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Nadri P, Nadri T, Gholami D, Zahmatkesh A, Hosseini Ghaffari M, Savvulidi Vargova K, Georgijevic Savvulidi F, LaMarre J. Role of miRNAs in assisted reproductive technology. Gene 2024; 927:148703. [PMID: 38885817 DOI: 10.1016/j.gene.2024.148703] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2024] [Revised: 06/11/2024] [Accepted: 06/14/2024] [Indexed: 06/20/2024]
Abstract
Cellular proteins and the mRNAs that encode them are key factors in oocyte and sperm development, and the mechanisms that regulate their translation and degradation play an important role during early embryogenesis. There is abundant evidence that expression of microRNAs (miRNAs) is crucial for embryo development and are highly involved in regulating translation during oocyte and early embryo development. MiRNAs are a group of short (18-24 nucleotides) non-coding RNA molecules that regulate post-transcriptional gene silencing. The miRNAs are secreted outside the cell by embryos during preimplantation embryo development. Understanding regulatory mechanisms involving miRNAs during gametogenesis and embryogenesis will provide insights into molecular pathways active during gamete formation and early embryo development. This review summarizes recent findings regarding multiple roles of miRNAs in molecular signaling, plus their transport during gametogenesis and embryo preimplantation.
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Affiliation(s)
- Parisa Nadri
- Department of Animal Science, College of Agriculture, Isfahan University of Technology, Isfahan, Iran
| | - Touba Nadri
- Department of Animal Science, College of Agriculture, Urmia University, Urmia, Iran; Department of Animal Science, College of Agriculture, Tehran University, Karaj, Iran.
| | - Dariush Gholami
- Department of Microbial Biotechniligy, Faculty of Biotechnology, Amol University of Special Modern Technologies, Amol, Iran
| | - Azadeh Zahmatkesh
- Department of Anaerobic Vaccine Research and Production, Razi Vaccine and Serum Research Institute (RVSRI), Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran
| | | | - Karin Savvulidi Vargova
- Institute of Pathological Physiology, First Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Filipp Georgijevic Savvulidi
- Department of Animal Science, Faculty of Agrobiology, Food and Natural Resources, Czech University, Prague, Kamýcká, Czech Republic
| | - Jonathan LaMarre
- Department of Biomedical Sciences, Ontario Veterinary College, University of Guelph, Canada
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Wang L, Han C, Cai C, Wu J, Chen J, Su C. Identification of immune-related gene signature for non-small cell lung cancer patients with immune checkpoint inhibitors. Heliyon 2024; 10:e26974. [PMID: 38463866 PMCID: PMC10923664 DOI: 10.1016/j.heliyon.2024.e26974] [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: 06/02/2023] [Revised: 01/31/2024] [Accepted: 02/22/2024] [Indexed: 03/12/2024] Open
Abstract
Background The utilization of immune checkpoint inhibitors (ICIs) has become the established protocol for treating advanced non-small cell lung cancer (NSCLC). This work aimed to identify the immune-related gene signature that can predict the prognosis of NSCLC patients receiving ICI treatment. Methods The ImmPort database was queried to obtain a list of immune-related genes (IRGs). Differentially expressed IRGs in NSCLC patients were identified using the TCGA database. RNA-seq data and clinical information from NSCLC patients receiving immunotherapy were obtained from the GEO database (GSE93157 and ////). A gene signature was generated through multivariate Cox and LASSO regression analyses. The prognostic value and function of this gene signature were thoroughly investigated using comprehensive bioinformatics analyses. Results A total of 6 prognostic-related genes were identified from 617 differentially expressed genes, and two prognostic-related differentially expressed genes (CAMP and IL17A) were determined to construct gene signature. Our gene signature demonstrated superior performance compared to other clinicopathological parameters in predicting the prognosis of NSCLC patients receiving immunotherapy, with an area under the ROC curve (AUC) of 0.812. Furthermore, immune infiltration analysis indicated that the high-risk group was enriched with resting CD4 T cell memory, while the low-risk group showed a "hot" tumor microenvironment that promotes anti-tumor immunity in NSCLC patients. Conclusion Gene signatures based on immune-related genes exhibited excellent indicator performance of prognosis and immune infiltration, which has the potential to be an effective biomarker for NSCLC with ICI treatment.
