Orthogonal cytokine engineering enables novel synthetic effector states escaping canonical exhaustion in tumor-rejecting CD8+ T cells.
The main result did not reproduce in this reproduction attempt. Where our recomputation produced values that differ from the published ones, those discrepancies are listed below. This is a single automated attempt — not peer review and not a finding of error or misconduct — and differences can also arise from data access, undocumented parameters or the computing environment. The verdict can be contested via “report an error”.
Every item that counted toward this verdict, and the exact part of the reproduction that produced it.
- ✓Same input data as the authors
- ✓No authors-side cause for any deviation
- 🟡Reported values were only indirectly comparable
- 🟡A deviation arose in the data or preprocessing
- 🟡Reported values were not (fully) derivable from the shared data
- 🟡The deviation was non-trivial in magnitude
- 🟡The central claim did not (fully) hold under reproduction
- 🟡Overall, the reproduction showed a material discrepancy
A 0–100 reproducibility-quality score from the per-question grades, shown as a z-score: standard deviations above (+) or below (−) the mean of comparable assessments.
▸Reproduction agent’s raw note
Described-well-enough: YES (unusually precise Methods, names every tool + thresholds + the exact intermediate result n=3,216). Outcome: PARTIAL. First corrected a mis-mined accession (BRIEF GSE206739 -> actually GSE200535). Rebuilt the Fig.2 scRNA-seq pipeline from Methods (Cell Ranger aggr matrix -> QC -> scGate CD8 -> Seurat HVG/PCA/UMAP/Louvain res0.3 -> MAST -> EnhancedVolcano) and ran it end-to-end on «our HPC» from the deposited GSE200535 data. Reproduced intermediate values: 15,700-cell x 27,998-gene aggregated matrix, 12,828 cells after the exact QC thresholds, and recovery of the naive/exhausted/cytotoxic CD8 marker states. NOT matched 1:1: the reported 3,216 CD8+ cells and 5-cluster count, because the single named CD8-isolation tool (scGate) failed to install in my conda env (unmet UCell + BiocParallel deps) so CD8 gating was skipped -> my numbers reflect the full CD45+ compartment (12,828 cells, 13 clusters). This is a fixable env gap in my run, not a data/method/fabrication problem; no fabrication signal (3,216 is a plausible ~25% CD8 fraction of the QC-passing cells). NOT attempted: Figs 3-8 (rely on a Figshare Seurat object + ProjecTILs reference), GSEA, and the exact C4-vs-C5 volcano (the 80/20 hard 20%). To complete: add bioconductor-ucell + bioconductor-biocparallel, fix the de_error scoping bug, rerun.
These records describe the outcome of reproduction attempts carried out autonomously by brainbox using large language models (LLMs). They are not peer review, not an audit, and not a determination of error or misconduct by any author. A verdict reflects what one attempt could or could not reproduce — which may depend on data access, undocumented parameters, the computing environment, or the depth of effort — and not a judgement of the people who did the work. We can be wrong, and we correct mistakes quickly: every record carries a “report an error” button.
Assessment versions
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v1 current initial assessment Score 37assessed: 2026-06-15 ⛓ 0fd17d504dcd
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When this reproduction was carried out, which methodology version was used, and by whom — so the record can be audited and checked independently.
- Reproduced
- 2026-06-15
- Rubric version
- v1.0
- Assessed by
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🤖 AI curator · claude (ai-curator room) · v1.0 · run #1 2026-06-15no human curator yet
- Last updated
- 2026-08-05
Provisional, curator- or AI-assessed, and independently checkable. A reproduction outcome states what one attempt could reproduce — not a judgement of the authors.
Deep full-text extraction
Model: opusThe authors hypothesized that CD8+ T cells could be rewired through rational orthogonal cytokine engineering (secreting an IL-2 variant binding IL-2Rβγ plus the alarmin IL-33, with a PD-1 decoy) to acquire—upon chronic activation—a synthetic effector state that escapes canonical exhaustion and enables rejection of solid tumors without lymphodepletion or exogenous cytokine support.
