miRNAs derived from plasma small extracellular vesicles predict organo-tropic metastasis of gastric cancer

Zhang, Cheng; Yang, Jing; Chen, Yang; Jiang, Fangli; Liao, Haiyan; Liu, Xiang; Wang, Yuan; Kong, Guanyi; Zhang, Xiaotian; Li, Jian; Gao, Jing; Shen, Lin

doi:10.1007/s10120-021-01267-5

Cited by 12 publications

(8 citation statements)

References 48 publications

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“…Our previously reported 5 miRNA-ratio predictive model that was developed to differentiate between Controls combined with NDB vs. oesophageal adenocarcinoma, using a high throughput qPCR based technology [ 6 ], also contained miR-324-5p and miR-17-5p . Other researchers have identified circulating sEV miR-324-5p and miR-17-5p as potential biomarkers in gastric cancer [ 24 , 25 ].…”

Section: Discussionmentioning

confidence: 99%

A Method for Increasing the Robustness of Stable Feature Selection for Biomarker Discovery in Molecular Medicine Developed Using Serum Small Extracellular Vesicle Associated miRNAs and the Barrett’s Oesophagus Disease Spectrum

Mayne

Woodman

Watson

et al. 2023

IJMS

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The biomarker development field within molecular medicine remains limited by the methods that are available for building predictive models. We developed an efficient method for conservatively estimating confidence intervals for the cross validation-derived prediction errors of biomarker models. This new method was investigated for its ability to improve the capacity of our previously developed method, StaVarSel, for selecting stable biomarkers. Compared with the standard cross validation method, StaVarSel markedly improved the estimated generalisable predictive capacity of serum miRNA biomarkers for the detection of disease states that are at increased risk of progressing to oesophageal adenocarcinoma. The incorporation of our new method for conservatively estimating confidence intervals into StaVarSel resulted in the selection of less complex models with increased stability and improved or similar predictive capacities. The methods developed in this study have the potential to improve progress from biomarker discovery to biomarker driven translational research.

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Section: Discussionmentioning

confidence: 99%

A Method for Increasing the Robustness of Stable Feature Selection for Biomarker Discovery in Molecular Medicine Developed Using Serum Small Extracellular Vesicle Associated miRNAs and the Barrett’s Oesophagus Disease Spectrum

Mayne

Woodman

Watson

et al. 2023

IJMS

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“…Moreover, research in genetics has allowed us to better perform risk stratification of patients in clinical care ( Nabors et al, 2020 ). In the case of STAD, a variety of prognostic models have been developed with wide application prospects ( Shimura et al, 2022 ; Spolverato et al, 2022 ; Zhang et al, 2022 ). We have developed a high-performance prognostic model based on m6A-associated immune genes that has been successfully internally and externally validated and shows some degree of clinical translational value.…”

Section: Discussionmentioning

confidence: 99%

Prognostic Role of M6A-Associated Immune Genes and Cluster-Related Tumor Microenvironment Analysis: A Multi-Omics Practice in Stomach Adenocarcinoma

Luo

Zhang

et al. 2022

Front. Cell Dev. Biol.

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N6-methylandrostenedione (m6A) methylation plays a very important role in the development of malignant tumors. The immune system is the key point in the progression of tumors, particularly in terms of tumor treatment and drug resistance. Tumor immunotherapy has now become a hot spot and a new approach for tumor treatment. However, as far as the stomach adenocarcinoma (STAD) is concerned, the in-depth research is still a gap in the m6A-associated immune markers. The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases is extremely important for our research, where we obtained gene mutation, gene expression data and relevant clinical information of STAD patients. Firstly, the samples from GEO were used as external validation groups, while the TCGA samples were divided into a training group and an internal validation group randomly. Using the way of Single factor COX-LASSO- and multi-factor Cox to construct the prognostic model. Then, all samples were subjected to cluster analysis to generate high and low expression groups of immune gene. Meanwhile, we also collected the correlation between these types and tumor microenvironment. On this basis, a web version of the dynamic nomogram APP was developed. In addition, we performed microenvironmental correlation, copy number variation and mutation analyses for model genes. The prognostic model for STAD developed here demonstrated a very strong predictive ability. The results of cluster analysis manifested that the immune gene low expression group had lower survival rate and higher degree of immune infiltration. Therefore, the immune gene low expression group was associated with lower survival rates and a higher degree of immune infiltration. Gene set enrichment analysis suggested that the potential mechanism might be related to the activation of immunosuppressive functions and multiple signaling pathways. Correspondingly, the web version of the dynamic nomogram APP produced by the DynNom package has successfully achieved rapid and accurate calculation of patient survival rates. Finally, the multi-omics analysis of model genes further enriched the research content. Interference of RAB19 was confirmed to facilitate migration of STAD cells in vitro, while its overexpression inhibited these features. The prognostic model for STAD constructed in this study is accurate and efficient based on multi-omics analysis and experimental validation. Additionally, the results of the correlation analysis between the tumor microenvironment and m6Ascore are the basics of further exploration of the pathophysiological mechanism in STAD.

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“…Therefore, it is necessary to bear in mind that the molecular signature of each type of tumor is unique. Cancer is considered a heterogeneous disease, due to which it is crucial to start focusing efforts on deciphering common patterns of different tumors [ 22 , 23 ].…”

Section: Discussionmentioning

confidence: 99%

Identification of Two Exosomal miRNAs in Circulating Blood of Cancer Patients by Using Integrative Transcriptome and Network Analysis

Rincón-Riveros

Rodríguez

Villegas

et al. 2022

ncRNA

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Exosomes carry molecules of great biological and clinical interest, such as miRNAs. The contents of exosomes vary between healthy controls and cancer patients. Therefore, miRNAs and other molecules transported in exosomes are considered a potential source of diagnostic and prognostic biomarkers in cancer. Many miRNAs have been detected in recent years. Consequently, a substantial amount of miRNA-related data comparing patients and healthy individuals is available, which contributes to a better understanding of the initiation, development, malignancy, and metastasis of cancer using non-invasive sampling procedures. However, a re-analysis of available ncRNA data is rare. This study used available data about miRNAs in exosomes comparing healthy individuals and cancer patients to identify possible global changes related to the presence of cancer. A robust transcriptomic analysis identified two common miRNAs (miR-495-3p and miR-543) deregulated in five cancer datasets. They had already been implicated in different cancers but not reported in exosomes circulating in blood. The study also examined their target genes and the implications of these genes for functional processes.

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miRNAs derived from plasma small extracellular vesicles predict organo-tropic metastasis of gastric cancer

Cited by 12 publications

References 48 publications

A Method for Increasing the Robustness of Stable Feature Selection for Biomarker Discovery in Molecular Medicine Developed Using Serum Small Extracellular Vesicle Associated miRNAs and the Barrett’s Oesophagus Disease Spectrum

A Method for Increasing the Robustness of Stable Feature Selection for Biomarker Discovery in Molecular Medicine Developed Using Serum Small Extracellular Vesicle Associated miRNAs and the Barrett’s Oesophagus Disease Spectrum

Prognostic Role of M6A-Associated Immune Genes and Cluster-Related Tumor Microenvironment Analysis: A Multi-Omics Practice in Stomach Adenocarcinoma

Identification of Two Exosomal miRNAs in Circulating Blood of Cancer Patients by Using Integrative Transcriptome and Network Analysis

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