51
|
Murtha JA, Liu N, Birstler J, Hanlon BM, Venkatesh M, Hanrahan LP, Borza T, Kushner DM, Funk LM. Obesity and "obesity-related" cancers: are there body mass index cut-points? Int J Obes (Lond) 2022; 46:1770-1777. [PMID: 35817851 PMCID: PMC9615027 DOI: 10.1038/s41366-022-01178-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Revised: 06/15/2022] [Accepted: 06/23/2022] [Indexed: 11/08/2022]
Abstract
BACKGROUND Despite compelling links between excess body weight and cancer, body mass index (BMI) cut-points, or thresholds above which cancer incidence increased, have not been identified. The objective of this study was to determine if BMI cut-points exist for 14 obesity-related cancers. SUBJECTS/METHODS In this retrospective cohort study, patients 18-75 years old were included if they had ≥2 clinical encounters with BMI measurements in the electronic health record (EHR) at a single academic medical center from 2008 to 2018. Patients who were pregnant, had a history of cancer, or had undergone bariatric surgery were excluded. Adjusted logistic regression was performed to identify cancers that were associated with increasing BMI. For those cancers, BMI cut-points were calculated using adjusted quantile regression for cancer incidence at 80% sensitivity. Logistic and quantile regression models were adjusted for age, sex, race/ethnicity, and smoking status. RESULTS A total of 7079 cancer patients (mean age 58.5 years, mean BMI 30.5 kg/m2) and 270,441 non-cancer patients (mean age 43.8 years, mean BMI 28.8 kg/m2) were included in the study. In adjusted logistic regression analyses, statistically significant associations were identified between increasing BMI and the incidence of kidney, thyroid, and uterine cancer. BMI cut-points were identified for kidney (26.3 kg/m2) and uterine (26.9 kg/m2) cancer. CONCLUSIONS BMI cut-points that accurately predicted development kidney and uterine cancer occurred in the overweight category. Analysis of multi-institutional EHR data may help determine if these relationships are generalizable to other health care settings. If they are, incorporation of BMI into the screening algorithms for these cancers may be warranted.
Collapse
Affiliation(s)
| | - Natalie Liu
- Department of Surgery, University of Wisconsin, Madison, WI, USA
| | - Jen Birstler
- Department of Biostatistics and Medical Informatics, University of Wisconsin, Madison, WI, USA
| | - Bret M Hanlon
- Department of Surgery, University of Wisconsin, Madison, WI, USA
- Department of Biostatistics and Medical Informatics, University of Wisconsin, Madison, WI, USA
| | - Manasa Venkatesh
- Department of Surgery, University of Wisconsin, Madison, WI, USA
| | - Lawrence P Hanrahan
- Department of Family Medicine and Community Health, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Tudor Borza
- Department of Urology, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - David M Kushner
- Division of Gynecologic Oncology, Department of Obstetrics and Gynecology, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Luke M Funk
- Department of Surgery, University of Wisconsin, Madison, WI, USA.
- Department of Surgery, William S. Middleton Memorial VA, Madison, WI, USA.
| |
Collapse
|
52
|
Zheng K, Wang Y, Wang J, Wang C, Chen J. Integrated analysis of Helicobacter pylori-related prognostic gene modification patterns in the tumour microenvironment of gastric cancer. Front Surg 2022; 9:964203. [PMID: 36248367 PMCID: PMC9561901 DOI: 10.3389/fsurg.2022.964203] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Accepted: 09/13/2022] [Indexed: 11/30/2022] Open
Abstract
Background Helicobacter pylori (HP) infection is one of the leading causes of gastric cancer (GC). However, the interaction between HP and the TME, and its carcinogenic mechanism remains unknown. Methods The HP-related prognostic genes were identified based on HP infection-related gene markers and HP infection sample datasets by risk method and NMF algorithm. Principal component analysis (PCA) algorithm was used to constructed the HPscore system. The “limma” R package was employed to determine differentially expressed genes. In addition, the R packages, such as “xCell” and “GSVA”, was used to analyze the relationship between the HPscore and tumor microenvironment. Finally, quantitative real-time polymerase chain reaction (qRT-PCR) was conducted to verify the expression levels of 28 HP-related prognostic genes in tissues. Results We successfully identified 28 HP-related prognostic genes that accurately classified the GC population. There are significant differences in survival between different subgroups (high-, low-risk and cluster_1,2). Thereafter, the HPscore system was constructed to evaluate the signatures of the 28 HP-related prognostic genes. The overall survival rate in the high-HPscore group was poor and immunological surveillance was reduced, whereas the low-HPscore group had a survival advantage and was related to the inflammatory response. HPscore was also strongly correlated with the tumour stage, TME cell infiltration and stemness. The qRT-PCR results showed that DOCK4 expression level of 28 HP-related prognostic genes was higher in gastric cancer tissues than in adjacent tissues. Conclusions HP signatures play a crucial role in the TME and tumourigenesis. HPscore evaluation of a single tumour sample can help identify the TME characteristics and the carcinogenic mechanism of GC patients infected with HP, based on which personalized treatment can be administered.
Collapse
Affiliation(s)
- Kaitian Zheng
- Department of Gastrointestinal Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
- Guangxi Key Laboratory of Enhanced Recovery After Surgery for Gastrointestinal Cancer, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
- Guangxi Clinical Research Center for Enhanced Recovery After Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
- Guangxi Zhuang Autonomous Region Engineering Research Center for Artificial Intelligence Analysis of Multimodal Tumor Images, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Ye Wang
- Department of Gastrointestinal Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
- Guangxi Key Laboratory of Enhanced Recovery After Surgery for Gastrointestinal Cancer, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
- Guangxi Clinical Research Center for Enhanced Recovery After Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
- Guangxi Zhuang Autonomous Region Engineering Research Center for Artificial Intelligence Analysis of Multimodal Tumor Images, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Jiancheng Wang
- Department of Gastrointestinal Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
- Guangxi Key Laboratory of Enhanced Recovery After Surgery for Gastrointestinal Cancer, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
- Guangxi Clinical Research Center for Enhanced Recovery After Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
- Guangxi Zhuang Autonomous Region Engineering Research Center for Artificial Intelligence Analysis of Multimodal Tumor Images, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Congjun Wang
- Department of Gastrointestinal Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
- Guangxi Key Laboratory of Enhanced Recovery After Surgery for Gastrointestinal Cancer, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
- Guangxi Clinical Research Center for Enhanced Recovery After Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
- Guangxi Zhuang Autonomous Region Engineering Research Center for Artificial Intelligence Analysis of Multimodal Tumor Images, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Junqiang Chen
- Department of Gastrointestinal Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
- Guangxi Key Laboratory of Enhanced Recovery After Surgery for Gastrointestinal Cancer, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
- Guangxi Clinical Research Center for Enhanced Recovery After Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
- Guangxi Zhuang Autonomous Region Engineering Research Center for Artificial Intelligence Analysis of Multimodal Tumor Images, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
- Correspondence: Jun-Qiang Chen
| |
Collapse
|
53
|
Radiomic Analysis for Pretreatment Prediction of Recurrence Post-Radiotherapy in Cervical Squamous Cell Carcinoma Cancer. Diagnostics (Basel) 2022; 12:diagnostics12102346. [PMID: 36292034 PMCID: PMC9600567 DOI: 10.3390/diagnostics12102346] [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: 09/14/2022] [Revised: 09/21/2022] [Accepted: 09/23/2022] [Indexed: 11/30/2022] Open
Abstract
Background: The current study aims to predict the recurrence of cervical cancer patients treated with radiotherapy from radiomics features on pretreatment T1- and T2-weighted MR images. Methods: A total of 89 patients were split into model training (63 patients) and model testing (26 patients). The predictors of recurrence were selected using the least absolute shrinkage and selection operator (LASSO) regression. The machine learning used neural network classifiers. Results: Using LASSO analysis of radiomics, we found 25 features from the T1-weighted and 4 features from T2-weighted MR images, respectively. The accuracy was highest with the combination of T1- and T2-weighted MR images. The model performances with T1- or T2-weighted MR images were 86.4% or 89.4% accuracy, 74.9% or 38.1% sensitivity, 81.8% or 72.2% specificity, and 0.89 or 0.69 of the area under the curve (AUC). The model performance with the combination of T1- and T2-weighted MR images was 93.1% accuracy, 81.6% sensitivity, 88.7% specificity, and 0.94 of AUC. Conclusions: The radiomics analysis with T1- and T2-weighted MR images could highly predict the recurrence of cervix cancer after radiotherapy. The variation of the distribution and the difference in the pixel number at the peripheral and the center were important predictors.
Collapse
|
54
|
Wang X, Lu J, Song Z, Zhou Y, Liu T, Zhang D. From past to future: Bibliometric analysis of global research productivity on nomogram (2000-2021). Front Public Health 2022; 10:997713. [PMID: 36203677 PMCID: PMC9530946 DOI: 10.3389/fpubh.2022.997713] [Citation(s) in RCA: 33] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Accepted: 09/02/2022] [Indexed: 01/26/2023] Open
Abstract
Background Nomogram, a visual clinical predictive model, provides a scientific basis for clinical decision making. Herein, we investigated 20 years of nomogram research responses, focusing on current and future trends and analytical challenges. Methods We mined data of scientific literature from the Core Collection of Web of Science, searching for the original articles with title "Nomogram*/Parton Table*/Parton Nomogram*", published within January 1st, 2000 to December 30th, 2021. Data records were validated using HistCite Version and analyzed with a transformable statistical method, the Bibliometrix 3.0 package of R Studio. Results In total, 4,176 original articles written by 19,158 authors were included from 915 sources. Annually, Nomogram publications are continually produced, which have rapidly grown since 2018. China published the most articles; however, its total citations ranked second after the United States. Both total citations and average article citations in the United States rank first globally, and a high degree of cooperation exists between countries. Frontiers in Oncology published the most papers (238); this number has grown rapidly since 2019. Journal of Urology had the highest H-index, with an average increase in publications over the past 20 years. Most research topics were tumor-related, among which tumor risk prediction and prognostic evaluation were the main contents. Research on prognostic assessment is more published and advanced, while risk prediction and diagnosis have good developmental prospects. Furthermore, nomogram of the urinary system has been highly developed. Following advancements in nomogram modeling, it has recently been applied to non-oncological subjects. Conclusion This bibliometric analysis provides a comprehensive overview of the current nomogram status, which could enable better understanding of its development over the years, and provide global researchers a comprehensive analysis and structured information to help identify hot spots and gaps in future research.
Collapse
Affiliation(s)
- Xiaoxue Wang
- Department of Health Management, Shengjing Hospital of China Medical University, Shenyang, China
| | - Jingliang Lu
- Lanzhou Information Center, Chinese Academy of Sciences, Lanzhou, China
| | - Zixuan Song
- Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Yangzi Zhou
- Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Tong Liu
- Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China,Tong Liu
| | - Dandan Zhang
- Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China,*Correspondence: Dandan Zhang
| |
Collapse
|
55
|
Chen J, Yao S, Sun Z, Wang Y, Yue J, Cui Y, Yu C, Xu H, Li L. The pattern of expression and prognostic value of key regulators for m7G RNA methylation in hepatocellular carcinoma. Front Genet 2022; 13:894325. [PMID: 36118897 PMCID: PMC9478798 DOI: 10.3389/fgene.2022.894325] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Accepted: 07/26/2022] [Indexed: 11/13/2022] Open
Abstract
N7-methylguanosine (m7G) modification on internal RNA positions plays a vital role in several biological processes. Recent research shows m7G modification is associated with multiple cancers. However, in hepatocellular carcinoma (HCC), its implications remain to be determined. In this place, we need to interrogate the mRNA patterns for 29 key regulators of m7G RNA modification and assess their prognostic value in HCC. Initial, the details from The Cancer Genome Atlas (TCGA) database concerning transcribed gene data and clinical information of HCC patients were inspected systematically. Second, according to the mRNA profiles of 29 m7G RNA methylation regulators, two clusters (named 1 and 2, respectively) were identified by consensus clustering. Furthermore, robust risk signature for seven m7G RNA modification regulators was constructed. Last, we used the Gene Expression Omnibus (GEO) dataset to validate the prognostic associations of the seven-gene risk signature. We figured out that 24/29 key regulators of m7G RNA modification varied remarkably in their grades of expression between the HCC and the adjacent tumor control tissues. Cluster one compared with cluster two had a substandard prognosis and was also positively correlated with T classification (T), pathological stage, and vital status (fustat) significantly. Consensus clustering results suggested the expression pattern of m7G RNA modification regulators was correlated with the malignancy of HCC strongly. In addition, cluster one was extensively enriched in metabolic-related pathways. Seven optimal genes (METTL1, WDR4, NSUN2, EIF4E, EIF4E2, NCBP1, and NCBP2) were selected to establish the risk model for HCC. Indicating by further analyses and validation, the prognostic model has fine anticipating command and this probability signature might be a self supporting presage factor for HCC. Finally, a new prognostic nomogram based on age, gender, pathological stage, histological grade, and prospects were established to forecast the prognosis of HCC patients accurately. In essence, we detected association of HCC severity and expression levels of m7G RNA modification regulators, and developed a risk score model for predicting prognosis of HCC patients’ progression.
Collapse
Affiliation(s)
- Jianxing Chen
- College of Chemistry and Life Science, Chifeng University, Chifeng, China
- Department of General Surgery, The First Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Shibin Yao
- Department of Emergency, Affiliated Hospital of Chifeng University, Chifeng, China
| | - Zhijuan Sun
- International Education School, Chifeng University, Chifeng, China
| | - Yanjun Wang
- Department of Pediatrics, Affiliated Hospital of Chifeng University, Chifeng, China
| | - Jili Yue
- Department of General Surgery, Affiliated Hospital of Chifeng University, Chifeng, China
| | - Yongkang Cui
- Department of General Surgery, The First Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Chengping Yu
- Department of General Surgery, The First Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Haozhi Xu
- Department of General Surgery, The First Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Linqiang Li
- Department of General Surgery, The First Affiliated Hospital of Harbin Medical University, Harbin, China
- Key Laboratory of Hepatosplenic Surgery, Ministry of Education, Harbin Medical University, Harbin, China
- *Correspondence: Linqiang Li,
| |
Collapse
|
56
|
Kt RD, Karthick D, Saravanaraj KS, Jaganathan MK, Ghorai S, Hemdev SP. The Roles of MicroRNA in Pancreatic Cancer Progression. Cancer Invest 2022; 40:700-709. [PMID: 35333689 DOI: 10.1080/07357907.2022.2057526] [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: 07/05/2021] [Revised: 02/21/2022] [Accepted: 03/21/2022] [Indexed: 11/09/2022]
Abstract
Pancreatic Ductal Adenocarcinoma (PDAC) has a poor patient survival rate in comparison with other cancer types, even after targeted therapy, chemotherapy, and immunotherapy. Therefore, a great deal needs to be done to gain a better understanding of the biology and identification of prognostic and predictive markers for the development of superior therapies. The microRNAs (miRNAs) belong to small non-coding RNAs that regulate post-transcriptional gene expression. Several shreds of evidence indicate that miRNAs play an important role in the pathogenesis of pancreatic cancer. Here we review the recent developments in miRNAs and their target role in the development, metastasis, migration, and invasion.
Collapse
Affiliation(s)
- Ramya Devi Kt
- Department of Biotechnology, School of Bioengineering, Faculty of Engineering and Technology, SRM Institute of Science and Technology, Tamil Nadu, India
| | - Dharshene Karthick
- Department of Biotechnology, School of Bioengineering, Faculty of Engineering and Technology, SRM Institute of Science and Technology, Tamil Nadu, India
| | - Kirtikesav Salem Saravanaraj
- Department of Biotechnology, School of Bioengineering, Faculty of Engineering and Technology, SRM Institute of Science and Technology, Tamil Nadu, India
| | - M K Jaganathan
- Department of Biotechnology, School of Bioengineering, Faculty of Engineering and Technology, SRM Institute of Science and Technology, Tamil Nadu, India
| | - Suvankar Ghorai
- Department of Microbiology, Raiganj University, Uttar Dinajpur, India
| | - Sanjana Prakash Hemdev
- School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, USA
| |
Collapse
|
57
|
Guo HL, Lu XZ, Hu HT, Ruan SM, Zheng X, Xie XY, Lu MD, Kuang M, Shen SL, Chen LD, Wang W. Contrast-Enhanced Ultrasound-Based Nomogram: A Potential Predictor of Individually Postoperative Early Recurrence for Patients With Combined Hepatocellular-Cholangiocarcinoma. JOURNAL OF ULTRASOUND IN MEDICINE : OFFICIAL JOURNAL OF THE AMERICAN INSTITUTE OF ULTRASOUND IN MEDICINE 2022; 41:1925-1938. [PMID: 34751450 DOI: 10.1002/jum.15869] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/28/2021] [Revised: 10/17/2021] [Accepted: 10/22/2021] [Indexed: 12/17/2022]
Abstract
PURPOSES To evaluate the postsurgical prognostic implication of contrast-enhanced ultrasound (CEUS) for combined hepatocellular-cholangiocarcinoma (CHC). To build a CEUS-based early recurrence prediction classifier for CHC, in comparison with tumor-node-metastasis (TNM) staging. METHODS The CEUS features and clinicopathological findings of each case were analyzed, and the Liver Imaging Reporting and Data System categories were assigned. The recurrence-free survival associated factors were evaluated by Cox proportional hazard model. Incorporating the independent factors, nomograms were built to estimate the possibilities of 3-month, 6-month, and 1-year recurrence and whose prognostic value was determined by time-dependent receiver operating characteristics, calibration curves, and hazard layering efficiency validation, comparing with TNM staging system. RESULTS In the multivariable analysis, the levels of carbohydrate antigen 19-9, prothrombin time and total bilirubin, and tumor shape, the Liver Imaging Reporting and Data System category were independent factors for recurrence-free survival. The LR-M category showed longer recurrence-free survival than did the LR-4/5 category. The 3-month, 6-month, and 1-year area under the curves of the CEUS-clinical nomogram, clinical nomogram, and TNM staging system were 0.518, 0.552, and 0.843 versus 0.354, 0.240, and 0.624 (P = .048, .049, and .471) vs. 0.562, 0.545, and 0.843 (P = .630, .564, and .007), respectively. The calibration curves of the CEUS-clinical model at different prediction time pionts were all close to the ideal line. The CEUS-clinical model effectively stratified patients into groups of high and low risk of recurrence in both training and validation set, while the TNM staging system only works on the training set. CONCLUSIONS Our CEUS-clinical nomogram is a reliable early recurrence prediction tool for hepatocellular-cholangiocarcinoma and helps postoperative risk stratification.
