Evidence map›Paper›PMID 37639013›Full record

ArticleJournal of cancer research and clinical oncology2023

Hsa_circ_0041150 serves as a novel biomarker for monitoring chemotherapy resistance in small cell lung cancer patients treated with a first-line chemotherapy regimen.

Yang Zhang, Fengmei Chao, Lihua Lv, Ming Li, Zuojun Shen

Open access · hybridAbstract read
In one paragraph

Article in Journal of cancer research and clinical oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.5field-weighted citation impact, top 17% 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

9 citing papers in PubMed, 10 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
  4. Article
  5. Review
  6. Recent advances of circular RNAs in gastrointestinal cancer.World journal of clinical oncology · 2025
    Review
  7. Review
  8. Liquid biopsy techniques and lung cancer: diagnosis, monitoring and evaluation.Journal of experimental & clinical cancer research : CR · 2024
    Review
  9. Review
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

5 authors at 1 institution in 1 country.

Yang ZhangCheeloo College of Medicine, Shandong University, Jinan, China.ORCID http://orcid.org/0009-0009-2238-8273
Fengmei ChaoDivision of Life Sciences and Medicine, Department of Cancer Epigenetics Program, The First Affiliated Hospital of USTC, University of Science and Technology of China, Hefei, 230001, Anhui, China.
Lihua LvDepartment of Laboratory Medicine, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230031, Anhui, China.
Ming LiDepartment of Laboratory Medicine, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230031, Anhui, China. lm831216@ustc.edu.cn.
Zuojun ShenCheeloo College of Medicine, Shandong University, Jinan, China. zuojunshen@ustc.edu.cn.
University of Science and Technology of China · CN

Funding

the Fundamental Research Funds for the Central Universities WK911000057the Key Programs for Research and Development of Anhui Province No.1704a0802153the Project of the Science and Technology Innovation of Anhui province 2017070802D146the Youth Fund of Anhui Cancer Hospital No. 2023YJQN009the Youth Fund of the Natural Science Foundation of Anhui Province 2208085QH259
6 · The paper itself

Abstract

purposeTo explore the potential of circRNAs as biomarkers in non-invasive body fluids for monitoring chemotherapy resistance in SCLC patients.

methodsCircRNAs were screened and characterized using transcriptome sequencing, Sanger sequencing, actinomycin D treatment, and Ribonuclease R assay. Our study involved 174 participants, and serum samples were collected from all chemotherapy-resistant patients (n = 54) at two time points: stable disease and progressive disease. We isolated and identified serum extracellular vesicles (EVs) from the patients using ultracentrifugation, transmission electron microscopy, nanoflow cytometry, and western blotting analysis. The expression levels of serum and serum EVs circRNAs were determined by quantitative real-time polymerase chain reaction (qRT-PCR). The impact of circRNA on the function of SCLC cells was assessed through various assays, including proliferation assay, scratch assay, transwell assay, and cisplatin resistance assay.

resultsHsa_circ_0041150 was found to be upregulated in chemoresistant SCLC cells and played a role in promoting proliferation, invasion, migration, and cisplatin resistance. Furthermore, the expression levels of hsa_circ_0041150 in serum and serum EVs increased when SCLC patients developed resistance after a first-line chemotherapy regimen. When combined with NSE, the monitoring sensitivity (70.37%) and specificity (81.48%) for chemotherapy resistance significantly improved. Moreover, the expression level of hsa_circ_0041150 showed significant associations with time to progression from SD to PD, and high hsa_circ_0041150 levels after drug resistance were more likely to cause chemotherapy resistance. Additionally, hsa_circ_0041150 demonstrated valuable potential in monitoring the progression from initial diagnosis to chemotherapy resistance in SCLC patients.

conclusionThus, EVs hsa_circ_0041150 holds promise as a biomarker for monitoring chemotherapy resistance in SCLC patients.

Indexed as

Lung NeoplasmsMicroRNAsSmall Cell Lung CarcinomaBiomarkersCell ProliferationCisplatinHumansRNA, CircularBiomarkersCisplatinMicroRNAsRNA, CircularExtracellular vesicleshsa_circ_0041150Monitor chemoresistanceSmall cell lung cancer

Identifiers

PMID37639013
PMCPMC10620281
OpenAlexW4386209834

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.