Proteomic Signature of Extracellular Vesicles for Lung Cancer Recognition

Novikova, Svetlana; Соловьева, Н А; Farafonova, T. E.; Tikhonova, Olga V.; Liao, Pao‐Chi; Zgoda, Victor G.

doi:10.3390/molecules26206145

Cited by 16 publications

(9 citation statements)

References 48 publications

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“…Individual proteins, such as fibronectin 1 (FN1), have previously been found in cancer-associated vesicles [ 22 ]. However, to our knowledge, a simultaneous analysis of 13 proteins identified in this study has not been previously performed [ 60 ]. We identified several CRC-associated proteins, e.g., FN1, HSPA8, and TLN1, in the blood plasma obtained from patients with lung cancer.…”

Section: Discussionmentioning

confidence: 99%

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Proteomic Signature of Extracellular Vesicles Associated with Colorectal Cancer

et al. 2023

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The proteins of extracellular vesicles (EVs) provide proteomic signatures that reflect molecular features of EV-producing cells, including cancer cells. Detection of cancer cell EV proteins is of great interest due to the development of novel predictive diagnostic approaches. Using targeted mass spectrometry with stable-isotope-labeled peptide standards (SIS), we measured in this study the levels of 34 EV-associated proteins in vesicles and whole lysate derived from the colorectal cancer (CRC) cell lines Caco-2, HT29 and HCT116. We also evaluated the abundance of 13 EV-associated proteins (FN1, TLN1, ITGB3, HSPA8, TUBA4A, CD9, CD63, HSPG2, ITGB1, GNAI2, TSG101, PACSIN2, and CDC42) in EVs isolated from blood plasma samples from 11 CRC patients and 20 healthy volunteers. Downregulation of TLN1, ITGB3, and TUBA4A with simultaneous upregulation of HSPG2 protein were observed in cancer samples compared to healthy controls. The proteomic cargo of the EVs associated with CRC represents a promising source of potential prognostic markers.

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Section: Discussionmentioning

confidence: 99%

“…Sample preparation of EVs obtained from the culture medium of CRC cell lines for further targeted mass spectrometry analysis was performed as described previously [ 60 ].…”

Section: Methodsmentioning

confidence: 99%

Proteomic Signature of Extracellular Vesicles Associated with Colorectal Cancer

et al. 2023

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“…TUBA4A mutations have been linked to neurodegenerative diseases such as amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) [ 34 , 35 ]. Little articles concern TUBA4A in cancer, and only lung cancer was mentioned [ 36 – 38 ]. TUBA4A could be a potential biomarker for BLCA prognosis prediction, but specific mechanisms must be investigated.…”

Section: Discussionmentioning

confidence: 99%

A Multiomics Profiling Based on Online Database Revealed Prognostic Biomarkers of BLCA

Chen

2022

BioMed Research International

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Background. Bladder cancer (BLCA) is one of the most common urological malignancies globally, posing a severe threat to public health. In combination with protein-protein interaction (PPI) network analysis of proteomics, Gene Set Variation Analysis (GSVA) and “CancerSubtypes” package of R software for transcriptomics can help identify biomarkers related to BLCA prognosis. This will have significant implications for prevention and treatment. Method. BLCA data were downloaded from The Cancer Genome Atlas (TCGA) database and GEO database (GSE13507). GSVA analysis converted the gene expression matrix to the gene set expression matrix. “CancerSubtypes” classified patients into three subtypes and established a prognostic model based on differentially expressed gene sets (DEGSs) among the three subtypes. For genes from prognosis-related DEGSs, functional and pathway enrichment analyses and PPI network analysis were carried out. The Human Protein Atlas (HPA) database was used for validation. Finally, the proportion of tumor-infiltrating immune cells (TIICs) was determined using the CIBERSORT algorithm. Results. In total, 414 tumor samples and 19 adjacent-tumor samples were obtained from TCGA, with 145 samples belonging to subtype A, 126 samples belonging to subtype B, and 136 samples belonging to subtype C. Then, we identified 83 DEGSs and constituted a prognostic signature with two of them: “GSE1460_CD4_THYMOCYTE_VS_THYMIC_STROMAL_CELL_DN” and “MODULE_253.” Finally, five subnets of two PPI networks were established, and nine core proteins were obtained: CDH2, COL1A1, EIF2S2, PSMA3, NAA10, DNM1L, TUBA4A, KIF11, and KIF23. The HPA database confirmed the expression of the nine core proteins in BLCA tissues. Furthermore, EIF2S2, PSMA3, DNM1L, and TUBA4A could be novel BLCA prognostic biomarkers. Conclusions. In this study, we discovered two gene sets linked to BLCA prognosis. PPI analysis confirmed the network’s core proteins, and several newly discovered biomarkers of BLCA prognosis were identified.

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“…Looking deeper in their molecular content, both circulating and tissue-specific EVs are being used as diagnosis and prognosis biomarkers at every level of content. Several diagnostic markers are being identified at RNA, protein and metabolic level of EVs in a wide range of cancers [ 26 ], such as colorectal cancer [ 27 , 28 ], prostatic cancer [ 29 , 30 ], lung cancers [ 31 , 32 ], breast cancer [ 33 , 34 ], as well as in many other diseases, such as pulmonary diseases [ 35 , 36 , 37 ], neurodegenerative diseases [ 38 , 39 ] and others. In fact, the most pursued objective in EVs biomarker discovery is the diagnosis of early-stage diseases by circulating vesicles from blood, urine or plasma, referred to as “liquid-biopsy”, as easily accessible biological fluids [ 40 ].…”

Section: Introductionmentioning

confidence: 99%

Multi-Omics Integrative Approach of Extracellular Vesicles: A Future Challenging Milestone

et al. 2022

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In the era of multi-omic sciences, dogma on singular cause-effect in physio-pathological processes is overcome and system biology approaches have been providing new perspectives to see through. In this context, extracellular vesicles (EVs) are offering a new level of complexity, given their role in cellular communication and their activity as mediators of specific signals to target cells or tissues. Indeed, their heterogeneity in terms of content, function, origin and potentiality contribute to the cross-interaction of almost every molecular process occurring in a complex system. Such features make EVs proper biological systems being, therefore, optimal targets of omic sciences. Currently, most studies focus on dissecting EVs content in order to either characterize it or to explore its role in various pathogenic processes at transcriptomic, proteomic, metabolomic, lipidomic and genomic levels. Despite valuable results being provided by individual omic studies, the categorization of EVs biological data might represent a limit to be overcome. For this reason, a multi-omic integrative approach might contribute to explore EVs function, their tissue-specific origin and their potentiality. This review summarizes the state-of-the-art of EVs omic studies, addressing recent research on the integration of EVs multi-level biological data and challenging developments in EVs origin.

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Proteomic Signature of Extracellular Vesicles for Lung Cancer Recognition

Cited by 16 publications

References 48 publications

Proteomic Signature of Extracellular Vesicles Associated with Colorectal Cancer

Proteomic Signature of Extracellular Vesicles Associated with Colorectal Cancer

A Multiomics Profiling Based on Online Database Revealed Prognostic Biomarkers of BLCA

Multi-Omics Integrative Approach of Extracellular Vesicles: A Future Challenging Milestone

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