Collapse
Affiliation(s)
- Huan-Ling Guo
- Department of Medical Ultrasonics, Ultrasomics Artificial Intelligence X-Lab, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Xiao-Zhou Lu
- Department of Traditional Chinese Medicine, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Hang-Tong Hu
- Department of Medical Ultrasonics, Ultrasomics Artificial Intelligence X-Lab, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Si-Min Ruan
- Department of Medical Ultrasonics, Ultrasomics Artificial Intelligence X-Lab, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Xin Zheng
- Department of Medical Ultrasonics, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou, China
| | - Xiao-Yan Xie
- Department of Medical Ultrasonics, Ultrasomics Artificial Intelligence X-Lab, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Ming-De Lu
- Department of Medical Ultrasonics, Ultrasomics Artificial Intelligence X-Lab, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Ming Kuang
- Department of Medical Ultrasonics, Ultrasomics Artificial Intelligence X-Lab, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Shun-Li Shen
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Li-Da Chen
- Department of Medical Ultrasonics, Ultrasomics Artificial Intelligence X-Lab, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Wei Wang
- Department of Medical Ultrasonics, Ultrasomics Artificial Intelligence X-Lab, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| |
Collapse
|
58
|
You D, Zhang S, Yan S, Ding Y, Li C, Cheng X, Wu L, Wang W, Zhang T, Li Z, He Y. SAMHD1 as a prognostic and predictive biomarker in stage II colorectal cancer: A multicenter cohort study. Front Oncol 2022; 12:939982. [PMID: 35978833 PMCID: PMC9376296 DOI: 10.3389/fonc.2022.939982] [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: 05/09/2022] [Accepted: 07/11/2022] [Indexed: 11/19/2022] Open
Abstract
Background The identification of high-risk population patients is key to the personalized treatment options for the stage II colorectal cancers. The use of proteomics in the prognosis of patients with stage II colorectal cancer remains unclear. Methods Using quantitative proteomics, we analyzed proteins that are differentially expressed in the tumor and adjacent normal tissues of 11 paired colorectal cancer patients with and without recurrence selected by a nested case-control design. Of the 21 identified proteins, we selected one candidate protein. The association of the corresponding gene of the selected protein with overall survival (OS) and adjuvant chemotherapy was analyzed using two independent cohorts of patients with stages II colorectal cancer. Results Sterile α motif and histidine-aspartate domain-containing protein 1 (SAMHD1) was selected as the candidate biomarker. A group of 124 patients (12.5%) were stratified into SAMHD1-high subgroup. The 5-year OS rate of SAMHD1-high patients was lower than that of SAMHD1-low patients with stage II colorectal cancer (discovery cohort: hazard ratio [HR] = 2.89, 95% confidence interval [CI], 1.17-7.18, P = 0.016; validation cohort: HR = 2.25, 95% CI, 1.17-4.34, P = 0.013). The Cox multivariate analysis yielded similar results. In a pooled database, the 5-year OS rate was significantly different between patients with and without adjuvant chemotherapy among stage II SAMHD1-low tumors than in patients with stage II SAMHD1-high tumors (88% vs. 77%, P = 0.032). Conclusions SAMHD1-high expression could help in identifying patients with stage II colorectal cancer with poor prognosis and less benefit from adjuvant chemotherapy.
Collapse
Affiliation(s)
- Dingyun You
- Department of Dental Research, The Affiliated Stomatological Hospital of Kunming Medical University, Kunming, China
- Yunnan Key Laboratory of Stomatology, Kunming Medical University, Kunming, China
- Yunnan Key Laboratory of Stem Cell and Regenerative Medicine, Biomedical Engineering Research Center, Kunming Medical University, Kunming, China
| | - Shuai Zhang
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Shan Yan
- Yunnan Key Laboratory of Stem Cell and Regenerative Medicine, Biomedical Engineering Research Center, Kunming Medical University, Kunming, China
| | - Yingying Ding
- Department of Radiology, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Yunnan Cancer Center, Kunming, China
| | - Chunxia Li
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Xianshuo Cheng
- Department of Colorectal Surgery, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Yunnan Cancer Center, Kunming, China
| | - Lin Wu
- Department of Pathology, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Yunnan Cancer Center, Kunming, China
| | - Weizhou Wang
- Department of Orthopedics, The First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Tao Zhang
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Zhenhui Li
- Department of Radiology, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Yunnan Cancer Center, Kunming, China
| | - Yongwen He
- Department of Dental Research, The Affiliated Stomatological Hospital of Kunming Medical University, Kunming, China
| |
Collapse
|
59
|
Kubo K, Kawahara D, Murakami Y, Takeuchi Y, Katsuta T, Imano N, Nishibuchi I, Saito A, Konishi M, Kakimoto N, Yoshioka Y, Toratani S, Ono S, Ueda T, Takeno S, Nagata Y. Development of a radiomics and machine learning model for predicting occult cervical lymph node metastasis in patients with tongue cancer. Oral Surg Oral Med Oral Pathol Oral Radiol 2022; 134:93-101. [PMID: 35431177 DOI: 10.1016/j.oooo.2021.12.122] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2021] [Revised: 11/10/2021] [Accepted: 12/10/2021] [Indexed: 10/19/2022]
Abstract
OBJECTIVE We aimed to develop a predictive model for occult cervical lymph node metastasis in patients with tongue cancer using radiomics and machine learning from pretreatment contrast-enhanced computed tomography. STUDY DESIGN This study included 161 patients with tongue cancer who received local treatment. Computed tomography images were transferred to a radiomics platform. The volume of interest was the total neck node level, including levels Ia, Ib, II, III, and IVa at the ipsilateral side, and each neck node level. The dimensionality of the radiomics features was reduced using least absolute shrinkage and selection operator logistic regression analysis. We compared 5 classifiers with or without the synthetic minority oversampling technique (SMOTE). RESULTS For the analysis at the total neck node level, random forest with SMOTE was the best model, with an accuracy of 0.85 and an area under the curve score of 0.92. For the analysis at each neck node level, a support vector machine with SMOTE was the best model, with an accuracy of 0.96 and an area under the curve score of 0.98. CONCLUSIONS Predictive models using radiomics and machine learning have potential as clinical decision support tools in the management of patients with tongue cancer for prediction of occult cervical lymph node metastasis.
Collapse
Affiliation(s)
- Katsumaro Kubo
- Department of Radiation Oncology, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan
| | - Daisuke Kawahara
- Department of Radiation Oncology, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan
| | - Yuji Murakami
- Department of Radiation Oncology, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan.
| | - Yuki Takeuchi
- Department of Radiation Oncology, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan
| | - Tsuyoshi Katsuta
- Department of Radiation Oncology, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan
| | - Nobuki Imano
- Department of Radiation Oncology, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan
| | - Ikuno Nishibuchi
- Department of Radiation Oncology, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan
| | - Akito Saito
- Department of Radiation Oncology, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan
| | - Masaru Konishi
- Department of Oral and Maxillofacial Radiology, Hiroshima University Hospital, Hiroshima, Japan
| | - Naoya Kakimoto
- Department of Oral and Maxillofacial Radiology, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan
| | - Yukio Yoshioka
- Department of Molecular Oral Medicine and Maxillofacial Surgery, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan
| | - Shigeaki Toratani
- Department of Molecular Oral Medicine and Maxillofacial Surgery, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan
| | - Shigehiro Ono
- Department of Oral and Maxillofacial Surgery, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan
| | - Tsutomu Ueda
- Department of Otolaryngology, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan; Department of Head and Neck Surgery, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan
| | - Sachio Takeno
- Department of Otolaryngology, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan; Department of Head and Neck Surgery, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan
| | - Yasushi Nagata
- Department of Radiation Oncology, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan
| |
Collapse
|
60
|
Nie K, Hu P, Zheng J, Zhang Y, Yang P, Jabbour SK, Yue N, Dong X, Xu S, Shen B, Niu T, Hu X, Cai X, Sun J. Incremental Value of Radiomics in 5-Year Overall Survival Prediction for Stage II-III Rectal Cancer. Front Oncol 2022; 12:779030. [PMID: 35847948 PMCID: PMC9279662 DOI: 10.3389/fonc.2022.779030] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Accepted: 05/30/2022] [Indexed: 11/13/2022] Open
Abstract
Although rectal cancer comprises up to one-third of colorectal cancer cases and several prognosis nomograms have been established for colon cancer, statistical tools for predicting long-term survival in rectal cancer are lacking. In addition, previous prognostic studies did not include much imaging findings, qualitatively or quantitatively. Therefore, we include multiparametric MRI information from both radiologists' readings and quantitative radiomics signatures to construct a prognostic model that allows 5-year overall survival (OS) prediction for advance-staged rectal cancer patients. The result suggested that the model combined with quantitative imaging findings might outperform that of conventional TNM staging or other clinical prognostic factors. It was noteworthy that the identified radiomics signature consisted of three from dynamic contrast-enhanced (DCE)-MRI, four from anatomical MRI, and one from functional diffusion-weighted imaging (DWI). This highlighted the importance of multiparametric MRI to address the issue of long-term survival estimation in rectal cancer. Additionally, the constructed radiomics signature demonstrated value to the conventional prognostic factors in predicting 5-year OS for stage II-III rectal cancer. The presented nomogram also provides a practical example of individualized prognosis estimation and may potentially impact treatment strategies.
Collapse
Affiliation(s)
- Ke Nie
- Department of Radiology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Department of Radiation Oncology, Rutgers-Cancer Institute of New Jersey, Rutgers-Robert Wood Johnson Medical School, New Brunswick, NJ, United States
| | - Peng Hu
- Department of Radiology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Jianjun Zheng
- Department of Radiology, Hwa Mei Hospital, Key Laboratory of Diagnosis and Treatment of Digestive System Tumors of Zhejiang Province, University of Chinese Academy of Sciences, Ningbo, China
| | - Yang Zhang
- Department of Radiation Oncology, Rutgers-Cancer Institute of New Jersey, Rutgers-Robert Wood Johnson Medical School, New Brunswick, NJ, United States
| | - Pengfei Yang
- Institute of Translational Medicine, Zhejiang University, Hangzhou, China
| | - Salma K. Jabbour
- Department of Radiation Oncology, Rutgers-Cancer Institute of New Jersey, Rutgers-Robert Wood Johnson Medical School, New Brunswick, NJ, United States
| | - Ning Yue
- Department of Radiation Oncology, Rutgers-Cancer Institute of New Jersey, Rutgers-Robert Wood Johnson Medical School, New Brunswick, NJ, United States
| | - Xue Dong
- Department of Radiology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Shufeng Xu
- Department of Radiology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Bo Shen
- Department of Radiology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Tianye Niu
- Institute of Translational Medicine, Zhejiang University, Hangzhou, China
| | - Xiaotong Hu
- Biomedical Research Center and Key Laboratory of Biotherapy of Zhejiang Province, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Xiujun Cai
- Department of General Surgery, Innovation Center for Minimally Invasive Techniques and Devices, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Jihong Sun
- Department of Radiology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Innovation Center for Minimally Invasive Techniques and Devices, Zhejiang University, Hangzhou, China
| |
Collapse
|
61
|
Yang B, Liu C, Wu R, Zhong J, Li A, Ma L, Zhong J, Yin S, Zhou C, Ge Y, Tao X, Zhang L, Lu G. Development and Validation of a DeepSurv Nomogram to Predict Survival Outcomes and Guide Personalized Adjuvant Chemotherapy in Non-Small Cell Lung Cancer. Front Oncol 2022; 12:895014. [PMID: 35814402 PMCID: PMC9260694 DOI: 10.3389/fonc.2022.895014] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2022] [Accepted: 05/02/2022] [Indexed: 11/22/2022] Open
Abstract
Objective To develop and validate a DeepSurv nomogram based on radiomic features extracted from computed tomography images and clinicopathological factors, to predict the overall survival and guide individualized adjuvant chemotherapy in patients with non-small cell lung cancer (NSCLC). Patients and Methods This retrospective study involved 976 consecutive patients with NSCLC (training cohort, n=683; validation cohort, n=293). DeepSurv was constructed based on 1,227 radiomic features, and the risk score was calculated for each patient as the output. A clinical multivariate Cox regression model was built with clinicopathological factors to determine the independent risk factors. Finally, a DeepSurv nomogram was constructed by integrating the risk score and independent clinicopathological factors. The discrimination capability, calibration, and clinical usefulness of the nomogram performance were assessed using concordance index evaluation, the Greenwood-Nam-D’Agostino test, and decision curve analysis, respectively. The treatment strategy was analyzed using a Kaplan–Meier curve and log-rank test for the high- and low-risk groups. Results The DeepSurv nomogram yielded a significantly better concordance index (training cohort, 0.821; validation cohort 0.768) with goodness-of-fit (P<0.05). The risk score, age, thyroid transcription factor-1, Ki-67, and disease stage were the independent risk factors for NSCLC.The Greenwood-Nam-D’Agostino test showed good calibration performance (P=0.39). Both high- and low-risk patients did not benefit from adjuvant chemotherapy, and chemotherapy in low-risk groups may lead to a poorer prognosis. Conclusions The DeepSurv nomogram, which is based on the risk score and independent risk factors, had good predictive performance for survival outcome. Further, it could be used to guide personalized adjuvant chemotherapy in patients with NSCLC.
Collapse
Affiliation(s)
- Bin Yang
- Medical Imaging Center, Calmette Hospital and The First Hospital of Kunming (Affiliated Calmette Hospital of Kunming Medical University), Kunming, China
- Department of Medical Imaging, Affiliated Jinling Hospital, Medical School of Nanjing University, Nanjing, China
| | - Chengxing Liu
- Department of Cardiology, Tongji Hospital, Tongji University School of Medicine, Shanghai, China
| | - Ren Wu
- Department of Medical Imaging, Jinling Hospital, Nanjing Medical University, Nanjing, China
| | - Jing Zhong
- Department of Medical Imaging, Affiliated Jinling Hospital, Medical School of Nanjing University, Nanjing, China
| | - Ang Li
- Department of Medical Imaging, Affiliated Jinling Hospital, Medical School of Nanjing University, Nanjing, China
| | - Lu Ma
- Department of Medical Imaging, Affiliated Jinling Hospital, Medical School of Nanjing University, Nanjing, China
| | - Jian Zhong
- Department of Medical Imaging, Affiliated Jinling Hospital, Medical School of Nanjing University, Nanjing, China
| | - Saisai Yin
- Department of Medical Imaging, Affiliated Jinling Hospital, Medical School of Nanjing University, Nanjing, China
| | - Changsheng Zhou
- Department of Medical Imaging, Affiliated Jinling Hospital, Medical School of Nanjing University, Nanjing, China
| | | | - Xinwei Tao
- Siemens Healthineers Ltd., Shanghai, China
| | - Longjiang Zhang
- Department of Medical Imaging, Affiliated Jinling Hospital, Medical School of Nanjing University, Nanjing, China
- *Correspondence: Guangming Lu, ; Longjiang Zhang,
| | - Guangming Lu
- Department of Medical Imaging, Affiliated Jinling Hospital, Medical School of Nanjing University, Nanjing, China
- Department of Medical Imaging, Jinling Hospital, Nanjing Medical University, Nanjing, China
- *Correspondence: Guangming Lu, ; Longjiang Zhang,
| |
Collapse
|
62
|
Jia X, Chu X, Jiang L, Li Y, Zhang Y, Mao Z, Liang T, Du Y, Xu L, Shen Y, Niu G, Meng R, Ni Y, Su C, Guo H. Predicting checkpoint inhibitors pneumonitis in non-small cell lung cancer using a dynamic online hypertension nomogram. Lung Cancer 2022; 170:74-84. [PMID: 35717705 DOI: 10.1016/j.lungcan.2022.06.001] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Revised: 05/30/2022] [Accepted: 06/01/2022] [Indexed: 11/29/2022]
Abstract
OBJECTIVES Checkpoint inhibitors pneumonitis (CIP) is one of the most lethal adverse events in non-small cell lung cancer (NSCLC) patients treated with immune checkpoint inhibitors (ICIs). Currently, there is no recognized and effective predictive model to predict CIP in NSCLC. MATERIALS AND METHODS This study retrospectively analyzed 460 NSCLC patients who were first treated with ICIs. Patients were divided into three cohorts based on the occurrence of CIP: any grade CIP cohort, grade ≥ 2 CIP cohort and grade ≥ 3 CIP cohort. RESULTS A dynamic hypertension nomogram was constructed with elements including hypertension, interstitial lung disease (ILD), emphysema at baseline, and higher baseline platelet/lymphocyte ratio (PLR). The C indices of the training cohort and the internal and external validation cohort in any grade CIP cohort were 0.872, 0.833 and 0.840, respectively. The constructed hypertension nomogram was applied to grade ≥ 2 cohort and grade ≥ 3 cohort, and their C indices were 0.844 and 0.866, respectively. Compared with the non-hypertension nomogram, the hypertension nomogram presented better predictive power. CONCLUSIONS After validated by internal and external validation cohorts, the dynamic online hypertension has the potential to become a convenient, intuitive, and personalized clinical tool for assessing the risk of CIP in NSCLC patients.
Collapse
Affiliation(s)
- Xiaohui Jia
- Department of Medical Oncology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710061, PR China
| | - Xiangling Chu
- Department of Medical Oncology, Shanghai Pulmonary Hospital & Thoracic Cancer Institute, School of Medicine, Tongji University, Shanghai 200433, PR China
| | - Lili Jiang
- Department of Medical Oncology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710061, PR China
| | - Yanlin Li
- Department of Medical Oncology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710061, PR China
| | - Yajuan Zhang
- Department of Medical Oncology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710061, PR China
| | - Ziyang Mao
- Department of Medical Oncology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710061, PR China
| | - Ting Liang
- Department of Radiology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710061, PR China
| | - Yonghao Du
- Department of Radiology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710061, PR China
| | - Longwen Xu
- Department of Medical Oncology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710061, PR China
| | - Yuan Shen
- Department of Epidemiology and Biostatistics, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi 710061, PR China
| | - Gang Niu
- Department of Radiology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710061, PR China
| | - Rui Meng
- Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430022, PR China
| | - Yunfeng Ni
- Department of Thoracic Surgery, Tangdu Hospital, Fourth Military Medical University, Xi'an, Shaanxi 710038, PR China
| | - Chunxia Su
- Department of Medical Oncology, Shanghai Pulmonary Hospital & Thoracic Cancer Institute, School of Medicine, Tongji University, Shanghai 200433, PR China.
| | - Hui Guo
- Department of Medical Oncology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710061, PR China; Key Laboratory of Environment and Genes Related to Diseases, Xi'an Jiaotong University, Ministry of Education of China, Xi'an, Shaanxi 710061, PR China; Bioinspired Engineering and Biomechanics Center (BEBC), Xi'an Jiaotong University, Xi'an, Shaanxi 710061, PR China.
| |
Collapse
|
63
|
Ravegnini G, Gorini F, Dondi G, Tesei M, De Crescenzo E, Morganti AG, Hrelia P, De Iaco P, Angelini S, Perrone AM. Emerging Role of MicroRNAs in the Therapeutic Response in Cervical Cancer: A Systematic Review. Front Oncol 2022; 12:847974. [PMID: 35747791 PMCID: PMC9209727 DOI: 10.3389/fonc.2022.847974] [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: 01/03/2022] [Accepted: 04/13/2022] [Indexed: 11/13/2022] Open
Abstract
Cervical cancer is a common female cancer, with nearly 600,000 cases and more than 300,000 deaths worldwide every year. From a clinical point of view, surgery plays a key role in early cancer management, whereas advanced stages are treated with chemotherapy and/or radiation as adjuvant therapies. Nevertheless, predicting the degree of cancer response to chemotherapy or radiation therapy at diagnosis in order to personalize the clinical approach represents the biggest challenge in locally advanced cancers. The feasibility of such predictive models has been repeatedly assessed using histopathological factors, imaging and nuclear methods, tissue and fluid scans, however with poor results. In this context, the identification of novel potential biomarkers remains an unmet clinical need, and microRNAs (miRNAs) represent an interesting opportunity. With this in mind, the aim of this systematic review was to map the current literature on tumor and circulating miRNAs identified as significantly associated with the therapeutic response in cervical cancer; finally, a perspective point of view sheds light on the challenges ahead in this tumor.Systematic Review RegistrationPROSPERO (CRD42021277980).
