Evidence map›Paper›PMID 38702451›Full record

ArticleCommunications medicine2024

Independent transcriptional patterns reveal biological processes associated with disease-free survival in early colorectal cancer.

Daan G Knapen, Sara Hone Lopez, Derk Jan A de Groot, Jacco-Juri de Haan, Elisabeth G E de Vries, Rodrigo Dienstmann, Steven de Jong, Arkajyoti Bhattacharya, Rudolf S N Fehrmann

Abstract read
In one paragraph

Article in Communications medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

3 citing papers in PubMed.

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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

9 authors.

Daan G KnapenDepartment of Medical Oncology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands.ORCID http://orcid.org/0000-0002-2523-137X
Sara Hone LopezDepartment of Medical Oncology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands.ORCID http://orcid.org/0000-0001-7615-3474
Derk Jan A de GrootDepartment of Medical Oncology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands.
Jacco-Juri de HaanDepartment of Medical Oncology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands.ORCID http://orcid.org/0000-0002-1629-4715
Elisabeth G E de VriesDepartment of Medical Oncology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands.ORCID http://orcid.org/0000-0002-8949-7425
Rodrigo DienstmannOncology Data Science (ODysSey) Group, Vall d'Hebron Institute of Oncology, Universitat Autónoma de Barcelona, Barcelona, Spain.
Steven de JongDepartment of Medical Oncology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands.ORCID http://orcid.org/0000-0001-5831-6997
Arkajyoti BhattacharyaDepartment of Medical Oncology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands.ORCID http://orcid.org/0000-0003-1479-0739
Rudolf S N FehrmannDepartment of Medical Oncology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands. r.s.n.fehrmann@umcg.nl.ORCID http://orcid.org/0000-0002-7516-315X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBulk transcriptional profiles of early colorectal cancer (CRC) can fail to detect biological processes associated with disease-free survival (DFS) if the transcriptional patterns are subtle and/or obscured by other processes' patterns. Consensus-independent component analysis (c-ICA) can dissect such transcriptomes into statistically independent transcriptional components (TCs), capturing both pronounced and subtle biological processes.

methodsIn this study we (1) integrated transcriptomes (n = 4228) from multiple early CRC studies, (2) performed c-ICA to define the TC landscape within this integrated data set, 3) determined the biological processes captured by these TCs, (4) performed Cox regression to identify DFS-associated TCs, (5) performed random survival forest (RSF) analyses with activity of DFS-associated TCs as classifiers to identify subgroups of patients, and 6) performed a sensitivity analysis to determine the robustness of our results

resultsWe identify 191 TCs, 43 of which are associated with DFS, revealing transcriptional diversity among DFS-associated biological processes. A prominent example is the epithelial-mesenchymal transition (EMT), for which we identify an association with nine independent DFS-associated TCs, each with coordinated upregulation or downregulation of various sets of genes.

conclusionsThis finding indicates that early CRC may have nine distinct routes to achieve EMT, each requiring a specific peri-operative treatment strategy. Finally, we stratify patients into DFS patient subgroups with distinct transcriptional patterns associated with stage 2 and stage 3 CRC.

Identifiers

PMID38702451
PMCPMC11068726

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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.