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Affiliation(s)
- Li Wang
- Department of Medical Oncology, Shanghai Pulmonary Hospital & Thoracic Cancer Institute, Tongji University School of Medicine, Shanghai, 200433, PR China
| | - Chaonan Han
- Department of Medical Oncology, Shanghai Pulmonary Hospital & Thoracic Cancer Institute, Tongji University School of Medicine, Shanghai, 200433, PR China
| | - Chenlei Cai
- Department of Medical Oncology, Shanghai Pulmonary Hospital & Thoracic Cancer Institute, Tongji University School of Medicine, Shanghai, 200433, PR China
| | - Jing Wu
- Department of Medical Oncology, Shanghai Pulmonary Hospital & Thoracic Cancer Institute, Tongji University School of Medicine, Shanghai, 200433, PR China
| | - Jianing Chen
- Department of Medical Oncology, Shanghai Pulmonary Hospital & Thoracic Cancer Institute, Tongji University School of Medicine, Shanghai, 200433, PR China
| | - Chunxia Su
- Department of Medical Oncology, Shanghai Pulmonary Hospital & Thoracic Cancer Institute, Tongji University School of Medicine, Shanghai, 200433, PR China
- Department of Clinical Research Center, Shanghai Pulmonary Hospital & Thoracic Cancer Institute, Tongji University School of Medicine, Shanghai, 200433, PR China
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Dai J, Cai J, Zhang T, Pang M, Xu X, Bai J, Liu Y, Qin Y. Transcriptome and Metabolome Analyses Reveal the Mechanism of Corpus Luteum Cyst Formation in Pigs. Genes (Basel) 2023; 14:1848. [PMID: 37895197 PMCID: PMC10606659 DOI: 10.3390/genes14101848] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Revised: 09/16/2023] [Accepted: 09/21/2023] [Indexed: 10/29/2023] Open
Abstract
Corpus luteum cysts are a serious reproductive disorder that affects the reproductive performance of sows. In this study, transcriptome and metabolome datasets of porcine normal and cyst luteal granulosa cells were generated to explore the molecular mechanism of luteal cyst formation. We obtained 28.9 Gb of high-quality transcriptome data from luteum tissue samples and identified 1048 significantly differentially expressed genes between the cyst and normal corpus luteum samples. Most of the differentially expressed genes were involved in cancer and immune signaling pathways. Furthermore, 22,622 information-containing positive and negative ions were obtained through gas chromatography-mass spectrometry, and 1106 metabolites were successfully annotated. Important differentially abundant metabolites and pathways were identified, among which abnormal lipid and choline metabolism were involved in the formation of luteal cysts. The relationships between granulosa cells of luteal cysts and cancer, immune-related signaling pathways, and abnormalities of lipid and choline metabolism were elaborated, providing new entry points for studying the pathogenesis of porcine luteal cysts.
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Affiliation(s)
- Jiage Dai
- Institute of Animal Husbandry and Veterinary Medicine, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China; (J.D.); (J.C.); (M.P.); (X.X.); (J.B.); (Y.L.)
- College of Animal Sciences and Technology, China Agricultural University, Beijing 100193, China
| | - Jiabao Cai
- Institute of Animal Husbandry and Veterinary Medicine, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China; (J.D.); (J.C.); (M.P.); (X.X.); (J.B.); (Y.L.)
- College of Life Sciences and Food Engineering, Hebei University of Engineering, Handan 056038, China;
| | - Taipeng Zhang
- College of Life Sciences and Food Engineering, Hebei University of Engineering, Handan 056038, China;
| | - Mingyue Pang
- Institute of Animal Husbandry and Veterinary Medicine, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China; (J.D.); (J.C.); (M.P.); (X.X.); (J.B.); (Y.L.)
- Animal Science and Technology College, Beijing University of Agriculture, Beijing 102206, China
| | - Xiaoling Xu
- Institute of Animal Husbandry and Veterinary Medicine, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China; (J.D.); (J.C.); (M.P.); (X.X.); (J.B.); (Y.L.)
| | - Jiahua Bai
- Institute of Animal Husbandry and Veterinary Medicine, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China; (J.D.); (J.C.); (M.P.); (X.X.); (J.B.); (Y.L.)
| | - Yan Liu
- Institute of Animal Husbandry and Veterinary Medicine, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China; (J.D.); (J.C.); (M.P.); (X.X.); (J.B.); (Y.L.)
| | - Yusheng Qin
- Institute of Animal Husbandry and Veterinary Medicine, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China; (J.D.); (J.C.); (M.P.); (X.X.); (J.B.); (Y.L.)
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Ren Z, Wang L, Leng C. PTPRD mutation is a prognostic biomarker for sensitivity to ICIs treatment in advanced non-small cell lung cancer. Aging (Albany NY) 2023; 15:8204-8219. [PMID: 37602864 PMCID: PMC10497019 DOI: 10.18632/aging.204964] [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: 05/02/2023] [Accepted: 07/06/2023] [Indexed: 08/22/2023]
Abstract
BACKGROUND Immune checkpoint inhibitors (ICIs) have become the standard treatment for advanced non-small cell lung cancer (NSCLC). ICIs can provide durable responses and prolong survival for some patients. With the increasing routine of next-generation sequencing (NGS) in clinical practice, it is essential to integrate prognostic factors to establish novel nomograms to improve clinical prediction ability in NSCLC with ICIs treatment. METHODS Clinical information, response data, and genome data of advanced NSCLC treated ICIs were obtained from cBioPortal. The top 20 gene alterations in durable clinical benefit (DCB) were compared with those genes in no durable benefit (NDB). Survival analyses were performed using the Kaplan-Meier plot method and selected clinical variables to develop a novel nomogram. RESULTS The mutation of PTPRD was significantly related to progression free survival (PFS) and overall survival (OS) in advanced NSCLC with ICIs treatment (PFS: p = 0.0441, OS: p = 0.0086). The PTPRD mutation was closely related to tumor mutational burden (TMB) and tumor-infiltrating immune cells (TIICs). Two novel nomograms were built to predict the PFS and OS of advanced NSCLC patients with ICIs treatment. CONCLUSIONS Our study suggested that PTPRD mutations could serve as a predictive biomarker for the sensitivity to ICIs treatment and PFS and OS in advanced NSCLC with ICIs. Our systematic nomograms showed great potential value in clinical application to predict the PFS and OS for advanced NSCLC patients with ICIs.
