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Li W, Lan J, Zhou C, Yang R, Wang J, He J, Xiao B, Ou Q, Fang Y, Fan W, Lin J, Pan Z, Peng J, Wu X. Chromosomal instability is associated with prognosis and efficacy of bevacizumab after resection of colorectal cancer liver metastasis. Ann Med 2024; 56:2396559. [PMID: 39247989 PMCID: PMC11385633 DOI: 10.1080/07853890.2024.2396559] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/23/2023] [Revised: 03/18/2024] [Accepted: 04/24/2024] [Indexed: 09/10/2024] Open
Abstract
INTRODUCTION Individualized treatment of colorectal cancer liver metastases (CRLM) remains challenging due to differences in the severity of metastatic disease and tumour biology. Exploring specific prognostic risk subgroups is urgently needed. The current study aimed to investigate the prognostic value of chromosomal instability (CIN) in patients with initially resectable CRLM and the predictive value of CIN for the efficacy of bevacizumab. METHODS Ninety-one consecutive patients with initially resectable CRLM who underwent curative liver resection from 2006 to 2018 at Sun Yat-sen University Cancer Center were selected for analysis. CIN was evaluated by automated digital imaging systems. Immunohistochemistry (IHC) was performed to detect interleukin-6 (IL-6), vascular endothelial growth factor A (VEGFA) and CD31 expression in paraffin-embedded specimens. Recurrence-free survival (RFS) and overall survival (OS) were analysed using the Kaplan-Meier method and Cox regression models. RESULTS Patients with high chromosomal instability (CIN-H) had a worse 3-year RFS rate (HR, 1.953; 95% CI, 1.001-3.810; p = 0.049) and a worse 3-year OS rate (HR, 2.449; 95% CI, 1.150-5.213; p = 0.016) than those with low chromosomal instability (CIN-L). CIN-H was identified as an independent prognostic factor for RFS (HR, 2.569; 95% CI, 1.078-6.121; p = 0.033) and OS (HR, 3.852; 95% CI, 1.173-12.645; p = 0.026) in the multivariate analysis. The protein levels of IL-6, VEGFA and CD31 were upregulated in patients in the CIN-H group compared to those in the CIN-L group in both primary tumour and liver metastases tissues. Among them, 22 patients with recurrent tumours were treated with first-line bevacizumab treatment and based on the clinical response assessment, disease control rates were adversely associated with chromosomal instability (p = 0.043). CONCLUSIONS Our study showed that high chromosomal instability is a negative prognostic factor for patients with initially resectable CRLM after liver resection. CIN may have positive correlations with angiogenesis through expression of IL-6-VEGFA axis and be used as a potential predictor of efficacy of bevacizumab.
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Affiliation(s)
- Weihao Li
- Department of Colorectal Surgery, Sun Yat-Sen University Cancer Center, Guangzhou, China
| | - Jin Lan
- Department of Colorectal Surgery, Sun Yat-Sen University Cancer Center, Guangzhou, China
| | - Chi Zhou
- Department of Colorectal Surgery, Sun Yat-Sen University Cancer Center, Guangzhou, China
| | - Rong Yang
- Department of Intensive Care Unit, Sun Yat-Sen University Cancer Center, Guangzhou, China
| | - Jiayu Wang
- Department of Pathology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong, P. R. China
| | - Jiahua He
- Department of Colorectal Surgery, Sun Yat-Sen University Cancer Center, Guangzhou, China
| | - Binyi Xiao
- Department of Colorectal Surgery, Sun Yat-Sen University Cancer Center, Guangzhou, China
| | - Qingjian Ou
- Department of Colorectal Surgery, Sun Yat-Sen University Cancer Center, Guangzhou, China
| | - Yujing Fang
- Department of Colorectal Surgery, Sun Yat-Sen University Cancer Center, Guangzhou, China
| | - Wenhua Fan
- Department of Colorectal Surgery, Sun Yat-Sen University Cancer Center, Guangzhou, China
| | - Junzhong Lin
- Department of Colorectal Surgery, Sun Yat-Sen University Cancer Center, Guangzhou, China
| | - Zhizhong Pan
- Department of Colorectal Surgery, Sun Yat-Sen University Cancer Center, Guangzhou, China
| | - Jianhong Peng
- Department of Colorectal Surgery, Sun Yat-Sen University Cancer Center, Guangzhou, China
| | - Xiaojun Wu
- Department of Colorectal Surgery, Sun Yat-Sen University Cancer Center, Guangzhou, China
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Das S, Zea Rojas MP, Tran EJ. Novel insights on the positive correlation between sense and antisense pairs on gene expression. WILEY INTERDISCIPLINARY REVIEWS. RNA 2024; 15:e1864. [PMID: 39087253 DOI: 10.1002/wrna.1864] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Revised: 05/14/2024] [Accepted: 05/19/2024] [Indexed: 08/02/2024]
Abstract
