Cancer-associated fibroblasts are associated with poor prognosis in solid type of lung adenocarcinoma in a machine learning analysis.
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ABSTRACT:
SUBMITTER: Min KW
PROVIDER: S-EPMC8373913 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Background:Cancer-associated fibroblasts (CAFs) are a heterogeneous population, and different subpopulations play differential roles in tumor microenvironment. However, the prognostic role of podoplanin-positive CAFs in human lung cancer still remains controversial. Methods:Herein, we performed a meta-analysis including 12 published studies with 1,802 patients identified from PubMed and EBSCO to assess the prognostic impact of podoplanin-positive CAFs in lung cancer patients. Results:We found that podoplanin+ fibroblast infiltration significantly decreased overall survival (OS), disease-free survival (DFS), and progression-free survival in patients. In stratified analyses, podoplanin+ fibroblast infiltration was significantly associated with worse OS and DFS in both squamous cell carcinoma and adenocarcinoma of lung. In addition, high density of podoplanin-positive CAFs significantly correlated with unfavorable clinicopathological features such as lymph node metastasis, and lymphatic, vascular, and pleural invasion of patients. Conclusion:Podoplanin+ fibroblast infiltration leads to worse clinical outcome in lung cancer patients, implicating that it is a valuable prognostic biomarker and targeting it may have a potential for effective treatment.
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Project description:Background:Lung adenocarcinoma (LUAD), as the main subtype of lung cancer, is one of the common causes of cancer-related deaths worldwide. The AHNAK family is correlated with cell structure and migration, cardiac calcium channel signaling, and tumor metastasis. Previous studies showed AHNAK2 could promote tumor progression and cell migration in melanoma and renal clear cell carcinoma. However, the role of AHNAK2 in LUAD remains unknown. Methods:We examined the levels of AHNAK2 in pathological specimens and the database of Clinical Proteomic Tumor Analysis Consortium-Lung adenocarcinoma (CPTAC-LUAD), The Cancer Genome Atlas-Lung Adenocarcinoma (TCGA-LUAD), Gene Expression Omnibus dataset (GSE72094, GSE26939), and The Genotype-Tissue Expression (GTEx) of lung tissue samples. Univariate Cox regression, multivariate Cox regression, and Kaplan-Meier survival analysis were performed to reveal the relationship between AHNAK2 and prognosis. A nomogram was constructed to predict 2- or 3-year overall survival and validated via calibration curves, receiver operating characteristic (ROC) analysis, and decision curve analysis (DCA). Furthermore, Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were used to explore the functional role of AHNAK2 in lung adenocarcinoma. Finally, by transfecting siRNA, we examined the regulatory effect of AHNAK2 on cell migration. Results:The expression of AHNAK2 was upregulated in tumor samples and correlated with poor prognosis in LUAD patients. Nomogram with AHNAK2 and clinical parameters showed a good prediction in overall survival (OS), especially the 2-year OS. In addition, functional analyses and wound healing assay suggested that AHNAK2 might be involved in the regulation of migration in LUAD. Conclusion:In summary, our study showed that AHNAK2 might be a novel biomarker in LUAD and revealed the potential mechanism of AHNAK2 in LUAD progression which could provide new insights for target therapy.
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Project description:In the study, we obtained 36 pairs of lung adenocarcinoma (LUAD) tissues and adjacent non-tumorous tissues. Then, we chose a specific hub-target gene of miRNA and used qRT-PCR to evaluate the expression of PECAM1. We found that the expression level of PECAM1 mRNA in LUAD was significantly lower than that in adjacent nontumor tissues (P<0.0001). Univariate and multivariate analyses were conducted on 481 LUAD patients from The Cancer Genome Atlas (TCGA) according to the Cox proportional hazard regression model to evaluate the impact of PECAM1 expression and other clinicopathological factors on survival. The results showed that the low expression of PECAM1 was an important independent predictor of poor overall survival (HR, 0.704; 95% CI, 0.518-0.957; P = 0.025). Based on the Tumor Immune Estimation Resource (TIMER) database, the relationship between PECAM1 expression and B cell, CD8+ T cell, CD4+ T cell, macrophage, neutrophil, and dendritic cell infiltration was weak in LUAD (P<0.01). In particular, a more significant positive correlation between PECAM1 expression and HLA-complex members, CD1C, NRP1, and ITGAX expression in dendritic cell was detected in LUAD. The mechanism which PECAM1 involved in the development of LUAD may be closely related to changes in the immune microenvironment.
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Project description:BackgroundAfter curative surgical resection, about 30-75% lung adenocarcinoma (LUAD) patients suffer from recurrence with dismal survival outcomes. Identification of patients with high risk of recurrence to impose intense therapy is urgently needed.Materials and methodsGene expression data of LUAD were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Differentially expressed genes (DEGs) were calculated by comparing the recurrent and primary tissues. Prognostic genes associated with the recurrence-free survival (RFS) of LUAD patients were identified using univariate analysis. LASSO Cox regression and multivariate Cox analysis were applied to extract key genes and establish the prediction model.ResultsWe detected 37 DEGs between primary and recurrent LUAD tumors. Using univariate analysis, 31 DEGs were found to be significantly associated with RFS. We established the RFS prediction model including thirteen genes using the LASSO Cox regression. In the training cohort, we classified patients into high- and low-risk groups and found that patients in the high-risk group suffered from worse RFS compared to those in the low-risk group (P < 0.01). Concordant results were confirmed in the internal and external validation cohort. The efficiency of the prediction model was also confirmed under different clinical subgroups. The high-risk group was significantly identified as the risk factor of recurrence in LUAD by the multivariate Cox analysis (HR = 13.37, P = 0.01). Compared to clinicopathological features, our prediction model possessed higher accuracy to identify patients with high risk of recurrence (AUC = 96.3%). Finally, we found that the G2M checkpoint pathway was enriched both in recurrent tumors and primary tumors of high-risk patients.ConclusionsOur recurrence-specific gene-based prognostic prediction model provides extra information about the risk of recurrence in LUAD, which is conducive for clinicians to conduct individualized therapy in clinic.
