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Prediction of occult tumor progression via platelet RNAs in a mouse melanoma model: a potential new platform for early detection of cancer

BACKGROUND: Cancer screening provides the opportunity to detect cancer early, ideally before symptom onset and metastasis, and offers an increased opportunity for a better prognosis. The ideal biomarkers for cancer screening should discriminate individuals who have not developed invasive cancer yet...

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Autores principales: Yin, Yue, Jiang, Ruilan, Shen, Mingwang, Li, Zhaofang, Yan, Ni, Feng, Junqiao, Jiang, Hong, Lv, Jiaxin, Shi, Lijuan, Wang, Lina, Liu, Xi, Zhang, Kaiyun, Chen, Di
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8817485/
https://www.ncbi.nlm.nih.gov/pubmed/35123499
http://dx.doi.org/10.1186/s12967-022-03268-z
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author Yin, Yue
Jiang, Ruilan
Shen, Mingwang
Li, Zhaofang
Yan, Ni
Feng, Junqiao
Jiang, Hong
Lv, Jiaxin
Shi, Lijuan
Wang, Lina
Liu, Xi
Zhang, Kaiyun
Chen, Di
author_facet Yin, Yue
Jiang, Ruilan
Shen, Mingwang
Li, Zhaofang
Yan, Ni
Feng, Junqiao
Jiang, Hong
Lv, Jiaxin
Shi, Lijuan
Wang, Lina
Liu, Xi
Zhang, Kaiyun
Chen, Di
author_sort Yin, Yue
collection PubMed
description BACKGROUND: Cancer screening provides the opportunity to detect cancer early, ideally before symptom onset and metastasis, and offers an increased opportunity for a better prognosis. The ideal biomarkers for cancer screening should discriminate individuals who have not developed invasive cancer yet but are destined to do so from healthy subjects. However, most cancers lack effective screening recommendations. Therefore, further studies on novel screening strategies are urgently required. METHODS: We used a simple suboptimal inoculation melanoma mouse model to obtain ‘pre-diagnostic samples’ of mice with macroscopic melanomas. High-throughput sequencing and bioinformatic analysis were employed to identify differentially expressed RNAs in platelet signatures of mice injected with a suboptimal number of melanoma cells (eDEGs) compared with mice with macroscopic melanomas and negative controls. Moreover, 36 genes selected from the eDEGs via bioinformatics analysis were verified in a mouse validation cohort via quantitative real-time PCR. LASSO regression was utilized to generate the prediction models with gene expression signatures as the best predictors for occult tumor progression in mice. RESULTS: These RNAs identified from eDEGs of mice injected with a suboptimal number of cancer cells were strongly enriched in pathways related to immune response and regulation. The prediction models generated by 36 gene qPCR verification data showed great diagnostic efficacy and predictive value in our murine validation cohort, and could discriminate mice with occult tumors from control group (area under curve (AUC) of 0.935 (training data) and 0.912 (testing data)) (gene signature including Cd19, Cdkn1a, S100a9, Tap1, and Tnfrsf1b) and also from macroscopic tumor group (AUC of 0.920 (training data) and 0.936 (testing data)) (gene signature including Ccr7, Cd4, Kmt2d, and Ly6e). CONCLUSIONS: Our proof-of-concept study provides evidence for potential clinical relevance of blood platelets as a platform for liquid biopsy-based early detection of cancer. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12967-022-03268-z.
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spelling pubmed-88174852022-02-07 Prediction of occult tumor progression via platelet RNAs in a mouse melanoma model: a potential new platform for early detection of cancer Yin, Yue Jiang, Ruilan Shen, Mingwang Li, Zhaofang Yan, Ni Feng, Junqiao Jiang, Hong Lv, Jiaxin Shi, Lijuan Wang, Lina Liu, Xi Zhang, Kaiyun Chen, Di J Transl Med Research BACKGROUND: Cancer screening provides the opportunity to detect cancer early, ideally before symptom onset and metastasis, and offers an increased opportunity for a better prognosis. The ideal biomarkers for cancer screening should discriminate individuals who have not developed invasive cancer yet but are destined to do so from healthy subjects. However, most cancers lack effective screening recommendations. Therefore, further studies on novel screening strategies are urgently required. METHODS: We used a simple suboptimal inoculation melanoma mouse model to obtain ‘pre-diagnostic samples’ of mice with macroscopic melanomas. High-throughput sequencing and bioinformatic analysis were employed to identify differentially expressed RNAs in platelet signatures of mice injected with a suboptimal number of melanoma cells (eDEGs) compared with mice with macroscopic melanomas and negative controls. Moreover, 36 genes selected from the eDEGs via bioinformatics analysis were verified in a mouse validation cohort via quantitative real-time PCR. LASSO regression was utilized to generate the prediction models with gene expression signatures as the best predictors for occult tumor progression in mice. RESULTS: These RNAs identified from eDEGs of mice injected with a suboptimal number of cancer cells were strongly enriched in pathways related to immune response and regulation. The prediction models generated by 36 gene qPCR verification data showed great diagnostic efficacy and predictive value in our murine validation cohort, and could discriminate mice with occult tumors from control group (area under curve (AUC) of 0.935 (training data) and 0.912 (testing data)) (gene signature including Cd19, Cdkn1a, S100a9, Tap1, and Tnfrsf1b) and also from macroscopic tumor group (AUC of 0.920 (training data) and 0.936 (testing data)) (gene signature including Ccr7, Cd4, Kmt2d, and Ly6e). CONCLUSIONS: Our proof-of-concept study provides evidence for potential clinical relevance of blood platelets as a platform for liquid biopsy-based early detection of cancer. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12967-022-03268-z. BioMed Central 2022-02-05 /pmc/articles/PMC8817485/ /pubmed/35123499 http://dx.doi.org/10.1186/s12967-022-03268-z Text en © The Author(s) 2022 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
Yin, Yue
Jiang, Ruilan
Shen, Mingwang
Li, Zhaofang
Yan, Ni
Feng, Junqiao
Jiang, Hong
Lv, Jiaxin
Shi, Lijuan
Wang, Lina
Liu, Xi
Zhang, Kaiyun
Chen, Di
Prediction of occult tumor progression via platelet RNAs in a mouse melanoma model: a potential new platform for early detection of cancer
title Prediction of occult tumor progression via platelet RNAs in a mouse melanoma model: a potential new platform for early detection of cancer
title_full Prediction of occult tumor progression via platelet RNAs in a mouse melanoma model: a potential new platform for early detection of cancer
title_fullStr Prediction of occult tumor progression via platelet RNAs in a mouse melanoma model: a potential new platform for early detection of cancer
title_full_unstemmed Prediction of occult tumor progression via platelet RNAs in a mouse melanoma model: a potential new platform for early detection of cancer
title_short Prediction of occult tumor progression via platelet RNAs in a mouse melanoma model: a potential new platform for early detection of cancer
title_sort prediction of occult tumor progression via platelet rnas in a mouse melanoma model: a potential new platform for early detection of cancer
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8817485/
https://www.ncbi.nlm.nih.gov/pubmed/35123499
http://dx.doi.org/10.1186/s12967-022-03268-z
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