Evidence map›Paper›PMID 42640371›Full record

ArticleMolecular biomedicine2026

Exceptional treatment responses and molecular markers among 103 colorectal cancer cell lines.

Anita Sveen, Jakob M Stenersen, Theophilus Quachie Asenso, Solveig K Klokkerud, Christian Kranjec, Ina A Eilertsen, Bjarne Johannessen, Edward Leithe, Kushtrim Kryeziu, Manuela Zucknick and 1 more

Abstract read
In one paragraph

Article in Molecular biomedicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

11 authors.

Anita SveenDepartment of Molecular Oncology, Institute for Cancer Research, Oslo University Hospital, P.O. Box 4953 Nydalen, Oslo, NO-0424, Norway. anita.sveen@medisin.uio.no.ORCID http://orcid.org/0000-0001-8219-6251
Jakob M StenersenDepartment of Molecular Oncology, Institute for Cancer Research, Oslo University Hospital, P.O. Box 4953 Nydalen, Oslo, NO-0424, Norway.
Theophilus Quachie AsensoOslo Centre for Biostatistics and Epidemiology, Department of Biostatistics, University of Oslo, Oslo, Norway.
Solveig K KlokkerudDepartment of Molecular Oncology, Institute for Cancer Research, Oslo University Hospital, P.O. Box 4953 Nydalen, Oslo, NO-0424, Norway.
Christian KranjecDepartment of Molecular Oncology, Institute for Cancer Research, Oslo University Hospital, P.O. Box 4953 Nydalen, Oslo, NO-0424, Norway.
Ina A EilertsenDepartment of Molecular Oncology, Institute for Cancer Research, Oslo University Hospital, P.O. Box 4953 Nydalen, Oslo, NO-0424, Norway.
Bjarne JohannessenDepartment of Molecular Oncology, Institute for Cancer Research, Oslo University Hospital, P.O. Box 4953 Nydalen, Oslo, NO-0424, Norway.
Edward LeitheDepartment of Molecular Oncology, Institute for Cancer Research, Oslo University Hospital, P.O. Box 4953 Nydalen, Oslo, NO-0424, Norway.
Kushtrim KryeziuDepartment of Molecular Oncology, Institute for Cancer Research, Oslo University Hospital, P.O. Box 4953 Nydalen, Oslo, NO-0424, Norway.
Manuela ZucknickOslo Centre for Biostatistics and Epidemiology, Department of Biostatistics, University of Oslo, Oslo, Norway.
Ragnhild A LotheDepartment of Molecular Oncology, Institute for Cancer Research, Oslo University Hospital, P.O. Box 4953 Nydalen, Oslo, NO-0424, Norway.

Funding

Helse Sør-Øst RHF 2017102Helse Sør-Øst RHF 2023101Helse Sør-Øst RHF 2024108Kreftforeningen 182759Kreftforeningen 208336Kreftforeningen 223319Kreftforeningen 246954
6 · The paper itself

Abstract

Patients with colorectal cancer have few molecularly guided treatment options. Cancers with exceptional treatment response are valuable models for discovery of molecular response mechanisms and might reveal new predictive biomarkers to guide treatment selection. However, the rarity of events is a clinical challenge. We performed integrated high-throughput drug sensitivity testing (n = 620 drugs) and molecular analyses of 103 colorectal cancer cell lines to build an in vitro foundation for exceptional treatment responses and their molecular markers. Exceptional responses were scored by a two-way outlier detection approach and were identified in 67 unique cell line-drug pairs (0.13% of all pairs tested). This involved 35 cell lines (34.0%) and 49 drugs (7.9%) representing standard, experimental, and non-oncology drugs of diverse classes. Plausible response mechanisms on the gene, protein, and/or pathway expression levels were identified at baseline in 89.6% of the 67 pairs. Experimental validation confirmed treatment-induced marker suppression in seven of eight selected pairs, including target engagement of kinase inhibitors and downregulation of markers of extended response mechanisms. Recurrent exceptional sensitivity to the same drug in different cell lines involved functionally convergent molecular mechanisms, but rarely precisely the same marker. Most exceptional sensitivities (77.8%) could be predicted with multivariable transcriptomic models. In conclusion, this study provides in vitro support for biomarker-guided prescreening to potentially obtain exceptional treatment response to diverse drugs and therapeutic targets in colorectal cancer. Most exceptional responses have a clear molecular underpinning. The study also provides a large and openly available pharmaco-transcriptomics resource for colorectal cancer cell lines.

Indexed as

Antineoplastic AgentsBiomarkers, TumorColorectal NeoplasmsCell Line, TumorDrug Screening Assays, AntitumorGene Expression ProfilingGene Expression Regulation, NeoplasticHumansTreatment OutcomeAntineoplastic AgentsBiomarkers, TumorCell linesColorectal cancerDrug sensitivity testingExceptional treatment responsePrediction biomarkersTranscriptomics

Identifiers

PMID42640371
PMCPMC13507031

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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.