ReviewThe FEBS journal2022
CRISPR screens guide the way for PARP and ATR inhibitor biomarker discovery.
Review in The FEBS journal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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.
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.
Who cites it
10 citing papers in PubMed, 11 citations in OpenAlex.
- Antitumor activity and structure-activity relationship of poly (ADP-ribose) polymerase (PARP)-based dual inhibitors.Journal of enzyme inhibition and medicinal chemistry · 2026Review
- Genome-wide CRISPR screens identify the EXO1-CAF-1 pathway suppressing R-loop-associated DNA damage.Nucleic acids research · 2026Article
- Synthetic lethality in cancer therapy: Mechanisms, models and clinical translation for overcoming therapeutic resistance.Clinical and translational medicine · 2026Review
- Next Generation DNA Damage Response Inhibitors: Harnessing Nanocarriers and Tumor Microenvironment for Precision Cancer Therapy.Oncology research · 2026Review
- BRCAness, DNA gaps, and gain and loss of PARP inhibitor-induced synthetic lethality.The Journal of clinical investigation · 2024Review
- Optimized minimal genome-wide human sgRNA library.Scientific reports · 2023Article
- Fighting resistance: post-PARP inhibitor treatment strategies in ovarian cancer.Therapeutic advances in medical oncology · 2023Review
- Multiple-low-dose therapy: effective killing of high-grade serous ovarian cancer cells with ATR and CHK1 inhibitors.NAR cancer · 2022Article
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Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
DNA repair pathways are heavily studied for their role in cancer initiation and progression. Due to the large amount of inherent DNA damage in cancer cells, tumor cells profoundly rely on proper DNA repair for efficient cell cycle progression. Several current chemotherapeutics promote excessive DNA damage in cancer cells, thus leading to cell death during cell cycle progression. However, if the tumor has efficient DNA repair mechanisms, DNA-damaging therapeutics may not be as effective. Therefore, directly inhibiting DNA repair pathways alone and in combination with chemotherapeutics that cause DNA damage may result in improved clinical outcomes. Nevertheless, tumors can acquire resistance to DNA repair inhibitors. It is essential to understand the genetic mechanisms underlying this resistance. Genome-wide CRISPR screening has emerged as a powerful tool to identify biomarkers of resistance or sensitivity to DNA repair inhibitors. CRISPR knockout and CRISPR activation screens can be designed to investigate how the loss or overexpression of any human gene impacts resistance or sensitivity to specific inhibitors. This review will address the role of CRISPR screening in identifying biomarkers of resistance and sensitivity to DNA repair pathway inhibitors. We will focus on inhibitors targeting the PARP1 and ATR enzymes, and how the biomarkers identified from CRISPR screens can help inform the treatment plan for cancer patients.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.