Screening of tumor-associated antigens based on Oncomine database and evaluation of diagnostic value of autoantibodies in lung cancer

Wang, Tingting; Liu, Hongchun; Lü, Peng; Wang, Kaijuan; Song, Chunhua; Wang, Peng; Ye, Hua; Zhang, Jianying; Ji, Zhenyu; Ouyang, Songyun; Dai, Liping

doi:10.1016/j.clim.2019.108262

Cited by 34 publications

(17 citation statements)

References 43 publications

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“…Regarding the detection of FGF1 expression level, our results were consistent with Skrzypczak’s ( 19 ). However, a pooled analysis of 16 studies included by the Oncomine platform do not support the result that expression levels of FGF1 is higher in CRC than in normal tissues ( 20 , 21 ). Therefore, more studies are needed to clarify and support this conclusion.…”

Section: Discussionmentioning

confidence: 84%

The Association of Aberrant Expression of FGF1 and mTOR-S6K1 in Colorectal Cancer

et al. 2021

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Colorectal cancer (CRC) is one of the most frequent malignant neoplasms worldwide, and the effect of treatments is limited. Fibroblast growth factor 1 (FGF1) has been involved in a wide variety of several malignant diseases and takes part in the tumorigenesis of CRC. However, the function and mechanism of FGF1 in CRC remains elusive. In this study, the results indicated that FGF1 is elevated in CRC tissues and linked with poor prognosis (P < 0.001). In subgroup analysis of FGF1 in CRC, regardless of any clinic-factors except gender, high level FGF1 expression was associated with markedly shorter survival (P < 0.05). In addition, the expression of p-S6K1 and FGF1 was not associated in normal tissue (P = 0.781), but their expression was closely related in tumor tissue (P = 0.010). The oncogenic role of FGF1 was determined using in vitro and in vivo functional assays. FGF1 depletion inhibited the proliferation and migration of CRC cells in vitro and vivo. FGF1 was also significantly correlated with mTOR-S6K1 pathway on the gene and protein levels (P < 0.05). In conclusion, FGF1 acts as a tumor activator in CRC, and against FGF1 may provide a new visual field on treating CRC, especially for mTORC1-targeted resistant patients.

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Section: Discussionmentioning

confidence: 84%

The Association of Aberrant Expression of FGF1 and mTOR-S6K1 in Colorectal Cancer

et al. 2021

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“…The other 11 differential immune-related genes in this prognostic assessment model have been rarely reported in NSCLC. MMP12 is one of the zinc-dependent proteolytic enzymes, which plays a vital role in all aspects of tumor progression (such as tumor angiogenesis and metastasis) [11][12] . Klupp F et al have reported that serum MMP12 levels are a negative prognostic marker in colon cancer patients 13 .…”

Section: Discussionmentioning

confidence: 99%

Construction of a Prognostic Model of Non-small Cell Lung Cancer Based on TCGA and ImmPort Databases and Analysis of Its Correlation With Tumor Microenvironment

Song

Yang³

2021

Preprint

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PurposeBioinformatics methods are used to construct an immune gene prognosis assessment model for patients with non-small cell lung cancer (NSCLC), and to screen biomarkers that affect the occurrence and prognosis of NSCLC.MethodsThe transcriptomic data and clinicopathological data of NSCLC and cancer-adjacent normal tissues were downloaded from the Cancer Genome Atlas (TCGA) database and the immune-related genes were obtained from the IMMPORT database (http://www.immport.org/); then, the differentially expressed immune genes were screened out. Based on these genes, an immune gene prognosis model was constructed. The Cox proportional hazards regression model was used for univariate and multivariate analyses. Further, the correlations among the risk score, clinicopathological characteristics, tumor microenvironment, and the prognosis of NSCLC were analyzed.ResultsA total of 193 differentially expressed immune genes related to NSCLC were screened based on the "wilcox.test" in R language, and Cox single factor analysis showed that 19 differentially expressed immune genes were associated with the prognosis of NSCLC (P <0.05). After including 19 differentially expressed immune genes with P<0.05 into the Cox multivariate analysis, an immune gene prognosis model of NSCLC was constructed (it included 13 differentially expressed immune genes). Based on the risk score, the samples were divided into the high-risk and low-risk groups. The Kaplan-Meier survival curve results showed that the 5-year overall survival rate in the high-risk group was 32.4%, and the 5-year overall survival rate in the low-risk group was 53.7%. The receiver operating characteristic (ROC) model curve confirmed that the prediction model had a certain accuracy (AUC=0.673). After incorporating multiple variables into the Cox regression analysis, the results showed that the immune gene prognostic risk score was an independent predictor of the prognosis of NSCLC patients. There was a certain correlation between the risk score and degree of neutrophil infiltration in the tumor microenvironment.ConclusionThe NSCLC immune gene prognosis assessment model was constructed based on bioinformatics methods, and it can be used to calculate the prognostic risk score of NSCLC patients. Further, this model is expected to provide help for clinical judgment of the prognosis of NSCLC patients.

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“…In comparison with other types of biomarkers, serum TAAbs appeared earlier and more stable (16). They are a kind of promising biomarkers which could be applied for early diagnosis in cancers (17).…”

Section: Introductionmentioning

confidence: 96%

Discovering Panel of Autoantibodies for Early Detection of Lung Cancer Based on Focused Protein Array

et al. 2021

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Substantial studies indicate that autoantibodies to tumor-associated antigens (TAAbs) arise in early stage of lung cancer (LC). However, since single TAAbs as non-invasive biomarkers reveal low diagnostic performances, a panel approach is needed to provide more clues for early detection of LC. In the present research, potential TAAbs were screened in 150 serum samples by focused protein array based on 154 proteins encoded by cancer driver genes. Indirect enzyme-linked immunosorbent assay (ELISA) was used to verify and validate TAAbs in two independent datasets with 1,054 participants (310 in verification cohort, 744 in validation cohort). In both verification and validation cohorts, eight TAAbs were higher in serum of LC patients compared with normal controls. Moreover, diagnostic models were built and evaluated in the training set and the test set of validation cohort by six data mining methods. In contrast to the other five models, the decision tree (DT) model containing seven TAAbs (TP53, NPM1, FGFR2, PIK3CA, GNA11, HIST1H3B, and TSC1), built in the training set, yielded the highest diagnostic value with the area under the receiver operating characteristic curve (AUC) of 0.897, the sensitivity of 94.4% and the specificity of 84.9%. The model was further assessed in the test set and exhibited an AUC of 0.838 with the sensitivity of 89.4% and the specificity of 78.2%. Interestingly, the accuracies of this model in both early and advanced stage were close to 90%, much more effective than that of single TAAbs. Protein array based on cancer driver genes is effective in screening and discovering potential TAAbs of LC. The TAAbs panel with TP53, NPM1, FGFR2, PIK3CA, GNA11, HIST1H3B, and TSC1 is excellent in early detection of LC, and they might be new target in LC immunotherapy.

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Screening of tumor-associated antigens based on Oncomine database and evaluation of diagnostic value of autoantibodies in lung cancer

Cited by 34 publications

References 43 publications

The Association of Aberrant Expression of FGF1 and mTOR-S6K1 in Colorectal Cancer

The Association of Aberrant Expression of FGF1 and mTOR-S6K1 in Colorectal Cancer

Construction of a Prognostic Model of Non-small Cell Lung Cancer Based on TCGA and ImmPort Databases and Analysis of Its Correlation With Tumor Microenvironment

Discovering Panel of Autoantibodies for Early Detection of Lung Cancer Based on Focused Protein Array

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