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pmid:24361865

Proteome screening of pleural effusions identifies galectin 1 as a diagnostic biomarker and highlights several prognostic biomarkers for malignant mesothelioma.

Filip Mundt · Henrik J Johansson · Jenny Forshed · Sertaç Arslan · Muzaffer Metintas · Katalin Dobra · Janne Lehtiö · Anders Hjerpe

Molecular & cellular proteomics : MCP · 2014 doi:10.1074/mcp.M113.030775

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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pmid:24361865
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title
Proteome screening of pleural effusions identifies galectin 1 as a diagnostic biomarker and highlights several prognostic biomarkers for malignant mesothelioma.
doi
10.1074/mcp.M113.030775
pmid
24361865
authors array · 8 items
[0]
Filip Mundt
[1]
Henrik J Johansson
[2]
Jenny Forshed
[3]
Sertaç Arslan
[4]
Muzaffer Metintas
[5]
Katalin Dobra
[6]
Janne Lehtiö
[7]
Anders Hjerpe
journal
Molecular & cellular proteomics : MCP
year
2014
abstract
Malignant mesothelioma is an aggressive asbestos-induced cancer, and affected patients have a median survival of approximately one year after diagnosis. It is often difficult to reach a conclusive diagnosis, and ancillary measurements of soluble biomarkers could increase diagnostic accuracy. Unfortunately, few soluble mesothelioma biomarkers are suitable for clinical application. Here we screened the effusion proteomes of mesothelioma and lung adenocarcinoma patients to identify novel soluble mesothelioma biomarkers. We performed quantitative mass-spectrometry-based proteomics using isobaric tags for quantification and used narrow-range immobilized pH gradient/high-resolution isoelectric focusing (pH 4-4.25) prior to analysis by means of nano liquid chromatography coupled to MS/MS. More than 1,300 proteins were identified in pleural effusions from patients with malignant mesothelioma (n = 6), lung adenocarcinoma (n = 6), or benign mesotheliosis (n = 7). Data are available via ProteomeXchange with identifier PXD000531. The identified proteins included a set of known mesothelioma markers and proteins that regulate hallmarks of cancer such as invasion, angiogenesis, and immune evasion, plus several new candidate proteins. Seven candidates (aldo-keto reductase 1B10, apolipoprotein C-I, galectin 1, myosin-VIIb, superoxide dismutase 2, tenascin C, and thrombospondin 1) were validated by enzyme-linked immunosorbent assays in a larger group of patients with mesothelioma (n = 37) or metastatic carcinomas (n = 25) and in effusions from patients with benign, reactive conditions (n = 16). Galectin 1 was identified as overexpressed in effusions from lung adenocarcinoma relative to mesothelioma and was validated as an excellent predictor for metastatic carcinomas against malignant mesothelioma. Galectin 1, aldo-keto reductase 1B10, and apolipoprotein C-I were all identified as potential prognostic biomarkers for malignant mesothelioma. This analysis of the effusion proteome furthers our understanding of malignant mesothelioma, identified galectin 1 as a potential diagnostic biomarker, and highlighted several possible prognostic biomarkers of this disease.
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The three sample groups (mesothelioma, metastatic carcinomas, and benign conditions) were compared using the nonparametric Kruskal–Wallis test, with comparisons between groups performed using Dunn's post hoc test to obtain multiplicity-adjusted p values.
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sections[26] "Comparison of Groups Using One-way ANOVA" paragraph 2
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The three sample groups (mesothelioma, metastatic carcinomas, and benign conditions) were compared using the nonparametric Kruskal–Wallis test, with comparisons between groups performed using Dunn's post hoc test to obtain multiplicity-adjusted p values.
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The raw data associated with this manuscript have been deposited in the ProteomeXchange Consortium via the PRIDE partner repository (36) with the dataset identifier PXD000531.
