Molecular and Clinical Relevance of ZBTB38 Expression Levels in Prostate Cancer.
Provisional — an automated or curator check raised a specific concern and points reviewers here. This is NOT a final assessment and not a determination about the authors.
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.
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- 🟡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 reproduce the named Taylor/GSE21032 cohort (== cBioPortal prad_mskcc); all compute on «our HPC» (R 4.3.3 conda env on «infra», GEOquery GSE21034 probe 4299 + cBioPortal mRNA/clinical/CNA). The brief's 'Code: RSEM' is a text-mining artefact — authors did not run RSEM; the real pipeline is chi-square/C-index/Cox stats on public tables, which we re-ran. RESULT IS MIXED (hence 'partial'): Table 1 differential expression reproduced 1:1 (FC -1.05 vs -1.07, p in same tier, sample N 29/131/19 matches exactly) and clinical T-stage is concordantly non-significant — BUT three headline claims did NOT reproduce: pathological grade (paper p=0.019 'significant' vs ours p=0.43 n.s.), copy-number/genomic-instability cluster (paper p=0.028 vs ours p=0.757), and the ZBTB38 C-index for recurrence (paper 0.76 vs ours 0.52). Strongest auditable flag, independent of our data: the paper's own Table-2 pathological-grade row is INTERNALLY INCONSISTENT — recomputing Pearson chi2 from its printed 2x2 cells [[38,46],[26,19]] yields chi2=1.84/p=0.175, not the reported 5.45/p=0.019, while the other 9/10 rows reproduce to 3 decimals (see reproduction/check_table2_internal_consistency.py). Paper's C-indices are also implausibly high (Gleason 0.93 in TCGA). NOT ATTEMPTED (80/20): other cohorts (TCGA/Ross-Adams/Kunderfranco/Grasso), Table 2 Age/PSA/SVI/LNI/SMS/ECE (absent from cBioPortal prad_mskcc & GEO GSE21034 metadata; only in Taylor's print supplement), multivariate Cox HR, Kaplan-Meier, the 216-/5-gene DEG signature, qPCR/doxorubicin wet-lab, and RSEM on raw TCGA RNA-seq (controlled-access, not run by authors). All grades are provisional for human audit (AUDIT.md).
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 35assessed: 2026-06-15 ⛓ 4393744c8e86
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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
- 2026-06-15
- 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 study tests the clinical significance of ZBTB38 expression in prostate cancer, hypothesizing that ZBTB38 mRNA levels are associated with tumour aggressiveness, genomic instability, prognosis, and differential drug sensitivity in localised prostate cancer.
- ★ ZBTB38 expression is decreased in localised prostate cancer and further decreased in metastatic prostate cancer compared to non-cancerous prostate tissue finding
- ★ Low ZBTB38 expression is an independent prognostic marker associated with poor disease-free survival (biochemical recurrence) in localised prostate cancer finding
- ★ Low ZBTB38 expression associates with increased genomic/chromosomal instability (copy number aberrations) in localised but not metastatic tumours finding
- ★ Low ZBTB38 expression correlates with SPOP mutation, CHD1/SPOPL/RB1 deletions, and the SPOP-mutant molecular subgroup (integrative Cluster 1, methylation cluster 2, mRNA cluster 1) finding
- ★ Tumours with low ZBTB38 expression display a gene signature suggesting increased sensitivity to the ROS-generating drug doxorubicin finding
- ★ Depletion of ZBTB38 in prostate cancer cell lines causes heightened ROS levels and higher sensitivity to doxorubicin treatment mechanism
- ★ ZBTB38 mRNA level can help discriminate aggressive localised prostate tumours from indolent ones and identify high-risk, highly rearranged tumours susceptible to doxorubicin resource
- Low ZBTB38 expression correlates with higher PSA levels, higher pathological grade, and higher Gleason score across independent cohorts finding
| Assay | System | Perturbation | Readout | Platform |
|---|---|---|---|---|
| Gene expression microarray analysis (differential ZBTB38 expression) | Human prostate tissue (benign/normal, localised and metastatic prostate cancer) — nine published cohorts | none | ZBTB38 mRNA expression levels | — |
