Using wastewater for population colorectal cancer screening and future research needs
Wurtzler, E.; Barnell, E.; Morrison, C.; Grass, C.; DuPre, N. C.; Biddle, D. J.; Jin, A.; Kavalukas, S.; Holm, R. H.; Smith, T. R.
Show abstract
Colorectal cancer (CRC) is the third most common cancer and the second leading cause of cancer-related deaths in the United States. Individual screening is typically done with either a clinical stool-based test or direct clinical examination such as a colonoscopy. Given the low compliance with current screening recommendations and the high morbidity and mortality observed in areas with health disparities, we consider whether population-based testing using human RNA biomarkers in wastewater might effectively track the presence of CRC at the neighborhood level might be feasible. Wastewater samples were collected from four clusters in Louisville, KY: three representing cancer hotspots and one serving as a control neighborhood for feasibility data. Three wastewater replicates were obtained from each cluster. Human RNA biomarkers were isolated, quantified, and their RNA concentration levels were compared to clinical correlates. All replicates showed detectable levels of human cancer-associated RNA, including CDH1, which is a colorectal neoplasia-associated biomarker. Among CRC cluster sewershed samples, 8 of 9 replicate samples (89%) had a ratio of CDH1/GAPDH >=1 while the control sewershed sample showed ratio <1 for 2 of 3 samples. These preliminary data indicate that human RNA biomarkers can be detected in pooled community wastewater samples. While we have successfully identified the presence of these markers, further investigation with additional samples and closer alignment with documented case activity is necessary.
Matching journals
The top 5 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Tracking SARS-CoV-2 RNA through the wastewater treatment process 96%
- Evaluation of sampling frequency and normalization of SARS-CoV-2 wastewater concentrations for capturing COVID-19 burdens in the community 96%
- Within-Day Variability of SARS-CoV-2 RNA in Municipal Wastewater Influent During Periods of Varying COVID-19 Prevalence and Positivity 96%
Similar papers in this journal
- Applicability of Neighborhood and Building Scale Wastewater-Based Genomic Epidemiology to Track the SARS-CoV-2 Pandemic and other Pathogens 97%
- Tracking the temporal variation of COVID-19 surges through wastewater-based epidemiology during the peak of the pandemic: a six-month long study in Charlotte, North Carolina 96%
- Automated method to extract and purify RNA from wastewater enables more sensitive detection of SARS-CoV-2 markers in community sewersheds 96%
Similar papers in this journal
- Monitoring SARS-CoV-2 in wastewater during New York City’s second wave of COVID-19: Sewershed-level trends and relationships to publicly available clinical testing data 98%
- Prewhitening and Normalization Help Detect a Strong Cross-Correlation Between Daily Wastewater SARS-CoV-2 RNA Abundance and COVID-19 Cases in a Community 97%
- Development and optimization of a new method for direct extraction of SARS-CoV-2 RNA from municipal wastewater using magnetic beads 96%
Similar papers in this journal
- High-resolution within-sewer SARS-CoV-2 surveillance facilitates informed intervention 97%
- Biomarkers Selection for Population Normalization in SARS-CoV-2 Wastewater-based Epidemiology 96%
- Wastewater Monitoring of SARS-CoV-2 from Acute Care Hospitals Identifies Nosocomial Transmission and Outbreaks 96%
Similar papers in this journal
- Solid evidence and liquid gold: trade-offs of processing settled solids, whole influent, or centrifuged influent for co-detecting viral, bacterial, and eukaryotic pathogens in wastewater 96%
- Benchmarking concentration and direct extraction methods for wastewater-based surveillance of eight human respiratory viruses: implications for rapid application to novel pathogens 96%
- Detection of Hemagglutinin H5 influenza A virus RNA and model of potential inputs in an urban California sewershed 96%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.