute, Boston, MA, USA
- Present Address: Institute of Biomedical Informatics, National Yang Ming Chiao Tung University, Taipei, 112, Taiwan
| | - Qi Song
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Present Address: Computational Biology Department, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Enakshi Saha
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Dawn L DeMeo
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Megha Padi
- Department of Molecular and Cellular Biology, University of Arizona, Tucson, AZ, USA
| | - John Platig
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Marieke L Kuijjer
- Center for Molecular Medicine Norway, Nordic EMBL Partnership, University of Oslo, Oslo, Norway
- Department of Pathology, Leiden University Medical Center, Leiden, The Netherlands
- Leiden Center for Computational Oncology, Leiden University, Leiden, The Netherlands
| | - Kimberly Glass
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - John Quackenbush
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
- Dana-Farber Cancer Institute, Boston, MA, USA.
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Chromatin complex dependencies reveal targeting opportunities in leukemia. Nat Commun 2023; 14:448. [PMID: 36707513 PMCID: PMC9883437 DOI: 10.1038/s41467-023-36150-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Accepted: 01/18/2023] [Indexed: 01/28/2023] Open
Abstract
Chromatin regulators are frequently mutated in human cancer and are attractive drug targets. They include diverse proteins that share functional domains and assemble into related multi-subunit complexes. To investigate functional relationships among these regulators, here we apply combinatorial CRISPR knockouts (KOs) to test over 35,000 gene-gene pairings in leukemia cells, using a library of over 300,000 constructs. Top pairs that demonstrate either compensatory non-lethal interactions or synergistic lethality enrich for paralogs and targets that occupy the same protein complex. The screen highlights protein complex dependencies not apparent in single KO screens, for example MCM histone exchange, the nucleosome remodeling and deacetylase (NuRD) complex, and HBO1 (KAT7) complex. We explore two approaches to NuRD complex inactivation. Paralog and non-paralog combinations of the KAT7 complex emerge as synergistic lethal and specifically nominate the ING5 PHD domain as a potential therapeutic target when paired with other KAT7 complex member losses. These findings highlight the power of combinatorial screening to provide mechanistic insight and identify therapeutic targets within redundant networks.
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Sigismondo G, Arseni L, Palacio-Escat N, Hofmann TG, Seiffert M, Krijgsveld J. Multi-layered chromatin proteomics identifies cell vulnerabilities in DNA repair. Nucleic Acids Res 2023; 51:687-711. [PMID: 36629267 PMCID: PMC9881138 DOI: 10.1093/nar/gkac1264] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Revised: 12/14/2022] [Accepted: 12/19/2022] [Indexed: 01/12/2023] Open
Abstract
The DNA damage response (DDR) is essential to maintain genome stability, and its deregulation predisposes to carcinogenesis while encompassing attractive targets for cancer therapy. Chromatin governs the DDR via the concerted interplay among different layers, including DNA, histone post-translational modifications (hPTMs) and chromatin-associated proteins. Here, we employ multi-layered proteomics to characterize chromatin-mediated functional interactions of repair proteins, signatures of hPTMs and the DNA-bound proteome during DNA double-strand break (DSB) repair at high temporal resolution. Our data illuminate the dynamics of known and novel DDR-associated factors both at chromatin and at DSBs. We functionally attribute novel chromatin-associated proteins to repair by non-homologous end-joining (NHEJ), homologous recombination (HR) and DSB repair pathway choice. We reveal histone reader ATAD2, microtubule organizer TPX2 and histone methyltransferase G9A as regulators of HR and involved in poly-ADP-ribose polymerase-inhibitor sensitivity. Furthermore, we distinguish hPTMs that are globally induced by DNA damage from those specifically acquired at sites flanking DSBs (γH2AX foci-specific) and profiled their dynamics during the DDR. Integration of complementary chromatin layers implicates G9A-mediated monomethylation of H3K56 in DSBs repair via HR. Our data provide a dynamic chromatin-centered view of the DDR that can be further mined to identify novel mechanistic links and cell vulnerabilities in DSB repair.
