Comparative proteomics analysis in different stages of urothelial bladder cancer for identification of potential biomarkers: highlighted role for antioxidant activity

Tabaei, Samira; Haghshenas, Mohammad Reza; Ariafar, Ali; Gilany, Kambiz; Stensballe, Allan; Farjadian, Shirin; Ghaderi, Abbas

doi:10.1186/s12014-023-09419-8

Cited by 5 publications

(5 citation statements)

References 80 publications

(69 reference statements)

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“…In this study, proteomic analysis of bladder cancer was completed by LC−MS, and 331 differential proteins were also reported to be differential proteins in other studies ( 16 – 20 , 23 – 34 ). The differentially expressed proteins reflected the functions of cell motility, proliferation, metabolism, necrosis and signal transduction.…”

Section: Discussionmentioning

confidence: 85%

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Exploration of potential biomarkers for early bladder cancer based on urine proteomics

Zhou,

Xue,

et al. 2024

Front. Oncol.

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BackgroundBladder cancer is a common malignant tumor of the urinary system. The progression of the condition is associated with a poor prognosis, so it is necessary to identify new biomarkers to improve the diagnostic rate of bladder cancer.MethodsIn this study, 338 urine samples (144 bladder cancer, 123 healthy control, 32 cystitis, and 39 upper urinary tract cancer samples) were collected, among which 238 samples (discovery group) were analyzed by LC−MS. The urinary proteome characteristics of each group were compared with those of bladder cancer, and the differential proteins were defined by bioinformatics analysis. The pathways and functional enrichments were annotated. The selected proteins with the highest AUC score were used to construct a diagnostic panel. One hundred samples (validation group) were used to test the effect of the panel by ELISA.ResultsCompared with the healthy control, cystitis and upper urinary tract cancer samples, the number of differential proteins in the bladder cancer samples was 325, 158 and 473, respectively. The differentially expressed proteins were mainly related to lipid metabolism and iron metabolism and were involved in the proliferation, metabolism and necrosis of bladder cancer cells. The AUC of the panel of APOL1 and ITIH3 was 0.96 in the discovery group. ELISA detection showed an AUC of 0.92 in the validation group.ConclusionThis study showed that urinary proteins can reflect the pathophysiological changes in bladder cancer and that important molecules can be used as biomarkers for bladder cancer screening. These findings will benefit the application of the urine proteome in clinical research.

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Section: Discussionmentioning

confidence: 85%

“…In the latest study in 2023, Tabaei S et al. ( 20 ) collected urine protein information from 42 urine samples (25 nonmuscle invasive bladder cancer and 17 muscle invasive bladder cancer samples) by 2-DE and LC-MS, and 12 differential expressed proteins were identified.…”

Section: Introductionmentioning

confidence: 99%

Exploration of potential biomarkers for early bladder cancer based on urine proteomics

Zhou,

Xue,

et al. 2024

Front. Oncol.

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“…Proteomic pro ling of bladder cancer tissue performed by others revealed subtype and stage-related differences converging on glucolipid metabolism. [11][12][13] Whole-organ spatial geographic analyses revealed that bladder carcinogenesis may develop innocuously over several decades and can be divided into dormant and Highly variable mutagenesis signatures were identi ed in individual mucosal samples but signatures 1 and 6 were dominant. 14 Moreover, the development of α, β, and ϒ mutations were driven by distinct mutational mechanisms.…”

Section: Discussionmentioning

confidence: 99%

Inferring Bladder Cancer Evolution from Mucosal Field Effects by Whole-Organ Spatial Mutational, Proteomic, and Metabolomic Mapping

Czerniak,

Lee,

Jung

et al. 2024

Preprint

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Multi-platform mutational, proteomic, and metabolomic spatial mapping was used on the whole-organ scale to identify the molecular evolution of bladder cancer from mucosal field effects. We identified complex proteomic and metabolomic dysregulations in microscopically normal areas of bladder mucosa adjacent to dysplasia and carcinoma in situ. The mutational landscape developed in a background of complex defects of protein homeostasis which included dysregulated nucleocytoplasmic transport, splicesome, ribosome biogenesis, and peroxisome. These changes were combined with altered urothelial differentiation which involved lipid metabolism and protein degradations controlled by PPAR. The complex alterations of proteome were accompanied by dysregulation of gluco-lipid energy-related metabolism. The analysis of mutational landscape identified three types of mutations based on their geographic distribution and variant allele frequencies. The most common were low frequency α mutations restricted to individual mucosal samples. The two other groups of mutations were associated with clonal expansion. The first of this group referred to as β mutations occurred at low frequencies across the mucosa. The second of this group called γ mutations increased in frequency with disease progression. Modeling of the mutations revealed that carcinogenesis may span nearly 30 years and can be divided into dormant and progressive phases. The α mutations developed gradually in the dormant phase. The progressive phase lasted approximately five years and was signified by the advent of β mutations, but it was driven by γ mutations which developed during the last 2–3 years of disease progression to invasive cancer. Our study indicates that the understanding of complex alterations involving mucosal microenvironment initiating bladder carcinogenesis can be inferred from the multi-platform whole-organ mapping.

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“…In recent years, mass spectrometry (MS)-based proteomics has become a widely used platform for clinical biomarker discovery and studying cellular signaling networks. This has led to technological developments of fast sequencing mass spectrometers that facilitate short online liquid chromatography tandem mass spectrometry (LC-MS/MS) enabling highthroughput analyses of hundreds of samples per day (1)(2)(3)(4). It is increasingly feasible to utilize LC-MS/MS for analyzing large patient cohorts but the bottlenecks for large-scale studies have moved to the pre-and post-analytical sample processing steps, which are unable to keep up with the increased throughput of the LC-MS/MS analyses.…”

Section: Introductionmentioning

confidence: 99%

Fully automated workflow for integrated sample digestion and Evotip loading enabling high-throughput clinical proteomics

Kverneland,

Harking,

Vej-Nielsen

et al. 2023

Preprint

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Protein identification and quantification is an important tool for biomarker discovery. With the increased sensitivity and speed of modern mass spectrometers, sample-preparation remains a bottleneck for studying large cohorts. To address this issue, we prepared and evaluated a simple and efficient workflow on the Opentrons OT-2 (OT-2) robot that combines sample digestion, cleanup and Evotip loading in a fully automated manner, allowing the processing of up to 192 samples in 6 hours. Our results demonstrate a highly sensitive workflow yielding both reproducibility and stability even at low sample inputs. The workflow is optimized for minimal sample starting amount to reduce the costs for reagents needed for sample preparation, which is critical when analyzing large biological cohorts. Building on the digesting workflow, we incorporated an automated phosphopeptide enrichment step using magnetic Ti-IMAC beads. This allows for a fully automated proteome and phosphoproteome sample preparation in a single step with high sensitivity. Using the integrated workflow, we evaluated the effects of cancer immune therapy on the plasma proteome in metastatic melanoma patients.

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Comparative proteomics analysis in different stages of urothelial bladder cancer for identification of potential biomarkers: highlighted role for antioxidant activity

Cited by 5 publications

References 80 publications

Exploration of potential biomarkers for early bladder cancer based on urine proteomics

Exploration of potential biomarkers for early bladder cancer based on urine proteomics

Inferring Bladder Cancer Evolution from Mucosal Field Effects by Whole-Organ Spatial Mutational, Proteomic, and Metabolomic Mapping

Fully automated workflow for integrated sample digestion and Evotip loading enabling high-throughput clinical proteomics

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