Limits...
A Pilot Proteogenomic Study with Data Integration Identifies MCT1 and GLUT1 as Prognostic Markers in Lung Adenocarcinoma.

Stewart PA, Parapatics K, Welsh EA, Müller AC, Cao H, Fang B, Koomen JM, Eschrich SA, Bennett KL, Haura EB - PLoS ONE (2015)

Bottom Line: We performed a pilot proteogenomic study to compare lung adenocarcinoma to lung squamous cell carcinoma using quantitative proteomics (6-plex TMT) combined with a customized Affymetrix GeneChip.We then compared our results to published adenocarcinoma versus squamous cell carcinoma proteomic data that we also processed with MaxQuant.Data are available via ProteomeXchange with identifier PXD002622.

View Article: PubMed Central - PubMed

Affiliation: Department of Thoracic Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida, United States of America 33612.

ABSTRACT
We performed a pilot proteogenomic study to compare lung adenocarcinoma to lung squamous cell carcinoma using quantitative proteomics (6-plex TMT) combined with a customized Affymetrix GeneChip. Using MaxQuant software, we identified 51,001 unique peptides that mapped to 7,241 unique proteins and from these identified 6,373 genes with matching protein expression for further analysis. We found a minor correlation between gene expression and protein expression; both datasets were able to independently recapitulate known differences between the adenocarcinoma and squamous cell carcinoma subtypes. We found 565 proteins and 629 genes to be differentially expressed between adenocarcinoma and squamous cell carcinoma, with 113 of these consistently differentially expressed at both the gene and protein levels. We then compared our results to published adenocarcinoma versus squamous cell carcinoma proteomic data that we also processed with MaxQuant. We selected two proteins consistently overexpressed in squamous cell carcinoma in all studies, MCT1 (SLC16A1) and GLUT1 (SLC2A1), for further investigation. We found differential expression of these same proteins at the gene level in our study as well as in other public gene expression datasets. These findings combined with survival analysis of public datasets suggest that MCT1 and GLUT1 may be potential prognostic markers in adenocarcinoma and druggable targets in squamous cell carcinoma. Data are available via ProteomeXchange with identifier PXD002622.

No MeSH data available.


Related in: MedlinePlus

Overlap Between Proteomic Datasets.(A) Peptide overlap between proteomic datasets. (B) Protein overlap between proteomic datasets. (C) Differentially expressed protein overlap between proteomic datasets. D) Differentially expressed protein overlap between proteomic datasets, excluding proteins not sharing the same direction of change.
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4634858&req=5

pone.0142162.g002: Overlap Between Proteomic Datasets.(A) Peptide overlap between proteomic datasets. (B) Protein overlap between proteomic datasets. (C) Differentially expressed protein overlap between proteomic datasets. D) Differentially expressed protein overlap between proteomic datasets, excluding proteins not sharing the same direction of change.

Mentions: We then compared our quantitative results to published proteomic studies of ADC and SCC. To reduce analytical variability in our cross-study comparison, we used MaxQuant and the same analysis pipeline to process publically available ADC and SCC lung tissue data from Kikuchi et al. and Li et al. (Table 1) [15,19]. Our dataset identified 51,001 unique peptides, the Li et al. data had 39,048 unique peptides, and the Kikuchi et al. data had 18,198 unique peptides. There were 6,372 peptides in common between the three datasets (Fig 2A). Peptides that overlapped between our results and the other studies showed low correlation (Fig 3A and 3B). Our data had 395 missing reporter ion intensities (0.1% of all peptide intensities from this dataset), the Kikuchi et al. data had 23,287 missing peptide intensity values (16% of all peptide measurement from this dataset were affected), and the Li et al. data had 92,255 missing peptide intensity values (21% of all peptide measurements from this dataset were affected). Peptide lengths (S1A Fig) between our data (mean length = 12.26) and the others (Kikuchi et al. mean length = 13.58, Li et al. mean length = 15.99) were significantly different by a Mann-Whitney/Wilcoxon rank-sum test (P < 0.05). This may be explained by the increased fractionation enabling additional sequencing of shorter peptides or by the increased mass and trend toward higher charge states from addition of the covalent TMT modifier.


