Breast cancer is a highly heterogeneous disease. The efficacy of tailored therapeutic strategies relies on the precise detection of diagnostic biomarkers by immunohistochemistry (IHC). Therefore, considering the increasing incidence of breast cancer cases, a concomitantly time-efficient and accurate diagnosis is clinically highly relevant. Microfluidics is a promising innovative technology in the field of tissue diagnostic, enabling for rapid, reliable, and automated immunostaining. We previously reported the microfluidic-based HER2 (human epidermal growth factor receptor 2) detection in breast carcinomas to greatly correlate with the HER2 gene amplification level. Here, we aimed to develop a panel of microfluidic-based IHC protocols for prognostic and therapeutic markers routinely assessed for breast cancer diagnosis, namely HER2, estrogen/progesterone receptor (ER/PR), and Ki67 proliferation factor. The microfluidic IHC protocol for each marker was optimized to reach high staining quality comparable to the standard procedure, while concomitantly shortening the staining time to 16 min-excluding deparaffinization and antigen retrieval step-with a turnaround time reduction up to 7 folds. Comparison of the diagnostic score on 50 formaldehyde-fixed paraffin-embedded breast tumor resections by microfluidic versus standard staining showed high concordance (overall agreement: HER2 94%, ER 95.9%, PR 93.6%, Ki67 93.7%) and strong correlation (ρ coefficient: ER 0.89, PR 0.88, Ki67 0.87; p < 0.0001) for all the analyzed markers. Importantly, HER2 genetic reflex test for all discordant cases confirmed the scores obtained by the microfluidic technique. Overall, the microfluidic-based IHC represents a clinically validated equivalent approach to the standard chromogenic staining for rapid, accurate, and automated breast cancer diagnosis.
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http://dx.doi.org/10.1007/s00428-019-02616-7 | DOI Listing |
Pharm Dev Technol
January 2025
Department of Pharmacy, School of Chemistry and Chemical Engineering, Liaoning Normal University, Dalian 116029, China.
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 PDFJ Med Econ
January 2025
UNESCO-TWAS, The World Academy of Sciences, Trieste, Italy.
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.
Int J Surg
January 2025
Computer Science and Technology, Harbin Institute of Technology (Shenzhen), Shenzhen, China.
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 PDFInt J Gen Med
December 2024
Department of Thyroid and Breast Surgery, Quzhou People's Hospital, Quzhou, 324000, People's Republic of China.
Objective: This study aims to demonstrate the impact of sarcopenia on the prognosis of early breast cancer and its role in early multimodal intervention.
Methods: The clinical data of patients (n=285) subjected to chemotherapy for early-stage breast cancer diagnosed pathologically between January 1, 2016, and December 31, 2020, in our hospital were retrospectively analyzed. Accordingly, the recruited subjects were divided into sarcopenia (n=85) and non-sarcopenia (n=200) groups according to CT diagnosis correlating with single-factor and multifactorial logistic regression analyses.
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