A considerable proportion of the eukaryotic genome undergoes transcription, leading to the generation of noncoding RNA molecules that lack protein-coding information and are not subjected to translation. These noncoding RNAs (ncRNAs) are well recognized to have essential roles in several biological processes. Long noncoding RNAs (lncRNAs) represent the most extensive category of ncRNAs found in the human genome. Much research has focused on investigating the roles of cis-acting lncRNAs in the regulation of specific target gene expression. In the majority of instances, the regulation of sense gene expression by its corresponding antisense pair occurs in a negative (discordant) manner, resulting in the suppression of the target genes. The notion that a negative correlation exists between sense and antisense pairings is, however, not universally valid. In fact, several recent studies have reported a positive relationship between corresponding cis antisense pairs within plants, budding yeast, and mammalian cancer cells. The positive (concordant) correlation between anti-sense and sense transcripts leads to an increase in the level of the sense transcript within the same genomic loci. In addition, mechanisms such as altering chromatin structure, the formation of R loops, and the recruitment of transcription factors can either enhance transcription or stabilize sense transcripts through their antisense pairs. The primary objective of this work is to provide a comprehensive understanding of both aspects of antisense regulation, specifically focusing on the positive correlation between sense and antisense transcripts in the context of eukaryotic gene expression, including its implications towards cancer progression. This article is categorized under: RNA Processing > 3' End Processing Regulatory RNAs/RNAi/Riboswitches > Regulatory RNAs.
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Affiliation(s)
- Subhadeep Das
- Department of Biochemistry, Purdue University, West Lafayette, Indiana, USA
- Purdue University Institute for Cancer Research, Purdue University, West Lafayette, Indiana, USA
| | | | - Elizabeth J Tran
- Department of Biochemistry, Purdue University, West Lafayette, Indiana, USA
- Purdue University Institute for Cancer Research, Purdue University, West Lafayette, Indiana, USA
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Mokhtari K, Peymani M, Rashidi M, Hushmandi K, Ghaedi K, Taheriazam A, Hashemi M. Colon cancer transcriptome. PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2023; 180-181:49-82. [PMID: 37059270 DOI: 10.1016/j.pbiomolbio.2023.04.002] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/21/2023] [Revised: 03/31/2023] [Accepted: 04/06/2023] [Indexed: 04/16/2023]
Abstract
Over the last four decades, methodological innovations have continuously changed transcriptome profiling. It is now feasible to sequence and quantify the transcriptional outputs of individual cells or thousands of samples using RNA sequencing (RNA-seq). These transcriptomes serve as a connection between cellular behaviors and their underlying molecular mechanisms, such as mutations. This relationship, in the context of cancer, provides a chance to unravel tumor complexity and heterogeneity and uncover novel biomarkers or treatment options. Since colon cancer is one of the most frequent malignancies, its prognosis and diagnosis seem to be critical. The transcriptome technology is developing for an earlier and more accurate diagnosis of cancer which can provide better protectivity and prognostic utility to medical teams and patients. A transcriptome is a whole set of expressed coding and non-coding RNAs in an individual or cell population. The cancer transcriptome includes RNA-based changes. The combined genome and transcriptome of a patient may provide a comprehensive picture of their cancer, and this information is beginning to affect treatment decision-making in real-time. A full assessment of the transcriptome of colon (colorectal) cancer has been assessed in this review paper based on risk factors such as age, obesity, gender, alcohol use, race, and also different stages of cancer, as well as non-coding RNAs like circRNAs, miRNAs, lncRNAs, and siRNAs. Similarly, they have been examined independently in the transcriptome study of colon cancer.
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Affiliation(s)
- Khatere Mokhtari
- Department of Modern Biology, ACECR Institute of Higher Education (Isfahan Branch), Isfahan, Iran
| | - Maryam Peymani
- Department of Biology, Faculty of Basic Sciences, Shahrekord Branch, Islamic Azad University, Shahrekord, Iran.
| | - Mohsen Rashidi
- Department Pharmacology, Faculty of Medicine, Mazandaran University of Medical Sciences, Sari, 4815733971, Iran; The Health of Plant and Livestock Products Research Center, Mazandaran University of Medical Sciences, Sari, 4815733971, Iran
| | - Kiavash Hushmandi
- Department of Food Hygiene and Quality Control, Division of Epidemiology, Faculty of Veterinary Medicine, University of Tehran, Tehran, Iran
| | - Kamran Ghaedi
- Department of Cell and Molecular Biology and Microbiology, Faculty of Biological Science and Technology, University of Isfahan, Isfahan, Iran.
| | - Afshin Taheriazam
- Farhikhtegan Medical Convergence Sciences Research Center, Farhikhtegan Hospital Tehran Medical Sciences, Islamic Azad University, Tehran, Iran; Department of Orthopedics, Faculty of Medicine, Tehran Medical Sciences, Islamic Azad University, Tehran, Iran.
| | - Mehrdad Hashemi
- Farhikhtegan Medical Convergence Sciences Research Center, Farhikhtegan Hospital Tehran Medical Sciences, Islamic Azad University, Tehran, Iran; Department of Genetics, Faculty of Advanced Science and Technology, Tehran Medical Sciences, Islamic Azad University, Tehran, Iran.