A Pilot Proteogenomic Study with Data Integration Identifies MCT1 and GLUT1 as Prognostic Markers in Lung Adenocarcinoma.

Stewart PA, Parapatics K, Welsh EA, Müller AC, Cao H, Fang B, Koomen JM, Eschrich SA, Bennett KL, Haura EB - PLoS ONE (2015)

Overlap Between Proteomic Datasets.(A) Peptide overlap between proteomic datasets. (B) Protein overlap between proteomic datasets. (C) Differentially expressed protein overlap between proteomic datasets. D) Differentially expressed protein overlap between proteomic datasets, excluding proteins not sharing the same direction of change.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4634858&req=5

pone.0142162.g002: Overlap Between Proteomic Datasets.(A) Peptide overlap between proteomic datasets. (B) Protein overlap between proteomic datasets. (C) Differentially expressed protein overlap between proteomic datasets. D) Differentially expressed protein overlap between proteomic datasets, excluding proteins not sharing the same direction of change.
Mentions: We then compared our quantitative results to published proteomic studies of ADC and SCC. To reduce analytical variability in our cross-study comparison, we used MaxQuant and the same analysis pipeline to process publically available ADC and SCC lung tissue data from Kikuchi et al. and Li et al. (Table 1) [15,19]. Our dataset identified 51,001 unique peptides, the Li et al. data had 39,048 unique peptides, and the Kikuchi et al. data had 18,198 unique peptides. There were 6,372 peptides in common between the three datasets (Fig 2A). Peptides that overlapped between our results and the other studies showed low correlation (Fig 3A and 3B). Our data had 395 missing reporter ion intensities (0.1% of all peptide intensities from this dataset), the Kikuchi et al. data had 23,287 missing peptide intensity values (16% of all peptide measurement from this dataset were affected), and the Li et al. data had 92,255 missing peptide intensity values (21% of all peptide measurements from this dataset were affected). Peptide lengths (S1A Fig) between our data (mean length = 12.26) and the others (Kikuchi et al. mean length = 13.58, Li et al. mean length = 15.99) were significantly different by a Mann-Whitney/Wilcoxon rank-sum test (P < 0.05). This may be explained by the increased fractionation enabling additional sequencing of shorter peptides or by the increased mass and trend toward higher charge states from addition of the covalent TMT modifier.

Bottom Line: We performed a pilot proteogenomic study to compare lung adenocarcinoma to lung squamous cell carcinoma using quantitative proteomics (6-plex TMT) combined with a customized Affymetrix GeneChip.We then compared our results to published adenocarcinoma versus squamous cell carcinoma proteomic data that we also processed with MaxQuant.Data are available via ProteomeXchange with identifier PXD002622.

View Article: PubMed Central - PubMed

Affiliation: Department of Thoracic Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida, United States of America 33612.

ABSTRACT
We performed a pilot proteogenomic study to compare lung adenocarcinoma to lung squamous cell carcinoma using quantitative proteomics (6-plex TMT) combined with a customized Affymetrix GeneChip. Using MaxQuant software, we identified 51,001 unique peptides that mapped to 7,241 unique proteins and from these identified 6,373 genes with matching protein expression for further analysis. We found a minor correlation between gene expression and protein expression; both datasets were able to independently recapitulate known differences between the adenocarcinoma and squamous cell carcinoma subtypes. We found 565 proteins and 629 genes to be differentially expressed between adenocarcinoma and squamous cell carcinoma, with 113 of these consistently differentially expressed at both the gene and protein levels. We then compared our results to published adenocarcinoma versus squamous cell carcinoma proteomic data that we also processed with MaxQuant. We selected two proteins consistently overexpressed in squamous cell carcinoma in all studies, MCT1 (SLC16A1) and GLUT1 (SLC2A1), for further investigation. We found differential expression of these same proteins at the gene level in our study as well as in other public gene expression datasets. These findings combined with survival analysis of public datasets suggest that MCT1 and GLUT1 may be potential prognostic markers in adenocarcinoma and druggable targets in squamous cell carcinoma. Data are available via ProteomeXchange with identifier PXD002622.

No MeSH data available.


Related in: MedlinePlus