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Affiliation(s)
- Zhixuan Ren
- Department of Radiation Oncology, Huadong Hospital, Fudan University, Shanghai 200433, P.R. China
| | - Li Wang
- Department of Medical Oncology, Shanghai Pulmonary Hospital and Thoracic Cancer Institute, Tongji University School of Medicine, Shanghai 200433, P.R. China
| | - Chaohui Leng
- Department of Oncology, Jiujiang University Affilliated Hospital, Jiujiang 332000, P.R. China
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Guo JH, Ma YS, Lin JW, Jiang GX, He J, Lu HM, Wu W, Diao X, Fan QY, Wu CY, Liu JB, Fu D, Hou LK. Whole-exome and targeted gene sequencing of large-cell lung carcinoma reveals recurrent mutations in the PI3K pathway. Br J Cancer 2023; 129:366-373. [PMID: 37179440 PMCID: PMC10338432 DOI: 10.1038/s41416-023-02301-2] [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: 12/23/2022] [Revised: 04/25/2023] [Accepted: 05/02/2023] [Indexed: 05/15/2023] Open
Abstract
BACKGROUND Large cell lung carcinoma (LCLC) is an exceptionally aggressive disease with a poor prognosis. At present, little is known about the molecular pathology of LCLC. METHODS Ultra-deep sequencing of cancer-related genes and exome sequencing were used to detect the LCLC mutational in 118 tumor-normal pairs. The cell function test was employed to confirm the potential carcinogenic mutation of PI3K pathway. RESULTS The mutation pattern is determined by the predominance of A > C mutations. Genes with a significant non-silent mutation frequency (FDR) < 0.05) include TP53 (47.5%), EGFR (13.6%) and PTEN (12.1%). Moreover, PI3K signaling (including EGFR, FGRG4, ITGA1, ITGA5, and ITGA2B) is the most mutated pathway, influencing 61.9% (73/118) of the LCLC samples. The cell function test confirmed that the potential carcinogenic mutation of PI3K pathway had a more malignant cell function phenotype. Multivariate analysis further revealed that patients with the PI3K signaling pathway mutations have a poor prognosis (P = 0.007). CONCLUSIONS These results initially identified frequent mutation of PI3K signaling pathways in LCLC and indicate potential targets for the treatment of this fatal type of LCLC.
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Affiliation(s)
- Jun-Hong Guo
- Department of Pathology, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, 200433, China
| | - Yu-Shui Ma
- Institute of Oncology, Affiliated Tumor Hospital of Nantong University, Nantong, 226631, China
| | - Jie-Wei Lin
- Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, 200433, China
| | - Geng-Xi Jiang
- Department of Thoracic Surgery, Navy Military Medical University Affiliated Changhai Hospital, Shanghai, 200433, China
| | - Juan He
- Pharmacy Department, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, 200025, China
| | - Hai-Min Lu
- Department of Thoracic Surgery, Affiliated Tumor Hospital of Nantong University, Nantong, 226631, China
| | - Wei Wu
- Department of Pathology, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, 200433, China
| | - Xun Diao
- Institute of Oncology, Affiliated Tumor Hospital of Nantong University, Nantong, 226631, China
| | - Qi-Yu Fan
- Institute of Oncology, Affiliated Tumor Hospital of Nantong University, Nantong, 226631, China
| | - Chun-Yan Wu
- Department of Pathology, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, 200433, China.
| | - Ji-Bin Liu
- Institute of Oncology, Affiliated Tumor Hospital of Nantong University, Nantong, 226631, China.
| | - Da Fu
- Institute of Oncology, Affiliated Tumor Hospital of Nantong University, Nantong, 226631, China.
| | - Li-Kun Hou
- Department of Pathology, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, 200433, China.
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Tostes K, Siqueira AP, Reis RM, Leal LF, Arantes LMRB. Biomarkers for Immune Checkpoint Inhibitor Response in NSCLC: Current Developments and Applicability. Int J Mol Sci 2023; 24:11887. [PMID: 37569262 PMCID: PMC10418476 DOI: 10.3390/ijms241511887] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Revised: 07/20/2023] [Accepted: 07/21/2023] [Indexed: 08/13/2023] Open
Abstract
Lung cancer has the highest mortality rate among all cancer types, resulting in over 1.8 million deaths annually. Immunotherapy utilizing immune checkpoint inhibitors (ICIs) has revolutionized the treatment of non-small cell lung cancer (NSCLC). ICIs, predominantly monoclonal antibodies, modulate co-stimulatory and co-inhibitory signals crucial for maintaining immune tolerance. Despite significant therapeutic advancements in NSCLC, patients still face challenges such as disease progression, recurrence, and high mortality rates. Therefore, there is a need for predictive biomarkers that can guide lung cancer treatment strategies. Currently, programmed death-ligand 1 (PD-L1) expression is the only established biomarker for predicting ICI response. However, its accuracy and robustness are not consistently reliable. This review provides an overview of potential biomarkers currently under development or in the validation stage that hold promise in improving the classification of responders and non-responders to ICI therapy in the near future.
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Affiliation(s)
- Katiane Tostes
- Molecular Oncology Research Center, Barretos Cancer Hospital, Barretos 14784-400, São Paulo, Brazil; (K.T.)
| | - Aléxia Polo Siqueira
- Molecular Oncology Research Center, Barretos Cancer Hospital, Barretos 14784-400, São Paulo, Brazil; (K.T.)
| | - Rui Manuel Reis
- Molecular Oncology Research Center, Barretos Cancer Hospital, Barretos 14784-400, São Paulo, Brazil; (K.T.)
- Life and Health Sciences Research Institute (ICVS), Medical School, University of Minho, 4710-057 Braga, Portugal
- ICVS/3B’s-PT Government Associate Laboratory, 4806-909 Guimarães, Portugal
| | - Leticia Ferro Leal
- Molecular Oncology Research Center, Barretos Cancer Hospital, Barretos 14784-400, São Paulo, Brazil; (K.T.)