| RNA-sequencing expression analysis | Human prostate tissue — TCGA cohort (52 normal, 498 localised prostate cancer) | none | ZBTB38 mRNA expression levels | TCGA RNA-sequencing |
| Clinico-pathological correlation analysis (ZBTB38-low vs ZBTB38-high by median) | Human localised prostate cancer cohorts (Taylor GSE21032, Kunderfranco GSE14206, Ross-Adams GSE70770, TCGA) | none | Association of ZBTB38 expression with PSA, Gleason score, pathological grade, margin status, age | — |
| Survival analysis (Kaplan-Meier, C-index, multivariate Cox regression) | Human localised prostate cancer cohorts (Taylor, TCGA, Ross-Adams; including ethnicity stratification) | none | Disease-free survival / biochemical recurrence | — |
| Genomic instability / copy number and mutation correlation analysis | Human localised prostate cancer (Taylor GSE21034, TCGA) and metastatic cohorts | none | Copy number aberrations, fraction genome altered, mutational burden, SPOP/CHD1/RB1/PTEN/TP53 alterations, ETS fusions, molecular clusters | — |
| Whole-genome differential gene expression profiling (1st vs 4th quartile ZBTB38) | Human localised prostate cancer — four cohorts (Taylor, Kunderfranco, Ross-Adams, and one other) | none | Differentially expressed genes (p<0.001) and predicted drug sensitivity signature | — |
| Cellular assays (ROS measurement and drug sensitivity) | Prostate cancer cell lines | ZBTB38 knock-down/depletion; doxorubicin treatment | ROS levels and doxorubicin sensitivity | — |
- ▼ ZBTB38 expression significantly lower in localised prostate cancer in 8 of 9 microarray cohorts and in TCGA RNA-seq cohort
- ▼ Low ZBTB38 expression associated with shorter disease-free survival; significant in Taylor and TCGA cohorts and intermediate-risk (Gleason 7) TCGA
- – ZBTB38 expression is an independent predictor of disease-free survival; C-index 0.76 (Taylor), 0.791 (TCGA), 0.716 (Ross-Adams) C-index 0.76 / 0.791 / 0.716
- ▲ Low ZBTB38 expression correlates with high copy number aberration in Taylor and with somatic copy-number aberration and fraction genome altered in TCGA, but not mutational burden
- – Low ZBTB38 expression correlates with SPOP point mutation and CHD1/SPOPL/RB1 deletions, FANCC gain, and SPOP-mutant molecular clusters
- ▼ Low ZBTB38 correlates with shorter disease-free survival specifically in Gleason 4+3 tumours but not Gleason 3+4 p<0.001
- – No significant association between ZBTB38 expression and genomic instability in metastatic tumours
- – Five genes (ADAM10, ARMC8, COMMD8, EEA1, PPM1B) differentially expressed between ZBTB38-low and ZBTB38-high tumours across all four cohorts 5 genes in 4 cohorts; 216 genes in ≥3 cohorts
- count 52 normal prostate specimens and 498 localised prostate cancer (TCGA) (TCGA RNA-seq cohort size)
- correlation C-index = 0.791 (Prognostic performance of ZBTB38 expression in TCGA cohort)
- correlation C-index = 0.76 (Prognostic performance in Taylor cohort)
- correlation C-index = 0.716 (Prognostic performance in Ross-Adams cohort)
- pvalue p < 0.00001 (Low ZBTB38 vs somatic copy-number aberration in TCGA)
- pvalue p = 0.0004 (Low ZBTB38 vs fraction of genome altered in TCGA)
- pvalue p = 0.001 (Low ZBTB38 vs SPOP point mutation in TCGA)
- pvalue p < 0.001 (Low ZBTB38 vs shorter disease-free survival in Gleason 4+3 TCGA patients)
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 performed retrospective analysis of multiple publicly available prostate cancer microarray and RNA-seq cohorts (Taylor/GSE21032, Kunderfranco/GSE14206, Ross-Adams/GSE70770, TCGA, and others) to characterize ZBTB38 expression associations with clinico-pathological features, genomic instability, and disease-free survival. Patients within each cohort were dichotomized at the median ZBTB38 expression value into low and high groups, and each cohort was analyzed independently with results compared qualitatively across cohorts. Primary statistical approaches included Kaplan-Meier survival analysis, multivariate Cox regression, C-index computation, and p-value-based association tests for clinico-pathological and genomic features; differentially expressed genes were identified using a p < 0.001 threshold intersected across four independent cohorts.
