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Li Q, Li K, Guo Q, Yang T. CircRNA circSTIL inhibits ferroptosis in colorectal cancer via miR-431/SLC7A11 axis. ENVIRONMENTAL TOXICOLOGY 2023; 38:981-989. [PMID: 36840697 DOI: 10.1002/tox.23670] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/17/2022] [Revised: 09/04/2022] [Accepted: 09/16/2022] [Indexed: 06/18/2023]
Abstract
Ferroptosis is an emerging programmed cell death and plays essential roles in tumorigenesis, including colorectal cancer (CRC). The present study intended to disclose the role of a novel oncogene circular RNA (circRNA) circSTIL in CRC phenotypes, especially ferroptosis. The expression of circSTIL was measured in CRC tissues and cells. Then, the impacts of circSTIL expression on the proliferation and ferroptosis of CRC cells were examined by loss-of-function assays in vitro. Bioinformatics, luciferase reporter assay and cell rescue assay were further performed to reveal the ceRNA-associated mechanism of circSTIL. CircSTIL was significantly upregulated in CRC. Cell proliferation was suppressed while ferroptosis was induced with the silencing of circSTIL in CRC cells. Interestingly, circSTIL competed with miR-431 for solute carrier family 7 member 11 (SLC7A11) binding. Additionally, miR-431 suppression or SLC7A11 overexpression overturned circSTIL silencing-mediated cell phenotypes in CRC cells. CircSTIL promotes CRC cell proliferation and suppresses ferroptosis in vitro via miR-431/SLC7A11 signaling, revealing the pathogenesis of CRC, and providing potential therapeutic targets of CRC.
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Affiliation(s)
- Qiang Li
- Department of General Surgery, The First Affiliated Hospital of Jinzhou Medical University, Jinzhou, Liaoning, People's Republic of China
| | - Kaimin Li
- The First Affiliated Hospital of Jinzhou Medical University, Jinzhou Medical University, Jinzhou, Liaoning, People's Republic of China
| | - Qinying Guo
- Operating Room, The First Affiliated Hospital of Jinzhou Medical University, Jinzhou, Liaoning, People's Republic of China
| | - Tao Yang
- Department of General Surgery, The First Affiliated Hospital of Jinzhou Medical University, Jinzhou, Liaoning, People's Republic of China
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2
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Weidle UH, Nopora A. Up-regulated Circular RNAs in Colorectal Cancer: New Entities for Therapy and Tools for Identification of Therapeutic Targets. Cancer Genomics Proteomics 2023; 20:132-153. [PMID: 36870691 PMCID: PMC9989668 DOI: 10.21873/cgp.20369] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Revised: 12/20/2022] [Accepted: 12/28/2022] [Indexed: 03/06/2023] Open
Abstract
Patients with disseminated colorectal cancer have a dismal prognosis with a 5-year survival rate of only 13%. In order to identify new treatment modalities and new targets, we searched the literature for up-regulated circular RNAs in colorectal cancer which induce tumor growth in corresponding preclinical in vivo models. We identified nine circular RNAs that mediate resistance against chemotherapeutic agents, seven that up-regulate transmembrane receptors, five that induce secreted factors, nine that activate signaling components, five which up-regulate enzymes, six which activate actin-related proteins, six which induce transcription factors and two which up-regulate the MUSASHI family of RNA binding proteins. All of the circular RNAs discussed in this paper induce the corresponding targets by sponging microRNAs (miRs) and can be inhibited by RNAi or shRNA in vitro and in xenograft models. We have focused on circular RNAs with demonstrated activity in preclinical in vivo models because the latter is an important milestone in drug development. All circular RNAs with in vitro activity only data are not referenced in this review. The translational impact of inhibition of these circular RNAs and of the identified targets for treatment of colorectal cancer (CRC) are discussed.
