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Lagache L, Zirem Y, Le Rhun É, Fournier I, Salzet M. Predicting Protein Pathways Associated to Tumor Heterogeneity by Correlating Spatial Lipidomics and Proteomics: The Dry Proteomic Concept. Mol Cell Proteomics 2024; 24:100891. [PMID: 39644924 DOI: 10.1016/j.mcpro.2024.100891] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2024] [Revised: 11/20/2024] [Accepted: 12/04/2024] [Indexed: 12/09/2024] Open
Abstract
Prediction of proteins and associated biological pathways from lipid analyses via matrix-assisted laser desorption/ionization (MALDI) MSI is a pressing challenge. We introduced "dry proteomics," using MALDI MSI to validate spatial localization of identified optimal clusters in lipid imaging. Consistent cluster appearance across omics images suggests association with specific lipid and protein in distinct biological pathways, forming the basis of dry proteomics. The methodology was refined using rat brain tissue as a model, then applied to human glioblastoma, a highly heterogeneous cancer. Sequential tissue sections underwent omics MALDI MSI and unsupervised clustering. Spatial omics analysis facilitated lipid and protein characterization, leading to a predictive model identifying clusters in any tissue based on unique lipid signatures and predicting associated protein pathways. Application to rat brain slices revealed diverse tissue subpopulations, including successfully predicted cerebellum areas. Similarly, the methodology was applied to a dataset from a cohort of 50 glioblastoma patients, reused from a previous study. However, among the 50 patients, only 13 lipid signatures from MALDI MSI data were available, allowing for the identification of lipid-protein associations that correlated with patient prognosis. For cases lacking lipid imaging data, a classification model based on protein data was developed from dry proteomic results to effectively categorize the remaining cohort.
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Affiliation(s)
- Laurine Lagache
- Univ.Lille, Inserm, CHU Lille, U1192 - Proteomics Inflammatory Response Mass Spectrometry- PRISM, Lille, France
| | - Yanis Zirem
- Univ.Lille, Inserm, CHU Lille, U1192 - Proteomics Inflammatory Response Mass Spectrometry- PRISM, Lille, France
| | - Émilie Le Rhun
- Univ.Lille, Inserm, CHU Lille, U1192 - Proteomics Inflammatory Response Mass Spectrometry- PRISM, Lille, France; Department of Neurosurgery and Neurology, Clinical Neuroscience Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Isabelle Fournier
- Univ.Lille, Inserm, CHU Lille, U1192 - Proteomics Inflammatory Response Mass Spectrometry- PRISM, Lille, France; Department Institut Universitaire de France, Ministère de l'Enseignement supérieur, de la Recherche et de l'Innovation, Paris, France.
| | - Michel Salzet
- Univ.Lille, Inserm, CHU Lille, U1192 - Proteomics Inflammatory Response Mass Spectrometry- PRISM, Lille, France; Department Institut Universitaire de France, Ministère de l'Enseignement supérieur, de la Recherche et de l'Innovation, Paris, France.