| Test | Applied to | n | Assumptions |
|---|---|---|---|
| Kaplan-Meier survival analysis (log-rank test implied but not named) | Disease-free survival comparing ZBTB38-low vs. ZBTB38-high in Taylor, TCGA, and Ross-Adams cohorts; also within ethnicity subgroups (white vs. Black/African American) and Gleason score subgroups (score 7; 3+4 vs. 4+3) | TCGA: 498 localised tumours; Taylor: 106 white + 26 Black/African American men stated; Ross-Adams n not stated in excerpted text | not stated |
| Multivariate Cox proportional hazards regression | Disease-free survival versus ZBTB38 mRNA expression, Gleason score, PSA levels, and positive margin status in Taylor and TCGA cohorts (Table 3) | — | not stated |
| C-index (concordance index / Harrell's C) | Prognostic performance of ZBTB38 expression, Gleason score, and PSA at diagnosis in Taylor (C=0.76), TCGA (C=0.791), and Ross-Adams (C=0.716) cohorts (Table 3) | — | na |
| Unspecified differential expression test computed per cohort (microarray-based; TCGA arm uses RNA-seq data) | ZBTB38 expression in cancerous vs. normal/benign prostate tissue across nine microarray cohorts and TCGA RNA-seq cohort (Table 1); also localised vs. metastatic comparisons | TCGA: 498 localised vs. 52 normal; other cohorts: at least 5 per group per stated inclusion criterion | not stated |
| Unspecified association tests (test family not named; likely chi-square or Fisher's exact for categorical variables, Mann-Whitney U or t-test for continuous variables) | Correlation of ZBTB38-low vs. ZBTB38-high with clinico-pathological features (age, PSA levels, Gleason score, pathological grade, seminal vesicle invasion, lymph node involvement, margin status, extra capsular extension) across Taylor, Kunderfranco, Ross-Adams, and TCGA cohorts (Table 2) | — | not stated |
| Unspecified differential expression test with p < 0.001 threshold, intersected across cohorts | Gene expression profiling comparing 1st quartile (ZBTB38-low) vs. 4th quartile (ZBTB38-high) localised tumours in four independent cohorts (Taylor, Kunderfranco, Ross-Adams, Sboner) to identify 216 co-differentially expressed genes (Figure 4a) | — | not stated |
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Patients were dichotomized at the median ZBTB38 expression value within each cohort to define ZBTB38-low and ZBTB38-high groups for all association and survival analyses↳ Could also: ZBTB38 expression could be retained as a continuous variable in Cox regression and correlation analyses, or a data-driven threshold could be selected using methods such as maxstat or X-tile with appropriate adjustment for the search — Dichotomization at the median discards within-group variation and can reduce statistical power; treating expression as continuous captures the full dose-response relationship between expression level and outcome, and data-driven cutoff methods can identify clinically meaningful breakpoints
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Multiple clinico-pathological associations with ZBTB38 expression were tested via individual p-values across many variables and cohorts without a stated correction for multiple comparisons↳ Could also: A Benjamini-Hochberg false discovery rate correction or Bonferroni adjustment could be applied across the family of tests within each cohort, with the corrected threshold reported — Reporting many uncorrected p-values across multiple variables and cohorts increases the expected number of false positives; a stated correction allows readers to assess which associations survive under an explicit error-rate control
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Survival analyses were conducted and reported separately within each cohort using Kaplan-Meier curves with implied log-rank tests↳ Could also: An individual-patient-data meta-analysis or a stratified Cox model pooling all cohorts (with cohort as a stratification variable) could also have been employed — Pooling across cohorts increases statistical power to detect modest associations and enables a formal test of heterogeneity; separate within-cohort analyses leave the degree of cross-cohort consistency qualitative rather than quantified
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The Cox multivariate model results are described as demonstrating independent prognostic value, but specific hazard ratios and confidence intervals are not reported in the text↳ Could also: Hazard ratios with 95% confidence intervals for each covariate in the multivariate models could be reported in a table — Confidence intervals convey the direction, magnitude, and precision of each association and are standard practice for survival analyses under REMARK reporting guidelines for tumor biomarker studies; point p-values alone do not communicate effect size
