1
|
Sannigrahi MK, Cao AC, Rajagopalan P, Sun L, Brody RM, Raghav L, Gimotty PA, Basu D. A novel pipeline for prioritizing cancer type-specific therapeutic vulnerabilities using DepMap identifies PAK2 as a target in head and neck squamous cell carcinomas. Mol Oncol 2024; 18:336-349. [PMID: 37997254 PMCID: PMC10850805 DOI: 10.1002/1878-0261.13558] [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: 06/10/2023] [Revised: 10/23/2023] [Accepted: 11/22/2023] [Indexed: 11/25/2023] Open
Abstract
There is limited guidance on exploiting the genome-wide loss-of-function CRISPR screens in cancer Dependency Map (DepMap) to identify new targets for individual cancer types. This study integrated multiple tools to filter these data in order to seek new therapeutic targets specific to head and neck squamous cell carcinoma (HNSCC). The resulting pipeline prioritized 143 targetable dependencies that represented both well-studied targets and emerging target classes like mitochondrial carriers and RNA-binding proteins. In total, 14 targets had clinical inhibitors used for other cancers or nonmalignant diseases that hold near-term potential to repurpose for HNSCC therapy. Comparing inhibitor response data that were publicly available for 13 prioritized targets between the cell lines with high vs. low dependency on each target uncovered novel therapeutic potential for the PAK2 serine/threonine kinase. PAK2 gene dependency was found to be associated with wild-type p53, low PAK2 mRNA, and diploid status of the 3q amplicon containing PAK2. These findings establish a generalizable pipeline to prioritize clinically relevant targets for individual cancer types using DepMap. Its application to HNSCC highlights novel relevance for PAK2 inhibition and identifies biomarkers of PAK2 inhibitor response.
Collapse
Affiliation(s)
- Malay K. Sannigrahi
- Department of Otorhinolaryngology‐Head and Neck SurgeryUniversity of PennsylvaniaPhiladelphiaPAUSA
| | - Austin C. Cao
- Department of Otorhinolaryngology‐Head and Neck SurgeryUniversity of PennsylvaniaPhiladelphiaPAUSA
| | - Pavithra Rajagopalan
- Department of Otorhinolaryngology‐Head and Neck SurgeryUniversity of PennsylvaniaPhiladelphiaPAUSA
| | - Lova Sun
- Department of MedicineUniversity of PennsylvaniaPhiladelphiaPAUSA
| | - Robert M. Brody
- Department of Otorhinolaryngology‐Head and Neck SurgeryUniversity of PennsylvaniaPhiladelphiaPAUSA
| | - Lovely Raghav
- Department of Otorhinolaryngology‐Head and Neck SurgeryUniversity of PennsylvaniaPhiladelphiaPAUSA
| | - Phyllis A. Gimotty
- Department of Biostatistics, Epidemiology and InformaticsUniversity of PennsylvaniaPhiladelphiaPAUSA
| | - Devraj Basu
- Department of Otorhinolaryngology‐Head and Neck SurgeryUniversity of PennsylvaniaPhiladelphiaPAUSA
- Ellen and Ronald Caplan Cancer CenterThe Wistar InstitutePhiladelphiaPAUSA
| |
Collapse
|
2
|
Zhao N, Weng S, Liu Z, Xu H, Ren Y, Guo C, Liu L, Zhang Z, Ji Y, Han X. CRISPR-Cas9 identifies growth-related subtypes of glioblastoma with therapeutical significance through cell line knockdown. BMC Cancer 2023; 23:749. [PMID: 37580710 PMCID: PMC10424363 DOI: 10.1186/s12885-023-11131-7] [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: 02/18/2023] [Accepted: 06/29/2023] [Indexed: 08/16/2023] Open
Abstract
BACKGROUND Glioblastoma (GBM) is a type of highly malignant brain tumor that is known for its significant intratumoral heterogeneity, meaning that there can be a high degree of variability within the tumor tissue. Despite the identification of several subtypes of GBM in recent years, there remains to explore a classification based on genes related to proliferation and growth. METHODS The growth-related genes of GBM were identified by CRISPR-Cas9 and univariate Cox regression analysis. The expression of these genes in the Cancer Genome Atlas cohort (TCGA) was used to construct growth-related genes subtypes (GGSs) via consensus clustering. Validation of this subtyping was performed using the nearest template prediction (NTP) algorithm in two independent Gene Expression Omnibus (GEO) cohorts and the ZZ cohort. Additionally, copy number variations, biological functions, and potential drugs were analyzed for each of the different subtypes separately. RESULTS Our research established multicenter-validated GGSs. GGS1 exhibits the poorest prognosis, with the highest frequency of chr 7 gain & chr 10 loss, and the lowest frequency of chr 19 & 20 co-gain. Additionally, GGS1 displays the highest expression of EGFR. Furthermore, it is significantly enriched in metabolic, stemness, proliferation, and signaling pathways. Besides we showed that Foretinib may be a potential therapeutic agent for GGS1, the worst prognostic subtype, through data screening and in vitro experiments. GGS2 has a moderate prognosis, with a slightly higher proportion of chr 7 gain & chr 10 loss, and the highest proportion of chr 19 & 20 co-gain. The prognosis of GGS3 is the best, with the least chr 7 gain & 10 loss and EGFR expression. CONCLUSIONS These results enhance our understanding of the heterogeneity of GBM and offer insights for stratified management and precise treatment of GBM patients.
