scholarly journals Upregulated expression of pyruvate kinase M2 mRNA predicts poor prognosis in lung adenocarcinoma

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e8625
Author(s):  
Guiping Wang ◽  
Yingying Zhong ◽  
Jiecong Liang ◽  
Zhibin Li ◽  
Yun Ye
Keyword(s):  
Lung Adenocarcinoma ◽  
Pyruvate Kinase ◽  
Poor Prognosis ◽  
Prognostic Value ◽  
Prognostic Significance ◽  
Tumor Stage ◽  
Pooled Analysis ◽  
Copy Number Variations ◽  
Pyruvate Kinase M2 ◽  
Kaplan Meier

Background Pyruvate kinase M2 (PKM2) is critical regulator contributing to Warburg effect. However, the expression pattern and prognostic value of PKM2 remain unknown in lung adenocarcinoma (LUAD). The aim of this study is to clarify the prognostic value of PKM2 via intergrated bioinformatics analysis. Methods Firstly, mRNA expression levels of PKM2 in LUAD were systematically analyzed using the ONCOMINE and TCGA databases. Then, the association between PKM2 expression and clinical parameters was investigated by UALCAN. The Kaplan–Meier Plotter was used to assess the prognostic significance of PKM2. Finally, the relationship between PKM2 expression and its genetic and epigenetic changes was evaluated with MEXPRESS and MethHC database. Results Pooled analysis showed that PKM2 is frequently upregulated expression in LUAD. Subsequently, PKM2 expression was identified to be positively associated with tumor stage and lymph node metastasis and also strongly correlated with worse OS (P = 2.80e−14), PPS (P = 0.022), FP (P = 1.30e−6) and RFS (P = 3.41e−8). Importantly, our results demonstrated that over-expressed PKM2 is associated with PKM2 hypomethylation and copy number variations (CNVs). Conclusion This study confirms that over-expressed PKM2 in LUAD is associated with poor prognosis, suggesting that PKM2 might act as a promising prognostic biomarker and novel therapeutic target for LUAD.

scholarly journals Pyruvate Kinase M2 is a marker of poor prognosis in lung adenocarcinoma but not lung squamous cell carcinoma

2020 ◽  
Vol 9 (5) ◽  
pp. 3293-3302
Author(s):  
Junxia Zhang ◽  
Chengjuan Zhang ◽  
Xianghua Liu ◽  
Ning Sun ◽  
Caili Zhang ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Lung Adenocarcinoma ◽  
Cell Carcinoma ◽  
Pyruvate Kinase ◽  
Squamous Cell ◽  
Poor Prognosis ◽  
Lung Squamous Cell Carcinoma ◽  
Pyruvate Kinase M2

scholarly journals Elevated Heterogeneous Nuclear Ribonucleoprotein C Expression Correlates With Poor Prognosis in Patients With Surgically Resected Lung Adenocarcinoma

2021 ◽  
Vol 10 ◽  
Author(s):  
Wei Guo ◽  
Qilin Huai ◽  
Guochao Zhang ◽  
Lei Guo ◽  
Peng Song ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Lung Adenocarcinoma ◽  
Poor Prognosis ◽  
Prognostic Value ◽  
Cox Regression ◽  
Gene Set Enrichment Analysis ◽  
Normal Lung ◽  
Heterogeneous Nuclear Ribonucleoprotein ◽  
Kaplan Meier ◽  
Nuclear Ribonucleoprotein