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Lin I, Awamleh Z, Sinvhal M, Wan A, Bondhus L, Wei A, Russell BE, Weksberg R, Arboleda VA. ASXL1 truncating variants in BOS and myeloid leukemia drive shared disruption of Wnt-signaling pathways but have differential isoform usage of RUNX3. BMC Med Genomics 2024; 17:282. [PMID: 39614348 DOI: 10.1186/s12920-024-02039-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2024] [Accepted: 10/30/2024] [Indexed: 12/01/2024] Open
Abstract
BACKGROUND Rare variants in epigenes (a.k.a. chromatin modifiers), a class of genes that control epigenetic regulation, are commonly identified in both pediatric neurodevelopmental syndromes and as somatic variants in cancer. However, little is known about the extent of the shared disruption of signaling pathways by the same epigene across different diseases. To address this, we study an epigene, Additional Sex Combs-like 1 (ASXL1), where truncating heterozygous variants cause Bohring-Opitz syndrome (BOS, OMIM #605039), a germline neurodevelopmental disorder, while somatic variants are driver events in acute myeloid leukemia (AML). No BOS patients have been reported to have AML. METHODS This study explores common pathways dysregulated by ASXL1 variants in patients with BOS and AML. We analyzed whole blood transcriptomic and DNA methylation data from patients with BOS and AML with ASXL1-variant (AML-ASXL1) and examined differential exon usage and cell proportions. RESULTS Our analyses identified common molecular signatures between BOS and AML-ASXL1 and highlighted key biomarkers, including VANGL2, GRIK5 and GREM2, that are dysregulated across samples with ASXL1 variants, regardless of disease type. Notably, our data revealed significant de-repression of posterior homeobox A (HOXA) genes and upregulation of Wnt-signaling and hematopoietic regulator HOXB4. While we discovered many shared epigenetic and transcriptomic features, we also identified differential splice isoforms in RUNX3 where the long isoform, p46, is preferentially expressed in BOS, while the shorter p44 isoform is expressed in AML-ASXL1. CONCLUSION Our findings highlight the strong effects of ASXL1 variants that supersede cell-type and even disease states. This is the first direct comparison of transcriptomic and methylation profiles driven by pathogenic variants in a chromatin modifier gene in distinct diseases. Similar to RASopathies, in which pathogenic variants in many genes lead to overlapping phenotypes that can be treated by inhibiting a common pathway, our data identifies common pathways for ASXL1 variants that can be targeted for both disease states. Comparative approaches of high-penetrance genetic variants across cell types and disease states can identify targetable pathways to treat multiple diseases. Finally, our work highlights the connections of epigenes, such as ASXL1, to an underlying stem-cell state in both early development and in malignancy.
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Affiliation(s)
- Isabella Lin
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, UCLA, Los Angeles, CA, USA
- Department of Computational Medicine, David Geffen School of Medicine, UCLA, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine, UCLA, Los Angeles, CA, USA
| | - Zain Awamleh
- Department of Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON, Canada
| | - Mili Sinvhal
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, UCLA, Los Angeles, CA, USA
- Department of Computational Medicine, David Geffen School of Medicine, UCLA, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine, UCLA, Los Angeles, CA, USA
| | - Andrew Wan
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, UCLA, Los Angeles, CA, USA
- Department of Computational Medicine, David Geffen School of Medicine, UCLA, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine, UCLA, Los Angeles, CA, USA
| | - Leroy Bondhus
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, UCLA, Los Angeles, CA, USA
- Department of Computational Medicine, David Geffen School of Medicine, UCLA, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine, UCLA, Los Angeles, CA, USA
| | - Angela Wei
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, UCLA, Los Angeles, CA, USA
- Department of Computational Medicine, David Geffen School of Medicine, UCLA, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine, UCLA, Los Angeles, CA, USA
- Department of Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON, Canada
| | - Bianca E Russell
- Department of Human Genetics, David Geffen School of Medicine, UCLA, Los Angeles, CA, USA
- Department of Human Genetics, Division of Clinical Genetics, UCLA, Los Angeles, CA, USA
| | - Rosanna Weksberg
- Department of Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON, Canada
- Department of Pediatrics, Division of Clinical & Metabolic Genetics, The Hospital for Sick Children, Toronto, ON, Canada
- Institute of Medical Sciences, Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
| | - Valerie A Arboleda
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, UCLA, Los Angeles, CA, USA.
- Department of Computational Medicine, David Geffen School of Medicine, UCLA, Los Angeles, CA, USA.
- Department of Human Genetics, David Geffen School of Medicine, UCLA, Los Angeles, CA, USA.
- Interdepartmental Bioinformatics Program, UCLA, Los Angeles, CA, USA.
- Molecular Biology institute, UCLA, Los Angeles, CA, USA.