Collapse
Affiliation(s)
- Nannan Zhao
- Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450052, China
- Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450052, China
| | - Siyuan Weng
- Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450052, China
| | - Zaoqu Liu
- Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450052, China
| | - Hui Xu
- Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450052, China
| | - Yuqin Ren
- Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Chunguang Guo
- Department of Endovascular Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Long Liu
- Department of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Zhenyu Zhang
- Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450052, China.
| | - Yuchen Ji
- Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450052, China.
| | - Xinwei Han
- Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450052, China.
| |
Collapse
|
3
|
Luo L, Chen X, Huang F. Machine learning revealed ferroptosis features and ferroptosis-related gene-based immune microenvironment in lung adenocarcinoma. Chem Biol Interact 2023; 378:110471. [PMID: 37061114 DOI: 10.1016/j.cbi.2023.110471] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Revised: 03/20/2023] [Accepted: 04/03/2023] [Indexed: 04/17/2023]
Abstract
Ferroptosis has been identified as a novel type of programmed cell death that has a major effect on the development of lung adenocarcinoma. Nevertheless, there has yet to be a clear set of therapeutic targets based on ferroptosis. This study seeks to employ machine learning methods to determine the regulators of ferroptosis in LUAD. 318 LUAD samples were investigated to determine three ferroptosis molecular phenotypes in LUAD, and then Boruta dimensionality reduction combined with principal component analysis was used to measure the ferroptosis regulation score (FRS) of patients. We additionally presented DeepFerr, a deep learning neural network model, which used the transcriptome map of 11 ferroptosis regulators to predict ferroptosis in LUAD. LASSO, SVM-RFE and elastic net were used to dissect the differential ferroptosis regulators, and the eight pivotal ferroptosis regulators have considerable ferroptosis prediction ability. It was established that RRM2 and AURKA are key suppressors of ferroptosis, and the depletion of RRM2 and AURKA caused an increase in ferroptosis in H358 cells. In addition, not only did they act as pro-proliferative factors that hindered immune infiltration in LUAD, but they were also essential for anti-PD1 therapy and chemotherapy. In summary, this research confirms the regulatory role of RRM2 and AURKA in ferroptosis, and could be useful in predicting individualized treatment for patients with LUAD.
Collapse
Affiliation(s)
- Lianxiang Luo
- The Marine Biomedical Research Institute, Guangdong Medical University, Zhanjiang, Guangdong, 524023, China; The Marine Biomedical Research Institute of Guangdong Zhanjiang, Zhanjiang, Guangdong, 524023, China.
