Evidence map›Paper›PMID 27467958›Full record

ArticleOncoimmunology2016

Serum anti-MDM2 and anti-c-Myc autoantibodies as biomarkers in the early detection of lung cancer.

Pei Li, Jian-Xiang Shi, Li-Ping Dai, Yu-Rong Chai, Hong-Fei Zhang, Mutombo Kankonde, Peggy Kankonde, Bao-Fa Yu, Jian-Ying Zhang

Open access · goldAbstract read
In one paragraph

Article in Oncoimmunology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
2.3field-weighted citation impact, top 12% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed, 31 citations in OpenAlex.

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  8. Autoimmune Responses in Oncology: Causes and Significance.International journal of molecular sciences · 2021
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 2 institutions in 2 countries.

Pei LiThe Academy of Medical Sciences, Zhengzhou University, Zhengzhou, Henan, China; Department of Biological Sciences, The University of Texas at El Paso, 500 W University Ave, El Paso, TX, USA.
Jian-Xiang ShiThe Academy of Medical Sciences, Zhengzhou University, Zhengzhou, Henan, China; Department of Biological Sciences, The University of Texas at El Paso, 500 W University Ave, El Paso, TX, USA; Henan Key Laboratory for Tumor Epidemiology, College of Public Health, Zhengzhou University, Zhengzhou, Henan, China.
Li-Ping DaiThe Academy of Medical Sciences, Zhengzhou University, Zhengzhou, Henan, China; Department of Biological Sciences, The University of Texas at El Paso, 500 W University Ave, El Paso, TX, USA; Henan Key Laboratory for Tumor Epidemiology, College of Public Health, Zhengzhou University, Zhengzhou, Henan, China.
Yu-Rong ChaiThe Academy of Medical Sciences, Zhengzhou University, Zhengzhou, Henan, China; Department of Biological Sciences, The University of Texas at El Paso, 500 W University Ave, El Paso, TX, USA.
Hong-Fei ZhangThe Academy of Medical Sciences, Zhengzhou University, Zhengzhou, Henan, China; Department of Biological Sciences, The University of Texas at El Paso, 500 W University Ave, El Paso, TX, USA; Henan Key Laboratory for Tumor Epidemiology, College of Public Health, Zhengzhou University, Zhengzhou, Henan, China.
Mutombo KankondeGreater East Cancer Center & Coalition for the Reversal of Breast Cancer Mortality in African American Women , El Paso, TX, USA.
Peggy KankondeGreater East Cancer Center & Coalition for the Reversal of Breast Cancer Mortality in African American Women , El Paso, TX, USA.
Bao-Fa YuBeijing Baofa Tumor Hospital , Changping Dist, Beijing, China.
Jian-Ying ZhangThe Academy of Medical Sciences, Zhengzhou University, Zhengzhou, Henan, China; Department of Biological Sciences, The University of Texas at El Paso, 500 W University Ave, El Paso, TX, USA; Henan Key Laboratory for Tumor Epidemiology, College of Public Health, Zhengzhou University, Zhengzhou, Henan, China.
The University of Texas at El Paso · USZhengzhou University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aims to investigate the clinical significance of serum autoantibodies against MDM2 and c-Myc and evaluate their feasibility in the immunodiagnosis of lung cancer. 50 sera samples with 43 available paired lung cancer tissue and adjacent normal tissue slides with follow up information and 44 sera from normal human controls (NHC) were used in the research group. Another 62 lung cancer sera and 43 NHC sera were used in the validation group. The results of IHC showed that MDM2 and c-Myc protein were overexpressed in lung cancer tissues compared to adjacent normal tissues (p < 0.001). Likewise, significantly higher levels of serum autoantibodies against MDM2 and c-Myc were found in lung cancer compared to NHC both in research and validation groups. Further analysis on IHC and ELISA results showed that serum level of autoantibodies against these two TAAs were positively associated with tissue staining scores (both p < 0.05). The area under curve (AUC) values of anti-MDM2 and anti-cMyc autoantibodies for discriminating lung cancers from NHC were 0.698 and 0.636 in research group, 0.777 and 0.815 in the validation group, respectively. Both anti-MDM2 and anti-c-Myc autoantibodies can discriminate stage I lung cancer patients from NHC with AUC values of 0.703 and 0.662. Kaplan-Meier analysis showed that higher level of serum anti-c-Myc autoantibodies was significantly related to shortened disease-free survival (DFS) (p = 0.041). In conclusion, our finding suggested that serum MDM2 and c-Myc autoantibodies may have the potential to serve as non-invasive diagnostic biomarkers in patients with lung cancer.

Indexed as

Autoantibodybiomarkerc-Mycimmunodiagnosislung cancerMDM2tumor-associated antigen

Identifiers

PMID27467958
PMCPMC4910725
OpenAlexW2336043554

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.