Biology subjects

Nielsen, G.

Publications and source records attributed to Nielsen, G..

3 recordsLinked to original sources

bioRxiv2025

Quantification of HER2-low and ultra-low expression in breast cancer specimens by quantitative IHC and artificial intelligence

Recent results of clinical trials in antibody drug conjugate therapies have significantly broadened treatment options for the HER2 low and ultra-low breast cancer patients. However, sensitive, accurate and quantitative evaluation of HER2 expression based on current immunohistochemistry (IHC) assays remain challenging, especially in low and ultra-low HER2 expression ranges. We developed a novel methodology for quantifying HER2 protein expression, targeting breast cancer cases in the HER2 IHC 0 and 1+ categories. We measured HER2 expression using quantitative IHC (qIHC) that enables precise and tunable HER2 detection across different expression levels as demonstrated in formalin-fixed paraffin-embedded cell lines. Additionally, we developed an AI-based interpretation of HercepTest mAb pharmDx (Dako Omnis) (HercepTest mAb) using qIHC measurements as the ground truth. Both methodologies allowed spatial resolution and visualization of low and ultra-low levels of HER2 expression across entire tissue sections to demonstrate and enable quantification of heterogeneity of HER2 expression. Serial sections of 82 formalin-fixed paraffin-embedded tissue blocks of invasive breast carcinoma with HER2 IHC scores 0 or 1+ were stained with H&E, HercepTest (mAb), qIHC and p63, then scanned and digitally aligned. Tumor areas were manually selected and reviewed by expert pathologists. HER2 expression was quantitatively evaluated based on the qIHC assay in each 128x128{micro}m2 area within tumor regions. We observed statistically significant differences in HER2 expression between IHC 0, 0<IHC<1+, and IHC 1+ groups, and high degree of spatial heterogeneity of the HER2 expression levels within the same tissue, up to five-fold in some cases. We demonstrated high slide-level tumor region agreement of estimates of HER2 expression between the AI-based interpretation of HercepTest mAb and the qIHC ground truth with a Pearson correlation of 0.94, and R2 of 0.87. The developed methodologies can be used to stratify HER2 low-expression patient groups, potentially improving the interpretation of IHC assays and maximizing therapeutic benefits. This method can be implemented in histology labs without requiring a specialized workflow.

pathology↗

bioRxiv2021

Predicting the Effects of Per- and Polyfluoroalkyl Substance Mixtures on Peroxisome Proliferator-Activated Receptor Alpha Activity in Vitro

Human exposure to per- and polyfluoroalkyl substances (PFAS) is ubiquitous, with mixtures of PFAS detected in drinking water, food, household dust, and other exposure sources. Animal toxicity studies and human epidemiology indicate that PFAS may act through shared mechanisms including activation of peroxisome proliferator activated receptor (PPAR). However, the effect of PFAS mixtures on human relevant molecular initiating events remains an important data gap in the PFAS literature. Here, we tested the ability of modeling approaches to predict the effect of diverse PPAR ligands on receptor activity using Cos7 cells transiently transfected with a full length human PPAR (hPPAR) expression construct and a peroxisome proliferator response element-driven luciferase reporter. Cells were treated for 24 hours with two full hPPAR agonists (pemafibrate and GW7647), a full and a partial hPPAR agonist (pemafibrate and mono(2-ethylhexyl) phthalate), or a full hPPAR agonist and a competitive antagonist (pemafibrate and GW6471). Receptor activity was modeled with three additive approaches: effect summation, relative potency factors (RPF), and generalized concentration addition (GCA). While RPF and GCA accurately predicted activity for mixtures of full hPPAR agonists, only GCA predicted activity for full and partial hPPAR agonists and a full agonist and antagonist. We then generated concentration response curves for seven PFAS, which were well-fit with three-parameter Hill functions. The four perfluorinated carboxylic acids (PFCA) tended to act as full hPPAR agonists while the three perfluorinated sulfonic acids (PFSA) tended to act as partial agonists that varied in efficacy between 28-67% of the full agonist, positive control level. GCA and RPF performed equally well at predicting the effects of mixtures with three PFCAs, but only GCA predicted experimental activity with mixtures of PFSAs and a mixture of PFCAs and PFSAs at ratios found in the general population. We conclude that of the three approaches, GCA most accurately models the effect of PFAS mixtures on hPPAR activity in vitro. HighlightsO_LIPerfluorinated carboxylic acids are full human PPAR agonists C_LIO_LIPerfluorinated sulfonic acids are partial human PPAR agonists C_LIO_LIGCA predicts human PPAR activity for mixtures of full and partial agonists C_LIO_LIGCA predicts human PPAR activity for mixtures of agonists and competitive antagonists C_LIO_LIGCA accurately predicts human PPAR activity in response to PFAS mixtures C_LI

pharmacology and toxicology↗

bioRxiv2020

Perfluorooctanoic acid activates multiple nuclear receptor pathways and skews expression of genes regulating cholesterol homeostasis in liver of humanized PPARα mice fed an American diet

Humans are exposed to per- and polyfluoroalkyl substances (PFAS) in their drinking water, food, air, dust in their homes, and by direct use of consumer products. Increased concentrations of serum total cholesterol and low density lipoprotein cholesterol are among the endpoints best supported by epidemiology. The objectives of this study were to generate a new model for examining PFAS-induced dyslipidemia and to conduct molecular studies to better define mechanism(s) of action. We tested the hypothesis that PFOA exposure at a human-relevant level dysregulates expression of genes controlling cholesterol homeostasis in livers of mice expressing human PPAR (hPPAR). Female and male hPPAR and PPAR null mice were fed a diet based on the "What we eat in America" analysis and exposed to perfluorooctanoic acid (PFOA) in drinking water (8 {micro}M) for 6 weeks. This resulted in a serum PFOA concentration of 48 g/ml. PFOA increased liver mass, which was associated with histologically-evident lipid accumulation. PFOA induced PPAR and constitutive androstane receptor target gene expression in liver. Expression of genes in four pathways regulating cholesterol homeostasis were also measured. PFOA decreased expression of Hmgcr in a PPAR-dependent manner. PFOA decreased expression of Ldlr and Cyp7a1 in a PPAR-independent manner. Apob expression was not changed. Gene expression in females appeared to be more sensitive to PFOA exposure than in males. This novel study design (hPPAR mice, American diet, long term exposure) generated new insight on the effects of PFOA on cholesterol regulation in the liver and the role of hPPAR.

pharmacology and toxicology↗