Collapse
Affiliation(s)
- Gloria Ravegnini
- Department of Pharmacy and Biotechnology (FABIT), University of Bologna, Bologna, Italy
- *Correspondence: Gloria Ravegnini, ; Pierandrea De Iaco, ; Sabrina Angelini,
| | - Francesca Gorini
- Department of Pharmacy and Biotechnology (FABIT), University of Bologna, Bologna, Italy
| | - Giulia Dondi
- Division of Oncologic Gynecology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy
- Department of Medical and Surgical Sciences (DIMEC), University of Bologna, Bologna, Italy
| | - Marco Tesei
- Division of Oncologic Gynecology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy
| | - Eugenia De Crescenzo
- Division of Oncologic Gynecology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy
- Department of Medical and Surgical Sciences (DIMEC), University of Bologna, Bologna, Italy
| | - Alessio G. Morganti
- Department of Experimental, Diagnostic and Specialty Medicine (DIMES), University of Bologna, Bologna, Italy
| | - Patrizia Hrelia
- Department of Pharmacy and Biotechnology (FABIT), University of Bologna, Bologna, Italy
| | - Pierandrea De Iaco
- Division of Oncologic Gynecology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy
- Department of Medical and Surgical Sciences (DIMEC), University of Bologna, Bologna, Italy
- *Correspondence: Gloria Ravegnini, ; Pierandrea De Iaco, ; Sabrina Angelini,
| | - Sabrina Angelini
- Department of Pharmacy and Biotechnology (FABIT), University of Bologna, Bologna, Italy
- *Correspondence: Gloria Ravegnini, ; Pierandrea De Iaco, ; Sabrina Angelini,
| | - Anna Myriam Perrone
- Division of Oncologic Gynecology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy
- Department of Medical and Surgical Sciences (DIMEC), University of Bologna, Bologna, Italy
| |
Collapse
|
64
|
Zhang Z, Zhu X. MiR-103a-3p Contributes to the Progression of Colorectal Cancer by Regulating GREM2 Expression. Yonsei Med J 2022; 63:520-529. [PMID: 35619575 PMCID: PMC9171664 DOI: 10.3349/ymj.2022.63.6.520] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/19/2021] [Revised: 01/14/2022] [Accepted: 02/04/2022] [Indexed: 12/24/2022] Open
Abstract
PURPOSE Our research aimed to investigate the influence of miR-103a-3p on the growth and apoptosis of colorectal cancer (CRC) cells. MATERIALS AND METHODS Bioinformatics was employed to analyze differentially expressed microRNAs and predict target genes. qRT-PCR was applied to detect the expression of miR-103a-3p in CRC and normal cells. HCT116 and Caco-2 were chosen, and miR-103a-3p mimics, miR-103a-3p inhibitor, as well as specific siRNAs targeting GREM2, were constructed. We subsequently evaluated alternations in cell proliferation, cell cycle and cell cycle regulators, apoptosis, and related proteins (Bcl-2 and Bax) by CCK-8 testing, Western blotting, luciferase reporter, colony formation, and Annexin V-FITC/PI. Possible binding sites for miR-103a-3p on the 3'UTR of GREM2 were checked with luciferase assay, and the impact of GREM2 on miR-103a-3p activity was also validated with above biological function testing. Additionally, the effect of miR-103a-3p knockdown in CRC cells and the molecular mechanism of miR-103a-3p targeting GREM2 were also studied. RESULTS Bioinformatics analysis revealed that miR-103a-3p expression increased remarkably in CRC, and targeted regulatory correlation existed between miR-103a-3p and GREM2. MiR-103a-3p inhibitor significantly impeded proliferative capacity and caused cell cycle arrest, as well as apoptosis, in HCT116 and Caco-2 cells. Consistent with this finding, overexpression of GREM2 showed similar effects to miR-103a-3p inhibition. Moreover, we demonstrated that miR-103a-3p connected target GREM2 and GREM2 knockdown reversed the effects of miR-103a-3p inhibitor on HCT116 and Caco-2 cell proliferation, cell cycle, and apoptosis. Further study showed that miR-103a-3p targeting GREM2 appeared to affect CRC progression via the transforming growth factor-β pathway. CONCLUSION MiR-103a-3p could augment CRC progression by targeting GREM2 and that miR-103a-3p/GREM2 could be potential novel targets for CRC therapy.
Collapse
Affiliation(s)
- Zongxiang Zhang
- Department of General Surgery, Zhejiang Chinese Medicine and Western Medicine Integrated Hospital/Hangzhou Red Cross Hospital, Hangzhou, China
| | - Xiaolian Zhu
- Department of Medical Oncology, Zhuji People's Hospital of Zhejiang Province, Zhuji Affiliated Hospital of Shaoxing University, Zhuji, China.
| |
Collapse
|
65
|
Lu Q, Yu S, Meng X, Shi M, Huang S, Li J, Zhang J, Liang Y, Ji M, Zhao Y, Fan H. MicroRNAs: Important Regulatory Molecules in Acute Lung Injury/Acute Respiratory Distress Syndrome. Int J Mol Sci 2022; 23:5545. [PMID: 35628354 PMCID: PMC9142048 DOI: 10.3390/ijms23105545] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Revised: 05/07/2022] [Accepted: 05/13/2022] [Indexed: 02/06/2023] Open
Abstract
Acute lung injury (ALI)/acute respiratory distress syndrome (ARDS) is an overactivated inflammatory response caused by direct or indirect injuries that destroy lung parenchymal cells and dramatically reduce lung function. Although some research progress has been made in recent years, the pathogenesis of ALI/ARDS remains unclear due to its heterogeneity and etiology. MicroRNAs (miRNAs), a type of small noncoding RNA, play a vital role in various diseases. In ALI/ARDS, miRNAs can regulate inflammatory and immune responses by targeting specific molecules. Regulation of miRNA expression can reduce damage and promote the recovery of ALI/ARDS. Consequently, miRNAs are considered as potential diagnostic indicators and therapeutic targets of ALI/ARDS. Given that inflammation plays an important role in the pathogenesis of ALI/ARDS, we review the miRNAs involved in the inflammatory process of ALI/ARDS to provide new ideas for the pathogenesis, clinical diagnosis, and treatment of ALI/ARDS.
Collapse
Affiliation(s)
- Qianying Lu
- Institute of Disaster and Emergency Medicine, Tianjin University, Tianjin 300072, China; (Q.L.); (S.Y.); (X.M.); (M.S.); (S.H.); (J.L.); (J.Z.); (Y.L.); (M.J.)
- Tianjin Key Laboratory of Disaster Medicine Technology, Tianjin 300072, China
| | - Sifan Yu
- Institute of Disaster and Emergency Medicine, Tianjin University, Tianjin 300072, China; (Q.L.); (S.Y.); (X.M.); (M.S.); (S.H.); (J.L.); (J.Z.); (Y.L.); (M.J.)
- Tianjin Key Laboratory of Disaster Medicine Technology, Tianjin 300072, China
| | - Xiangyan Meng
- Institute of Disaster and Emergency Medicine, Tianjin University, Tianjin 300072, China; (Q.L.); (S.Y.); (X.M.); (M.S.); (S.H.); (J.L.); (J.Z.); (Y.L.); (M.J.)
- Tianjin Key Laboratory of Disaster Medicine Technology, Tianjin 300072, China
| | - Mingyu Shi
- Institute of Disaster and Emergency Medicine, Tianjin University, Tianjin 300072, China; (Q.L.); (S.Y.); (X.M.); (M.S.); (S.H.); (J.L.); (J.Z.); (Y.L.); (M.J.)
- Tianjin Key Laboratory of Disaster Medicine Technology, Tianjin 300072, China
| | - Siyu Huang
- Institute of Disaster and Emergency Medicine, Tianjin University, Tianjin 300072, China; (Q.L.); (S.Y.); (X.M.); (M.S.); (S.H.); (J.L.); (J.Z.); (Y.L.); (M.J.)
- Tianjin Key Laboratory of Disaster Medicine Technology, Tianjin 300072, China
| | - Junfeng Li
- Institute of Disaster and Emergency Medicine, Tianjin University, Tianjin 300072, China; (Q.L.); (S.Y.); (X.M.); (M.S.); (S.H.); (J.L.); (J.Z.); (Y.L.); (M.J.)
- Tianjin Key Laboratory of Disaster Medicine Technology, Tianjin 300072, China
| | - Jianfeng Zhang
- Institute of Disaster and Emergency Medicine, Tianjin University, Tianjin 300072, China; (Q.L.); (S.Y.); (X.M.); (M.S.); (S.H.); (J.L.); (J.Z.); (Y.L.); (M.J.)
- Tianjin Key Laboratory of Disaster Medicine Technology, Tianjin 300072, China
| | - Yangfan Liang
- Institute of Disaster and Emergency Medicine, Tianjin University, Tianjin 300072, China; (Q.L.); (S.Y.); (X.M.); (M.S.); (S.H.); (J.L.); (J.Z.); (Y.L.); (M.J.)
- Tianjin Key Laboratory of Disaster Medicine Technology, Tianjin 300072, China
| | - Mengjun Ji
- Institute of Disaster and Emergency Medicine, Tianjin University, Tianjin 300072, China; (Q.L.); (S.Y.); (X.M.); (M.S.); (S.H.); (J.L.); (J.Z.); (Y.L.); (M.J.)
- Tianjin Key Laboratory of Disaster Medicine Technology, Tianjin 300072, China
| | - Yanmei Zhao
- Institute of Disaster and Emergency Medicine, Tianjin University, Tianjin 300072, China; (Q.L.); (S.Y.); (X.M.); (M.S.); (S.H.); (J.L.); (J.Z.); (Y.L.); (M.J.)
- Tianjin Key Laboratory of Disaster Medicine Technology, Tianjin 300072, China
| | - Haojun Fan
- Institute of Disaster and Emergency Medicine, Tianjin University, Tianjin 300072, China; (Q.L.); (S.Y.); (X.M.); (M.S.); (S.H.); (J.L.); (J.Z.); (Y.L.); (M.J.)
- Tianjin Key Laboratory of Disaster Medicine Technology, Tianjin 300072, China
| |
Collapse
|
66
|
Tao R, Liu Q, Huang R, Wang K, Sun Z, Yang P, Wang J. A Novel TNFSF-Based Signature Predicts the Prognosis and Immunosuppressive Status of Lower-Grade Glioma. BIOMED RESEARCH INTERNATIONAL 2022; 2022:3194996. [PMID: 35592520 PMCID: PMC9112166 DOI: 10.1155/2022/3194996] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/25/2021] [Revised: 02/22/2022] [Accepted: 03/03/2022] [Indexed: 02/08/2023]
Abstract
Purpose Tumour necrosis factor (TNF) superfamilies play important roles in cell proliferation, migration, differentiation, and apoptosis. We believe that TNF has a huge potential and might cast new insight into antitumour therapies. Therefore, we established this signature based on TNF superfamilies. Results A six-gene signature derived from the TNF superfamilies was established. The Riskscore correlated significantly with the expression of immune checkpoint genes and infiltrating M2 macrophages in the tumour specimen. This signature was also associated with mutations in genes that regulate tumour cell proliferation. Univariate and multivariate regression analyses further confirmed the Riskscore, TNFRSF11b, and TNFRSF12a as independent risk factors in The Cancer Genome Atlas and Chinese Glioma Genome Atlas datasets. Conclusion Our signature could accurately predict the prognosis of lower-grade gliomas (LGG). In addition, this six-gene signature could predict the immunosuppressive status of LGG and provide evidence that TNF superfamilies had correlations with some critical mutations that could be effectively targeted now.
Collapse
Affiliation(s)
- Rui Tao
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Qi Liu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Ruoyu Huang
- Department of Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Kuanyu Wang
- Gamma Knife Center, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Zhiyan Sun
- Department of Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Pei Yang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Jiangfei Wang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| |
Collapse
|
67
|
Wang Z, Zhang Z, Zhang K, Zhou Q, Chen S, Zheng H, Wang G, Cai S, Wang F, Li S. Multi-Omics Characterization of a Glycerolipid Metabolism-Related Gene Enrichment Score in Colon Cancer. Front Oncol 2022; 12:881953. [PMID: 35600382 PMCID: PMC9117699 DOI: 10.3389/fonc.2022.881953] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Accepted: 04/04/2022] [Indexed: 11/13/2022] Open
Abstract
Background Glycerolipid metabolism is involved in the genesis and progression of colon cancer. The current study aims at exploring the prognostic value and potential molecular mechanism of glycerolipid metabolism-related genes in colon cancer from the perspective of multi-omics. Methods Clinical information and mRNA expression data of patients with colon cancer were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Single-sample gene set enrichment analysis (ssGSEA) was applied to calculate the glycerolipid metabolism-related gene enrichment score (GLMS). Univariable and multivariable Cox regression analyses were used to study the prognostic value of GLMS in TCGA-COAD and GSE39582 cohorts. The molecular mechanism of the prognostic factor was investigated via immune cell infiltration estimation and correlation analysis of cancer hallmark pathways. Single-cell transcriptomic dataset GSE146771 was used to identify the cell populations which glycerolipid metabolism targeted on. Results The GLMS was found to be associated with tumor location and consensus molecular types (CMSs) of colon cancer in TCGA-COAD cohort (P < 0.05). Patients in the low-GLMS group exhibited poorer overall survival (OS) in TCGA cohort (P = 0.03; HR, 0.63; 95% CI, 0.42-0.94), which was further validated in the GSE39582 dataset (P < 0.001; HR, 0.57; 95% CI, 0.43-0.76). The association between the GLMS and OS remained significant in the multivariable analysis (TCGA cohort: P = 0.04; HR, 0.64; 95% CI, 0.42-0.98; GSE39582 cohort: P < 0.001; HR, 0.60; 95% CI, 0.45-0.80). The GLMS was positively correlated with cancer hallmark pathways including bile acid metabolism, xenobiotic metabolism, and peroxisome and negatively correlated with pathways such as interferon gamma response, allograft rejection, apoptosis, and inflammatory response (P < 0.05). Increased immune infiltration and upregulated expression of immune checkpoints were observed in patients with lower GLMS (P < 0.05). Single-cell datasets verified the different distribution of GLMS in cell subsets, with significant enrichment of GLMS in malignant cells and Tprolif cells. Conclusion We demonstrated that GLMS was a potential independent prognostic factor for colon cancer. The GLMS was also correlated with several cancer hallmark pathways, as well as immune microenvironment.
Collapse
Affiliation(s)
- Zhiyu Wang
- Department of Medical Oncology, Hebei Key Laboratory of Cancer Radiotherapy and Chemotherapy, Affiliated Hospital of Hebei University, Baoding, China
| | - Zhuoqi Zhang
- Department of Gastrointestinal Surgery, Affiliated Hospital of Hebei University, Baoding, China
| | - Ke Zhang
- General Surgery Department, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Qiaoxia Zhou
- Medical Department, Burning Rock Biotech, Guangzhou, China
| | - Sidong Chen
- Medical Department, Burning Rock Biotech, Guangzhou, China
| | - Hao Zheng
- General Surgery Department, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Guoqiang Wang
- Medical Department, Burning Rock Biotech, Guangzhou, China
| | - Shangli Cai
- Medical Department, Burning Rock Biotech, Guangzhou, China
| | - Fujing Wang
- General Surgery Department, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Shenglong Li
- General Surgery Department, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| |
Collapse
|
68
|
Prognostic Risk Signature and Comprehensive Analyses of Endoplasmic Reticulum Stress-Related Genes in Lung Adenocarcinoma. J Immunol Res 2022; 2022:6567916. [PMID: 35571564 PMCID: PMC9096573 DOI: 10.1155/2022/6567916] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Revised: 03/29/2022] [Accepted: 04/04/2022] [Indexed: 12/24/2022] Open
Abstract
Lung adenocarcinoma (LUAD) is the main pathological subtype of non-small-cell lung cancer. Endoplasmic reticulum stress (ERS) has been found to be involved in multiple tumor-related biological processes. At present, a comprehensive analysis of ERS-related genes in LUAD is still lacking. A total of 1034 samples from TCGA and GEO were used to screen differentially expressed genes. Further, Random Forest algorithm was utilized to screen characteristic genes related to prognosis. Then, LASSO Cox regression was used to construct a prognostic signature. Taking the median of signature score as the threshold, patients were separated into high-risk (HR) group and low-risk (LR) group. Tumor mutation burden (TMB), immune cell infiltration, cancer stem cell infiltration, expression of HLA, and immune checkpoints of the two risk groups were analyzed. TIDE score was used to evaluate the response of the two risk groups to immunotherapy. Finally, the gene expression was verified in clinical tissues with RT-qPCR. An eight-gene signature (ADRB2, AGER, CDKN3, GJB2, SFTPC, SLC2A1, SLC6A4, and SSR4) was constructed. TMB and cancer stem cell infiltration were higher in the HR group than the LR group. TIDE score and expression level of HLA were higher in the LR group than the HR group. Expression level of immune checkpoints, including CD28, CD27, IDO2, and others, were higher in the LR group. Multiple drugs approved by FAD, targeting ERS-related genes, were available for the treatment of LUAD. In summary, we established a stable prognostic model based on ERS-related genes to help the classification of LUAD patients and looked for new treatment strategies from aspects of immunity, tumor mutation, and tumor stem cell infiltration.
Collapse
|
69
|
Selven H, Andersen S, Pedersen MI, Lombardi APG, Busund LTR, Kilvær TK. High expression of miR-17-5p and miR-20a-5p predicts favorable disease-specific survival in stage I-III colon cancer. Sci Rep 2022; 12:7080. [PMID: 35490164 PMCID: PMC9056518 DOI: 10.1038/s41598-022-11090-2] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2022] [Accepted: 04/15/2022] [Indexed: 12/23/2022] Open
Abstract
In many types of cancer, microRNAs (miRs) are aberrantly expressed. The aim of this study was to explore the prognostic impact of miR-17-5p and miR-20a-5p in colon cancer. Tumor tissue from 452 stage I-III colon cancer patients was retrospectively collected and tissue microarrays constructed. miR-17-5p and miR-20a-5p expression was evaluated by in situ hybridization and analyzed using digital pathology. Cell line experiments, using HT-29 and CACO-2, were performed to assess the effect of miR-17-5p and miR-20a-5p over expression on viability, invasion and migration. In multivariate analyses, high miR-17-5p expression in tumor (HR = 0.43, CI 0.26–0.71, p < 0.001) and high expression of miR-20a-5p in tumor (HR = 0.60, CI 0.37–0.97, p = 0.037) and stroma (HR = 0.63, CI 0.42–0.95, p = 0.027) remained independent predictors of improved disease-specific survival. In cell lines, over expression of both miRs resulted in mitigated migration without any significant effect on viability or invasion. In conclusion, in stage I-III colon cancer, high expression of both miR-17-5p and miR-20a-5p are independent predictors of favorable prognosis.
