scholarly journals Proteomic Signatures of Diffuse and Intestinal Subtypes of Gastric Cancer

Cancers ◽  
2021 ◽  
Vol 13 (23) ◽  
pp. 5930
Author(s):  
Smrita Singh ◽  
Mohd Younis Bhat ◽  
Gajanan Sathe ◽  
Champaka Gopal ◽  
Jyoti Sharma ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Gastric Cancer ◽  
Normal Tissue ◽  
Thyroid Hormone Receptor ◽  
Spectrometric Analysis ◽  
Tandem Mass ◽  
Discovery Cohort ◽  
Interacting Protein ◽  
Cancer Subtypes ◽  
Tumor Tissues

Gastric cancer is a leading cause of death from cancer globally. Gastric cancer is classified into intestinal, diffuse and indeterminate subtypes based on histology according to the Laurén classification. The intestinal and diffuse subtypes, although different in histology, demographics and outcomes, are still treated in the same fashion. This study was designed to discover proteomic signatures of diffuse and intestinal subtypes. Mass spectrometry-based proteomics using tandem mass tags (TMT)-based multiplexed analysis was used to identify proteins in tumor tissues from patients with diffuse or intestinal gastric cancer with adjacent normal tissue control. A total of 7448 or 4846 proteins were identified from intestinal or diffuse subtype, respectively. This quantitative mass spectrometric analysis defined a proteomic signature of differential expression across the two subtypes, which included gremlin1 (GREM1), bcl-2-associated athanogene 2 (BAG2), olfactomedin 4 (OLFM4), thyroid hormone receptor interacting protein 6 (TRIP6) and melanoma-associated antigen 9 (MAGE-A9) proteins. Although GREM1, BAG2, OLFM4, TRIP6 and MAGE-A9 have all been previously implicated in tumor progression and metastasis, they have not been linked to intestinal or diffuse subtypes of gastric cancer. Using immunohistochemical labelling of a tissue microarray comprising of 124 cases of gastric cancer, we validated the proteomic signature obtained by mass spectrometry in the discovery cohort. Our findings should help investigate the pathogenesis of these gastric cancer subtypes and potentially lead to strategies for early diagnosis and treatment.

Metabolomic discrimination of intestinal- and diffuse-type gastric cancer tissues using capillary electrophoresis time-of-flight mass spectrometry.

2012 ◽  
Vol 30 (15_suppl) ◽  
pp. e14635-e14635
Author(s):  
Masanori Terashima ◽  
Masatoshi Kusuhara ◽  
Masanori Tokunaga ◽  
Yutaka Tanizawa ◽  
Etsuro Bando ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Gastric Cancer ◽  
Capillary Electrophoresis ◽  
Cancer Patients ◽  
Time Of Flight ◽  
Diffuse Type ◽  
Flight Mass Spectrometry ◽  
Tumor Tissues ◽  
Gastric Cancer Patients ◽  
Diffuse Type Gastric Cancer