| | - Xinming Chen
- The First Clinical College, Guangdong Medical University, Zhanjiang, Guangdong, 524023, China
| | - Fangfang Huang
- Graduate School, Guangdong Medical University, Zhanjiang, Guangdong, 524023, China
| |
Collapse
|
4
|
Screening and identification of CNIH4 gene associated with cell proliferation in gastric cancer based on a large-scale CRISPR-Cas9 screening database DepMap. Gene 2023; 850:146961. [DOI: 10.1016/j.gene.2022.146961] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Revised: 09/28/2022] [Accepted: 10/04/2022] [Indexed: 02/05/2023]
|
5
|
Chen W, Lin Y, Jiang M, Wang Q, Shu Q. Identification of LARS as an essential gene for osteosarcoma proliferation through large-Scale CRISPR-Cas9 screening database and experimental verification. Lab Invest 2022; 20:355. [PMID: 35962451 PMCID: PMC9373537 DOI: 10.1186/s12967-022-03571-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Accepted: 08/04/2022] [Indexed: 11/12/2022]
Abstract
Background Osteosarcoma is one of the most malignant tumors, and it occurs mostly in children and adolescents. Currently, surgery and chemotherapy are the main treatments. The recurrence rate is high and the prognosis is often poor. Finding an effective target gene therapy for osteosarcoma may effectively improve its prognosis. Method In this study, genes essential for the survival of osteosarcoma cells were identified by genome-wide screening of CRISPR-Cas9 based on the DepMap database. The expression of these essential genes in osteosarcoma patients’ tissues and normal tissues was identified in the GSE19276 database. Functional pathway enrichment analysis, protein interaction network construction, and LASSO were performed to construct a prognostic risk model based on these essential genes. CCK8 assay was used to detect the effect of essential gene-LARS (Leucyl-TRNA Synthetase 1) on the proliferation of osteosarcoma. Results In this study, 785 genes critical for osteosarcoma cell proliferation were identified from the DepMap. Among these 785 essential genes, 59 DEGs were identified in osteosarcoma tissues. In the functional enrichment analysis, these 59 essential genes were mainly enriched in cell cycle-related signaling pathways. Furthermore, we established a risk score module, including LARS and DNAJC17, screened from these 59 genes, and this module could divide osteosarcoma patients into the low-risk and high-risk groups. In addition, knockdown of LARS expression inhibited the proliferative ability of osteosarcoma cells. A significant correlation was found between LARS expression and Monocytic lineage, T cells, and Fibroblasts. Conclusion In conclusion, LARS was identified as an essential gene for survival in osteosarcoma based on the DepMap database. Knockdown of LARS expression significantly inhibited the proliferation of osteosarcoma cells, suggesting that it is involved in the formation and development of osteosarcoma. The results are useful as a foundation for further studies to elucidate a potential osteosarcoma diagnostic index and therapeutic targets. Supplementary Information The online version contains supplementary material available at 10.1186/s12967-022-03571-9.
Collapse
Affiliation(s)
- Wenhao Chen
- Department of Orthopedics, The Children's Hospital, Zhejiang University School of Medicine, National Children's Regional Medical Center, National Clinical Research Center for Child Health, 3333 Bingsheng Road, Hangzhou, 310052, Zhejiang Province, China
| | - Yuxiang Lin
- Department of Breast Surgery, Fujian Medical University Union Hospital, 29 Xinquan Road, Fuzhou, 350001, Fujian Province, China.,Department of General Surgery, Fujian Medical University Union Hospital, Fuzhou, 350001, Fujian Province, China.,Breast Cancer Institute, Fujian Medical University, Fuzhou, Fujian Province, China
| | - Meichen Jiang
- Department of Pathology, Fujian Medical University Union Hospital, 29 Xinquan Road, Fuzhou, 350001, Fujian Province, China
| | - Qingshui Wang
- College of Life Sciences, Fujian Normal University, 8 South Xuefu Road, Fuzhou, 350117, Fujian Province, China.
| | - Qiang Shu
- The Children's Hospital, Zhejiang University School of Medicine, National Children's Regional Medical Center, National Clinical Research Center for Child Health, 3333 Bingsheng Road, Hangzhou, 310052, Zhejiang Province, China.