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Affiliation(s)
- Ulrich H Weidle
- Roche Pharma Research and Early Development, Roche Innovation Center Munich, Penzberg, Germany
| | - Adam Nopora
- Roche Pharma Research and Early Development, Roche Innovation Center Munich, Penzberg, Germany
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Circ_CSPP1 Regulates the Development of Non-small Cell Lung Cancer via the miR-486-3p/BRD9 Axis. Biochem Genet 2023; 61:1-20. [PMID: 35678942 DOI: 10.1007/s10528-022-10231-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Accepted: 04/18/2022] [Indexed: 01/24/2023]
Abstract
In this study, we explored the role of circ_CSPP1 in non-small cell lung cancer (NSCLC) using NSCLC cell lines (A549 and H1299) and human bronchial epithelioid cells (16HBE). The differential expression of circ_CSPP1, miR-486-3p and BRD9 in NSCLC by quantitative real-time polymerase chain reaction (qRT-PCR) and western blot in A549 cells, H1299 cells, 16HBE cells, NSCLC tissues and healthy lung tissues. Dual-luciferase reporter assay was conducted to verify the interaction between circ_CSPP1 and miR-486-3p or miR-486-3p and BRD9. The effect of circ_CSPP1/miR-486-3p/BRD9 axis on NSCLC cell proliferation was evaluated using cell counting kit-8 assay, colony formation assay, and 5-ethynyl-2'-deoxyuridine assay. Additionally, transwell assays were performed to evaluate the effect of circ_CSPP1/miR-486-3p/BRD9 axis on A549 and H1299 cell migration and invasion. The effect of circ_CSPP1 on tumor tumorigenesis of A549 cells in vivo was determined by xenograft tumor model and immunohistochemistry assay. Circ_CSPP1 and BRD9 expression were upregulated, while miR-486-3p expression was downregulated in tumor tissues of NSCCL patients and A549 and H1299 cells. Circ_CSPP1 specifically bound miR-486-3p, and miR-486-3p could target BRD9. Circ_CSPP1 upregulation promoted proliferation, invasion and migration of NSCLC cells, circ_CSPP1 knockdown or miR-486-3p upregulation had the opposite effects. Circ_CSPP1 knockdown-induced effects were reverted by miR-486-3p inhibition. Similarly, the effects of miR-486-3p upregulation on NSCLC cell proliferation, invasion and migration were reversed by BRD9 overexpression. In addition, circ_CSPP1 silencing inhibited tumor growth in nude mice. Circ_CSPP1 promoted A549 and H1299 cell malignancy by competitively inhibiting BRD9 and binding to miR-486-3p.
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Xiao Y, Qiu M, Tan C, Huang W, Hu S, Jiang X, Guo M, Wang C, Liang J, Wu Y, Li M, Li Q, Qin C. Systematic analysis of circRNA biomarkers for diagnosis, prognosis and therapy in colorectal cancer. Front Genet 2022; 13:938672. [PMID: 36313458 PMCID: PMC9597305 DOI: 10.3389/fgene.2022.938672] [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: 05/16/2022] [Accepted: 09/23/2022] [Indexed: 08/13/2023] Open
Abstract
As the third most common cancer and the second leading cause of cancer death worldwide, colorectal cancer (CRC) poses a serious threat to people's health. In recent years, circRNA has been widely reported as a new biomarker in CRC, but a comprehensive summary and analysis is lacking. This study aims to evaluate the diagnostic, therapeutic and prognostic significance of circRNAs in CRC by systematically analysing their expression patterns, biological functions and clinical significance in CRC. The literature on circRNA in CRC was searched in the PubMed database and included for analysis after screening according to strict inclusion and exclusion criteria. The UALCAN online tool was used to obtain host gene expression data. The miRTargetLink 2.0 was used to predict target genes for miRNAs action in CRC patients. Cytoscape was used to construct circRNA-miRNA-mRNA interaction networks. From the 236 included papers, we identified 217 circRNAs and their associated 108 host genes and 145 miRNAs. Among the 145 miRNAs, 27 miRNAs had no corresponding target genes. After prediction of target genes and differential analysis, a total of 25 target genes were obtained and a circRNA-miRNA-mRNA interaction network was constructed. Among the 217 circRNAs, 74 were associated with diagnosis, 160 with treatment and 51 with prognosis. And 154 of them function as oncogenes while 58 as tumour suppressor genes. In addition, these circRNAs include 32 exosomal circRNAs, which have unique advantages as biomarkers. In total, we summarize and analyze the expression patterns, biological functions and clinical significance of circRNAs in CRC. In addition, we constructed some new circRNA-miRNA-mRNA regulatory axes based on the miRNAs sponged by circRNAs.