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sections[18] "Peptide and Protein Identification" paragraph 2
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The raw data associated with this manuscript have been deposited in the ProteomeXchange Consortium via the PRIDE partner repository (36) with the dataset identifier PXD000531.
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Cutoff Finder–selected, Kaplan–Meier survival analysis with log-rank testing found significant prognostic trends for aldo-keto reductase 1B10, apolipoprotein C-I, and galectin 1 in malignant mesothelioma (hazard ratios 3.4, 2.30, and 2.34, respectively), while the proteomics source data were deposited through ProteomeXchange under identifier PXD000531.
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For aldo-keto reductase 1B10, there was a survival difference of 5.5 months for patients below and above 0.65 ng/ml (11- and 5.5-month median survival, respectively; p value = 0.01), and the corresponding Mantel–Cox hazard ratio was 3.4 between the two groups (95% confidence interval = 1.33–8.63).
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sections[28] "Survival Analysis" paragraph 2
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The Web-based threshold selection tool Cutoff Finder was used to condition a threshold for each biomarker based on its most significant hazard ratio (42).
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sections[28] "Survival Analysis" paragraph 2
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The Kaplan–Meier estimator was used to evaluate possible prognostic information.
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sections[28] "Survival Analysis" paragraph 2
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The log-rank (Mantel–Cox) test was performed to compare survival curves and to estimate hazard ratios.
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sections[40] "Survival Analyses" paragraph 2
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Aldo-keto reductase 1B10, apolipoprotein C-I, and galectin 1 showed significant prognostic trends (Fig. 6).
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sections[40] "Survival Analyses" paragraph 2
quote
For aldo-keto reductase 1B10, there was a survival difference of 5.5 months for patients below and above 0.65 ng/ml (11- and 5.5-month median survival, respectively; p value = 0.01), and the corresponding Mantel–Cox hazard ratio was 3.4 between the two groups (95% confidence interval = 1.33–8.63).
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sections[40] "Survival Analyses" paragraph 2
quote
Patients with high apolipoprotein C-I levels (>5.33 μg/ml) also had a mean survival time that was 5.5 months longer (10 months compared with low expressing patients' survival of 4.5 months; p value = 0.02) with a reciprocal hazard ratio of 2.30 (1.4–9.0).
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sections[40] "Survival Analyses" paragraph 2
quote
At a cutoff of 22.5 ng/ml, galectin 1 separated high- and low-expressing patients with median survival times of 4.5 and 9.5 months, respectively (p value = 0.04), with a hazard ratio of 2.34 (1.02–5.41).
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Data are available via ProteomeXchange with identifier PXD000531.
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Cutoff Finder–selected, Kaplan–Meier survival analysis with log-rank testing found significant prognostic trends for aldo-keto reductase 1B10, apolipoprotein C-I, and galectin 1 in malignant mesothelioma (hazard ratios 3.4, 2.30, and 2.34, respectively), while the proteomics source data were deposited through ProteomeXchange under identifier PXD000531.
