Evidence map›Paper›PMID 33212364›Full record

ArticleNeoplasia (New York, N.Y.)2021

Patient-derived xenograft (PDX) models of colorectal carcinoma (CRC) as a platform for chemosensitivity and biomarker analysis in personalized medicine.

Maria Rivera, Iduna Fichtner, Annika Wulf-Goldenberg, Christine Sers, Johannes Merk, Giannino Patone, Keziban M Alp, Tamara Kanashova, Philipp Mertins, Jens Hoffmann and 2 more

Open access · goldAbstract read
In one paragraph

Article in Neoplasia (New York, N.Y.), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
41citing papers in PubMed, 1 pooled it
3.0field-weighted citation impact, top 7% 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

41 citing papers in PubMed, 1 synthesis or guideline pooled it, 63 citations in OpenAlex.

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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

12 authors at 3 institutions in 1 country.

Maria RiveraEPO GmbH Berlin-Buch, Berlin, Germany.
Iduna FichtnerEPO GmbH Berlin-Buch, Berlin, Germany.
Annika Wulf-GoldenbergEPO GmbH Berlin-Buch, Berlin, Germany.
Christine SersCharité Universitätsmedizin Berlin, Institute of Pathology, Berlin, Germany.
Johannes MerkLabor Dr. Merk & Kollegen GmbH, Ochsenhausen, Germany.
Giannino PatoneGerman Cancer Consortium (DKTK), Heidelberg, Germany.
Keziban M AlpProteomics Platform, Max-Delbrück-Center for Molecular Medicine and Berlin Institute of Health, Berlin, Germany.
Tamara KanashovaProteomics Platform, Max-Delbrück-Center for Molecular Medicine and Berlin Institute of Health, Berlin, Germany.
Philipp MertinsProteomics Platform, Max-Delbrück-Center for Molecular Medicine and Berlin Institute of Health, Berlin, Germany.
Jens HoffmannEPO GmbH Berlin-Buch, Berlin, Germany.
Ulrike SteinExperimental and Clinical Research Center, Charité Universitätsmedizin Berlin, and Max-Delbrück-Center for Molecular Medicine, Berlin, Germany.
Wolfgang WaltherExperimental and Clinical Research Center, Charité Universitätsmedizin Berlin, and Max-Delbrück-Center for Molecular Medicine, Berlin, Germany.
Max Delbrück Center · DECharité - Universitätsmedizin Berlin · DEGerman Cancer Research Center · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Patient-derived xenograft (PDX) tumor models represent a valuable platform for identifying new biomarkers and novel targets, to evaluate therapy response and resistance mechanisms. This study aimed at establishment, characterization and therapy testing of colorectal carcinoma-derived PDX. We generated 49 PDX and validated identity between patient tumor and corresponding PDX. Sensitivity of PDX toward conventional and targeted drugs revealed that 92% of PDX responded toward irinotecan, 45% toward 5-FU, 65% toward bevacizumab, and 61% toward cetuximab. Expression of epidermal growth factor receptor (EGFR) ligands correlated to the sensitivity toward cetuximab. Proto-oncogene B-RAF, EGFR, Kirsten rat sarcoma virus oncogene homolog gene copy number correlated positively with cetuximab and erlotinib sensitivity. The mutational analyses revealed an individual mutational profile of PDX and mainly identical profiles of PDX from primary tumor vs corresponding metastasis. Mutation in PIK3CA was a determinant of accelerated tumor doubling time. PDX with wildtype Kirsten rat sarcoma virus oncogene homolog, proto-oncogene B-RAF, and phosphatidylinositol-4,5-bisphosphate 3-kinaseM catalytic subunit alfa showed higher sensitivity toward cetuximab and erlotinib. To study the molecular mechanism of cetuximab resistance, cetuximab resistant PDX models were generated, and changes in HER2, HER3, betacellulin, transforming growth factor alfa were observed. Global proteome and phosphoproteome profiling showed a reduction in canonical EGFR-mediated signaling via PTPN11 (SHP2) and AKT1S1 (PRAS40) and an increase in anti-apoptotic signaling as a consequence of acquired cetuximab resistance. This demonstrates that PDX models provide a multitude of possibilities to identify and validate biomarkers, signaling pathways and resistance mechanisms for clinically relevant improvement in cancer therapy.

Indexed as

Biomarkers, TumorHeterograftsAnimalsAntineoplastic AgentsColorectal NeoplasmsDNA Copy Number VariationsDrug Resistance, NeoplasmFluorescent Antibody TechniqueGene Expression ProfilingGenomic InstabilityHumansImmunohistochemistryMiceMolecular Targeted TherapyMutationPrecision MedicineAntineoplastic AgentsBiomarkers, TumorMAS1 protein, humanProteomeProto-Oncogene MasColorectal carcinomaIn vivo drug testingPatient-derived xenograft modelsPersonalized medicine

Identifiers

PMID33212364
PMCPMC7680704
OpenAlexW3099376746

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.