Evidence map›Paper›PMID 38182978›Full record

ArticleClinical proteomics2024

Prognostic biomarker discovery based on proteome landscape of Chinese lung adenocarcinoma.

Yuqi Huang, Sheng Ma, Jun-Yu Xu, Kun Qian, Yaru Wang, Yi Zhang, Minjia Tan, Ting Xiao

Abstract read
In one paragraph

Article in Clinical proteomics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
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

4 citing papers in PubMed.

  1. Article
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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

8 authors.

Yuqi Huang *State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China.
Sheng Ma *State Key Laboratory of Molecular Oncology, Department of Etiology and Carcinogenesis, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
Jun-Yu Xu *State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China. jyxu@simm.ac.cn.
Kun QianDepartment of Thoracic Surgery, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
Yaru WangState Key Laboratory of Molecular Oncology, Department of Etiology and Carcinogenesis, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
Yi ZhangDepartment of Thoracic Surgery, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China. steven9130@sina.com.
Minjia TanState Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China. mjtan@simm.ac.cn.
Ting XiaoState Key Laboratory of Molecular Oncology, Department of Etiology and Carcinogenesis, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China. xiaot@cicams.ac.cn.

Funding

Guangdong High-level Innovative Research Institute 2021B0909050003Guangdong High-level new R&D Institute 2019B090904008National Key Research and Development Program of China 2020YFE0202200National Natural Science Foundation of China 22225702National Natural Science Foundation of China 32322048Shanghai Rising-Star Program 22QA1411100Young Elite Scientists Sponsorship Program by CAST 2022QNRC001Youth Innovation Promotion Association of the Chinese Academy of Sciences 2021276
6 · The paper itself

Abstract

Despite recent innovations in imaging and genomic screening promotes advance in diagnosis and treatment of lung adenocarcinoma (LUAD), there remains high mortality of LUAD and insufficient understanding of LUAD biology. Our previous study performed an integrative multi-omic analysis of LUAD, filling the gap between genomic alterations and their biological proteome effects. However, more detailed molecular characterization and biomarker resources at proteome level still need to be uncovered. In this study, a quantitative proteomic experiment of patient-derived benign lung disease samples was carried out. After that, we integrated the proteomic data with previous dataset of 103 paired LUAD samples. We depicted the proteomic differences between non-cancerous and tumor samples and among diverse pathological subtypes. We also found that up-regulated mitophagy was a significant characteristic of early-stage LUAD. Additionally, our integrative analysis filtered out 75 potential prognostic biomarkers and validated two of them in an independent LUAD serum cohort. This study provided insights for improved understanding proteome abnormalities of LUAD and the novel prognostic biomarker discovery offered an opportunity for LUAD precise management.

Indexed as

Benign lung disease casesLung adenocarcinomaPrognostic biomarkerProteomeSolid pathological subtype

Identifiers

PMID38182978
PMCPMC10768252

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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.