Biology subjects

Ben-David, O.

Publications and source records attributed to Ben-David, O..

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↗

bioRxiv2019

Unexpected implications of STAT3 acetylation revealed by genetic encoding of acetyl-lysine

The signal transducer and activator of transcription 3 (STAT3) protein is activated by phosphorylation of a specific tyrosine residue (Tyr705) in response to various extracellular signals. STAT3 activity was also found to be regulated by acetylation of Lys685. However, the molecular mechanism by which Lys685 acetylation affects the transcriptional activity of STAT3 remains elusive. By genetically encoding the co-translational incorporation of acetyl-lysine into position Lys685 and co-expression with the Elk receptor tyrosine kinase, we were able to biochemically characterize site-specifically acetylated, and simultaneously acetylated and phosphorylated STAT3. We measured the effect of acetylation on the crystal structure, and DNA binding affinity and specificity of Tyr705-phosphorylated and non-phosphorylated STAT3. In addition, we monitored the deacetylation of acetylated Lys685 by reconstituting the mammalian enzymatic deacetylation reaction in live bacteria. Surprisingly, we found that acetylation, per se, had no effect on the crystal structure, and DNA binding affinity or specificity of STAT3, implying that the previously observed acetylation-dependent transcriptional activity of STAT3 involves an additional cellular component. In addition, we discovered that Tyr705-phosphorylation protects Lys685 from deacetylation in bacteria, providing a new possible explanation for the observed correlation between STAT3 activity and Lys685 acetylation.

biochemistry↗

bioRxiv2017

Reducing Pyrrolysine tRNA Copy Number Improves the Performance of Genetic Code Expansion in Live Cell Imaging of Bioorthogonally Labeled Proteins

Genetic code expansion enables the incorporation of non-canonical amino acids (ncAAs) into expressed proteins. ncAAs are usually encoded by a stop codon that is decoded by an exogenous orthogonal aminoacyl tRNA synthetase and its cognate suppressor tRNA, such as the pyrrolysine synthetase/[Formula] pair. In such systems, stop codon suppression is dependent on the intracellular levels of the exogenous tRNA. Therefore, multiple copies of the tRNAPyl gene (PylT) are encoded to improve ncAA incorporation. However, certain applications in mammalian cells, such as live-cell imaging applications, where labelled tRNA contributes to background fluorescence, can benefit from the use of less invasive minimal expression systems. Accordingly, we studied the effect of tRNAPyl on live-cell fluorescence imaging of bioorthogonally-labelled intracellular proteins. We found that in COS7 cells, a decrease in PylT copy numbers had no measurable effect on protein expression levels. Importantly, reducing PylT copy numbers improved the quality of live-cells images by enhancing the signal-to-noise ratio and reducing an immobile tRNAPyl population. This enabled us to improve live cell imaging of bioorthogonally labelled intracellular proteins, and to simultaneously label two different proteins in a cell. Our results indicate that the number of introduced PylT genes can be minimized according to the transfected cell line, incorporated ncAA, and application.

synthetic biology↗