- Jonsson Comprehensive Cancer Center, UCLA, Los Angeles, CA, USA.
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Cohen Z, Lau L, Ahmed M, Jack CR, Liu C. Quantitative susceptibility mapping in the brain reflects spatial expression of genes involved in iron homeostasis and myelination. Hum Brain Mapp 2024; 45:e26688. [PMID: 38896001 PMCID: PMC11187871 DOI: 10.1002/hbm.26688] [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: 03/01/2023] [Revised: 04/02/2024] [Accepted: 04/05/2024] [Indexed: 06/21/2024] Open
Abstract
Quantitative susceptibility mapping (QSM) is an MRI modality used to non-invasively measure iron content in the brain. Iron exhibits a specific anatomically varying pattern of accumulation in the brain across individuals. The highest regions of accumulation are the deep grey nuclei, where iron is stored in paramagnetic molecule ferritin. This form of iron is considered to be what largely contributes to the signal measured by QSM in the deep grey nuclei. It is also known that QSM is affected by diamagnetic myelin contents. Here, we investigate spatial gene expression of iron and myelin related genes, as measured by the Allen Human Brain Atlas, in relation to QSM images of age-matched subjects. We performed multiple linear regressions between gene expression and the average QSM signal within 34 distinct deep grey nuclei regions. Our results show a positive correlation (p < .05, corrected) between expression of ferritin and the QSM signal in deep grey nuclei regions. We repeated the analysis for other genes that encode proteins thought to be involved in the transport and storage of iron in the brain, as well as myelination. In addition to ferritin, our findings demonstrate a positive correlation (p < .05, corrected) between the expression of ferroportin, transferrin, divalent metal transporter 1, several gene markers of myelinating oligodendrocytes, and the QSM signal in deep grey nuclei regions. Our results suggest that the QSM signal reflects both the storage and active transport of iron in the deep grey nuclei regions of the brain.
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Affiliation(s)
- Zoe Cohen
- Department of Electrical Engineering and Computer SciencesUniversity of California, BerkeleyBerkeleyCaliforniaUSA
| | - Laurance Lau
- Department of Electrical Engineering and Computer SciencesUniversity of California, BerkeleyBerkeleyCaliforniaUSA
| | - Maruf Ahmed
- Department of Electrical Engineering and Computer SciencesUniversity of California, BerkeleyBerkeleyCaliforniaUSA
| | - Clifford R. Jack
- Mayo Foundation for Medical Education and ResearchRochesterMinnesotaUSA
| | - Chunlei Liu
- Department of Electrical Engineering and Computer SciencesUniversity of California, BerkeleyBerkeleyCaliforniaUSA
- Helen Wills Neuroscience InstituteUniversity of California, BerkeleyBerkeleyCaliforniaUSA
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Cox N, De Swaef E, Corteel M, Van Den Broeck W, Bossier P, Nauwynck HJ, Dantas-Lima JJ. Experimental Infection Models and Their Usefulness for White Spot Syndrome Virus (WSSV) Research in Shrimp. Viruses 2024; 16:813. [PMID: 38793694 PMCID: PMC11125927 DOI: 10.3390/v16050813] [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: 03/26/2024] [Revised: 05/14/2024] [Accepted: 05/17/2024] [Indexed: 05/26/2024] Open
Abstract
White spot syndrome virus (WSSV) is marked as one of the most economically devastating pathogens in shrimp aquaculture worldwide. Infection of cultured shrimp can lead to mass mortality (up to 100%). Although progress has been made, our understanding of WSSV's infection process and the virus-host-environment interaction is far from complete. This in turn hinders the development of effective mitigation strategies against WSSV. Infection models occupy a crucial first step in the research flow that tries to elucidate the infectious disease process to develop new antiviral treatments. Moreover, since the establishment of continuous shrimp cell lines is a work in progress, the development and use of standardized in vivo infection models that reflect the host-pathogen interaction in shrimp is a necessity. This review critically examines key aspects of in vivo WSSV infection model development that are often overlooked, such as standardization, (post)larval quality, inoculum type and choice of inoculation procedure, housing conditions, and shrimp welfare considerations. Furthermore, the usefulness of experimental infection models for different lines of WSSV research will be discussed with the aim to aid researchers when choosing a suitable model for their research needs.