e14635 Background: Clinicopathological characteristics of gastric cancer patients strongly depend on histological type. In contrast with gene and protein expressions, metabolic properties of intestinal- and diffuse-type gastric cancer have been largely unknown. Here, we conducted metabolome analysis of paired non-tumor and tumor gastric tissues by using capillary electrophoresis and liquid chromatography combined with time-of-flight mass spectrometry (CE- and LC-TOFMS, respectively) in order to metabolomically characterize non-tumors (NTs), intestinal-type tumors (ITs), and diffuse-type tumors (DTs). Methods: Tumor and surrounding non-tumor tissues were surgically excised pair-wise from 27 gastric cancer patients (18 ITs and 9 DTs) who underwent gastrectomy at our institution between February and May 2011. Following tissue homogenization and metabolite extraction, we measured 254 and 138 metabolites, respectively, by CE-TOFMS and LC-TOFMS. Results: Metabolomic profiles of tumor tissues, especially ITs, were well-distinguished from those of NTs: Lactate and most glycolytic intermediate levels in ITs were significantly higher than those in NTs, which reaffirms the Warburg effect of cancer, but the significance was lesser in DTs. Levels of all the measured amino acids were significantly higher in ITs and relatively higher in DTs than in NTs, showing high capacities of cancer cells for protein synthesis. Although levels of ATP, GTP, and energy charge in ITs and DTs were lower than those in NTs, purine contents were rather higher in the tumors than in NTs, which may support their high demand for DNA replication. Moreover, reduced glutathione in DTs were the lowest among others, implying their potential vulnerability against oxidative stress. Conclusions: Metabolomic profiles of NTs, ITs, and DTs were discriminated by CE- and LC-TOFMS analyses: Considerably high lactate, amino acid, and purine levels highlighted the metabolome of tumors, especially of ITs. Relatively low energy and redox statuses of DTs, however, could be targeted for developing more effective cancer therapeutics.

scholarly journals Profiling of gastric cancer cell-surface markers to achieve tumour–normal discrimination

2020 ◽  
Vol 7 (1) ◽  
pp. e000452 ◽  
Author(s):  
Judith Toh ◽  
Michal Marek Hoppe ◽  
Teena Thakur ◽  
Henry Yang ◽  
Kar Tong Tan ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Cell Surface ◽  
Normal Tissue ◽  
Roc Curves ◽  
The Cancer Genome Atlas ◽  
Composite Panel ◽  
Surface Markers ◽  
Cell Surface Markers ◽  
Discovery Cohort ◽  
Specificity And Sensitivity

BackgroundDifferentiating between malignant and normal cells within tissue samples is vital for molecular profiling of cancer using advances in genomics and transcriptomics. Cell-surface markers of tumour–normal discrimination have additional value in terms of translatability to diagnostic and therapeutic strategies. In gastric cancer (GC), previous studies have identified individual genes or proteins that are upregulated in cancer. However, a systematic analysis of cell-surface markers and development of a composite panel involving multiple candidates to differentiate tumour from normal has not been previously reported.MethodsWhole transcriptome sequencing (WTS) of GC and matched normal samples from the Singapore Gastric Cancer Consortium (SGCC) was used as a discovery cohort to identify upregulated putative cell-surface proteins. Matched WTS data from the The Cancer Genome Atlas (TCGA) was used as a validation cohort. Promising candidates from this analysis were validated orthogonally using multispectral immunohistochemistry (mIHC) with automated quantitative analysis using the Vectra platform. mIHC was performed on a tissue microarray containing matched normal, marginal and tumour tissues. The receiver-operating characteristic (ROC) curves were analysed to identify markers with the highest diagnostic validity independently and in combination.ResultsAnalysis of putative membrane protein transcripts from the SGCC discovery cohort WTS data (n=15 matched tumour and normal pairs) identified several differentially and highly expressed candidates in tumour compared with normal tissues. After validation with TCGA data (n=29 matched tumour and normal pairs), the following proteins were selected for mIHC analysis: CEACAM5, CEACAM6, CLDN4, CLDN7, and EpCAM. These were compared with established glycoprotein markers in GC, namely CA19-9 and CA72-4. Individual ROC curves yielded the best performance for CEACAM5 (area under the ROC curve (AUC)=0.80), CEACAM6 (AUC=0.82), EpCAM (AUC=0.83), and CA72-4 (AUC=0.76). Combined multiplexed imaging of these four markers revealed improved specificity and sensitivity for detection of tumour from normal tissue (AUC of 4-plex=0.91).ConclusionCEAMCAM5, CEACAM6, EpCAM, and CA72-4 form a versatile set of markers for robust discrimination of GC from adjacent normal tissue. As cell-surface markers, they are compatible with both IHC and live imaging approaches. These candidates may be exploited to improve automated identification of tumour tissue in GC.

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