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Li Q, Chu Y, Yao Y, Song Q. A Treg-related riskscore model may improve the prognosis evaluation of colorectal cancer. J Gene Med 2024; 26:e3668. [PMID: 38342959 DOI: 10.1002/jgm.3668] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Revised: 12/25/2023] [Accepted: 01/14/2024] [Indexed: 02/13/2024] Open
Abstract
BACKGROUND Colorectal cancer (CRC) poses a significant health challenge. This study aims to investigate the prognostic value of a regulatory T cell (Treg)-related gene signature in CRC. METHODS We extracted the gene expression and clinical data on CRC from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The gene module related to Treg was identified by weighted gene co-expression network analysis (WGCNA). The genes in the significant module were filtered by univariate Cox, least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analysis. A riskscore model was established in terms of the key Treg-related genes. The reliability of this riskscore model was validated using the external GEO dataset. The association of riskscore with clinical features, mutation patterns and signaling pathways was explored. RESULTS Genes in the blue module showed the strongest association with Tregs. After a series of filtering cycles, seven Treg-related key genes, GDE1, GSR, HSPB1, AOC2, TBX19, TAMM41 and TIGD6, were selected to construct a riskscore model. This model performed well in evaluating the patients' survival in TCGA cohort, and was further affirmed by the GSE17536 validation cohort. For precise evaluation of the patients' survival, we established a nomogram in light of riskscore and clinical factors. Patients in different risk groups had distinct clinical features, mutation patterns and signaling pathway activities. The expression of five key genes was significantly associated with Treg infiltration in the CRC samples. CONCLUSION We established a useful riskscore model in light of seven Treg-related genes. This model may contribute to the prognosis evaluation, direct tailored treatment, and hopefully improve clinical outcomes of the CRC patients.
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Affiliation(s)
- Qingqing Li
- Cancer Center, Renmin Hospital of Wuhan University, Wuhan, China
| | - Yuxin Chu
- Cancer Center, Renmin Hospital of Wuhan University, Wuhan, China
| | - Yi Yao
- Cancer Center, Renmin Hospital of Wuhan University, Wuhan, China
| | - Qibin Song
- Cancer Center, Renmin Hospital of Wuhan University, Wuhan, China
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Wang Y, Gao X, Wang J. Functional Proteomic Profiling Analysis in Four Major Types of Gastrointestinal Cancers. Biomolecules 2023; 13:biom13040701. [PMID: 37189448 DOI: 10.3390/biom13040701] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 04/05/2023] [Accepted: 04/18/2023] [Indexed: 05/17/2023] Open
Abstract
Gastrointestinal (GI) cancer accounts for one in four cancer cases and one in three cancer-related deaths globally. A deeper understanding of cancer development mechanisms can be applied to cancer medicine. Comprehensive sequencing applications have revealed the genomic landscapes of the common types of human cancer, and proteomics technology has identified protein targets and signalling pathways related to cancer growth and progression. This study aimed to explore the functional proteomic profiles of four major types of GI tract cancer based on The Cancer Proteome Atlas (TCPA). We provided an overview of functional proteomic heterogeneity by performing several approaches, including principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), t-stochastic neighbour embedding (t-SNE) analysis, and hierarchical clustering analysis in oesophageal carcinoma (ESCA), stomach adenocarcinoma (STAD), colon adenocarcinoma (COAD), and rectum adenocarcinoma (READ) tumours, to gain a system-wide understanding of the four types of GI cancer. The feature selection approach, mutual information feature selection (MIFS) method, was conducted to screen candidate protein signature subsets to better distinguish different cancer types. The potential clinical implications of candidate proteins in terms of tumour progression and prognosis were also evaluated based on TCPA and The Cancer Genome Atlas (TCGA) databases. The results suggested that functional proteomic profiling can identify different patterns among the four types of GI cancers and provide candidate proteins for clinical diagnosis and prognosis evaluation. We also highlighted the application of feature selection approaches in high-dimensional biological data analysis. Overall, this study could improve the understanding of the complexity of cancer phenotypes and genotypes and thus be applied to cancer medicine.