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Sun H, Li L, Lao I, Li X, Xu B, Cao Y, Jin W. Single-cell RNA sequencing reveals cellular and molecular reprograming landscape of gliomas and lung cancer brain metastases. Clin Transl Med 2022; 12:e1101. [PMID: 36336787 PMCID: PMC9637666 DOI: 10.1002/ctm2.1101] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Revised: 10/13/2022] [Accepted: 10/14/2022] [Indexed: 11/09/2022] Open
Abstract
BACKGROUND Brain malignancies encompass gliomas and brain metastases originating from extracranial tumours including lung cancer. Approximately 50% of patients with lung adenocarcinoma (LUAD) will eventually develop brain metastases. However, the specific characteristics of gliomas and lung-to-brain metastases (LC) are largely unknown. METHODS We applied single-cell RNA sequencing to profile immune and nonimmune cells in 4 glioma and 10 LC samples. RESULTS Our analysis revealed that tumour microenvironment (TME) cells are present in heterogeneous subpopulations. LC reprogramed cells into immune suppressed state, including microglia, macrophages, endothelial cells, and CD8+ T cells, with unique cell proportions and gene signatures. Particularly, we identified that a subset of macrophages was associated with poor prognosis. ROS (reactive oxygen species)-producing neutrophils was found to participant in angiogenesis. Furthermore, endothelial cells participated in active communication with fibroblasts. Metastatic epithelial cells exhibited high heterogeneity in chromosomal instability (CIN) and cell population. CONCLUSIONS Our findings provide a comprehensive understanding of the heterogenicity of the tumor microenvironment and tumour cells and it will be crucial for successful immunotherapy development for brain metastasis of lung cancer.
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Affiliation(s)
- He‐Fen Sun
- Department of Breast SurgeryKey Laboratory of Breast Cancer in ShanghaiFudan University Shanghai Cancer CenterShanghaiChina
- Department of OncologyShanghai Medical CollegeFudan UniversityShanghaiChina
| | - Liang‐Dong Li
- Department of Breast SurgeryKey Laboratory of Breast Cancer in ShanghaiFudan University Shanghai Cancer CenterShanghaiChina
- Department of NeurosurgeryFudan University Shanghai Cancer CenterShanghaiChina
- Department of OncologyShanghai Medical CollegeFudan UniversityShanghaiChina
| | - I‐Weng Lao
- Department of PathologyFudan University Shanghai Cancer CenterShanghaiChina
- Department of OncologyShanghai Medical CollegeFudan UniversityShanghaiChina
| | - Xuan Li
- Department of Breast SurgeryKey Laboratory of Breast Cancer in ShanghaiFudan University Shanghai Cancer CenterShanghaiChina
- Department of OncologyShanghai Medical CollegeFudan UniversityShanghaiChina
| | - Bao‐Jin Xu
- Department of Breast SurgeryKey Laboratory of Breast Cancer in ShanghaiFudan University Shanghai Cancer CenterShanghaiChina
- Department of OncologyShanghai Medical CollegeFudan UniversityShanghaiChina
| | - Yi‐Qun Cao
- Department of NeurosurgeryFudan University Shanghai Cancer CenterShanghaiChina
- Department of OncologyShanghai Medical CollegeFudan UniversityShanghaiChina
| | - Wei Jin
- Department of Breast SurgeryKey Laboratory of Breast Cancer in ShanghaiFudan University Shanghai Cancer CenterShanghaiChina
- Department of OncologyShanghai Medical CollegeFudan UniversityShanghaiChina
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Guo L, Kang Y, Xia D, Ren Y, Yang X, Xiang Y, Tang L, Ren D, Yu J, Wang J, Liang T. Characterization of Immune-Based Molecular Subtypes and Prognostic Model in Prostate Adenocarcinoma. Genes (Basel) 2022; 13:1087. [PMID: 35741849 PMCID: PMC9223199 DOI: 10.3390/genes13061087] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Revised: 05/27/2022] [Accepted: 06/15/2022] [Indexed: 11/21/2022] Open
Abstract
Prostate adenocarcinoma (PRAD), also named prostate cancer, the most common visceral malignancy, is diagnosed in male individuals. Herein, in order to obtain immune-based subtypes, we performed an integrative analysis to characterize molecular subtypes based on immune-related genes, and further discuss the potential features and differences between identified subtypes. Simultaneously, we also construct an immune-based risk model to assess cancer prognosis. Our findings showed that the two subtypes, C1 and C2, could be characterized, and the two subtypes showed different characteristics that could clearly describe the heterogeneity of immune microenvironments. The C2 subtype presented a better survival rate than that in the C1 subtype. Further, we constructed an immune-based prognostic model based on four screened abnormally expressed genes, and they were selected as predictors of the robust prognostic model (AUC = 0.968). Our studies provide reference for characterization of molecular subtypes and immunotherapeutic agents against prostate cancer, and the developed robust and useful immune-based prognostic model can contribute to cancer prognosis and provide reference for the individualized treatment plan and health resource utilization. These findings further promote the development and application of precision medicine in prostate cancer.