- Barretos School of Health Sciences, Dr. Paulo Prata-FACISB, Barretos 14785-002, São Paulo, Brazil
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Hu X, Guo J, Shi J, Li D, Li X, Zhao W. A 20-gene mutation signature predicts the efficacy of immune checkpoint inhibitor therapy in advanced non-small cell lung cancer patients. BMC Pulm Med 2023; 23:223. [PMID: 37349743 DOI: 10.1186/s12890-023-02512-6] [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: 03/08/2023] [Accepted: 06/07/2023] [Indexed: 06/24/2023] Open
Abstract
BACKGROUND There is an unmet need to identify novel predictive biomarkers that enable more accurate identification of individuals who can benefit from immune checkpoint inhibitor (ICI) therapy. The US FDA recently approved tumor mutational burden (TMB) score of ≥ 10 mut/Mb as a threshold for pembrolizumab treatment of solid tumors. Our study aimed to test the hypothesis that specific gene mutation signature may predict the efficacy of ICI therapy more precisely than high TMB (≥ 10). METHODS We selected 20 candidate genes that may predict for the efficacy of ICI therapy by the analysis of data from a published cohort of 350 advanced non-small cell lung cancer (NSCLC) patients. Then, we compared the influences of various gene mutation signatures on the efficacy of ICI treatment. They were also compared with PD-L1 and TMB. The Kaplan-Meier method was utilized to evaluate the prognosis univariates, while selected univariates were adopted to develop a systematic nomogram. RESULTS A high mutation signature, where three or more of the 20 selected genes were mutated, was associated with the significant benefits of ICI therapy. Specifically, patients with high mutation signature were confirmed to have better prognosis for ICI treatment, compared with those with wild type (the median PFS: 7.17 vs. 2.90 months, p = 0.0004, HR = 0.47 (95% [CI]:0.32-0.68); the median OS: unreached vs. 9 months, p = 1.8E-8, HR = 0.17 (95% [CI]:0.11-0.25)). Moreover, those patients with the high mutation signature achieved significant ICI treatment benefits, while there was no difference of OS and PFS between patients without the signature but TMB-H (≥ 10) and those without the signature and low TMB(< 10). Finally, we constructed a novel nomogram to evaluate the efficacy of ICI therapy. CONCLUSION A high mutational signature with 3 or more of the 20-gene panel could provide more accurate predictions for the outcomes of ICI therapy than TMB ≥ 10 in NSCLC patients.
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Affiliation(s)
- Xilin Hu
- Department of Thoracic Surgery, The First Affiliated Hospital of Ningbo University, 315010, Ningbo, China
| | - Jing Guo
- Department of Thoracic Surgery, The First Affiliated Hospital of Ningbo University, 315010, Ningbo, China
| | - Jianguang Shi
- Department of Thoracic Surgery, The First Affiliated Hospital of Ningbo University, 315010, Ningbo, China
| | - Da Li
- Department of Thoracic Surgery, The First Affiliated Hospital of Ningbo University, 315010, Ningbo, China
| | - Xinjian Li
- Department of Thoracic Surgery, The First Affiliated Hospital of Ningbo University, 315010, Ningbo, China
| | - Weijun Zhao
- Department of Thoracic Surgery, The First Affiliated Hospital of Ningbo University, 315010, Ningbo, China.
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Zheng Y, Dong J, Yang X, Shuai P, Li Y, Li H, Dong S, Gong Y, Liu M, Zeng Q. Benign-malignant classification of pulmonary nodules by low-dose spiral computerized tomography and clinical data with machine learning in opportunistic screening. Cancer Med 2023. [PMID: 37248730 DOI: 10.1002/cam4.5886] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2022] [Revised: 03/14/2023] [Accepted: 03/19/2023] [Indexed: 05/31/2023] Open
Abstract
BACKGROUND Many people were found with pulmonary nodules during physical examinations. It is of great practical significance to discriminate benign and malignant nodules by using data mining technology. METHODS The subjects' demographic data, baseline examination results, and annual follow-up low-dose spiral computerized tomography (LDCT) results were recorded. The findings from annual physical examinations of positive nodules, including highly suspicious nodules and clinically tentative benign nodules, was analyzed. The extreme gradient boosting (XGBoost) model was constructed and the Grid Search CV method was used to select the super parameters. External unit data were used as an external validation set to evaluate the generalization performance of the model. RESULTS A total of 135,503 physical examinees were enrolled. Baseline testing found that 27,636 (20.40%) participants had clinically tentative benign nodules and 611 (0.45%) participants had highly suspicious nodules. The proportion of highly suspicious nodules in participants with negative baseline was about 0.12%-0.46%, which was lower than the baseline level except the follow-up of >5 years. In the 27,636 participants with clinically tentative benign nodules, only in the first year of LDCT re-examination was the proportion of highly suspicious nodules (1.40%) significantly greater than that of baseline screening (0.45%) (p < 0.001), and the proportion of highly suspicious nodules was not different between the baseline screening and other follow-up years (p > 0.05). Furthermore, 322 cases with benign nodules and 196 patients with malignant nodules confirmed by surgery and pathology were compared. A model and the top 15 most important clinical variables were determined by XGBoost algorithm. The area under the curve (AUC) of the model was 0.76 [95% CI: 0.67-0.84], and the accuracy was 0.75. The sensitivity and specificity of the model under this threshold were 0.78 and 0.73, respectively. In the validation of model using external data, the AUC was 0.87 and the accuracy was 0.80. The sensitivity and specificity were 0.83 and 0.77, respectively. CONCLUSIONS It is important that pulmonary nodules could be more accurately identified at the first LDCT examination. A model with 15 variables which are routinely measured in the clinic could be helpful to distinguish benign and malignant nodules. It could help the radiological team issue a more accurate report; and it may guide the clinical team regarding LDCT follow-up.