BackgroundLung adenocarcinoma (LUAD), as the most common histological subtype of lung cancer, is a high-grade malignancy and a leading cause of cancer-related death globally. Identification of biomarkers with prognostic value is of great significance for the diagnosis and treatment of LUAD. Heterogeneous nuclear ribonucleoprotein C (HNRNPC) is an RNA-binding protein “reader” of N6-methyladenosine (m6A) methylation, and is related to the progression of various cancers; however, its role in LUAD is unclear. The aims of this study aims were to study the expression and prognostic value of HNRNPC in LUAD.MethodsThe Oncomine database and gene expression profiling interactive analysis (GEPIA) were used for preliminary exploration of HNRNPC expression and prognostic value in LUAD. LUAD cases from The Cancer Genome Atlas (TCGA) (n = 416) and the Kaplan-Meier plotter database (n = 720) were extracted to study the differential expression and prognostic value of HNRNPC. HNRNPC expression in the National Cancer Center of China (NCC) cohort was analyzed by immunohistochemical staining, and the relationship between HNRNPC expression and survival rate evaluated using the Kaplan-Meier method and log-rank test. Univariate and multivariate Cox regression analyses were used to identify independent prognostic factors. Several pathways that were significantly enriched in the HNRNPC high expression group were identified by Gene Set Enrichment Analysis (GSEA).ResultsFive data sets from the Oncomine and GEPIA databases all supported that HNRNPC expression is significantly higher in LUAD than in normal lung tissue. In TCGA cohort, HNRNPC was highly expressed in LUAD tissues and significantly related to age, sex, smoking history, ethnicity, lymph node metastasis, and TNM staging (P < 0.001). High HNRNPC expression was significantly correlated with poor prognosis in the three cohorts (NCC, TCGA, and K-M plotter) (P < 0.05). Multivariate Cox regression analysis showed that HNRNPC expression was an independent prognostic factor in both TCGA and NCC cohorts (P < 0.05). Further, 10 significantly enriched pathways were identified from TCGA data and 118 lung cancer cell lines in CCLE, respectively.ConclusionsHigh HNRNPC expression is significantly related to poor overall survival in patients with LUAD, suggesting that HNRNPC may be a cancer-promoting factor and a potential prognostic biomarker in LUAD.

Prognostic value of biglycan in gastric cancer

2020 ◽  
Author(s):  
Sizhe Hu ◽  
Peipei Li ◽  
Chenying Wang ◽  
Xiyong Liu
Keyword(s):  
Gastric Cancer ◽  
Transcription Factors ◽  
Poor Prognosis ◽  
Prognostic Significance ◽  
Bioinformatic Analysis ◽  
Gene Set Enrichment Analysis ◽  
High Expression ◽  
Mrna Levels ◽  
Gene Signatures ◽  
Kaplan Meier

Abstract Background: BGN (biglycan) is a family member of small leucine-rich repeat proteoglycans. High expression of BGN might enhance the invasion and metastasis in some types of tumors. Here, the prognostic significance of BGN was evaluated in gastric cancer.Material and Methods: Two independent Gene Expression Omnibus (GEO) gastric cancer microarray datasets( n= 64, n=432) were collected for this study. Kaplan-Meier analysis was applied to evaluate if BGN impacts the outcomes of gastric cancer. The gene set enrichment analysis (GSEA) was used to explore BGN and cancer-related gene signatures. Bioinformatic analysis predicted the putative transcription factors of BGN.Results: For gastric cancer, the mRNA expression level of BGN in tumor tissues was significantly higher than that in normal tissues. Kaplan-Meier analysis showed that higher expression of BGN mRNA was significantly associated with more reduced recurrence-free survival (RFS). GSEA results suggested that BGN significantly enriched metastasis and poor prognosis gene signatures, revealing that BGN might be associated with cell proliferation, poor differentiation, high invasiveness of gastric cancer. Meanwhile, the putative transcription factors, including AR, E2F1, and TCF4, weres predicted by bioinformatic analysis and also significantly correlated with expression of BGN in mRNA levels. Conclusion: High expression of BGN mRNA was significantly related to poor prognosis, which suggested BGN was a potential prognostic biomarker and therapeutic target of gastric cancer.

scholarly journals Integrative Analysis of Three Novel Competing Endogenous RNA Biomarkers with a Prognostic Value in Lung Adenocarcinoma