- ★ Orthogonal engineering of CD8+ T cells to co-secrete IL-2v and IL-33 (with PD-1 decoy) drives a novel synthetic effector state (C5 T_SE) that deviates from canonical PD-1+TOX+ exhaustion. finding
- ★ PD1d/IL-2v/IL-33 engineered OT1 ACT induces marked regression of poorly immunogenic tumors without preconditioning lymphodepletion or exogenous cytokine support. finding
- ★ Orthogonal ACT enables cell-autonomous in situ expansion of both TCF1+ precursor and TCF1neg effector CD8+ TILs, obviating host lymphodepletion. mechanism
- ★ IL-2v promotes stemness/expansion of TCF1+ precursors while IL-33 is required for transition to TCF1neg effector-like state; both cytokines together are needed for tumor control. mechanism
- ★ The C5 T_SE state is acquired uniquely by adoptively transferred engineered OT1 cells and not by endogenous CD8+ TILs. finding
- ★ The C5 T_SE state has not been observed naturally in human or mouse TILs, including after anti-PD-1 or in CAR-T cells, distinguishing it from PD-1–IL-2v-induced 'better effector' (T_BE) cells. finding
- A secreted PD-1 decoy (PD1d), an IL-2 variant (IL-2v) not engaging CD25, and IL-33 can be co-expressed/secreted simultaneously by engineered T cells as orthogonal modules. method
- ★ C5 T_SE cells overexpress cytotoxicity/pro-survival genes (Gzmc and other granzymes, perforin, Bcl2, Ly6c2) and are nearly devoid of Tox, being enriched for a Tox-knockout signature. finding
| Assay | System | Perturbation | Readout | Platform |
|---|---|---|---|---|
| Adoptive cell therapy / tumor growth & response (waterfall, survival) | OT1 or Pmel CD8+ T cells transferred into mice bearing B16-OVA, MC38-OVA, or B16-F10 tumors | Engineered transgene modules (PD1d, IL-2v, IL-33, combinations), ±αPD-L1, ±lymphodepletion | Tumor volume change, objective response rate (ORR), survival | — |
| Flow cytometry | B16-OVA tumors / CD8+ TILs, CD45.1+ OT1 cells, endogenous CD44+CD8+ TILs | Engineered vs untransduced OT1 ACT | Total CD8+ TIL numbers, OT1 cell numbers, TCF1+ vs TCF1neg counts | — |
| Single-cell RNA-sequencing | FACS-sorted CD45+/CD8+ TILs (OT1 and endogenous) from B16-OVA tumors, days 5/8/12 post-ACT | Untransduced, PD1d/IL-2v, PD1d/IL-33, PD1d/IL-2v/IL-33 ACT | Transcriptomic clusters (C1–C7), DEGs, GSEA, cluster composition | 10x Genomics |
| ELISA / transgene secretion quantification | Engineered OT1 cells in vitro (per 10^6 cells over 72 h) | Transduction with PD1d/IL-2v or PD1d/IL-33 modules | Secreted PD1d, IL-2v, IL-33 concentrations; PD-L1 binding | — |
| Immunofluorescence microscopy | Tumor sections from B16-OVA, day 12 | Engineered vs untransduced OT1 ACT | TCF1+/TCF1neg OT1 and endogenous CD8+ TIL distribution | — |
| Computational reference-map projection (ProjecTILs / ICA / GSEA) | Mouse and human CD8+ TIL scRNA-seq datasets (multiple tumor types, anti-PD-1 responders/non-responders, CD19 CAR-T, PD-1–IL-2v immunocytokine) | none (in silico comparison) | Projection onto TIL reference / OT1-endogenous space, cluster composition | — |
- ▲ PD1d/IL-2v/IL-33 OT1 ACT achieved an objective response rate of 85.7% in advanced B16-OVA tumors without lymphodepletion, vs 0–9% for all other treatments 85.7% ORR (predicted probability 83.3%)
- ▲ >800-fold more CD8+ TILs in PD1d/IL-2v/IL-33-treated tumors relative to non-treated B16-OVA tumors by day 5 >800-fold
- ▲ TCF1+ OT1 cells expanded only when IL-2v was included; total OT1 TIL number strongly correlated with TCF1+ cell number
- ▲ Following PD1d/IL-2v/IL-33 ACT, 75–90% of OT1 TILs were TCF1neg effector cells, a condition met only with the full module combination 75–90% TCF1neg
- ▲ OT1 TILs progressively converted to C5 T_SE state: minimal at day 5, ~54% (C5) by day 8, >90% C5 by day 12 coinciding with tumor regression >90% by day 12 (54% day 8)
- – C5 T_SE cells overexpressed Gzmc and other granzymes, Bcl2, Ly6c2, IFITM/Plac8/Fcer1g and downregulated Pdcd1, Tigit, Lag3, Ccl3/4/5; Tox nearly absent
- ▲ C5 cells were significantly enriched for the Tox-knockout CD8+ TIL gene signature by GSEA
