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Record W3049319010 · doi:10.1038/s41467-020-17958-z

Enhancing chemotherapy response through augmented synthetic lethality by co-targeting nucleotide excision repair and cell-cycle checkpoints

2020· article· en· W3049319010 on OpenAlexaff
Yi Wen Kong, Erik C. Dreaden, Sandra Morandell, Wen Zhou, Sanjeev Dhara, Ganapathy Sriram, Fred C. Lam, Jesse C. Patterson, Mohiuddin Quadir, Anh Dinh, Kevin E. Shopsowitz, Shohreh Varmeh, Stephen J. Lippard, Hans Christian Reinhardt, Michael T. Hemann, Paula T. Hammond, Michael B. Yaffe

Bibliographic record

VenueNature Communications · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced biosensing and bioanalysis techniques
Canadian institutionsHamilton General Hospital
FundersDivision of Materials ResearchNational Institute of Biomedical Imaging and BioengineeringNational Institute of Environmental Health SciencesCongressionally Directed Medical Research ProgramsBreast Cancer AllianceNational Institute on AgingKoch Institute for Integrative Cancer Research, Massachusetts Institute of TechnologyMaterials Research Science and Engineering Center, Harvard UniversityNational Institute of General Medical SciencesOvarian Cancer Research FoundationNational Cancer InstituteU.S. Department of Health and Human ServicesNational Institutes of HealthNational Science FoundationU.S. Department of Defense
KeywordsSynthetic lethalityDNA damageCisplatinCancer researchDNA repairCHEK1Cell cycle checkpointMutantBiologyCell cycleCell biologyDNACellGeneChemotherapyGenetics

Abstract

fetched live from OpenAlex

In response to DNA damage, a synthetic lethal relationship exists between the cell cycle checkpoint kinase MK2 and the tumor suppressor p53. Here, we describe the concept of augmented synthetic lethality (ASL): depletion of a third gene product enhances a pre-existing synthetic lethal combination. We show that loss of the DNA repair protein XPA markedly augments the synthetic lethality between MK2 and p53, enhancing anti-tumor responses alone and in combination with cisplatin chemotherapy. Delivery of siRNA-peptide nanoplexes co-targeting MK2 and XPA to pre-existing p53-deficient tumors in a highly aggressive, immunocompetent mouse model of lung adenocarcinoma improves long-term survival and cisplatin response beyond those of the synthetic lethal p53 mutant/MK2 combination alone. These findings establish a mechanism for co-targeting DNA damage-induced cell cycle checkpoints in combination with repair of cisplatin-DNA lesions in vivo using RNAi nanocarriers, and motivate further exploration of ASL as a generalized strategy to improve cancer treatment.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.102
Threshold uncertainty score0.661

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.012
GPT teacher head0.310
Teacher spread0.298 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations48
Published2020
Admission routes1
Has abstractyes

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