Evidence map›Paper›PMID 34735995›Full record

ArticleNeoplasia (New York, N.Y.)2021

Genomic landscape of metastatic lung adenocarcinomas from large-scale clinical sequencing.

Dingbiao Li, Yong Huang, Lijun Cai, Min Wu, Hua Bao, Yang Xu, Yulin Wei, Shuyu Wu, Xue Wu, Yang Shao and 5 more

Abstract read
In one paragraph

Article in Neoplasia (New York, N.Y.), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Molecular and clinical disparity ofTranslational lung cancer research · 2026
    Article
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  5. Article
  6. Article
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  8. Review
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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

15 authors.

Dingbiao LiDepartment of Thoracic Surgery, Kunming Yan'an Hospital, Yunnan Provincial Key Laboratory of Cancer Immune Prevention and Control, Yan'an Affiliated Hospital of Kunming Medical University, Kunming 650051, China.
Yong HuangChongqing General Hospital, University of Chinese Academy of Sciences, Chongqing, China.
Lijun CaiCancer Center, Sichuan Academy of Medical Sciences and Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu 610072, China.
Min WuNanjing Geneseeq Technology Inc., Nanjing 210032, China.
Hua BaoNanjing Geneseeq Technology Inc., Nanjing 210032, China.
Yang XuNanjing Geneseeq Technology Inc., Nanjing 210032, China.
Yulin WeiNanjing Geneseeq Technology Inc., Nanjing 210032, China.
Shuyu WuNanjing Geneseeq Technology Inc., Nanjing 210032, China.
Xue WuNanjing Geneseeq Technology Inc., Nanjing 210032, China.
Yang ShaoNanjing Geneseeq Technology Inc., Nanjing 210032, China; School of Public Health, Nanjing Medical University, Nanjing 211166, China.
Wei ZhaoDepartment of Thoracic Surgery, First Affiliated Hospital of Kunming Medical University, Kunming 650032, China.
Guoli LvDepartment of Thoracic Surgery, First Affiliated Hospital of Kunming Medical University, Kunming 650032, China.
Shan HuangCancer Center, Sichuan Academy of Medical Sciences and Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu 610072, China. Electronic address: Shan_huang2020@126.com.
Tao ZhangDepartment of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 100021, China.. Electronic address: zhangt10@126.com.
Yunfei ShiDepartment of Thoracic Surgery, First Affiliated Hospital of Kunming Medical University, Kunming 650032, China.. Electronic address: km-syf@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMetastases are responsible for over 70% of deaths from lung adenocarcinomas. Previous large-scale studies of LUAD mainly focused on primary diseases. We aimed to comprehensively analyze the genomic landscape of metastatic LUADs and elucidate its clinical implications in the context of precision medicine.

methodsWe performed retrospective analyses on targeted sequencing data of 3,743 primary tumors and 934 metastases from 4,480 patients with lung adenocarcinomas, and PD-L1 immunohistochemical data of 1,336 primary tumors and 252 metastases from 1,588 LUAD patients.

resultsMetastases generally manifested significantly higher mutational burdens and chromosomal instability than primary lung adenocarcinomas. Clinically actionable alterations, including ALK mutations, ALK and ROS1 fusions, and MET copy number gains, were enriched in metastases, particularly metastases to some specific organs/tissues, such as lymph nodes, liver, and brain. PD-L1 expression decreased as the approximate metastatic distance increased. Additional data of paired primary tumors and metastases to lymph nodes and brain validated patterns of actionable alterations and candidates for metastatic drivers. Two evolutionary modes of metastatic dissemination, common origins and distinct origins, were identified in both types of primary-metastasis pairs.

conclusionsOur study showed heterogenous patterns of clinically actionable alterations, PD-L1 expressions, metastatic driver candidates, and evolutionary patterns among multiple types of metastases of lung adenocarcinomas, which may advise the planning of treatments and the identification of novel therapeutic targets.

Indexed as

Adenocarcinoma of LungBiomarkers, TumorGene Expression ProfilingHigh-Throughput Nucleotide SequencingHumansLung NeoplasmsNeoplasm MetastasisRetrospective StudiesSequence Analysis, DNABiomarkers, TumorGenomic profilingMetastasisNSCLCTherapeutic target

Identifiers

PMID34735995
PMCPMC8571538

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Registered trials

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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.