Evidence map›Paper›PMID 35078435›Full record

ArticleBMC cancer2022

Identification of TIMELESS and RORA as key clock molecules of non-small cell lung cancer and the comprehensive analysis.

Haocheng Xian, Yuan Li, Boliang Zou, Yajuan Chen, Houqing Yin, Xuejun Li, Yan Pan

Open access · goldAbstract read
In one paragraph

Article in BMC cancer, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
5.5field-weighted citation impact, top 3% 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

20 citing papers in PubMed, 29 citations in OpenAlex.

  1. Article
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  4. Circadian clock and cancer.Military Medical Research · 2026
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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

7 authors at 2 institutions in 1 country.

Haocheng XianDepartment of Pharmacology, School of Basic Medical Sciences, Health Science Center, Peking University, Beijing, 100191, China.
Yuan LiDepartment of Pharmacology, School of Basic Medical Sciences, Health Science Center, Peking University, Beijing, 100191, China.
Boliang ZouDepartment of Pharmacology, School of Basic Medical Sciences, Health Science Center, Peking University, Beijing, 100191, China.
Yajuan ChenDepartment of Rehabilitation Medicine, Kunming Medical University, 1168 Western Chunrong Road, Yuhua Street, Chenggong District, Kunming, 650500, Yunnan, China.
Houqing YinDepartment of Pharmacology, School of Basic Medical Sciences, Health Science Center, Peking University, Beijing, 100191, China.
Xuejun LiDepartment of Pharmacology, School of Basic Medical Sciences, Health Science Center, Peking University, Beijing, 100191, China.
Yan PanDepartment of Pharmacology, School of Basic Medical Sciences, Health Science Center, Peking University, Beijing, 100191, China. pannay26@bjmu.edu.cn.
Peking University · CNKunming Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe incidence rate of non-small cell lung cancer (NSCLC) has been increasing worldwide, and the correlation of circadian rhythm disruption with a raised risk of cancer and worse prognosis has been shown by accumulating evidences recently. On the other hand, drug resistance and the impact of tumor heterogeneity have been inevitable in NSCLC therapy. These both lead to an urgent need to identify more useful prognostic and predictive markers for NSCLC diagnosis and treatment, especially on the aspect of circadian clock genes.

methodsThe expression of the main clock genes in cancer was probed with TIMER and Oncomine databases. The prognostic value of key clock genes was probed systematically with the Kaplan-Meier estimate and Cox regression on samples from TCGA database. RT-qPCR was performed on patient tissue samples to further validate the results from databases. The functional enrichment analysis was performed using the "ClusterProfiler" R package, and the correlation of key clock genes with tumor mutation burden, immune checkpoint, and immune infiltration levels were also assessed using multiple algorithms including TIDE, TIMER2.0, and XCELL.

resultsTIMELESS was significantly upregulated in lung tissue of clinical lung cancer patients as well as TCGA and Oncomine databases, while RORA was downregulated. Multivariate Cox regression analysis indicated that TIMELESS (P = 0.004, HR = 1.21 [1.06, 1.38]) and RORA (P = 0.047, HR = 0.868 [0.755, 0.998]) has a significant correlation with overall survival in NSCLC. Genes related to TIMELESS were enriched in the cell cycle and immune system, and the function of RORA was mainly focused on oncogenic signaling pathways or glycosylation and protein activation. Also, TIMELESS was positively correlated with tumor mutation burden while RORA was negatively correlated with it. TIMELESS and RORA were also significantly correlated with immune checkpoint and immune infiltration levels in NSCLC. Additionally, TIMELESS showed a significant positive relationship with lipid metabolism.

conclusionsTIMELESS and RORA were identified as key clock genes in NSCLC, and were independent prognostic factors for overall survival in NSCLC. The function of them were assessed in many aspects, indicating the strong potential of the two genes to serve as biomarkers for NSCLC progression and prognosis.

Indexed as

Biomarkers, TumorCarcinoma, Non-Small-Cell LungCell Cycle ProteinsCircadian ClocksCircadian RhythmGene Expression Regulation, NeoplasticHumansIntracellular Signaling Peptides and ProteinsKaplan-Meier EstimateLung NeoplasmsMutationNuclear Receptor Subfamily 1, Group F, Member 1PrognosisProportional Hazards ModelsBiomarkers, TumorCell Cycle ProteinsIntracellular Signaling Peptides and ProteinsNuclear Receptor Subfamily 1, Group F, Member 1RORA protein, humanTIMELESS protein, humanBioinformaticsCircadian clock genesNon-small cell lung cancerRORATIMELESS

Identifiers

PMID35078435
PMCPMC8788117
OpenAlexW4207026254

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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.