Plasma Extracellular Vesicle Long RNAs Have Potential as Biomarkers in Early Detection of Colorectal Cancer

Guo, Tong; Lai, Hongyan; Liu, Cong; Yan, Li; Li, Yuchen; Jin, Y.; Zhang, Zhao-Zhen; Huang, Haobo; Huang, Shenglin; Xu, Ye

doi:10.3389/fonc.2022.829230

Cited by 9 publications

(1 citation statement)

References 49 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Speci c miRNA candidates such as miR-21, miR-23a, miR-1246, and miR-92a have been suggested as potential diagnostic markers 39 . Furthermore, a signature based on long RNAs within plasma-derived sEVs has demonstrated promise in discerning CRC patients from healthy counterparts 40 . Notably, Zhang et al 38 observed signi cantly elevated levels of CD147 and A33 on SEVs isolated from fecal samples of CRC patients, facilitating the discrimination between CRC patients and healthy individuals.…”

Section: Discussionmentioning

confidence: 99%

Characterization and proteomic analysis of plasma-derived small extracellular vesicles in locally advanced rectal cancer patients

Chen,

Fang,

Dai

et al. 2024

Preprint

View full text Add to dashboard Cite

Background Neoadjuvant chemoradiotherapy (nCRT) stands as a pivotal therapeutic approach for locally advanced rectal cancer (LARC), yet the absence of a reliable biomarker to forecast its efficacy remains a challenge. Thus, this study aimed to assess whether the proteomic compositions of small extracellular vesicles (sEVs) might offer predictive insights into nCRT response among patients with LARC, while also delving into the proteomic alterations within sEVs post nCRT. Methods Plasma samples were obtained from LARC patients both pre- and post-nCRT. Plasma-derived sEVs were isolated utilizing the TIO2-based method, followed by LC-MS/MS-based proteomic analysis. Subsequently, pathway enrichment analysis were performed to the Differentially Expressed Proteins (DEPs). Additionally, ROC curves were generated to evaluate the predictive potential of sEV proteins in determining nCRT response. Public databases were interrogated to identify sEV protein-associated genes that are correlated with the response to nCRT in LARC. Results A total of 16 patients were enrolled. Among them, 8 patients achieved a pathological complete response (good responders, GR), while the remaining 8 did not achieve a complete response (poor responders, PR). Our analysis of pretreatment plasma-derived sEVs revealed 67 significantly up-regulated DEPs and 9 significantly down-regulated DEPs. Notably, PROC (AUC: 0.922), F7 (AUC: 0.953) and AZU1 (AUC: 0.906) demonstrated high AUC values and significant differences (P value < 0.05) in discriminating between GR and PR patients. Furthermore, a signature consisting of 5 sEV protein-associated genes (S100A6, ENO1, MIF, PRDX6 and MYL6) was capable of predicting the response to nCRT, yielding an AUC of 0.621(95% CI: 0.454–0.788). Besides, this 5-sEV protein-associated gene signature enabled stratification of patients into low- and high-risk group, with the low-risk group demonstrating a longer overall survival in the testing set (P = 0.048). Moreover, our investigation identified 11 significantly up-regulated DEPs and 31 significantly down-regulated DEPs when comparing pre- and post-nCRT proteomic profiles. GO analysis unveiled enrichment in the regulation of phospholipase A2 activity. Conclusions Differential expression of sEV proteins distinguishes between GR and PR patients and holds promise as predictive markers for nCRT response and prognosis in patients with LARC. Furthermore, our findings highlight substantial alterations in sEV protein composition following nCRT.

show abstract

Section: Discussionmentioning

confidence: 99%

Characterization and proteomic analysis of plasma-derived small extracellular vesicles in locally advanced rectal cancer patients

Chen,

Fang,

Dai

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

StructmRNA a BERT based model with dual level and conditional masking for mRNA representation

Nahali,

Safari,

Khanteymoori

et al. 2024

Sci Rep

View full text Add to dashboard Cite

In this study, we introduce StructmRNA, a new BERT-based model that was designed for the detailed analysis of mRNA sequences and structures. The success of DNABERT in understanding the intricate language of non-coding DNA with bidirectional encoder representations is extended to mRNA with StructmRNA. This new model uses a special dual-level masking technique that covers both sequence and structure, along with conditional masking. This enables StructmRNA to adeptly generate meaningful embeddings for mRNA sequences, even in the absence of explicit structural data, by capitalizing on the intricate sequence-structure correlations learned during extensive pre-training on vast datasets. Compared to well-known models like those in the Stanford OpenVaccine project, StructmRNA performs better in important tasks such as predicting RNA degradation. Thus, StructmRNA can inform better RNA-based treatments by predicting the secondary structures and biological functions of unseen mRNA sequences. The proficiency of this model is further confirmed by rigorous evaluations, revealing its unprecedented ability to generalize across various organisms and conditions, thereby marking a significant advance in the predictive analysis of mRNA for therapeutic design. With this work, we aim to set a new standard for mRNA analysis, contributing to the broader field of genomics and therapeutic development.

show abstract

Predicting high sensitivity C-reactive protein levels and their associations in a large population using decision tree and linear regression

Ghiasi Hafezi,

Sahranavard,

Kooshki

et al. 2024

Sci Rep

View full text Add to dashboard Cite

Plasma Extracellular Vesicle Long RNAs Have Potential as Biomarkers in Early Detection of Colorectal Cancer

Cited by 9 publications

References 49 publications

Characterization and proteomic analysis of plasma-derived small extracellular vesicles in locally advanced rectal cancer patients

Characterization and proteomic analysis of plasma-derived small extracellular vesicles in locally advanced rectal cancer patients

StructmRNA a BERT based model with dual level and conditional masking for mRNA representation

Predicting high sensitivity C-reactive protein levels and their associations in a large population using decision tree and linear regression

Contact Info

Product

Resources

About