nach oben

Journal of Cancer Research and Clinical Oncology

Erschienen in:

20.07.2020 | Original Article – Clinical Oncology

Stem signatures associated antibodies yield early diagnosis and precise prognosis predication of patients with non-small cell lung cancer

verfasst von: Si-Si Chen, Kai Li, Jie Wu, Zi-Yang Peng, Zhi-Dong Wang, Ji-Chang Wang, Chong-Wen Xu, Cai-lin Zhu, Bao-Cheng Li, Hong Ren, Shou-Ching Tang, Xin Sun

Erschienen in: Journal of Cancer Research and Clinical Oncology | Ausgabe 1/2021

Einloggen, um Zugang zu erhalten

Abstract

Background

This study was designed to detect patients with early NSCLC with tentatively using the stem signatures associated autoantibodies (AAbs), and to evaluate its latent values in the early diagnosis and precise prognosis prediction.

Methods

The serum concentrations of selective antibodies were quantitated by enzyme-linked immunosorbent assay (ELISA), and a total of 458 cases were enrolled (training set = 401; validation set = 57). TCGA databases were used to analyze the distinct expressions and prognostic values of related genes. The optimal cut-off values were 11.60 U/ml for P53, 4.90 U/ml for MAGEA1, 3.85 U/ml for SOX2, and 7.05U/ml for PGP9.5.

Results

We found that the stem signatures associated antibodies of MAGEA1, PGP9.5, SOX2, and TP53 exhibited high expressions in NSCLC, negatively correlating with the overall survival (OS) (P < 0.05). In the test groups, the diagnosis sensitivity of P53, PGP9.5, SOX2, and MAGEA1 reached to 21.5%, 39.0%, 50.3%, and 35.0%, respectively, and the specificity reached to 98.7%, 99.4%, 92.2%, and 97.4%. The four candidates’ panel gave a sensitivity of 71.8% with a specificity of 89%. In the validation group, the detection of the four antibodies in early diagnosis of NSCLC also exhibited high specificity and sensitivity, further consolidating their potential application.

Conclusions

The detection regarding stem signatures associated antibodies could be used as effective tools in early NSCLC diagnosis, but not for localized screening of cancers, and their abnormal expression was in accordance with poorer survival.

Nur mit Berechtigung zugänglich

Bach PB et al (2007) Computed tomography screening and lung cancer outcomes. JAMA 297(9):953–961CrossRef

Bach PB et al (2012) Benefits and harms of CT screening for lung cancer: a systematic review. JAMA 307(22):2418–2429CrossRef

Blandin Knight S et al (2017) Progress and prospects of early detection in lung cancer. Open Biol 7(9)

Boyle P et al (2011) Clinical validation of an autoantibody test for lung cancer. Ann Oncol 22(2):383–389CrossRef

Chapman CJ et al (2008) Autoantibodies in lung cancer: possibilities for early detection and subsequent cure. Thorax 63(3):228–233CrossRef

Chapman CJ et al (2012) EarlyCDT(R)-Lung test: improved clinical utility through additional autoantibody assays. Tumour Biol 33(5):1319–1326CrossRef

Croswell JM et al (2010) (2010) Cumulative incidence of false-positive test results in lung cancer screening: a randomized trial. Ann Intern Med 152(8):505–512 (W176-80)CrossRef

Grah JJ et al (2014) Clinical significance of immunohistochemical expression of cancer/testis tumor-associated antigens (MAGE-A1, MAGE-A3/4, NY-ESO-1) in patients with non-small cell lung cancer. Tumori 100(1):60–68CrossRef

Gyorffy B et al (2013) Online survival analysis software to assess the prognostic value of biomarkers using transcriptomic data in non-small-cell lung cancer. PLoS ONE 8(12):e82241CrossRef

Huang G et al (2019) TUSC7 suppression of Notch activation through sponging MiR-146 recapitulated the asymmetric cell division in lung adenocarcinoma stem cells. Life Sci 232:116630CrossRef

Kossenkov AV et al (2019) A gene expression classifier from whole blood distinguishes benign from malignant lung nodules detected by low-dose CT. Cancer Res 79(1):263–273CrossRef

Kulpa J et al (2002) Carcinoembryonic antigen, squamous cell carcinoma antigen, CYFRA 21–1, and neuron-specific enolase in squamous cell lung cancer patients. Clin Chem 48(11):1931–1937CrossRef

Lam S et al (2011) EarlyCDT-Lung: an immunobiomarker test as an aid to early detection of lung cancer. Cancer Prev Res (Phila) 4(7):1126–1134CrossRef