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Affiliation(s)
- Natasja Cox
- IMAQUA, 9080 Lochristi, Belgium; (E.D.S.); (M.C.); (J.J.D.-L.)
- Laboratory of Virology, Department of Translational Physiology, Infectiology and Public Health, Faculty of Veterinary Medicine, Ghent University, 9820 Merelbeke, Belgium;
| | | | - Mathias Corteel
- IMAQUA, 9080 Lochristi, Belgium; (E.D.S.); (M.C.); (J.J.D.-L.)
| | - Wim Van Den Broeck
- Department of Morphology, Medical Imaging, Orthopedics, Physiotherapy and Nutrition, Faculty of Veterinary Medicine, Ghent University, 9820 Merelbeke, Belgium;
| | - Peter Bossier
- Laboratory of Aquaculture & Artemia Reference Center, Department of Animal Sciences and Aquatic Ecology, Faculty of Bioscience Engineering, Ghent University, 9000 Ghent, Belgium;
| | - Hans J. Nauwynck
- Laboratory of Virology, Department of Translational Physiology, Infectiology and Public Health, Faculty of Veterinary Medicine, Ghent University, 9820 Merelbeke, Belgium;
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Ye J, Huang Z, Li Q, Li Z, Lan Y, Wang Z, Ni C, Wu X, Jiang T, Li Y, Yang Q, Lim J, Ren CY, Jiang M, Li S, Jin P, Chen JH, Zhao C. Transition of allele-specific DNA hydroxymethylation at regulatory loci is associated with phenotypic variation in monozygotic twins discordant for psychiatric disorders. BMC Med 2023; 21:491. [PMID: 38082312 PMCID: PMC10714646 DOI: 10.1186/s12916-023-03177-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Accepted: 11/13/2023] [Indexed: 12/18/2023] Open
Abstract
BACKGROUND Major psychiatric disorders such as schizophrenia (SCZ) and bipolar disorder (BPD) are complex genetic mental illnesses. Their non-Mendelian features, such as those observed in monozygotic twins discordant for SCZ or BPD, are likely complicated by environmental modifiers of genetic effects. 5-Hydroxymethylcytosine (5hmC) is an important epigenetic mark in gene regulation, and whether it is linked to genetic variants that contribute to non-Mendelian features remains largely unexplored. METHODS We combined the 5hmC-selective chemical labeling method (5hmC-seq) and whole-genome sequencing (WGS) analysis of peripheral blood DNA obtained from monozygotic (MZ) twins discordant for SCZ or BPD to identify allelic imbalances in hydroxymethylome maps, and examined association of allele-specific hydroxymethylation (AShM) transition with disease susceptibility based on Bayes factors (BF) derived from the Bayesian generalized additive linear mixed model. We then performed multi-omics integrative analysis to determine the molecular pathogenic basis of those AShM sites. We finally employed luciferase reporter, CRISPR/Cas9 technology, electrophoretic mobility shift assay (EMSA), chromatin immunoprecipitation (ChIP), PCR, FM4-64 imaging analysis, and RNA sequencing to validate the function of interested AShM sites in the human neuroblastoma SK-N-SH cells and human embryonic kidney 293T (HEK293T) cells. RESULTS We identified thousands of genetic variants associated with AShM imbalances that exhibited phenotypic variation-associated AShM changes at regulatory loci. These AShM marks showed plausible associations with SCZ or BPD based on their effects on interactions among transcription factors (TFs), DNA methylation levels, or other epigenomic marks and thus contributed to dysregulated gene expression, which ultimately increased disease susceptibility. We then validated that competitive binding of POU3F2 on the alternative allele at the AShM site rs4558409 (G/T) in PLLP-enhanced PLLP expression, while the hydroxymethylated alternative allele, which alleviated the POU3F2 binding activity at the rs4558409 site, might be associated with the downregulated PLLP expression observed in BPD or SCZ. Moreover, disruption of rs4558409 promoted neural development and vesicle trafficking. CONCLUSION Our study provides a powerful strategy for prioritizing regulatory risk variants and contributes to our understanding of the interplay between genetic and epigenetic factors in mediating SCZ or BPD susceptibility.