| |
Collapse
|
6
|
Sun JX, Liu CQ, Xu JZ, An Y, Xu MY, Zhong XY, Zeng N, Ma SY, He HD, Zhang ZB, Wang SG, Xia QD. A Four-Cell-Senescence-Regulator-Gene Prognostic Index Verified by Genome-Wide CRISPR Can Depict the Tumor Microenvironment and Guide Clinical Treatment of Bladder Cancer. Front Immunol 2022; 13:908068. [PMID: 35898492 PMCID: PMC9312376 DOI: 10.3389/fimmu.2022.908068] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Accepted: 06/08/2022] [Indexed: 01/10/2023] Open
Abstract
Bladder cancer (BCa) is the 10th most commonly diagnosed cancer worldwide, and cellular senescence is defined as a state of permanent cell cycle arrest and considered to play important roles in the development and progression of tumor. However, the comprehensive effect of senescence in BCa has not ever been systematically evaluated. Using the genome-wide CRISPR screening data acquired from DepMap (Cancer Dependency Map), senescence genes from the CellAge database, and gene expression data from The Cancer Genome Atlas (TCGA), we screened out 12 senescence genes which might play critical roles in BCa. A four-cell-senescence-regulator-gene prognostic index was constructed using the least absolute shrinkage and selection operator (LASSO) and multivariate COX regression model. The transcriptomic data and clinical information of BCa patients were downloaded from TCGA and Gene Expression Omnibus (GEO). We randomly divided the patients in TCGA cohort into training and testing cohorts and calculated the risk score according to the expression of the four senescence genes. The validity of this risk score was validated in the testing cohort (TCGA) and validation cohort (GSE13507). The Kaplan–Meier curves revealed a significant difference in the survival outcome between the high- and low-risk score groups. A nomogram including the risk score and other clinical factors (age, gender, stage, and grade) was established with better predictive capacity of OS in 1, 3, and 5 years. Besides, we found that patients in the high-risk group had higher tumor mutation burden (TMB); lower immune, stroma, and ESTIMATE scores; higher tumor purity; aberrant immune functions; and lower expression of immune checkpoints. We also performed gene set variation analysis (GSVA) and gene set enrichment analysis (GSEA) to investigate the interaction between risk score and hallmark pathways and found that a high risk score was connected with activation of senescence-related pathways. Furthermore, we found that a high risk score was related to better response to immunotherapy and chemotherapy. In conclusion, we identified a four-cell-senescence-regulator-gene prognostic index in BCa and investigated its relationship with TMB, the immune landscape of tumor microenvironment (TME), and response to immunotherapy and chemotherapy, and we also established a nomogram to predict the prognosis of patients with BCa.
Collapse
Affiliation(s)
| | | | | | | | | | | | | | | | | | - Zong-Biao Zhang
- *Correspondence: Zong-Biao Zhang, ; Shao-Gang Wang, ; Qi-Dong Xia,
| | - Shao-Gang Wang
- *Correspondence: Zong-Biao Zhang, ; Shao-Gang Wang, ; Qi-Dong Xia,
| | - Qi-Dong Xia
- *Correspondence: Zong-Biao Zhang, ; Shao-Gang Wang, ; Qi-Dong Xia,
| |
Collapse
|
7
|
Jiang X, Qin N, Hua T, Wei X, Li Y, Chen C, Gong L, Liu S, Wang C, Yin R, Jiang Y, Dai J, Xu L, Shen H, Ma H. Functional characterization and clinical significance of super-enhancers in lung adenocarcinoma. Mol Carcinog 2022; 61:776-786. [PMID: 35596703 DOI: 10.1002/mc.23419] [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: 01/17/2022] [Revised: 04/10/2022] [Accepted: 05/03/2022] [Indexed: 11/06/2022]
Abstract
Super-enhancers (SEs) are important transcriptional regulators in tumorigenesis; however, the functional characterization and clinical significance of SEs in lung adenocarcinoma (LUAD) remain unclear. By using H3K27ac ChIP-seq data of two LUAD cell lines and eight lung tissues, we detected 1045 cancer-specific and 5032 normal-specific SEs. Compared to normal-specific SEs, cancer-specific SEs have different regulatory mechanisms where associated target genes were enriched in critical tumor-related pathways and tended to be regulated by transcription factors of Fos Proto-Oncogene, AP-1 Transcription Factor Subunit and Jun Proto-Oncogene, AP-1 Transcription Factor Subunit families. By using expression data of 513 LUAD and 57 adjacent samples from The Cancer Genome Atlas and 80 tumor-normal paired LUAD samples from the Nanjing Lung Cancer Cohort study, we performed differential expression analysis of target genes for SEs and defined 243 crucial SEs. Unsupervised clustering of crucial SEs revealed two subtypes with different levels of genomic aberrations (i.e., mutation and copy number alteration) and clinical outcomes (progression-free interval: p = 0.030; disease-free interval: p = 0.047). In addition, patients with adverse clinical outcomes were more sensitive to three small molecule inhibitors (bortezomib, doxorubicin, and etoposide), and their targets (PSMB5 and TOP2A) also have elevated expression levels among these patients. Taken together, our findings provided a comprehensive characterization of SEs in LUAD and emphasized their clinical significance in LUAD therapy.
