Multi-scale integrative analyses identify THBS2+ cancer-associated fibroblasts as a key orchestrator promoting aggressiveness in early-stage lung ade
The main results reproduced, with only marginal, non-material deviations.
- Nothing in this column.
- 🟡Could not use the authors’ exact input data
- 🟡Reported values were only indirectly comparable
- 🟡A deviation arose in the data or preprocessing
- 🟡A deviation was attributed to the published material
- 🟡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 to PARTIALLY reproduce from the single open dataset pinned to this room. The paper is a large multi-scale study whose headline results (THBS2+ CAF discovery via scRNA-seq, CellChat ligand-receptor signaling, WGCNA + Cox survival) all rest on the authors' OWN unreleased single-cell and clinical-cohort data and are not reproducible from public data. Using GSE10072 (the pinned Affymetrix LUAD tumor-vs-normal microarray, 58 tumor / 49 normal), a clean limma DE on «our HPC» independently CORROBORATES the paper's central tumor-enrichment claim: THBS2 is strongly upregulated in tumor (logFC +2.09, adj.P 4.7e-22), and 7 of 8 testable THBS2+ CAF signature markers (COL3A1, COL5A2, COL1A1, COL6A3, FAP, SULF1, + THBS2) are significantly upregulated in tumor vs normal — consistent with CAF/stromal enrichment in tumor tissue. BGN was borderline (adj.P 0.088) and CTHRC1 is not on the older U133A array. This is an honest 1:1 directional corroboration of the open-data slice, NOT a reproduction of the single-cell / CellChat / survival results, which the pinned code (CellChat) cannot regenerate without the unreleased data. compute_ran=true, «our HPC» reachable throughout; healthy=true (run completed as intended).
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
Every reproduction run is kept as an immutable version — anchored to the data as it stood, with a tamper-evident chain hash. A rerun (e.g. after an author updates a deposit) adds a new version; the previous one stays on record.
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v1 current initial assessment Score 68assessed: 2026-06-20 ⛓ 54fc3933c122
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Provenance — full disclosure
When this reproduction was carried out, which methodology version was used, and by whom — so the record can be audited and checked independently.
- Reproduced
- 2026-06-20
- Rubric version
- v1.0
- Assessed by
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🤖 AI curator · claude (ai-curator room) · v1.0 · run #1 2026-06-19no 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: sonnetThe study tests whether a specific molecular biomarker and its cellular source in the tumor microenvironment can explain and predict the aggressive, high-risk phenotype seen in a subset of pathologically node-negative (pN0), early-stage lung adenocarcinoma patients who have poor post-surgical outcomes despite curative resection.
- ★ THBS2 is a tumor size-independent biomarker that robustly predicts post-surgical OS and RFS in multiple independent early-stage LUAD cohorts finding
- ★ THBS2 is exclusively derived from a specific CAF subset distinct from CAFs defined by classical markers finding
- ★ THBS2 is preferentially secreted via exosomes in early-stage LUAD tumors with high aggressiveness finding
- ★ THBS2-high early-stage LUAD is characterized by suppressed antitumor immunity, decreased immune infiltrates, and increased immune exhaustion markers finding
- ★ THBS2+ CAFs mainly interact with B cells, CD8+ T lymphocytes, and macrophages within the tumor microenvironment finding
- ★ High THBS2 expression predicts poor response to immunotherapy and short post-treatment survival finding
- ★ THBS2 recombinant protein suppresses ex vivo T cell proliferation and promotes in vivo LUAD tumor growth and distant micro-metastasis mechanism
- WGCNA applied to TCGA LUAD transcriptomic and survival data identifies gene modules correlated with RFS/OS to nominate biomarker candidates method
| Assay | System | Perturbation | Readout | Platform |
|---|---|---|---|---|
| WGCNA / bulk transcriptomics | TCGA pN0/M0-stage LUAD tumor tissue | none | gene co-expression modules correlated with RFS and OS | — |
| scRNA-seq | paired primary human LUAD tumor and matched normal lung tissue (Huadong Hospital) | none | cell type identity and CAF subclustering | 10X Genomics Chromium; Illumina NovaSeq 6000 |
| GSEA (hallmark gene sets) | THBS2+ vs THBS2- CAFs (scRNA-seq derived) | none | differentially enriched pathways | — |
| Cell-cell interaction network analysis (CellChat) | scRNA-seq data from lung cancer samples | none | ligand-receptor interactions among cell types | CellChat R toolkit v1.1.2 |
| Exosome isolation and characterization (TEM, NTA, Western blot) | human LUAD tumor tissue, normal adjacent tissue, and plasma (patients and healthy donors) | none | exosome morphology, size, and THBS2/marker protein levels | SEC + ultracentrifugation; ZetaView PMX 110; H-7650 TEM |
| Transwell migration assay | LUAD cell line | THBS2 recombinant protein (50 ng/mL) vs PBS | cell migration | Corning Transwell plates |
| Ex vivo T cell proliferation assay | T cells | THBS2 recombinant protein | T cell proliferation | — |
| In vivo tumor growth/metastasis assay | LUAD mouse model | THBS2 recombinant protein | tumor growth and distant micro-metastasis | — |
