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Narendra G, Raju B, Verma H, Kumar M, Jain SK, Tung GK, Thakur S, Kaur R, Kaur S, Sapra B, Silakari O. Scaffold hopping based designing of selective ALDH1A1 inhibitors to overcome cyclophosphamide resistance: synthesis and biological evaluation. RSC Med Chem 2024; 15:309-321. [PMID: 38283216 PMCID: PMC10809718 DOI: 10.1039/d3md00543g] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2023] [Accepted: 11/27/2023] [Indexed: 01/30/2024] Open
Abstract
Aldehyde dehydrogenase 1A1 (ALDH1A1) is an isoenzyme that catalyzes the conversion of aldehydes to acids. However, the overexpression of ALDH1A1 in a variety of malignancies is the major cause of resistance to an anti-cancer drug, cyclophosphamide (CP). CP is a prodrug that is initially converted into 4-hydroxycyclophosphamide and its tautomer aldophosphamide, in the liver. These compounds permeate into the cell and are converted as active metabolites, i.e., phosphoramide mustard (PM), through spontaneous beta-elimination. On the other hand, the conversion of CP to PM is diverted at the level of aldophosphamide by converting it into inactive carboxyphosphamide using ALDH1A1, which ultimately leads to high drug inactivation and CP resistance. Hence, in combination with our earlier work on the target of resistance, i.e., ALDH1A1, we hereby report selective ALDH1A1 inhibitors. Herein, we selected a lead molecule from our previous virtual screening and implemented scaffold hopping analysis to identify a novel scaffold that can act as an ALDH1A1 inhibitor. This results in the identification of various novel scaffolds. Among these, on the basis of synthetic feasibility, the benzimidazole scaffold was selected for the design of novel ALDH1A1 inhibitors, followed by machine learning-assisted structure-based virtual screening. Finally, the five best compounds were selected and synthesized. All synthesized compounds were evaluated using in vitro enzymatic assay against ALDH1A1, ALDH2, and ALDH3A1. The results disclosed that three molecules A1, A2, and A3 showed significant selective ALDH1A1 inhibitory potential with an IC50 value of 0.32 μM, 0.55 μM, and 1.63 μM, respectively, and none of the compounds exhibits potency towards the other two ALDH isoforms i.e. ALDH2 and ALDH3A1. Besides, the potent compounds (A1, A2, and A3) have been tested for in vitro cell line assay in combination with mafosfamide (analogue of CP) on two cell lines i.e. A549 and MIA-PaCa-2. All three compounds show significant potency to reverse mafosfamide resistance by inhibiting ALDH1A1 against these cell lines.
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Affiliation(s)
- Gera Narendra
- Department of Pharmaceutical Sciences and Drug Research, Punjabi University Patiala Punjab 147002 India +91 17522 83075 +91 95015 42696
| | - Baddipadige Raju
- Department of Pharmaceutical Sciences and Drug Research, Punjabi University Patiala Punjab 147002 India +91 17522 83075 +91 95015 42696
| | - Himanshu Verma
- Department of Pharmaceutical Sciences and Drug Research, Punjabi University Patiala Punjab 147002 India +91 17522 83075 +91 95015 42696
| | - Manoj Kumar
- Department of Pharmaceutical Sciences and Drug Research, Punjabi University Patiala Punjab 147002 India +91 17522 83075 +91 95015 42696
| | - Subheet Kumar Jain
- Department of Pharmaceutical Sciences, Guru Nanak Dev University Amritsar India
| | - Gurleen Kaur Tung
- Centre for Basic and Translational Research in Health Sciences, Guru Nanak Dev University Amritsar India
| | - Shubham Thakur
- Department of Pharmaceutical Sciences, Guru Nanak Dev University Amritsar India
| | - Rasdeep Kaur
- Department of Botany and Environmental Sciences, Guru Nanak Dev University Amritsar India
| | - Satwinderjeet Kaur
- Department of Botany and Environmental Sciences, Guru Nanak Dev University Amritsar India
| | - Bharti Sapra
- Department of Pharmaceutical Sciences and Drug Research, Punjabi University Patiala Punjab 147002 India +91 17522 83075 +91 95015 42696
| | - Om Silakari
- Department of Pharmaceutical Sciences and Drug Research, Punjabi University Patiala Punjab 147002 India +91 17522 83075 +91 95015 42696
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Alom MM, Faruqe MO, Molla MKI, Rahman MM. Exploring Prognostic Biomarkers of Acute Myeloid Leukemia to Determine Its Most Effective Drugs from the FDA-Approved List through Molecular Docking and Dynamic Simulation. BIOMED RESEARCH INTERNATIONAL 2023; 2023:1946703. [PMID: 37359050 PMCID: PMC10287530 DOI: 10.1155/2023/1946703] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Revised: 05/04/2023] [Accepted: 05/20/2023] [Indexed: 06/28/2023]
Abstract
