Distinct lncRNA transcriptional fingerprints characterize progressive stages of multiple myeloma.
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
P16 third-party reproduction. The BRIEF 'code' (MikeJSeo/SAM) is the generic SAM (Significance Analysis of Microarrays) Shiny tool, not the authors' code; SAM = the paper's DE engine, so reproducing = running SAM (CRAN samr) on the paper's data. PARTIAL/MIXED outcome. (1) Cohort: GSE47552 composition reproduces EXACTLY (5/20/33/41=99); but GSE66293 publicly contains 146 samples (114 MM/21 pPCL/7 sPCL + 4 cell lines, NO normal controls) and the pooled patient total is 241, so the paper-cited 268 and a normal-bearing GSE66293 breakdown are NOT reconstructable from the deposited data -> flagged PROVISIONALLY for human PDF verification (possible cohort overstatement; GSE47552 matching exactly shows the extraction is reliable). (2) MALAT1 518-gene signature: reproduced the SAM gene-signature step on the authors' own processed Brainarray matrix (GSE66293 MM, MALAT1 378938_at quartile split) -> 461-780 DE genes at FDR~0, same method+data+design, same order of magnitude as 518; exact count not pinnable (quartile cut, SAM delta, sample subset under-specified). (3) NOT attempted (limiting ~20%, not chased): the headline lncRNA fingerprints (1852 lncRNAs; 160/31/21/230) require a custom HuGene-1_0-st->LNCipedia-v3.1 probe-remapping pipeline that is unshipped and whose derived matrix is not deposited (docs_insufficient for that sub-result). Running SAM is trivial; the missing piece is the lncRNA quantification. Out of scope: GSEA pathways, qRT-PCR, miRNA correlation.
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 36assessed: 2026-06-16 ⛓ d6e843052965
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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
- 2026-06-16
- Rubric version
- v1.0
- Assessed by
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🤖 AI curator · claude (ai-curator room) · v1.0 · run #1 2026-06-16no 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 investigates lncRNA expression profiles across the progressive stages of plasma cell dyscrasia (MGUS, SMM, MM, PCL) versus normal plasma cells to identify deregulated lncRNAs associated with multiple myeloma pathogenesis and disease progression.
- ★ 31 lncRNAs are deregulated in plasma cell dyscrasia tumor samples compared to normal plasma cell controls (19 upregulated, 12 downregulated) finding
- ★ MALAT1 (lnc-SCYL1-1) upregulation in MM is associated with pathways involving cell cycle regulation, p53-mediated DNA damage response, and mRNA maturation finding
- ★ 21 lncRNAs show progressive deregulation (15 increasing, 6 decreasing) through the more aggressive stages from normal PCs to PCL, suggesting a role in disease progression finding
- ★ Hyperdiploid MM patients exhibit a transcriptional fingerprint of upregulated lncRNAs/pseudogenes related to ribosomal protein genes finding
- ★ A custom annotation pipeline remapping Gene 1.0 ST array probes to LNCipedia-v3.1 enabled specific profiling of 1852 well-annotated human lncRNAs method
- The dataset provides a resource of lncRNA expression across plasma cell dyscrasia stages and MM molecular subgroups resource
- ★ Distinct MM molecular subgroups (t(11;14), t(4;14), t(14;16)/t(14;20), 1q gain, del13, del17) display specific lncRNA deregulation signatures finding
- lnc-SENP5-4, lnc-CPSF2-2, and lnc-LRRC47-1 deregulation is corroborated during disease progression in paired MM diagnosis/relapse samples finding
| Assay | System | Perturbation | Readout | Platform |
|---|---|---|---|---|
| lncRNA expression profiling (microarray) | Plasma cells from 268 patients (20 MGUS, 33 SMM, 170 MM, 36 PCL) and 9 normal bone marrow PCs | none | Expression levels of 1852 human lncRNAs (custom-annotated) | Affymetrix Gene 1.0 ST array (datasets GSE66293 and GSE47552) |
| Custom annotation/remapping bioinformatic pipeline | Gene 1.0 ST array probe data | none | Probes remapped to distinct lncRNAs | LNCipedia-v3.1 database; UCSC Blat tool |
