Evidence map›Paper›PMID 36634615›Full record

ArticleCancer research and treatment2023

Genomic Characteristics and the Potential Clinical Implications in Oligometastatic Non-Small Cell Lung Cancer.

Rongxin Liao, Kehong Chen, Jinjin Li, Hengqiu He, Guangming Yi, Mingfeng Huang, Rongrong Chen, Lu Shen, Xiaoyue Zhang, Zaicheng Xu and 2 more

Open access · diamondAbstract read
In one paragraph

Article in Cancer research and treatment, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.3field-weighted citation impact, top 19% 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

6 citing papers in PubMed, 5 citations in OpenAlex.

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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

12 authors at 3 institutions in 1 country.

Rongxin LiaoDepartment of Cancer Center, Second Affiliated Hospital, Chongqing Medical University, Chongqing, China.
Kehong ChenDepartment of Cancer Center, Second Affiliated Hospital, Chongqing Medical University, Chongqing, China.
Jinjin LiDepartment of Cancer Center, Second Affiliated Hospital, Chongqing Medical University, Chongqing, China.
Hengqiu HeDepartment of Cancer Center, Second Affiliated Hospital, Chongqing Medical University, Chongqing, China.
Guangming YiDepartment of Cancer Center, Second Affiliated Hospital, Chongqing Medical University, Chongqing, China.
Mingfeng HuangGeneplus-Beijing, Beijing, China.
Rongrong ChenGeneplus-Beijing, Beijing, China.
Lu ShenGeneplus-Beijing, Beijing, China.
Xiaoyue ZhangDepartment of Cancer Center, Second Affiliated Hospital, Chongqing Medical University, Chongqing, China.
Zaicheng XuDepartment of Cancer Center, Second Affiliated Hospital, Chongqing Medical University, Chongqing, China.
Zhenzhou YangDepartment of Cancer Center, Second Affiliated Hospital, Chongqing Medical University, Chongqing, China.
Yuan PengDepartment of Cancer Center, Second Affiliated Hospital, Chongqing Medical University, Chongqing, China.
Chongqing Medical University · CNSecond Affiliated Hospital of Chongqing Medical University · CNDalian Medical University · CN

Funding

Chongqing Talents Program CQYC20200303151Hospital of Chongqing Medical University KRYC-YQ-2116Municipal Natural Science Foundation of Chongqing cstc2020jcyj-msxmX0208Yuan Peng and the Project of Chongqing Technology Innovation and Application Development CSTC2021jscx-gksb-N0022
6 · The paper itself

Abstract

purposeOligometastatic non-small cell lung cancer (NSCLC) patients have been increasingly regarded as a distinct group that could benefit from local treatment to achieve a better clinical outcome. However, current definitions of oligometastasis are solely numerical, which are imprecise because of ignoring the biological heterogeneity caused by genomic characteristics. Our study aimed to profile the molecular alterations of oligometastatic NSCLC and elucidate its potential difference from polymetastasis. Materials and Methods: We performed next-generation sequencing to analyze tumors and paired peripheral blood from 77 oligometastatic and 21 polymetastatic NSCLC patients to reveal their genomic characteristics and assess the genetic heterogeneity.

resultsWe found ERBB2, ALK, MLL4, PIK3CB, and TOP2A were mutated at a significantly lower frequency in oligometastasis compared with polymetastasis. EGFR and KEAP1 alterations were mutually exclusive in oligometastatic group. More importantly, oligometastasis has a unique significant enrichment of apoptosis signaling pathway. In contrast to polymetastasis, a highly enriched COSMIC signature 4 and a special mutational process, COSMIC signature 14, were observed in the oligometastatic cohort. According to OncoKB database, 74.03% of oligometastatic NSCLC patients harbored at least one actionable alteration. The median tumor mutation burden of oligometastasis was 5.00 mutations/Mb, which was significantly associated with smoking, DNA damage repair genes, TP53 mutation, SMARCA4 mutation, LRP1B mutation, ABL1 mutation.

conclusionOur results shall help redefine oligometastasis beyond simple lesion enumeration that will ultimately improve the selection of patients with real oligometastatic state and optimize personalized cancer therapy for oligometastatic NSCLC.

Indexed as

Carcinoma, Non-Small-Cell LungLung NeoplasmsDNA HelicasesGenomicsHigh-Throughput Nucleotide SequencingHumansKelch-Like ECH-Associated Protein 1MutationNF-E2-Related Factor 2Nuclear ProteinsTranscription FactorsDNA HelicasesKelch-Like ECH-Associated Protein 1NF-E2-Related Factor 2Nuclear ProteinsSMARCA4 protein, humanTranscription FactorsGenomic profilingHigh-throughput nucleotide sequencingNon–small cell lung cancerOligometastaticTumor mutational burden

Identifiers

PMID36634615
PMCPMC10372584
OpenAlexW4315927685

What OpenQuestion holds

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LicenceCC BY-NC
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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.