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Project description:Background: Topoisomerase IIA (TOP2A) gene encodes DNA topoisomerase enzyme and has been reported that TOP2A is broadly expressed in many types of cancers. Our study aims to investigate the prognostic effect of TOP2A on lung adenocarcinoma (LUAD) and the potential molecular mechanism of TOP2A to tumorigenesis. Methods: Bioinformatical analysis, real-time PCR and Western blot were applied to explore the expression level of TOP2A. Kaplan-Meier survival analysis was used to evaluate the effect of TOP2A on patients' prognosis. Cell proliferation, migration and invasion ability were examined by colony-formation, Cell Counting Kit-8 (CCK8) assay, wound healing assay and transwell invasion assay, respectively. Results: We firstly investigated differentially expressed genes in lung adenocarcinoma and normal tissues of GEO (tumor = 666, normal = 184) and TCGA (tumor = 517, normal = 59) and these data showed that TOP2A is broadly expressed in LUAD and the expression level of TOP2A is associated with poor prognosis, which indicated that TOP2A is an upregulated prognostic related gene in LUAD. Then we identified that the expression level of TOP2A was upregulated in both surgically removed lung cancer tissues and lung cancer cell lines. Knockdown of TOP2A in A549 and GLC82 cells inhibited cell proliferation, migration and invasion. Inhibition of TOP2A reduced the expression levels of CCNB1 and CCNB2, which indicated that TOP2A targeting CCNB1 and CCNB2 promotes GLC82 and A549 cells proliferation and metastasis. Conclusions: Our study revealed an important role of TOP2A in LUAD, and may provide a potential prognostic indicator and target for cancer therapy.
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Project description:BackgroundThis study was conducted to investigate the clinical significance of claudin-1 (CLDN1) expression in patients with lung adenocarcinoma.MethodsWe examined CLDN1 protein expression by immunohistochemistry in a tissue microarray from 258 patients with lung adenocarcinoma. We investigated messenger ribonucleic acid (mRNA) expression in H358 (formerly bronchioloalveolar carcinoma) and lung adenocarcinoma cell lines (A549) by real-time reverse transcriptase-polymerase chain reaction.ResultsMultivariate analysis showed that prognostic factors for lung adenocarcinoma were histologic type, CLDN1, T stage and N stage. Patients with positive CLDN1 expression had a poorer prognosis than patients with negative CLDN1 expression. CLDN1 expression was correlated with Ras and epidermal growth factor receptor (EGFR) expression. Patients with positive expressions of both CLDN1 and Ras/EGFR had a poorer prognosis than patients with CLDN1 (+) Ras/EGFR(-) or CLDN1 (-) Ras/EGFR(+) and patients with negative expressions of both CLDN1 and Ras/EGFR. CLDN1 mRNA expression was lower in the H358 compared with the lung adenocarcinoma cell line (A549).ConclusionThe combination of CLDN1 and Ras/EGFR is a valuable independent prognostic predictor for lung adenocarcinoma.
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Project description:Objectives: DNA damage inducible transcript 4 (DDIT4) plays a key role in different cancers, but the role of DDIT4 in lung adenocarcinoma (LUAD) is not completely understood. The aim of this study was to evaluate the utility of DDIT4 as a prognostic biomarker for LUAD. Methods: First, DDIT4 mRNA expression in LUAD cell lines (A549, H1299 and HBE) and tissues (89 cases) was assessed by RT-PCR. Next, DDIT4 protein expression in LUAD tissues and normal tissues was assessed by immunohistochemistry (75 cases). Then, the correlation between DDIT4 expression and overall survival was analyzed using the Kaplan-Meier method. After that, we verified the utility of the DDIT4 gene as a prognostic marker of lung cancer in the TCGA database (1133 cases). Finally, the possible mechanism of the DDIT4 gene as a prognostic marker of LUAD was preliminarily explored. Results: mRNA levels of DDIT4 in HBE cells were significantly lower than in A549 and H1299 cells (P<0.05), and expression of the DDIT4 gene in cancer tissues was significantly higher than in adjacent tissues (P<0.0001). Immunohistochemical staining results showed that high expression of DDIT4 accounted for approximately 68.0% of LUAD tissues. DDIT4 expression was significantly correlated with differentiation (P < 0.05). However, it was not correlated with sex, age, smoking, tumor size, lymph node metastasis, or TNM stage (P>0.05). The survival analysis demonstrated that high DDIT4 expression was correlated with shorter overall survival (P < 0.05). Univariate and multivariate analyses indicated that DDIT4 was an independent predictor of overall survival for LUAD, which was confirmed by data from the TCGA database. Finally, we found that DDIT4 gene expression was significantly increased in the hypoxic environment compared to the normal oxygen environment, indicating that the DDIT4 gene may play an important role in the hypoxic microenvironment of tumor tissue. Conclusion: High expression levels of DDIT4 correlated with poor overall survival in patients with LUAD, and DDIT4 was an independent predictor of overall survival. These findings provide new insight for understanding the development of LUAD.
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