Evidence map›Paper›PMID 31526717›Full record

ArticleEBioMedicine2019

Generation of in situ sequencing based OncoMaps to spatially resolve gene expression profiles of diagnostic and prognostic markers in breast cancer.

Jessica Svedlund, Carina Strell, Xiaoyan Qian, Kilian J C Zilkens, Nicholas P Tobin, Jonas Bergh, Anieta M Sieuwerts, Mats Nilsson

Open access · goldAbstract read
In one paragraph

Article in EBioMedicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
1.7field-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

22 citing papers in PubMed, 41 citations in OpenAlex.

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  11. Novel insights from spatial transcriptome analysis in solid tumors.International journal of biological sciences · 2023
    Review
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  13. Article
  14. Spatial Resolution ofFrontiers in immunology · 2022
    Article
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  18. Spatially resolved transcriptomics and its applications in cancer.Current opinion in genetics & development · 2021
    Review
  19. Article
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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

8 authors at 3 institutions in 3 countries.

Jessica SvedlundScience for Life Laboratory, Department of Biochemistry and Biophysics, Stockholm University, Stockholm, Sweden.
Carina StrellScience for Life Laboratory, Department of Biochemistry and Biophysics, Stockholm University, Stockholm, Sweden.
Xiaoyan QianScience for Life Laboratory, Department of Biochemistry and Biophysics, Stockholm University, Stockholm, Sweden.
Kilian J C ZilkensScience for Life Laboratory, Department of Biochemistry and Biophysics, Stockholm University, Stockholm, Sweden.
Nicholas P TobinKarolinska Institutet and Breast Cancer Section, Cancer Theme Karolinska University Hospital, Department of Oncology and Pathology, Stockholm, Sweden.
Jonas BerghKarolinska Institutet and Breast Cancer Section, Cancer Theme Karolinska University Hospital, Department of Oncology and Pathology, Stockholm, Sweden; Department of Public Health, Oxford University, Oxford, United Kingdom.
Anieta M SieuwertsErasmus MC Cancer Institute and Cancer Genomics Netherlands, Department of Medical Oncology, Rotterdam, the Netherlands.
Mats NilssonScience for Life Laboratory, Department of Biochemistry and Biophysics, Stockholm University, Stockholm, Sweden. Electronic address: mats.nilsson@scilifelab.se.
Stockholm University · SEKarolinska University Hospital · SEErasmus MC Cancer Institute · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGene expression analysis of breast cancer largely relies on homogenized tissue samples. Due to the high degree of cellular and molecular heterogeneity of tumor tissues, bulk tissue-based analytical approaches can only provide very limited system-level information about different signaling mechanisms and cellular interactions within the complex tissue context.

methodsWe describe an analytical approach using in situ sequencing (ISS), enabling highly multiplexed, spatially and morphologically resolved gene expression profiling. Ninety-one genes including prognostic and predictive marker profiles, as well as genes involved in specific cellular pathways were mapped within whole breast cancer tissue sections, covering luminal A/B-like, HER2-positive and triple negative tumors. Finally, all these features were combined and assembled into a molecular-morphological OncoMap for each tumor tissue.

findingsOur in situ approach spatially revealed intratumoral heterogeneity with regard to tumor subtype as well as to the OncotypeDX recurrence score and even uncovered areas of minor cellular subpopulations. Since ISS-resolved molecular profiles are linked to their histological context, a deeper analysis of the core and periphery of tumor foci enabled identification of specific gene expression patterns associated with these morphologically relevant regions.

interpretationISS generated OncoMaps represent useful tools to extend our general understanding of the biological processes behind tumor progression and can further support the identification of novel therapeutical targets as well as refine tumor diagnostics. FUND: Swedish Cancerfonden, UCAN, Vetenskapsrådet, Cancer Genomics Netherlands, Iris, Stig och Gerry Castenbäcks Stiftelse, BRECT, PCM Program, King Gustaf V Jubilee Fund, BRO, KI and Stockholm County Council, Alice Wallenberg Foundation.

Indexed as

Biomarkers, TumorGene Expression ProfilingOncogenesTranscriptomeBreast NeoplasmsCell Line, TumorFemaleGene Expression Regulation, NeoplasticHumansImmunohistochemistryPolymorphism, Single NucleotidePrognosisReproducibility of ResultsBiomarkers, TumorBreast cancerDiagnosticGene expression analysisPrognosticTumor heterogeneity

Identifiers

PMID31526717
PMCPMC6838368
OpenAlexW2972757028

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.