Collapse
Affiliation(s)
- Hallgeir Selven
- Department of Oncology, University Hospital of North Norway, 9038, Tromso, Norway. .,Department of Clinical Medicine, UiT The Arctic University of Norway, Tromso, Norway.
| | - Sigve Andersen
- Department of Oncology, University Hospital of North Norway, 9038, Tromso, Norway.,Department of Clinical Medicine, UiT The Arctic University of Norway, Tromso, Norway
| | - Mona I Pedersen
- Department of Clinical Medicine, UiT The Arctic University of Norway, Tromso, Norway
| | | | - Lill-Tove Rasmussen Busund
- Department of Medical Biology, UiT The Arctic University of Norway, Tromso, Norway.,Department of Clinical Pathology, University Hospital of North Norway, Tromso, Norway
| | - Thomas Karsten Kilvær
- Department of Oncology, University Hospital of North Norway, 9038, Tromso, Norway.,Department of Clinical Medicine, UiT The Arctic University of Norway, Tromso, Norway
| |
Collapse
|
70
|
Singh A, Jain D, Pandey J, Yadav M, Bansal KC, Singh IK. Deciphering the role of miRNA in reprogramming plant responses to drought stress. Crit Rev Biotechnol 2022; 43:613-627. [PMID: 35469523 DOI: 10.1080/07388551.2022.2047880] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Drought is the most prevalent environmental stress that affects plants' growth, development, and crop productivity. However, plants have evolved adaptive mechanisms to respond to the harmful effects of drought. They reprogram their: transcriptome, proteome, and metabolome that alter their cellular and physiological processes and establish cellular homeostasis. One of the crucial regulatory processes that govern this reprogramming is post-transcriptional regulation by microRNAs (miRNAs). miRNAs are small non-coding RNAs, involved in the downregulation of the target mRNA via translation inhibition/mRNA degradation/miRNA-mediated mRNA decay/ribosome drop off/DNA methylation. Many drought-inducible miRNAs have been identified and characterized in plants. Their main targets are regulatory genes that influence growth, development, osmotic stress tolerance, antioxidant defense, phytohormone-mediated signaling, and delayed senescence during drought stress. Overexpression of drought-responsive miRNAs (Osa-miR535, miR160, miR408, Osa-miR393, Osa-miR319, and Gma-miR394) in certain plants has led to tolerance against drought stress indicating their vital role in stress mitigation. Similarly, knock down (miR166/miR398c) or deletion (miR169 and miR827) of miRNAs has also resulted in tolerance to drought stress. Likewise, engineered Arabidopsis plants with miR165, miR166 using short tandem target mimic strategy, exhibited drought tolerance. Since miRNAs regulate the expression of an array of drought-responsive genes, they can act as prospective targets for genetic manipulations to enhance drought tolerance in crops and achieve sustainable agriculture. Further investigations toward functional characterization of diverse miRNAs, and understanding stress-responses regulated by these miRNAs and their utilization in biotechnological applications is highly recommended.
Collapse
Affiliation(s)
- Archana Singh
- Department of Botany, Hansraj College, University of Delhi, New Delhi, India
| | - Deepti Jain
- Department of Plant Molecular Biology, Interdisciplinary Centre for Plant Genomics, Delhi University South Campus, New Delhi, India
| | - Jyotsna Pandey
- Department of Botany, Hansraj College, University of Delhi, New Delhi, India
| | - Manisha Yadav
- Department of Botany, Hansraj College, University of Delhi, New Delhi, India
| | - Kailash C Bansal
- The Alliance of Bioversity International and CIAT (CGIAR), New Delhi, India
| | - Indrakant K Singh
- Department of Zoology, Molecular Biology Research Lab, Deshbandhu College, University of Delhi, New Delhi, India.,DBC i4 Center, Deshbandhu College, University of Delhi, New Delhi, India
| |
Collapse
|
71
|
Yang F, Xuan G, Chen Y, Cao L, Zhao M, Wang C, Chen E. MicroRNAs Are Key Molecules Involved in the Gene Regulation Network of Colorectal Cancer. Front Cell Dev Biol 2022; 10:828128. [PMID: 35465317 PMCID: PMC9023807 DOI: 10.3389/fcell.2022.828128] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2021] [Accepted: 03/07/2022] [Indexed: 12/12/2022] Open
Abstract
Colorectal cancer (CRC) is one of the most common types of cancer and one of the leading causes of mortality worldwide. MicroRNAs (miRNAs) play central roles in normal cell maintenance, development, and other physiological processes. Growing evidence has illustrated that dysregulated miRNAs can participate in the initiation, progression, metastasis, and therapeutic resistance that confer miRNAs to serve as clinical biomarkers and therapeutic targets for CRC. Through binding to the 3′-untranslated region (3′-UTR) of target genes, miRNAs can lead to target mRNA degradation or inhibition at a post-transcriptional level. During the last decade, studies have found numerous miRNAs and their potential targets, but the complex network of miRNA/Targets in CRC remains unclear. In this review, we sought to summarize the complicated roles of the miRNA-target regulation network (Wnt, TGF-β, PI3K-AKT, MAPK, and EMT related pathways) in CRC with up-to-date, high-quality published data. In particular, we aimed to discuss the downstream miRNAs of specific pathways. We hope these data can be a potent supplement for the canonical miRNA-target regulation network.
Collapse
Affiliation(s)
- Fangfang Yang
- Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, Northwest University, Xi’an, China
- Provincial Key Laboratory of Biotechnology of Shaanxi Province, Northwest University, Xi’an, China
| | - Guoyun Xuan
- State Key Laboratory of Cancer Biology and National Clinical Research Center for Digestive Diseases, Xijing Hospital of Digestive Diseases, The Fourth Military Medical University, Xi’an, China
| | - Yixin Chen
- Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, Northwest University, Xi’an, China
- Provincial Key Laboratory of Biotechnology of Shaanxi Province, Northwest University, Xi’an, China
| | - Lichao Cao
- Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, Northwest University, Xi’an, China
- Provincial Key Laboratory of Biotechnology of Shaanxi Province, Northwest University, Xi’an, China
| | - Min Zhao
- Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, Northwest University, Xi’an, China
- Provincial Key Laboratory of Biotechnology of Shaanxi Province, Northwest University, Xi’an, China
| | - Chen Wang
- Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, Northwest University, Xi’an, China
- Provincial Key Laboratory of Biotechnology of Shaanxi Province, Northwest University, Xi’an, China
| | - Erfei Chen
- Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, Northwest University, Xi’an, China
- Provincial Key Laboratory of Biotechnology of Shaanxi Province, Northwest University, Xi’an, China
- *Correspondence: Erfei Chen,
| |
Collapse
|
72
|
miR-1266-3p Suppresses Epithelial-Mesenchymal Transition in Colon Cancer by Targeting P4HA3. Anal Cell Pathol (Amst) 2022; 2022:1542117. [PMID: 35433237 PMCID: PMC9010195 DOI: 10.1155/2022/1542117] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2021] [Accepted: 03/19/2022] [Indexed: 12/13/2022] Open
Abstract
Numerous studies have been conducted to demonstrate that miRNA is strongly related to colon cancer progression. Nevertheless, there are few studies regarding the function for miR-1266-3p in colon cancer, and the molecular mechanism remains poorly know. Our study was designed to examine the level of miR-1266-3p expression among the colon cancer tissue and cell and to study the role and regulatory mechanism for miR-1266-3p among colon cancer's malignant biologic behavior. First, we found that miR-1266-3p expression was distinctly lower in colonic carcinoma tissues and cells than in nontumor ones, and the prognosis of low miR-1266-3p patients was distinctly worse than that of high miR-1266-3p patients. Second, we predicted that the target gene of miR-1266-3p was prolyl 4-hydroxylase subunit alpha 3 (P4HA3) through bioinformatics, and the targeting relationship between the two was verified by a dual luciferase assay report. Furthermore, miR-1266-3p inhibited the growth and metastasis of colon cancer in vitro as well as in vivo, and this effect could be alleviated by overexpressing P4HA3. Even more importantly, our study demonstrated that miR-1266-3p inhibited epithelial-mesenchymal transition (EMT) by targeting P4HA3. In conclusion, miR-1266-3p could inhibit growth, metastasis, and EMT in colon cancer by targeting P4HA3. Our discoveries might offer a novel target for colon cancer diagnosis and treatment.
Collapse
|
73
|
Ye Y, Lu W, Deng Q, Chen Y, Han S, Dai S, Chen Z, Li J, Song Y, Wang Z, Ding K. Tumor enhancement ratio on preoperative abdominal contrast-enhanced CT scan for predicting recurrence risk in stage II colon cancer. Abdom Radiol (NY) 2022; 47:1265-1275. [PMID: 35146573 DOI: 10.1007/s00261-022-03412-9] [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: 09/12/2021] [Revised: 01/05/2022] [Accepted: 01/06/2022] [Indexed: 11/01/2022]
Abstract
PURPOSE The identification of high recurrence risk stage II colon cancer patients was critical to adjuvant chemotherapy decision. However, current definition of high-risk features remains inadequate. This study aimed to construct a model for predicting recurrence risk based on tumor enhancement ratio (TER) on abdominal contrast-enhanced CT scan. METHOD 282 stage II colon cancer patients were included and randomly divided into training and validation sets in the ratio of 7:3. TER was calculated using maximum tumor attenuation value in contrast-enhanced CT scan divided by the minimum. Kaplan-Meier survival analyses were adopted to evaluate the prognostic value of variables. A model based on TER was built to predict recurrence risk through the LASSO Cox model. The recurrence risk score of patients was calculated based on this model. RESULTS The optimal cut-off value of TER was 1.83 derived from the time-dependent ROC (tdROC) curve. Patients with high-TER showed increasingly poorer disease-free survival (DFS) in both training (p < 0.001) and validation (p < 0.001) sets. A model was built based on TER demonstrated satisfactory performance to recurrence risk prediction (C-index: 0.784 in the training set and 0.725 in the validation set). Patients were regrouped into modified high-risk and non-high risk according to recurrence risk score (cut-off value: 1.75) and a significant DFS difference was observed (training set: p < 0.001; validation set: p < 0.001). CONCLUSION TER can serve as a high-risk feature of stage II colon cancer. And a model based on TER provided a new approach to assess recurrence risk of stage II disease.
Collapse
|
74
|
Zhou N, Ji Z, Li F, Qiao B, Lin R, Jiang W, Zhu Y, Lin Y, Zhang K, Li S, You B, Gao P, Dong R, Wang Y, Du J. Machine Learning-Based Personalized Risk Prediction Model for Mortality of Patients Undergoing Mitral Valve Surgery: The PRIME Score. Front Cardiovasc Med 2022; 9:866257. [PMID: 35433879 PMCID: PMC9010531 DOI: 10.3389/fcvm.2022.866257] [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: 01/31/2022] [Accepted: 03/01/2022] [Indexed: 11/24/2022] Open
Abstract
Background Mitral valve surgery (MVS) is an effective treatment for mitral valve diseases. There is a lack of reliable personalized risk prediction models for mortality in patients undergoing mitral valve surgery. Our aim was to develop a risk stratification system to predict all-cause mortality in patients after mitral valve surgery. Methods Different machine learning models for the prediction of all-cause mortality were trained on a derivation cohort of 1,883 patients undergoing mitral valve surgery [split into a training cohort (70%) and internal validation cohort (30%)] to predict all-cause mortality. Forty-five clinical variables routinely evaluated at discharge were used to train the models. The best performance model (PRIME score) was tested in an externally validated cohort of 220 patients undergoing mitral valve surgery. The model performance was evaluated according to the area under the curve (AUC). Net reclassification improvement (NRI) and integrated discrimination improvement (IDI) were compared with existing risk strategies. Results After a median follow-up of 2 years, there were 133 (7.063%) deaths in the derivation cohort and 17 (7.727%) deaths in the validation cohort. The PRIME score showed an AUC of 0.902 (95% confidence interval [CI], 0.849–0.956) in the internal validation cohort and 0.873 (95% CI: 0.769–0.977) in the external validation cohort. In the external validation cohort, the performance of the PRIME score was significantly improved compared with that of the existing EuroSCORE II (NRI = 0.550, [95% CI 0.001–1.099], P = 0.049, IDI = 0.485, [95% CI 0.230–0.741], P < 0.001). Conclusion Machine learning-based model (the PRIME score) that integrate clinical, demographic, imaging, and laboratory features demonstrated superior performance for the prediction of mortality patients after mitral valve surgery compared with the traditional risk model EuroSCORE II. Clinical Trial Registration [http://www.clinicaltrials.gov], identifier [NCT05141292].
Collapse
Affiliation(s)
- Ning Zhou
- Beijing Anzhen Hospital, Capital Medical University, Beijing, China
- Beijing Institute of Heart, Lung and Blood Vessel Diseases, Beijing Anzhen Hospital, Capital Medical University, Beijing, China
- Department of Cardiac Surgery, Beijing Anzhen Hospital, Capital Medical University, Beijing, China
| | - Zhili Ji
- Beijing Anzhen Hospital, Capital Medical University, Beijing, China
| | - Fengjuan Li
- Beijing Anzhen Hospital, Capital Medical University, Beijing, China
- Beijing Institute of Heart, Lung and Blood Vessel Diseases, Beijing Anzhen Hospital, Capital Medical University, Beijing, China
| | - Bokang Qiao
- Beijing Anzhen Hospital, Capital Medical University, Beijing, China
- Beijing Institute of Heart, Lung and Blood Vessel Diseases, Beijing Anzhen Hospital, Capital Medical University, Beijing, China
| | - Rui Lin
- Beijing Anzhen Hospital, Capital Medical University, Beijing, China
- Beijing Institute of Heart, Lung and Blood Vessel Diseases, Beijing Anzhen Hospital, Capital Medical University, Beijing, China
| | - Wenxi Jiang
- Beijing Anzhen Hospital, Capital Medical University, Beijing, China
- Beijing Institute of Heart, Lung and Blood Vessel Diseases, Beijing Anzhen Hospital, Capital Medical University, Beijing, China
| | - Yuexin Zhu
- Beijing Anzhen Hospital, Capital Medical University, Beijing, China
- Beijing Institute of Heart, Lung and Blood Vessel Diseases, Beijing Anzhen Hospital, Capital Medical University, Beijing, China
| | - Yuwei Lin
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Kui Zhang
- Beijing Anzhen Hospital, Capital Medical University, Beijing, China
- Department of Cardiac Surgery, Beijing Anzhen Hospital, Capital Medical University, Beijing, China
| | - Shuanglei Li
- Department of Cardiac Surgery, Chinese People’s Liberation Army General Hospital, Beijing, China
| | - Bin You
- Beijing Anzhen Hospital, Capital Medical University, Beijing, China
- Department of Cardiac Surgery, Beijing Anzhen Hospital, Capital Medical University, Beijing, China
| | - Pei Gao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Peking University Health Science Center, Peking University, Beijing, China
- Key Laboratory of Molecular Cardiovascular Sciences, Ministry of Education, Peking University, Beijing, China
| | - Ran Dong
- Beijing Anzhen Hospital, Capital Medical University, Beijing, China
- Department of Cardiac Surgery, Beijing Anzhen Hospital, Capital Medical University, Beijing, China
- *Correspondence: Ran Dong,
| | - Yuan Wang
- Beijing Anzhen Hospital, Capital Medical University, Beijing, China
- Beijing Institute of Heart, Lung and Blood Vessel Diseases, Beijing Anzhen Hospital, Capital Medical University, Beijing, China
- Yuan Wang,
| | - Jie Du
- Beijing Anzhen Hospital, Capital Medical University, Beijing, China
- Beijing Institute of Heart, Lung and Blood Vessel Diseases, Beijing Anzhen Hospital, Capital Medical University, Beijing, China
- Jie Du,
| |
Collapse
|
75
|
Zhang L, Chen Y, Liu J, Yu Y, Cui H, Chen Q, Chen K, Yang C, Yang Y. Novel physical performance-based models for activities of daily living disability prediction among Chinese older community population: a nationally representative survey in China. BMC Geriatr 2022; 22:267. [PMID: 35361135 PMCID: PMC8974010 DOI: 10.1186/s12877-022-02905-y] [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: 09/30/2021] [Accepted: 03/07/2022] [Indexed: 11/29/2022] Open
Abstract
Background Physical performances including upper and lower limb functions have predictive roles in activities of daily living (ADL) disability, but they have rarely been incorporated into prediction models. This study primarily aimed to develop and validate novel physical performance-based models for ADL disability among Chinese older adults. Comparisons of predictive performance across multiple models were performed, and model simplification was further explored. Methods Data were obtained from the China Health and Retirement Longitudinal Study in the 2011 and 2015 waves, containing 2192 older adults over 60 years old. Our models were constructed by logistic regression analysis, using a backward stepwise selection. Model performance was internally validated by discrimination, calibration, and clinical utility. Integrated Discrimination Improvement (IDI) and Net Reclassification Improvement (NRI) were used to assess the incremental benefit of the extended models. Moreover, nomograms were built for visualization. Results We selected gender, age, smoking, self-report health condition, BMI, depressive symptoms, and cognitive function into the fundamental model (Model 1). Based on Model 1, five novel prediction models were constructed by adding handgrip strength (Model 2), Short Physical Performance Battery (SPPB) (Model 3), gait speed (Model 4), handgrip strength plus SPPB (Model 5), and handgrip strength plus gait speed (Model 6), respectively. Significant improvement in predictive values were observed for all five novel models compared with Model 1 (C-index = 0.693). The lower limb model (Model 3 SPPB model: C-index = 0.731) may play a key role in the prediction of ADL disability, reflecting a comparable predictive value to the comprehensive models combining both upper and lower limbs (Model 5 handgrip strength + SPPB model: C-index = 0.732). When we simplified the lower limb models by replacing SPPB with gait speed, the predictive values attenuated slightly (C-index: Model 3 vs Model 4: 0.731 vs 0.714; Model 5 vs Model 6: 0.732 vs 0.718), but still better than the upper limb model (Model 2 handgrip strength model: C-index = 0.701). Conclusions Physical performance-based models, especially lower limb model, provided improved prediction for ADL disability among Chinese older adults, which may help guide the targeted intervention. Supplementary Information The online version contains supplementary material available at 10.1186/s12877-022-02905-y.