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Genome-wide differential expression between ZBTB38-low and ZBTB38-high tumours was assessed using a per-gene p < 0.001 threshold without a stated genome-wide multiple-testing correction↳ Could also: A genome-wide false discovery rate (FDR) correction such as Benjamini-Hochberg, applied within each cohort prior to intersecting results across cohorts, could also have been used — With tens of thousands of probes tested simultaneously, a nominal p < 0.001 threshold still permits many expected false positives; an FDR-controlled threshold makes the anticipated proportion of false discoveries explicit and is a widely adopted standard for microarray analysis
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The specific statistical tests used for clinico-pathological associations (Table 2) and genomic feature associations (Table 4, Tables S1-S5) are not named in the text↳ Could also: Explicitly naming each test used (e.g., Mann-Whitney U for continuous variables, Fisher's exact test for binary categorical variables, Kruskal-Wallis for ordered multi-category variables) and reporting an accompanying effect-size measure (e.g., rank-biserial correlation, odds ratio) would be an alternative reporting practice — Named tests and effect-size estimates allow readers to judge whether test assumptions were appropriate for each variable type and to gauge the magnitude of each association independently of sample size
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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Five genes (ADAM10, ARMC8, COMMD8, EEA1, PPM1B) are consistently differentially expressed between ZBTB38-low and ZBTB38-high prostate cancer tumors across four independent cohorts.microarray human prostate cancer mixed 2020×1papers★ This paper is the founder (earliest)
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ZBTB38 mRNA expression is significantly reduced in localized prostate cancer versus benign/normal prostate tissue across 8 of 9 microarray cohorts and the TCGA RNA-seq cohort.microarray human prostate tissue down 2020×1papers★ This paper is the founder (earliest)
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ZBTB38 expression does not associate with genomic instability in metastatic prostate cancer.other human metastatic prostate cancer none 2020×1papers★ This paper is the founder (earliest)
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Low ZBTB38 expression predicts shorter disease-free survival specifically in Gleason 4+3 but not Gleason 3+4 localized prostate cancer.other human prostate cancer down 2020×1papers★ This paper is the founder (earliest)
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Somatic copy number aberrations and fraction genome altered are elevated in ZBTB38-low localized prostate cancer tumors.other human prostate cancer up 2020×1papers★ This paper is the founder (earliest)
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SPOP point mutations and CHD1/RB1 deletions are enriched in ZBTB38-low prostate cancer, aligning with SPOP-mutant molecular cluster membership.other human prostate cancer up 2020×1papers★ This paper is the founder (earliest)
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Low ZBTB38 expression associates with shorter disease-free survival in localized prostate cancer.other human prostate cancer down 2020×1papers★ This paper is the founder (earliest)
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ZBTB38 expression is an independent predictor of disease-free survival in localized prostate cancer (C-index 0.716–0.791 across three cohorts).other human prostate cancer 2020×1papers★ This paper is the founder (earliest)
Citation network
Where this publication sits in the reproducibility-weighted citation graph — what it is built on, and what is built on it. Citation data from OpenAlex.
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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-32365491
Paper: de Dieuleveult M, Marchal C, Jouinot A, Letessier A, Miotto B. Molecular and Clinical Relevance of ZBTB38 Expression Levels in Prostate Cancer. Cancers (Basel) 2020;12(5):1106. PMID 32365491 · PMCID PMC7281456 · DOI 10.3390/cancers12051106.
What kind of paper is this?
A secondary / re-analysis study. The authors did NOT generate the high-throughput data; they mined public microarray (GEO, Oncomine) and RNA-seq (TCGA via cBioPortal) prostate-cancer cohorts and asked whether ZBTB38 mRNA expression correlates with clinico-pathological features, disease-free survival (DFS) and genomic instability. Plus a small wet-lab arm (qPCR, doxorubicin cell assays) that is out of scope (not pipeline-derived).
