Endogenous retrotransposable elements as a novel predictive biomarker of response to immunotherapy.
Bibliographic record
Abstract
2628 Background: Non-coding DNA repetitive sequences such as the endogenous retrotransposable elements (EREs) can influence the transcription of adjacent genes and shape antitumor immune responses through viral mimicry. Here, we examine the role of EREs as a biomarker of response to immune-checkpoint inhibition (ICI) in the phase II INSPIRE trial (NTC02644369). Methods: Baseline (B) and on-treatment (T) tumor samples from patients (pts) with advance solid tumors treated with pembrolizumab were retrospectively analyzed. Response was evaluated by RECIST 1.1; pts were classified as responders (R) (complete or partial response) or non-responders (NR) (progressive disease). ERE expression was analyzed by total RNA-seq in B and T samples. Differentially expressed EREs between R and NR were quantified by the TPM score (mean of normalized transcript per million values for upregulated ERE in a sample comparison) and its standardized Z score. For survival analysis, EREs were dichotomized into high or low expression based on median Z score values of R versus NR. CD8+ population was inferred by CIBERSORT of RNAseq data. Multivariable Cox regression models were used to assess PFS and OS. Results: 82/106 pts with median age 52y (21-80), 59% female, in 5 tumor cohorts (head and neck 16%, triple negative breast cancer 16%, ovarian 22%, melanoma 12%, and mixed tumor cohort 34%) were available for analysis after data QC. Of 82 pts, 14 (17.3%) were classified as R and 44 (54.3%) as NR. Differential ERE expression was observed between R and NR to pembrolizumab at baseline (B Z score 0.22 vs -0.21 p <0.001) and on-treatment (T Z score 1.12 vs -0.29 p <0.001). The upregulated EREs were LINE (32.2%), SINE (30.5%) and LTR (20.9%) at baseline; and LINE (15.9%) SINE (59.9%) and LTR (9.1%) on treatment. An elevated ERE expression was observed in T samples compared to B, in both R (Z score 0.48 vs -0.26 p=0.009) and NR (Z score 0.25 vs -0.31 p <0.001). A strong positive correlation between EREs TPM score of all ERE subgroups and CD8+ was seen when comparing B vs T samples of responders (R 0.79, p=0.006), while in NR a weak positive correlation was seen only in some ERE subgroups (Alu R=0.38, p=0.02; LINE R 0.35, p=0.03). Of 74 pts with survival data and median follow-up of 14 months (m) (2.3-76.8), median PFS and OS were 1.9m and 14m, respectively. Multivariable analysis including ERE expression, cohort, PD-L1 and TMB, showed higher ERE expression was associated with longer PFS (1.9m vs 10.1m, aHR 0.07, 95% CI 0.03-0.18, p <0.001) and OS (8.3m vs 22.6m, aHR 0.4, 95% IC 0.22-0.74; p=0.004). Long-term survivors (OS ≥60m) had higher ERE Z score vs pts with OS <60m (0.18 vs -0.15, p=0.03), and specifically SINE (p=0.02) and LTR (p=0.03) subgroups. Conclusions: Tumor ERE expression analysis between ICI responders and NR suggests an association between ERE upregulation and radiological response, PFS and OS during ICI treatment. Further validation studies are warranted.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".