Collapse
Affiliation(s)
- Li Zhang
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, No.17 Section 3, Renmin South Road, Chengdu, 610041, Sichuan, China
| | - Yueqiao Chen
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, No.17 Section 3, Renmin South Road, Chengdu, 610041, Sichuan, China
| | - Jing Liu
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, No.17 Section 3, Renmin South Road, Chengdu, 610041, Sichuan, China
| | - Yifan Yu
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, No.17 Section 3, Renmin South Road, Chengdu, 610041, Sichuan, China
| | - Huijie Cui
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, No.17 Section 3, Renmin South Road, Chengdu, 610041, Sichuan, China
| | - Qiuzhi Chen
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, No.17 Section 3, Renmin South Road, Chengdu, 610041, Sichuan, China
| | - Kejin Chen
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, No.17 Section 3, Renmin South Road, Chengdu, 610041, Sichuan, China
| | - Chunxia Yang
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, No.17 Section 3, Renmin South Road, Chengdu, 610041, Sichuan, China
| | - Yanfang Yang
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, No.17 Section 3, Renmin South Road, Chengdu, 610041, Sichuan, China.
| |
Collapse
|
76
|
Ma L, Gong J, Zhao M, Kong X, Gao P, Jiang Y, Liu Y, Feng X, Si S, Cao Y. A Novel Stool Methylation Test for the Non-Invasive Screening of Gastric and Colorectal Cancer. Front Oncol 2022; 12:860701. [PMID: 35419280 PMCID: PMC8995552 DOI: 10.3389/fonc.2022.860701] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2022] [Accepted: 03/02/2022] [Indexed: 11/13/2022] Open
Abstract
Background Because of poor compliance or low sensitivity, existing diagnostic approaches are unable to provide an efficient diagnosis of patients with gastric and colorectal cancer. Here, we developed the ColoCaller test, which simultaneously detects the methylation status of the SDC2, TFPI2, WIF1, and NDRG4 genes in stool DNA, to optimize the screening of gastric and colorectal cancer in high-risk populations. Methods A total of 217 stool samples from patients with gastrointestinal cancer and from patients with negative endoscopy were prospectively collected, complete with preoperative and postoperative clinical data from patients. The methylation of these samples was detected using ColoCaller, which was designed by selecting CpGs with a two-step screening strategy, and was interpreted using a prediction model built using libSVM to evaluate its clinical value for gastric and colorectal cancer screening. Results Compared to pathological diagnosis, the sensitivity and specificity of the ColoCaller test in 217 stool DNA samples were 95.56% and 91.86%, respectively, for colorectal cancer, and 67.5% and 97.81%, respectively, for gastric cancer. The detection limit was as low as 1% in 8 ng of DNA. Conclusion In this study, we developed and established a new test, ColoCaller, which can be used as a screening tool or as an auxiliary diagnostic approach in high-risk populations with gastric and colorectal cancer to promote timely diagnosis and treatment.
Collapse
Affiliation(s)
- Liang Ma
- Department of Clinical Laboratory, China-Japan Friendship Hospital, Beijing, China
| | - Jian Gong
- Department of Research and Development, Apexbio Biotechnology (Suzhou) Co., Ltd., Suzhou, China
| | - Meimei Zhao
- Department of Clinical Laboratory, China-Japan Friendship Hospital, Beijing, China
| | - Xiaomu Kong
- Department of Clinical Laboratory, China-Japan Friendship Hospital, Beijing, China
| | - Peng Gao
- Department of Clinical Laboratory, China-Japan Friendship Hospital, Beijing, China
| | - Yongwei Jiang
- Department of Clinical Laboratory, China-Japan Friendship Hospital, Beijing, China
| | - Yi Liu
- Department of Clinical Laboratory, China-Japan Friendship Hospital, Beijing, China
| | - Xiaoyan Feng
- Department of Research and Development, Apexbio Biotechnology (Suzhou) Co., Ltd., Suzhou, China
| | - Shuang Si
- Department of General Surgery, China-Japan Friendship Hospital, Beijing, China
| | - Yongtong Cao
- Department of Clinical Laboratory, China-Japan Friendship Hospital, Beijing, China
| |
Collapse
|
77
|
Ma L, Li W, Liu N, Ding Z, Cai J, Zhang Y. Prothrombin time (PT) and CEA as prognostic predictive biomarkers for postoperative recurrence after curative resection in patients with stage I-III colorectal cancer: a retrospective cohort study. Updates Surg 2022; 74:999-1009. [PMID: 35322387 DOI: 10.1007/s13304-022-01268-8] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2021] [Accepted: 03/04/2022] [Indexed: 11/29/2022]
Abstract
There are no ideal biomarkers including the TNM stage that can accurately predict the recurrence of colorectal cancer (CRC) and the benefit of chemotherapy for stage II patients. Here, 451 CRC patients were divided into three groups according to preoperative levels of prothrombin time (PT) and CEA to analyze the value of these indexes in predicting postoperative recurrence in different TNM stages. Preoperatively elevated levels of PT and CEA were significantly associated with a high 5-year cumulative recurrence rate (CRR) and short recurrence-free survival (RFS). According to PT and CEA levels, the 5-year CRR and RFS differed significantly among the High-risk (PT ≥ 12.65 s and CEA ≥ 10.175 ng/ml), Middle-risk (PT ≥ 12.65 s or CEA ≥ 10.175 ng/ml), and Low-risk (PT < 12.65 s and CEA < 10.175 ng/ml) groups (p < 0.001). In the same TNM stage, the 5-year CRR of the High-risk group was significantly higher and the RFS was markedly shorter than those in the Low-risk and even those in stage III (p < 0.001). In the subgroup of early stage (stage I and II), the 5-year CRR of the High-risk group was significantly higher and the RFS was significantly shorter than those in stage IIIA and IIIB (p < 0.001), which is similar to IIIC. In conclusion, preoperatively elevated levels of serum PT and CEA were reliable predictors of postoperative high-risk recurrence in CRC and combined with TNM stage precisely identify postoperative recurrence CRC patients in stage I-III and the benefit of adjuvant chemotherapy for patients with stage II CRC.
Collapse
Affiliation(s)
- Lulu Ma
- Department of Gastrointestinal Surgery, Zhongshan Hospital of Xiamen University, Xiamen, 361000, China.,Gastrointestinal Oncology Center of Xiamen University, Xiamen, 361000, China.,Medical College of Xiamen University, Xiamen, 361000, China
| | - Wenya Li
- Department of Gastrointestinal Surgery, Zhongshan Hospital of Xiamen University, Xiamen, 361000, China.,Gastrointestinal Oncology Center of Xiamen University, Xiamen, 361000, China.,Medical College of Xiamen University, Xiamen, 361000, China
| | - Ningquan Liu
- Department of Gastrointestinal Surgery, Zhongshan Hospital of Xiamen University, Xiamen, 361000, China.,Gastrointestinal Oncology Center of Xiamen University, Xiamen, 361000, China.,Medical College of Xiamen University, Xiamen, 361000, China
| | - Zhijie Ding
- Department of Gastrointestinal Surgery, Zhongshan Hospital of Xiamen University, Xiamen, 361000, China.,Gastrointestinal Oncology Center of Xiamen University, Xiamen, 361000, China.,Medical College of Xiamen University, Xiamen, 361000, China
| | - Jianchun Cai
- Department of Gastrointestinal Surgery, Zhongshan Hospital of Xiamen University, Xiamen, 361000, China.,Gastrointestinal Oncology Center of Xiamen University, Xiamen, 361000, China.,Medical College of Xiamen University, Xiamen, 361000, China
| | - Yiyao Zhang
- Department of Gastrointestinal Surgery, Zhongshan Hospital of Xiamen University, Xiamen, 361000, China. .,Gastrointestinal Oncology Center of Xiamen University, Xiamen, 361000, China. .,Medical College of Xiamen University, Xiamen, 361000, China.
| |
Collapse
|
78
|
Cinque A, Capasso A, Vago R, Floris M, Lee MW, Minnei R, Trevisani F. MicroRNA Signatures in the Upper Urinary Tract Urothelial Carcinoma Scenario: Ready for the Game Changer? Int J Mol Sci 2022; 23:2602. [PMID: 35269744 PMCID: PMC8910117 DOI: 10.3390/ijms23052602] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Revised: 02/20/2022] [Accepted: 02/24/2022] [Indexed: 12/18/2022] Open
Abstract
Upper urinary tract urothelial carcinoma (UTUC) represents a minor subgroup of malignancies arising in the urothelium of the renal pelvis or ureter. The estimated annual incidence is around 2 cases per 100,000 people, with a mean age at diagnosis of 73 years. UTUC is more frequently diagnosed in an invasive or metastatic stage. However, even though the incidence of UTUC is not high, UTUC tends to be aggressive and rapidly progressing with a poor prognosis in some patients. A significant challenge in UTUC is ensuring accurate and timely diagnosis, which is complicated by the non-specific nature of symptoms seen at the onset of disease. Moreover, there is a lack of biomarkers capable of identifying the early presence of the malignancy and guide-tailored medical treatment. However, the growing understanding of the molecular biology underlying UTUC has led to the discovery of promising new biomarkers. Among these biomarkers, there is a class of small non-coding RNA biomarkers known as microRNAs (miRNAs) that are particularly promising. In this review, we will analyze the main characteristics of UTUC and focus on microRNAs as possible novel tools that could enter clinical practice in order to optimize the current diagnostic and prognostic algorithm.
Collapse
Affiliation(s)
- Alessandra Cinque
- Biorek S.r.l., San Raffaele Scientific Institute, 20132 Milan, Italy;
| | - Anna Capasso
- Department of Medical Oncology Livestrong Cancer Institutes, Dell Medical School, University of Texas at Austin, Austin, TX 78723, USA;
| | - Riccardo Vago
- Urological Research Institute, Division of Experimental Oncology, IRCCS San Raffaele Scientific Institute, 20132 Milan, Italy;
- Faculty of Medicine and Surgery,, Università Vita-Salute San Raffaele, 20132 Milan, Italy
| | - Matteo Floris
- Nephrology, Dialysis, and Transplantation, Università degli Studi di Cagliari, G. Brotzu Hospital, 09134 Cagliari, Italy; (M.F.); (R.M.)
| | - Michael W. Lee
- Department of Medical Oncology and Medical Education, Dell Medical School, Livestrong Cancer Institutes, University of Texas at Austin, Austin, TX 78723, USA;
| | - Roberto Minnei
- Nephrology, Dialysis, and Transplantation, Università degli Studi di Cagliari, G. Brotzu Hospital, 09134 Cagliari, Italy; (M.F.); (R.M.)
| | - Francesco Trevisani
- Biorek S.r.l., San Raffaele Scientific Institute, 20132 Milan, Italy;
- Urological Research Institute, Division of Experimental Oncology, IRCCS San Raffaele Scientific Institute, 20132 Milan, Italy;
- Unit of Urology, San Raffaele Scientific Institute, 20132 Milan, Italy
| |
Collapse
|
79
|
miRNome Profiling and Functional Analysis Reveal Involvement of hsa-miR-1246 in Colon Adenoma-Carcinoma Transition by Targeting AXIN2 and CFTR. Int J Mol Sci 2022; 23:ijms23042107. [PMID: 35216222 PMCID: PMC8876010 DOI: 10.3390/ijms23042107] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2021] [Revised: 01/26/2022] [Accepted: 02/10/2022] [Indexed: 12/24/2022] Open
Abstract
Regulatory changes occurring early in colorectal cancer development remain poorly investigated. Since the majority of cases develop from polyps in the adenoma-carcinoma transition, a search of early molecular features, such as aberrations in miRNA expression occurring prior to cancer development, would enable identification of potentially causal, rather than consequential, candidates in the progression of polyp to cancer. In the current study, by employing small RNA-seq profiling of colon biopsy samples, we described differentially expressed miRNAs and their isoforms in the adenoma-carcinoma transition. Analysis of healthy-adenoma-carcinoma sequence in an independent validation group enabled us to identify early deregulated miRNAs including hsa-miR-1246 and hsa-miR-215-5p, the expressions of which are, respectively, gradually increasing and decreasing. Loss-of-function experiments revealed that inhibition of hsa-miR-1246 lead to reduced cell viability, colony formation, and migration rate, thereby indicating an oncogenic effect of this miRNA in vitro. Subsequent western blot and luciferase reporter assay provided evidence of hsa-miR-1246 being involved in the regulation of target AXIN2 and CFTR genes’ expression. To conclude, the present study revealed possible involvement of hsa-miR-1246 in early colorectal cancer development and regulation of tumor suppressors AXIN2 and CFTR.
Collapse
|
80
|
A web-based calculator for predicting the prognosis of patients with sarcoma on the basis of antioxidant gene signatures. Aging (Albany NY) 2022; 14:1407-1428. [PMID: 35143416 PMCID: PMC8876918 DOI: 10.18632/aging.203885] [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: 09/30/2021] [Accepted: 01/25/2022] [Indexed: 11/25/2022]
Abstract
Background: Oxidative stress plays a critical role in tumorigenesis, tumor development, and resistance to therapy. A systematic analysis of the interactions between antioxidant gene expression and the prognosis of patients with sarcoma is lacking but urgently needed. Methods: Gene expression and clinical data of patients with sarcoma were derived from The Cancer Genome Atlas Sarcoma (training cohort) and Gene Expression Omnibus (validation cohorts) databases. Least absolute shrinkage, selection operator regression, and Cox regression were used to develop prognostic signatures for overall survival (OS) and disease-free survival (DFS). Based on the signatures and clinical features, two nomograms for predicting 2-, 4-, and 6-year OS and DFS were established. Results: On the basis of the training cohort, we identified five-gene (CHAC2, GPX5, GSTK1, PXDN, and S100A9) and six-gene (GGTLC2, GLO1, GPX7, GSTK1, GSTM5, and IPCEF1) signatures for predicting OS and DFS, respectively, in patients with sarcoma. Kaplan–Meier survival analysis of the training and validation cohorts revealed that patients in the high-risk group had a significantly poorer prognosis than those in the low-risk group. On the basis of the signatures and other independent risk factors, we established two models for predicting OS and DFS that showed excellent calibration and discrimination. For the convenience of clinical application, we built web-based calculators (OS: https://quankun.shinyapps.io/sarcOS/; DFS: https://quankun.shinyapps.io/sarcDFS/). Conclusions: The antioxidant gene signature models established in this study can be novel prognostic predictors for sarcoma.
Collapse
|
81
|
Xiao Q, Hou R, Li H, Zhang S, Zhang F, Zhu X, Pan X. Circulating Exosomal circRNAs Contribute to Potential Diagnostic Value of Large Artery Atherosclerotic Stroke. Front Immunol 2022; 12:830018. [PMID: 35095932 PMCID: PMC8792990 DOI: 10.3389/fimmu.2021.830018] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Accepted: 12/24/2021] [Indexed: 01/08/2023] Open
Abstract
Large artery atherosclerotic (LAA) stroke is closely associated with atherosclerosis, characterized by the accumulation of immune cells. Early recognition of LAA stroke is crucial. Circulating exosomal circRNAs profiling represents a promising, noninvasive approach for the detection of LAA stroke. Exosomal circRNA sequencing was used to identify differentially expressed circRNAs between LAA stroke and normal controls. From a further validation stage, the results were validated using RT-qPCR. We then built logistic regression models of exosomal circRNAs based on a large replication stage, and receiver operating characteristic (ROC) curves were constructed to assess the diagnostic efficacy. Using exosomal circRNA sequencing, large sample validation, and diagnostic model construction revealed that exosomal circ_0043837 and circ_ 0001801were independent predictive factors for LAA stroke, and had better diagnostic efficacy than plasma circRNAs. In the atherosclerotic group (AS), we developed a nomogram for clinical use that integrated the two-circRNA-based risk factors to predict which patients might have the risk of plaque rupture. Circulating exosomal circRNAs profiling identifies novel predictive biomarkers for the LAA stroke and plaque rupture, with superior diagnostic value than plasma circRNAs. It might facilitate the prevention and better management of this disease.
Collapse
Affiliation(s)
- Qi Xiao
- Department of Neurology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Rongyao Hou
- Department of Neurology, The Affiliated Hiser Hospital of Qingdao University, Qingdao, China
| | - Hong Li
- Department of Neurology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Shuai Zhang
- Department of Neurology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Fuzhi Zhang
- Department of Neurology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Xiaoyan Zhu
- Department of Critical Care Medicine, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Xudong Pan
- Department of Neurology, The Affiliated Hospital of Qingdao University, Qingdao, China
| |
Collapse
|
82
|
Cai M, Yao F, Ding J, Zheng R, Huang X, Yang Y, Lin F, Hu Z. MRI Radiomic Features: A Potential Biomarker for Progression-Free Survival Prediction of Patients With Locally Advanced Cervical Cancer Undergoing Surgery. Front Oncol 2022; 11:749114. [PMID: 34970482 PMCID: PMC8712932 DOI: 10.3389/fonc.2021.749114] [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: 07/29/2021] [Accepted: 11/19/2021] [Indexed: 11/13/2022] Open
Abstract
Objectives To investigate the prognostic role of radiomic features based on pretreatment MRI in predicting progression-free survival (PFS) of locally advanced cervical cancer (LACC). Methods All 181 women with histologically confirmed LACC were randomly divided into the training cohort (n = 126) and the validation cohort (n = 55). For each patient, we extracted radiomic features from whole tumors on sagittal T2WI and axial DWI. The least absolute shrinkage and selection operator (LASSO) algorithm combined with the Cox survival analysis was applied to select features and construct a radiomic score (Rad-score) model. The cutoff value of the Rad-score was used to divide the patients into high- and low-risk groups by the X-tile. Kaplan–Meier analysis and log-rank test were used to assess the prognostic value of the Rad-score. In addition, we totally developed three models, the clinical model, the Rad-score, and the combined nomogram. Results The Rad-score demonstrated good performance in stratifying patients into high- and low-risk groups of progression in the training (HR = 3.279, 95% CI: 2.865–3.693, p < 0.0001) and validation cohorts (HR = 2.247, 95% CI: 1.735–2.759, p < 0.0001). Otherwise, the combined nomogram, integrating the Rad-score and patient’s age, hemoglobin, white blood cell, and lymph vascular space invasion, demonstrated prominent discrimination, yielding an AUC of 0.879 (95% CI, 0.811–0.947) in the training cohort and 0.820 (95% CI, 0.668–0.971) in the validation cohort. The Delong test verified that the combined nomogram showed better performance in estimating PFS than the clinical model and Rad-score in the training cohort (p = 0.038, p = 0.043). Conclusion The radiomics nomogram performed well in individualized PFS estimation for the patients with LACC, which might guide individual treatment decisions.
Collapse
Affiliation(s)
- Mengting Cai
- Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Fei Yao
- Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Jie Ding
- Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Ruru Zheng
- Department of Gynecology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Xiaowan Huang
- Department of Gynecology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Yunjun Yang
- Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Feng Lin
- Department of Gynecology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Zhangyong Hu
- Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| |
Collapse
|
83
|
Lin YW, Kang WP, Huang BL, Qiu ZH, Wei LF, Zhang B, Ding TY, Luo Y, Liu CT, Chu LY, Guo HP, Xu YW, Peng YH. Nomogram based on clinical characteristics and serological inflammation markers to predict overall survival of oral tongue squamous cell carcinoma patient after surgery. BMC Oral Health 2021; 21:667. [PMID: 34961504 PMCID: PMC8711158 DOI: 10.1186/s12903-021-02028-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2021] [Accepted: 12/14/2021] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND Oral tongue squamous cell carcinoma (OTSCC) is a prevalent malignant disease that is characterized by high rates of metastasis and postoperative recurrence. The aim of this study was to establish a nomogram to predict the outcome of OTSCC patients after surgery. METHODS We retrospectively analyzed 169 OTSCC patients who underwent treatments in the Cancer Hospital of Shantou University Medical College from 2008 to 2019. The Cox regression analysis was performed to determine the independent prognostic factors associated with patient's overall survival (OS). A nomogram based on these prognostic factors was established and internally validated using a bootstrap resampling method. RESULTS Multivariate Cox regression analysis revealed the independent prognostic factors for OS were TNM stage, age, lymphocyte-to-monocyte ratio and immunoglobulin G, all of which were identified to create the nomogram. The Akaike Information Criterion and Bayesian Information Criterion of the nomogram were lower than those of TNM stage (292.222 vs. 305.480; 298.444 vs. 307.036, respectively), indicating a better goodness-of-fit of the nomogram for predicting OS. The bootstrap-corrected of concordance index (C-index) of nomogram was 0.784 (95% CI 0.708-0.860), which was higher than that of TNM stage (0.685, 95% CI 0.603-0.767, P = 0.017). The results of time-dependent C-index for OS also showed that the nomogram had a better discriminative ability than that of TNM stage. The calibration curves of the nomogram showed good consistency between the probabilities and observed values. The decision curve analysis also revealed the potential clinical usefulness of the nomogram. Based on the cutoff value obtained from the nomogram, the proposed high-risk group had poorer OS than low-risk group (P < 0.0001). CONCLUSIONS The nomogram based on clinical characteristics and serological inflammation markers might be useful for outcome prediction of OTSCC patient.
