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Record W2955554680 · doi:10.1158/1538-7445.am2019-3925

Abstract 3925: A screen for epigenetic radiosensitizers in small cell lung cancer

2019· article· en· W2955554680 on OpenAlexaff
Mansi K. Aparnathi, Lifang Song, Ratheesh Subramaniam, Richard Marcellus, Rima Al‐awar, Benjamin H. Lok

Bibliographic record

VenueCancer Research · 2019
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Research Studies
Canadian institutionsOntario Institute for Cancer ResearchPrincess Margaret Cancer CentreUniversity Health Network
Fundersnot available
KeywordsEpigeneticsEpigenetic therapyCancer researchLung cancerCancerMalignancyCell cultureCellMedicineChemistryBiologyOncologyGeneticsInternal medicineDNA methylationGene expression

Abstract

fetched live from OpenAlex

Abstract Objective: Small cell lung cancer (SCLC) is a highly aggressive neuroendocrine malignancy. Post-platinum-based chemotherapy, rapid relapse of chemoresistant tumor is commonly seen. Unidentifiable causative mutations and from reversible nature of acquired chemoresistance, involvement of epigenetic switch regulating SCLC progression is evident. Aim of this screen is to identify epigenetic modifiers that could sensitize SCLC cells to ionizing radiation (IR). Methods: To recapitulate molecular diversity of patients, a range of SCLC cell lines (n=10) from classic or variant and ASCL1 or NeuroD1 sub-groups, driven by varying MYC family amplifications were picked. Short term viability experiment was setup in 3 groups: (a) Epigenetic monotherapy: cells were screened with 10 epigenetic modifiers (0 to 10 µM). (b) IR monotherapy: cells were irradiated from 0 to 8 gy. (c) Combination therapy: cells were treated with different doses of epigenetic probes and IR. Radiosensitization was measured as dose modifying factor at SF63 for each epigenetic modulator. Results: (a) Epigenetic monotherapy: All 10 cell lines were responsive to GSK-J4 (KDMi, IC50 3.1-0.9 µM), SAHA (HDACi, IC50 2.9-0.79 µM) and JIB04 (Jumonji KDMi, IC50 74-2.4 nM). Other interesting epi-probe to which 9/10 cell lines responded was JQ1 (BET-BRDi, IC50 5.7 to 0.15 µM, except SBC-5). Compounds with lesser universal potency were MS023 (PRMTi), UNC0642 (G9a/GLPi) and UNC1999 (EZH2i). All cell lines were irresponsive to PFI3 (SMARCA2/4 BRDi), BAY598 (SMYD2 MTi) and OICR-9429 (WDR5i). (b) IR monotherapy: All 10 cell lines demonstrated different sensitivities to 4 days of IR. They’re ranked in descending order of radiosensitivity as H446, H82, SHP77, LX22, H889, H1092, H196, H69, SBC5, H526. (c) Epi-probes + IR combination therapy: Epi-probes ranked in descending order of number of cell lines they radiosensitized are JQ1, JIB-04, GSK-J4, SAHA, UNC0642, BAY598, MS023, UNC1999, OICR9429 and PFI3. Interestingly, drugs that demonstrated potency as a single agent did not necessarily radiosensitize the cell lines. On the contrary, certain epi-probes that were ineffective as monotherapy radiosensitized a few of the cell lines. H82 is a sensitive cell line which was radiosensitized by all epi-probes used. Conclusions: This screen shows that treating cells with IR in conjunction with epigenetic modifiers may potentially improve therapeutic efficacy of radiotherapy in SCLC. Further validation is being done with long term colonogenic assays followed by in vivo studies for the potent radiosensitizing candidate drugs. It would be therapeutically relevant to correlate the probability of radiosensitization by an epi-probe with the molecular profile of the patients for more predictive targeted therapeutics. Citation Format: Mansi K. Aparnathi, Lifang Song, Ratheesh Subramaniam, Richard Marcellus, Rima Al-awar, Benjamin H. Lok. A screen for epigenetic radiosensitizers in small cell lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 3925.

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)0.002
metaresearch head score (Gemma)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.184
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.081
GPT teacher head0.444
Teacher spread0.364 · 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 designObservational
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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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