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Affiliation(s)
- Gianluca Sigismondo
- Division of Proteomics of Stem Cells and Cancer, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Lavinia Arseni
- Division of Molecular Genetics, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Nicolàs Palacio-Escat
- Division of Proteomics of Stem Cells and Cancer, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Thomas G Hofmann
- Institute of Toxicology, University Medical Center of the Johannes Gutenberg University Mainz, 55131 Mainz, Germany
| | - Martina Seiffert
- Division of Molecular Genetics, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
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Zhang W, Liu L, Xiao X, Zhou H, Peng Z, Wang W, Huang L, Xie Y, Xu H, Tao L, Nie W, Yuan X, Liu F, Yuan Q. Identification of common molecular signatures of SARS-CoV-2 infection and its influence on acute kidney injury and chronic kidney disease. Front Immunol 2023; 14:961642. [PMID: 37026010 PMCID: PMC10070855 DOI: 10.3389/fimmu.2023.961642] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2022] [Accepted: 03/07/2023] [Indexed: 04/08/2023] Open
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the main cause of COVID-19, causing hundreds of millions of confirmed cases and more than 18.2 million deaths worldwide. Acute kidney injury (AKI) is a common complication of COVID-19 that leads to an increase in mortality, especially in intensive care unit (ICU) settings, and chronic kidney disease (CKD) is a high risk factor for COVID-19 and its related mortality. However, the underlying molecular mechanisms among AKI, CKD, and COVID-19 are unclear. Therefore, transcriptome analysis was performed to examine common pathways and molecular biomarkers for AKI, CKD, and COVID-19 in an attempt to understand the association of SARS-CoV-2 infection with AKI and CKD. Three RNA-seq datasets (GSE147507, GSE1563, and GSE66494) from the GEO database were used to detect differentially expressed genes (DEGs) for COVID-19 with AKI and CKD to search for shared pathways and candidate targets. A total of 17 common DEGs were confirmed, and their biological functions and signaling pathways were characterized by enrichment analysis. MAPK signaling, the structural pathway of interleukin 1 (IL-1), and the Toll-like receptor pathway appear to be involved in the occurrence of these diseases. Hub genes identified from the protein-protein interaction (PPI) network, including DUSP6, BHLHE40, RASGRP1, and TAB2, are potential therapeutic targets in COVID-19 with AKI and CKD. Common genes and pathways may play pathogenic roles in these three diseases mainly through the activation of immune inflammation. Networks of transcription factor (TF)-gene, miRNA-gene, and gene-disease interactions from the datasets were also constructed, and key gene regulators influencing the progression of these three diseases were further identified among the DEGs. Moreover, new drug targets were predicted based on these common DEGs, and molecular docking and molecular dynamics (MD) simulations were performed. Finally, a diagnostic model of COVID-19 was established based on these common DEGs. Taken together, the molecular and signaling pathways identified in this study may be related to the mechanisms by which SARS-CoV-2 infection affects renal function. These findings are significant for the effective treatment of COVID-19 in patients with kidney diseases.
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Affiliation(s)
- Weiwei Zhang
- Department of Nephrology, Xiangya Hospital of Central South University, Changsha, China
| | - Leping Liu
- Department of Pediatrics, The Third Xiangya Hospital of Central South University, Changsha, China
| | - Xiangcheng Xiao
- Department of Nephrology, Xiangya Hospital of Central South University, Changsha, China
| | - Hongshan Zhou
- Department of Nephrology, Xiangya Hospital of Central South University, Changsha, China
| | - Zhangzhe Peng
- Department of Nephrology, Xiangya Hospital of Central South University, Changsha, China