Collapse
Affiliation(s)
- Yi-Wei Lin
- Department of Clinical Laboratory Medicine, The Cancer Hospital of Shantou University Medical College, Shantou, 515041, Guangdong, People's Republic of China
- Precision Medicine Research Center, Shantou University Medical College, Shantou, 515041, Guangdong, People's Republic of China
| | - Wei-Piao Kang
- Department of Otolaryngology, The Second Affiliated Hospital of Shantou University Medical College, Shantou, 515041, Guangdong, People's Republic of China
| | - Bin-Liang Huang
- Department of Clinical Laboratory Medicine, The Cancer Hospital of Shantou University Medical College, Shantou, 515041, Guangdong, People's Republic of China
- Precision Medicine Research Center, Shantou University Medical College, Shantou, 515041, Guangdong, People's Republic of China
| | - Zi-Han Qiu
- Department of Otolaryngology-Head and Neck Surgery, The First Affiliated Hospital of Shantou University Medical College, Shantou, 515041, Guangdong, People's Republic of China
| | - Lai-Feng Wei
- Department of Clinical Laboratory Medicine, The Cancer Hospital of Shantou University Medical College, Shantou, 515041, Guangdong, People's Republic of China
- Precision Medicine Research Center, Shantou University Medical College, Shantou, 515041, Guangdong, People's Republic of China
| | - Biao Zhang
- Department of Clinical Laboratory Medicine, The Cancer Hospital of Shantou University Medical College, Shantou, 515041, Guangdong, People's Republic of China
- Precision Medicine Research Center, Shantou University Medical College, Shantou, 515041, Guangdong, People's Republic of China
| | - Tian-Yan Ding
- Department of Clinical Laboratory Medicine, The Cancer Hospital of Shantou University Medical College, Shantou, 515041, Guangdong, People's Republic of China
- Precision Medicine Research Center, Shantou University Medical College, Shantou, 515041, Guangdong, People's Republic of China
| | - Yun Luo
- Department of Clinical Laboratory Medicine, The Cancer Hospital of Shantou University Medical College, Shantou, 515041, Guangdong, People's Republic of China
- Precision Medicine Research Center, Shantou University Medical College, Shantou, 515041, Guangdong, People's Republic of China
| | - Can-Tong Liu
- Department of Clinical Laboratory Medicine, The Cancer Hospital of Shantou University Medical College, Shantou, 515041, Guangdong, People's Republic of China
- Precision Medicine Research Center, Shantou University Medical College, Shantou, 515041, Guangdong, People's Republic of China
| | - Ling-Yu Chu
- Department of Clinical Laboratory Medicine, The Cancer Hospital of Shantou University Medical College, Shantou, 515041, Guangdong, People's Republic of China
- Precision Medicine Research Center, Shantou University Medical College, Shantou, 515041, Guangdong, People's Republic of China
| | - Hai-Peng Guo
- Department of Head and Neck Surgery, The Cancer Hospital of Shantou University Medical College, Shantou, 515041, Guangdong, People's Republic of China.
| | - Yi-Wei Xu
- Department of Clinical Laboratory Medicine, The Cancer Hospital of Shantou University Medical College, Shantou, 515041, Guangdong, People's Republic of China.
- Precision Medicine Research Center, Shantou University Medical College, Shantou, 515041, Guangdong, People's Republic of China.
- Guangdong Esophageal Cancer Institute, The Cancer Hospital of Shantou University Medical College, Shantou, 515041, Guangdong, People's Republic of China.
| | - Yu-Hui Peng
- Department of Clinical Laboratory Medicine, The Cancer Hospital of Shantou University Medical College, Shantou, 515041, Guangdong, People's Republic of China.
- Precision Medicine Research Center, Shantou University Medical College, Shantou, 515041, Guangdong, People's Republic of China.
- Guangdong Esophageal Cancer Institute, The Cancer Hospital of Shantou University Medical College, Shantou, 515041, Guangdong, People's Republic of China.
| |
Collapse
|
84
|
Ren J, Xu L, Zhou S, Ouyang J, You W, Sheng N, Yan L, Peng D, Xie L, Wang Z. Clinicopathological Features Combined With Immune Infiltration Could Well Distinguish Outcomes in Stage II and Stage III Colorectal Cancer: A Retrospective Study. Front Oncol 2021; 11:776997. [PMID: 34926285 PMCID: PMC8678133 DOI: 10.3389/fonc.2021.776997] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Accepted: 11/15/2021] [Indexed: 01/01/2023] Open
Abstract
Background The Immunoscore predicts prognosis in patients with colorectal cancer (CRC). However, a few studies have incorporated the Immunoscore into the construction of comprehensive prognostic models in CRC, especially stage II CRC. We aimed to construct and validate multidimensional models integrating clinicopathological characteristics and the Immunoscore to predict the prognosis of patients with stage II–III CRC. Methods Patients (n = 254) diagnosed with stage II–III CRC from 2009 to 2016 were used to generate Cox models for predicting disease-free survival (DFS) and overall survival (OS). The variables included basic clinical indicators, blood inflammatory markers, preoperative tumor biomarkers, mismatch repair status, and the Immunoscore (CD3+ and CD8+ T-cell densities). Univariate and multivariate Cox proportional regressions were used to construct the prognostic models for DFS and OS. We validated the predictive accuracy and ability of the prognostic models in our cohort of 254 patients. Results We constructed two predictive prognostic models with C-index values of 0.6941 for DFS and 0.7138 for OS in patients with stage II–III CRC. The Immunoscore was the most informative predictor of DFS (11.92%), followed by pN stage, carcinoembryonic antigen (CEA), and vascular infiltration. For OS, the Immunoscore was the most informative predictor (8.59%), followed by pN stage, age, CA125, and CEA. Based on the prognostic models, nomograms were developed to predict the 3- and 5-year DFS and OS rates. Patients were divided into three risk groups (low, intermediate, and high) according to the risk scores obtained from the nomogram, and significant differences were observed in the recurrence and survival of the different risk groups (p < 0.0001). Calibration curve and time-dependent receiver operating characteristic (ROC) analysis showed good accuracy of our models. Furthermore, the decision curve analysis indicated that our nomograms had better net benefit than pathological TNM (pTNM) stage within a wide threshold probability. Especially, we developed a website based on our prognostic models to predict the risks of recurrence and death of patients with stage II–III CRC. Conclusions Multidimensional models including the clinicopathological characteristics and the Immunoscore were constructed and validated, with good accuracy and convenience, to evaluate the risks of recurrence and death of stage II–III CRC patients.
Collapse
Affiliation(s)
- Jiazi Ren
- Department of General Surgery, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Linfeng Xu
- Shanghai Center for Bioinformation Technology, Shanghai Institute for Biomedical and Pharmaceutical Technologies, Shanghai, China.,School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, China
| | - Siyu Zhou
- Department of General Surgery, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Jian Ouyang
- Shanghai Center for Bioinformation Technology, Shanghai Institute for Biomedical and Pharmaceutical Technologies, Shanghai, China
| | - Weiqiang You
- Department of General Surgery, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Nengquan Sheng
- Department of General Surgery, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Li Yan
- Department of General Surgery, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Du Peng
- Department of Colorectal Surgery, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Lu Xie
- Shanghai Center for Bioinformation Technology, Shanghai Institute for Biomedical and Pharmaceutical Technologies, Shanghai, China
| | - Zhigang Wang
- Department of General Surgery, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| |
Collapse
|
85
|
MiR-1246 regulates the PI3K/AKT signaling pathway by targeting PIK3AP1 and inhibits thyroid cancer cell proliferation and tumor growth. Mol Cell Biochem 2021; 477:649-661. [PMID: 34870753 PMCID: PMC8857084 DOI: 10.1007/s11010-021-04290-3] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2021] [Accepted: 11/04/2021] [Indexed: 02/07/2023]
Abstract
One of the most prevalent forms of endocrine malignancies is thyroid cancer. Herein, we explored the mechanisms whereby miR-1246 is involved in thyroid cancer. Phosphoinositide 3-kinase adapter protein 1 (PIK3AP1) was identified as a potential miR-1246 target, with the online Gene Expression Omnibus (GEO) database. The binding between miR-1246 and PIK3AP1 and the dynamic role of these two molecules in downstream PI3K/AKT signaling were evaluated. Analysis of GEO data demonstrated significant miR-1246 downregulation in thyroid cancer, and we confirmed that overexpression of miR-1246 can inhibit migratory, invasive, and proliferative activity in vitro and tumor growth in vivo. Subsequent studies indicated that miR-1246 overexpression decreased the protein level of PIK3AP1 and the phosphorylation of PI3K and AKT, which were reversed by PIK3AP1 overexpression. At the same time, overexpression of PIK3AP1 also reversed the miR-1246 mimics-induced inhibition proliferative, migratory, and invasive activity, while promoting increases in apoptotic death, confirming that miR-1246 function was negatively correlated with that of PIK3AP1. Subsequently, we found that the miR-1246 mimics-induced inhibition of PI3K/AKT phosphorylation was reversed by the PI3K/AKT activator IGF-1. miR-1246 mimics inhibited proliferative, migratory, and invasive activity while promoting increases in apoptotic death, which were reversed by IGF-1. Furthermore, miR-1246 agomir can inhibit tumor growth in vivo. We confirmed that miR-1246 affects the signaling pathway of PI3K/AKT via targeting PIK3AP1 and inhibits the development of thyroid cancer. Thus, miR-1246 is a new therapeutic target for thyroid cancer.
Collapse
|
86
|
Wang K, Liu Y, Lu G, Xiao J, Huang J, Lei L, Peng J, Li Y, Wei S. A functional methylation signature to predict the prognosis of Chinese lung adenocarcinoma based on TCGA. Cancer Med 2021; 11:281-294. [PMID: 34854250 PMCID: PMC8704183 DOI: 10.1002/cam4.4431] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Revised: 10/08/2021] [Accepted: 10/10/2021] [Indexed: 01/16/2023] Open
Abstract
Background Lung cancer is the leading cause of cancer morbidity and mortality worldwide, however, the individualized treatment is still unsatisfactory. DNA methylation can affect gene regulation and may be one of the most valuable biomarkers in predicting the prognosis of lung adenocarcinoma. This study was aimed to identify methylation CpG sites that may be used to predict lung adenocarcinoma prognosis. Methods The Cancer Genome Atlas (TCGA) database was used to detect methylation CpG sites associated with lung adenocarcinoma prognosis and construct a methylation signature model. Then, a Chinese cohort was carried out to estimate the association between methylation and lung adenocarcinoma prognosis. Biological function studies, including demethylation treatment, cell proliferative capacity, and gene expression changes in lung adenocarcinoma cell lines, were further performed. Results In the TCGA set, three methylation CpG sites were selected that were associated with lung adenocarcinoma prognosis (cg14517217, cg15386964, and cg18878992). The risk of mortality was increased in lung adenocarcinoma patients with the gradual increase level of methylation signature based on three methylation sites levels (HR = 45.30, 95% CI = 26.69–66.83; p < 0.001). The C‐statistic value increased to 0.77 when age, gender, and other clinical variables were added to the signature to prediction model. A similar situation was confirmed in Chinese lung adenocarcinoma cohort. In the biological function studies, the proliferative capacity of cell lines was inhibited when the cells were demethylated with 5‐aza‐2'‐deoxycytidine (5‐aza‐2dC). The mRNA and protein expression levels of SEPT9 and HIST1H2BH (cg14517217 and cg15386964) were downregulated with different concentrations of 5‐aza‐2dC treatment, while cg18878992 showed the opposite result. Conclusion This study is the first to develop a three‐CpG‐based model for lung adenocarcinoma, which is a practical and useful tool for prognostic prediction that has been validated in a Chinese population.
Collapse
Affiliation(s)
- Ke Wang
- Medical College, Hubei University of Arts and Science, Xiangyang, Hubei, China.,Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Ying Liu
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Guanzhong Lu
- Medical College, Hubei University of Arts and Science, Xiangyang, Hubei, China
| | - Jinrong Xiao
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Jiao Huang
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Lin Lei
- Department of Cancer Control, Shenzhen Center for Chronic Disease Control, Shenzhen, Guangdong, China
| | - Ji Peng
- Department of Cancer Control, Shenzhen Center for Chronic Disease Control, Shenzhen, Guangdong, China
| | - Yangkai Li
- Department of Thoracic Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Sheng Wei
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| |
Collapse
|
87
|
Zhang Y, Guan B, WU Y, Du F, Zhuang J, Yang Y, Guan G, Liu X. LncRNAs Associated with Chemoradiotherapy Response and Prognosis in Locally Advanced Rectal Cancer. J Inflamm Res 2021; 14:6275-6292. [PMID: 34866926 PMCID: PMC8636753 DOI: 10.2147/jir.s334096] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2021] [Accepted: 11/05/2021] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND There are only limited studies on the long non-coding RNAs (lncRNAs) associated with neoadjuvant chemoradiotherapy (NCRT) response and prognosis of locally advanced rectal cancer (LARC) patients. This study identified lncRNAs associated with NCRT response and prognosis in CRC patients and explored their potential predictive mechanisms. METHODS The study subjected the LncRNA expression profiles from our previous gene chip data to LASSO and identified a four-lncRNA signature that predicted NCRT response and prognosis. A Cox regression model was subsequently performed to identify the prognostic risk factors. The function of LINC00909, the lncRNA with the most powerful predictive ability, was finally identified in vivo and in vitro using CRC cell lines. RESULTS A comparison of the relative lncRNA expression of NCRT-responsive and non-responsive patients revealed four hub lncRNAs: DBET, LINC00909, FLJ33534, and HSD52 with AUC = 0.68, 0.73, 0.73, and 0.70, respectively (all p < 0.05). COX regression analysis further demonstrated that DBET, LINC00909 and FLJ33534 were associated with the DFS in CRC patients. The expression of the four lncRNAs was also significant in LARC patients who had not undergone NCRT (all p < 0.05). A risk score model was subsequently constructed based on the results of the multivariate COX analysis and used to predict NCRT response and prognosis in the CRC and LARC patients. The expression and prognosis of DBET, LINC00909 and FLJ33534 in the CRC tissues were further validated in the R2 platform and Oncomine database. Notably, overexpression of the LINC00909 increased the cell line resistance to the 5-FU and radiotherapy in vivo and in vitro. CONCLUSION DBET, LINC00909, and FLJ33534 are potential novel biomarkers for predicting NCRT response and prognosis in CRC patients. In particular, LINC00909 is an effective oncogene in CRC that could be used as a novel therapeutic target to enhance NCRT response.
Collapse
Affiliation(s)
- Yiyi Zhang
- Department of Colorectal Surgery, The First Affiliated Hospital of Fujian Medical University, Fuzhou, People’s Republic of China
| | - Bingjie Guan
- Department of Radiation Oncology, Fujian Medical University Union Hospital, Fuzhou, People’s Republic of China
| | - Yong WU
- Department of Colorectal Surgery, The First Affiliated Hospital of Fujian Medical University, Fuzhou, People’s Republic of China
| | - Fan Du
- Department of Gastroenterology, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, 330006, People’s Republic of China
| | - Jinfu Zhuang
- Department of Colorectal Surgery, The First Affiliated Hospital of Fujian Medical University, Fuzhou, People’s Republic of China
| | - Yuanfeng Yang
- Department of Colorectal Surgery, The First Affiliated Hospital of Fujian Medical University, Fuzhou, People’s Republic of China
| | - Guoxian Guan
- Department of Colorectal Surgery, The First Affiliated Hospital of Fujian Medical University, Fuzhou, People’s Republic of China
| | - Xing Liu
- Department of Colorectal Surgery, The First Affiliated Hospital of Fujian Medical University, Fuzhou, People’s Republic of China
| |
Collapse
|
88
|
Comprehensive analysis of ceRNA networks to determine genes related to prognosis, overall survival, and immune infiltration in clear cell renal carcinoma. Comput Biol Med 2021; 141:105043. [PMID: 34839901 DOI: 10.1016/j.compbiomed.2021.105043] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2021] [Revised: 10/27/2021] [Accepted: 11/13/2021] [Indexed: 12/22/2022]
Abstract
BACKGROUND Clear cell renal cell carcinoma (ccRCC) is one of the common subtypes of kidney cancer. Circular RNAs (circRNAs) act as competing endogenous RNAs (ceRNAs) to affect the expression of microRNAs (miRNAs), and hence the expression of genes involved in the development and progression of ccRCC. However, these interactions have not been sufficiently explored. METHODS The differential expression of circRNAs (DEC) was extracted from the GEO database, and the expression of circRNAs was analyzed by the Limma R package. The interaction of miRNAs with circRNAs was predicted using (cancer-specific circRNA database) CSCD and circinteractome database. The genes affected by the miRNAs were predicted by miRwalk version 3, and the differential expression was retrieved using TCGA. Functional enrichment was assessed and a PPI network was created using DAVID and Cytoscape, respectively. The genes with significant interactions (hub-genes) were screened, and the total survival rate of ccRCC patients was extracted from the Gene Expression Profiling Interactive Analysis (GEPIA) database. To confirm the expression of OS genes we used the Immunohistochemistry (IHC) data and TCGA database. The correlation between gene expression and immune cell infiltration was investigated using TIMER2.0. Finally, potential drug candidates were predicted by the cMAP database. RESULTS Four DECs (hsa_circ_0003340, hsa_circ_0007836, hsa_circ_0020303, and hsa_circ_0001873) were identified, along with 11 interacting miRNAs (miR-1224-3p, miR-1294, miR-1205, miR-1231, miR-615-5p, miR-940, miR-1283, and miR-1305). These miRNAs were predicted to affect 1282 target genes, and function enrichment was used to identify the genes involved in cancer biology. 18 hub-genes (CCR1, VCAM1, NCF2, LAPTM5, NCKAP1L, CTSS, BTK, LILRB2, CD53, MPEG1, C3AR1, GPR183, C1QA, C1QC, P2RY8, LY86, CYBB, and IKZF1) were identified from a PPI network. VCAM1, NCF2, CTSS, LILRB2, MPEG1, C3AR1, P2RY8, and CYBB could affect the survival of ccRCC patients. The hub-gene expression was correlated with tumor immune cell infiltration and patient prognosis. Two potantial drug candidates, naphazoline and lithocholic acid could play a role in ccRCC therapy, as well other cancers. CONCLUSION This bioinformatics analysis brings a new insight into the role of circRNA/miRNA/mRNA interactions in ccRCC pathogenesis, prognosis, and possible drug treatment or immunotherapy.
