Evidence map›Paper›PMID 41796449›Full record

ReviewTrends in cancer2026

Disarming cancer resistance: FAK as a therapeutic target.

Terrance J Haanen, David D Schlaepfer

Abstract readReview
In one paragraph

Review in Trends in cancer, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
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

2 authors.

Terrance J HaanenDepartment of Obstetrics, Gynecology, and Reproductive Sciences, Division of Gynecologic Oncology, University of California, San Diego, Moores Cancer Center, 3855 Health Sciences Drive, MC0803, La Jolla, CA 92093, USA.
David D SchlaepferDepartment of Obstetrics, Gynecology, and Reproductive Sciences, Division of Gynecologic Oncology, University of California, San Diego, Moores Cancer Center, 3855 Health Sciences Drive, MC0803, La Jolla, CA 92093, USA. Electronic address: dschlaepfer@health.ucsd.edu.

Funding

UCSD Cancer Center Training Program in Drug DevelopmentT32CA121938 · NCI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Michael Bouvet, Dwayne G. Stupack · 2006 to 2026
$10.3M
NCI NIH HHS T32 CA121938
6 · The paper itself

Abstract

The FDA recently granted accelerated approval of the small-molecule focal adhesion kinase (FAK) inhibitor (FAKi, defactinib) in combination with a RAF-MEK clamp inhibitor (avutometinib) for KRAS-mutated low-grade serous ovarian cancer developed by Verastem Inc. This milestone moment represents a long journey in FAKi development, from initial findings of limited single-agent activity to orally delivered FAKi effects that can sensitize solid tumors to chemotherapy, radiotherapy, and immunotherapy treatments. In this study, we review a short history of FAK, summarize ongoing combinatorial clinical trials, discuss potential mechanisms of action, and highlight studies showing that FAK activation is a chemo- and mechano-sensitive signaling hub driving tumor adaptive changes. Targeting FAK disarms tumor resistance through multiple mechanisms, which supports new biological insights and future clinical combinations.

Indexed as

Antineoplastic Combined Chemotherapy ProtocolsDrug Resistance, NeoplasmFocal Adhesion Protein-Tyrosine KinasesNeoplasmsOvarian NeoplasmsProtein Kinase InhibitorsAnimalsBenzamidesFemaleHumansMolecular Targeted TherapyPyrazinesSignal TransductionSulfonamidesBenzamidesdefactinibFocal Adhesion Protein-Tyrosine KinasesProtein Kinase InhibitorsPyrazinesSulfonamidesadaptive resistanceavutometinibdefactinibFAKRAFRAS

Identifiers

PMID41796449
PMCPMC13174975

What OpenQuestion holds

Textmetadata
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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.