- Organ Fibrosis Key Lab of Hunan Province, Central South University, Changsha, China
| | - Wei Wang
- Department of Nephrology, Xiangya Hospital of Central South University, Changsha, China
- Organ Fibrosis Key Lab of Hunan Province, Central South University, Changsha, China
| | - Ling Huang
- Department of Nephrology, Xiangya Hospital of Central South University, Changsha, China
- Organ Fibrosis Key Lab of Hunan Province, Central South University, Changsha, China
| | - Yanyun Xie
- Department of Nephrology, Xiangya Hospital of Central South University, Changsha, China
- Organ Fibrosis Key Lab of Hunan Province, Central South University, Changsha, China
| | - Hui Xu
- Department of Nephrology, Xiangya Hospital of Central South University, Changsha, China
- Organ Fibrosis Key Lab of Hunan Province, Central South University, Changsha, China
| | - Lijian Tao
- Department of Nephrology, Xiangya Hospital of Central South University, Changsha, China
- Organ Fibrosis Key Lab of Hunan Province, Central South University, Changsha, China
| | - Wannian Nie
- Department of Nephrology, Xiangya Hospital of Central South University, Changsha, China
| | - Xiangning Yuan
- Department of Nephrology, Xiangya Hospital of Central South University, Changsha, China
- Organ Fibrosis Key Lab of Hunan Province, Central South University, Changsha, China
| | - Fang Liu
- Health Management Center, Xiangya Hospital of Central South University, Changsha, China
- *Correspondence: Fang Liu, ; Qiongjing Yuan,
| | - Qiongjing Yuan
- Department of Nephrology, Xiangya Hospital of Central South University, Changsha, China
- Organ Fibrosis Key Lab of Hunan Province, Central South University, Changsha, China
- National Clinical Medical Research Center for Geriatric Diseases, Xiangya Hospital of Central South University, Changsha, China
- Research Center for Medical Metabolomics, Xiangya Hospital of Central South University, Changsha, China
- *Correspondence: Fang Liu, ; Qiongjing Yuan,
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Aughton K, Sabat-Pośpiech D, Barlow S, Coupland SE, Kalirai H. Investigating the Role of DUSP4 in Uveal Melanoma. Transl Vis Sci Technol 2022; 11:13. [PMID: 36576731 PMCID: PMC9804032 DOI: 10.1167/tvst.11.12.13] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022] Open
Abstract
Purpose Dual-specificity phosphatase 4 (DUSP4) inactivates factors in the mitogen-activated protein kinase (MAPK) signaling cascade, activated in uveal melanoma (UM) by mutations in upstream G-protein α subunits GNAQ/11 in >90% cases. This study examined whether DUSP4 (1) protein expression in primary UM (pUM) was a biomarker of metastatic risk and (2) knockdown sensitized UM cells to therapeutic agents, selumetinib or doxorubicin. Methods DUSP4 mRNA data from The Cancer Genome Atlas and DUSP4 protein expression examined using immunohistochemistry in 28 cases of pUM were evaluated for association with clinical, genetic, and histological features. In vitro cytotoxic drug assays tested the efficacy of selumetinib and doxorubicin in UM cell lines with/without small interfering RNA DUSP4 gene silencing. Results DUSP4 protein expression was observed in 93% of cases, with strong nuclear positivity in 79%. Despite higher DUSP4 messenger RNA levels in disomy 3/wild-type BAP1 UM, there was no significant association of nDUSP4 protein with these metastatic risk predictors or outcome. DUSP4 expression in UM cell lines varied. DUSP4 silencing in Mel202, MP46, and MP41 cells did not affect ERK1/2 or phospho-ERK levels. Despite increased phospho-ERK levels in Mel285, no cell line showed enhanced sensitivity to selumetinib/doxorubicin. Conclusions DUSP4 protein expression is not a biomarker of UM metastatic risk. DUSP4 plays a complex role in oncogenesis, as reported in other cancers, and further work is required to fully understand its functional role in the MAPK pathway. Translational Relevance Understanding the role of phosphatases, such as DUSP4, in the control of intracellular signaling cascades will facilitate our ability to identify successful treatment options.