Acute myeloid leukemia (AML) is a blood cancer caused by the abnormal proliferation and differentiation of hematopoietic stem cells in the bone marrow. The actual genetic markers and molecular mechanisms of AML prognosis are unclear till today. This study used bioinformatics approaches for identifying hub genes and pathways associated with AML development to uncover potential molecular mechanisms. The expression profiles of RNA-Seq datasets, GSE68925 and GSE183817, were retrieved from the Gene Expression Omnibus (GEO) database. These two datasets were analyzed by GREIN to obtain differentially expressed genes (DEGs), which were used for performing the Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, protein-protein interaction (PPI), and survival analysis. The molecular docking and dynamic simulation were performed to identify the most effective drug/s for AML from the drug list approved by the Food and Drug Administration (FDA). By integrating the two datasets, 238 DEGs were identified as likely to be affected by AML progression. GO enrichment analyses exhibited that the upregulated genes were mainly associated with inflammatory response (BP) and extracellular region (CC). The downregulated DEGs were involved in the T-cell receptor signalling pathway (BP), an integral component of the lumenal side of the endoplasmic reticulum membrane (CC) and peptide antigen binding (MF). The pathway enrichment analysis showed that the upregulated DEGs were mainly associated with the T-cell receptor signalling pathway. Among the top 15 hub genes, the expression levels of ALDH1A1 and CFD were associated with the prognosis of AML. Four FDA-approved drugs were selected, and a top-ranked drug was identified for each biomarker through molecular docking studies. The top-ranked drugs were further confirmed by molecular dynamic simulation that revealed their binding stability and confirmed their stable performance. Therefore, the drug compounds, enasidenib and gilteritinib, can be recommended as the most effective drugs against the ALDH1A1 and CFD proteins, respectively.
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Affiliation(s)
- Md. Murshid Alom
- Laboratory of Molecular Health Science, Department of Genetic Engineering and Biotechnology, University of Rajshahi, Rajshahi 6205, Bangladesh
| | - Md Omar Faruqe
- Department of Computer Science and Engineering, University of Rajshahi, Rajshahi 6205, Bangladesh
| | - Md. Khademul Islam Molla
- Department of Computer Science and Engineering, University of Rajshahi, Rajshahi 6205, Bangladesh
| | - Md Motiur Rahman
- Laboratory of Molecular Health Science, Department of Genetic Engineering and Biotechnology, University of Rajshahi, Rajshahi 6205, Bangladesh
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Narendra G, Raju B, Verma H, Kumar M, Jain SK, Tung GK, Thakur S, Kaur R, Kaur S, Sapra B, Singh PK, Silakari O. Raloxifene and bazedoxifene as selective ALDH1A1 inhibitors to ameliorate cyclophosphamide resistance: A drug repurposing approach. Int J Biol Macromol 2023; 242:124749. [PMID: 37160174 DOI: 10.1016/j.ijbiomac.2023.124749] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Revised: 02/25/2023] [Accepted: 05/01/2023] [Indexed: 05/11/2023]
Abstract
Cyclophosphamide (CP) is one of the most widely used anticancer drugs for various malignancies. However, its long-term use leads to ALDH1A1-mediated inactivation and subsequent resistance which necessitates the development of potential ALDH1A1 inhibitors. Currently, ALDH1A1 inhibitors from different chemical classes have been reported, but these failed to reach the market due to safety and efficacy problems. Developing a new treatment from the ground requires a huge amount of time, effort, and money, therefore it is worthwhile to improve CP efficacy by proposing better adjuvants as ALDH1A1 inhibitors. Herein, the database constituting the FDA-approved drugs with well-established safety and toxicity profiles was screened through already reported machine learning models by our research group. This model is validated for discriminating the ALDH1A1 inhibitors and non-inhibitors. Virtual screening protocol (VS) from this model identified four FDA-approved drugs, raloxifene, bazedoxifene, avanafil, and betrixaban as selective ALDH1A1 inhibitors. The molecular docking, dynamics, and water swap analysis also suggested these drugs to be promising ALDH1A1 inhibitors which were further validated for their CP resistance reversal potential by in-vitro analysis. The in-vitro enzymatic assay results indicated that raloxifene and bazedoxifene selectively inhibited the ALDH1A1 enzyme with IC50 values of 2.35 and 4.41 μM respectively, whereas IC50 values of both the drugs against ALDH2 and ALDH3A1 was >100 μM. Additional in-vitro stu = dies with well-reported ALDH1A1 overexpressing A549 and MIA paCa-2 cell lines suggested that mafosfamide sensitivity was further ameliorated by the combination of both raloxifene and bazedoxifene. Collectively, in-silico and in-vitro studies indicate raloxifene and bazedoxifene act as promising adjuvants with CP that may improve the quality of treatment for cancer patients with minimal toxicities.
