AI Article Synopsis

  • The study explores the potential of circulating microRNAs as noninvasive biomarkers for breast cancer diagnosis and prognosis, focusing on their levels before and after surgery.
  • Five microRNAs that showed significant declines post-surgery were identified, with four of them (miR-130b-5p, miR-151a-5p, miR-206, and miR-222-3p) demonstrating good diagnostic potential.
  • MiR-222-3p was particularly noteworthy as an independent factor for predicting disease-free survival, suggesting that monitoring these microRNAs could improve patient outcomes.

Article Abstract

Success in curing breast cancer largely depends on the stage at diagnosis. Circulating microRNAs are becoming a promising noninvasive biomarker. We postulate that a postoperative decline in circulating microRNAs might have diagnostic and prognostic value. Applying high-throughput microarrays, we screened the dysregulated microRNAs in paired serum samples before and after surgery. The relative concentrations of putative markers between the early breast cancer and cancer-free groups were evaluated in the training set and verified in the validation set. Sensitivity, specificity, and receiver operating characteristic (ROC) curves were used to assess diagnostic value. Survival analysis was performed using Kaplan-Meier estimates and a Cox proportional hazards model. Five microRNAs significantly reduced after surgery were selected for the training set. We found that miR-130b-5p, miR-151a-5p, miR-206, and miR-222-3p were significantly higher in the breast cancer group. Each of the four microRNAs had potential diagnostic value. The combined four microRNAs (training set: area under the curve (AUC) 0.8457; validation set: AUC 0.9309) had better diagnostic value than each single microRNA. MiR-222-3p was an independent prognostic factor for disease-free survival (HR = 13.19; 95% CI, 1.06-163.59;  = 0.045). Patients with no fewer than three highly expressed miRNAs had shorter DFS than patients with 0-2 highly expressed miRNAs (HR = 2.293; 95% CI, 1.128-0.662;  = 0.022). Our findings indicate that postoperatively downregulated circulating miR-130b-5p, miR-151a-5p, miR-206, and miR-222-3p may be potential biomarkers for breast cancer diagnosis and prognosis.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6078958PMC
http://dx.doi.org/10.1038/s41420-018-0089-7DOI Listing

Publication Analysis

Top Keywords

breast cancer
20
circulating micrornas
12
training set
12
downregulated circulating
8
diagnosis prognosis
8
early breast
8
validation set
8
mir-130b-5p mir-151a-5p
8
mir-151a-5p mir-206
8
mir-206 mir-222-3p
8

Similar Publications

No evidence that breast cancer occurs at higher rates among young Arab women.

East Mediterr Health J

December 2024

Department of Radiology, King Abdulaziz University, Jeddah, Saudi Arabia.

Article Synopsis
  • The study investigates breast cancer incidence rates among Arab women compared to women from high- and middle-income countries, focusing on age-specific data.
  • Findings reveal that young Arab women have breast cancer rates that are comparable to or lower than those in selected high- and middle-income countries, contradicting the perception of higher risk in this demographic.
  • The results suggest that the higher number of cases in Arab countries may be attributed to a younger population structure, emphasizing the need for updated breast cancer screening policies in the region.
View Article and Find Full Text PDF

In this paper, the pH-sensitive targeting functional material NGR-poly(2-ethyl-2-oxazoline)-cholesteryl methyl carbonate (NGR-PEtOz-CHMC, NPC) modified quercetin (QUE) liposomes (NPC-QUE-L) was constructed. The structure of NPC was confirmed by infrared spectroscopy (IR) and nuclear magnetic resonance hydrogen spectrum (H-NMR). Pharmacokinetic results showed that the accumulation of QUE in plasma of the NPC-QUE-L group was 1.

View Article and Find Full Text PDF

Aim: Dynamic cancer control is a current health system priority, yet methods for achieving it are lacking. This study aims to review the application of system dynamics modeling (SDM) on cancer control and evaluate the research quality.

Methods: Articles were searched in PubMed, Web of Science, and Scopus from the inception of the study to November 15th, 2023.

View Article and Find Full Text PDF

Detection of biomarkers of breast cancer incurs additional costs and tissue burden. We propose a deep learning-based algorithm (BBMIL) to predict classical biomarkers, immunotherapy-associated gene signatures, and prognosis-associated subtypes directly from hematoxylin and eosin stained histopathology images. BBMIL showed the best performance among comparative algorithms on the prediction of classical biomarkers, immunotherapy related gene signatures, and subtypes.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!