Molecular profiling of ctDNA in pancreatic cancer: Opportunities and challenges for clinical application

Pancreatic ductal adenocarcinoma (PDAC) is predicted to become the second leading cause of cancer-related mortality within the next decade, with limited effective treatment options and a dismal long-term prognosis for patients. Genomic profiling has not yet manifested clinical benefits for diagnosis, treatment or prognosis in PDAC, due to the lack of available tissues for sequencing and the confounding effects of low tumour cellularity in many biopsy specimens. Increasing focus is now turning to the use of minimally invasive liquid biopsies to enhance the characterisation of actionable PDAC tumour genomes. Circulating tumour DNA (ctDNA) is the most comprehensively studied liquid biopsy analyte in blood and can provide insight into the molecular profile and biological characteristics of individual PDAC tumours, in real-time and in advance of traditional imaging modalities. This can pave the way for identification of new therapeutic targets, novel risk variants and markers of tumour response, to supplement diagnostic screening and provide enhanced scrutiny in treatment stratification. In the roadmap towards the application of precision medicine for clinical management in PDAC, ctDNA analyses may serve a leading role in streamlining candidate biomarkers for clinical integration. In this review, we highlight recent developments in the use of ctDNA-based liquid biopsies for PDAC and provide new insights into the technical, analytical and biological challenges that must be overcome for this potential to be realised.     

Evaluation of neurobehavioral abnormalities and immunotoxicity in response to oral imidacloprid exposure in domestic chickens (Gallus gallus domesticus)

ABSTRACT

Domestic chickens (Gallus gallus domesticus) were exposed to imidacloprid by gavage once daily for 7 consecutive days at 0, 0.03, 0.34, 3.42, 10.25, and 15.5 mg/kg/day (n = 20 per group; 5 6-week-old males, 5 6-week-old females, 5 9-week-old males, and 5 9-week-old females). The severity and duration of neurobehavioral abnormalities were recorded. Components of the innate and adaptive immune system were assessed with 7 standard functional assays. Temporary neurobehavioral abnormalities were observed in a dose-dependent manner, including muscle tremors, ataxia, and depressed mentation. Based upon mean clinical severity scores, the no observed adverse effect level (NOAEL) was 3.42 mg/kg/day, and the lowest observed adverse effect level (LOAEL) was 10.25 mg/kg/day. The effective dose value for the presence of any neurobehavioral abnormalities in 50% of the test group (ED₅₀) was 4.62 ± 0.98 mg/kg/day. The ED₅₀ for an adjusted score that included both severity and duration of neurobehavioral abnormalities was 11.24 ± 9.33 mg/kg/day. These ED₅₀ values are equivalent to a 1 kg bird ingesting 29 or 70 imidacloprid treated soybean seeds respectively. Immunotoxicity was not documented, possible causes include the assays were insensitive, relevant immune functions were not examined, or imidacloprid is not immunotoxic at this dosing schedule in this species. Neurobehavioral abnormalities were a more sensitive indicator of the sublethal effects of imidacloprid than immunotoxicity.     

Population Genetics Identifies Challenges in Analyzing Rare Variants

Geneticists have, for years, understood the nature of genome‐wide association studies using common genomic variants. Recently, however, focus has shifted to the analysis of rare variants. This presents potential problems for researchers, as rare variants do not always behave in the same way common variants do, sometimes rendering decades of solid intuition moot. In this paper, we present examples of the differences between common and rare variants. We show why one must be significantly more careful about the origin of rare variants, and how failing to do so can lead to highly inflated type I error. We then explain how to best avoid such concerns with careful understanding and study design. Additionally, we demonstrate that a seemingly low error rate in next‐generation sequencing can dramatically impact the false‐positive rate for rare variants. This is due to the fact that rare variants are, by definition, seen infrequently, making it hard to distinguish between errors and real variants. Compounding this problem is the fact that the proportion of errors is likely to get worse, not better, with increasing sample size. One cannot simply scale their way up in order to solve this problem. Understanding these potential pitfalls is a key step in successfully identifying true associations between rare variants and diseases.