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Q3SY84
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Keratin, type II cytoskeletal 71
[3]
−1.5
[4]
65.1
[17] array · 5 items
[0]
ZNF704
[1]
Q6ZNC4
[2]
Zinc finger protein 704
[3]
−1.5
[4]
65.1
[18] array · 5 items
[0]
C8G
[1]
P07360
[2]
Complement component C8 γ chain
[3]
−1.5
[4]
64.1
[19] array · 5 items
[0]
ZNF670
[1]
Q9BS34
[2]
Zinc finger protein 670
[3]
−1.5
[4]
67.6
[20] array · 5 items
[0]
C9
[1]
P02748
[2]
Complement component C9
[3]
−1.6
[4]
64.1
[21] array · 5 items
[0]
C1S
[1]
P09871
[2]
Complement component 1, s subcomponent
[3]
−1.6
[4]
64.1
[22] array · 5 items
[0]
COL3A1
[1]
P02461
[2]
Collagen α-1(III) chain
[3]
−1.6
[4]
65.1
[23] array · 5 items
[0]
GOLM1
[1]
Q8NBJ4
[2]
Golgi membrane protein 1
[3]
−1.7
[4]
64.1
[24] array · 5 items
[0]
C16orf71
[1]
Q8IYS4
[2]
Uncharacterized protein C16orf71
[3]
−1.7
[4]
65.1
[25] array · 5 items
[0]
SDC1
[1]
P18827
[2]
Syndecan-1
[3]
−1.8
[4]
64.1
[26] array · 5 items
[0]
NRP1
[1]
O14786
[2]
Neuropilin 1
[3]
−1.8
[4]
64.1
[27] array · 5 items
[0]
HRG
[1]
P04196
[2]
Histidine-rich glycoprotein
[3]
−1.8
[4]
64.1
[28] array · 5 items
[0]
F12
[1]
P00748
[2]
Coagulation factor XII
[3]
−1.9
[4]
64.1
[29] array · 5 items
[0]
LRRC28
[1]
Q86X40
[2]
Leucine-rich repeat-containing protein 28
[3]
−2.0
[4]
64.1
[30] array · 5 items
[0]
SERPINA4
[1]
P29622
[2]
Kallistatin (KAL)
[3]
−2.0
[4]
64.1
[31] array · 5 items
[0]
LRG1
[1]
P02750
[2]
Leucine-rich α-2-glycoprotein
[3]
−2.1
[4]
64.1
[32] array · 5 items
[0]
MMRN2
[1]
Q9H8L6
[2]
Multimerin 2
[3]
−2.3
[4]
64.1
[33] array · 5 items
[0]
POU4F3
[1]
Q15319
[2]
POU domain, class 4, transcription factor 3
[3]
−2.3
[4]
64.1
[34] array · 5 items
[0]
LAMA4
[1]
Q16363
[2]
Laminin, α 4
[3]
−2.5
[4]
64.1
[35] array · 5 items
[0]
FBF1
[1]
Q8TES7
[2]
Fas binding factor 1
[3]
−2.5
[4]
64.1
[36] array · 5 items
[0]
FXYD3
[1]
Q14802
[2]
FXYD domain-containing ion transport regulator 3
[3]
−2.6
[4]
64.1
[37] array · 5 items
[0]
C4BPA
[1]
P04003
[2]
C4b-binding protein α chain
[3]
−3.0
[4]
64.1
locator
section[36]/table-wrap[1]#TIII
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asset:table:pmid:24361865:5
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jats-table
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List of the proteins identified and quantified in the significant analysis of microarrays
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pmcid
PMC3945903
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37
section_title
Univariate Analysis
row_count
22
column_count
3
table object · 8 fields
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Table IV
caption
List of the proteins identified and quantified in the significant analysis of microarrays
rows array · 22 items
[0] array · 3 items
[0]
Protein name
[1]
FC
[2]
q-value
[1] array · 3 items
[0]
Myosin-VIIb
[1]
4.5
[2]
0
[2] array · 3 items
[0]
Superoxide dismutase 2a
[1]
4.1
[2]
0
[3] array · 3 items
[0]
Keratin, type II cytoskeletal 8
[1]
3.1
[2]
0
[4] array · 3 items
[0]
Thrombospondin 1
[1]
2.7
[2]
0
[5] array · 3 items
[0]
AF4/FMR2 family, member 3
[1]
2.9
[2]
20.2
[6] array · 3 items
[0]
Apolipoprotein C-Ia
[1]
2.5
[2]
20.2
[7] array · 3 items
[0]
Fructose-bisphosphate aldolase A
[1]
2.4
[2]
20.2
[8] array · 3 items
[0]
Tenascin C
[1]
2.3
[2]
20.2
[9] array · 3 items
[0]
Collagen α-1(VI) chain
[1]
2.1
[2]
20.2
[10] array · 3 items
[0]
Conserved oligomeric Golgi complex subunit 3
[1]
2.7