Collapse
Affiliation(s)
- Xiangxiang Jiang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Na Qin
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China
| | - Tingting Hua
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Xiaoxia Wei
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Yuancheng Li
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Congcong Chen
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Linnan Gong
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Su Liu
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Cheng Wang
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China.,Department of Bioinformatics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, China
| | - Rong Yin
- Jiangsu Key Laboratory of Molecular and Translational Cancer Research, Department of Thoracic Surgery, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
| | - Yue Jiang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China
| | - Juncheng Dai
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China
| | - Lin Xu
- Jiangsu Key Laboratory of Molecular and Translational Cancer Research, Department of Thoracic Surgery, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
| | - Hongbing Shen
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China.,Research Units of Cohort Study on Cardiovascular Diseases and Cancers, Chinese Academy of Medical Sciences, Beijing, China
| | - Hongxia Ma
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China.,Research Units of Cohort Study on Cardiovascular Diseases and Cancers, Chinese Academy of Medical Sciences, Beijing, China
| |
Collapse
|
8
|
Li X, Xiong K, Bi D, Zhao C. A Novel CRISPR/Cas9 Screening Potential Index for Prognostic and Immunological Prediction in Low-Grade Glioma. Front Genet 2022; 13:839884. [PMID: 35586564 PMCID: PMC9109250 DOI: 10.3389/fgene.2022.839884] [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: 12/26/2021] [Accepted: 03/18/2022] [Indexed: 12/05/2022] Open
Abstract
Glioma is a malignancy with the highest mortality in central nervous system disorders. Here, we implemented the computational tools based on CRISPR/Cas9 to predict the clinical outcomes and biological characteristics of low-grade glioma (LGG). The transcriptional expression profiles and clinical phenotypes of LGG patients were retrieved from The Cancer Genome Atlas and Chinese Glioma Genome Atlas. The CERES algorithm was used to screen for LGG-lethal genes. Cox regression and random survival forest were adopted for survival-related gene selection. Nonnegative matrix factorization distinguished patients into different clusters. Single-sample gene set enrichment analysis was employed to create a novel CRISPR/Cas9 screening potential index (CCSPI), and patients were stratified into low- and high-CCSPI groups. Survival analysis, area under the curve values (AUCs), nomogram, and tumor microenvironment exploration were included for the model validation. A total of 20 essential genes in LGG were used to classify patients into two clusters and construct the CCSPI system. High-CCSPI patients were associated with a worse prognosis of both training and validation set (p < 0.0001) and higher immune fractions than low-CCSPI individuals. The CCSPI system had a promising performance with 1-, 3-, and 5-year AUCs of 0.816, 0.779, 0.724, respectively, and the C-index of the nomogram model reached 0.743 (95% CI = 0.725–0.760). Immune-infiltrating cells and immune checkpoints such as PD-1/PD-L1 and POLD3 were positively associated with CCSPI. In conclusion, the CCSPI had prognostic value in LGG, and the model will deepen our cognition of the interaction between the CNS and immune system in different LGG subtypes.
Collapse
Affiliation(s)
- Xiangpan Li
- Department of Oncology, Renmin Hospital of Wuhan University, Wuhan, China
| | - Kewei Xiong
- Department of Oncology, Renmin Hospital of Wuhan University, Wuhan, China.,School of Mathematics and Statistics, Central China Normal University, Wuhan, China
| | - Dong Bi
- Department of Oncology, Renmin Hospital of Wuhan University, Wuhan, China
| | - Chen Zhao
- Department of Oncology, Renmin Hospital of Wuhan University, Wuhan, China
| |
Collapse
|
9
|
Li F, Lai L, You Z, Cheng H, Guo G, Tang C, Xu L, Liu H, Zhong W, Lin Y, Wang Q, Lin Y, Wei Y. Identification of UBE2I as a Novel Biomarker in ccRCC Based on a Large-Scale CRISPR-Cas9 Screening Database and Immunohistochemistry. Front Mol Biosci 2022; 9:813428. [PMID: 35211510 PMCID: PMC8861443 DOI: 10.3389/fmolb.2022.813428] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Accepted: 01/03/2022] [Indexed: 12/12/2022] Open
Abstract
Background: The genome-wide CRISPR-cas9 dropout screening has emerged as an outstanding approach for characterization of driver genes of tumor growth. The present study aims to investigate core genes related to clear cell renal cell carcinoma (ccRCC) cell viability by analyzing the CRISPR-cas9 screening database DepMap, which may provide a novel target in ccRCC therapy. Methods: Candidate genes related to ccRCC cell viability by CRISPR-cas9 screening from DepMap and genes differentially expressed between ccRCC tissues and normal tissues from TCGA were overlapped. Weighted gene coexpression network analysis, pathway enrichment analysis, and protein–protein interaction network analysis were applied for the overlapped genes. The least absolute shrinkage and selection operator (LASSO) regression was used to construct a signature to predict the overall survival (OS) of ccRCC patients and validated in the International Cancer Genome Consortium (ICGC) and E-MTAB-1980 database. Core protein expression was determined using immunohistochemistry in 40 cases of ccRCC patients. Results: A total of 485 essential genes in the DepMap database were identified and overlapped with differentially expressed genes in the TCGA database, which were enriched in the cell cycle pathway. A total of four genes, including UBE2I, NCAPG, NUP93, and TOP2A, were included in the gene signature based on LASSO regression. The high-risk score of ccRCC patients showed worse OS compared with these low-risk patients in the ICGC and E-MTAB-1980 validation cohort. UBE2I was screened out as a key gene. The immunohistochemistry indicated UBE2I protein was highly expressed in ccRCC tissues, and a high-level nuclear translocation of UBE2I occurs in ccRCC. Based on the area under the curve (AUC) values, nuclear UBE2I had the best diagnostic power (AUC = 1). Meanwhile, the knockdown of UBE2I can inhibit the proliferation of ccRCC cells. Conclusion: UBE2I, identified by CRISPR-cas9 screening, was a core gene-regulating ccRCC cell viability, which accumulated in the nucleus and acted as a potential novel promising diagnostic biomarker for ccRCC patients. Blocking the nuclear translocation of UBE2I may have potential therapeutic value with ccRCC patients.