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Affiliation(s)
- Karen Aughton
- Liverpool Ocular Oncology Research Group, University of Liverpool, Molecular and Clinical Cancer Medicine, Institute of Systems Molecular & Integrative Biology, University of Liverpool, Liverpool, UK
| | - Dorota Sabat-Pośpiech
- Liverpool Ocular Oncology Research Group, University of Liverpool, Molecular and Clinical Cancer Medicine, Institute of Systems Molecular & Integrative Biology, University of Liverpool, Liverpool, UK
| | - Samantha Barlow
- Liverpool Ocular Oncology Research Group, University of Liverpool, Molecular and Clinical Cancer Medicine, Institute of Systems Molecular & Integrative Biology, University of Liverpool, Liverpool, UK,Liverpool Clinical Laboratories, Liverpool University Hospital Foundation Trust, Liverpool, UK
| | - Sarah E. Coupland
- Liverpool Ocular Oncology Research Group, University of Liverpool, Molecular and Clinical Cancer Medicine, Institute of Systems Molecular & Integrative Biology, University of Liverpool, Liverpool, UK,Liverpool Clinical Laboratories, Liverpool University Hospital Foundation Trust, Liverpool, UK
| | - Helen Kalirai
- Liverpool Ocular Oncology Research Group, University of Liverpool, Molecular and Clinical Cancer Medicine, Institute of Systems Molecular & Integrative Biology, University of Liverpool, Liverpool, UK,Liverpool Clinical Laboratories, Liverpool University Hospital Foundation Trust, Liverpool, UK
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Tang S, Gökbağ B, Fan K, Shao S, Huo Y, Wu X, Cheng L, Li L. Synthetic lethal gene pairs: Experimental approaches and predictive models. Front Genet 2022; 13:961611. [PMID: 36531238 PMCID: PMC9751344 DOI: 10.3389/fgene.2022.961611] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2022] [Accepted: 11/07/2022] [Indexed: 03/27/2024] Open
Abstract
Synthetic lethality (SL) refers to a genetic interaction in which the simultaneous perturbation of two genes leads to cell or organism death, whereas viability is maintained when only one of the pair is altered. The experimental exploration of these pairs and predictive modeling in computational biology contribute to our understanding of cancer biology and the development of cancer therapies. We extensively reviewed experimental technologies, public data sources, and predictive models in the study of synthetic lethal gene pairs and herein detail biological assumptions, experimental data, statistical models, and computational schemes of various predictive models, speculate regarding their influence on individual sample- and population-based synthetic lethal interactions, discuss the pros and cons of existing SL data and models, and highlight potential research directions in SL discovery.
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Affiliation(s)
- Shan Tang
- College of Pharmacy, The Ohio State University, Columbus, OH, United States
| | - Birkan Gökbağ
- Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, United States
| | - Kunjie Fan
- Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, United States
| | - Shuai Shao
- College of Pharmacy, The Ohio State University, Columbus, OH, United States
| | - Yang Huo
- Indiana University, Bloomington, IN, United States
| | - Xue Wu
- Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, United States
| | - Lijun Cheng
- Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, United States
| | - Lang Li
- Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, United States
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Hu Y, Ewen-Campen B, Comjean A, Rodiger J, Mohr SE, Perrimon N. Paralog Explorer: A resource for mining information about paralogs in common research organisms. Comput Struct Biotechnol J 2022; 20:6570-6577. [PMID: 36467589 PMCID: PMC9712503 DOI: 10.1016/j.csbj.2022.11.041] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2022] [Revised: 11/21/2022] [Accepted: 11/21/2022] [Indexed: 11/27/2022] Open
Abstract
Paralogs are genes which arose via gene duplication, and when such paralogs retain overlapping or redundant function, this poses a challenge to functional genetics research. Recent technological advancements have made it possible to systematically probe gene function for redundant genes using dual or multiplex gene perturbation, and there is a need for a simple bioinformatic tool to identify putative paralogs of a gene(s) of interest. We have developed Paralog Explorer (https://www.flyrnai.org/tools/paralogs/), an online resource that allows researchers to quickly and accurately identify candidate paralogous genes in the genomes of the model organisms D. melanogaster, C. elegans, D. rerio, M. musculus, and H. sapiens. Paralog Explorer deploys an effective between-species ortholog prediction software, DIOPT, to analyze within-species paralogs. Paralog Explorer allows users to identify candidate paralogs, and to navigate relevant databases regarding gene co-expression, protein-protein and genetic interaction, as well as gene ontology and phenotype annotations. Altogether, this tool extends the value of current ortholog prediction resources by providing sophisticated features useful for identification and study of paralogous genes.
