Detachable DNA Assembly Module to Dissect Tumor Cells Heterogeneity via RNA Pinpoint Screening

Differential RNA expression is becoming increasingly valuable in evaluating tumor heterogeneity for a better understanding of malignant tumors and guiding personalized therapy. However, traditional techniques for analyzing cellular RNA are mainly focused on determining the absolute level of RNA, which may lead to inaccuracies in understanding tumor heterogeneity, primarily due to i) the subtle differences in certain RNA types that have similar total concentrations and ii) the existence of variations in RNA expression across different samples. Herein, a detachable DNA assembly module is proposed that is capable not only of quantifying the expression level of target RNA but also of innovatively evaluating its proportion within its RNA family population through a sequential assembly and disassembly route. Using the let-7 family as an experimental model, a significant difference is discovered in let-7a proportion between normal mammary epithelial cells and breast cancer cells, a characteristic that is often missed in bulk analysis of traditional techniques. By combining concentration and proportion information, the detachable DNA assembly module demonstrates markedly higher efficiency in discerning among various types of cells compared to traditional techniques. This innovative assembly module is expected to offer a new perspective to highlight tumor heterogeneity and guide personalized therapy.

Authors

Institutions

Publication Details

Journal
Advanced Science
Published
2024-10-18
DOI
https://doi.org/10.1002/advs.202401253
Citations
13
Primary Topic
RNA modifications and cancer
Type
article
Field-Weighted Citation Impact
3.04

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Detachable DNA Assembly Module to Dissect Tumor Cells Heterogeneity via RNA Pinpoint Screening

Yan‐Mei Lei, Xia Yang, Chaoyong James Yang, Ruo Yuan et al.
13 citations
Advanced Science
RNA modifications and cancer
3.04
article

Detachable DNA Assembly Module to Dissect Tumor Cells Heterogeneity via RNA Pinpoint Screening

Yan‐Mei Lei, Xia Yang, Chaoyong James Yang, Ruo Yuan, Wei Liu, Ni Liao, Ying Zhuo, Wenbin Liang
article en
13 citations

Abstract

Differential RNA expression is becoming increasingly valuable in evaluating tumor heterogeneity for a better understanding of malignant tumors and guiding personalized therapy. However, traditional techniques for analyzing cellular RNA are mainly focused on determining the absolute level of RNA, which may lead to inaccuracies in understanding tumor heterogeneity, primarily due to i) the subtle differences in certain RNA types that have similar total concentrations and ii) the existence of variations in RNA expression across different samples. Herein, a detachable DNA assembly module is proposed that is capable not only of quantifying the expression level of target RNA but also of innovatively evaluating its proportion within its RNA family population through a sequential assembly and disassembly route. Using the let-7 family as an experimental model, a significant difference is discovered in let-7a proportion between normal mammary epithelial cells and breast cancer cells, a characteristic that is often missed in bulk analysis of traditional techniques. By combining concentration and proportion information, the detachable DNA assembly module demonstrates markedly higher efficiency in discerning among various types of cells compared to traditional techniques. This innovative assembly module is expected to offer a new perspective to highlight tumor heterogeneity and guide personalized therapy.

Advanced ScienceVol. 11(46)
Southwest University (CN), Shanghai Jiao Tong University (CN), Xiamen University (CN), Renji Hospital (CN), Panzhihua University (CN)
National Natural Science Foundation of China, Fundamental Research Funds for the Central Universities
Good health and well-being
Openalex Percentile: Top 8%
RNA modifications and cancer
3.04
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.