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Affiliation(s)
- Yangyang Wang
- School of Electronics and Information, Northwestern Polytechnical University, Xi'an 710129, China
| | - Xiaoguang Gao
- School of Electronics and Information, Northwestern Polytechnical University, Xi'an 710129, China
| | - Jihan Wang
- Institute of Medical Research, Northwestern Polytechnical University, Xi'an 710072, China
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Atreya I, Neurath MF. How the Tumor Micromilieu Modulates the Recruitment and Activation of Colorectal Cancer-Infiltrating Lymphocytes. Biomedicines 2022; 10:biomedicines10112940. [PMID: 36428508 PMCID: PMC9687992 DOI: 10.3390/biomedicines10112940] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2022] [Revised: 11/10/2022] [Accepted: 11/11/2022] [Indexed: 11/17/2022] Open
Abstract
The successful treatment of advanced colorectal cancer disease still represents an insufficiently solved clinical challenge, which is further complicated by the fact that the majority of malignant colon tumors show only relatively low immunogenicity and therefore have only limited responsiveness to immunotherapeutic approaches, such as, for instance, the use of checkpoint inhibitors. As it has been well established over the past two decades that the local tumor microenvironment and, in particular, the quantity, quality, and activation status of intratumoral immune cells critically influence the clinical prognosis of patients diagnosed with colorectal cancer and their individual benefits from immunotherapy, the enhancement of the intratumoral accumulation of cytolytic effector T lymphocytes and other cellular mediators of the antitumor immune response has emerged as a targeted objective. For the future identification and clinical validation of novel therapeutic target structures, it will thus be essential to further decipher the molecular mechanisms and cellular interactions in the intestinal tumor microenvironment, which are crucially involved in immune cell recruitment and activation. In this context, our review article aims at providing an overview of the key chemokines and cytokines whose presence in the tumor micromilieu relevantly modulates the numeric composition and antitumor capacity of tumor-infiltrating lymphocytes.
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Affiliation(s)
- Imke Atreya
- Department of Medicine 1, Erlangen University Hospital, Friedrich-Alexander-University Erlangen-Nürnberg, 91054 Erlangen, Germany
- Deutsches Zentrum Immuntherapie (DZI), Erlangen University Hospital, Friedrich-Alexander-University Erlangen-Nürnberg, 91054 Erlangen, Germany
| | - Markus F. Neurath
- Department of Medicine 1, Erlangen University Hospital, Friedrich-Alexander-University Erlangen-Nürnberg, 91054 Erlangen, Germany
- Deutsches Zentrum Immuntherapie (DZI), Erlangen University Hospital, Friedrich-Alexander-University Erlangen-Nürnberg, 91054 Erlangen, Germany
- Correspondence: ; Tel.: +49-9131-8535204; Fax: +49-9131-8535209
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Yang J, Zhang J, Na S, Wang Z, Li H, Su Y, Ji L, Tang X, Yang J, Xu L. Integration of single-cell RNA sequencing and bulk RNA sequencing to reveal an immunogenic cell death-related 5-gene panel as a prognostic model for osteosarcoma. Front Immunol 2022; 13:994034. [PMID: 36225939 PMCID: PMC9549151 DOI: 10.3389/fimmu.2022.994034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Accepted: 09/05/2022] [Indexed: 11/13/2022] Open
Abstract
BackgroundDespite the comparatively low prevalence of osteosarcoma (OS) compared to other cancer types, metastatic OS has a poor overall survival rate of fewer than 30%. Accumulating data has shown the crucial functions of immunogenic cell death (ICD) in various cancers; nevertheless, the relationship between ICD and OS was not previously well understood. This research aims to determine the function of ICD in OS and construct an ICD-based prognostic panel.MethodsSingle cell RNA sequencing data from GSE162454 dataset distinguished malignant cells from normal cells in OS. The discrepancy in ICD scores and corresponding gene expression was intensively explored between malignant cells and normal cells. Using the RNA sequencing data of the TARGET-OS, GSE16091, GSE21257, and GSE39058 datasets, the molecular subtype of OS was determined by clustering seventeen ICD-related genes obtained from the literature. Differentially expressed genes (DEGs) between different molecular subtypes were identified to develop a novel ICD-associated prognostic panel.ResultsThe malignant cells had a remarkable decrease in the ICD scores and corresponding gene expression compared with normal cells. A total of 212 OS patients were successfully stratified into two subtypes: C1 and C2. C1-like OS patients were characterized by better prognostic outcomes, overexpression of ICD genes, activation of the ICD pathway, high inflitration abundance of immunocytes, and low expression levels of immune checkpoint genes (ICGs); however, the reverse is true in C2-like OS patients. Utilizing the limma programme in R, the DEGs between two subtypes were determined, and a 5-gene risk panel consisting of BAMBI, TMCC2, NOX4, DKK1, and CBS was developed through LASSO-Cox regression analysis. The internal- and external-verification cohorts were employed to verify the efficacy and precision of the risk panel. The AUC values of ROC curves indicated excellent prognostic prediction values of our risk panel.ConclusionsOverall, ICD represented a protective factor against OS, and our 5-gene risk panel serving as a biomarker could effectively evaluate the prognostic risk in patients with OS.