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Affiliation(s)
- Junping Ye
- Key Laboratory of Mental Health of the Ministry of Education, Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, Guangdong Province Key Laboratory of Psychiatric Disorders, and Department of Medical Genetics, School of Basic Medical Sciences, Southern Medical University, Guangzhou, 510515, China
| | - Zhanwang Huang
- Key Laboratory of Mental Health of the Ministry of Education, Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, Guangdong Province Key Laboratory of Psychiatric Disorders, and Department of Medical Genetics, School of Basic Medical Sciences, Southern Medical University, Guangzhou, 510515, China
| | - Qiyang Li
- Key Laboratory of Mental Health of the Ministry of Education, Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, Guangdong Province Key Laboratory of Psychiatric Disorders, and Department of Medical Genetics, School of Basic Medical Sciences, Southern Medical University, Guangzhou, 510515, China
- Department of Rehabilitation, Zhujiang Hospital of Southern Medical University, Guangzhou, China
| | - Zhongwei Li
- Key Laboratory of Mental Health of the Ministry of Education, Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, Guangdong Province Key Laboratory of Psychiatric Disorders, and Department of Medical Genetics, School of Basic Medical Sciences, Southern Medical University, Guangzhou, 510515, China
| | - Yuting Lan
- Key Laboratory of Mental Health of the Ministry of Education, Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, Guangdong Province Key Laboratory of Psychiatric Disorders, and Department of Medical Genetics, School of Basic Medical Sciences, Southern Medical University, Guangzhou, 510515, China
- Department of Psychiatry, the Affiliated Brain Hospital of Guangzhou Medical University (Guangzhou Huiai Hospital), Guangzhou, Guangdong, China
| | - Zhongju Wang
- Key Laboratory of Mental Health of the Ministry of Education, Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, Guangdong Province Key Laboratory of Psychiatric Disorders, and Department of Medical Genetics, School of Basic Medical Sciences, Southern Medical University, Guangzhou, 510515, China
| | - Chaoying Ni
- Key Laboratory of Mental Health of the Ministry of Education, Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, Guangdong Province Key Laboratory of Psychiatric Disorders, and Department of Medical Genetics, School of Basic Medical Sciences, Southern Medical University, Guangzhou, 510515, China
| | - Xiaohui Wu
- Key Laboratory of Mental Health of the Ministry of Education, Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, Guangdong Province Key Laboratory of Psychiatric Disorders, and Department of Medical Genetics, School of Basic Medical Sciences, Southern Medical University, Guangzhou, 510515, China
| | - Tingyun Jiang
- The Third People's Hospital of Zhongshan, Zhongshan, Guangdong, China
| | - Yujing Li
- Departments of Human Genetics, Emory University, Atlanta, GA, USA
| | - Qiong Yang
- Department of Psychiatry, the Affiliated Brain Hospital of Guangzhou Medical University (Guangzhou Huiai Hospital), Guangzhou, Guangdong, China
| | - Junghwa Lim
- Departments of Human Genetics, Emory University, Atlanta, GA, USA
| | - Cun-Yan Ren
- Laboratory of Genomic and Precision Medicine, Wuxi School of Medicine, Jiangnan University, Wuxi, China
| | - Meijun Jiang
- Guangdong Provincial People's Hospital (Guangdong Academy of Medical Science), Guangdong Mental Health Center, Southern Medical University, Guangzhou, China
| | - Shufen Li
- Key Laboratory of Mental Health of the Ministry of Education, Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, Guangdong Province Key Laboratory of Psychiatric Disorders, and Department of Medical Genetics, School of Basic Medical Sciences, Southern Medical University, Guangzhou, 510515, China
| | - Peng Jin
- Departments of Human Genetics, Emory University, Atlanta, GA, USA
| | - Jian-Huan Chen
- Laboratory of Genomic and Precision Medicine, Wuxi School of Medicine, Jiangnan University, Wuxi, China.
