Cargando…
Quantitative proteomics identifies and validates urinary biomarkers of rhabdomyosarcoma in children
BACKGROUND: Rhabdomyosarcoma (RMS) is the most common soft tissue sarcoma with poor prognosis in children. The 5-year survival rate for early RMS has improved, whereas it remains unsatisfactory for advanced patients. Urine can rapidly reflect changes in the body and identify low-abundance proteins....
Autores principales: | , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10012572/ https://www.ncbi.nlm.nih.gov/pubmed/36918772 http://dx.doi.org/10.1186/s12014-023-09401-4 |
_version_ | 1784906629892800512 |
---|---|
author | Xu, Na Yu, Yuncui Duan, Chao Wei, Jing Sun, Wei Jiang, Chiyi Jian, Binglin Cao, Wang Jia, Lulu Ma, Xiaoli |
author_facet | Xu, Na Yu, Yuncui Duan, Chao Wei, Jing Sun, Wei Jiang, Chiyi Jian, Binglin Cao, Wang Jia, Lulu Ma, Xiaoli |
author_sort | Xu, Na |
collection | PubMed |
description | BACKGROUND: Rhabdomyosarcoma (RMS) is the most common soft tissue sarcoma with poor prognosis in children. The 5-year survival rate for early RMS has improved, whereas it remains unsatisfactory for advanced patients. Urine can rapidly reflect changes in the body and identify low-abundance proteins. Early screening of tumor markers through urine in RMS allows for earlier treatment, which is associated with better outcomes. METHODS: RMS patients under 18 years old, including those newly diagnosed and after surgery, were enrolled. Urine samples were collected at the time points of admission and after four cycles of chemotherapy during follow-up. Then, a two-stage workflow was established. (1) In the discovery stage, differential proteins (DPs) were initially identified in 43 RMS patients and 12 healthy controls (HCs) using a data-independent acquisition method. (2) In the verification stage, DPs were further verified as biomarkers in 54 RMS patients and 25 HCs using parallel reaction monitoring analysis. Furthermore, a receiver operating characteristic (ROC) curve was used to construct the protein panels for the diagnosis of RMS. Gene Ontology (GO) and Ingenuity Pathway Analysis (IPA) software were used to perform bioinformatics analysis. RESULTS: A total of 251 proteins were significantly altered in the discovery stage, most of which were enriched in the head, neck and urogenital tract, consistent with the most common sites of RMS. The most overrepresented biological processes from GO analysis included immunity, inflammation, tumor invasion and neuronal damage. Pathways engaging the identified proteins revealed 33 common pathways, including WNT/β-catenin signaling and PI3K/AKT signaling. Finally, 39 proteins were confirmed as urinary biomarkers for RMS, and a diagnostic panel composed of 5 candidate proteins (EPS8L2, SPARC, HLA-DRB1, ACAN, and CILP) was constructed for the early screening of RMS (AUC: 0.79, 95%CI = 0.66 ~ 0.92). CONCLUSIONS: These findings provide novel biomarkers in urine that are easy to translate into clinical diagnosis of RMS and illustrate the value of global and targeted urine proteomics to identify and qualify candidate biomarkers for noninvasive molecular diagnosis. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12014-023-09401-4. |
format | Online Article Text |
id | pubmed-10012572 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-100125722023-03-15 Quantitative proteomics identifies and validates urinary biomarkers of rhabdomyosarcoma in children Xu, Na Yu, Yuncui Duan, Chao Wei, Jing Sun, Wei Jiang, Chiyi Jian, Binglin Cao, Wang Jia, Lulu Ma, Xiaoli Clin Proteomics Research BACKGROUND: Rhabdomyosarcoma (RMS) is the most common soft tissue sarcoma with poor prognosis in children. The 5-year survival rate for early RMS has improved, whereas it remains unsatisfactory for advanced patients. Urine can rapidly reflect changes in the body and identify low-abundance proteins. Early screening of tumor markers through urine in RMS allows for earlier treatment, which is associated with better outcomes. METHODS: RMS patients under 18 years old, including those