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Affiliation(s)
- Jiaqi Yang
- Department of Dermatology, Second Affiliated Hospital of Dalian Medical University, Dalian, China
- Department of Orthopedics, First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Jian Zhang
- Department of Orthopedics, First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Song Na
- Emergency Intensive Care Unit, Affiliated Zhongshan Hospital of Dalian University, Dalian, China
| | - Zhizhou Wang
- Department of General Surgery, First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Hanshuo Li
- Department of General Surgery, First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Yuxin Su
- Cardiovascular Research Institute of Northern Theater Command General Hospital, Shenyang, China
| | - Li Ji
- Department of Gastroenterology, DongZhiMen Hospital, Beijing University of Chinese Medicine, Beijing, China
| | - Xin Tang
- Department of Orthopedics, First Affiliated Hospital of Dalian Medical University, Dalian, China
- *Correspondence: Lu Xu, ; Xin Tang, ; Jun Yang,
| | - Jun Yang
- Department of Orthopedics, First Affiliated Hospital of Dalian Medical University, Dalian, China
- *Correspondence: Lu Xu, ; Xin Tang, ; Jun Yang,
| | - Lu Xu
- Department of Dermatology, Second Affiliated Hospital of Dalian Medical University, Dalian, China
- Institute of Cancer Stem Cell, Dalian Medical University, Dalian, China
- *Correspondence: Lu Xu, ; Xin Tang, ; Jun Yang,
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Novel Prognosis and Therapeutic Response Model of Immune-Related lncRNA Pairs in Clear Cell Renal Cell Carcinoma. Vaccines (Basel) 2022; 10:vaccines10071161. [PMID: 35891325 PMCID: PMC9325030 DOI: 10.3390/vaccines10071161] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Revised: 07/11/2022] [Accepted: 07/15/2022] [Indexed: 01/13/2023] Open
Abstract
Clear cell renal cell carcinoma (ccRCC) is the most common type of renal carcinoma. It is particularly important to accurately judge the prognosis of patients. Since most tumor prediction models depend on the specific expression level of related genes, a better model therefore needs to be constructed. To provide an immune-related lncRNA (irlncRNAs) tumor prognosis model that is independent of the specific gene expression levels, we first downloaded and sorted out the data on ccRCC in the TCGA database and screened irlncRNAs using co-expression analysis and then obtained the differently expressed irlncRNA (DEirlncRNA) pairs by means of univariate analysis. In addition, we modified LASSO penalized regression. Subsequently, the ROC curve was drawn, and we compared the area under the curve, calculated the Akaike information standard value of the 5-year receiver operating characteristic curve, and determined the cut-off point to establish the best model to distinguish the high- or low-disease-risk group of ccRCC. Subsequently, we reassessed the model from the perspectives of survival, clinic-pathological characteristics, tumor-infiltrating immune cells, chemotherapeutics efficacy, and immunosuppressed biomarkers. A total of 17 DEirlncRNAs pairs (AL031710.1|AC104984.5, AC020907.4|AC127-24.4,AC091185.1|AC005104.1, AL513218.1|AC079015.1, AC104564.3|HOXB-AS3, AC003070.1|LINC01355, SEMA6A-AS1|CR936218.1, AL513327.1|AS005785.1, AC084876.1|AC009704.2, IGFL2-AS1|PRDM16-DT, AC011462.4|MMP25-AS1, AL662844.3I|TGB2-AS1, ARHGAP27P1|AC116914.2, AC093788.1|AC007098.1, MCF2L-AS1|AC093001.1, SMIM25|AC008870.2, and AC027796.4|LINC00893) were identified, all of which were included in the Cox regression model. Using the cut-off point, we can better distinguish patients according to different factors, such as survival status, invasive clinic-pathological features, tumor immune infiltration, whether they are sensitive to chemotherapy or not, and expression of immunosuppressive biomarkers. We constructed the irlncRNA model by means of pairing, which can better eliminate the dependence on the expression level of the target genes. In other words, the signature established by pairing irlncRNA regardless of expression levels showed promising clinical prediction value.