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Affiliation(s)
- Gera Narendra
- Department of Pharmaceutical Sciences and Drug Research, Punjabi University, Patiala, Punjab 147002, India
| | - Baddipadige Raju
- Department of Pharmaceutical Sciences and Drug Research, Punjabi University, Patiala, Punjab 147002, India
| | - Himanshu Verma
- Department of Pharmaceutical Sciences and Drug Research, Punjabi University, Patiala, Punjab 147002, India
| | - Manoj Kumar
- Department of Pharmaceutical Sciences and Drug Research, Punjabi University, Patiala, Punjab 147002, India
| | - Subheet Kumar Jain
- Department of Pharmaceutical Sciences, Guru Nanak Dev University, Amritsar, India
| | - Gurleen Kaur Tung
- Centre for Basic and Translational Research in Health Sciences, Guru Nanak Dev University, Amritsar, India
| | - Shubham Thakur
- Department of Pharmaceutical Sciences, Guru Nanak Dev University, Amritsar, India
| | - Rasdeep Kaur
- Department of Botany and Environmental Sciences, Guru Nanak Dev University, Amritsar, India
| | - Satwinderjeet Kaur
- Department of Botany and Environmental Sciences, Guru Nanak Dev University, Amritsar, India
| | - Bharti Sapra
- Department of Pharmaceutical Sciences and Drug Research, Punjabi University, Patiala, Punjab 147002, India
| | - Pankaj Kumar Singh
- Integrative Physiology and Pharmacology, Institute of Biomedicine, Faculty of Medicine, University of Turku, FI-20520 Turku, Finland
| | - Om Silakari
- Department of Pharmaceutical Sciences and Drug Research, Punjabi University, Patiala, Punjab 147002, India.
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Carneiro J, Magalhães RP, de la Oliva Roque VM, Simões M, Pratas D, Sousa SF. TargIDe: a machine-learning workflow for target identification of molecules with antibiofilm activity against Pseudomonas aeruginosa. J Comput Aided Mol Des 2023; 37:265-278. [PMID: 37085636 DOI: 10.1007/s10822-023-00505-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Accepted: 04/12/2023] [Indexed: 04/23/2023]
Abstract
Bacterial biofilms are a source of infectious human diseases and are heavily linked to antibiotic resistance. Pseudomonas aeruginosa is a multidrug-resistant bacterium widely present and implicated in several hospital-acquired infections. Over the last years, the development of new drugs able to inhibit Pseudomonas aeruginosa by interfering with its ability to form biofilms has become a promising strategy in drug discovery. Identifying molecules able to interfere with biofilm formation is difficult, but further developing these molecules by rationally improving their activity is particularly challenging, as it requires knowledge of the specific protein target that is inhibited. This work describes the development of a machine learning multitechnique consensus workflow to predict the protein targets of molecules with confirmed inhibitory activity against biofilm formation by Pseudomonas aeruginosa. It uses a specialized database containing all the known targets implicated in biofilm formation by Pseudomonas aeruginosa. The experimentally confirmed inhibitors available on ChEMBL, together with chemical descriptors, were used as the input features for a combination of nine different classification models, yielding a consensus method to predict the most likely target of a ligand. The implemented algorithm is freely available at https://github.com/BioSIM-Research-Group/TargIDe under licence GNU General Public Licence (GPL) version 3 and can easily be improved as more data become available.