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Affiliation(s)
- Yansong Zheng
- Department of Health Medicine, Second Medical Center & National Clinical Research Center for Geriatric Diseases, Chinese People's Liberation Army General Hospital, Beijing, China
| | - Jing Dong
- Research of Medical Big Data Center & National Engineering Laboratory for Medical Big Data Application Technology, Chinese PLA General Hospital, Beijing, China
| | - Xue Yang
- Department of Health Medicine, Second Medical Center & National Clinical Research Center for Geriatric Diseases, Chinese People's Liberation Army General Hospital, Beijing, China
| | - Ping Shuai
- Health Management Center, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China
| | - Yongli Li
- Department of Health Management/ Henan Provincial People's Hospital of Zhengzhou University, Henan Key Laboratory of Chronic Disease Management, Zhengzhou, China
| | - Hailin Li
- Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, School of Medicine and Engineering, Beihang University, Beijing, China
- CAS Key Laboratory of Molecular Imaging, Institute of Automation, Beijing, China
| | - Shengyong Dong
- Department of Health Medicine, Second Medical Center & National Clinical Research Center for Geriatric Diseases, Chinese People's Liberation Army General Hospital, Beijing, China
| | - Yan Gong
- Department of Health Medicine, Second Medical Center & National Clinical Research Center for Geriatric Diseases, Chinese People's Liberation Army General Hospital, Beijing, China
| | - Miao Liu
- Graduate School, Chinese PLA general hospital, Beijing, China
| | - Qiang Zeng
- Department of Health Medicine, Second Medical Center & National Clinical Research Center for Geriatric Diseases, Chinese People's Liberation Army General Hospital, Beijing, China
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Moes-Sosnowska J, Skupinska M, Lechowicz U, Szczepulska-Wojcik E, Skronska P, Rozy A, Stepniewska A, Langfort R, Rudzinski P, Orlowski T, Popiel D, Stanczak A, Wieczorek M, Chorostowska-Wynimko J. FGFR1-4 RNA-Based Gene Alteration and Expression Analysis in Squamous Non-Small Cell Lung Cancer. Int J Mol Sci 2022; 23:ijms231810506. [PMID: 36142417 PMCID: PMC9505002 DOI: 10.3390/ijms231810506] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Revised: 08/27/2022] [Accepted: 09/02/2022] [Indexed: 02/07/2023] Open
Abstract
While fibroblast growth factor receptors (FGFRs) are involved in several biological pathways and FGFR inhibitors may be useful in the treatment of squamous non-small cell lung cancer (Sq-NSCLC), FGFR aberrations are not well characterized in Sq-NSCLC. We comprehensively evaluated FGFR expression, fusions, and variants in 40 fresh-frozen primary Sq-NSCLC (stage IA3−IV) samples and tumor-adjacent normal tissues using real-time PCR and next-generation sequencing (NGS). Protein expression of FGFR1−3 and amplification of FGFR1 were also analyzed. FGFR1 and FGFR4 median gene expression was significantly (p < 0.001) decreased in tumors compared with normal tissue. Increased FGFR3 expression enhanced the recurrence risk (hazard ratio 4.72, p = 0.029), while high FGFR4 expression was associated with lymph node metastasis (p = 0.036). Enhanced FGFR1 gene expression was correlated with FGFR1 protein overexpression (r = 0.75, p = 0.0003), but not with FGFR1 amplification. NGS revealed known pathogenic FGFR2,3 variants, an FGFR3::TACC3 fusion, and a novel TACC1::FGFR1 fusion together with FGFR1,2 variants of uncertain significance not previously reported in Sq-NSCLC. These findings expand our knowledge of the Sq-NSCLC molecular background and show that combining different methods increases the rate of FGFR aberrations detection, which may improve patient selection for FGFRi treatment.