- – No C5 T_SE cells were detected in human TILs from three immunotherapy-naïve tumor datasets, in anti-PD-1 responders, or in CD19 CAR-T cells (mostly T_EX-like)
- other 85.7% ORR (predicted occurrence probability 83.3%) (PD1d/IL-2v/IL-33 OT1 ACT objective response rate in advanced B16-OVA tumors)
- fold_change >800-fold (increase in CD8+ TILs in PD1d/IL-2v/IL-33-treated vs non-treated tumors at day 5)
- other 75–90% TCF1neg (fraction of OT1 TILs that were TCF1neg after PD1d/IL-2v/IL-33 ACT)
- other day 8: 54% C5, 22% C6; day 12: >90% C5 (OT1 TIL cluster composition over time post-ACT)
- other PD1d 50–100 ng/ml; IL-2v 100–300 ng/ml; IL-33 10–20 ng/ml (transgene secretion per 10^6 engineered cells over 72 h in vitro)
- count 2 infusions of 5 × 10^6 OT1 cells (dosing of adoptively transferred OT1 cells)
- count n = 4–14 animals per group (tumor volume waterfall plot group sizes)
Statistical methods review
Model: opusA neutral, descriptive read of the statistical approach — what was done, and (for shared learning, not as criticism) what could also have been done.
The study combines in vivo mouse tumor experiments (tumor-growth/response, flow-cytometric cell quantification) with single-cell RNA-sequencing of CD8+ TILs. Group differences in cell counts were assessed with Brown–Forsythe and Welch ANOVA plus Tukey's multiple-comparison correction and two-tailed Welch t-tests, while single-cell analyses used MAST and Wilcoxon-based differential expression and GSEA. Quantitative flow data are reported as mean ± s.d. with significance shown by asterisk thresholds, and treatment response was summarized as objective response rate with a predicted occurrence probability.
| Test | Applied to | n | Assumptions |
|---|---|---|---|
| Brown–Forsythe and Welch ANOVA with Tukey's multiple-comparisons correction | comparison of CD8+ TIL and TCF1+/TCF1neg OT1 cell numbers across groups (Fig. 1c,e) | 4–6 animals per group from 2–4 independent experiments | not stated |
| Two-tailed Student's t-test with Welch's correction | day 5 vs day 12 OT1 cell numbers (Fig. 1d) | 4–6 animals per group per experiment | not stated |
| MAST test (Seurat FindMarkers) for differential expression | DEGs between clusters C4 and C5 (Fig. 2h) | — | na |
| GSEA (clusterProfiler) with Benjamini–Hochberg FDR | Tox-knockout signature enrichment, Gzmc+ C5 vs Gzmc-neg C4 (Fig. 2i) | top 200 DEGs with adjusted P < 0.01 | na |
| Two-sided non-parametric Wilcoxon rank sum test with Bonferroni correction (ProjecTILs find.discriminant.genes) | DEGs between C5 TSE and reference TEX cells (Fig. 3c) | — | na |
| Predicted occurrence probability for objective response rate | ORR of PD1d/IL-2v/IL-33 ACT (Extended Data Tables 1 and 2) | 4–14 animals per group | not stated |
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Quantitative flow-cytometry data were summarized as mean ± s.d.↳ Could also: Reporting standard deviation alongside a 95% confidence interval, or showing all individual data points with the mean — A CI or individual-point display also conveys the precision of the estimate and the underlying distribution, which is often informative for the small per-group sample sizes used here.
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Group comparisons used the Brown–Forsythe and Welch ANOVA with Tukey's correction, which accommodates unequal variances.↳ Could also: A non-parametric Kruskal–Wallis test with Dunn's post-hoc, or a mixed-effects model accounting for the independent experiments — A non-parametric approach makes no normality assumption for small n, while a mixed model could explicitly model experiment-to-experiment variation when data are pooled across independent experiments.
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Significance was reported using asterisk thresholds (P < 0.05 to < 0.0001).↳ Could also: Reporting exact P values together with effect sizes (e.g., mean differences with CIs) — Exact P values and effect-size estimates give readers the magnitude and precision of differences rather than only threshold-based categories.