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Affiliation(s)
- Yafei Xiao
- Department of General Surgery, Huaihe Hospital of Henan University, Kaifeng, China
| | - Mengyuan Qiu
- Department of Neurology, Peking University People’s Hospital, Peking University School of Medicine, Beijing, China
| | - Cong Tan
- Institute of Biomedical Informatics, Cell Signal Transduction Laboratory, Bioinformatics Center, Henan Provincial Engineering Center for Tumor Molecular Medicine, School of Basic Medical Sciences, Henan University, Kaifeng, China
| | - Wanting Huang
- Department of Gynecology and Obstetrics, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Shaowen Hu
- Department of General Surgery, Huaihe Hospital of Henan University, Kaifeng, China
| | - Xiaowei Jiang
- Department of Pediatric Orthopaedics, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Mingjie Guo
- Department of Thoracic Surgery, The First Affiliated Hospital of Henan University, Kaifeng, China
| | - Congcong Wang
- Department of General Surgery, Huaihe Hospital of Henan University, Kaifeng, China
| | - Jingyu Liang
- Institute of Biomedical Informatics, Cell Signal Transduction Laboratory, Bioinformatics Center, Henan Provincial Engineering Center for Tumor Molecular Medicine, School of Basic Medical Sciences, Henan University, Kaifeng, China
| | - Yimei Wu
- Institute of Biomedical Informatics, Cell Signal Transduction Laboratory, Bioinformatics Center, Henan Provincial Engineering Center for Tumor Molecular Medicine, School of Basic Medical Sciences, Henan University, Kaifeng, China
| | - Mengmeng Li
- Department of General Surgery, Huaihe Hospital of Henan University, Kaifeng, China
| | - Quanying Li
- Department of General Surgery, Huaihe Hospital of Henan University, Kaifeng, China
| | - Changjiang Qin
- Department of General Surgery, Huaihe Hospital of Henan University, Kaifeng, China
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Russo V, Lallo E, Munnia A, Spedicato M, Messerini L, D’Aurizio R, Ceroni EG, Brunelli G, Galvano A, Russo A, Landini I, Nobili S, Ceppi M, Bruzzone M, Cianchi F, Staderini F, Roselli M, Riondino S, Ferroni P, Guadagni F, Mini E, Peluso M. Artificial Intelligence Predictive Models of Response to Cytotoxic Chemotherapy Alone or Combined to Targeted Therapy for Metastatic Colorectal Cancer Patients: A Systematic Review and Meta-Analysis. Cancers (Basel) 2022; 14:4012. [PMID: 36011003 PMCID: PMC9406544 DOI: 10.3390/cancers14164012] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Revised: 07/26/2022] [Accepted: 08/12/2022] [Indexed: 12/24/2022] Open
Abstract
Tailored treatments for metastatic colorectal cancer (mCRC) have not yet completely evolved due to the variety in response to drugs. Therefore, artificial intelligence has been recently used to develop prognostic and predictive models of treatment response (either activity/efficacy or toxicity) to aid in clinical decision making. In this systematic review, we have examined the ability of learning methods to predict response to chemotherapy alone or combined with targeted therapy in mCRC patients by targeting specific narrative publications in Medline up to April 2022 to identify appropriate original scientific articles. After the literature search, 26 original articles met inclusion and exclusion criteria and were included in the study. Our results show that all investigations conducted on this field have provided generally promising results in predicting the response to therapy or toxic side-effects. By a meta-analytic approach we found that the overall weighted means of the area under the receiver operating characteristic (ROC) curve (AUC) were 0.90, 95% C.I. 0.80-0.95 and 0.83, 95% C.I. 0.74-0.89 in training and validation sets, respectively, indicating a good classification performance in discriminating response vs. non-response. The calculation of overall HR indicates that learning models have strong ability to predict improved survival. Lastly, the delta-radiomics and the 74 gene signatures were able to discriminate response vs. non-response by correctly identifying up to 99% of mCRC patients who were responders and up to 100% of patients who were non-responders. Specifically, when we evaluated the predictive models with tests reaching 80% sensitivity (SE) and 90% specificity (SP), the delta radiomics showed an SE of 99% and an SP of 94% in the training set and an SE of 85% and SP of 92 in the test set, whereas for the 74 gene signatures the SE was 97.6% and the SP 100% in the training set.