| | - Cunyou Zhao
- Key Laboratory of Mental Health of the Ministry of Education, Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, Guangdong Province Key Laboratory of Psychiatric Disorders, and Department of Medical Genetics, School of Basic Medical Sciences, Southern Medical University, Guangzhou, 510515, China.
- Department of Rehabilitation, Zhujiang Hospital of Southern Medical University, Guangzhou, China.
- Guangdong Provincial People's Hospital (Guangdong Academy of Medical Science), Guangdong Mental Health Center, Southern Medical University, Guangzhou, China.
- Experimental Education/Administration Center, School of Basic Medical Science, Southern Medical University, Guangzhou, China.
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Labat-de-Hoz L, Rubio-Ramos A, Correas I, Alonso MA. The MAL Family of Proteins: Normal Function, Expression in Cancer, and Potential Use as Cancer Biomarkers. Cancers (Basel) 2023; 15:2801. [PMID: 37345137 DOI: 10.3390/cancers15102801] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 04/06/2023] [Accepted: 05/15/2023] [Indexed: 06/23/2023] Open
Abstract
The MAL family of integral membrane proteins consists of MAL, MAL2, MALL, PLLP, CMTM8, MYADM, and MYADML2. The best characterized members are elements of the machinery that controls specialized pathways of membrane traffic and cell signaling. This review aims to help answer the following questions about the MAL-family genes: (i) is their expression regulated in cancer and, if so, how? (ii) What role do they play in cancer? (iii) Might they have biomedical applications? Analysis of large-scale gene expression datasets indicated altered levels of MAL-family transcripts in specific cancer types. A comprehensive literature search provides evidence of MAL-family gene dysregulation and protein function repurposing in cancer. For MAL, and probably for other genes of the family, dysregulation is primarily a consequence of gene methylation, although copy number alterations also contribute to varying degrees. The scrutiny of the two sources of information, datasets and published studies, reveals potential prognostic applications of MAL-family members as cancer biomarkers-for instance, MAL2 in breast cancer, MAL2 and MALL in pancreatic cancer, and MAL and MYADM in lung cancer-and other biomedical uses. The availability of validated antibodies to some MAL-family proteins sanctions their use as cancer biomarkers in routine clinical practice.
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Affiliation(s)
- Leticia Labat-de-Hoz
- Centro de Biología Molecular Severo Ochoa, Consejo Superior de Investigaciones Científicas, Universidad Autónoma de Madrid, 28049 Madrid, Spain
| | - Armando Rubio-Ramos
- Centro de Biología Molecular Severo Ochoa, Consejo Superior de Investigaciones Científicas, Universidad Autónoma de Madrid, 28049 Madrid, Spain
| | - Isabel Correas
- Centro de Biología Molecular Severo Ochoa, Consejo Superior de Investigaciones Científicas, Universidad Autónoma de Madrid, 28049 Madrid, Spain
- Department of Molecular Biology, Universidad Autónoma de Madrid, 28049 Madrid, Spain
| | - Miguel A Alonso
- Centro de Biología Molecular Severo Ochoa, Consejo Superior de Investigaciones Científicas, Universidad Autónoma de Madrid, 28049 Madrid, Spain
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