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Background <p>Early detection and treatment stratification of breast cancer remain major clinical challenges, particularly in the Middle East and North Africa (MENA) region, where population-specific circulating biomarkers are poorly defined. Circulating microRNAs (miRNAs) represent promising minimally invasive biomarkers; however, comprehensive multicenter studies in diverse MENA populations with large-scale external validation are lacking.</p> Methods <p>Plasma circulating miRNA profiling using small RNA sequencing was performed in a multi-national MENA cohort comprising 152 breast cancer patients and 376 non-cancer controls from Qatar and Jordan, including control samples from previous studies, generating expression data for 842 detectable human miRNAs. Differential expression and receiver operating characteristic (ROC) analyses were used to identify diagnostic circulating miRNA panels. Machine learning–based feature selection using penalized logistic regression (LASSO) was used to refine candidate signatures. Leveraging MENA-shortlisted miRNAs, model development was performed in the GSE211692 (675 breast cancer, 5,643 controls) dataset, and the resulting model was externally validated in an independent dataset (GSE73002: 1,280 breast cancer, 2,836 controls). Functional enrichment analyses were conducted to predict associated biological pathways, while tumor tissue expression was evaluated using the ENCORI database as supportive biological context.</p> Results <p>Panels of eight upregulated and eleven downregulated circulating miRNAs achieved strong diagnostic accuracy (AUC up to 0.91), independent of age, tumor grade, ER/HER2 status, and remained robust in sensitivity analyses accounting for control heterogeneity and sex imbalance. A five-upregulated miRNA LASSO-derived signature (hsa-let-7 g-5p, hsa-miR-138-5p, hsa-miR-142-3p, hsa-miR-24-3p, hsa-miR-32-3p) demonstrated robust performance in external datasets and showed variable cross-cancer discriminative performance. ENCORI tumor analysis showed upregulation of hsa-miR-142-3p and hsa-miR-32-3p, consistent with their increased abundance in the circulation. KEGG enrichment analyses of validated targets of upregulated miRNAs revealed pathways related to microRNAs in cancer, cell cycle regulation, and cellular senescence. A pre-treatment 14-miRNA signature distinguished patients with residual disease from those achieving pathological complete response following neoadjuvant chemotherapy (AUC = 0.95), although this finding should be considered exploratory given the limited sample size.</p> Conclusion <p>This multicenter, multi-national study supports circulating miRNAs as robust biomarkers for breast cancer detection and molecular stratification in a MENA cohort, with potential utility for treatment response prediction pending further validation in larger prospective studies, addressing a critical regional knowledge gap. These circulating miRNA signals likely reflect a combination of tumor-associated and systemic host responses.</p> Graphical Abstract <p></p>

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Minimally invasive circulating MicroRNA signatures for breast cancer detection and neoadjuvant therapy response prediction in a multicenter MENA cohort

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月8日

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  • Radhakrishnan Vishnubalaji,
  • Hikmat Abdel-Razeq,
  • Salahddin A. Gehani,
  • Maher Sughayer,
  • Hibah Shaath,
  • Remy Thomas,
  • Neyla Al Akl,
  • Artefaa Al-Shamari,
  • Gamila El Mabrok,
  • Kulsoom Junejo,
  • Renad Hamdan Mansour,
  • Abdelilah Arredouani,
  • Julie Decock,
  • Omar Albagha,
  • Nehad M. Alajez

摘要

Background

Early detection and treatment stratification of breast cancer remain major clinical challenges, particularly in the Middle East and North Africa (MENA) region, where population-specific circulating biomarkers are poorly defined. Circulating microRNAs (miRNAs) represent promising minimally invasive biomarkers; however, comprehensive multicenter studies in diverse MENA populations with large-scale external validation are lacking.

Methods

Plasma circulating miRNA profiling using small RNA sequencing was performed in a multi-national MENA cohort comprising 152 breast cancer patients and 376 non-cancer controls from Qatar and Jordan, including control samples from previous studies, generating expression data for 842 detectable human miRNAs. Differential expression and receiver operating characteristic (ROC) analyses were used to identify diagnostic circulating miRNA panels. Machine learning–based feature selection using penalized logistic regression (LASSO) was used to refine candidate signatures. Leveraging MENA-shortlisted miRNAs, model development was performed in the GSE211692 (675 breast cancer, 5,643 controls) dataset, and the resulting model was externally validated in an independent dataset (GSE73002: 1,280 breast cancer, 2,836 controls). Functional enrichment analyses were conducted to predict associated biological pathways, while tumor tissue expression was evaluated using the ENCORI database as supportive biological context.

Results

Panels of eight upregulated and eleven downregulated circulating miRNAs achieved strong diagnostic accuracy (AUC up to 0.91), independent of age, tumor grade, ER/HER2 status, and remained robust in sensitivity analyses accounting for control heterogeneity and sex imbalance. A five-upregulated miRNA LASSO-derived signature (hsa-let-7 g-5p, hsa-miR-138-5p, hsa-miR-142-3p, hsa-miR-24-3p, hsa-miR-32-3p) demonstrated robust performance in external datasets and showed variable cross-cancer discriminative performance. ENCORI tumor analysis showed upregulation of hsa-miR-142-3p and hsa-miR-32-3p, consistent with their increased abundance in the circulation. KEGG enrichment analyses of validated targets of upregulated miRNAs revealed pathways related to microRNAs in cancer, cell cycle regulation, and cellular senescence. A pre-treatment 14-miRNA signature distinguished patients with residual disease from those achieving pathological complete response following neoadjuvant chemotherapy (AUC = 0.95), although this finding should be considered exploratory given the limited sample size.

Conclusion

This multicenter, multi-national study supports circulating miRNAs as robust biomarkers for breast cancer detection and molecular stratification in a MENA cohort, with potential utility for treatment response prediction pending further validation in larger prospective studies, addressing a critical regional knowledge gap. These circulating miRNA signals likely reflect a combination of tumor-associated and systemic host responses.

Graphical Abstract