Abstract 83: Point-of-Care Technologies for Molecular Subtyping of Breast Cancer in Low- and Middle-Income Countries

Abstract Purpose: Breast cancer, the most common malignancy among women globally, demands precise molecular subtyping to guide effective treatment. However, in low- and middle-income countries (LMICs), limited access to diagnostic resources hinders timely interventions. We developed a triplex lateral flow immunoassay (LFIA) capable of simultaneously quantifying progesterone receptor (PR), estrogen receptor (ER), and human epidermal growth factor receptor 2 (HER2) to address these diagnostic challenges with a portable and cost-effective solution. Methods: The triplex LFIA incorporates europium-streptavidin fluorescence for enhanced sensitivity and specificity, coupled with an incubation pad to improve antigen-antibody interactions. Detection limits of PR, ER, and HER2 were established as 32 pM, 76 pM, and 25 pM, respectively. Comparative analysis with enzyme-linked immunosorbent assay (ELISA) validated the assay’s accuracy and clinical utility. A Portable Rapid Onsite Versatile Image-based Detection System (PROVIDS) was developed for real-time quantitative biomarker analysis. Results: The LFIA demonstrated high sensitivity, specificity (cross-reactivity <5%), and strong correlation with ELISA (R2 > 0.95). The platform’s performance aligns with clinical thresholds, distinguishing breast cancer subtypes across biomarker profiles. PROVIDS-enabled analysis ensures quantitative readouts, achieving point-of-care compatibility. While its laboratory performance is promising, further field validation is required to assess its operational impact in LMICs. Conclusion: The triplex LFIA represents a significant step toward accessible molecular subtyping in resource-limited settings. With its innovative design and promising laboratory performance, this platform holds potential to address diagnostic disparities in LMICs and improve timely breast cancer care upon further validation. Citation Format: Wenting Gao, Iftak Hussain, Thea Nikolaou, Clement Adebamowo, David Erickson. Point-of-Care Technologies for Molecular Subtyping of Breast Cancer in Low- and Middle-Income Countries [abstract]. In: Proceedings of the 13th Annual Symposium on Global Cancer Research; 2025 Sep 16. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2025;34(12_Suppl):Abstract nr 83.

Authors

Institutions

Publication Details

Journal
Cancer Epidemiology Biomarkers & Prevention
Published
2025-12-01
DOI
https://doi.org/10.1158/1538-7755.asgcr25-abstract-83
Primary Topic
Biosensors and Analytical Detection
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Abstract 83: Point-of-Care Technologies for Molecular Subtyping of Breast Cancer in Low- and Middle-Income Countries

David Erickson, Iftak Hussain, Sally N. Adebamowo, Wenting Gao et al.
Cancer Epidemiology Biomarkers & Prevention
Biosensors and Analytical Detection
article

Abstract 83: Point-of-Care Technologies for Molecular Subtyping of Breast Cancer in Low- and Middle-Income Countries

David Erickson, Iftak Hussain, Sally N. Adebamowo, Wenting Gao, Thea Nikolaou
article en

Abstract

Abstract Purpose: Breast cancer, the most common malignancy among women globally, demands precise molecular subtyping to guide effective treatment. However, in low- and middle-income countries (LMICs), limited access to diagnostic resources hinders timely interventions. We developed a triplex lateral flow immunoassay (LFIA) capable of simultaneously quantifying progesterone receptor (PR), estrogen receptor (ER), and human epidermal growth factor receptor 2 (HER2) to address these diagnostic challenges with a portable and cost-effective solution. Methods: The triplex LFIA incorporates europium-streptavidin fluorescence for enhanced sensitivity and specificity, coupled with an incubation pad to improve antigen-antibody interactions. Detection limits of PR, ER, and HER2 were established as 32 pM, 76 pM, and 25 pM, respectively. Comparative analysis with enzyme-linked immunosorbent assay (ELISA) validated the assay’s accuracy and clinical utility. A Portable Rapid Onsite Versatile Image-based Detection System (PROVIDS) was developed for real-time quantitative biomarker analysis. Results: The LFIA demonstrated high sensitivity, specificity (cross-reactivity <5%), and strong correlation with ELISA (R2 > 0.95). The platform’s performance aligns with clinical thresholds, distinguishing breast cancer subtypes across biomarker profiles. PROVIDS-enabled analysis ensures quantitative readouts, achieving point-of-care compatibility. While its laboratory performance is promising, further field validation is required to assess its operational impact in LMICs. Conclusion: The triplex LFIA represents a significant step toward accessible molecular subtyping in resource-limited settings. With its innovative design and promising laboratory performance, this platform holds potential to address diagnostic disparities in LMICs and improve timely breast cancer care upon further validation. Citation Format: Wenting Gao, Iftak Hussain, Thea Nikolaou, Clement Adebamowo, David Erickson. Point-of-Care Technologies for Molecular Subtyping of Breast Cancer in Low- and Middle-Income Countries [abstract]. In: Proceedings of the 13th Annual Symposium on Global Cancer Research; 2025 Sep 16. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2025;34(12_Suppl):Abstract nr 83.

Cancer Epidemiology Biomarkers & PreventionVol. 34(12_Supplement)
University of Maryland, Baltimore (US), Cornell University (US)
Openalex Percentile: Top 63%
Biosensors and Analytical Detection
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.