- ▲ THBS2 high expression predicts poor OS and RFS in multiple independent early-stage LUAD cohorts, independent of tumor size
- – THBS2 is exclusively expressed by a distinct CAF subset not captured by classical CAF markers
- ▲ THBS2 is preferentially secreted via exosomes in tumors with high aggressiveness
- ▲ Plasma THBS2 levels associate with short recurrence-free survival
- – THBS2-high LUAD shows decreased immune cell infiltrates and increased immune exhaustion markers
- ▲ High THBS2 expression predicts poor immunotherapy response and shorter post-treatment survival
- ▼ THBS2 recombinant protein suppresses ex vivo T cell proliferation
- ▲ THBS2 recombinant protein promotes in vivo LUAD tumor growth and distant micro-metastasis
- count 43,779 (total number of cells clustered and visualized by UMAP in scRNA-seq analysis)
- count 332 CAFs categorized into 10 clusters (number of cancer-associated fibroblasts identified and subclustered)
- other soft-thresholding power = 12, scale-free R2 ≈ 0.9, cut height = 0.25, minimal module size = 30 (WGCNA parameters used to construct gene co-expression network)
- count top 30 intramodular connected genes (definition of hub genes in WGCNA module)
- count N = 5 tumor, N = 5 normal adjacent tissue (tissue samples used for exosome isolation)
- count N = 5 pN0M0-LUAD, N = 5 healthy controls (plasma samples used for exosome isolation and comparison)
- other Transwell assay results from three independent experiments (replication of migration assay)
Statistical methods review
Model: sonnetA neutral, descriptive read of the statistical approach — what was done, and (for shared learning, not as criticism) what could also have been done.
The paper uses a multi-omic, cohort-based discovery-and-validation design: WGCNA (module eigengenes correlated with RFS/OS via Pearson correlation) applied to TCGA LUAD transcriptomic data to nominate a prognostic gene, followed by validation of THBS2 across independent transcriptomic, proteomic, and single-cell cohorts. Functional characterization used GO/KEGG/Reactome and GSEA pathway enrichment, Seurat-based single-cell clustering/marker identification, and CellChat ligand-receptor interaction scoring, alongside in vitro (e.g., Transwell, three independent experiments) and in vivo functional assays and RECIST v1.1-based clinical response classification. The provided text does not include a dedicated 'Statistical Analysis' subsection detailing specific inferential group-comparison tests, survival-analysis methods, or multiple-testing correction, so several standard reporting fields below are marked as not stated.
| Test | Applied to | n | Assumptions |
|---|---|---|---|
| Pearson correlation (WGCNA module eigengene vs. clinical trait) | Correlating co-expression module eigengenes with RFS and OS in the TCGA LUAD training cohort | — | not stated |
| Gene Ontology / KEGG / Reactome pathway enrichment analysis | Functional characterization of the RFS/OS-associated WGCNA module | — | not stated |
| Gene set enrichment analysis (GSEA, hallmark gene sets) | Differentially expressed genes between THBS2+ and THBS2- cancer-associated fibroblasts | 332 CAFs (categorized into 10 clusters) | not stated |
| Ligand-receptor interaction scoring (CellChat) | Cell-cell interaction network among cell types in the tumor microenvironment | 43,779 cells (scRNA-seq) | not stated |
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Module-trait relationships in WGCNA were assessed by correlating module eigengenes with RFS and OS using Pearson correlation.↳ Could also: A Cox proportional-hazards model, or a log-rank test comparing eigengene-defined groups, could also be used — RFS and OS are time-to-event outcomes with censoring; methods designed for censored survival data explicitly incorporate follow-up time and censoring status, which a direct correlation with a continuous trait value does not.
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Pathway enrichment (GO, KEGG, Reactome) and GSEA were run with default clusterProfiler/GSEABase settings.↳ Could also: Reporting the specific multiple-testing correction applied within these tools (e.g., Benjamini-Hochberg FDR) and/or complementary gene-set testing methods such as fgsea or camera could also be used — Making the correction method explicit helps readers directly compare the false-discovery control across the several enrichment analyses performed.
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Differential expression between THBS2+ and THBS2- CAFs was derived from single-cell data and used as GSEA input.↳ Could also: A pseudobulk approach (aggregating counts per biological replicate before applying DESeq2 or edgeR) could also be used — Pseudobulk methods are designed to account for biological replicate-level variance in scRNA-seq comparisons, which can complement cell-level differential expression testing.
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Functional assay results (e.g., Transwell migration) are reported as derived from three independent experiments, without the comparison test specified in the provided text.↳ Could also: Reporting a specific paired or unpaired test (e.g., Student's t-test) or, for small n, a non-parametric alternative such as the Mann-Whitney U test, together with a dispersion measure (SD or 95% CI), could also be used — With n=3 replicates, explicitly naming the test and showing spread helps convey both statistical and practical significance.