Collapse
|
89
|
Deng GC, Lv Y, Yan H, Sun DC, Qu TT, Pan YT, Han QL, Dai GH. Nomogram to predict survival of patients with advanced and metastatic pancreatic Cancer. BMC Cancer 2021; 21:1227. [PMID: 34781928 PMCID: PMC8594118 DOI: 10.1186/s12885-021-08943-w] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2021] [Accepted: 10/28/2021] [Indexed: 01/04/2023] Open
Abstract
BACKGROUND Nomograms are rarely employed to estimate the survival of patients with advanced and metastatic pancreatic cancer (PC). Herein, we developed a comprehensive approach to using a nomogram to predict survival probability in patients with advanced and metastatic PC. METHODS A total of 323 patients with advanced and metastatic PC were identified from the Chinese People's Liberation Army (PLA) General Hospital. A baseline nomogram was constructed using baseline variables of 323 patients. Additionally, 233 patients, whose tumors showed initial responses to first-line chemotherapy, were enrolled in the chemotherapy response-based model. 128 patients and 108 patients with advanced and metastatic PC from January 2019 to April 2021 were selected for external validating baseline model and chemotherapy response-based model. The 1-year and 2-year survival probability was evaluated using multivariate COX regression models. The discrimination and calibration capacity of the nomograms were assessed using C-statistic and calibration plots. The predictive accuracy and net benefit of the nomograms were evaluated using ROC curve and DCA, respectively. RESULTS In the baseline model, six variables (gender, KPS, baseline TB, baseline N, baseline WBC and baseline CA19-9) were used in the final model. In the chemotherapy response-based model, nine variables (KPS, gender, ascites, baseline N, baseline CA 19-9, baseline CEA, change in CA 19-9 level at week, change in CEA level at week and initial response to chemotherapy) were included in the final model. The C-statistics of the baseline nomogram and the chemotherapy response-based nomogram were 0.67 (95% CI, 0.62-0.71) and 0.74 (95% CI, 0.69-0.77), respectively. CONCLUSION These nomograms were constructed to predict the survival probability of patients of advanced and metastatic PC. The baseline model and chemotherapy response-based model performed well in survival prediction.
Collapse
Affiliation(s)
- G C Deng
- School of Medicine, Nankai University, Tianjin, China
- Senior Department of Oncology, The Fifth Medical Center of PLA General Hospital, Beijing, China
| | - Y Lv
- School of Medicine, Nankai University, Tianjin, China
| | - H Yan
- School of Medicine, Nankai University, Tianjin, China
| | - D C Sun
- School of Medicine, Nankai University, Tianjin, China
| | - T T Qu
- School of Medicine, Nankai University, Tianjin, China
- Senior Department of Oncology, The Fifth Medical Center of PLA General Hospital, Beijing, China
| | - Y T Pan
- School of Medicine, Nankai University, Tianjin, China
| | - Q L Han
- School of Medicine, Nankai University, Tianjin, China.
| | - G H Dai
- School of Medicine, Nankai University, Tianjin, China.
- Senior Department of Oncology, The Fifth Medical Center of PLA General Hospital, Beijing, China.
| |
Collapse
|
90
|
Xue B, Jiang J, Chen L, Wu S, Zheng X, Zheng X, Tang K. Development and Validation of a Radiomics Model Based on 18F-FDG PET of Primary Gastric Cancer for Predicting Peritoneal Metastasis. Front Oncol 2021; 11:740111. [PMID: 34765549 PMCID: PMC8576566 DOI: 10.3389/fonc.2021.740111] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Accepted: 10/07/2021] [Indexed: 12/24/2022] Open
Abstract
Objectives The aim of this study was to develop a preoperative positron emission tomography (PET)-based radiomics model for predicting peritoneal metastasis (PM) of gastric cancer (GC). Methods In this study, a total of 355 patients (109PM+, 246PM-) who underwent preoperative fluorine-18-fludeoxyglucose (18F-FDG) PET images were retrospectively analyzed. According to a 7:3 ratio, patients were randomly divided into a training set and a validation set. Radiomics features and metabolic parameters data were extracted from PET images. The radiomics features were selected by logistic regression after using maximum relevance and minimum redundancy (mRMR) and the least shrinkage and selection operator (LASSO) method. The radiomics models were based on the rest of these features. The performance of the models was determined by their discrimination, calibration, and clinical usefulness in the training and validation sets. Results After dimensionality reduction, 12 radiomics feature parameters were obtained to construct radiomics signatures. According to the results of the multivariate logistic regression analysis, only carbohydrate antigen 125 (CA125), maximum standardized uptake value (SUVmax), and the radiomics signature showed statistically significant differences between patients (P<0.05). A radiomics model was developed based on the logistic analyses with an AUC of 0.86 in the training cohort and 0.87 in the validation cohort. The clinical prediction model based on CA125 and SUVmax was 0.76 in the training set and 0.69 in the validation set. The comprehensive model, which contained a rad-score and the clinical factor (CA125) as well as the metabolic parameter (SUVmax), showed promising performance with an AUC of 0.90 in the training cohort and 0.88 in the validation cohort, respectively. The calibration curve showed the actual rate of the nomogram-predicted probability of peritoneal metastasis. Decision curve analysis (DCA) also demonstrated the good clinical utility of the radiomics nomogram. Conclusions The comprehensive model based on the rad-score and other factors (SUVmax, CA125) can provide a novel tool for predicting peritoneal metastasis of gastric cancer patients preoperatively.
Collapse
Affiliation(s)
- Beihui Xue
- Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Jia Jiang
- Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Lei Chen
- Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Sunjie Wu
- Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Xuan Zheng
- Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Xiangwu Zheng
- Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Kun Tang
- Department of Nuclear Medicine, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| |
Collapse
|
91
|
Chen D, Chen H, Chi L, Fu M, Wang G, Wu Z, Xu S, Sun C, Xu X, Lin L, Cheng J, Jiang W, Dong X, Lu J, Zheng J, Chen G, Li G, Zhuo S, Yan J. Association of Tumor-Associated Collagen Signature With Prognosis and Adjuvant Chemotherapy Benefits in Patients With Gastric Cancer. JAMA Netw Open 2021; 4:e2136388. [PMID: 34846524 PMCID: PMC8634059 DOI: 10.1001/jamanetworkopen.2021.36388] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
IMPORTANCE The current TNM staging system provides limited information for prognosis prediction and adjuvant chemotherapy benefits for patients with gastric cancer (GC). OBJECTIVE To develop a tumor-associated collagen signature of GC (TACSGC) in the tumor microenvironment to predict prognosis and adjuvant chemotherapy benefits in patients with GC. DESIGN, SETTING, AND PARTICIPANTS This retrospective cohort study included a training cohort of 294 consecutive patients treated between January 1, 2012, and December 31, 2013, from Nanfang Hospital, Southern Medical University, People's Republic of China, and a validation cohort of 225 consecutive patients treated between October 1, 2010, and December 31, 2012, from Fujian Provincial Cancer Hospital, Fujian Medical University, People's Republic of China. In total, 146 collagen features in the tumor microenvironment were extracted with multiphoton imaging. A TACSGC was then constructed using the least absolute shrinkage and selection operator Cox proportional hazards regression model in the training cohort. Data analysis was conducted from October 1, 2020, to April 30, 2021. MAIN OUTCOMES AND MEASURES The association of TACSGC with disease-free survival (DFS) and overall survival (OS) was assessed. An independent external cohort was included to validate the results. Interactions between TACSGC and adjuvant chemotherapy were calculated. RESULTS This study included 519 patients (median age, 57 years [IQR, 49-65 years]; 360 [69.4%] male). A 9 feature-based TACSGC was built. A higher TACSGC level was significantly associated with worse DFS and OS in both the training (DFS: hazard ratio [HR], 3.57 [95% CI, 2.45-5.20]; OS: HR, 3.54 [95% CI, 2.41-5.20]) and validation (DFS: HR, 3.10 [95% CI, 2.26-4.27]; OS: HR, 3.24 [95% CI, 2.33-4.50]) cohorts (continuous variable, P < .001 for all comparisons). Multivariable analyses found that carbohydrate antigen 19-9, depth of invasion, lymph node metastasis, distant metastasis, and TACSGC were independent prognostic predictors of GC, and 2 integrated nomograms that included the 5 predictors were established for predicting DFS and OS. Compared with clinicopathological models that included only the 4 clinicopathological predictors, the integrated nomograms yielded an improved discrimination for prognosis prediction in a C index comparison (training cohort: DFS, 0.80 [95% CI, 0.73-0.88] vs 0.78 [95% CI, 0.71-0.85], P = .03; OS, 0.81 [95% CI, 0.75-0.88] vs 0.80 [95% CI, 0.73-0.86], P = .03; validation cohort: DFS, 0.78 [95% CI, 0.70-0.87] vs 0.76 [95% CI, 0.67-0.84], P = .006; OS, 0.78 [95% CI, 0.69-0.86] vs 0.75 [95% CI, 0.67-0.84], P = .002). Patients with stage II and III GC and low TACSGC levels rather than high TACSGC levels had a favorable response to adjuvant chemotherapy (DFS: HR, 0.65 [95% CI, 0.43-0.96]; P = .03; OS: HR, 0.55 [95% CI, 0.36-0.82]; P = .004; dichotomized variable, P < .001 for interaction for both comparisons). CONCLUSIONS AND RELEVANCE The findings suggest that TACSGC provides additional prognostic information for patients with GC and may distinguish patients with stage II and III disease who are more likely to derive benefits from adjuvant chemotherapy.
Collapse
Affiliation(s)
- Dexin Chen
- Department of General Surgery, Guangdong Provincial Key Laboratory of Precision Medicine for Gastrointestinal Tumor, Nanfang Hospital, The First School of Clinical Medicine, Southern Medical University, Guangzhou, People’s Republic of China
- School of Science, Jimei University, Xiamen, People’s Republic of China
| | - Hao Chen
- Department of General Surgery, Guangdong Provincial Key Laboratory of Precision Medicine for Gastrointestinal Tumor, Nanfang Hospital, The First School of Clinical Medicine, Southern Medical University, Guangzhou, People’s Republic of China
| | - Liangjie Chi
- Department of General Surgery, Guangdong Provincial Key Laboratory of Precision Medicine for Gastrointestinal Tumor, Nanfang Hospital, The First School of Clinical Medicine, Southern Medical University, Guangzhou, People’s Republic of China
- Department of Gastrointestinal Surgery, Fujian Provincial Hospital, Teaching Hospital of Fujian Medical University, Fuzhou, People’s Republic of China
| | - Meiting Fu
- Department of Gastroenterology, Guangdong Provincial Key Laboratory of Gastroenterology, Nanfang Hospital, The First School of Clinical Medicine, Southern Medical University, Guangzhou, People’s Republic of China
| | - Guangxing Wang
- Key Laboratory of OptoElectronic Science and Technology for Medicine of Ministry of Education, Fujian Normal University, Fuzhou, People’s Republic of China
| | - Zhida Wu
- Department of Pathology, Fujian Medical University Cancer Hospital and Fujian Cancer Hospital, Fuzhou, People’s Republic of China
| | - Shuoyu Xu
- Department of General Surgery, Guangdong Provincial Key Laboratory of Precision Medicine for Gastrointestinal Tumor, Nanfang Hospital, The First School of Clinical Medicine, Southern Medical University, Guangzhou, People’s Republic of China
| | - Caihong Sun
- Key Laboratory of OptoElectronic Science and Technology for Medicine of Ministry of Education, Fujian Normal University, Fuzhou, People’s Republic of China
| | - Xueqin Xu
- Key Laboratory of OptoElectronic Science and Technology for Medicine of Ministry of Education, Fujian Normal University, Fuzhou, People’s Republic of China
| | - Liyan Lin
- Department of Pathology, Fujian Medical University Cancer Hospital and Fujian Cancer Hospital, Fuzhou, People’s Republic of China
| | - Jiaxin Cheng
- Department of General Surgery, Guangdong Provincial Key Laboratory of Precision Medicine for Gastrointestinal Tumor, Nanfang Hospital, The First School of Clinical Medicine, Southern Medical University, Guangzhou, People’s Republic of China
| | - Wei Jiang
- Department of General Surgery, Guangdong Provincial Key Laboratory of Precision Medicine for Gastrointestinal Tumor, Nanfang Hospital, The First School of Clinical Medicine, Southern Medical University, Guangzhou, People’s Republic of China
| | - Xiaoyu Dong
- Department of General Surgery, Guangdong Provincial Key Laboratory of Precision Medicine for Gastrointestinal Tumor, Nanfang Hospital, The First School of Clinical Medicine, Southern Medical University, Guangzhou, People’s Republic of China
| | - Jianping Lu
- Department of Pathology, Fujian Medical University Cancer Hospital and Fujian Cancer Hospital, Fuzhou, People’s Republic of China
| | - Jixiang Zheng
- Department of General Surgery, Guangdong Provincial Key Laboratory of Precision Medicine for Gastrointestinal Tumor, Nanfang Hospital, The First School of Clinical Medicine, Southern Medical University, Guangzhou, People’s Republic of China
| | - Gang Chen
- Department of Pathology, Fujian Medical University Cancer Hospital and Fujian Cancer Hospital, Fuzhou, People’s Republic of China
| | - Guoxin Li
- Department of General Surgery, Guangdong Provincial Key Laboratory of Precision Medicine for Gastrointestinal Tumor, Nanfang Hospital, The First School of Clinical Medicine, Southern Medical University, Guangzhou, People’s Republic of China
| | - Shuangmu Zhuo
- School of Science, Jimei University, Xiamen, People’s Republic of China
| | - Jun Yan
- Department of General Surgery, Guangdong Provincial Key Laboratory of Precision Medicine for Gastrointestinal Tumor, Nanfang Hospital, The First School of Clinical Medicine, Southern Medical University, Guangzhou, People’s Republic of China
| |
Collapse
|
92
|
A Novel Cancer Stemness-Related Signature for Predicting Prognosis in Patients with Colon Adenocarcinoma. Stem Cells Int 2021; 2021:7036059. [PMID: 34691191 PMCID: PMC8536464 DOI: 10.1155/2021/7036059] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Accepted: 09/13/2021] [Indexed: 12/19/2022] Open
Abstract
Objective To explore the cancer stemness features and develop a novel cancer stemness-related prognostic signature for colon adenocarcinoma (COAD). Methods We downloaded the mRNA expression data and clinical data of COAD from TCGA database and GEO database. Stemness index, mRNAsi, was utilized to investigate cancer stemness features. Weighted gene coexpression network analysis (WGCNA) was used to identify cancer stemness-related genes. Univariate and multivariate Cox regression analyses were applied to construct a prognostic risk cancer stemness-related signature. We then performed internal and external validation. The relationship between cancer stemness and COAD immune microenvironment was investigated. Results COAD patients with higher mRNAsi score or EREG-mRNAsi score have significant longer overall survival (OS). We identified 483 differently expressed genes (DEGs) between the high and low mRNAsi score groups. We developed a cancer stemness-related signature using fifteen genes (including RAB31, COL6A3, COL5A2, CCDC80, ADAM12, VGLL3, ECM2, POSTN, DPYSL3, PCDH7, CRISPLD2, COLEC12, NRP2, ISLR, and CCDC8) for prognosis prediction of COAD. Low-risk score was associated with significantly preferable OS in comparison with high-risk score, and the area under the ROC curve (AUC) for OS prediction was 0.705. The prognostic signature was an independent predictor for OS of COAD. Macrophages, mast cells, and T helper cells were the vital infiltration immune cells, and APC costimulation and type II IFN response were the vital immune pathways in COAD. Conclusions We developed and validated a novel cancer stemness-related prognostic signature for COAD, which would contribute to understanding of molecular mechanism in COAD.
Collapse
|
93
|
Tian B, Hou M, Zhou K, Qiu X, Du Y, Gu Y, Yin X, Wang J. A Novel TCGA-Validated, MiRNA-Based Signature for Prediction of Breast Cancer Prognosis and Survival. Front Cell Dev Biol 2021; 9:717462. [PMID: 34589485 PMCID: PMC8473752 DOI: 10.3389/fcell.2021.717462] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Accepted: 08/19/2021] [Indexed: 12/21/2022] Open
Abstract
Breast cancer (BC) is the most common cancer affecting women and the leading cause of cancer-related deaths worldwide. Compelling evidence indicates that microRNAs (miRNAs) are inextricably involved in the development of cancer. Here, we constructed a novel model, based on miRNA-seq and clinical data downloaded from The Cancer Genome Atlas (TCGA). Data from a total of 962 patients were included in this study, and the relationships among their clinicopathological features, survival, and miRNA-seq expression levels were analyzed. Hsa-miR-186 and hsa-miR-361 were identified as internal reference miRNAs and used to normalize miRNA expression data. A five-miRNA signature, constructed using univariate and multivariate Cox regression, was significantly associated with disease-specific survival (DSS) of patients with BC. Kaplan–Meier (KM) and receiver operating characteristic (ROC) analyses were conducted to confirm the clinical significance of the five-miRNA signature. Finally, a nomogram was constructed based on the five-miRNA signature to evaluate its clinical value. Cox regression analysis revealed that a five-miRNA signature was significantly associated with DSS of patients with BC. KM analysis demonstrated that the signature could efficiently distinguish high- and low-risk patients. Moreover, ROC analysis showed that the five-miRNA signature exhibited high sensitivity and specificity in predicting the prognosis of patients with BC. Patients in the high-risk subgroup who received adjuvant chemotherapy had a significantly lower incidence of mortality than those who did not. A nomogram constructed based on the five-miRNA signature was effective in predicting 5-year DSS. This study presents a novel five-miRNA signature as a reliable prognostic tool to predict DSS and provide theoretical reference significance for individualized clinical decisions for patients with BC.
