scholarly journals ADAM12 as a Clinical Prognostic Indicator Associated with Tumour Immune Infiltration in Lung Adenocarcinoma

2021 ◽  
Author(s):  
Junfan Pan ◽  
Zhidong Huang ◽  
Yiquan Xu
Keyword(s):  
Lung Adenocarcinoma ◽  
Prognostic Model ◽  
Immune Cell ◽  
Genetic Alterations ◽  
The Cancer Genome Atlas ◽  
Migration And Invasion ◽  
Receptor Interaction ◽  
Significant Differential Expression ◽  
Immune Related Genes

Abstract Background: Lung cancer is the most common cause of cancer-related death worldwide. In humans, 22 functional α-disintegrinand metalloproteinases (ADAMs) have been identified, 12 of which have proteolytic activity. The role of ADAMs in cancer has attracted increasing attention. However, the expression and significance of ADAMs in lung adenocarcinoma (LUAD) remain unclear. The current study aimed to explore the expression and prognostic value of ADAM12 in LUAD.Methods: The Cancer Genome Atlas(TCGA) database was used to analyse the expression of ADAMs in LUAD. The cBioPortal database was used to obtain and analyse ADAM12 copy number changes, and the LinkedOmics database was utilised for the analysis of ADAM12-related genes. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was then performed using TIMER. The relationship between ADAM12 and the tumour immune microenvironment(TIM) was assessed via the TISIDB database. ADAM12 and immune-related genes were used to construct a prognostic model. Knockdown of ADAM12 was performed in vitro in order to verify its biological function. The unpaired t-test was used for comparison between the two groups, ANOVA was used for analysing differences between multiple groups, and the Kaplan-Meier test was used to compare survival between groups.Results: Most ADAMs exhibited significant differential expression in LUAD. ADAM12 expression was significantly higher in LUAD tissues than in healthy tissues, and lower ADAM12 expression was associated with better survival. Genetic alterations of ADAM12 mainly included missense mutations, amplifications, and deep deletions. ADAM12 and positively correlated genes were mainly enriched in protein digestion and absorption, ECM-receptor interaction, and adhesion plaques. ADAM12 had a moderate correlation with immune cell markers EBIP1, CCNB1, EXO1, KNTC1, PRC1 and FAM198B. Prognostic model was established based on ADAM12 and immune-related genes. In vitro experiments revealed that knocking down ADAM12 inhibited cell proliferation, migration and invasion.Conclusion: ADAM12 potentially plays an important role in the occurrence of LUAD and may be utilised as an immunotherapy target and a valuable prognostic biomarker for LUAD.

scholarly journals ADAM12 as a Clinical Prognostic Indicator Associated with Tumour Immune Infiltration in Lung Adenocarcinoma

2021 ◽  
Author(s):  
Junfan Pan ◽  
Zhidong Huang ◽  
Yiquan Xu
Keyword(s):  
Lung Adenocarcinoma ◽  
Prognostic Model ◽  
Immune Cell ◽  
Genetic Alterations ◽  
The Cancer Genome Atlas ◽  
Migration And Invasion ◽  
Receptor Interaction ◽  
Significant Differential Expression ◽  
Immune Related Genes

Abstract Background: Lung cancer is the most common cause of cancer-related death worldwide. In humans, 22 functional α-disintegrin and metalloproteinases (ADAMs) have been identified, 12 of which have proteolytic activity. The role of ADAMs in cancer has attracted increasing attention. However, the expression and significance of ADAMs in lung adenocarcinoma (LUAD) remain unclear. The current study aimed to explore the expression and prognostic value of ADAM12in LUAD.Methods: The Cancer Genome Atlas(TCGA) database was used to analyse the expression of ADAMs in LUAD. The cBioPortal database was used to obtain and analyse ADAM12 copy number changes, and the LinkedOmics database was utilised for the analysis of ADAM12-related genes. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was then performed using TIMER. The relationship between ADAM12 and the tumour immune microenvironment(TIM) was assessed via the TISIDB database. ADAM12 and immune-related genes were used to construct a prognostic model. Knockdown of ADAM12 was performed in vitro in order to verify its biological function. The unpaired t-test was used for comparison between the two groups, ANOVA was used for analysing differences between multiple groups, and the Kaplan-Meier test was used to compare survival between groups.Results: Most ADAMs exhibited significant differential expression in LUAD. ADAM12 expression was significantly higher in LUAD tissues than in healthy tissues, and lower ADAM12 expression was associated with better survival. Genetic alterations of ADAM12 mainly included missense mutations, amplifications, and deep deletions. ADAM12 and positively correlated genes were mainly enriched in protein digestion and absorption, ECM-receptor interaction, and adhesion plaques. ADAM12 had a moderate correlation with immune cell markers EBIP1, CCNB1, EXO1, KNTC1, PRC1 and FAM198B. Prognostic model was established based on ADAM12 and immune-related genes. In vitro experiments revealed that knocking down ADAM12 inhibited cell proliferation, migration and invasion.Conclusion: ADAM12 potentially plays an important role in the occurrence of LUAD and may be utilised as an immunotherapy target and a valuable prognostic biomarker for LUAD.