[2]
34.6
[11] array · 3 items
[0]
Keratin 81
[1]
2.6
[2]
34.6
[12] array · 3 items
[0]
Versican core protein
[1]
2.6
[2]
34.6
[13] array · 3 items
[0]
Negative elongation factor B
[1]
2.6
[2]
34.6
[14] array · 3 items
[0]
Aldo-keto reductase family 1 member B10
[1]
2.4
[2]
34.6
[15] array · 3 items
[0]
Osteopontina
[1]
2.3
[2]
34.6
[16] array · 3 items
[0]
ATP synthase subunit α
[1]
2.3
[2]
34.6
[17] array · 3 items
[0]
Splicing factor, arginine/serine-rich 3
[1]
2.2
[2]
34.6
[18] array · 3 items
[0]
Lamin B1
[1]
2.0
[2]
34.6
[19] array · 3 items
[0]
Niemann-Pick disease, type C2
[1]
1.9
[2]
34.6
[20] array · 3 items
[0]
Coiled-coil domain containing 91
[1]
1.9
[2]
34.6
[21] array · 3 items
[0]
Actin, α cardiac muscle 1
[1]
1.6
[2]
34.6
locator
section[37]/table-wrap[1]#TIV
[7] object · 16 fields
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asset:table:pmid:24361865:6
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jats-table
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application/vnd.jats.table+json
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sha256:f5c7f175845989e1dc5eb310764a525632ad6d0629f5eb43ab0173ff0bd55890
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section[39]/table-wrap[1]#TV
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Receiver operator characteristic curves for validated candidates
structure object · 5 fields
pmcid
PMC3945903
section_index
39
section_title
Validation of Biomarker Candidate Proteins in an Extended Patient Group
row_count
11
column_count
3
table object · 8 fields
label
Table V
caption
Receiver operator characteristic curves for validated candidates
rows array · 11 items
[0] array · 2 items
[0]
Biomarker candidate
[1]
AUC (95%CI)
[1] array · 2 items
[0]
MM vs. non-MM
[1]
MM vs. Mets
[2] array · 3 items
[0]
Aldo-keto reductase 1B10
[1]
0.71 (0.59–0.83)
[2]
0.66 (0.52–0.81)
[3] array · 3 items
[0]
Apolipoprotein C-I
[1]
0.60 (0.46–0.73)
[2]
0.57 (0.41–0.74)
[4] array · 3 items
[0]
Galectin 1
[1]
0.87 (0.79–0.95)
[2]
0.93 (0.86–0.99)
[5] array · 3 items
[0]
Myosin-VIIb
[1]
0.60 (0.47–0.74)
[2]
0.59 (0.43–0.75)
[6] array · 3 items
[0]
Superoxide dismutase 2
[1]
0.64 (0.51–0.78)
[2]
0.71 (0.55–0.86)
[7] array · 3 items
[0]
Tenascin C
[1]
0.54 (0.40–0.68)
[2]
0.56 (0.40–0.72)
[8] array · 3 items
[0]
Thrombospondin 1
[1]
0.54 (0.40–0.68)
[2]
0.54 (0.37–0.70)
[9] array · 3 items
[0]
Hyaluronan
[1]
0.71 (0.59–0.83)
[2]
0.82 (0.70–0.94)
[10] array · 3 items
[0]
N-ERC/mesothelin
[1]
0.89 (0.80–0.97)
[2]
0.87 (0.77–0.96)
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section[39]/table-wrap[1]#TV
gaps array · 2 items
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asset:data:geo:PXD000531 not downloaded
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asset:data:geo:PXD000531 licence not read
analysis object · 4 fields
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method-1
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null
specific
null
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Nonparametric Kruskal–Wallis test with Dunn’s post hoc test
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score
1
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verbatim
quote
The three sample groups (mesothelioma, metastatic carcinomas, and benign conditions) were compared using the nonparametric Kruskal–Wallis test, with comparisons between groups performed using Dunn's post hoc test to obtain multiplicity-adjusted p values.
