Biology subjects

Szczepanek, K.

Publications and source records attributed to Szczepanek, K..

4 recordsLinked to original sources

bioRxiv2025

Investigating the genomic landscape of mouse models of breast cancer metastasis

Metastasis remains a major cause of cancer mortality. AbstractThis study, expanding upon previous findings in the MMTV-PyMT model, investigated four independent mouse models, representing luminal (MMTV-PyMT, MMTV-Myc), HER2-amplified (MMTV-Her2) and triple negative (C3(1)TAg) breast cancer subtypes. Consistent with previous results, limited evidence for metastasis-associated somatic point mutations was found for all models. We also found that oncogenic drivers significantly influenced the number and size of metastasis-specific copy number variations (MSCNVs), but common driver-independent MSCNVs were rare. Furthermore, analyzing a cohort with varying genetic backgrounds while maintaining a constant oncogenic driver (PyMT) revealed that genetic background profoundly impacts MSCNVs. Transcriptome analysis demonstrated that oncogenic drivers strongly shaped metastasis-specific gene expression (MSGE), with each driver exhibiting distinct expression profiles. In contrast, MSGE in the PyMT-F1 cohort was more variable across strains. Despite the diversity of MSCNV and MSGE, functional analysis revealed that both mechanisms converge on the modulation of key cellular processes, including immune responses, metabolism, and extracellular matrix interactions. These findings emphasize the complex interplay between oncogenic drivers and genetic background in shaping the genomic and transcriptional landscapes of metastatic lesions.

cancer biology↗

bioRxiv2019

Metastasis-specific gene expression in autochthonous and allograft mouse mammary tumor models: stratificationand identification of targetable signatures

Breast cancer is a leading cause of cancer-related death of women in the U.S., which is ultimately due to metastasis rather than primary tumor burden. Therefore, increased understanding of metastasis to develop novel therapies is critical in reducing breast cancer-related mortality. Indeed, a major hurdle in advancing metastasis-targeted intervention is the genotypic and phenotypic heterogeneity that exists between primary and secondary lesions. To identify targetable metastasis-specific gene expression profiles we performed RNA sequencing of breast cancer metastasis mouse models. We analyzed metastases from models of various oncogenic drivers and routes, including orthotopic injection, tail vein injection, intracardiac injection, and genetically engineered mouse models (GEMMs). Herein, we analyzed samples from 176 mice and tissue culture samples, resulting in 338 samples total. Using these data, we contrasted the different breast cancer metastasis models, and also identified common, targetable metastasis specific gene expression signatures. Principal component analysis revealed that mouse model (Allograft v. GEMM) rather than tissue source (PT v metastatic nodule) shaped the transcriptomes of our samples. Allograft models exhibited more mesenchymal-like gene expression than GEMM models, and primary culturing of GEMM-derived metastatic tissue induced more mesenchymal-like gene expression. Furthermore, metastasis-specific gene expression differed between tail vein and orthotopic injection models of the same cell line, the degree of which was cell line dependent. Finally, we examined metastasis-specific gene expression common to models of spontaneous metastasis (orthotopic injection and GEMMs). Pathway analysis identified upregulation of the sildenafil response, and nicotine degradation pathways. The influence of these pathways on metastatic spread was assessed by treatment of allograft models with clinically relevant dosing of sildenafil or nicotine. Sildenafil significantly reduced pulmonary metastasis while nicotine administration significantly increased metastasis, and neither regimen altered primary tumor mass. Taken together our data reveals critical differences between pre-clinical models of metastatic breast cancer. Additionally, this strategy has identified clinically targetable metastasis-specific pathways integral to metastatic spread.

cancer biology↗

bioRxiv2019

The genomic landscape of metastasis in treatment-naive breast cancer models

Metastasis remains the principle cause of mortality for breast cancer and presents a critical challenge because secondary lesions are often refractory to conventional treatments. While specific genetic alterations are tightly linked to primary tumour development and progression, the role of genetic alteration in the metastatic process is not well-understood. To investigate how somatic evolution might contribute to breast cancer metastasis, we performed exome, whole genome, and RNA sequencing of matched metastatic and primary tumours from pre-clinical mouse models of breast cancer. Here we show that in a treatment-naive setting, recurrent single nucleotide variants and copy number variation, but not gene fusion events, play key metastasis-driving roles in breast cancer. For instance, we identified recurrent mutations in Kras, a known driver of tumorigenesis that has not been previously implicated in breast cancer metastasis. The strategy presented here represents a novel framework to identify actionable metastasis-targeted therapies.

cancer biology↗

bioRxiv2018

Integrated sequence and gene expression analysis of mouse models of breast cancer reveals critical events with human parallels

Mouse models have an essential role in cancer research, yet little is known about how various models resemble human cancer at a genomic level. However, the shared genomic alterations in each model and corresponding human cancer are critical for translating findings in mice to the clinic. We have completed whole genome sequencing and transcriptome profiling of two widely used mouse models of breast cancer, MMTV-Neu and MMTV-PyMT. This genomic information was integrated with phenotypic data and CRISPR/Cas9 studies to understand the impact of key events on tumor biology. Despite the engineered initiating transgenic event in these mouse models, they contain similar copy number alterations, single nucleotide variants, and translocation events as human breast cancer. Through integrative in vitro and in vivo studies, we identified copy number alterations in key extracellular matrix proteins including Collagen 1 Type 1 alpha 1 (Col1a1) and Chondroadherin (CHAD) that drive metastasis in these mouse models. Importantly this amplification is also found in 25% of HER2+ human breast cancer and is associated with increased metastasis. In addition to copy number alterations, we observed a propensity of the tumors to modulate tyrosine kinase mediated signaling through mutation of phosphatases. Specifically, we found that 81% of MMTV-PyMT tumors have a mutation in the EGFR regulatory phosphatase, PTPRH. Mutation in PTPRH led to increased phospho-EGFR levels and decreased latency. Moreover, PTPRH mutations increased response to EGFR kinase inhibitors. Analogous PTPRH mutations are present in lung cancer patients and together this data suggests that a previously unidentified population of human lung cancer patients may respond to EGFR targeted therapy. These findings underscore the importance of understanding the complete genomic landscape of a mouse model and illustrate the utility this has in understanding human cancers.

cancer biology↗