scholarly journals Effect of LAMA4 on Prognosis and Its Correlation with Immune Infiltration in Gastric Cancer

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Mingming Wang ◽  
Changzheng Li ◽  
Ying Liu ◽  
Zuomin Wang
Keyword(s):  
Gene Expression ◽  
Gastric Cancer ◽  
Immune Cell ◽  
Expression Patterns ◽  
Disease Free Survival ◽  
Genetic Alterations ◽  
Clinicopathological Characteristics ◽  
Basement Membranes ◽  
The Cancer Genome Atlas ◽  
Receptor Interaction

Background. Laminin alpha 4 (LAMA4) is widely distributed in the basement membranes of various tissues. It can regulate cancer cell proliferation and migration. We investigated the effects of LAMA4 in gastric cancer (GC). Methods. LAMA4 expression patterns were analyzed in GC using the Gene Expression Omnibus (GEO), Gene Expression Profiling Interactive Analysis (GEPIA), and UALCAN. Correlations between LAMA4 expression and clinicopathological characteristics were evaluated using data from The Cancer Genome Atlas (TCGA). The survival analysis was examined using the Kaplan-Meier plotter and GEPIA and ascertained by multivariate Cox analysis. Genetic alterations and DNA methylation of LAMA4 were analyzed using cBioPortal and MethSurv. LinkedOmics was applied to identify coexpressed genes of LAMA4. The association between LAMA4 and infiltration of immune cells was explored using Tumor Immune Estimation Resource (TIMER) and GEPIA. Results. LAMA4 was highly expressed in GC, and its upregulation significantly correlated with T classification ( P = 0.040 ). LAMA4 expression was an independent risk factor for overall survival (OS, P = 0.033 ). Patients with genetic alterations of LAMA4 showed a significantly better disease-free survival (DFS, P = 0.022 ). Ten CpG sites of LAMA4 were significantly associated with prognosis in GC. The functions of LAMA4 and coexpression genes were mainly involved in extracellular matrix (ECM) receptor interaction. LAMA4 expression significantly correlated with infiltration of macrophages ( P < 0.001 ), CD4+ T cells ( P < 0.001 ), and dendritic cells ( P < 0.001 ). Furthermore, LAMA4 expression was significantly associated with markers of M2 and tumor-associated macrophages (TAMs). Conclusion. LAMA4 expression was linked to GC prognosis and immune cell infiltration, indicating its potential use as a prognostic biomarker and therapeutic target.

scholarly journals Development of a prognostic signature for esophageal cancer based on nine immune related genes

2020 ◽  
Author(s):  
zhi Zhang ◽  
cheng chen ◽  
ying fang ◽  
sheng Li ◽  
xiaohua Wang ◽  
...  
Keyword(s):  
T Cells ◽  
Esophageal Cancer ◽  
Prognostic Model ◽  
Cox Regression ◽  
Risk Group ◽  
The Cancer Genome Atlas ◽  
Receptor Interaction ◽  
Prognostic Signature ◽  
Cox Regression Analysis ◽  
Immune Related Genes

