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Record W4409634358 · doi:10.1158/1538-7445.am2025-2060

Abstract 2060: Independent validation of endogenous retrotransposable elements as predictive biomarkers of immune checkpoint blockade response

2025· article· en· W4409634358 on OpenAlexaff
M. Zurita Herrera, Sajid A. Marhon, Farnoosh Abbas‐Aghababazadeh, David Chen, Amy Liu, Helen LooYau, Emily Van de Laar, Jeffrey P. Bruce, Helen Chow, Philippe L. Bédard, Albiruni R. Abdul Razak, Anna Spreafico, Aaron R. Hansen, Marcus O. Butler, Stéphanie Lheureux, Trevor J. Pugh, Benjamin Haibe‐Kains, Daniel D. De Carvalho, Lillian L. Siu, Pavlina Spiliopoulou

Bibliographic record

VenueCancer Research · 2025
Typearticle
Languageen
FieldMedicine
TopicCytomegalovirus and herpesvirus research
Canadian institutionsUniversity of TorontoPrincess Margaret Cancer Centre
Fundersnot available
KeywordsBlockadeImmune checkpointEndogenyBiologyImmunologyImmune systemMedicineOncologyInternal medicineImmunotherapyGeneticsReceptor

Abstract

fetched live from OpenAlex

Abstract Background: Endogenous retrotransposable elements (EREs) can modulate antitumor immune responses via viral mimicry response. We previously described an association between ERE upregulation and radiological response to immune checkpoint blockade (ICB) in advanced solid tumors in the phase II INSPIRE trial (NCT02644369) (ASCO 2024). Here, we validate the association of EREs and ICB response in two independent cohorts of patients (pts) with melanoma and non-small cell lung cancer (NSCLC) treated with ICB. Methods: Publicly available datasets were screened to identify cohorts of pts with solid tumors receiving ICB with accessible clinical outcomes (responders, RP; or non-responders, NR) and total RNA-sequencing data. Two independent datasets (Riaz et al., PMID 29033130; Jung et al., PMID 31537801) were examined. ERE expression was analyzed in total RNA-seq from anonymized raw data in baseline (B) and on-treatment (T) samples of pts with melanoma and B samples of NSCLC. Differentially expressed EREs between RP and NR were quantified by the TPMscore (mean of normalized transcript per million values for upregulated EREs in a sample comparison) and its standardized Zscore. Immune cell infiltration was inferred from RNA-seq-based deconvolution. The cytolytic activity (CYT) immune score, derived from the mRNA expression of GZMA and PRF1, was reported in the melanoma cohort, while tumor mutational burden (TMB) data was available for both cohorts. Results: A total of 43 pts (14 RP and 29 NR) in the melanoma cohort and 27 pts (8 RP and 19 NR) in the NSCLC cohort were identified for analysis. Baseline upregulated ERE classes included LINE (27%), SINE (30%), LTR (23%), simple repeats (10%), and others (10%) in melanoma, and LINE (34%), SINE (21%), LTR (29%), simple repeats (8%), and others (8%) in NSCLC. Differential ERE expression was observed in RP compared to NR across B samples in both cohorts (melanoma: RP vs NR Zscore 0.50 vs -0.23, p< 0.001; NSCLC: RP vs NR Zscore 0.89 vs -0.27, p= 0.001). In the melanoma cohort, on-treatment samples confirmed higher ERE expression in RP vs NR (Zscore 0.77 vs -0.32, p< 0.001). A moderate positive correlation between TPMscore of RP and CD8+ T cell expression vs NR was seen in the melanoma pts in B samples (Pearson correlation R = 0.54, p = 0.001) and on-treatment (R= 0.62, p< 0.001), but no correlation was seen in B samples of the NSCLC cohort (R= 0.2, p= 0.31). Zscore did not correlate with TMB in melanoma or NSCLC pts. In melanoma pts, the Zscore showed a moderate positive correlation with CYT immune score (R= 0.41, p= 0.017). Conclusion: This validation study on melanoma and NSCLC pts adds to the previously observed association of ERE upregulation and clinical outcomes during ICB treatment in a pan-cancer cohort. The association with CD8+ T cell infiltration and CYT immune score, but not with TMB, suggests an immune activation independent of other biomarkers such as TMB. Citation Format: Mercedes Herrera, Sajid A. Marhon, Farnoosh Abbas-Aghababazadeh, David Chen, Amy Liu, Helen LooYau, Emily Van de Laar, Jeffrey Bruce, Helen Chow, Philippe L. Bedard, Albiruni Razak, Anna Spreafico, Aaron R. Hansen, Marcus O. Butler, Stephanie Lheureux, Trevor J. Pugh, Benjamin Haibe-Kains, Daniel D. De Carvalho, Lillian L. Siu, Pavlina Spiliopoulou. Independent validation of endogenous retrotransposable elements as predictive biomarkers of immune checkpoint blockade response [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 2060.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.076
GPT teacher head0.409
Teacher spread0.333 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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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Citations1
Published2025
Admission routes1
Has abstractyes

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