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MESH Headings
- Carcinoma, Non-Small-Cell Lung/pathology
- Carcinoma, Squamous Cell/genetics
- Carcinoma, Squamous Cell/pathology
- Humans
- Lung Neoplasms/genetics
- Lung Neoplasms/pathology
- Microtubule-Associated Proteins
- Receptor, Fibroblast Growth Factor, Type 1/genetics
- Receptor, Fibroblast Growth Factor, Type 2/genetics
- Receptor, Fibroblast Growth Factor, Type 3/genetics
- Receptor, Fibroblast Growth Factor, Type 4/genetics
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Affiliation(s)
- Joanna Moes-Sosnowska
- Department of Genetics and Clinical Immunology, National Institute of Tuberculosis and Lung Diseases, 01-138 Warsaw, Poland or
| | - Monika Skupinska
- Preclinical Development Department, Celon Pharma S.A, Research & Development Centre, 05-152 Kazun Nowy, Poland
| | - Urszula Lechowicz
- Department of Genetics and Clinical Immunology, National Institute of Tuberculosis and Lung Diseases, 01-138 Warsaw, Poland or
| | - Ewa Szczepulska-Wojcik
- Department of Pathology, National Institute of Tuberculosis and Lung Diseases, 01-138 Warsaw, Poland
| | - Paulina Skronska
- Department of Genetics and Clinical Immunology, National Institute of Tuberculosis and Lung Diseases, 01-138 Warsaw, Poland or
| | - Adriana Rozy
- Department of Genetics and Clinical Immunology, National Institute of Tuberculosis and Lung Diseases, 01-138 Warsaw, Poland or
| | - Aneta Stepniewska
- Department of Genetics and Clinical Immunology, National Institute of Tuberculosis and Lung Diseases, 01-138 Warsaw, Poland or
| | - Renata Langfort
- Department of Pathology, National Institute of Tuberculosis and Lung Diseases, 01-138 Warsaw, Poland
| | - Piotr Rudzinski
- Department of Surgery, National Institute of Tuberculosis and Lung Diseases, 01-138 Warsaw, Poland
| | - Tadeusz Orlowski
- Department of Surgery, National Institute of Tuberculosis and Lung Diseases, 01-138 Warsaw, Poland
| | - Delfina Popiel
- Preclinical Development Department, Celon Pharma S.A, Research & Development Centre, 05-152 Kazun Nowy, Poland
| | - Aleksandra Stanczak
- Clinical Development Department, Celon Pharma S.A., Research & Development Centre, 05-152 Kazun Nowy, Poland
| | - Maciej Wieczorek
- Preclinical Development Department, Celon Pharma S.A, Research & Development Centre, 05-152 Kazun Nowy, Poland
- Clinical Development Department, Celon Pharma S.A., Research & Development Centre, 05-152 Kazun Nowy, Poland
| | - Joanna Chorostowska-Wynimko
- Department of Genetics and Clinical Immunology, National Institute of Tuberculosis and Lung Diseases, 01-138 Warsaw, Poland or
- Correspondence: or
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Wei FZ, Mei SW, Wang ZJ, Chen JN, Zhao FQ, Li J, Xiao TX, Zhao W, Ma YB, Yuan W, Liu Q. HAMP as a Prognostic Biomarker for Colorectal Cancer Based on Tumor Microenvironment Analysis. Front Oncol 2022; 12:884474. [PMID: 35992796 PMCID: PMC9386429 DOI: 10.3389/fonc.2022.884474] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2022] [Accepted: 06/23/2022] [Indexed: 11/20/2022] Open
Abstract
Colorectal cancer (CRC) is the most common digestive tumor in the world and has a high mortality rate. The development and treatment of CRC are related to the immune microenvironment, but immune response-related prognostic biomarkers are lacking. In this study, we used The Cancer Genome Atlas (TCGA) to explore the tumor microenvironment (TME) and weighted gene coexpression network analysis (WGCNA) to identify significant prognostic genes. We also identified differentially expressed genes in the TCGA data and explored immune-related genes and transcription factors (TFs). Then, we built a TF regulatory network and performed a comprehensive prognostic analysis of an lncRNA-associated competitive endogenous RNA network (ceRNA network) to build a prognostic model. CCR8 and HAMP were identified both in the WGCNA key module and as immune-related genes. HAMP had good prognostic value for CRC and was highly expressed in CRC tissues and had a negative correlation with CD4+ T cells and M0 macrophages based on immunohistochemistry and immunofluorescence staining of clinical specimens.We found that HAMP had high prognostic and therapeutic target value for CRC and was associated with liver metastasis. These analysis results revealed that HAMP may be a candidate immune-related prognostic biomarker for CRC.
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Affiliation(s)
- Fang-Ze Wei
- Department of Colorectal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Shi-Wen Mei
- Department of Colorectal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Zhi-Jie Wang
- Department of Colorectal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jia-Nan Chen
- Department of Colorectal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Fu-Qiang Zhao
- Department of Colorectal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Juan- Li
- Department of Colorectal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Ti-Xian Xiao
- Department of Colorectal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Wei Zhao
- Department of Colorectal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yun-Bin Ma
- Department of Colorectal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Wei Yuan
- State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- *Correspondence: Wei Yuan, ; Qian Liu,
| | - Qian Liu
- Department of Colorectal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- *Correspondence: Wei Yuan, ; Qian Liu,
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11
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Issa M, Klamer BG, Mladkova N, Laliotis GI, Karivedu V, Bhateja P, Byington C, Dibs K, Pan X, Chakravarti A, Grecula J, Jhawar SR, Mitchell D, Baliga S, Old M, Carrau RL, Rocco JW, Blakaj DM, Bonomi M. Update of a prognostic survival model in head and neck squamous cell carcinoma patients treated with immune checkpoint inhibitors using an expansion cohort. BMC Cancer 2022; 22:767. [PMID: 35836204 PMCID: PMC9284772 DOI: 10.1186/s12885-022-09809-5] [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: 04/01/2022] [Accepted: 06/14/2022] [Indexed: 11/15/2022] Open
Abstract
Background Immune checkpoint inhibitors (ICI) treatment in recurrent/metastatic (R/M) head and neck squamous cell carcinoma (HNSCC) offers new therapeutic venues. We have previously developed a predictive survival model in this patient population based on clinical parameters, and the purpose of this study was to expand the study cohort and internally validate the model. Methods A single institutional retrospective analysis of R/M HNSCC patients treated with ICI. Clinical parameters collected included p-16 status, hemoglobin (Hb), albumin (Alb), lactate dehydrogenase (LDH), neutrophil, lymphocyte and platelet counts. Cox proportional hazard regression was used to assess the impact of patient characteristics and clinical variables on survival. A nomogram was created using the rms package to generate individualized survival prediction. Results 201 patients were included, 47 females (23%), 154 males (77%). Median age was 61 years (IQR: 55-68). P-16 negative (66%). Median OS was 12 months (95% CI: 9.4, 14.9). Updated OS model included age, sex, absolute neutrophil count, absolute lymphocyte count, albumin, hemoglobin, LDH, and p-16 status. We stratified patients into three risk groups based on this model at the 0.33 and 0.66 quantiles. Median OS in the optimal risk group reached 23.7 months (CI: 18.5, NR), 13.8 months (CI: 11.1, 20.3) in the average risk group, and 2.3 months (CI: 1.7, 4.4) in the high-risk group. Following internal validation, the discriminatory power of the model reached a c-index of 0.72 and calibration slope of 0.79. Conclusions Our updated nomogram could assist in the precise selection of patients for which ICI could be beneficial and cost-effective.