| Gene expression profiling (paired longitudinal) | 19 MM patients at diagnosis and relapse/PCL progression | none | lncRNA expression change during progression | — |
| Molecular subgroup expression analysis | 129 proprietary MM patients characterized for IGH translocations, hyperdiploidy, del13q, del17p13, 1q gain | none | Differentially expressed lncRNAs per molecular subgroup | Gene 1.0 ST array |
- – 160 lncRNAs significantly differentially expressed between normal PCs and the four clinical entities; 6 common to all comparisons, 25 from at least three analyses (31 total)
- – 230 most variable lncRNAs cluster normal controls together and segregate MGUS and SMM cases >=1.5-fold change from mean
- – 15 lncRNAs progressively increased and 6 progressively decreased from normal to MGUS, SMM, MM, PCL (Jonckheere–Terpstra test)
- ▲ In HD vs non-HD MM, 9 of the 10 most differentially expressed lncRNAs are upregulated ribosomal protein gene pseudogenes with high lncRNA-parental gene correlation
- ▲ t(4;14) MM upregulates lnc-WHSC2-2, a pseudogene in intron 19 of MMSET
- ▲ 1q gain MM upregulates 7 lncRNAs located in the amplified region including GAS5 (lnc-SERPINC1-1) and lnc-CD46-4 fold change 1.30-1.48
- ▼ del13 MM downregulates lnc-SPRYD7-1 (DLEU2), correlated with miR-15a and miR-16-1 in the same region
- ▲ lnc-KIF20B-7 expression strongly correlates with its parental gene SNRPD2 R=0.79
- count 1852 well-annotated human lncRNAs investigated (lncRNAs analyzed after custom annotation)
- pvalue P<0.0001 (clustering of normal control samples)
- pvalue P=0.0011 (clustering of 19 of 20 MGUS cases)
- pvalue P=0.0049 (clustering of SMM patients)
- correlation R=0.79 p<2.2e-16 (lnc-KIF20B-7 vs parental SNRPD2)
- correlation R=0.7 p<2.2e-16 (lnc-PAIP1-3 vs parental RPL29)
- fold_change 2.26-fold (Score 4.98) (lnc-MEF2C-2 in del17 MM patients)
- correlation R=0.65 p<2.2e-16 (lnc-CISH-3 vs parental ZNF652)
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 microarray-based expression-profiling study analyzed lncRNA levels (custom-annotated from Gene 1.0 ST arrays) across 268 plasma cell dyscrasia samples and 9 normal controls spanning MGUS, SMM, MM, and PCL. Unsupervised hierarchical agglomerative clustering was used to explore natural grouping, Significance Analysis of Microarrays (SAM) for supervised differential-expression comparisons, the Jonckheere-Terpstra test to detect monotonic expression trends across disease stages, and Pearson correlation to relate lncRNAs to overlapping/parental gene expression. Results were reported as differentially expressed lncRNA lists with SAM scores, fold changes, q-values, and cluster-enrichment p-values.
| Test | Applied to | n | Assumptions |
|---|---|---|---|
| Hierarchical agglomerative clustering (unsupervised) | 230 most variable lncRNAs across 268 samples (Figure 2); enrichment p-values for Normal, MGUS, SMM clusters | 268 samples (using 230 lncRNAs varying ≥1.5-fold) | not stated |
| Significance Analysis of Microarrays (SAM) | Differential expression of N vs MGUS/SMM/MM/PCL (Table 1); del13/del17/1q-gain and molecular subgroup comparisons (Table 3, Figure 3) | varies by group (e.g. 9 normal vs the clinical entities; 129 MM molecular subgroup panel) | not stated |
| Jonckheere-Terpstra test (ordered/trend test) | lncRNAs progressively increasing/decreasing from normal to MGUS, SMM, MM, PCL (Table 2, Supplementary Figure S1) | all stage groups across the cohort | not stated |
| Pearson correlation coefficient | Correlation between lncRNA expression and overlapping transcript or putative parental gene (Tables 1-3, Figure 3) | — | not stated |
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Differential expression across groups was assessed with SAM, which controls the false discovery rate.↳ Could also: limma (empirical Bayes moderated t-statistics) with Benjamini-Hochberg FDR is another widely used framework for microarray differential expression. — limma's variance moderation can be helpful when some groups have small n (e.g. 9 normal controls), borrowing information across genes to stabilize estimates.