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Affiliation(s)
- Yanhui Hu
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Harvard University, Boston, MA 02115, USA
- Drosophila RNAi Screening Center, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115, USA
| | - Ben Ewen-Campen
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Harvard University, Boston, MA 02115, USA
| | - Aram Comjean
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Harvard University, Boston, MA 02115, USA
- Drosophila RNAi Screening Center, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115, USA
| | - Jonathan Rodiger
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Harvard University, Boston, MA 02115, USA
- Drosophila RNAi Screening Center, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115, USA
| | - Stephanie E. Mohr
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Harvard University, Boston, MA 02115, USA
- Drosophila RNAi Screening Center, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115, USA
| | - Norbert Perrimon
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Harvard University, Boston, MA 02115, USA
- Drosophila RNAi Screening Center, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115, USA
- Howard Hughes Medical Institute, Boston, MA 02138, USA
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50
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Farnsworth DA, Inoue Y, Johnson FD, de Rappard-Yuswack G, Lu D, Shi R, Ma LIJ, Mattar MS, Somwar R, Ladanyi M, Unni AM, Lockwood WW. MEK inhibitor resistance in lung adenocarcinoma is associated with addiction to sustained ERK suppression. NPJ Precis Oncol 2022; 6:88. [PMID: 36418460 PMCID: PMC9684561 DOI: 10.1038/s41698-022-00328-x] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Accepted: 11/01/2022] [Indexed: 11/25/2022] Open
Abstract
MEK inhibitors (MEKi) have limited efficacy in KRAS mutant lung adenocarcinoma (LUAD) patients, and this is attributed to both intrinsic and adaptive mechanisms of drug resistance. While many studies have focused on the former, there remains a dearth of data regarding acquired resistance to MEKi in LUAD. We established trametinib-resistant KRAS mutant LUAD cells through dose escalation and performed targeted MSK-IMPACT sequencing to identify drivers of MEKi resistance. Comparing resistant cells to their sensitive counterparts revealed alteration of genes associated with trametinib response. We describe a state of "drug addiction" in resistant cases where cells are dependent on continuous culture in trametinib for survival. We show that dependence on ERK2 suppression underlies this phenomenon and that trametinib removal hyperactivates ERK, resulting in ER stress and apoptosis. Amplification of KRASG12C occurs in drug-addicted cells and blocking mutant-specific activity with AMG 510 rescues the lethality associated with trametinib withdrawal. Furthermore, we show that increased KRASG12C expression is lethal to other KRAS mutant LUAD cells, consequential to ERK hyperactivation. Our study determines the drug-addicted phenotype in lung cancer is associated with KRAS amplification and demonstrates that toxic acquired genetic changes can develop de novo in the background of MAPK suppression with MEK inhibitors. We suggest that the presence of mutant KRAS amplification in patients may identify those that may benefit from a "drug holiday" to circumvent drug resistance. These findings demonstrate the toxic potential of hyperactive ERK signaling and highlight potential therapeutic opportunities in patients bearing KRAS mutations.
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Affiliation(s)
- Dylan A. Farnsworth
- Department of Integrative Oncology, BC Cancer Research Institute, Vancouver, Canada
| | - Yusuke Inoue
- Department of Integrative Oncology, BC Cancer Research Institute, Vancouver, Canada
| | - Fraser D. Johnson
- Department of Integrative Oncology, BC Cancer Research Institute, Vancouver, Canada
| | | | - Daniel Lu
- Department of Integrative Oncology, BC Cancer Research Institute, Vancouver, Canada
| | - Rocky Shi
- Department of Integrative Oncology, BC Cancer Research Institute, Vancouver, Canada
| | - Lok In Josephine Ma
- Department of Integrative Oncology, BC Cancer Research Institute, Vancouver, Canada
| | - Marissa S. Mattar
- grid.51462.340000 0001 2171 9952Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY USA
| | - Romel Somwar
- grid.51462.340000 0001 2171 9952Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY USA ,grid.51462.340000 0001 2171 9952Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY USA
| | - Marc Ladanyi
- grid.51462.340000 0001 2171 9952Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY USA ,grid.51462.340000 0001 2171 9952Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY USA
| | - Arun M. Unni
- grid.5386.8000000041936877XMeyer Cancer Center, Weill Cornell Medicine, New York, NY USA
| | - William W. Lockwood
- Department of Integrative Oncology, BC Cancer Research Institute, Vancouver, Canada ,grid.17091.3e0000 0001 2288 9830Department of Pathology & Laboratory Medicine, University of British Columbia, Vancouver, Canada
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