Evidence map›Paper›PMID 35962452›Full record

ArticleGenome medicine2022

Molecular profiling of human non-small cell lung cancer by single-cell RNA-seq.

Qingqing Li, Rui Wang, Zhenlin Yang, Wen Li, Jingwei Yang, Zhijie Wang, Hua Bai, Yueli Cui, Yanhua Tian, Zixin Wu and 6 more

Open access · goldAbstract read
In one paragraph

Article in Genome medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 59 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
59citing papers in PubMed, 1 pooled it
6.2field-weighted citation impact, top 2% 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

59 citing papers in PubMed, 1 synthesis or guideline pooled it, 70 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

16 authors at 3 institutions in 1 country.

Qingqing Li *Biomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing, China.
Rui Wang *Biomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing, China.
Zhenlin Yang *State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Wen LiBiomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing, China.
Jingwei YangBiomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing, China.
Zhijie WangState Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Hua BaiState Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Yueli CuiBiomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing, China.
Yanhua TianState Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Zixin WuBiomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing, China.
Yuqing GuoBiomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing, China.
Jiachen XuState Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Lu WenBiomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing, China.
Jie HeState Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China. hejie@cicams.ac.cn.
Fuchou TangBiomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing, China. tangfuchou@pku.edu.cn.
Jie WangState Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China. zlhuxi@163.com.
Peking University · CNChinese Academy of Medical Sciences & Peking Union Medical College · CNCenter for Life Sciences · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLung cancer, one of the most common malignant tumors, exhibits high inter- and intra-tumor heterogeneity which contributes significantly to treatment resistance and failure. Single-cell RNA sequencing (scRNA-seq) has been widely used to dissect the cellular composition and characterize the molecular properties of cancer cells and their tumor microenvironment in lung cancer. However, the transcriptomic heterogeneity among various cancer cells in non-small cell lung cancer (NSCLC) warrants further illustration.

methodsTo comprehensively analyze the molecular heterogeneity of NSCLC, we performed high-precision single-cell RNA-seq analyses on 7364 individual cells from tumor tissues and matched normal tissues from 19 primary lung cancer patients and 1 pulmonary chondroid hamartoma patient.

resultsIn 6 of 16 patients sequenced, we identified a significant proportion of cancer cells simultaneously expressing classical marker genes for two or even three histologic subtypes of NSCLC-adenocarcinoma (ADC), squamous cell carcinoma (SCC), and neuroendocrine tumor (NET) in the same individual cell, which we defined as mixed-lineage tumor cells; this was verified by both co-immunostaining and RNA in situ hybridization. These data suggest that mixed-lineage tumor cells are highly plastic with mixed features of different types of NSCLC. Both copy number variation (CNV) patterns and mitochondrial mutations clearly showed that the mixed-lineage and single-lineage tumor cells from the same patient had common tumor ancestors rather than different origins. Moreover, we revealed that patients with high mixed-lineage features of different cancer subtypes had worse survival than patients with low mixed-lineage features, indicating that mixed-lineage tumor features were associated with poorer prognosis. In addition, gene signatures specific to mixed-lineage tumor cells were identified, including AKR1B1. Gene knockdown and small molecule inhibition of AKR1B1 can significantly decrease cell proliferation and promote cell apoptosis, suggesting that AKR1B1 plays an important role in tumorigenesis and can serve as a candidate target for tumor therapy of NSCLC patients with mixed-lineage tumor features.

conclusionsIn summary, our work provides novel insights into the tumor heterogeneity of NSCLC in terms of the identification of prevalent mixed-lineage subpopulations of cancer cells with combined signatures of SCC, ADC, and NET and offers clues for potential treatment strategies in these patients.

Indexed as

AdenocarcinomaCarcinoma, Non-Small-Cell LungCarcinoma, Squamous CellLung NeoplasmsAldehyde ReductaseBiomarkers, TumorDNA Copy Number VariationsGene Expression Regulation, NeoplasticHumansPrognosisRNA-SeqTumor MicroenvironmentAKR1B1 protein, humanAldehyde ReductaseBiomarkers, TumorMixed-lineage cancer cellsNon-small cell lung cancerSingle-cell RNA sequencingTumor heterogeneity

Identifiers

PMID35962452
PMCPMC9375433
OpenAlexW4290960388

What OpenQuestion holds

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LicenceCC BY
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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.