The brief's "Code: github.com/deweylab/RSEM" is a text-mining artdefact
RSEM appears in the Methods only as the tool by which TCGA/cBioPortal had already quantified RNA-seq expression ("expression … quantified using the RSEM package"). The authors did not run RSEM. Re-running RSEM would require raw TCGA RNA-seq FASTQs (controlled-access, dbGaP) — out of scope and not what the paper did. The paper's actual computational pipeline is statistics on public expression+clinical tables: median-split of ZBTB38 → chi-square (Tables 2, 4), Harrell C-index + Cox regression (Table 3), Kaplan-Meier (Fig 3), differential expression / GEO2R + g:Profiler overlap (Fig 4), fold-change t-tests (Table 1).
Named dataset = GSE21032 = Taylor et al. 2010 (MSKCC) → our reproduction target
GSE21032 is the SuperSeries of Taylor 2010 (Cancer Cell). Its mRNA component is GSE21034 (Affymetrix Human Exon 1.0 ST; ZBTB38 = probe 4299 per the paper). The same cohort is in cBioPortal as study prad_mskcc with structured clinical + mRNA + copy-number-cluster data. This is the most clearly-specified, fully-public, low-hanging target.
In scope (attempted) — Taylor/GSE21032 only
| Result | Where | Pipeline | Reproducible from public data? |
|---|---|---|---|
| Table 1: ZBTB38 benign-vs-primary fold change + p | Table 1, GSE21032 row | fold change + test on probe 4299 | YES (GEO GSE21034) |
| Table 2: ZBTB38(median split) × clinico-path features, chi² | Table 2, Taylor col | median split + Pearson chi² | PARTIAL (Gleason, path-T, clin-T in cBioPortal; Age/PSA/SVI/LNI/SMS/ECE only in Taylor supp) |
| Table 4: ZBTB38 × copy-number-aberration cluster, chi² | Table 4, Taylor col | median split + chi² | YES (cBioPortal COPY_NUMBER_CLUSTER) |
| Table 3: ZBTB38 C-index for DFS | Table 3, Taylor col | Harrell C-index / Cox | YES (cBioPortal DFS) |
Out of scope / not attempted (the hard ~20%, stated honestly)
- Other cohorts (TCGA, Ross-Adams/GSE70770, Kunderfranco/GSE14206, Grasso/GSE35988, and Table 1's GSE3325/GSE3933/GSE55945/GSE68545/Oncomine) — each is a separate dataset fetch + harmonisation; one cohort (Taylor) is a sufficient clear 1:1 datapoint per the brief.
- Table 2 features Age, PSA(diag/pre-tx), SVI, LNI, surgical margins, ECE — these clinical fields are NOT in cBioPortal prad_mskcc nor in the GSE21034 GEO sample metadata; they live only in Taylor's 2010 Cancer Cell supplementary table. Requires manual supp parsing.
- Table 3 multivariate Cox HRs, Fig 3 Kaplan-Meier, Fig 4 216-/5-gene DEG signature (GEO2R + g:Profiler), Fig S1, qPCR / doxorubicin assays.
- RSEM on raw TCGA RNA-seq — controlled-access data; not what the authors ran.
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.
Table 1 differential expression reproduces essentially 1:1 (FC -1.05 vs -1.07, p in same tier, N=29/131 exact) and clinical T-stage is concordantly non-significant, but three headline claims fail: pathological grade (p=0.019→0.43), CNA/genomic-instability cluster (p=0.028→0.757), and the ZBTB38 recurrence C-index (0.76→0.517). The strongest, data-independent flag is on the authors' side: the paper's reported pathological-grade chi2=5.45/p=0.019 is internally inconsistent with its own printed cells (which give p=0.175), while 9/10 sibling rows self-reproduce — a possible-fabrication signal on a headline 'aggressive features' claim. Combined with implausibly high reported C-indices (0.93), the central conclusion does not hold under reproduction; overall red.
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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