ArticleBMC medical genomics2020
Fusion transcript detection using spatial transcriptomics.
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.
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Who cites it
10 citing papers in PubMed, 22 citations in OpenAlex.
- Spatial Transcriptomics: Technical Aspects of Recent Developments and Their Applications in Neuroscience and Cancer Research.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2023Review
- Pattern recognition in the landscape of seemingly random chimeric transcripts.Computational and structural biotechnology journal · 2023Article
- Novel insights from spatial transcriptome analysis in solid tumors.International journal of biological sciences · 2023Review
- Challenges and considerations for single-cell and spatially resolved transcriptomics sample collection during spaceflight.Cell reports methods · 2022Review
- Single-Cell RNA Sequencing with Spatial Transcriptomics of Cancer Tissues.International journal of molecular sciences · 2022Review
- Spatial transcriptomics technology in cancer research.Frontiers in oncology · 2022Review
- Review
- Applicability of spatial transcriptional profiling to cancer research.Molecular cell · 2021Review
- Spatially resolved transcriptomics and its applications in cancer.Current opinion in genetics & development · 2021Review
- Full-Length Transcriptome Analysis ofFrontiers in cellular and infection microbiology · 2021Article
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
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.
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