Abstract Background: Function of the immune system is correlated with the prognosis of the tumor. The effect of immune microenvironment on esophageal cancer (EC) development has not been fully investigated. Methods: This study aimed to explore a prognostic model based on immune-related genes (IRGs) for EC. We obtained the RNA-seq dataset and clinical information of EC from the Cancer Genome Atlas (TCGA). Results: We identified 247 upregulated IRGs and 56 downregulated IRGs. Pathway analysis revealed that the most differentially expressed IRGs were enriched in Cytokine-cytokine receptor interaction. We further screened 13 survival-related IRGs and constructed regulatory networks involving related transcription factors (TFs). Finally, a prognostic model was constructed with 9 IRGs (HSPA6, S100A12, CACYBP, NOS2, DKK1, OSM ,STC2 ,NGPTL3 and NR2F2) by multivariate Cox regression analysis. The patients were classified into two subgroups with different outcomes. When adjusted with clinical factors, this model was verified as an independent predictor, which performed accurately in prognostic prediction. Next, M0 and M2 macrophages and activated mast cells were significantly enriched in high-risk group, while CD8 T cells and regulatory T cells (Tregs) were significantly enriched in low-risk group. Conclusions: Prognosis related IRGs were identified and a prognostic signature for esophageal cancer based on nine IRGs was developed.

scholarly journals Development of a prognostic model for esophageal cancer based on nine immune related genes

2020 ◽  
Author(s):  
Zhi Zhang ◽  
Cheng Chen ◽  
Ying Fang ◽  
Sheng Li ◽  
Xiaohua Wang ◽  
...  
Keyword(s):  
T Cells ◽  
Esophageal Cancer ◽  
Regulatory Networks ◽  
Prognostic Model ◽  
Cox Regression ◽  
Risk Group ◽  
The Cancer Genome Atlas ◽  
Receptor Interaction ◽  
Cox Regression Analysis ◽  
Immune Related Genes

Abstract Background: Function of the immune system is correlated with the prognosis of the tumor. The effect of immune microenvironment on esophageal cancer (EC) development has not been fully investigated. Methods: This study aimed to explore a prognostic model based on immune-related genes (IRGs) for EC. We obtained the RNA-seq dataset and clinical information of EC from the Cancer Genome Atlas (TCGA). Results: We identified 247 upregulated IRGs and 56 downregulated IRGs. Pathway analysis revealed that the most differentially expressed IRGs were enriched in Cytokine-cytokine receptor interaction. We further screened 13 survival-related IRGs and constructed regulatory networks involving related transcription factors (TFs). Finally, a prognostic model was constructed with 9 IRGs (HSPA6, S100A12, CACYBP, NOS2, DKK1, OSM ,STC2 ,NGPTL3 and NR2F2) by multivariate Cox regression analysis. The patients were classified into two subgroups with different outcomes. When adjusted with clinical factors, this model was verified as an independent predictor, which performed accurately in prognostic prediction. Next, M0 and M2 macrophages and activated mast cells were significantly enriched in high-risk group, while CD8 T cells and regulatory T cells (Tregs) were significantly enriched in low-risk group. Conclusions: These molecules may serve as potential therapeutic targets and biomarkers for the new-immunotherapy of EC.

scholarly journals ESCO2 promotes lung adenocarcinoma progression by regulating hnRNPA1 acetylation

2020 ◽  
Author(s):  
Hui-er Zhu ◽  
Tao Li ◽  
Shengnan Shi ◽  
De-xiong Chen ◽  
Weiping Chen ◽  
...  
Keyword(s):  
Cell Proliferation ◽  
Lung Adenocarcinoma ◽  
Nuclear Translocation ◽  
Lactate Production ◽  
Gene Set Enrichment Analysis ◽  
Metabolic Reprogramming ◽  
The Cancer Genome Atlas ◽  
Migration And Invasion