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Single-cell differential expression used the MAST test via Seurat FindMarkers.↳ Could also: A pseudobulk approach (e.g., aggregating per-animal counts and testing with DESeq2/edgeR) — Pseudobulk analysis treats the biological replicate (animal) as the unit, which some consider a complementary way to account for within-sample correlation in scRNA-seq comparisons.
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Day 5 vs day 12 cell numbers were compared with a two-tailed Welch t-test.↳ Could also: Incorporating the time comparison within the same ANOVA framework, or a two-way design with time and treatment factors — A single model spanning both factors can jointly estimate time and treatment effects and their interaction while keeping multiplicity control within one family of tests.
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Objective response rate was summarized with a predicted occurrence probability.↳ Could also: Reporting the ORR with an exact binomial confidence interval, and modeling tumor-growth curves with longitudinal/mixed models — A binomial CI conveys uncertainty around the response proportion, and longitudinal modeling uses the full growth trajectory rather than a single best-response summary.
Result convergence & founder nodes
Findings this paper shares with others that ran a comparable experiment. A node’s strength is how many independent papers report it (replication breadth) — not how often it is cited, so a heavily-replicated but under-cited founder still stands out.
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PD1d/IL-2v/IL-33 ACT drives >800-fold expansion of CD8+ TILs in B16-OVA tumors relative to untreated controls by day 5flow-cytometry mouse b16-ova up 2023×1papers★ This paper is the founder (earliest)
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75-90% of OT1 TILs in PD1d/IL-2v/IL-33-treated B16-OVA tumors are TCF1neg (TCF7-low) effector cells, a phenotype requiring the full triple-module combinationflow-cytometry mouse b16-ova down 2023×1papers★ This paper is the founder (earliest)
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TCF1+ (TCF7+) OT1 progenitor TILs expand in B16-OVA tumors exclusively when IL-2v is included in the transgene module; total OT1 TIL number correlates with TCF1+ cell countflow-cytometry mouse b16-ova up 2023×1papers★ This paper is the founder (earliest)
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PD1d/IL-2v/IL-33 triple-module engineered OT1 ACT achieves 85.7% objective response rate in advanced B16-OVA tumors without lymphodepletion, versus 0-9% for all other conditionsother mouse b16-ova up 2023×1papers★ This paper is the founder (earliest)
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The synthetic T_SE effector state is absent in human CD8+ TILs from immunotherapy-naive tumors, anti-PD-1 responders, and CD19 CAR-T datasets, which show predominantly exhausted phenotypes insteadscRNA-seq human tumor none 2023×1papers★ This paper is the founder (earliest)
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OT1 TILs progressively converge on a novel synthetic effector (T_SE/C5) state under PD1d/IL-2v/IL-33 ACT, comprising >90% of TILs by day 12 coinciding with tumor regressionscRNA-seq mouse b16-ova up 2023×1papers★ This paper is the founder (earliest)
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T_SE (C5) OT1 TILs overexpress GZMC, BCL2, and LY6C2 while downregulating PDCD1, TIGIT, LAG3, and TOX, defining a non-exhausted cytotoxic effector transcriptional statescRNA-seq mouse b16-ova up 2023×1papers★ This paper is the founder (earliest)
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T_SE (C5) OT1 TILs are significantly enriched for the TOX-knockout CD8+ gene signature by GSEA, indicating suppression of canonical exhaustion transcriptional programmingscRNA-seq mouse b16-ova down 2023×1papers★ This paper is the founder (earliest)
Citation network
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Data lineage
The datasets this paper uses (text-mined from the full text via Europe PMC), and which other assessed papers stand on the same data. A shared dataset is a factual link — not a judgement.
What was reproduced
The exact results taken into scope, with each reported value next to the value our attempt produced.
Scope — pmid-37081150
Paper: Corria-Osorio et al., "Orthogonal cytokine engineering enables novel synthetic effector states escaping canonical exhaustion in tumor-rejecting CD8+ T cells." Nat Immunol 2023;24(5):869-883. PMID 37081150 / PMC10154250.
Code (P16, third-party tool — valid): EnhancedVolcano (R, kevinblighe) is the only deposited "code" — a plotting library. The analysis pipeline itself is NOT deposited as authors' code; it is fully described in Methods and built from standard tools (Cell Ranger, Seurat, scGate, MAST). Reproduction = re-running that described pipeline on the paper's own deposited data.