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Affiliation(s)
- Li Guo
- Department of Bioinformatics, Smart Health Big Data Analysis and Location Services Engineering Lab of Jiangsu Province, School of Geographic and Biologic Information, Nanjing University of Posts and Telecommunications, Nanjing 210023, China; (L.G.); (Y.K.); (D.X.); (Y.R.); (X.Y.); (Y.X.); (L.T.); (D.R.)
| | - Yihao Kang
- Department of Bioinformatics, Smart Health Big Data Analysis and Location Services Engineering Lab of Jiangsu Province, School of Geographic and Biologic Information, Nanjing University of Posts and Telecommunications, Nanjing 210023, China; (L.G.); (Y.K.); (D.X.); (Y.R.); (X.Y.); (Y.X.); (L.T.); (D.R.)
| | - Daoliang Xia
- Department of Bioinformatics, Smart Health Big Data Analysis and Location Services Engineering Lab of Jiangsu Province, School of Geographic and Biologic Information, Nanjing University of Posts and Telecommunications, Nanjing 210023, China; (L.G.); (Y.K.); (D.X.); (Y.R.); (X.Y.); (Y.X.); (L.T.); (D.R.)
| | - Yujie Ren
- Department of Bioinformatics, Smart Health Big Data Analysis and Location Services Engineering Lab of Jiangsu Province, School of Geographic and Biologic Information, Nanjing University of Posts and Telecommunications, Nanjing 210023, China; (L.G.); (Y.K.); (D.X.); (Y.R.); (X.Y.); (Y.X.); (L.T.); (D.R.)
| | - Xueni Yang
- Department of Bioinformatics, Smart Health Big Data Analysis and Location Services Engineering Lab of Jiangsu Province, School of Geographic and Biologic Information, Nanjing University of Posts and Telecommunications, Nanjing 210023, China; (L.G.); (Y.K.); (D.X.); (Y.R.); (X.Y.); (Y.X.); (L.T.); (D.R.)
| | - Yangyang Xiang
- Department of Bioinformatics, Smart Health Big Data Analysis and Location Services Engineering Lab of Jiangsu Province, School of Geographic and Biologic Information, Nanjing University of Posts and Telecommunications, Nanjing 210023, China; (L.G.); (Y.K.); (D.X.); (Y.R.); (X.Y.); (Y.X.); (L.T.); (D.R.)
| | - Lihua Tang
- Department of Bioinformatics, Smart Health Big Data Analysis and Location Services Engineering Lab of Jiangsu Province, School of Geographic and Biologic Information, Nanjing University of Posts and Telecommunications, Nanjing 210023, China; (L.G.); (Y.K.); (D.X.); (Y.R.); (X.Y.); (Y.X.); (L.T.); (D.R.)
| | - Dekang Ren
- Department of Bioinformatics, Smart Health Big Data Analysis and Location Services Engineering Lab of Jiangsu Province, School of Geographic and Biologic Information, Nanjing University of Posts and Telecommunications, Nanjing 210023, China; (L.G.); (Y.K.); (D.X.); (Y.R.); (X.Y.); (Y.X.); (L.T.); (D.R.)
| | - Jiafeng Yu
- Shandong Provincial Key Laboratory of Biophysics, Institute of Biophysics, Dezhou University, Dezhou 253023, China;
| | - Jun Wang
- Department of Bioinformatics, Smart Health Big Data Analysis and Location Services Engineering Lab of Jiangsu Province, School of Geographic and Biologic Information, Nanjing University of Posts and Telecommunications, Nanjing 210023, China; (L.G.); (Y.K.); (D.X.); (Y.R.); (X.Y.); (Y.X.); (L.T.); (D.R.)
| | - Tingming Liang
- Jiangsu Key Laboratory for Molecular and Medical Biotechnology, School of Life Science, Nanjing Normal University, Nanjing 210023, China
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