newly diagnosed and after surgery, were enrolled. Urine samples were collected at the time points of admission and after four cycles of chemotherapy during follow-up. Then, a two-stage workflow was established. (1) In the discovery stage, differential proteins (DPs) were initially identified in 43 RMS patients and 12 healthy controls (HCs) using a data-independent acquisition method. (2) In the verification stage, DPs were further verified as biomarkers in 54 RMS patients and 25 HCs using parallel reaction monitoring analysis. Furthermore, a receiver operating characteristic (ROC) curve was used to construct the protein panels for the diagnosis of RMS. Gene Ontology (GO) and Ingenuity Pathway Analysis (IPA) software were used to perform bioinformatics analysis. RESULTS: A total of 251 proteins were significantly altered in the discovery stage, most of which were enriched in the head, neck and urogenital tract, consistent with the most common sites of RMS. The most overrepresented biological processes from GO analysis included immunity, inflammation, tumor invasion and neuronal damage. Pathways engaging the identified proteins revealed 33 common pathways, including WNT/β-catenin signaling and PI3K/AKT signaling. Finally, 39 proteins were confirmed as urinary biomarkers for RMS, and a diagnostic panel composed of 5 candidate proteins (EPS8L2, SPARC, HLA-DRB1, ACAN, and CILP) was constructed for the early screening of RMS (AUC: 0.79, 95%CI = 0.66 ~ 0.92). CONCLUSIONS: These findings provide novel biomarkers in urine that are easy to translate into clinical diagnosis of RMS and illustrate the value of global and targeted urine proteomics to identify and qualify candidate biomarkers for noninvasive molecular diagnosis. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12014-023-09401-4. BioMed Central 2023-03-14 /pmc/articles/PMC10012572/ /pubmed/36918772 http://dx.doi.org/10.1186/s12014-023-09401-4 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Xu, Na Yu, Yuncui Duan, Chao Wei, Jing Sun, Wei Jiang, Chiyi Jian, Binglin Cao, Wang Jia, Lulu Ma, Xiaoli Quantitative proteomics identifies and validates urinary biomarkers of rhabdomyosarcoma in children |
title | Quantitative proteomics identifies and validates urinary biomarkers of rhabdomyosarcoma in children |
title_full | Quantitative proteomics identifies and validates urinary biomarkers of rhabdomyosarcoma in children |
title_fullStr | Quantitative proteomics identifies and validates urinary biomarkers of rhabdomyosarcoma in children |
title_full_unstemmed | Quantitative proteomics identifies and validates urinary biomarkers of rhabdomyosarcoma in children |
title_short | Quantitative proteomics identifies and validates urinary biomarkers of rhabdomyosarcoma in children |
title_sort | quantitative proteomics identifies and validates urinary biomarkers of rhabdomyosarcoma in children |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10012572/ https://www.ncbi.nlm.nih.gov/pubmed/36918772 http://dx.doi.org/10.1186/s12014-023-09401-4 |
work_keys_str_mv | AT xuna quantitativeproteomicsidentifiesandvalidatesurinarybiomarkersofrhabdomyosarcomainchildren AT yuyuncui quantitativeproteomicsidentifiesandvalidatesurinarybiomarkersofrhabdomyosarcomainchildren AT duanchao quantitativeproteomicsidentifiesandvalidatesurinarybiomarkersofrhabdomyosarcomainchildren AT weijing quantitativeproteomicsidentifiesandvalidatesurinarybiomarkersofrhabdomyosarcomainchildren AT sunwei quantitativeproteomicsidentifiesandvalidatesurinarybiomarkersofrhabdomyosarcomainchildren AT jiangchiyi quantitativeproteomicsidentifiesandvalidatesurinarybiomarkersofrhabdomyosarcomainchildren AT jianbinglin quantitativeproteomicsidentifiesandvalidatesurinarybiomarkersofrhabdomyosarcomainchildren AT caowang quantitativeproteomicsidentifiesandvalidatesurinarybiomarkersofrhabdomyosarcomainchildren AT jialulu quantitativeproteomicsidentifiesandvalidatesurinarybiomarkersofrhabdomyosarcomainchildren AT maxiaoli quantitativeproteomicsidentifiesandvalidatesurinarybiomarkersofrhabdomyosarcomainchildren |