Evidence map›Paper›PMID 35845819›Full record

ArticleJournal of hepatocellular carcinoma2022

Comparative Response of HCC Cells to TKIs: Modified in vitro Testing and Descriptive Expression Analysis.

Paula Sagmeister, Jimmy Daza, Andrea Ofner, Andreas Ziesch, Liangtao Ye, Najib Ben Khaled, Matthias Ebert, Julia Mayerle, Andreas Teufel, Enrico N De Toni and 1 more

Open access · goldAbstract read
In one paragraph

Article in Journal of hepatocellular carcinoma, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.4field-weighted citation impact, top 40% 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

4 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Review
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 at 3 institutions in 2 countries.

Paula Sagmeister *Department of Medicine II, LMU Munich, Munich, Bavaria, Germany.
Jimmy Daza *Department of Medicine II, Medical Faculty Mannheim, Heidelberg University, Mannheim, Baden Wurttenberg, Germany.ORCID 0000-0001-9902-5440
Andrea OfnerDepartment of Medicine II, LMU Munich, Munich, Bavaria, Germany.
Andreas ZieschDepartment of Medicine II, LMU Munich, Munich, Bavaria, Germany.
Liangtao YeDepartment of Medicine II, LMU Munich, Munich, Bavaria, Germany.
Najib Ben KhaledDepartment of Medicine II, LMU Munich, Munich, Bavaria, Germany.
Matthias EbertDepartment of Medicine II, Medical Faculty Mannheim, Heidelberg University, Mannheim, Baden Wurttenberg, Germany.
Julia MayerleDepartment of Medicine II, LMU Munich, Munich, Bavaria, Germany.
Andreas TeufelDepartment of Medicine II, Medical Faculty Mannheim, Heidelberg University, Mannheim, Baden Wurttenberg, Germany.
Enrico N De ToniDepartment of Medicine II, LMU Munich, Munich, Bavaria, Germany.ORCID 0000-0002-8101-8207
Stefan MunkerDepartment of Medicine II, LMU Munich, Munich, Bavaria, Germany.
LMU Klinikum · DEHeidelberg University · DESun Yat-sen University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Although the treatment paradigm for hepatocellular carcinoma (HCC) has recently shifted in favour of checkpoint inhibitor (CPI)-based treatment options, the tyrosine kinase inhibitors (TKI) currently approved for the treatment of HCC are expected to remain the cornerstone of HCC treatment alone or in combination with CPIs. Despite considerable research efforts, no biomarker capable of predicting the response to specific TKIs has been validated. Thus, personalized approaches to HCC may aid in determining optimal treatment lines for 2nd and 3rd lines. To identify new biomarkers, we examined differential sensitivity and investigated potential transcriptomic predictors. Methods: To this aim, the sensitivity of nine HCC cell lines to sorafenib, lenvatinib, regorafenib, and cabozantinib was evaluated by a prolonged treatment scheme to determine their respective growth rate inhibition concentrations (GR Results: The nine cell lines showed broadly different sensitivities to different TKIs. GR Conclusion: We observed diverse responses to either of the four TKIs. Subgroup analysis of TKI effectiveness showed distinct transcriptomic profiles and signaling pathways associated with responsiveness. This prompts more extensive studies to explore and validate pharmacogenomic and transcriptomic strategies for a personalized treatment approach, particularly after the failure of CPI treatment.

Indexed as

biomarkerscabozantiniblenvatinibregorafenibsorafenib

Identifiers

PMID35845819
PMCPMC9278726
OpenAlexW4284957974

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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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.