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[0] object · 8 fields
id
target-published-estimate
claim_id
claim-target-result
operation
null
unit
per cent
tolerance
null
state
complete
note
The published estimate as the reader quoted it from the paper. No tolerance is published because the paper states none.
gaps array · 1 item
[0]
method.reader_named_unmapped
capability object · 3 fields
state
complete
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capability:computational_analysis
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meta_analysis
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survival_analysis
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statistical_regression
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pca
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molecular_docking
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candidate
Automated Assays Laravel application and simulated adapters
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readiness object · 8 fields
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blocking_axis
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blocked_on
method:not_determinable
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R4
expressible
false
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basis
The reader quoted the method the paper names (Nonparametric Kruskal–Wallis test with Dunn’s post hoc test), but the corpus's method extractor could not map it onto a DSL operation, so the method is published but not expressible.
capability object · 4 fields
tier
R1
capability_id
capability:computational_analysis
availability_state
owned
basis
The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here.
data object · 6 fields
tier
R1
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true
accessions array · 1 item
[0]
PXD000531
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PXD000531
statements array · 1 item
[0]
The raw data associated with this manuscript have been deposited in the ProteomeXchange Consortium via the PRIDE partner repository (36) with the dataset identifier PXD000531.
basis
The paper names PXD000531 in ProteomeXchange Consortium via the PRIDE partner repository and the accession resolves in the repository. No dataset was downloaded and no licence was read.
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source:pmid:24361865
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run_analysis
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data:geo:PXD000531
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method:not_determinable
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MiniMax-M3.1-Flash
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minimax
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extraction
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complete
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review.independent_reader
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source:pmid:24361865
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rformed quantitative mass-spectrometry-based proteomics using isobaric tags for quantification and u
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d suggested biological relevance. Commercial ELISA assays were used to analyze samples from an
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validation population as measured by MS and ELISA, respectively. Receiver operator characteris
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[3]
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:24361865", "kind": "science-record", "revision": 6, "content_hash": "sha256:71f44c47536d83ba0364d1d4e1a4ffeaf0fefa419226c125bb6b0776b3f60d70", "created_at": "2026-11-01T15:40:04Z", "updated_at": "2026-11-01T21:19:45Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Proteome screening of pleural effusions identifies galectin 1 as a diagnostic biomarker and highlights several prognostic biomarkers for malignant mesothelioma.", "doi": "10.1074/mcp.M113.030775", "pmid": "24361865", "authors": ["Filip Mundt", "Henrik J Johansson", "Jenny Forshed", "Sertaç Arslan", "Muzaffer Metintas", "Katalin Dobra", "Janne Lehtiö", "Anders Hjerpe"], "journal": "Molecular & cellular proteomics : MCP", "year": 2014, "abstract": "Malignant mesothelioma is an aggressive asbestos-induced cancer, and affected patients have a median survival of approximately one year after diagnosis. It is often difficult to reach a conclusive diagnosis, and ancillary measurements of soluble biomarkers could increase diagnostic accuracy. Unfortunately, few soluble mesothelioma biomarkers are suitable for clinical application. Here we screened the effusion proteomes of mesothelioma and lung adenocarcinoma patients to identify novel soluble mesothelioma biomarkers. We performed quantitative mass-spectrometry-based proteomics