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DOI 10.1186/s12967-022-03268-z

Медицинская библиотека · Journal of translational medicine · 2022

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

СтатьяПоддержка исследования: вне правительства СШАПеревод в очереди

Аннотация

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.

Для цитирования: 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.. Journal of translational medicine. 2022. DOI: 10.1186/s12967-022-03268-z.

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