Collapse
Affiliation(s)
- Feng Li
- Shengli Clinical Medical College, Fujian Medical University, Fuzhou, China
- Department of Pathology, Fujian Provincial Hospital, Fuzhou, China
- The School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China
- *Correspondence: Feng Li, ; Qingshui Wang, ; Yao Lin, ; Yongbao Wei,
| | - Li Lai
- Shengli Clinical Medical College, Fujian Medical University, Fuzhou, China
- Central Laboratory, Fujian Provincial Hospital, Fuzhou, China
| | - Zhijie You
- Shengli Clinical Medical College, Fujian Medical University, Fuzhou, China
- Department of Pathology, Fujian Provincial Hospital, Fuzhou, China
| | - Hui Cheng
- Shengli Clinical Medical College, Fujian Medical University, Fuzhou, China
- Department of Pathology, Fujian Provincial Hospital, Fuzhou, China
| | - Guodong Guo
- Shengli Clinical Medical College, Fujian Medical University, Fuzhou, China
- Department of Pathology, Fujian Provincial Hospital, Fuzhou, China
| | - Chenchen Tang
- Shengli Clinical Medical College, Fujian Medical University, Fuzhou, China
- The School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China
| | - Luyun Xu
- Key Laboratory of Optoelectronic Science and Technology for Medicine of Ministry of Education, College of Life Sciences, Fujian Normal University, Fuzhou, China
| | - Hongxia Liu
- Key Laboratory of Optoelectronic Science and Technology for Medicine of Ministry of Education, College of Life Sciences, Fujian Normal University, Fuzhou, China
| | - Wenting Zhong
- Key Laboratory of Optoelectronic Science and Technology for Medicine of Ministry of Education, College of Life Sciences, Fujian Normal University, Fuzhou, China
| | - Youyu Lin
- Key Laboratory of Optoelectronic Science and Technology for Medicine of Ministry of Education, College of Life Sciences, Fujian Normal University, Fuzhou, China
| | - Qingshui Wang
- Key Laboratory of Optoelectronic Science and Technology for Medicine of Ministry of Education, College of Life Sciences, Fujian Normal University, Fuzhou, China
- Fujian Provincial Key Laboratory of Hepatic Drug Research, Fuzhou, China
- *Correspondence: Feng Li, ; Qingshui Wang, ; Yao Lin, ; Yongbao Wei,
| | - Yao Lin
- Key Laboratory of Optoelectronic Science and Technology for Medicine of Ministry of Education, College of Life Sciences, Fujian Normal University, Fuzhou, China
- Central Laboratory at the Second Affiliated Hospital of Fujian Traditional Chinese Medical University, Innovation and Transformation Center, Fujian University of Traditional Chinese Medicine, Fuzhou, China
- *Correspondence: Feng Li, ; Qingshui Wang, ; Yao Lin, ; Yongbao Wei,
| | - Yongbao Wei
- Shengli Clinical Medical College, Fujian Medical University, Fuzhou, China
- Department of Urology, Fujian Provincial Hospital, Fuzhou, China
- *Correspondence: Feng Li, ; Qingshui Wang, ; Yao Lin, ; Yongbao Wei,
| |
Collapse
|