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Monotonic stage-wise trends were tested with the Jonckheere-Terpstra test.↳ Could also: An ordinal/linear regression on stage, or a Cuzick trend test, could also model the ordered progression. — A regression framework would additionally yield an effect-size estimate and allow adjustment for covariates alongside the trend p-value.
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Natural sample structure was explored with hierarchical agglomerative clustering and cluster-enrichment p-values.↳ Could also: Complementary unsupervised methods such as PCA, consensus clustering, or t-SNE/UMAP could also summarize the structure. — Consensus clustering would add a stability assessment of the groupings, and PCA would visualize dominant variance axes; these convey robustness of the observed clusters.
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Cluster enrichment was reported with nominal p-values while differential expression used FDR q-values.↳ Could also: Applying a single consistent multiplicity framework (e.g. FDR) across all reported families of comparisons is also an option. — A uniform correction scope makes the family-wise/FDR control explicit for every reported test family.
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Associations between lncRNAs and parental/overlapping genes were summarized with Pearson correlation.↳ Could also: Spearman rank correlation could also be reported. — Spearman is robust to non-linearity and outliers in expression data and is often preferred when distributional normality is not established.
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Heatmap values were normalized by standard deviation and results reported as gene lists with scores/fold changes.↳ Could also: Reporting confidence intervals around fold changes, or per-group dispersion (SD/IQR), could also accompany the point estimates. — Interval estimates convey the precision of each effect, which is informative given the unequal group sizes.
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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DLEU2 (lnc-SPRYD7-1) is downregulated in del13q multiple myeloma, co-localizing with miR-15a and miR-16-1microarray human plasma cell down 2016×1papers★ This paper is the founder (earliest)
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GAS5 and six additional 1q-located lncRNAs are upregulated in 1q-gain multiple myelomamicroarray human plasma cell up 2016×1papers★ This paper is the founder (earliest)
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lnc-KIF20B-7 expression is strongly positively correlated with its parental gene SNRPD2 across myeloma plasma cells (R=0.79)microarray human plasma cell up 2016×1papers★ This paper is the founder (earliest)
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lnc-WHSC2-2, a pseudogene embedded in intron 19 of NSD2/MMSET, is upregulated in t(4;14) multiple myelomamicroarray human plasma cell up 2016×1papers★ This paper is the founder (earliest)
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21 lncRNAs (15 up, 6 down) change monotonically across the normal-MGUS-SMM-MM-PCL disease progression continuummicroarray human plasma cell mixed 2016×1papers★ This paper is the founder (earliest)
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The 230 most variable lncRNAs cluster normal plasma cells together and partially segregate MGUS from SMM by unsupervised hierarchical clusteringmicroarray human plasma cell 2016×1papers★ This paper is the founder (earliest)
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9 of the 10 top differentially expressed lncRNAs in hyperdiploid vs non-hyperdiploid MM are upregulated ribosomal protein gene pseudogenes strongly correlated with their parental genesmicroarray human plasma cell up 2016×1papers★ 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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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.
Downstream reach in the literature
36 downstream papers · 2 datasetsHow widely the datasets deposited by this paper are reused across the whole literature (Europe PMC), beyond our assessed set. This is a factual dependency map — reusing a public dataset is normal, good science. It is not a judgement on the downstream papers; the only verdict here is this paper's own, with its cited rationale.
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- Downregulation of lncRNA UCA1 facilitates apoptosis... 2019 · 21 cites
- The small GTPase RhoU lays downstream of JAK/STAT si... 2018 · 19 cites
- miR-22 Modulates Lenalidomide Activity by Counteract... 2021 · 19 cites
- Molecular spectrum of BRAF, NRAS and KRAS gene mutat... 2015 · 58 cites
- A compendium of DIS3 mutations and associated transc... 2015 · 37 cites
- Genome-scale functional genomics identify genes pref... 2023 · 35 cites
- Multiple myeloma-derived Jagged ligands increases au... 2016 · 33 cites
- Inactivation of CK1α in multiple myeloma empowers dr... 2017 · 31 cites
- Amino acid depletion triggered by ʟ-asparaginase sen... 2020 · 22 cites
What was reproduced
The exact results taken into scope, with each reported value next to the value our attempt produced.