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Affiliation(s)
- João Carneiro
- Interdisciplinary Centre of Marine and Environmental Research, CIIMAR, University of Porto, Terminal de Cruzeiros do Porto de Leixões, Av. General Norton de Matos, s/n, Porto, 4450-208, Portugal.
| | - Rita P Magalhães
- Faculty of Medicine, Associate Laboratory i4HB-Institute for Health and Bioeconomy, University of Porto, 4200-319, Porto, Portugal
- Department of Biomedicine, Faculty of Medicine, UCIBIO-Applied Molecular Biosciences Unit, University of Porto, BioSIM, Porto, 4200-319, Portugal
| | - Victor M de la Oliva Roque
- Faculty of Medicine, Associate Laboratory i4HB-Institute for Health and Bioeconomy, University of Porto, 4200-319, Porto, Portugal
- Department of Biomedicine, Faculty of Medicine, UCIBIO-Applied Molecular Biosciences Unit, University of Porto, BioSIM, Porto, 4200-319, Portugal
| | - Manuel Simões
- Faculty of Engineering, LEPABE Laboratory for Process Engineering, Environment, Biotechnology and Energy, University of Porto, Rua Dr. Roberto Frias, s/n, Porto, 4200-465, Portugal
- Faculty of Engineering, ALiCE-Associate Laboratory in Chemical Engineering, University of Porto, Rua Dr. Roberto Frias, 4200-465, Porto, Portugal
| | - Diogo Pratas
- Institute of Electronics and Informatics Engineering of Aveiro, IEETA, University of Aveiro, Aveiro, Portugal
- Department of Electronics, Telecommunications and Informatics, DETI, University of Aveiro, Aveiro, Portugal
- Department of Virology, DoV, University of Helsinki, Helsinki, Finland
| | - Sérgio F Sousa
- Faculty of Medicine, Associate Laboratory i4HB-Institute for Health and Bioeconomy, University of Porto, 4200-319, Porto, Portugal
- Department of Biomedicine, Faculty of Medicine, UCIBIO-Applied Molecular Biosciences Unit, University of Porto, BioSIM, Porto, 4200-319, Portugal
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Şahin S, Can NN. A Schiff Base with Polymorphic Structure ( Z′ = 2): Investigations with Computational Techniques and in Silico Predictions. Polycycl Aromat Compd 2023. [DOI: 10.1080/10406638.2022.2161585] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Affiliation(s)
- Songül Şahin
- Department of Chemistry, Faculty of Art and Sciences, Ondokuz Mayis University, Samsun, Turkey
| | - Nisa Nur Can
- Department of Neuroscience, Institute of Health Sciences, Ondokuz Mayis University, Samsun, Turkey
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Zacharioudakis E, Gavathiotis E. Targeting protein conformations with small molecules to control protein complexes. Trends Biochem Sci 2022; 47:1023-1037. [PMID: 35985943 PMCID: PMC9669135 DOI: 10.1016/j.tibs.2022.07.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2022] [Revised: 06/23/2022] [Accepted: 07/11/2022] [Indexed: 12/24/2022]
Abstract
Dynamic protein complexes function in all cellular processes, from signaling to transcription, using distinct conformations that regulate their activity. Conformational switching of proteins can turn on or off their activity through protein-protein interactions, catalytic function, cellular localization, or membrane interaction. Recent advances in structural, computational, and chemical methodologies have enabled the discovery of small-molecule activators and inhibitors of conformationally dynamic proteins by using a more rational design than a serendipitous screening approach. Here, we discuss such recent examples, focusing on the mechanism of protein conformational switching and its regulation by small molecules. We emphasize the rational approaches to control protein oligomerization with small molecules that offer exciting opportunities for investigation of novel biological mechanisms and drug discovery.
