Evidence map›Paper›PMID 31182966›Full record

ArticleCellular & molecular biology letters2019

Transcriptome profiling revealed multiple genes and ECM-receptor interaction pathways that may be associated with breast cancer.

Yulong Bao, Li Wang, Lin Shi, Fen Yun, Xia Liu, Yongxia Chen, Chen Chen, Yanni Ren, Yongfeng Jia

Open access · goldAbstract read
In one paragraph

Article in Cellular & molecular biology letters, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 211 papers.

0numbers the graph read from it
0cells of the map it votes in
211citing papers in PubMed
29.5field-weighted citation impact, top 1% 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

211 citing papers in PubMed, 385 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Identification of novel molecular subtypes in ovarian cancerThe Korean journal of physiology & pharmacology : official journal of the Korean Physiological Society and the Korean Society of Pharmacology · 2026
    Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article

151 more citing papers are in PubMed but not listed here.

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

9 authors at 2 institutions in 1 country.

Yulong Bao *1College of Basic Medicine, Inner Mongolia Medical University, Hohhot, Inner Mongolia China.
Li Wang *1College of Basic Medicine, Inner Mongolia Medical University, Hohhot, Inner Mongolia China.
Lin Shi2Department of Pathology, Inner Mongolia Medical University, Hohhot, Inner Mongolia China.
Fen Yun2Department of Pathology, Inner Mongolia Medical University, Hohhot, Inner Mongolia China.
Xia Liu2Department of Pathology, Inner Mongolia Medical University, Hohhot, Inner Mongolia China.
Yongxia ChenTumor Molecular Diagnostic Laboratory, The Inner Mongolia Cancer Hospital, Hohhot, Inner Mongolia China.
Chen Chen2Department of Pathology, Inner Mongolia Medical University, Hohhot, Inner Mongolia China.
Yanni Ren2Department of Pathology, Inner Mongolia Medical University, Hohhot, Inner Mongolia China.
Yongfeng Jia1College of Basic Medicine, Inner Mongolia Medical University, Hohhot, Inner Mongolia China.ORCID 0000-0002-4806-499X
Inner Mongolia Medical University · CNInner Mongolia People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundExploration of the genes with abnormal expression during the development of breast cancer is essential to provide a deeper understanding of the mechanisms involved. Transcriptome sequencing and bioinformatics analysis of invasive ductal carcinoma and paracancerous tissues from the same patient were performed to identify the key genes and signaling pathways related to breast cancer development.

methodsSamples of breast tumor tissue and paracancerous breast tissue were obtained from 6 patients. Sequencing used the Illumina HiSeq platform. All. Only perfectly matched clean reads were mapped to the reference genome database, further analyzed and annotated based on the reference genome information. Differentially expressed genes (DEGs) were identified using the DESeq R package (1.10.1) and DEGSeq R package (1.12.0). Using KOBAS software to execute the KEGG bioinformatics analyses, enriched signaling pathways of DEGs involved in the occurrence of breast cancer were determined. Subsequently, quantitative real time PCR was used to verify the accuracy of the expression profile of key DEGs from the RNA-seq result and to explore the expression patterns of novel cancer-related genes on 8 different clinical individuals.

resultsThe transcriptomic sequencing results showed 937 DEGs, including 487 upregulated and 450 downregulated genes in the breast cancer specimens. Further quantitative gene expression analysis was performed and captured 252 DEGs (201 downregulated and 51 upregulated) that showed the same differential expression pattern in all libraries. Finally, 6 upregulated DEGs (CST2, DRP2, CLEC5A, SCD, KIAA1211, DTL) and 6 downregulated DEGs (STAC2, BTNL9, CA4, CD300LG, GPIHBP1 and PIGR), were confirmed in a quantitative real time PCR comparison of breast cancer and paracancerous breast tissues from 8 clinical specimens. KEGG analysis revealed various pathway changes, including 20 upregulated and 21 downregulated gene enrichment pathways. The extracellular matrix-receptor (ECM-receptor) interaction pathway was the most enriched pathway: all genes in this pathway were DEGs, including the THBS family, collagen and fibronectin. These DEGs and the ECM-receptor interaction pathway may perform important roles in breast cancer.

conclusionSeveral potential breast cancer-related genes and pathways were captured, including 7 novel upregulated genes and 76 novel downregulated genes that were not found in other studies. These genes are related to cell proliferation, movement and adhesion. They may be important for research into breast cancer mechanisms, particularly CST2 and CA4. A key signaling pathway, the ECM-receptor interaction signal pathway, was also identified as possibly involved in the development of breast cancer.

Indexed as

Gene Expression ProfilingGene Expression Regulation, NeoplasticBreast NeoplasmsDown-RegulationFemaleHumansNeoplasm ProteinsReceptors, Cell SurfaceReproducibility of ResultsSequence Analysis, RNASignal TransductionTranscriptomeUp-Regulationextracellular matrix receptorNeoplasm ProteinsReceptors, Cell SurfaceBreast cancerDifferentially expressed genesECM-receptor interaction pathwayTranscriptome

Identifiers

PMID31182966
PMCPMC6554968
OpenAlexW2948388080

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.