Collapse
Affiliation(s)
- Baoxing Tian
- Department of Breast Surgery, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Mengjie Hou
- Shanghai Key Laboratory of Tissue Engineering, Department of Plastic and Reconstructive Surgery, Shanghai 9th People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Kun Zhou
- Department of General Surgery, Jing'an District Center Hospital, Fudan University, Shanghai, China
| | - Xia Qiu
- Department of Breast Surgery, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yibao Du
- Department of Breast Surgery, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yifan Gu
- Department of Breast Surgery, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xiaoxing Yin
- Department of General Surgery, Jing'an District Center Hospital, Fudan University, Shanghai, China
| | - Jie Wang
- Department of Breast Surgery, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| |
Collapse
|
94
|
Glycolysis-related gene expression profiling serves as a novel prognosis risk predictor for human hepatocellular carcinoma. Sci Rep 2021; 11:18875. [PMID: 34556750 PMCID: PMC8460833 DOI: 10.1038/s41598-021-98381-2] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2021] [Accepted: 08/31/2021] [Indexed: 02/07/2023] Open
Abstract
Metabolic pattern reconstruction is an important factor in tumor progression. Metabolism of tumor cells is characterized by abnormal increase in anaerobic glycolysis, regardless of high oxygen concentration, resulting in a significant accumulation of energy from glucose sources. These changes promotes rapid cell proliferation and tumor growth, which is further referenced a process known as the Warburg effect. The current study reconstructed the metabolic pattern in progression of cancer to identify genetic changes specific in cancer cells. A total of 12 common types of solid tumors were included in the current study. Gene set enrichment analysis (GSEA) was performed to analyze 9 glycolysis-related gene sets, which are implicated in the glycolysis process. Univariate and multivariate analyses were used to identify independent prognostic variables for construction of a nomogram based on clinicopathological characteristics and a glycolysis-related gene prognostic index (GRGPI). The prognostic model based on glycolysis genes showed high area under the curve (AUC) in LIHC (Liver hepatocellular carcinoma). The findings of the current study showed that 8 genes (AURKA, CDK1, CENPA, DEPDC1, HMMR, KIF20A, PFKFB4, STMN1) were correlated with overall survival (OS) and recurrence-free survival (RFS). Further analysis showed that the prediction model accurately distinguished between high- and low-risk cancer patients among patients in different clusters in LIHC. A nomogram with a well-fitted calibration curve based on gene expression profiles and clinical characteristics showed good discrimination based on internal and external cohorts. These findings indicate that changes in expression level of metabolic genes implicated in glycolysis can contribute to reconstruction of tumor-related microenvironment.
Collapse
|
95
|
MicroRNA-Based Risk Score for Predicting Tumor Progression Following Radioactive Iodine Ablation in Well-Differentiated Thyroid Cancer Patients: A Propensity-Score Matched Analysis. Cancers (Basel) 2021; 13:cancers13184649. [PMID: 34572876 PMCID: PMC8468667 DOI: 10.3390/cancers13184649] [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: 05/27/2021] [Revised: 08/07/2021] [Accepted: 08/27/2021] [Indexed: 12/12/2022] Open
Abstract
Simple Summary The three-tiered American Thyroid Association (ATA) risk stratification helps clinicians tailor decisions regarding follow-up modalities and the need for postoperative radioactive iodine (RAI) ablation and radiotherapy. However, a significant number of well-differentiated thyroid cancers (DTC) progress after treatment. Current follow-up modalities have also been proposed to detect disease relapse and recurrence but have failed to be sufficiently sensitive or specific to detect, monitor, or determine progression. Therefore, we assessed the predictive accuracy of the microRNA-based risk score in DTC with and without postoperative RAI. We confirm the prognostic role of triad biomarkers (miR-2f04, miR-221, and miR-222) with higher sensitivity and specificity for predicting disease progression than the ATA risk score. Compared to indolent tumors, a higher risk score was found in progressive samples and was associated with shorter survival. Consequently, our prognostic microRNA signature and nomogram provide a clinically practical and reliable ancillary measure to determine the prognosis of DTC patients. Abstract To identify molecular markers that can accurately predict aggressive tumor behavior at the time of surgery, a propensity-matching score analysis of archived specimens yielded two similar datasets of DTC patients (with and without RAI). Bioinformatically selected microRNAs were quantified by qRT-PCR. The risk score was generated using Cox regression and assessed using ROC, C-statistic, and Brier-score. A predictive Bayesian nomogram was established. External validation was performed, and causal network analysis was generated. Within the eight-year follow-up period, progression was reported in 51.5% of cases; of these, 48.6% had the T1a/b stage. Analysis showed upregulation of miR-221-3p and miR-222-3p and downregulation of miR-204-5p in 68 paired cancer tissues (p < 0.001). These three miRNAs were not differentially expressed in RAI and non-RAI groups. The ATA risk score showed poor discriminative ability (AUC = 0.518, p = 0.80). In contrast, the microRNA-based risk score showed high accuracy in predicting tumor progression in the whole cohorts (median = 1.87 vs. 0.39, AUC = 0.944) and RAI group (2.23 vs. 0.37, AUC = 0.979) at the cutoff >0.86 (92.6% accuracy, 88.6% sensitivity, 97% specificity) in the whole cohorts (C-statistics = 0.943/Brier = 0.083) and RAI subgroup (C-statistic = 0.978/Brier = 0.049). The high-score group had a three-fold increased progression risk (hazard ratio = 2.71, 95%CI = 1.86–3.96, p < 0.001) and shorter survival times (17.3 vs. 70.79 months, p < 0.001). Our prognostic microRNA signature and nomogram showed excellent predictive accuracy for progression-free survival in DTC.
Collapse
|
96
|
Identification and Prognostic Value Exploration of Radiotherapy Sensitivity-Associated Genes in Non-Small-Cell Lung Cancer. BIOMED RESEARCH INTERNATIONAL 2021; 2021:5963868. [PMID: 34518802 PMCID: PMC8433590 DOI: 10.1155/2021/5963868] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/14/2021] [Revised: 06/16/2021] [Accepted: 08/17/2021] [Indexed: 11/30/2022]
Abstract
Background Non-small-cell lung cancer (NSCLC) is a prevalent malignancy with high mortality and poor prognosis. The radiotherapy is one of the most common treatments of NSCLC, and the radiotherapy sensitivity of patients could affect the individual prognosis of NSCLC. However, the prognostic signatures related to radiotherapy response still remain limited. Here, we explored the radiosensitivity-associated genes and constructed the prognostically predictive model of NSCLC cases. Methods The NSCLC samples with radiotherapy records were obtained from The Cancer Genome Atlas database, and the mRNA expression profiles of NSCLC patients from the GSE30219 and GSE31210 datasets were obtained from the Gene Expression Omnibus database. The Weighted Gene Coexpression Network Analysis (WGCNA), univariate, least absolute shrinkage and selection operator (LASSO), multivariate Cox regression analysis, and nomogram were conducted to identify and validate the radiotherapy sensitivity-related signature. Results WGCNA revealed that 365 genes were significantly correlated with radiotherapy response. LASSO Cox regression analysis identified 8 genes, including FOLR3, SLC6A11, ALPP, IGFN1, KCNJ12, RPS4XP22, HIST1H2BH, and BLACAT1. The overall survival (OS) of the low-risk group was better than that of the high-risk group separated by the Risk Score based on these 8 genes for the NSCLC patients. Furthermore, the immune infiltration analysis showed that monocytes and activated memory CD4 T cells had different relative proportions in the low-risk group compared with the high-risk group. The Risk Score was correlated with immune checkpoints, including CTLA4, PDL1, LAG3, and TIGIT. Conclusion We identified 365 genes potentially correlated with the radiotherapy response of NSCLC patients. The Risk Score model based on the identified 8 genes can predict the prognosis of NSCLC patients.
Collapse
|
97
|
Ubaldi L, Valenti V, Borgese RF, Collura G, Fantacci ME, Ferrera G, Iacoviello G, Abbate BF, Laruina F, Tripoli A, Retico A, Marrale M. Strategies to develop radiomics and machine learning models for lung cancer stage and histology prediction using small data samples. Phys Med 2021; 90:13-22. [PMID: 34521016 DOI: 10.1016/j.ejmp.2021.08.015] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/03/2021] [Revised: 08/21/2021] [Accepted: 08/28/2021] [Indexed: 02/09/2023] Open
Abstract
Predictive models based on radiomics and machine-learning (ML) need large and annotated datasets for training, often difficult to collect. We designed an operative pipeline for model training to exploit data already available to the scientific community. The aim of this work was to explore the capability of radiomic features in predicting tumor histology and stage in patients with non-small cell lung cancer (NSCLC). We analyzed the radiotherapy planning thoracic CT scans of a proprietary sample of 47 subjects (L-RT) and integrated this dataset with a publicly available set of 130 patients from the MAASTRO NSCLC collection (Lung1). We implemented intra- and inter-sample cross-validation strategies (CV) for evaluating the ML predictive model performances with not so large datasets. We carried out two classification tasks: histology classification (3 classes) and overall stage classification (two classes: stage I and II). In the first task, the best performance was obtained by a Random Forest classifier, once the analysis has been restricted to stage I and II tumors of the Lung1 and L-RT merged dataset (AUC = 0.72 ± 0.11). For the overall stage classification, the best results were obtained when training on Lung1 and testing of L-RT dataset (AUC = 0.72 ± 0.04 for Random Forest and AUC = 0.84 ± 0.03 for linear-kernel Support Vector Machine). According to the classification task to be accomplished and to the heterogeneity of the available dataset(s), different CV strategies have to be explored and compared to make a robust assessment of the potential of a predictive model based on radiomics and ML.
Collapse
Affiliation(s)
- L Ubaldi
- Physics Department, University of Pisa, Pisa, Italy; National Institute for Nuclear Physics (INFN), Pisa Division, Pisa, Italy
| | - V Valenti
- REM Radiation Therapy Center, Viagrande (CT), I-95029 Catania, Italy
| | - R F Borgese
- Physics and Chemistry Department "Emilio Segrè", University of Palermo, Palermo, Italy; National Institute for Nuclear Physics (INFN), Catania Division, Catania, Italy
| | - G Collura
- Physics and Chemistry Department "Emilio Segrè", University of Palermo, Palermo, Italy; National Institute for Nuclear Physics (INFN), Catania Division, Catania, Italy
| | - M E Fantacci
- Physics Department, University of Pisa, Pisa, Italy; National Institute for Nuclear Physics (INFN), Pisa Division, Pisa, Italy
| | - G Ferrera
- Radiation Oncology, ARNAS-Civico Hospital, Palermo, Italy
| | - G Iacoviello
- Medical Physics Department, ARNAS-Civico Hospital, Palermo, Italy
| | - B F Abbate
- Medical Physics Department, ARNAS-Civico Hospital, Palermo, Italy
| | - F Laruina
- Physics Department, University of Pisa, Pisa, Italy; National Institute for Nuclear Physics (INFN), Pisa Division, Pisa, Italy
| | - A Tripoli
- REM Radiation Therapy Center, Viagrande (CT), I-95029 Catania, Italy
| | - A Retico
- National Institute for Nuclear Physics (INFN), Pisa Division, Pisa, Italy
| | - M Marrale
- Physics and Chemistry Department "Emilio Segrè", University of Palermo, Palermo, Italy; National Institute for Nuclear Physics (INFN), Catania Division, Catania, Italy
| |
Collapse
|
98
|
Chen R, Zhang C, Cheng Y, Wang S, Lin H, Zhang H. LncRNA UCC promotes epithelial-mesenchymal transition via the miR-143-3p/SOX5 axis in non-small-cell lung cancer. J Transl Med 2021; 101:1153-1165. [PMID: 33824420 DOI: 10.1038/s41374-021-00586-6] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2020] [Revised: 02/24/2021] [Accepted: 02/25/2021] [Indexed: 01/10/2023] Open
Abstract
Long non-coding RNAs (lncRNAs) have been found to play regulatory roles in cancers; for example, UCC was reported to promote colorectal cancer progression. However, the function of UCC in non-small-cell lung cancer (NSCLC) remains unclear. Therefore, mRNA and protein levels were assessed using qPCR and western blots. Cell viability was assessed by colony-formation assays. The interaction between lncRNAs and miRNAs was detected by dual-luciferase reporter and RIP assays. The tumorigenesis of NSCLC cells in vivo was determined by xenograft assays. LncRNA UCC was highly expressed in both NSCLC tissues and cells. Knockdown of UCC expression suppressed the proliferation of NSCLC cells. In addition, a dual-luciferase reporter system and RIP assays showed that UCC specifically bound to miR-143-3p and acted as a sponge of miR-143-3p in NSCLC cells. The miR-143-3p inhibitor rescued the inhibitory effect of sh-UCC on the proliferation of NSCLC cells. Moreover, miR-143-3p and UCC showed opposite effects on the expression of SOX5, which promoted EMT in NSCLC cells. In addition, in a mouse model, knockdown of UCC expression alleviated EMT and NSCLC progression in vivo, which was consistent with the in vitro results. In the current study, we found that UCC induced the proliferation and migration of NSCLC cells both in vitro and in vivo by inducing the expression of SOX5 via miR-143-3p and subsequently promoted EMT in NSCLC.
Collapse
Affiliation(s)
- Ri Chen
- Department of Cardiothoracic Surgery, Xiangya Hospital, Central South University, Changsha, Hunan, PR China
| | - Chunfan Zhang
- Department of General Thoracic Surgery, Xiangya Hospital, Central South University, Changsha, Hunan, PR China
- Xiangya Lung Cancer Center, Xiangya Hospital, Central South University, Changsha, Hunan, PR China
- Hunan Engineering Research Center for Pulmonary Nodules Precise Diagnosis & Treatment, Changsha, Hunan, PR China
| | - Yuanda Cheng
- Department of General Thoracic Surgery, Xiangya Hospital, Central South University, Changsha, Hunan, PR China
- Xiangya Lung Cancer Center, Xiangya Hospital, Central South University, Changsha, Hunan, PR China
- Hunan Engineering Research Center for Pulmonary Nodules Precise Diagnosis & Treatment, Changsha, Hunan, PR China
| | - Shaoqiang Wang
- Department of Thoracic Surgery, Affiliated Hospital of Jining Medical University, Jining Medical University, JiNing, Shandong, PR China
| | - Hang Lin
- Department of General Thoracic Surgery, Xiangya Hospital, Central South University, Changsha, Hunan, PR China
| | - Heng Zhang
- Department of General Thoracic Surgery, Xiangya Hospital, Central South University, Changsha, Hunan, PR China.
- Xiangya Lung Cancer Center, Xiangya Hospital, Central South University, Changsha, Hunan, PR China.
- Hunan Engineering Research Center for Pulmonary Nodules Precise Diagnosis & Treatment, Changsha, Hunan, PR China.
| |
Collapse
|
99
|
Jiang G, Zhang R, Yang X, Zhang W, Hou Y. Positive correlation between miR-570 and prognosis of colon cancer: inhibition of cell proliferation and invasion. Clin Exp Med 2021; 22:193-200. [PMID: 34471998 DOI: 10.1007/s10238-021-00753-5] [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: 10/21/2020] [Accepted: 08/09/2021] [Indexed: 10/20/2022]
Abstract
Colon cancer is one of most common cancers. The progression of various cancers is driven by miRNA-570. The role of miRNA-570 in the progression of colon cancer remains unclear. We aimed to investigate the clinical function of miR-570 and its impact on colon cancer cells. We evaluated the expression of miR-570 in colon cancer cells and analyzed its influence on the various clinical parameters. The Kaplan-Meier curve was plotted to understand the clinical role of miR-570. Cox regression analysis was performed to predict the prognostic factors in colon cancer. The Cell Counting Kit-8 was used to investigate the effect of miR-570 on cell proliferation. The transwell migration assay was performed to quantify cell migration and invasion. The quantitative real-time polymerase chain reaction technique was used to analyze the sample system. The results revealed that the level of miR-570 expression in colon cancer tissues and cell lines was low. The abnormal expression of miR-570 was associated with tumor size, extent of differentiation, lymph node metastasis, and tumor-node-metastasis stages. Downregulation of miR-570 indicated poor overall survival (OS), poor relapse-free survival, and unfavorable cancer-specific survival (CSS) rates in patients with colon cancer. The results from Cox regression analysis revealed that miR-570 expression could be used as an independent prognostic biomarker for OS and CSS in colon cancer. Overexpression of miR-570 can potentially result in the inhibition of cell proliferation, migration, and invasion. The results proved that miR-570 could potentially function as a tumor suppressor and a potential prognostic factor in patients with colon cancer.
Collapse
Affiliation(s)
- Guoxiang Jiang
- Second Department of Radiotherapy, Yantai Hill Hospital, Yantai, 264003, Shandong, China
| | - Ruihua Zhang
- Department of Gastroenterology, Weifang People's Hospital, Weifang, 261000, Shandong, China
| | - Xuan Yang
- Department of Gastroenterology, Shengli Oilfield Central Hospital, Dongying, 257034, Shandong, China
| | - Wen Zhang
- Department of Gastroenterology, Shengli Oilfield Central Hospital, Dongying, 257034, Shandong, China
| | - Yubin Hou
- First Department of Surgery, Yantai Tao Cun Central Hospital, Yantai, 265301, Shandong, China.
| |
Collapse
|
100
|
Wang X, Li C, Chen T, Li W, Zhang H, Zhang D, Liu Y, Han D, Li Y, Li Z, Luo D, Zhang N, Yang Q. Identification and Validation of a Five-Gene Signature Associated With Overall Survival in Breast Cancer Patients. Front Oncol 2021; 11:660242. [PMID: 34513664 PMCID: PMC8428534 DOI: 10.3389/fonc.2021.660242] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2021] [Accepted: 08/02/2021] [Indexed: 01/11/2023] Open
Abstract
BACKGROUND Recent years, the global prevalence of breast cancer (BC) was still high and the underlying molecular mechanisms remained largely unknown. The investigation of prognosis-related biomarkers had become an urgent demand. RESULTS In this study, gene expression profiles and clinical information of breast cancer patients were downloaded from the TCGA database. The differentially expressed genes (DEGs) were estimated by Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. A risk score formula involving five novel prognostic associated biomarkers (EDN2, CLEC3B, SV2C, WT1, and MUC2) were then constructed by LASSO. The prognostic value of the risk model was further confirmed in the TCGA entire cohort and an independent external validation cohort. To explore the biological functions of the selected genes, in vitro assays were performed, indicating that these novel biomarkers could markedly influence breast cancer progression. CONCLUSIONS We established a predictive five-gene signature, which could be helpful for a personalized management in breast cancer patients.
Collapse
Affiliation(s)
- Xiaolong Wang
- Department of Breast Surgery, Qilu Hospital of Shandong University, Jinan, China
| | - Chen Li
- Department of Breast Surgery, Qilu Hospital of Shandong University, Jinan, China
| | - Tong Chen
- Department of Breast Surgery, Qilu Hospital of Shandong University, Jinan, China
| | - Wenhao Li
- Department of Breast Surgery, Qilu Hospital of Shandong University, Jinan, China
| | - Hanwen Zhang
- Department of Breast Surgery, Qilu Hospital of Shandong University, Jinan, China
| | - Dong Zhang
- Department of Breast Surgery, Qilu Hospital of Shandong University, Jinan, China
| | - Ying Liu
- Department of Breast Surgery, Qilu Hospital of Shandong University, Jinan, China
| | - Dianwen Han
- Department of Breast Surgery, Qilu Hospital of Shandong University, Jinan, China
| | - Yaming Li
- Department of Breast Surgery, Qilu Hospital of Shandong University, Jinan, China
| | - Zheng Li
- Department of Breast Surgery, Qilu Hospital of Shandong University, Jinan, China
| | - Dan Luo
- Department of Pathology Tissue Bank, Qilu Hospital of Shandong University, Jinan, China
| | - Ning Zhang
- Department of Breast Surgery, Qilu Hospital of Shandong University, Jinan, China
| | - Qifeng Yang
- Department of Breast Surgery, Qilu Hospital of Shandong University, Jinan, China
- Department of Pathology Tissue Bank, Qilu Hospital of Shandong University, Jinan, China
- Research Institute of Breast Cancer, Shandong University, Jinan, China
| |
Collapse
|