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- All Subjects: Cancer
- All Subjects: SARS-CoV-2
- Creators: Compton, Carolyn
As the return to normality in the wake of the COVID-19 pandemic enters its early stages, the necessity for accurate, quick, and community-wide surveillance of SARS-CoV-2 has been emphasized. Wastewater-based epidemiology (WBE) has been used across the world as a tool for monitoring the pandemic, but studies of its efficacy in comparison to the best-known method for surveillance, randomly selected COVID-19 testing, has limited research. This study evaluated the trends and correlations present between SARS-CoV-2 in the effluent wastewater of a large university campus and random COVID-19 testing results published by the university. A moderately strong positive correlation was found between the random testing and WBE surveillance methods (r = 0.63), and this correlation was strengthened when accommodating for lost samples during the experiment (r = 0.74).
In mid-March of 2020, Arizona State University transformed one of its research labs into ASU Biodesign Clinical Testing Laboratory (ABCTL) to meet the testing needs of the surrounding community during the COVID-19 pandemic. The lab uses RT-qPCR, or reverse transcription polymerase chain reaction, to match the components of a biosample to a portion of the SARS-CoV-2 genome. The ABCTL uses the TaqPath™ COVID-19 Combo Kit, which has undergone many different types of efficacy and efficiency tests and can successfully denote saliva samples as positive even when an individual is infected with various emerging strains of the SARS-CoV-2. Samples are collected by volunteers at testing sites with stringent biosafety precautions and processed in the lab using specific guidelines. As the pandemic eventually becomes less demanding, the ABCTL plans to utilize the Devil’s Drop-off program at various school districts around Arizona to increase testing availability, transfer to the SalivaDirect method, and provide other forms of pathogen testing to distinguish COVID-19 from other types of infections in the ASU community.
The Molecular Disease Classifier (MDC) was trained on 34,352 cases and tested on 15,473 unambiguously diagnosed cases. The MDC predicted the correct tumor type out of thirteen possibilities in the labeled data set with sensitivity, specificity, PPV, and NPV of 90.5%, 99.2%, 90.5% and 99.2% respectively when considering up to 5 predictions for a case.
The availability of whole transcriptome data in the CMD prompted its inclusion into a new platform called MI GPSai (MI Genomic Prevalence Score). The algorithm trained on genomic data from 34,352 cases and genomic and transcriptomic data from 23,137 cases and was validated on 19,555 cases. MI GPSai can predict the correct tumor type out of 21 possibilities on 93% of cases with 94% accuracy. When considering the top two predictions for a case, the accuracy increases to 97%.
Finally, a 67 gene molecular signature predictive of efficacy of oxaliplatin-based chemotherapy in patients with metastatic colorectal cancer was developed - FOLFOXai. The signature was predictive of survival in an independent real-world evidence (RWE) dataset of 412 patients who had received FOLFOX/BV in 1st line and inversely predictive of survival in RWE data from 55 patients who had received 1st line FOLFIRI. Blinded analysis of TRIBE2 samples confirmed that FOLFOXai was predictive of OS in both oxaliplatin-containing arms (FOLFOX HR=0.629, p=0.04 and FOLFOXIRI HR=0.483, p=0.02).
Cancer is an ever-relevant disease with many genetic, social, environmental, and behavioral risk factors. One factor which has been garnering interest is the impact of nutrition on cancer. As a disease process, cancer is primarily driven by an accumulation of genetic aberrations. Recent epidemiological, pre-clinical, and clinical studies have demonstrated various impacts of bioactive food molecules on the promotion or prevention of these oncogenic mutations. This work explores several of these molecules and their relation to cancer prevention and provides a sample meal plan, which highlights many additional molecules that are currently being studied.
Cancer is an ever-relevant disease with many genetic, social, environmental, and behavioral risk factors. One factor which has been garnering interest is the impact of nutrition on cancer. As a disease process, cancer is primarily driven by an accumulation of genetic aberrations. Recent epidemiological, pre-clinical, and clinical studies have demonstrated various impacts of bioactive food molecules on the promotion or prevention of these oncogenic mutations. This work explores several of these molecules and their relation to cancer prevention and provides a sample meal plan, which highlights many additional molecules that are currently being studied.