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The Expression of PPAR Pathway-Related Genes Can Better Predict the Prognosis of Patients with Colon Adenocarcinoma. PPAR Res 2022; 2022:1285083. [PMID: 35481240 PMCID: PMC9038426 DOI: 10.1155/2022/1285083] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Revised: 03/24/2022] [Accepted: 03/26/2022] [Indexed: 12/03/2022] Open
Abstract
The postoperative survival time and quality of life of patients with colon adenocarcinoma (COAD) varies widely. In order to make accurate decisions after surgery, clinicians need to distinguish patients with different prognostic trends. However, we still lack effective methods to predict the prognosis of COAD patients. Accumulated evidences indicated that the inhibition of peroxisome proliferator-activated receptors (PPARs) and a portion of their target genes were associated with the development of COAD. Our study found that the expression of several PPAR pathway-related genes were linked to the prognosis of COAD patients. Therefore, we developed a scoring system (named PPAR-Riskscore) that can predict patients' outcomes. PPAR-Riskscore was constructed by univariate Cox regression based on the expression of 4 genes (NR1D1, ILK, TNFRSF1A, and REN) in tumor tissues. Compared to typical TNM grading systems, PPAR-Riskscore has better predictive accuracy and sensitivity. The reliability of the system was tested on six external validation datasets. Furthermore, PPAR-Riskscore was able to evaluate the immune cell infiltration and chemotherapy sensitivity of each tumor sample. We also combined PPAR-Riskscore and clinical features to create a nomogram with greater clinical utility. The nomogram can help clinicians make precise treatment decisions regarding the possible long-term survival of patients after surgery.
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Jiang Y, Xi Y, Li Y, Zuo Z, Zeng C, Fan J, Zhang D, Tao H, Guo Y. Ethanol promoting the upregulation of C-X-C Motif Chemokine Ligand 1(CXCL1) and C-X-C Motif Chemokine Ligand 6(CXCL6) in models of early alcoholic liver disease. Bioengineered 2022; 13:4688-4701. [PMID: 35156518 PMCID: PMC8973977 DOI: 10.1080/21655979.2022.2030557] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
Alcoholic liver disease (ALD) denotes a series of liver diseases caused by ethanol. Recently, immune-related genes (IRGs) play increasingly crucial role in diseases. However, it’s unclear the role of IRGs in ALD. Bioinformatic analysis was used to discern the core immune-related differential genes (IRDGs) in the present study. Subsequently, Cell Counting Kit-8 say, oil red O staining, and triglyceride detection were employed to explore optimal experimental conditions of establishing hepatocellular models of early ALD. Ultimately, real-time reverse transcription-PCR and immunohistochemistry/immunocytochemistry methods were adopted to verify the expressions of mRNA and proteins of core IRDGs, respectively. C-X-C Motif Chemokine Ligand 1 (Cxcl1) and Cxcl6 were regarded as core IRDGs via integrated bioinformatics analysis. Besides, Lieber Decarli Ethanol feeding and 200 mM and 300 mM ethanol stimulating L02 cells for 36 h can both successfully hepatocellular model. In ethanol groups, the levels of CXCL1 and CXCL6 mRNA were significantly upregulated than pair-fed groups (P < 0.0001). Also, immunohistochemistry revealed that positive particles of CXCL1 and CXCL6 in mice model of early ALD were obviously more than control groups (P < 0.0001). Besides, in L02 hepatocytes stimulated by ethanol, CXCL1 and CXCL6 mRNA were over-expressed, compared with normal L02 cells (P < 0.0001). Meanwhile, immunocytochemistry indicated that CXCL1 and CXCL6 proteins in hepatocellular model of early ALD were higher than normal L02 hepatocytes stimulus (P < 0.0001). Ethanol promoted the upregulation of Cxcl1 and Cxcl6 mRNA and proteins in models of early ALD, denoting their potentiality of acting as biomarkers of ALD.
