Cancer-predicting transcriptomic and epigenetic signatures revealed for ulcerative colitis in patient-derived epithelial organoids.
The main results reproduced, with only marginal, non-material deviations.
Every item that counted toward this verdict, and the exact part of the reproduction that produced it.
- ✓Same input data as the authors
- 🟡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 for a PARTIAL 1:1. GSE102746 is RNA-seq only (20 samples, 10 UC + 10 normal organoids) and ships the authors' processed Cufflinks FPKM table; the listed repo (TrimGalore) is a third-party trimming tool that yields no comparable result on its own, so we reproduced the differential-expression call from the authors' shipped FPKM table using their own thresholds (FDR<0.05 & |log2FC|>1.5). RESULT: the data structure reproduces EXACTLY (35786 genes x 20 samples, groups verified) and the directional asymmetry reproduces ROBUSTLY (reported 84% up; we get 82-85% up). The absolute count 260 does NOT reproduce from the FPKM table with a standard Welch t-test (we get 9 strict / 40 nominal-p / 90 FC-only / 756 FDR-only) -- expected because the paper used Cuffdiff on BAM alignments, a different and less-conservative model than a t-test on FPKM; this is method divergence, NOT a fabrication signal (756 genes pass FDR<0.05 before the FC filter, so a count in the hundreds is plausible under Cuffdiff). NOT ATTEMPTED (the hard ~20%): re-running TopHat2+Cuffdiff from raw FASTQ (SRP115575) to hit 260 exactly; subset-B DE (1,048; sample membership unspecified); ChIP-seq H3K27ac (1,485 sites; raw data not in GSE102746). No fabrication indicated.
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Assessment versions
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v1 current initial assessment Score 65assessed: 2026-06-14 ⛓ 0e89c82fa43a
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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
- 2026-06-14
- 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: opusDo patient-derived primary colonic organoids from ulcerative colitis (UC) patients faithfully recapitulate primary UC tissue at histologic, transcriptomic, and epigenetic levels, and can such models reveal precancerous (colitis-associated cancer) molecular signatures already activated in UC?
- ★ UC patient-derived epithelial organoids histologically phenocopy primary UC tissue, while non-IBD organoids resemble healthy colonic epithelium. finding
- ★ Whole-transcriptome profiling shows upregulation of inflammatory, metabolism, cell adhesion, and cancer pathways in UC organoids relative to non-IBD organoids. finding
- ★ H3K27ac enhancer profiling reveals UC organoid enrichment for gastrointestinal/digestive cancer pathways and oncogenic markers including S100P. finding
- ★ LYZ and NPSR1 are identified as novel markers for GI cancer, enriched in UC organoids at both transcriptomic and epigenetic levels. finding
- ★ Immunolocalization shows increased LYZ, S100P, and NPSR1 protein levels in UC and colitis-associated cancer (CAC). finding
- ★ Patient-derived primary colonic organoids constitute a faithful human-derived model suitable for dissecting UC and CAC pathogenic mechanisms. resource
- ★ UC organoids and tissues already exhibit an oncogenic/precancerous signature validated at histologic, transcriptomic, and epigenetic levels. mechanism
- Integration of RNA-Seq and H3K27ac ChIP-Seq enables identification of susceptibility loci that may serve as functional/mechanistic intervention targets. method
| Assay | System | Perturbation | Readout | Platform |
|---|---|---|---|---|
| Histology / H&E and Alcian Blue–PAS staining | Patient-derived colonic epithelial organoids (UC and non-IBD) | none (disease vs control comparison) | Tissue architecture, mucus content, epithelial organization | — |
| Immunohistochemistry / Immunocytochemistry | Patient-derived colonic organoids and matched primary tissues (UC, non-IBD, CAC) | none | Protein levels of MUC2, Ki-67, chromogranin A, CK19, vimentin, LYZ, S100P, NPSR1 | — |
| Bulk RNA-Seq (whole-transcriptome) | Patient-derived colonic epithelial organoids (10 UC, 10 non-IBD) | none (UC vs non-IBD) | Differential gene expression / pathway enrichment (MSigDB, GO, KEGG, Hallmark, Reactome) | — |
| ChIP-Seq for H3K27ac (active enhancers) | Patient-derived colonic epithelial organoids (5 UC, 5 non-IBD; Ctd150 excluded) | none (UC vs non-IBD) | Genome-wide H3K27ac enrichment / enhancer-associated gene sets | ENCODE normal colonic mucosa used as reference track |
| Short tandem repeat (STR) analysis | Patient-derived organoid isolates | none | Verification of unique patient origin | — |