Abstract Background: Emerging evidence indicates that metabolism reprogramming and abnormal acetylation modification play an important role in lung adenocarcinoma (LUAD) progression, although the mechanism is largely unknown. Methods: Here, we used three public databases (Oncomine, Gene Expression Omnibus [GEO], The Cancer Genome Atlas [TCGA]) to analyze ESCO2 (establishment of cohesion 1 homolog 2) expression in LUAD. The biological function of ESCO2 was studied using cell proliferation, colony formation, cell migration, and invasion assays in vitro, and mouse xenograft models in vivo. ESCO2 interacting proteins were searched using gene set enrichment analysis (GSEA) and mass spectrometry. Pyruvate kinase M1/2 (PKM) mRNA splicing assay was performed using RT-PCR together with restriction digestion. LUAD cell metabolism was studied using glucose uptake assays and lactate production. ESCO2 expression was significantly upregulated in LUAD tissues, and higher ESCO2 expression indicated worse prognosis for patients with LUAD. Results: We found that ESCO2 promoted LUAD cell proliferation and metastasis metabolic reprogramming in vitro and in vivo. Mechanistically, ESCO2 increased hnRNPA1 (heterogeneous nuclear ribonucleoprotein A1) binding to the intronic sequences flanking exon 9 (EI9) of PKM mRNA by inhibiting hnRNPA1 nuclear translocation, eventually inhibiting PKM1 isoform formation and inducing PKM2 isoform formation. Conclusions: Our findings confirm that ESCO2 is a key factor in promoting LUAD malignant progression and suggest that it is a new target for treating LUAD.

scholarly journals ESCO2 promotes lung adenocarcinoma progression by regulating hnRNPA1 acetylation

2021 ◽  
Vol 40 (1) ◽  
Author(s):  
Hui-er Zhu ◽  
Tao Li ◽  
Shengnan Shi ◽  
De-xiong Chen ◽  
Weiping Chen ◽  
...  
Keyword(s):  
Cell Proliferation ◽  
Lung Adenocarcinoma ◽  
Nuclear Translocation ◽  
Lactate Production ◽  
Gene Set Enrichment Analysis ◽  
Metabolic Reprogramming ◽  
The Cancer Genome Atlas ◽  
Migration And Invasion

Abstract Background Emerging evidence indicates that metabolism reprogramming and abnormal acetylation modification play an important role in lung adenocarcinoma (LUAD) progression, although the mechanism is largely unknown. Methods Here, we used three public databases (Oncomine, Gene Expression Omnibus [GEO], The Cancer Genome Atlas [TCGA]) to analyze ESCO2 (establishment of cohesion 1 homolog 2) expression in LUAD. The biological function of ESCO2 was studiedusing cell proliferation, colony formation, cell migration, and invasion assays in vitro, and mouse xenograft models in vivo. ESCO2 interacting proteins were searched using gene set enrichment analysis (GSEA) and mass spectrometry. Pyruvate kinase M1/2 (PKM) mRNA splicing assay was performed using RT-PCR together with restriction digestion. LUAD cell metabolism was studied using glucose uptake assays and lactate production. ESCO2 expression was significantly upregulated in LUAD tissues, and higher ESCO2 expression indicated worse prognosis for patients with LUAD. Results We found that ESCO2 promoted LUAD cell proliferation and metastasis metabolic reprogramming in vitro and in vivo. Mechanistically, ESCO2 increased hnRNPA1 (heterogeneous nuclear ribonucleoprotein A1) binding to the intronic sequences flanking exon 9 (EI9) of PKM mRNA by inhibiting hnRNPA1 nuclear translocation, eventually inhibiting PKM1 isoform formation and inducing PKM2 isoform formation. Conclusions Our findings confirm that ESCO2 is a key factor in promoting LUAD malignant progression and suggest that it is a new target for treating LUAD.

scholarly journals ESCO2 promotes lung adenocarcinoma progression by regulating hnRNPA1 acetylation

2021 ◽  
Author(s):  
Hui-er Zhu ◽  
Tao Li ◽  
Shengnan Shi ◽  
De-xiong Chen ◽  
Weiping Chen ◽  
...  
Keyword(s):  
Cell Proliferation ◽  
Lung Adenocarcinoma ◽  
Nuclear Translocation ◽  
Lactate Production ◽  
Gene Set Enrichment Analysis ◽  
Metabolic Reprogramming ◽  
The Cancer Genome Atlas ◽  
Migration And Invasion