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Affiliation(s)
- Emmanouil Zacharioudakis
- Department of Biochemistry, Albert Einstein College of Medicine, Bronx, NY, USA; Department of Medicine, Albert Einstein College of Medicine, Bronx, NY, USA; Albert Einstein Cancer Center, Albert Einstein College of Medicine, Bronx, NY, USA; Wilf Family Cardiovascular Research Institute, Albert Einstein College of Medicine, Bronx, NY, USA; Institute for Aging Research, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Evripidis Gavathiotis
- Department of Biochemistry, Albert Einstein College of Medicine, Bronx, NY, USA; Department of Medicine, Albert Einstein College of Medicine, Bronx, NY, USA; Albert Einstein Cancer Center, Albert Einstein College of Medicine, Bronx, NY, USA; Wilf Family Cardiovascular Research Institute, Albert Einstein College of Medicine, Bronx, NY, USA; Institute for Aging Research, Albert Einstein College of Medicine, Bronx, NY, USA.
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Narendra G, Choudhary S, Raju B, Verma H, Silakari O. Role of Genetic Polymorphisms in Drug-Metabolizing Enzyme-Mediated Toxicity and Pharmacokinetic Resistance to Anti-Cancer Agents: A Review on the Pharmacogenomics Aspect. Clin Pharmacokinet 2022; 61:1495-1517. [PMID: 36180817 DOI: 10.1007/s40262-022-01174-7] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/17/2022] [Indexed: 01/31/2023]
Abstract
The inter-individual differences in cancer susceptibility are somehow correlated with the genetic differences that are caused by the polymorphisms. These genetic variations in drug-metabolizing enzymes/drug-inactivating enzymes may negatively or positively affect the pharmacokinetic profile of chemotherapeutic agents that eventually lead to pharmacokinetic resistance and toxicity against anti-cancer drugs. For instance, the CYP1B1*3 allele is associated with CYP1B1 overexpression and consequent resistance to a variety of taxanes and platins, while 496T>G is associated with lower levels of dihydropyrimidine dehydrogenase, which results in severe toxicities related to 5-fluorouracil. In this context, a pharmacogenomics approach can be applied to ascertain the role of the genetic make-up in a person's response to any drug. This approach collectively utilizes pharmacology and genomics to develop effective and safe medications that are devoid of resistance problems. In addition, recently reported genomics studies revealed the impact of many single nucleotide polymorphisms in tumors. These studies emphasized the importance of single nucleotide polymorphisms in drug-metabolizing enzymes on the effect of anti-tumor drugs. In this review, we discuss the pharmacogenomics aspect of polymorphisms in detail to provide an insight into the genetic manipulations in drug-metabolizing enzymes that are responsible for pharmacokinetic resistance or toxicity against well-known anti-cancer drugs. Special emphasis is placed on different deleterious single nucleotide polymorphisms and their effect on pharmacokinetic resistance. The information provided in this report may be beneficial to researchers, especially those who are working in the field of biotechnology and human genetics, in rationally manipulating the genetic information of patients with cancer who are undergoing chemotherapy to avoid the problem of pharmacokinetic resistance/toxicity associated with drug-metabolizing enzymes.
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Affiliation(s)
- Gera Narendra
- Molecular Modeling Lab (MML), Department of Pharmaceutical Sciences and Drug Research, Punjabi University, 147002, Patiala, Punjab, India
| | - Shalki Choudhary
- Molecular Modeling Lab (MML), Department of Pharmaceutical Sciences and Drug Research, Punjabi University, 147002, Patiala, Punjab, India
| | - Baddipadige Raju
- Molecular Modeling Lab (MML), Department of Pharmaceutical Sciences and Drug Research, Punjabi University, 147002, Patiala, Punjab, India
| | - Himanshu Verma
- Molecular Modeling Lab (MML), Department of Pharmaceutical Sciences and Drug Research, Punjabi University, 147002, Patiala, Punjab, India
| | - Om Silakari
- Molecular Modeling Lab (MML), Department of Pharmaceutical Sciences and Drug Research, Punjabi University, 147002, Patiala, Punjab, India.
