Evidence map›Paper›PMID 32753032›Full record

ArticleBMC medical genomics2020

Fusion transcript detection using spatial transcriptomics.

Stefanie Friedrich, Erik L L Sonnhammer

Open access · goldAbstract read
In one paragraph

Article in BMC medical genomics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.5field-weighted citation impact, top 18% 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

10 citing papers in PubMed, 22 citations in OpenAlex.

  1. Review
  2. Pattern recognition in the landscape of seemingly random chimeric transcripts.Computational and structural biotechnology journal · 2023
    Article
  3. Novel insights from spatial transcriptome analysis in solid tumors.International journal of biological sciences · 2023
    Review
  4. Review
  5. Single-Cell RNA Sequencing with Spatial Transcriptomics of Cancer Tissues.International journal of molecular sciences · 2022
    Review
  6. Review
  7. Review
  8. Review
  9. Spatially resolved transcriptomics and its applications in cancer.Current opinion in genetics & development · 2021
    Review
  10. Full-Length Transcriptome Analysis ofFrontiers in cellular and infection microbiology · 2021
    Article
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

2 authors at 1 institution in 1 country.

Stefanie FriedrichScience for Life Laboratory, Department of Biochemistry and Biophysics, Stockholm University, Box 1031, 17121, Solna, Sweden. stefanie.friedrich@scilifelab.se.ORCID 0000-0002-3889-5589
Erik L L SonnhammerScience for Life Laboratory, Department of Biochemistry and Biophysics, Stockholm University, Box 1031, 17121, Solna, Sweden.
Stockholm University · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundFusion transcripts are involved in tumourigenesis and play a crucial role in tumour heterogeneity, tumour evolution and cancer treatment resistance. However, fusion transcripts have not been studied at high spatial resolution in tissue sections due to the lack of full-length transcripts with spatial information. New high-throughput technologies like spatial transcriptomics measure the transcriptome of tissue sections on almost single-cell level. While this technique does not allow for direct detection of fusion transcripts, we show that they can be inferred using the relative poly(A) tail abundance of the involved parental genes.

methodWe present a new method STfusion, which uses spatial transcriptomics to infer the presence and absence of poly(A) tails. A fusion transcript lacks a poly(A) tail for the 5' gene and has an elevated number of poly(A) tails for the 3' gene. Its expression level is defined by the upstream promoter of the 5' gene. STfusion measures the difference between the observed and expected number of poly(A) tails with a novel C-score.

resultsWe verified the STfusion ability to predict fusion transcripts on HeLa cells with known fusions. STfusion and C-score applied to clinical prostate cancer data revealed the spatial distribution of the cis-SAGe SLC45A3-ELK4 in 12 tissue sections with almost single-cell resolution. The cis-SAGe occurred in disease areas, e.g. inflamed, prostatic intraepithelial neoplastic, or cancerous areas, and occasionally in normal glands.

conclusionsSTfusion detects fusion transcripts in cancer cell line and clinical tissue data, and distinguishes chimeric transcripts from chimeras caused by trans-splicing events. With STfusion and the use of C-scores, fusion transcripts can be spatially localised in clinical tissue sections on almost single cell level.

Indexed as

Gene Expression Regulation, NeoplasticTranscriptomeComputational BiologyHeLa CellsHumansMaleOncogene Proteins, FusionProstatic NeoplasmsRNA, MessengerSpatial AnalysisOncogene Proteins, FusionRNA, MessengerCis-SAGEFusion transcript detectionGene fusionOncogeneSpatial Transcriptomics

Identifiers

PMID32753032
PMCPMC7437936
OpenAlexW3007524850

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.