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Record W2886691025 · doi:10.1158/1538-7445.am2018-4174

Abstract 4174: Differential response of non-small cell lung cancer harboring different epidermal growth factor receptor mutations to ablative radiation therapy

2018· article· en· W2886691025 on OpenAlexaff
Areej Al Rabea, Brian Meehan, Paul Daniel, Siham Sabri, Chaitanya S. Nirodi, Janusz Rak, Bassam Abdulkarim

Bibliographic record

VenueCancer Research · 2018
Typearticle
Languageen
FieldMedicine
TopicMedical Imaging and Pathology Studies
Canadian institutionsMcGill University
Fundersnot available
KeywordsEpidermal growth factor receptorCancer researchLung cancerProtein kinase domainTyrosine kinaseBiologyMolecular biologyMedicineCancerPathologyReceptorInternal medicineGeneMutant

Abstract

fetched live from OpenAlex

Abstract Background: ablative radiation therapy (ABR) serves as the treatment of choice for early stage non-small cell lung cancer (NSCLC) patients who are not surgical candidates. NSCLC patients with mutations in the tyrosine kinase domain (TKD) of the epidermal growth factor receptor (EGFR) had a significant response to tyrosine kinase inhibitors (TYIs). The most common mutations of EGFR in NSCLC are present in the TKD domain and include: deletion (DEL) in the exon 19 and a missense mutation (L858R) in the exon 21. The role of extracellular vesicles (EVs) has been under extensive investigation due to its contribution in preparing the distant site through a process named pre-metastatic niche formation. Release of irradiation-induced EVs in EGFR mutated NSCLC and their responses to ABR have not been well investigated. We aim to assess EVs release and tumor growth of NSCLC harboring different EGFR mutations post- ABR. Materials and methods: We used A549 that were transduced with different EGFR status: EGFR-WT (WT), EGFR-DEL (DEL) or EGFR-L858R (L858R) and irradiated them at 0, 12 or 34Gy. The condition media were then collected at 24hrs post-irradiation and used to measure release of extracellular vesicles (EVs) using nanosight. We transduced the cells with lentivirus expressing luciferase. Cells were irradiated at 0Gy (Ctrl group) or 34Gy (IR group) and injected subcutaneously in yellow fluorescent protein -severe combined immunodeficiency (YFP-SCID) mice. Tumor volume and animal weight were measured regularly and bioluminescence imaging (BLI) was used to evaluate tumor growth and metastasis. Results: L858R-expressing cells had an increase in EVs release post-ABR (12 and 34Gy), compared to WT-expressing cells which did not have difference in EVs release following ABR. DEL-expressing cells had an increase in EVs release only at 34Gy. Furthermore, in vivo data revels that ABR caused a decrease in tumor growth of IR-WT and IR-DEL groups when compared to Ctrl-WT and Ctrl-DEL, respectively. Interestingly, both Ctrl-L858R and IR-L858R groups presented similar tumor growth. Further investigations are undergoing assessing the EVs release and their function in the occurrence of distant metastasis post-ABR. Conclusion: in our study, we report a differential response of non-small cell lung cancer to ABR that could be caused by the differences in EGFR status. As a result, the standard use of ABR should not only be based on the patients' comorbidity status, but should also be based on his/her genetic background in order to determine the optimal treatment. Citation Format: Areej Al Rabea, Brian Meehan, Paul Daniel, Siham Sabri, Chaitanya Nirodi, Janusz Rak, Bassam Abdulkarim. Differential response of non-small cell lung cancer harboring different epidermal growth factor receptor mutations to ablative radiation therapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 4174.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.476
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.096
GPT teacher head0.432
Teacher spread0.336 · 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.

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

Citations0
Published2018
Admission routes1
Has abstractyes

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