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Juan Tan ◽  
Weimin Wang ◽  
Bin Song ◽  
Yingjian Song ◽  
Zili Meng
Keyword(s):  
High Risk ◽  
Lung Adenocarcinoma ◽  
Prognostic Value ◽  
Kegg Pathway ◽  
Enrichment Analysis ◽  
Cerna Network ◽  
Kaplan Meier ◽  
Function Enrichment Analysis ◽  
Pathway Function ◽  
Function Enrichment

Increasing evidence has shown competitive endogenous RNAs (ceRNAs) play key roles in numerous cancers. Nevertheless, the ceRNA network that can predict the prognosis of lung adenocarcinoma (LUAD) is still lacking. The aim of the present study was to identify the prognostic value of key ceRNAs in lung tumorigenesis. Differentially expressed (DE) RNAs were identified between LUAD and adjacent normal samples by limma package in R using The Cancer Genome Atlas database (TCGA). Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway function enrichment analysis was performed using the clusterProfiler package in R. Subsequently, the LUAD ceRNA network was established in three steps based on ceRNA hypothesis. Hub RNAs were identified using degree analysis methods based on Cytoscape plugin cytoHubba. Multivariate Cox regression analysis was implemented to calculate the risk score using the candidate ceRNAs and overall survival information. The survival differences between the high-risk and low-risk ceRNA groups were determined by the Kaplan-Meier and log-rank test using survival and survminer package in R. A total of 2,989 mRNAs, 185 lncRNAs, and 153 miRNAs were identified. GO and KEGG pathway function enrichment analysis showed that DE mRNAs were mainly associated with “sister chromatid segregation,” “regulation of angiogenesis,” “cell adhesion molecules (CAMs),” “cell cycle,” and “ECM-receptor interaction.” LUAD-related ceRNA network was constructed, which comprised of 54 nodes and 78 edges. Top ten hub RNAs (hsa-miR-374a-5p, hsa-miR-374b-5p, hsa-miR-340-5p, hsa-miR-377-3p, hsa-miR-21-5p, hsa-miR-326, SNHG1, RALGPS2, and PITX2) were identified according to their degree. Kaplan-Meier survival analyses demonstrated that hsa-miR-21-5p and RALGPS2 had a significant prognostic value. Finally, we found that a high risk of three novel ceRNA interactions (SNHG1-hsa-miR-21-5p-RALGPS2, SNHG1-hsa-miR-326-RALGPS2, and SNHG1-hsa-miR-377-3p-RALGPS2) was positively associated with worse prognosis. Three novel ceRNAs (SNHG1-hsa-miR-21-5p-RALGPS2, SNHG1-hsa-miR-326-RALGPS2, and SNHG1-hsa-miR-377-3p-RALGPS2) might be potential biomarkers for the prognosis and treatment of LUAD.

Low TWEAK expression indicates poor survival and is correlated with sparse TIICs in lung adenocarcinoma (LUAD).

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e21017-e21017
Author(s):  
Jinchun Wu ◽  
Xianyu Liu ◽  
Yanhua Mou ◽  
Shan Zeng ◽  
Jin Zhang ◽  
...  
Keyword(s):  
T Cells ◽  
Lung Adenocarcinoma ◽  
Cd8 T Cells ◽  
Immune Cells ◽  
Poor Prognosis ◽  
Immune Escape ◽  
Underlying Mechanism ◽  
Memory Cd8 T Cells ◽  
Kaplan Meier ◽  
Kaplan Meier Plotter

