A technical feasibility report on correlative studies from the investigator-initiated phase II study of pembrolizumab (Pembro) immunological response evaluation (INSPIRE).
Bibliographic record
Abstract
11607 Background: Validated biomarkers of response to immune checkpoint inhibitors are needed. Methods: INSPIRE (NCT02644369) is a biomarker-driven study to comprehensively evaluate changes in genomic and immune landscapes in tumors and blood of patients (pts) treated with pembro at 200 mg IV Q3W. It consists of 5 histological cohorts of 20 evaluable pts each: head and neck squamous cell cancer (SCCHN), triple negative breast cancer (TNBC), high grade serous ovarian cancer (HGSOC), melanoma (MM) and mixed solid tumors (MST). All pts undergo pre- and on-treatment (week 6-9) fresh tumor biopsies (bx), and at progression for responders. The first core bx is for immunohistochemistry and subsequent cores are pooled to create single cell suspension for 5 prioritized biomarker assay groups: (1) whole exome/RNA-/TCR-sequencing; (2) T/B/NK, APCs, and/or Treg phenotyping; (3) patient-derived xenografts; (4) RNA-seq on viably sorted immune populations; (5) TIL expansion and characterization. Serial blood samples for immunophenotyping, chemokines/cytokines and ctDNA are collected. Results: 53 pts were enrolled from March 21, 2016-January 16, 2017 (5 SCCHN, 8 TNBC, 17 HGSOC, 7 MM, 16 MST). 84 tumor bx (53 pre-, 30 on-treatment, 1 progression) and 244 blood-based biomarker samples have been collected. The most common sites of tumor bx were: lymph nodes (27%), liver (22%) and skin (14%) (see table). For the 5 cohorts, the % of tumor bx with sufficient cellularity for biomarker assay groups 1 and 2 are: SCCHN (33%), TNBC (9%), HGSOC (52%), MM (55%), MST (55%). Conclusions: This report provides robust technical feasibility data to plan immune and molecular characterization of tumor and blood-based biomarkers in pts receiving ICI. Clinical trial information: NCT02644369. [Table: see text]
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 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 | 0.039 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.018 | 0.007 |
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".