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Affiliation(s)
- Majd Issa
- Department of Internal Medicine, Division of Medical Oncology, The Ohio State University Wexner Medical Center, Columbus, OH, 43210, USA.
| | - Brett G Klamer
- Center for Biostatistics, Department of Biomedical Informatics, The Ohio State University, Columbus, OH, 43210, USA
| | - Nikol Mladkova
- Division of Radiation Oncology, The Ohio State University Wexner Medical Center, Columbus, OH, 43210, USA
| | - Georgios I Laliotis
- Sidney Kimmel Comprehensive Cancer Center and Department of Oncology, Johns Hopkins University, Baltimore, MD, 21231, USA
| | - Vidhya Karivedu
- Department of Internal Medicine, Division of Medical Oncology, The Ohio State University Wexner Medical Center, Columbus, OH, 43210, USA
| | - Priyanka Bhateja
- Department of Internal Medicine, Division of Medical Oncology, The Ohio State University Wexner Medical Center, Columbus, OH, 43210, USA
| | - Chase Byington
- Department of Internal Medicine, Division of Medical Oncology, The Ohio State University Wexner Medical Center, Columbus, OH, 43210, USA
| | - Khaled Dibs
- Division of Radiation Oncology, The Ohio State University Wexner Medical Center, Columbus, OH, 43210, USA
| | - Xueliang Pan
- Center for Biostatistics, Department of Biomedical Informatics, The Ohio State University, Columbus, OH, 43210, USA
| | - Arnab Chakravarti
- Division of Radiation Oncology, The Ohio State University Wexner Medical Center, Columbus, OH, 43210, USA
| | - John Grecula
- Division of Radiation Oncology, The Ohio State University Wexner Medical Center, Columbus, OH, 43210, USA
| | - Sachin R Jhawar
- Division of Radiation Oncology, The Ohio State University Wexner Medical Center, Columbus, OH, 43210, USA
| | - Darrion Mitchell
- Division of Radiation Oncology, The Ohio State University Wexner Medical Center, Columbus, OH, 43210, USA
| | - Sujith Baliga
- Division of Radiation Oncology, The Ohio State University Wexner Medical Center, Columbus, OH, 43210, USA
| | - Matthew Old
- Department of Otolaryngology - Head and Neck Surgery, The Ohio State University Wexner Medical Center, Columbus, OH, 43210, USA
| | - Ricardo L Carrau
- Department of Otolaryngology - Head and Neck Surgery, The Ohio State University Wexner Medical Center, Columbus, OH, 43210, USA
| | - James W Rocco
- Department of Otolaryngology - Head and Neck Surgery, The Ohio State University Wexner Medical Center, Columbus, OH, 43210, USA
| | - Dukagjin M Blakaj
- Division of Radiation Oncology, The Ohio State University Wexner Medical Center, Columbus, OH, 43210, USA
| | - Marcelo Bonomi
- Department of Internal Medicine, Division of Medical Oncology, The Ohio State University Wexner Medical Center, Columbus, OH, 43210, USA
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12
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Cui Y, Liu X, Wu Y, Liang X, Dai J, Zhang Z, Guo R. Deleterious AHNAK2 Mutation as a Novel Biomarker for Immune Checkpoint Inhibitors in Non-Small Cell Lung Cancer. Front Oncol 2022; 12:798401. [PMID: 35359393 PMCID: PMC8960743 DOI: 10.3389/fonc.2022.798401] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Accepted: 02/14/2022] [Indexed: 12/30/2022] Open
Abstract
Immune checkpoint inhibitors (ICIs) have exhibited promising efficacy in non-small cell lung cancer (NSCLC), but the response occurs in only a minority of patients. In clinic, biomarkers such as TMB (tumor mutation burden) and PD-L1 (programmed cell death 1 ligand 1) still have their limitations in predicting the prognosis of ICI treatment. Hence, reliable predictive markers for ICIs are urgently needed. A public immunotherapy dataset with clinical information and mutational data of 75 NSCLC patients was obtained from cBioPortal as the discovery cohort, and another immunotherapy dataset of 249 patients across multiple cancer types was collected as the validation. Integrated bioinformatics analysis was performed to explore the potential mechanism, and immunohistochemistry studies were used to verify it. AHNAK nucleoprotein 2 (AHNAK2) was reported to have pro-tumor growth effects across multiple cancers, while its role in tumor immunity was unclear. We found that approximately 11% of the NSCLC patients harbored AHNAK2 mutations, which were associated with promising outcomes to ICI treatments (ORR, p = 0.013). We further found that AHNAK2 deleterious mutation (del-AHNAK2mut) possessed better predictive function in NSCLC than non-deleterious AHNAK2 mutation (PFS, OS, log-rank p < 0.05), potentially associated with stronger tumor immunogenicity and an activated immune microenvironment. This work identified del-AHNAK2mut as a novel biomarker to predict favorable ICI response in NSCLC.