using isobaric tags for quantification and used narrow-range immobilized pH gradient/high-resolution isoelectric focusing (pH 4-4.25) prior to analysis by means of nano liquid chromatography coupled to MS/MS. More than 1,300 proteins were identified in pleural effusions from patients with malignant mesothelioma (n = 6), lung adenocarcinoma (n = 6), or benign mesotheliosis (n = 7). Data are available via ProteomeXchange with identifier PXD000531. The identified proteins included a set of known mesothelioma markers and proteins that regulate hallmarks of cancer such as invasion, angiogenesis, and immune evasion, plus several new candidate proteins. Seven candidates (aldo-keto reductase 1B10, apolipoprotein C-I, galectin 1, myosin-VIIb, superoxide dismutase 2, tenascin C, and thrombospondin 1) were validated by enzyme-linked immunosorbent assays in a larger group of patients with mesothelioma (n = 37) or metastatic carcinomas (n = 25) and in effusions from patients with benign, reactive conditions (n = 16). Galectin 1 was identified as overexpressed in effusions from lung adenocarcinoma relative to mesothelioma and was validated as an excellent predictor for metastatic carcinomas against malignant mesothelioma. Galectin 1, aldo-keto reductase 1B10, and apolipoprotein C-I were all identified as potential prognostic biomarkers for malignant mesothelioma. This analysis of the effusion proteome furthers our understanding of malignant mesothelioma, identified galectin 1 as a potential diagnostic biomarker, and highlighted several possible prognostic biomarkers of this disease.", "claims": [{"id": "claim-method", "statement": "The three sample groups (mesothelioma, metastatic carcinomas, and benign conditions) were compared using the nonparametric Kruskal–Wallis test, with comparisons between groups performed using Dunn's post hoc test to obtain multiplicity-adjusted p values.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:24361865", "locator": "sections[26] \"Comparison of Groups Using One-way ANOVA\" paragraph 2", "quote": "The three sample groups (mesothelioma, metastatic carcinomas, and benign conditions) were compared using the nonparametric Kruskal–Wallis test, with comparisons between groups performed using Dunn's post hoc test to obtain multiplicity-adjusted p values."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The raw data associated with this manuscript have been deposited in the ProteomeXchange Consortium via the PRIDE partner repository (36) with the dataset identifier PXD000531.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:24361865", "locator": "sections[18] \"Peptide and Protein Identification\" paragraph 2", "quote": "The raw data associated with this manuscript have been deposited in the ProteomeXchange Consortium via the PRIDE partner repository (36) with the dataset identifier PXD000531."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Cutoff Finder–selected, Kaplan–Meier survival analysis with log-rank testing found significant prognostic trends for aldo-keto reductase 1B10, apolipoprotein C-I, and galectin 1 in malignant mesothelioma (hazard ratios 3.4, 2.30, and 2.34, respectively), while the proteomics source data were deposited through ProteomeXchange under identifier PXD000531.", "kind": "quantitative", "target": {"value": 95.0, "unit": "per cent", "tolerance": null, "source": "For aldo-keto reductase 1B10, there was a survival difference of 5.5 months for patients below and above 0.65 ng/ml (11- and 5.5-month median survival, respectively; p value = 0.01), and the corresponding Mantel–Cox hazard ratio was 3.4 between the two groups (95% confidence interval = 1.33–8.63)."}, "evidence": [{"asset": "source:pmid:24361865", "locator": "sections[28] \"Survival Analysis\" paragraph 2", "quote": "The Web-based threshold selection tool Cutoff Finder was used to condition a threshold for each biomarker based on its most significant hazard ratio (42)."}, {"asset": "source:pmid:24361865", "locator": "sections[28] \"Survival Analysis\" paragraph 2", "quote": "The Kaplan–Meier estimator was used to evaluate possible prognostic information."}, {"asset": "source:pmid:24361865", "locator": "sections[28] \"Survival Analysis\" paragraph 2", "quote": "The log-rank (Mantel–Cox) test was performed to compare survival curves and to estimate hazard ratios."}, {"asset": "source:pmid:24361865", "locator": "sections[40] \"Survival Analyses\" paragraph 2", "quote": "Aldo-keto reductase 1B10, apolipoprotein C-I, and galectin 1 showed significant prognostic trends (Fig. 6)."}, {"asset": "source:pmid:24361865", "locator": "sections[40] \"Survival Analyses\" paragraph 2", "quote": "For aldo-keto reductase 1B10, there was a survival difference of 5.5 months for patients below and above 0.65 ng/ml (11- and 5.5-month median survival, respectively; 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