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Affiliation(s)
- Valentina Russo
- Research and Development Branch, Regional Cancer Prevention Laboratory, ISPRO-Study, Prevention and Oncology Network Institute, 50139 Florence, Italy
| | - Eleonora Lallo
- Research and Development Branch, Regional Cancer Prevention Laboratory, ISPRO-Study, Prevention and Oncology Network Institute, 50139 Florence, Italy
| | - Armelle Munnia
- Research and Development Branch, Regional Cancer Prevention Laboratory, ISPRO-Study, Prevention and Oncology Network Institute, 50139 Florence, Italy
| | - Miriana Spedicato
- Research and Development Branch, Regional Cancer Prevention Laboratory, ISPRO-Study, Prevention and Oncology Network Institute, 50139 Florence, Italy
| | - Luca Messerini
- Department of Experimental and Clinical Medicine, University of Florence, 50134 Florence, Italy
| | - Romina D’Aurizio
- Institute of Informatics and Telematics, National Research Council, 56124 Pisa, Italy
| | - Elia Giuseppe Ceroni
- Institute of Informatics and Telematics, National Research Council, 56124 Pisa, Italy
| | - Giulia Brunelli
- Institute of Informatics and Telematics, National Research Council, 56124 Pisa, Italy
| | - Antonio Galvano
- Department of Surgical, Oncological and Oral Sciences, University of Palermo, 90127 Palermo, Italy
| | - Antonio Russo
- Department of Surgical, Oncological and Oral Sciences, University of Palermo, 90127 Palermo, Italy
| | - Ida Landini
- Department of Health Sciences, University of Florence, 50139 Florence, Italy
| | - Stefania Nobili
- Department of Neurosciences, Imaging and Clinical Sciences, “G. D’Annunzio” Chieti-Pescara, 66100 Chieti, Italy
| | - Marcello Ceppi
- Clinical Epidemiology Unit, IRCCS-Ospedale Policlinico San Martino, 16131 Genova, Italy
| | - Marco Bruzzone
- Clinical Epidemiology Unit, IRCCS-Ospedale Policlinico San Martino, 16131 Genova, Italy
| | - Fabio Cianchi
- Department of Experimental and Clinical Medicine, University of Florence, 50134 Florence, Italy
| | - Fabio Staderini
- Department of Experimental and Clinical Medicine, University of Florence, 50134 Florence, Italy
| | - Mario Roselli
- Medical Oncology Unit, Department of Systems Medicine, Tor Vergata University, 00133 Rome, Italy
| | - Silvia Riondino
- Medical Oncology Unit, Department of Systems Medicine, Tor Vergata University, 00133 Rome, Italy
| | - Patrizia Ferroni
- BioBIM (InterInstitutional Multidisciplinary Biobank), IRCCS San Raffaele Roma, 00166 Rome, Italy
- Department of Human Sciences & Quality of Life Promotion, San Raffaele Roma Open University, 00166 Rome, Italy
| | - Fiorella Guadagni
- BioBIM (InterInstitutional Multidisciplinary Biobank), IRCCS San Raffaele Roma, 00166 Rome, Italy
- Department of Human Sciences & Quality of Life Promotion, San Raffaele Roma Open University, 00166 Rome, Italy
| | - Enrico Mini
- Department of Health Sciences, University of Florence, 50139 Florence, Italy
| | - Marco Peluso
- Research and Development Branch, Regional Cancer Prevention Laboratory, ISPRO-Study, Prevention and Oncology Network Institute, 50139 Florence, Italy
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A Novel Inflammation-Related Gene Signature for Overall Survival Prediction and Comprehensive Analysis in Pediatric Patients with Wilms Tumor. DISEASE MARKERS 2022; 2022:2651105. [PMID: 35578692 PMCID: PMC9107364 DOI: 10.1155/2022/2651105] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Accepted: 04/19/2022] [Indexed: 12/15/2022]
Abstract
Wilms tumor (WT) is a common pediatric renal cancer, with a poor prognosis and high-risk recurrence in some patients. The inflammatory microenvironment is gradually gaining attention in WT. In this study, novel inflammation-related signatures and prognostic model were explored and integrated using bioinformatics analysis. The mRNA profile of pediatric patients with WT and inflammation-related genes (IRGs) were acquired from Therapeutically Available Research to Generate Effective Treatments (TARGET) and Gene Set Enrichment Analysis (GSEA) databases, respectively. Then, a novel prognostic model founded on 7-IRGs signature (BICC1, CSPP1, KRT8, MYCN, NELFA, NXN, and RNF113A) was established by the least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression to stratify pediatric patients with WT into high- and low-risk groups successfully. And a stable performance of the prognostic risk model was verified in predicting overall survival (OS) by receiver-operating characteristic (ROC) curves, Kaplan-Meier (KM) curves, and independent prognostic analysis (p < 0.05). In addition, a novel nomogram integrating risk scores with good robustness was developed and validated by C-index, ROC, and calibration plots. The potential function and pathway were explored via Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and GSEA, with mainly inflammation and immune-related biological processes. The higher-risk scores, the lower immune infiltration, as shown in the single-sample GSEA (ssGSEA) and tumor microenvironment (TME) analysis. The drug sensitivity analysis showed that regulating 7-IRGs signature has a significant correlation with the chemotherapy drugs of WT patients. In summary, this study defined a prognostic risk model and nomogram based on 7-IRGs signature, which may provide novel insights into clinical prognosis and inflammatory study in WT patients. Besides, enhancing immune infiltration based on inflammatory response and regulating 7-IRGs signature are beneficial to ameliorating the efficacy in WT patients.
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