Abstract Background: Emerging evidence indicates that metabolism reprogramming and abnormal acetylation modification play an important role in lung adenocarcinoma (LUAD) progression, although the mechanism is largely unknown. Methods: Here, we used three public databases (Oncomine, Gene Expression Omnibus [GEO], The Cancer Genome Atlas [TCGA]) to analyze ESCO2 (establishment of cohesion 1 homolog 2) expression in LUAD. The biological function of ESCO2 was studiedusing cell proliferation, colony formation, cell migration, and invasion assays in vitro, and mouse xenograft models in vivo. ESCO2 interacting proteins were searched using gene set enrichment analysis (GSEA) and mass spectrometry. Pyruvate kinase M1/2 (PKM) mRNA splicing assay was performed using RT-PCR together with restriction digestion. LUAD cell metabolism was studied using glucose uptake assays and lactate production. ESCO2 expression was significantly upregulated in LUAD tissues, and higher ESCO2 expression indicated worse prognosis for patients with LUAD. Results: We found that ESCO2 promoted LUAD cell proliferation and metastasis metabolic reprogramming in vitro and in vivo. Mechanistically, ESCO2 increased hnRNPA1 (heterogeneous nuclear ribonucleoprotein A1) binding to the intronic sequences flanking exon 9 (EI9) of PKM mRNA by inhibiting hnRNPA1 nuclear translocation, eventually inhibiting PKM1 isoform formation and inducing PKM2 isoform formation. Conclusions: Our findings confirm that ESCO2 is a key factor in promoting LUAD malignant progression and suggest that it is a new target for treating LUAD.

scholarly journals Systematic Construction and Validation of a Prognostic Model for Hepatocellular Carcinoma Based on Immune-Related Genes

2021 ◽  
Vol 9 ◽  
Author(s):  
Jiahao Yu ◽  
Shuoyi Ma ◽  
Siyuan Tian ◽  
Miao Zhang ◽  
Xiaopeng Ding ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Liver Cancer ◽  
Differential Expression ◽  
Prognostic Model ◽  
Immune Cell ◽  
Clinical Stage ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Incidence And Mortality ◽  
Immune Related Genes

Hepatocellular carcinoma (HCC), a highly aggressive tumor, has high incidence and mortality rates. Recently, immunotherapies have been shown to be a promising treatment in HCC. The results of either the CheckMate-040 or IMbrave 150 trials demonstrate the importance of immunotherapy in the systemic treatment of liver cancer. Thus, in this study, we tried to establish a reliable prognostic model for liver cancer based on immune-related genes (IRGs) and to provide a new insight for immunotherapy of HCC. In this study, we used four datasets that incorporated 851 HCC samples, including 340 samples with complete clinical information from the cancer genome atlas (TCGA) database, to establish an effective model for predicting the prognosis of HCC patients based on the differential expression of IRGs and validated the prognostic model using the data from International Cancer Genome Consortium (ICGC). The top 6 characteristic IRGs identified by protein-protein interaction (PPI) network analysis, MMP9, FOS, CAT, ESR1, ANGPTL3, and KLKB1, were selected for further study. In addition, we assessed the correlations of the six characteristic IRGs with the tumor immune microenvironment, clinical stage, and sensitivity to anti-cancer drugs. We also explored whether the differential expression of the characteristic IRGs was specific to HCC or present in pan-cancer. The expression levels of the six characteristic IRGs were significantly different between most tumor tissues and adjacent normal tissues. In addition, these characteristic IRGs showed a strong association with immune cell infiltration in HCC patients. We found that MMP9 and ESR1 were independent prognostic factors for HCC, while CAT, ESR1, and KLKB1 were associated with the clinical stage. We collected HCC paraffin sections from 24 patients from Xijing hospital to identify the differential expression of the five genes (MMP9, ESR1, CAT, FOS, and KLKB1). Finally, the results of decision curve analysis (DCA) and nomogram revealed that our models provided a prognostic benefit for most HCC patients and the predicted overall survival (OS) was consistent with the actual OS. In conclusion, we systemically constructed a novel prognostic model that provides new insights into HCC.

scholarly journals Development of a prognostic signature for esophageal cancer based on nine immune related genes

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Zhi Zhang ◽  
Cheng Chen ◽  
Ying Fang ◽  
Sheng Li ◽  
Xiaohua Wang ◽  
...  
Keyword(s):  
T Cells ◽  
Esophageal Cancer ◽  
Prognostic Model ◽  
Cox Regression ◽  
Risk Group ◽  
The Cancer Genome Atlas ◽  
Receptor Interaction ◽  
Prognostic Signature ◽  
Cox Regression Analysis ◽  
Immune Related Genes

