Optimization of tumor-treating field therapy for triple-negative breast cancer cells in vitro via frequency modulation.

PURPOSE: Currently, tumor-treating field (TTField) therapy utilizes a single "optimal" frequency of electric fields to achieve maximal cell death in a targeted population of cells. However, because of differences in cell size, shape, and ploidy during mitosis, optimal electric field characteristics for universal maximal cell death may not exist. This study investigated the anti-mitotic effects of modulating electric field frequency as opposed to utilizing uniform electric fields. METHODS: We developed and validated a custom device that delivers a wide variety of electric field and treatment parameters including frequency modulation. We investigated the efficacy of frequency modulating tumor-treating fields on triple-negative breast cancer cells compared to human breast epithelial cells. RESULTS: We show that frequency-modulated (FM) TTFields are as selective at treating triple-negative breast cancer (TNBC) as uniform TTFields while having a greater efficacy for combating TNBC cell growth. TTField treatment at a mean frequency of 150 kHz with a frequency range of ± 10 kHz induced apoptosis in a greater number of TNBC cells after 24 h as compared to unmodulated treatment which led to further decreased cell viability after 48 h. Furthermore, all TNBC cells died after 72 h of FM treatment while cells that received unmodulated treatment were able to recover to cell number equivalent to the control. CONCLUSION: TTFields were highly efficacious against TNBC growth, FM TTFields showed minimal effects on epithelial cells similar to unmodulated treatment.

Efficacy and selectivity of tumor-treating field therapy for triple-negative breast cancer cells via in-house delivery device.

PURPOSE: Triple-negative breast cancer continues to be one of the leading causes of death in women, making up 7% of all cancer deaths. Tumor-treating electric fields are low-energy, low-frequency oscillating electric fields that induce an anti-proliferative effect on mitotic cells in glioblastoma multiforme, non-small cell lung cancer, and ovarian cancer. Little is known about effects of tumor-treating fields on triple-negative breast cancer and known research for tumor-treating fields only utilizes low (< 3 V/cm) electric field intensities. METHODS: We have developed an in-house field delivery device capable of high levels of customization to explore a much wider variety of electric field and treatment parameters. Furthermore, we investigated the selectivity of tumor-treating field treatment between triple-negative breast cancer and human breast epithelial cells. RESULTS: Tumor-treating fields show greatest efficacy against triple-negative breast cancer cell lines between 1 and 3 V/cm electric field intensities while having little effect on epithelial cells. CONCLUSION: These results provide a clear therapeutic window for tumor-treating field delivery to triple-negative breast cancer.

Identifying SARS-CoV-2 Variants of Concern through Saliva-Based RT-qPCR by Targeting Recurrent Mutation Sites.

SARS-CoV-2 variants of concern (VOCs) continue to pose a public health threat which necessitates a real-time monitoring strategy to complement whole genome sequencing. Thus, we investigated the efficacy of competitive probe RT-qPCR assays for six mutation sites identified in SARS-CoV-2 VOCs and, after validating the assays with synthetic RNA, performed these assays on positive saliva samples. When compared with whole genome sequence results, the SΔ69-70 and ORF1aΔ3675-3677 assays demonstrated 93.60 and 68.00% accuracy, respectively. The SNP assays (K417T, E484K, E484Q, L452R) demonstrated 99.20, 96.40, 99.60, and 96.80% accuracies, respectively. Lastly, we screened 345 positive saliva samples from 7 to 22 December 2021 using Omicron-specific mutation assays and were able to quickly identify rapid spread of Omicron in Upstate South Carolina. Our workflow demonstrates a novel approach for low-cost, real-time population screening of VOCs. IMPORTANCE SARS-CoV-2 variants of concern and their many sublineages can be characterized by mutations present within their genetic sequences. These mutations can provide selective advantages such as increased transmissibility and antibody evasion, which influences public health recommendations such as mask mandates, quarantine requirements, and treatment regimens. Our RT-qPCR workflow allows for strain identification of SARS-CoV-2 positive saliva samples by targeting common mutation sites shared between variants of concern and detecting single nucleotides present at the targeted location. This differential diagnostic system can quickly and effectively identify a wide array of SARS-CoV-2 strains, which can provide more informed public health surveillance strategies in the future.

Identifying SARS-CoV-2 Variants of Concern through saliva-based RT-qPCR by targeting recurrent mutation sites.

SARS-CoV-2 variants of concern (VOCs) continue to pose a public health threat which necessitates a real-time monitoring strategy to compliment whole genome sequencing. Thus, we investigated the efficacy of competitive probe RT-qPCR assays for six mutation sites identified in SARS-CoV-2 VOCs and, after validating the assays with synthetic RNA, performed these assays on positive saliva samples. When compared with whole genome sequence results, the SΔ69-70 and ORF1aΔ3675-3677 assays demonstrated 93.60% and 68.00% accuracy, respectively. The SNP assays (K417T, E484K, E484Q, L452R) demonstrated 99.20%, 96.40%, 99.60%, and 96.80% accuracies, respectively. Lastly, we screened 345 positive saliva samples from December 7-22, 2021 using Omicron-specific mutation assays and were able to quickly identify rapid spread of Omicron in Upstate South Carolina. Our workflow demonstrates a novel approach for low-cost, real-time population screening of VOCs. Importance: SARS-CoV-2 variants of concern and their many sublineages can be characterized by mutations present within their genetic sequences. These mutations can provide selective advantages such as increased transmissibility and antibody evasion, which influences public health recommendations such as mask mandates, quarantine requirements, and treatment regimens. Our real-time RT-qPCR workflow allows for strain identification of SARS-CoV-2 positive saliva samples by targeting common mutation sites shared between VOCs and detecting single nucleotides present at the targeted location. This differential diagnostic system can quickly and effectively identify a wide array of SARS-CoV-2 strains, which can provide more informed public health surveillance strategies in the future.

Efficient SARS-CoV-2 Quantitative Reverse Transcriptase PCR Saliva Diagnostic Strategy utilizing Open-Source Pipetting Robots.

The emergence of the recent SARS-CoV-2 global health crisis introduced key challenges for epidemiological research and clinical testing. Characterized by a high rate of transmission and low mortality, the COVID-19 pandemic necessitated accurate and efficient diagnostic testing, particularly in closed populations such as residential universities. Initial availability of nucleic acid testing, like nasopharyngeal swabs, was limited due to supply chain pressure which also delayed reporting of test results. Saliva-based reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) testing has shown to be comparable in sensitivity and specificity to other testing methods, and saliva collection is less physically invasive to participants. Consequently, we developed a multiplex RT-qPCR diagnostic assay for population surveillance of Clemson University and the surrounding community. The assay utilized open-source liquid handling robots and thermocyclers instead of complex clinical automation systems to optimize workflow and system flexibility. Automation of saliva-based RT-qPCR enables rapid and accurate detection of a wide range of viral RNA concentrations for both large- and small-scale testing demands. The average turnaround for the automated system was < 9 h for 95% of samples and < 24 h for 99% of samples. The cost for a single test was $2.80 when all reagents were purchased in bulk quantities.