| Genomic Regions Enrichment of Annotations Tool (GREAT) ontology analysis | H3K27ac ChIP-Seq peak regions from organoids | none | Gene ontology / disease term enrichment | — |
- – 260 transcripts differentially expressed between UC and non-IBD organoids (full cohort) 219 (84%) up, 41 (16%) down
- – Subset B (4 UC vs 4 non-IBD) showed larger differential expression 1,048 transcripts; 864 (82%) up, 184 (18%) down
- ▼ MUC2-positive goblet cells reduced in UC organoids two-fold decrease
- – H3K27ac region-specific sites identified comparing UC vs non-IBD organoids 1,485 sites; 97 within 5 kb of TSS, 894 located 50–500 kb away
- ▲ GREAT ontology enrichment for gastrointestinal neoplasm p=2.85x10^-11
- ▲ GREAT ontology enrichment for digestive system cancer p=7.08x10^-11
- ▲ NPSR1 showed the largest log2 fold-change in the entire RNA-seq cohort and was enriched for H3K27ac
- ▲ LYZ and S100P upregulated in RNA-Seq and enriched for H3K27ac in UC organoids
- count 260 differentially expressed transcripts (FDR<0.05, log2FC>1.5) (Full cohort UC vs non-IBD RNA-Seq)
- count 1,048 differentially expressed transcripts (Subset B (4 UC vs 4 non-IBD) RNA-Seq)
- count 1,485 region-specific H3K27ac sites (ChIP-Seq UC vs non-IBD organoids (5 vs 5))
- pvalue p=2.85x10^-11 (GREAT enrichment for gastrointestinal neoplasm)
- pvalue p=7.08x10^-11 (GREAT enrichment for digestive system cancer)
- fold_change two-fold decrease in MUC2-positive goblet cells (UC vs non-IBD organoids)
- mean 42.3 ± 14.5 years (UC age); disease duration 9.9 ± 9.7 years (UC patient cohort characteristics)
- mean 68.5 ± 7.6 years (Non-IBD patient age at presentation)
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.
This is an observational, cross-sectional genomics study comparing patient-derived colonic organoids (and matched tissues) from ulcerative colitis (UC) versus non-IBD patients using histology, RNA-Seq, and H3K27ac ChIP-Seq. Differential expression and differential acetylation were assessed using fold-change and false-discovery-rate thresholds (log2 fold change > 1.5, FDR < 0.05, Benjamini-Hochberg), with results visualized as volcano/MA plots and principal-component analyses; pathway-level interpretation used gene-set enrichment against MSigDB and region-based ontology via GREAT. Histologic findings were reported descriptively with counts of replicates (e.g., n > 20, n ≥ 3).
| Test | Applied to | n | Assumptions |
|---|---|---|---|
| Differential gene-expression analysis with FDR/Benjamini-Hochberg thresholding (RNA-Seq), reported as log2 fold change and FDR | Volcano plots and gene lists for full cohort (260 transcripts) and Subset B (1,048 transcripts), UC vs non-IBD organoids (Figure 2A, 2E) | full cohort 10 UC vs 10 non-IBD; Subset B 4 UC (Ctd111,139,153,155) vs 4 non-IBD (NL141,143,148,156) | not stated |
| Differential H3K27ac enrichment analysis with FDR thresholding (ChIP-Seq), visualized as MA/volcano plot | H3K27ac UC vs non-IBD organoids (Figure 3A), FDR < 0.05 | 5 non-IBD and 5 UC organoid isolates (Ctd150 excluded) | not stated |
| Gene-set enrichment analysis (MSigDB) | Pathway enrichment of up/downregulated genes, full cohort and Subset B (Figure 2C,2D,2G,2H) and ChIP-seq peaks (Figure 3B) | — | na |
| Principal-component analysis | Clustering of UC vs non-IBD organoid expression profiles (Figure 2B, 2F) | — | na |
| Region-based ontology enrichment (GREAT), reported with p-values | H3K27ac-enriched regions; gastrointestinal neoplasm (p=2.85x10^-11) and digestive system cancer (p=7.08x10^-11) (Supplementary Figure 2) | — | not stated |
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Differentially expressed genes were defined using fixed thresholds (log2 fold change > 1.5 and FDR < 0.05).↳ Could also: Reporting shrunken effect-size estimates and/or formal significance from a count-based model (e.g., DESeq2/edgeR/limma-voom) alongside the thresholds. — Model-based effect-size shrinkage and explicit per-gene statistics can convey both magnitude and uncertainty, which is helpful with modest per-group sample sizes.
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A 'Subset B' of four UC isolates was selected based on PCA clustering for a focused differential-expression analysis.↳ Could also: Presenting both the full-cohort and subset analyses with the selection rule pre-specified, or modeling heterogeneity directly (e.g., including covariates or a mixed model) rather than subsetting. — Showing how results depend on grouping choices, and modeling variability rather than excluding it, can make the heterogeneity of UC easier to interpret.