Li P et al (2017) Evaluation of serum autoantibodies against tumor-associated antigens as biomarkers in lung cancer. Tumour Biol 39(10):1010428317711662PubMed

Mauro C et al (2019) New and old biomarkers in the differential diagnosis of lung cancer: pro-gastrin-releasing peptide in comparison with neuron-specific enolase, carcinoembryonic antigen, and CYFRA 21-1. Int J Biol Mark 34(2):163–167. https://doi.org/10.1177/1724600819834235CrossRef

Mazzone PJ et al (2018) Evaluation of a serum lung cancer biomarker panel. Biomark Insights 13:1177271917751608CrossRef

Murray A et al (2010) Technical validation of an autoantibody test for lung cancer. Ann Oncol 21(8):1687–1693CrossRef

Nakamura H, Nishimura T (2017) History, molecular features, and clinical importance of conventional serum biomarkers in lung cancer. Surg Today 47(9):1037–1059CrossRef

National Lung Screening Trial Research T et al (2011) Reduced lung-cancer mortality with low-dose computed tomographic screening. N Engl J Med 365(5):395–409CrossRef

Oudkerk M et al (2017) European position statement on lung cancer screening. Lancet Oncol 18(12):e754–e766CrossRef

Rhodes DR et al (2004) ONCOMINE: a cancer microarray database and integrated data-mining platform. Neoplasia 6(1):1–6CrossRef

Rhodes DR et al (2007) Oncomine 3.0: genes, pathways, and networks in a collection of 18,000 cancer gene expression profiles. Neoplasia 9(2):166–180CrossRef

Roberts H et al (2013) Screening high-risk populations for lung cancer: guideline recommendations. J Thorac Oncol 8(10):1232–1237CrossRef

Seijo LM et al (2019) Biomarkers in lung cancer screening: achievements, promises, and challenges. J Thorac Oncol 14(3):343–357CrossRef

Siegel RL, Miller KD, Jemal A (2017) Cancer Statistics, 2017. CA Cancer J Clin 67(1):7–30CrossRef

Sun X et al (2015) MiR-208a stimulates the cocktail of SOX2 and beta-catenin to inhibit the let-7 induction of self-renewal repression of breast cancer stem cells and formed miR208a/let-7 feedback loop via LIN28 and DICER1. Oncotarget 6(32):32944–32954CrossRef

Tang Z et al (2017) GEPIA: a web server for cancer and normal gene expression profiling and interactive analyses. Nucleic Acids Res 45(W1):W98–W102CrossRef

Vargas AJ, Harris CC (2016) Biomarker development in the precision medicine era: lung cancer as a case study. Nat Rev Cancer 16(8):525–537CrossRef

Vatankulu B et al (2016) Accuracy of FDG-PET/CT and paraneoplastic antibodies in diagnosing cancer in paraneoplastic neurological syndromes. Rev Esp Med Nucl Imagen Mol 35(1):17–21PubMed

Wang M et al (2019) H19 regulation of oestrogen induction of symmetric division is achieved by antagonizing Let-7c in breast cancer stem-like cells. Cell Prolif 52(1):e12534CrossRef

Wang H et al (2020) Long noncoding RNA LINC01116 contributes to gefitinib resistance in non-small cell lung cancer through regulating IFI44. Mol Ther Nucl Acids 19:218–227CrossRef

Xiao G et al (2019) FAM83A-AS1 promotes lung adenocarcinoma cell migration and invasion by targeting miR-150-5p and modifying MMP14. Cell Cycle 18(21):2972–2985CrossRef

Yao Y et al (2012) Potential application of non-small cell lung cancer-associated autoantibodies to early cancer diagnosis. Biochem Biophys Res Commun 423(3):613–619CrossRef

Titel: Stem signatures associated antibodies yield early diagnosis and precise prognosis predication of patients with non-small cell lung cancer
verfasst von: Si-Si Chen
Kai Li
Jie Wu
Zi-Yang Peng
Zhi-Dong Wang
Ji-Chang Wang
Chong-Wen Xu
Cai-lin Zhu
Bao-Cheng Li
Hong Ren
Shou-Ching Tang
Xin Sun
Publikationsdatum: 20.07.2020
Verlag: Springer Berlin Heidelberg
Erschienen in: Journal of Cancer Research and Clinical Oncology / Ausgabe 1/2021
Print ISSN: 0171-5216
Elektronische ISSN: 1432-1335
DOI: https://doi.org/10.1007/s00432-020-03325-4

Springer Medizin

Stem signatures associated antibodies yield early diagnosis and precise prognosis predication of patients with non-small cell lung cancer