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Affiliation(s)
- Yao Jiang
- Clinical Laboratory, The Affiliated Traditional Chinese Medicine Hospital of Southwest Medical University, Luzhou, China
| | - Yuge Xi
- Clinical Laboratory, The Affiliated Traditional Chinese Medicine Hospital of Southwest Medical University, Luzhou, China
| | - Yiqin Li
- Clinical Laboratory, The Affiliated Traditional Chinese Medicine Hospital of Southwest Medical University, Luzhou, China
| | - Zhihua Zuo
- Department of Clinical Laboratory Medicine, The Affiliated Hospital of Southwest Medical University, Luzhou, China
| | - Chuyi Zeng
- Department of Clinical Laboratory Medicine, The Affiliated Hospital of Southwest Medical University, Luzhou, China
| | - Jia Fan
- Clinical Laboratory, The Affiliated Traditional Chinese Medicine Hospital of Southwest Medical University, Luzhou, China
| | - Dan Zhang
- Clinical Laboratory, The Affiliated Traditional Chinese Medicine Hospital of Southwest Medical University, Luzhou, China
| | - Hualin Tao
- Department of Clinical Laboratory Medicine, The Affiliated Hospital of Southwest Medical University, Luzhou, China
| | - Yongcan Guo
- Clinical Laboratory, The Affiliated Traditional Chinese Medicine Hospital of Southwest Medical University, Luzhou, China
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Zhang ZC, Guo JN, Zhang N, Wang ZQ, Lou G, Cui BB, Yang C. Identification and Validation of Immune-Related Gene for Predicting Prognosis and Therapeutic Response in Ovarian Cancer. Front Immunol 2021; 12:763791. [PMID: 34880862 PMCID: PMC8645858 DOI: 10.3389/fimmu.2021.763791] [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: 08/24/2021] [Accepted: 11/01/2021] [Indexed: 11/13/2022] Open
Abstract
Ovarian cancer (OC) is a devastating malignancy with a poor prognosis. The complex tumor immune microenvironment results in only a small number of patients benefiting from immunotherapy. To explore the different factors that lead to immune invasion and determine prognosis and response to immune checkpoint inhibitors (ICIs), we established a prognostic risk scoring model (PRSM) with differential expression of immune-related genes (IRGs) to identify key prognostic IRGs. Patients were divided into high-risk and low-risk groups according to their immune and stromal scores. We used a bioinformatics method to identify four key IRGs that had differences in expression between the two groups and affected prognosis. We evaluated the sensitivity of treatment from three aspects, namely chemotherapy, targeted inhibitors (TIs), and immunotherapy, to evaluate the value of prediction models and key prognostic IRGs in the clinical treatment of OC. Univariate and multivariate Cox regression analyses revealed that these four key IRGs were independent prognostic factors of overall survival in OC patients. In the high-risk group comprising four genes, macrophage M0 cells, macrophage M2 cells, and regulatory T cells, observed to be associated with poor overall survival in our study, were higher. The high-risk group had a high immunophenoscore, indicating a better response to ICIs. Taken together, we constructed a PRSM and identified four key prognostic IRGs for predicting survival and response to ICIs. Finally, the expression of these key genes in OC was evaluated using RT-qPCR. Thus, these genes provide a novel predictive biomarker for immunotherapy and immunomodulation.