Abstract Background Function of the immune system is correlated with the prognosis of the tumor. The effect of immune microenvironment on esophageal cancer (EC) development has not been fully investigated. Methods This study aimed to explore a prognostic model based on immune-related genes (IRGs) for EC. We obtained the RNA-seq dataset and clinical information of EC from the Cancer Genome Atlas (TCGA). Results We identified 247 upregulated IRGs and 56 downregulated IRGs. Pathway analysis revealed that the most differentially expressed IRGs were enriched in Cytokine-cytokine receptor interaction. We further screened 13 survival-related IRGs and constructed regulatory networks involving related transcription factors (TFs). Finally, a prognostic model was constructed with 9 IRGs (HSPA6, S100A12, CACYBP, NOS2, DKK1, OSM, STC2, NGPTL3 and NR2F2) by multivariate Cox regression analysis. The patients were classified into two subgroups with different outcomes. When adjusted with clinical factors, this model was verified as an independent predictor, which performed accurately in prognostic prediction. Next, M0 and M2 macrophages and activated mast cells were significantly enriched in high-risk group, while CD8 T cells and regulatory T cells (Tregs) were significantly enriched in low-risk group. Conclusions Prognosis related IRGs were identified and a prognostic signature for esophageal cancer based on nine IRGs was developed.

scholarly journals Prognostic Model of Colorectal Cancer Constructed by Eight Immune-Related Genes

2020 ◽  
Vol 7 ◽  
Author(s):  
Shuting Wen ◽  
Long He ◽  
Zhuotai Zhong ◽  
Hong Mi ◽  
Fengbin Liu
Keyword(s):  
Colorectal Cancer ◽  
Prognostic Model ◽  
Immune Cell ◽  
Cox Regression ◽  
Risk Group ◽  
Immune Cell Infiltration ◽  
Cox Regression Analysis ◽  
Prognostic Prediction ◽  
Immune Related Genes

BackgroundColorectal cancer (CRC) is a common malignant tumor of the digestive tract with a high mortality rate. Growing evidence demonstrates that immune-related genes play a prominent role in the occurrence and development of CRC. The aim of this study was to investigate the prognostic value of immune-related genes in CRC.MethodsGene expression profiles and clinical data of 568 CRC and 44 non-tumorous tissues were obtained from The Cancer Genome Atlas (TCGA) database. First, we performed a differentially expressed gene (DEG) analysis and univariate Cox regression analysis to determine the DEGs associated with overall survival. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were subsequently performed for prognostic immune-related genes. Then, a multivariate Cox regression analysis was performed to establish the immune prognostic model and identify the independent prognostic factors of CRC. Next, in vitro experiments were done to further validate the model. Finally, we analyzed the correlation among immune-related genes, clinical traits, and immune cell infiltration.ResultsIn total, 3,702 DEGs were obtained, and 338 prognostic immune-related genes were identified. Among them, 45 genes were significantly correlated with the prognosis of CRC patients. A TF-mediated network was set up to explore its internal mechanism. GO and KEGG analyses further illustrated that these genes were enriched in immune-and inflammatory-related pathways. Then, a prognostic prediction model composed of eight immune-related genes (SLC10A2, UTS2, FGF2, UCN, IL1RL2, ESM1, ADIPOQ, and VIP) was constructed. The AUC of the ROC curve for 1, 3, 5, and 10 years overall survival (OS) was 0.751, 0.707, 0.680, and 0.729, respectively. The survival analysis suggested that the OS of the high-risk group was significantly poorer than that of the low-risk group. Meanwhile, in vitro assays revealed that ESM1 and SLC10A2 exert opposing roles in colon cancer cell proliferation, validating the accuracy of the model. The correlation analysis indicated that immune cell infiltration was positively related to the model.ConclusionThis study screened prognosis-related immune genes and developed a prognostic prediction model of CRC. These findings may help provide potential novel prognostic biomarkers and therapeutic targets for CRC. At the same time, the understanding of the CRC immune microenvironment status was deepened.

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