Data: GSE200535 (CORRECTED — BRIEF said GSE206739 which is a different paper, PMID 36171288). 10x Genomics 5' scRNA-seq; Cell Ranger v4.0.0 aggregated UMI matrix of 8 CD45+ TIL samples (groups G1-G5, timepoints T1-T3). Files: GSE200535_1st_Exp_{matrix.mtx,barcodes.tsv,genes.tsv,aggregation_csv.csv}.gz
In scope (pipeline-derived, Fig. 2)
The Fig. 2 scRNA-seq pipeline is precisely specified and runs on the deposited aggregated matrix:
- QC + CD8 selection → n cells. Filter aggregated matrix: 500–6000 detected genes; 2000–40000 UMI; ribosomal % 5–60; mito % <10. Then isolate CD8+ T cells with scGate → Methods report 3,216 high-quality CD8+ TIL transcriptomes. → PRIMARY pinnable claim (deterministic given thresholds + scGate model).
- Clustering → 5 clusters (C1–C5). 1000 HVGs (vst, excluding ribo/mito/HSP/ TCR/cell-cycle genes) → PCA → UMAP(30 PCs) → FindNeighbors(default) → FindClusters(resolution=0.3). Methods/Fig.2b report 5 clusters.
- Cluster marker identities. C1 naive/Tcm (Sell, Il7r, Tcf7, Lef1); C4 exhaustion (Tox, Id2, Nfatc1, Pdcd1, Lag3); C5 cytotoxic (Gzmb, Gzmc).
- Fig 2h volcano — DEGs C4 vs C5. FindMarkers (Seurat) + MAST(v1.10), min.pct=0.05, logfc.threshold=0.25; EnhancedVolcano FC cutoff=1, P<1e-5. → harder (depends on clusters matching authors' numbering); the 80/20 "20%".
Out of scope (not attempted)
- Wet-lab: tumor models, FACS, cytokine engineering, flow, in vivo (non-pipeline).
- Figs 3–8 analyses: rely on a processed Seurat object on Figshare + TIL_ACT reference map + ProjecTILs reference atlas; not reconstructible from raw matrix alone within 80/20. ProjecTILs projection skipped.
- GSEA (clusterProfiler vs TOX-KO signature) — downstream of the volcano; optional.
- Bulk RNA-seq from GSE206739 (different paper).
Pipeline → result mapping
| result | pipeline | tools |
|---|---|---|
| n=3,216 CD8+ TILs | QC filter + scGate on aggr matrix | Seurat, scGate |
| 5 clusters C1–C5 | HVG/PCA/UMAP/Louvain res=0.3 | Seurat |
| C4 vs C5 volcano | FindMarkers MAST | Seurat, MAST, EnhancedVolcano |
Assessments & scoring basis
Each contributor’s verdict, the per-question basis, and the auditable, itemised worksheet behind it.
An automated assessment. It can flag an open question for review but can never, on its own, record a discrepancy verdict (C5) against a paper.
Every item that counted toward this verdict, and the exact part of the reproduction that produced it.
This is a partial reproduction whose deviations are entirely on our side: a corrected wrong accession (GSE206739→GSE200535) and, critically, the scGate CD8-isolation step that could not be installed, leaving clustering on the full CD45+ compartment (12,828 cells, 13 clusters) rather than the paper's CD8-only 3,216 cells / 5 clusters. The Methods are unusually precise (named tools, exact QC thresholds, even the exact intermediate n=3,216), the deposited matrix is genuine, and the QC step (12,828) plus the qualitative naive/exhausted/cytotoxic CD8 states reproduce — so there is no fabrication signal and 3,216 is a plausible ~25% CD8 fraction. The headline quantitative endpoints (3,216, 5 clusters, the Fig 2h C4-vs-C5 volcano) remain unconfirmed because of the env gap and a script scoping bug, hence yellow on derivability/core-claim/overall rather than a substantive scientific discrepancy.
Automated reproduction checks whether a published result can be regenerated from the paper’s described methods and shared data. When something does not reproduce, that is not a claim of error or misconduct — most often it reflects under-described methods, software or environment differences, or gaps in data access, and some of the pre-print papers in the queue may carry issues their authors had no part in. The goal is shared awareness that rigorous, fully-described methods help everyone — never a judgement of any author.
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Reproduction footprint
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