ReviewJournal of molecular biology2017
Exploiting Synthetic Lethality and Network Biology to Overcome EGFR Inhibitor Resistance in Lung Cancer.
Review in Journal of molecular biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 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
14 citing papers in PubMed.
- Construction and validation of an EGFR-related risk signature identifiedTranslational cancer research · 2025Article
- Phase Ia/Ib Study of Afatinib with Capecitabine in Patients with Refractory Solid Tumors and Pancreaticobiliary Cancers.Cancers · 2025Article
- Molecular Subtypes and Targeted Therapeutic Strategies in Small Cell Lung Cancer: Advances, Challenges, and Future Perspectives.Molecules (Basel, Switzerland) · 2025Review
- Article
- Molecular Pathology of Lung Cancer.Cold Spring Harbor perspectives in medicine · 2022Review
- Characterization of a small molecule inhibitor of disulfide reductases that induces oxidative stress and lethality in lung cancer cells.Cell reports · 2022Article
- Rare epidermal growth factor receptor (EGFR) mutations in non-small cell lung cancer.Seminars in cancer biology · 2020Review
- Epigenetic synthetic lethality approaches in cancer therapy.Clinical epigenetics · 2019Review
- Exploiting vulnerabilities in cancer signalling networks to combat targeted therapy resistance.Essays in biochemistry · 2018Review
- Article
- Quantitative phosphoproteomic analysis of acquired cancer drug resistance to pazopanib and dasatinib.Journal of proteomics · 2018Article
- Improved detection of synthetic lethal interactions inProceedings of the National Academy of Sciences of the United States of America · 2017Article
- Candidate synthetic lethality partners to PARP inhibitors in the treatment of ovarian clear cell cancer.Biomedical reports · 2017Article
- TargetingSignal transduction and targeted therapyReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Despite the recent approval of third-generation therapies, overcoming resistance to epidermal growth factor receptor (EGFR) inhibitors remains a major challenge in non-small cell lung cancer. Conceptually, synthetic lethality holds the promise of identifying non-intuitive targets for tackling both acquired and intrinsic resistance in this setting. However, translating these laboratory findings into effective clinical strategies continues to be elusive. Here, we provide an overview of the synthetic lethal approaches that have been employed to study EGFR inhibitor resistance and review the oncogene and non-oncogene signalling mechanisms that have thus far been unveiled by synthetic lethality screens. We highlight the potential challenges associated with progressing these discoveries into the clinic including context dependency, signalling plasticity, and tumour heterogeneity, and we offer a perspective on emerging network biology and computational solutions to exploit these phenomena for cancer therapy and biomarker discovery. We conclude by presenting a number of tangible steps to bolster our understanding of fundamental synthetic lethality mechanisms and advance these findings beyond the confines of the laboratory.
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.