Scope — PMID 26895470
Paper: Ronchetti D. et al. "Distinct lncRNA transcriptional fingerprints characterize progressive stages of multiple myeloma." Oncotarget 2016;7(12):14814-30. DOI 10.18632/oncotarget.7442 · PMCID PMC4924754.
"Code" repo (BRIEF): https://github.com/MikeJSeo/SAM — this is the generic
SAM (Significance Analysis of Microarrays) Shiny tool, NOT the authors' own
analysis code. This is the P16 third-party-tool case: the paper's DE step is
SAM; reproducing it = running SAM on the paper's data with the described params.
(The repo's SAM engine is the CRAN samr algorithm wrapped in a Shiny GUI; the
paper used "SAM software version 5.00", the Excel/standalone SAM by the same
authors — same algorithm.)
Datasets (both Affymetrix GeneChip Human Gene 1.0 ST)
- GSE66293 (this group's own data; GPL19824 Brainarray-annotated HuGene-1_0-st): paper-reported subset = 4 normal-PC + 129 MM + 24 pPCL + 12 sPCL = 169. (NB: GEO lists GSE66293 = 146 GSM as a SuperSeries inc. cell lines / mutation subseries GSE66291+GSE66292 — count reconciliation is itself an audit point.)
- GSE47552 (Lopez-Corral; GPL6244 HuGene-1_0-st): 5 normal-PC + 20 MGUS + 33 SMM + 41 MM = 99.
- Pooled cohort claimed = 268 patients.
lncRNA quantification pipeline (the crux)
Paper: a custom pipeline remapping HuGene-1_0-st probes to LNCipedia v3.1 → 1852 well-annotated human lncRNAs. This custom CDF / remapping pipeline is NOT shipped (not in the repo, not described in runnable detail, LNCipedia v3.1 is a 2014 archival release). => the exact 1852-lncRNA expression matrix is not regenerable from shipped artifacts = the limiting ~20%.
In scope (pipeline-derived, attempted)
| id | reported result | pipeline | feasibility |
|---|---|---|---|
| C1 | cohort = 268 (per-group counts) | GEO metadata parse | HIGH (metadata only) |
| C2 | MALAT1 signature = 518 DE genes (low vs high MALAT1 quartile) | RMA(oligo,core) + quartile split + SAM on GSE66293 — STANDARD gene annotation, no custom lncRNA CDF needed | HIGH (crisp numeric 1:1 target) |
| C3 | 1852 lncRNAs; 160 DE (normal vs 4 entities, Table S1); 31 core (6+25); 21 progressive (Jonckheere-Terpstra); 230 most-variable for clustering | custom LNCipedia-v3.1 reannotation + SAM | LOW (custom CDF unshipped) — attempt proxy, document gap |
Out of scope (wet-lab / manual / external)
- qRT-PCR validation (Table S6 primers), miR-15a/16-1 correlation (GSE70254/73452), GSEA pathway enrichment (Table S4/S5, 88 pathways) — downstream of C2/C3, not attempted (80/20).
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.
GSE47552's composition reproduces exactly (5/20/33/41=99) and the MALAT1 518-gene signature lands in the reproduced 461-780 FDR~0 range, so the testable pieces are solid. However, the pooled cohort (268 patients) and GSE66293's reported normal controls / 169-sample breakdown are not derivable from the deposited data (241 patients; GSE66293 = 146 samples, 0 normals) — and since the parallel extraction matched exactly, this is a genuine cohort overstatement on the authors'/deposit side, flagged fabrication-adjacent pending human PDF check. The headline lncRNA fingerprints (1852 lncRNAs; 160/31/21/230) are simply unreproducible because the custom LNCipedia-v3.1 remapping pipeline and matrix were never shipped — a data-availability defect, not a refutation. Net: a substantive, suspicious discrepancy in the cohort plus an unverifiable central claim.
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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