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Affiliation(s)
- Zhao-Cong Zhang
- Department of Gynecology Oncology, Harbin Medical University Cancer Hospital, Harbin, China
| | - Jun-Nan Guo
- Department of Colorectal Surgery, Harbin Medical University Cancer Hospital, Harbin, China
| | - Ning Zhang
- Department of Gynecology Oncology, Harbin Medical University Cancer Hospital, Harbin, China
| | - Zhi-Qiang Wang
- Department of Gynecology Oncology, Harbin Medical University Cancer Hospital, Harbin, China
| | - Ge Lou
- Department of Gynecology Oncology, Harbin Medical University Cancer Hospital, Harbin, China
| | - Bin-Bin Cui
- Department of Colorectal Surgery, Harbin Medical University Cancer Hospital, Harbin, China
| | - Chang Yang
- Department of Gynecology Oncology, Harbin Medical University Cancer Hospital, Harbin, China
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Acikgoz O, Cakan B, Demir T, Bilici A, Oven BB, Hamdard J, Olmuscelik O, Olmez OF, Seker M, Yildiz O. Platelet to lymphocyte ratio is associated with tumor localization and outcomes in metastatic colorectal cancer. Medicine (Baltimore) 2021; 100:e27712. [PMID: 34871263 PMCID: PMC8568374 DOI: 10.1097/md.0000000000027712] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/24/2021] [Accepted: 10/19/2021] [Indexed: 01/05/2023] Open
Abstract
The aim of this study was to investigate the predictive and prognostic value of PLR, and the relationship between PLR and tumor localization.A total of 229 patients with de-novo metastatic CRC were retrospectively analyzed. The cutoff value for PLR was defined by the receiver operating characteristic (ROC) curve analysis and threshold value of 196.5 as best cut-off value was found.The higher rate of BRAF mutation was significantly detected for patients with PLRhigh (> 196.5) compared to those with PLRlow (≤196.5) (P = .001). PLR was significantly higher in tumors located on the right colon (P = .012). PLR, tumor localization, the presence of surgery for primary tumor, the presence of curative surgery, the presence of metastasectomy for progression-free survival (PFS) and PLR, gender, BRAF mutation, tumor localization, the presence of surgery for primary tumor, the presence of metastasectomy for overall survival (OS) were found to be prognostic factors by univariate analysis. Multivariate analysis showed that PLR, the presence of curative surgery and the presence of metastasectomy for both PFS and OS were found to be independent prognostic factors. Moreover, a logistic regression analysis indicated that PLR and tumor localization were found to be an independent factors for predicting response to systemic treatment (P < .001 and P = .023 respectively).Our results showed that pretreatment PLR was readily feasible and simple biomarker predicting response to treatment and survival, in addition it was significantly associated with tumor localization.
