Biology subjects

Roth, S. M.

Publications and source records attributed to Roth, S. M..

3 recordsLinked to original sources

bioRxiv2023

HPV and p53 status as precision determinants of head and neck cancer response to DNA-PKcs inhibition in combination with irradiation

Major risk factors of head and neck squamous cell carcinoma (HNSCC) are tobacco use and human papillomavirus (HPV). HPV E6 oncoprotein leads to the degradation of the p53 protein, whereas HPV-negative cancers are frequently associated with TP53 mutations. Peposertib is a potent and selective, orally administered small-molecule inhibitor of the catalytic subunit of the DNA-dependent kinase (DNA-PKcs), a key regulator of non-homologous end joining (NHEJ). NHEJ inhibition along with irradiation (IR)-induced DNA double-strand breaks has the potential to increase antitumor treatment efficacy. Here, we investigated the responses of HNSCC models with distinct HPV and p53 status to treatments with IR, DNA-PKcs inhibition, and their combination. We observed that IR-induced DNA damage combined with peposertib administration shortly before IR results in decreased cell viability and proliferation and causes DNA repair delay in all the studied HNSCC cell lines. However, our data confirm that the actual cell fate upon this treatment is strongly dependent on cellular p53/HPV status. Cells lacking functional p53 due to its degradation by HPV or due to the presence of a loss-of-function mutation are arrested in the G2 phase of the cell cycle and eliminated by apoptosis whereas p53-proficient HNSCC cell lines undergo senescence. Consequently, HPV+ cancer cell lines and xenografts display stronger and more durable responses and seem to benefit from the combined treatment more than p53-proficient HNSCCs. In conclusion, DNA-PKcs inhibitor peposertib should be further studied as a potential radiosensitizer for HNSCCs, taking into consideration the genetic background and the HPV status of a particular tumor.

cancer biology↗

bioRxiv2022

Cell-free, methylated DNA in blood samples reveals tissue-specific, cellular damage from radiation treatment

Radiation therapy is an effective cancer treatment although damage to healthy tissues is common. Here we characterize the methylomes of healthy human and mouse tissues to establish sequencing-based, cell-type specific reference DNA methylation atlases. Identified cell-type specific DNA blocks were mostly hypomethylated and located within genes intrinsic to cellular identity. Cell-free DNA fragments released from dying cells into the circulation were captured from serum samples by hybridization to CpG-rich DNA panels. The origins of the circulating DNA fragments were inferred from mapping to the established DNA methylation atlases. Thoracic radiation-induced tissue damages in a mouse model were reflected by dose-dependent increases in lung endothelial, cardiomyocyte and hepatocyte methylated DNA in serum. The analysis of serum samples from breast cancer patients undergoing radiation treatment revealed distinct tissue-specific epithelial and endothelial responses to radiation across multiple organs. Strikingly, patients treated for right-sided breast cancers also showed increased hepatocyte and liver endothelial DNA in the circulation indicating the impact on liver tissues. Thus, changes in cell-free methylated DNA can uncover cell-type specific effects of radiation and provide a quantitative measure of the biologically effective radiation dose received by healthy tissues. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=174 SRC="FIGDIR/small/487966v3_ufig1.gif" ALT="Figure 1"> View larger version (46K): org.highwire.dtl.DTLVardef@129f229org.highwire.dtl.DTLVardef@d999bcorg.highwire.dtl.DTLVardef@1fc3543org.highwire.dtl.DTLVardef@10cebc2_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2019

Predicting suitability of regions for Zika outbreaks with zero-inflated models trained using climate data

In recent years, Zika spread through the Americas. This virus has been linked to Guillain-Barre syndrome, which can lead to paralysis, and microcephaly, a severe birth defect. Zika is primarily transmitted by Aedes (Ae.) aegypti, a mosquito whose geographic range has expanded and is anticipated to continue shifting as the climate changes.\n\nWe used statistical models to predict regional suitability for autochthonous Zika transmission using climatic variables. By suitability for Zika, we mean the potential for an outbreak to occur based on the climates habitability for Ae. aegypti. We trained zero-inflated Poisson (ZIP) and zero-inflated negative binomial (ZINB) regression models to predict Zika outbreak suitability using 20 subsets of climate variables for 102 regions. Variable subsets were selected for the final models based on importance to Ae. aegypti survival and their performance in aiding prediction of Zika-suitable regions. We determined the two best models to both be ZINB models. The best models regressors were winter mean temperature, yearly minimum temperature, and population, and the second-best models regressors were winter mean temperature and population.\n\nThese two models were then run on bias-corrected climate projections to predict future climate suitability for Zika, and they generated reasonable predictions. The predictions find that most of the sampled regions are expected to become more suitable for Zika outbreaks. The regions with the greatest risk have increasingly mild winters and high human populations. These predictions are based on the most extreme scenario for climate change, which we are currently on track for.\n\nAuthor SummaryIn recent years, Zika spread through the Americas. This virus has been linked to Guillain-Barre syndrome, which can lead to paralysis, and microcephaly, a severe birth defect. Zika is primarily transmitted by Aedes (Ae.) aegypti, a mosquito whose geographic range has expanded and is anticipated to continue shifting as the climate changes. We used statistical models to predict regional suitability for locally-acquired Zika cases using climatic variables. By suitability for Zika, we mean the potential for an outbreak to occur based on the climates habitability for Ae. aegypti. We trained statistical models to predict Zika outbreak suitability using 20 subsets of climate variables for 102 regions. Variable subsets were selected for the final two models based on importance to Ae. aegypti survival and their performance in aiding prediction of Zika-suitable regions. These two models were then run on climate projections to predict future climate suitability for Zika, and they generated reasonable predictions. The predictions find that most of the sampled regions are expected to become more suitable for Zika outbreaks. The regions with the greatest risk have high human populations and increasingly mild winters.

ecology↗