e21017 Background: Lung adenocarcinoma (LUAD) occupies the most of non-small cell lung cancer (NSCLC) and shows promising response to PD-1 immunotherapy, but immune escape will cause treatment failure indicating poor prognosis. TWEAK (Tumor necrosis factor-related weak inducer of apoptosis, also known as TNFSF12) combining with its receptor FN14 (fibroblast growth factor–inducible 14) mediates crucial innate and adaptive immune pathways to promote the progression of multiple autoimmune diseases. So we assumed that TWEAK is a prognostic predictor and related with tumor-infiltrating immune cells (TIICs) in LUAD. Methods: TWEAK expression of LUAD was primarily investigated in The Cancer Immunome Atlas (TCIA) and then validated in Tumor Immune Estimation Resource (TIMER) databases. We assessed the effect of TWEAK on the survival via the Kaplan-Meier plotter, GEPIA2 (gene expression profiling interactive analysis) and PrognoScan databases. The relation between TWEAK and TIICs was explored in TIMER and TCIA, as well as the correlation of TWEAK and FN14 was analyzed in TIMER and GEPIA2. Results: Low TWEAK expression was significantly associated with poor relapse-free survival (RFS) (HR = 0.62, 95% CI = 0.4~0.97, logrank P = 0.035) and overall survival (OS) (HR = 0.61, 95% CI = 0.46~0.83, logrank P = 0.0012) in LUAD from Kaplan-Meier plotter. Similar impacts of TWEAK on the survival were validated in GEPIA2 and four independent cohorts from PrognoScan (jacob-00182-CANDF, GSE13213, jacob-00182-MSK and GSE31210). Moreover, reduced TWEAK expression was closely related with the paucity of TIICs which contributed to poor OS, including central memory CD8 T cells, plasmacytoid dendritic cells, activated CD8 T cells, monocytes, T follicular helper cells, immature B cells and eosinophils. In addition, TWEAK expression was positively related with the expression level of FN14 in both GEPIA2(R = 0.13, P= 0.0031) and TIMER (partial.cor = 0.212, P= 2.04e-06). Conclusions: Low TWEAK expression maybe indicate poor prognosis in LUAD, and correlated with the impaired infiltration of immune cells in the tumor region. The defective TWEAK/FN14 pathway possibly accounts for these observations, but the underlying mechanism needs to be further explored.

scholarly journals High Expression of PXN Predicts a Poor Prognosis in Acute myeloid leukemia

2021 ◽  
Author(s):  
xinwen zhang ◽  
Hao Xiong ◽  
Jialin Duan ◽  
Xiaomin Chen ◽  
Yang Liu ◽  
...  
Keyword(s):  
Acute Myeloid Leukemia ◽  
Myeloid Leukemia ◽  
Poor Prognosis ◽  
Cox Regression ◽  
Prognostic Significance ◽  
Cox Regression Analysis ◽  
Kaplan Meier ◽  
Receive Treatment ◽  
To Receive ◽  
Acute Myeloid

Abstract Background: Acute myeloid leukemia (AML) is one of the common malignant diseases of hematopoietic system. Paxillin ( PXN ) is an important part of focal adhesions (FAs), which is related to the poor prognosis of many kinds of malignant tumors. However, no research has focused on the expression of PXN in AML. We aimed to investigate the expression of PXN in AML and its prognostic significance. Methods: Using GEPIA and UALCAN database to analyze the expression of PXN in AML patients and its prognostic significance. Bone marrow samples of newly diagnosed AML patients were collected to extract RNA, and qRT-PCR was used to detect the expression of PXN . The prognosis was followed up. Chi-square test was used to analyze the relationship between PXN expression and clinical laboratory characteristics. Kaplan-Meier analysis was used to draw survival curve, and Cox regression analysis was used to analyze the independent factors affecting the prognosis of patients with AML. The co-expression genes of PXN were analyzed by LinkedOmics to explore its biological significance in AML. Results: Kaplan-Meier analysis showed that the overall survival time of AML patients was related to whether to receive treatment and PXN expression(P<0.05). COX regression analysis showed that whether to receive treatment (HR=0.227，95%CI=0.075-0.689， P =0.009) and high expression of PXN (HR=4.484，95%CI=1.449-13.889， P =0.009) were independent poor prognostic factors in patients with AML. Conclusion: PXN is highly expressed in AML patient, and high PXN expression is an indicator of poor prognosis in AML patient.

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