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Yang R, Zha X, Gao X, Wang K, Cheng B, Yan B. Multi-stage virtual screening of natural products against p38α mitogen-activated protein kinase: predictive modeling by machine learning, docking study and molecular dynamics simulation. Heliyon 2022; 8:e10495. [PMID: 36105464 PMCID: PMC9465123 DOI: 10.1016/j.heliyon.2022.e10495] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2022] [Revised: 03/20/2022] [Accepted: 08/25/2022] [Indexed: 11/20/2022] Open
Abstract
p38α is a mitogen-activated protein kinase (MAPK), and the signaling pathways involved are closely related to the inflammation, apoptosis and differentiation of cells, which also makes it an attractive target for drug discovery. With the high efficiency and low cost, virtual screening technology is becoming an indispensable part of drug development. In this study, a novel multi-stage virtual screening method based on machine learning, molecular docking and molecular dynamics simulation was developed to identify p38α MAPK inhibitors from natural products in ZINC database, which improves the prediction accuracy by considering and utilizing both ligand and receptor information compared to any individual approach. Ultimately, we screened out two candidate inhibitors with acceptable ADMET properties (ZINC4260400 and ZINC8300300). Among the generated machine learning models, Random Forest (RF) and Support Vector Machine (SVM) performed better, with the area under the receiver operating characteristic curve (AUC) values of 0.932 and 0.931 on the test set, as well as 0.834 and 0.850 on the external validation set. In addition, the results of molecular docking and ADMET prediction showed that two compounds with appropriate pharmacokinetic properties had binding free energies less than −8.0 kcal/mol for the target protein, and the results of molecular dynamics simulations further confirmed that they were stable during the process of inhibition.
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Yue H, Hu Z, Hu R, Guo Z, Zheng Y, Wang Y, Zhou Y. ALDH1A1 in Cancers: Bidirectional Function, Drug Resistance, and Regulatory Mechanism. Front Oncol 2022; 12:918778. [PMID: 35814382 PMCID: PMC9256994 DOI: 10.3389/fonc.2022.918778] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Accepted: 05/17/2022] [Indexed: 01/16/2023] Open
Abstract
Aldehyde dehydrogenases 1 family member A1(ALDH1A1) gene codes a cytoplasmic enzyme and shows vital physiological and pathophysiological functions in many areas. ALDH1A1 plays important roles in various diseases, especially in cancers. We reviewed and summarized representative correlative studies and found that ALDH1A1 could induce cancers via the maintenance of cancer stem cell properties, modification of metabolism, promotion of DNA repair. ALDH1A1 expression is regulated by several epigenetic processes. ALDH1A1 also acted as a tumor suppressor in certain cancers. The detoxification of ALDH1A1 often causes chemotherapy failure. Currently, ALDH1A1-targeted therapy is widely used in cancer treatment, but the mechanism by which ALDH1A1 regulates cancer development is not fully understood. This review will provide insight into the status of ALDH1A1 research and new viewpoint for cancer therapy.
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Affiliation(s)
- Hanxun Yue
- The First School of Clinical Medicine, Lanzhou University, Lanzhou, China
- Department of Gastroenterology, The First Hospital of Lanzhou University, Lanzhou, China
- Key Laboratory for Gastrointestinal Diseases of Gansu Province, The First Hospital of Lanzhou University, Lanzhou, China
| | - Zenan Hu
- Department of Gastroenterology, The First Hospital of Lanzhou University, Lanzhou, China
- Key Laboratory for Gastrointestinal Diseases of Gansu Province, The First Hospital of Lanzhou University, Lanzhou, China
| | - Rui Hu
- The First School of Clinical Medicine, Lanzhou University, Lanzhou, China
- Key Laboratory for Reproductive Medicine and Embryo of Gansu Province, The First Hospital of Lanzhou University, Lanzhou, China
| | - Zeying Guo
- College of Chemistry and Chemical Engineering, Lanzhou University, Lanzhou, China
| | - Ya Zheng
- The First School of Clinical Medicine, Lanzhou University, Lanzhou, China
- Department of Gastroenterology, The First Hospital of Lanzhou University, Lanzhou, China
| | - Yuping Wang
- Department of Gastroenterology, The First Hospital of Lanzhou University, Lanzhou, China
- Key Laboratory for Gastrointestinal Diseases of Gansu Province, The First Hospital of Lanzhou University, Lanzhou, China
- *Correspondence: Yongning Zhou, ; Yuping Wang,
| | - Yongning Zhou
- Department of Gastroenterology, The First Hospital of Lanzhou University, Lanzhou, China
- Key Laboratory for Gastrointestinal Diseases of Gansu Province, The First Hospital of Lanzhou University, Lanzhou, China
- *Correspondence: Yongning Zhou, ; Yuping Wang,
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