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Affiliation(s)
- Ozgur Acikgoz
- Department of Medical Oncology, Istanbul Medipol University School of Medicine, Istanbul, Turkey
| | - Burcin Cakan
- Department of Medical Oncology, Denizli Pamukkale University School of Medicine, Denizli, Turkey
| | - Tarik Demir
- Department of Medical Oncology, Istanbul Bezmialem Vakif University School of Medicine, Istanbul, Turkey
| | - Ahmet Bilici
- Department of Medical Oncology, Istanbul Medipol University School of Medicine, Istanbul, Turkey
| | - Bala Basak Oven
- Department of Medical Oncology, Istanbul Bahcesehir University School of Medicine, Istanbul, Turkey
| | - Jamshid Hamdard
- Department of Medical Oncology, Istanbul Medipol University School of Medicine, Istanbul, Turkey
| | - Oktay Olmuscelik
- Department of Medical Oncology, Istanbul Medipol University School of Medicine, Istanbul, Turkey
| | - Omer Fatih Olmez
- Department of Medical Oncology, Istanbul Medipol University School of Medicine, Istanbul, Turkey
| | - Mesut Seker
- Department of Medical Oncology, Istanbul Bezmialem Vakif University School of Medicine, Istanbul, Turkey
| | - Ozcan Yildiz
- Department of Medical Oncology, Istanbul Medipol University School of Medicine, Istanbul, Turkey
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Guo JN, Chen D, Deng SH, Huang JR, Song JX, Li XY, Cui BB, Liu YL. Identification and quantification of immune infiltration landscape on therapy and prognosis in left- and right-sided colon cancer. Cancer Immunol Immunother 2021; 71:1313-1330. [PMID: 34657172 PMCID: PMC9122887 DOI: 10.1007/s00262-021-03076-2] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Accepted: 09/30/2021] [Indexed: 01/22/2023]
Abstract
Background The left-sided and right-sided colon cancer (LCCs and RCCs, respectively) have unique molecular features and clinical heterogeneity. This study aimed to identify the characteristics of immune cell infiltration (ICI) subtypes for evaluating prognosis and therapeutic benefits. Methods The independent gene datasets, corresponding somatic mutation and clinical information were collected from The Cancer Genome Atlas and Gene Expression Omnibus. The ICI contents were evaluated by “ESTIMATE” and “CIBERSORT.” We performed two computational algorithms to identify the ICI landscape related to prognosis and found the unique infiltration characteristics. Next, principal component analysis was conducted to construct ICI score based on three ICI patterns. We analyzed the correlation between ICI score and tumor mutation burden (TMB), and stratified patients into prognostic-related high- and low- ICI score groups (HSG and LSG, respectively). The role of ICI scores in the prediction of therapeutic benefits was investigated by "pRRophetic" and verified by Immunophenoscores (IPS) (TCIA database) and an independent immunotherapy cohort (IMvigor210). The key genes were preliminary screened by weighted gene co-expression network analysis based on ICI scores. And they were further identified at various levels, including single cell, protein and immunotherapy response. The predictive ability of ICI score for prognosis was also verified in IMvigor210 cohort. Results The ICI features with a better prognosis were marked by high plasma cells, dendritic cells and mast cells, low memory CD4+ T cells, M0 macrophages, M1 macrophages, as well as M2 macrophages. A high ICI score was characterized by an increased TMB and genomic instability related signaling pathways. The prognosis, sensitivities of targeted inhibitors and immunotherapy, IPS and expression of immune checkpoints were significantly different in HSG and LSG. The genes identified by ICI scores and various levels included CA2 and TSPAN1. Conclusion The identification of ICI subtypes and ICI scores will help gain insights into the heterogeneity in LCC and RCC, and identify patients probably benefiting from treatments. ICI scores and the key genes could serve as an effective biomarker to predict prognosis and the sensitivity of immunotherapy. Supplementary Information The online version contains supplementary material available at 10.1007/s00262-021-03076-2.
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Affiliation(s)
- Jun-Nan Guo
- Department of Colorectal Surgery, Harbin Medical University Cancer Hospital, Harbin, 150086, People's Republic of China
| | - Du Chen
- The First Department of Oncological Surgery, The First People's Hospital of Xiangtan City, Xiangtan, 411100, People's Republic of China
| | - Shen-Hui Deng
- Department of Anesthesiology, The Fourth Affiliated Hospital of Harbin Medical University, Harbin, 150086, People's Republic of China
| | - Jia-Rong Huang
- Department of Clinical Medicine, North Sichuan Medical College, Nanchong, 637000, People's Republic of China
| | - Jin-Xuan Song
- Department of Clinical Medicine, North Sichuan Medical College, Nanchong, 637000, People's Republic of China
| | - Xiang-Yu Li
- Department of Clinical Medicine, North Sichuan Medical College, Nanchong, 637000, People's Republic of China
| | - Bin-Bin Cui
- Department of Colorectal Surgery, Harbin Medical University Cancer Hospital, Harbin, 150086, People's Republic of China.
| | - Yan-Long Liu
- Department of Colorectal Surgery, Harbin Medical University Cancer Hospital, Harbin, 150086, People's Republic of China.
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