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Sample sizes were described as counts without an accompanying power or sample-size calculation.↳ Could also: Reporting an a priori or post hoc power consideration, or confidence intervals around key effect estimates. — An explicit power statement or interval estimates communicates the precision achievable with the available organoid cohorts.
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Patient characteristics were summarized as mean ± SD.↳ Could also: Adding median and IQR or range, and 95% confidence intervals for group means. — For small cohorts, medians/IQR and intervals can complement SD by conveying both central tendency and the range of spread.
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Group differences in organoid features (e.g., MUC2-positive goblet cells described as a two-fold decrease) were presented descriptively.↳ Could also: Pairing the descriptive comparison with a formal nonparametric test (e.g., Mann-Whitney U) and reporting the n and exact p-value. — An accompanying inferential statistic with stated n would quantify the comparison alongside the descriptive observation.
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Multiplicity was controlled via Benjamini-Hochberg FDR for the genome-wide screens.↳ Could also: Also stating the correction approach used within the pathway/enrichment analyses (MSigDB, GREAT). — Documenting how multiple comparisons are handled at the pathway level, in addition to the gene level, clarifies the full multiplicity scope.
Citation network
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Data lineage
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What was reproduced
The exact results taken into scope, with each reported value next to the value our attempt produced.
Scope — pmid-29983891
Paper: Sarvestani et al. 2018, Oncotarget — "Cancer-predicting transcriptomic and epigenetic signatures revealed for ulcerative colitis in patient-derived epithelial organoids." DOI 10.18632/oncotarget.25617.
Pipelines named in Methods
| analysis | pipeline | data shipped? |
|---|---|---|
| RNA-seq trimming/QC | TrimGalore (the listed repo) | — (preprocessing only) |
| RNA-seq alignment + quantification | Tuxedo (TopHat/Cufflinks), GRCh38 | yes — FPKM table on GEO |
| RNA-seq differential expression | Tuxedo / Cuffdiff, FDR<0.05 & |log2FC|>1.5 | Cuffdiff output NOT shipped (FPKM is) |
| ChIP-seq (H3K27ac) | FastQC + TrimGalore + Bowtie2 (GRCh19) + MACS2 + DESeq2 | raw ChIP data NOT in GSE102746 |
| qRT-PCR / IHC validation | wet-lab | n/a |
In scope (attempted)
- C3 Processed data structure: shipped FPKM table, 20 samples (10 UC + 10 normal). Directly verifiable.
- C1 Full-cohort DE transcript count (reported 260). Re-derived from the FPKM table.
- C2 Direction of DE (reported 84% up). Re-derived from the FPKM table.
Out of scope (not attempted — 80/20 and data limits)
- C4 Subset-B DE (1,048 transcripts): the subset's sample membership is not specified in the paper or GEO, so the comparison is not pinnable.
- C5 ChIP-seq H3K27ac (1,485 sites): the raw ChIP-seq data is not part of GSE102746 and no separate accession is given; cannot obtain input.
- Re-running TopHat2+Cuffdiff from raw FASTQ (SRP115575) to reproduce 260 exactly: the hard ~20% — intentionally skipped per the 80/20 rule.
Reproduction approach
The listed repo (TrimGalore) is a third-party trimming tool that produces no comparable result value on its own. The clear, low-hanging pipeline-derived result is the DE call. We therefore re-derived differential expression from the authors' own shipped Cufflinks FPKM table using the authors' own stated thresholds (FDR<0.05 & |log2FC|>1.5). This is a method-divergent reproduction on the authors' own data (the paper's count used Cuffdiff on BAM alignments, which the FPKM table cannot reconstruct).
Assessments & scoring basis
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Every item that counted toward this verdict, and the exact part of the reproduction that produced it.
Re-derived DE from the authors' own shipped FPKM table using their stated thresholds. The data structure is exact (35786 genes x 20 samples; 10 UC + 10 normal verified) and the directional asymmetry reproduces robustly (84% up reported vs 82-85%). The headline 260-DE-transcript count does NOT reproduce with a Welch t-test (9 strict / 756 FDR-only) — because the paper used Cuffdiff on BAM alignments, a less-conservative model than a t-test on FPKM. This is a method divergence on our side, not a fabrication signal: 756 genes pass FDR before the FC filter, so a few-hundred count under Cuffdiff is plausible. Reproducing 260 exactly needs TopHat2+Cuffdiff from raw FASTQ (the deliberately-skipped hard 20%). Note the listed code link (TrimGalore) is a harvest false-positive, not the analysis pipeline.
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Reproduction footprint
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