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Exosome/plasma comparisons (e.g., LUAD vs. NAT tissue, patients vs. healthy donors) used small, equal group sizes (n=5) with the comparative test not detailed in the provided text.↳ Could also: A non-parametric test such as the Mann-Whitney U or Wilcoxon rank-sum test could also be considered as an alternative to a t-test — With small sample sizes, distributional (normality) assumptions are harder to verify, and non-parametric tests avoid relying on that assumption.
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WGCNA network parameters (soft-thresholding power=12, cut height=0.25, minimum module size=30) were fixed based on approximate scale-free topology fit (R²≈0.9).↳ Could also: A sensitivity analysis across a range of power/cut-height values, or a module-stability assessment (e.g., bootstrapping/resampling), could also be presented — Showing results are stable across nearby parameter choices can complement a single fixed-parameter network construction.
What was reproduced
The exact results taken into scope, with each reported value next to the value our attempt produced.
Scope — pmid-35547750
Paper: Yang H et al. Multi-scale integrative analyses identify THBS2+ cancer-associated fibroblasts as a key orchestrator promoting aggressiveness in early-stage lung adenocarcinoma. Theranostics 2022. PMID 35547750 · PMCID PMC9065207 · DOI 10.7150/thno.69590.
Pinned code: https://github.com/sqjin/CellChat (third-party scRNA-seq cell-cell communication tool) Pinned data: GEO GSE10072 (Affymetrix HG-U133A microarray, 107 samples; 58 LUAD tumor vs 49 non-tumor lung)
This is a large multi-scale paper (TCGA WGCNA, 9 external microarray validation cohorts, scRNA-seq of 2 own surgical cases, CellChat ligand-receptor analysis, proteomics/RPPA, IHC/mIHC, exosome assays, mouse xenografts). The vast majority of figures rest on the authors' OWN unreleased scRNA-seq, wet-lab, and clinical-cohort data. Per the brief we scope to pipeline-derived results reproducible from the pinned open data (GSE10072).
IN SCOPE (pipeline-derived, reproducible from GSE10072)
The paper uses GSE10072 explicitly as an external transcriptomic validation cohort for tumor-vs-normal comparison ("transcriptomic data of early-stage LUAD and matched normal lung but without survival data"). The reproducible, low-hanging pipeline output is a differential-expression (limma) analysis of LUAD tumor vs normal on GSE10072, testing the direction/significance of the paper's central markers:
- R1 — THBS2 upregulation in tumor. THBS2 is the paper's titular gene; it is reported as a tumor/CAF-enriched, aggressiveness-promoting marker. Reproducible claim: THBS2 is significantly upregulated in LUAD tumor vs normal in GSE10072 (direction + adj.P).
- R2 — THBS2+ CAF top-10 marker signature direction. Paper's top upregulated genes in THBS2+ CAFs (Fig. of CAF markers): THBS2, COL3A1, BGN, COL5A2, COL1A1, COL6A3, FAP, CTHRC1, SULF1. Reproducible claim: these stromal/CAF markers are concordantly upregulated in tumor vs normal microarray (direction + adj.P per gene). This is a coherence check of the CAF signature against bulk tumor-vs-normal expression.
Pipeline named: limma on normalized GSE10072 series-matrix expression (microarray canonical path; method-card 100%-clean for arrays). Grouping from GEO sample titles ("Lung Tumor_" vs "Normal Lung_").
OUT OF SCOPE (not pipeline-derivable from pinned open data)
- CellChat ligand–receptor analysis — requires the authors' OWN scRNA-seq (43,779 cells, 2 surgical cases); no GEO/accession provided for it. CellChat cannot be run on a bulk microarray. Not reproducible from GSE10072 → data unavailable.
- scRNA-seq / Seurat clustering, 7 CAF subclusters, 332→10 clusters — own unreleased data.
- WGCNA on TCGA LUAD, Cox survival / KM, hazard ratios — separate cohorts; GSE10072 has no survival data (paper states this explicitly). Not attempted here (different accession).
- QuanTIseq immune infiltration, GSEA, proteomics/RPPA, IHC/mIHC, exosome assays, xenografts — wet-lab or external-cohort / different-accession; out of scope.
Verdict frame
A clean limma reproduction confirming THBS2 + CAF-marker upregulation in GSE10072 tumor-vs-normal is an honest partial reproduction: it independently corroborates the paper's central tumor-enrichment claim for THBS2 using the one open dataset pinned to this room, while the headline CAF/CellChat results depend on unreleased single-cell data and cannot be reproduced.
Assessments & scoring basis
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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
claude-opus-4-8Measured resources invested to assess this paper — sanitised (machine class only, no job ids/paths). Compute = HPC accounting (SLURM); tokens = the AI agent's session.