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Affiliation(s)
- Yanan Cui
- Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Xinyin Liu
- Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Yuemin Wu
- Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Xiao Liang
- Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Jiali Dai
- Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Zhihong Zhang
- Department of Pathology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Renhua Guo
- Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
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13
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Hu X, Xu H, Xue Q, Wen R, Jiao W, Tian K. The role of ERBB4 mutations in the prognosis of advanced non-small cell lung cancer treated with immune checkpoint inhibitors. Mol Med 2021; 27:126. [PMID: 34620079 PMCID: PMC8496027 DOI: 10.1186/s10020-021-00387-z] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Accepted: 09/23/2021] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Immune checkpoint inhibitors (ICIs) have witnessed the achievements of convincing clinical benefits that feature the significantly prolonged overall survival (OS) of patients suffering from advanced non-small cell lung cancer (NSCLC), according to reports recently. Sensitivity to immunotherapy is related to several biomarkers, such as PD-L1 expression, TMB level, MSI-H and MMR. However, a further investigation into the novel biomarkers of the prognosis on ICIs treatment is required. In addition, there is an urgent demand for the establishment of a systematic hazard model to assess the efficacy of ICIs therapy for advanced NSCLC patients. METHODS In this study, the gene mutation and clinical data of NSCLC patients was obtained from the TCGA database, followed by the analysis of the detailed clinical information and mutational data relating to two advanced NSCLC cohorts receiving the ICIs treatment from the cBioPortal of Cancer Genomics. The Kaplan-Meier plot method was used to perform survival analyses, while selected variables were adopted to develop a systematic nomogram. The prognostic significance of ERBB4 in pan-cancer was analyzed by another cohort from the cBioPortal of Cancer Genomics. RESULTS The mutation frequencies of TP53 and ERBB4 were 54% and 8% in NSCLC, respectively. The mutual exclusive analysis in cBioPortal has indicated that ERBB4 does show co-occurencing mutations with TP53. Patients with ERBB4 mutations were confirmed to have better prognosis for ICIs treatment, compared to those seeing ERBB4 wild type (PFS: exact p = 0.017; OS: exact p < 0.01) and only TP53 mutations (OS: p = 0.021). The mutation status of ERBB4 and TP53 was tightly linked to DCB of ICIs treatment, PD-L1 expression, TMB value, and TIICs. Finally, a novel nomogram was built to evaluate the efficacy of ICIs therapy. CONCLUSION ERBB4 mutations could serve as a predictive biomarker for the prognosis of ICIs treatment. The systematic nomogram was proven to have the great potential for evaluating the efficacy of ICIs therapy for advanced NSCLC patients.
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Affiliation(s)
- Xilin Hu
- Department of Thoracic Surgery, The Affiliated Hospital of Qingdao University, Qingdao, 266000, Shandong, China
| | - Hanlin Xu
- Department of Thoracic Surgery, The Affiliated Hospital of Qingdao University, Qingdao, 266000, Shandong, China
| | - Qianwen Xue
- Qingdao Maternal & Child Health and Family Planning Service Center, Qingdao, 266000, Shandong, China
| | - Ruran Wen
- Department of Thoracic Surgery, The Affiliated Hospital of Qingdao University, Qingdao, 266000, Shandong, China
| | - Wenjie Jiao
- Department of Thoracic Surgery, The Affiliated Hospital of Qingdao University, Qingdao, 266000, Shandong, China
| | - Kaihua Tian
- Department of Thoracic Surgery, The Affiliated Hospital of Qingdao University, Qingdao, 266000, Shandong, China.
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14
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Wei FZ, Mei SW, Wang ZJ, Chen JN, Shen HY, Zhao FQ, Li J, Xiao TX, Liu Q. Development and Validation of a Nomogram and a Comprehensive Prognostic Analysis of an LncRNA-Associated Competitive Endogenous RNA Network Based on Immune-Related Genes for Locally Advanced Rectal Cancer With Neoadjuvant Therapy. Front Oncol 2021; 11:697948. [PMID: 34350117 PMCID: PMC8327778 DOI: 10.3389/fonc.2021.697948] [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: 04/20/2021] [Accepted: 06/21/2021] [Indexed: 11/24/2022] Open
Abstract
Colorectal cancer (CRC) is a common digestive tract tumor worldwide. In recent years, neoadjuvant chemoradiotherapy (CRT) has been the most comprehensive treatment for locally advanced rectal cancer (LARC). In this study, we explored immune infiltration in rectal cancer (RC) and identified immune-related differentially expressed genes (IRDEGs). Then, we identified response markers in datasets in GEO databases by principal component analysis (PCA). We also utilized three GEO datasets to identify the up- and downregulated response-related genes simultaneously and then identified genes shared between the PCA markers and three GEO datasets. Based on the hub IRDEGs, we identified target mRNAs and constructed a ceRNA network. Based on the ceRNA network, we explored prognostic biomarkers to develop a prognostic model for RC through Cox regression. We utilized the specimen to validate the expression of the two biomarkers. We also utilized LASSO regression to screen hub IRDEGs and built a nomogram to predict the response of LARC patients to CRT. All of the results show that the nomogram and prognostic model offer good prognostic value and that the ceRNA network can effectively highlight the regulatory relationship. hsa-mir-107 and WDFY3-AS2 may be prognostic biomarkers for RC.
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Affiliation(s)
- Fang-Ze Wei
- Department of Colorectal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Shi-Wen Mei
- Department of Colorectal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Zhi-Jie Wang
- Department of Colorectal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jia-Nan Chen
- Department of Colorectal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Hai-Yu Shen
- Department of Colorectal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Fu-Qiang Zhao
- Department of Colorectal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Juan- Li
- Department of Colorectal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Ti-Xian Xiao
- Department of Colorectal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Qian Liu
- Department of Colorectal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
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