Large-Scale SARS-CoV-2 Testing Utilizing Saliva and Transposition Sample Pooling.

Identification and isolation of contagious individuals along with quarantine of close contacts, is critical for slowing the spread of COVID-19. Large-scale testing in a surveillance or screening capacity for asymptomatic carriers of COVID-19 provides both data on viral spread and the follow-up ability to rapidly test individuals during suspected outbreaks. The COVID-19 early detection program at Michigan State University has been utilizing large-scale testing in a surveillance or screening capacity since fall of 2020. The methods adapted here take advantage of the reliability, large sample volume, and self-collection benefits of saliva, paired with a cost-effective, reagent conserving two-dimensional pooling scheme. The process was designed to be adaptable to supply shortages, with many components of the kits and the assay easily substituted. The processes outlined for collecting and processing SARS-CoV-2 samples can be adapted to test for future viral pathogens reliably expressed in saliva. By providing this blueprint for universities or other organizations, preparedness plans for future viral outbreaks can be developed.

Systems biology approaches to pancreatic cancer detection, prevention and treatment.

Pancreatic cancer [PC] is a complex disease harboring multiple genetic alterations. It is now well known that deregulation in the expression and function of oncogenes and tumor suppressor genes contributes to the development and progression of PC. The last 40 years have not seen any major improvements in the dismal overall cure rate for PC where drug resistance is an emerging and recurring obstacle for successful treatment of PC. Additionally, the lack of molecular biomarkers for patient selection limits drug availabilities for tailored therapy for patients diagnosed with PC. The very high failure rate of new drugs in Phase III clinical trials in PC calls for a more robust pre-clinical and clinical testing of new compounds. In order to rationally choose combinations of targeted agents that may improve therapeutic outcome by overcoming drug resistance, one needs to apply newer research tools such as systems and network biology. These newer tools are expected to assist in the design of effective drug combinations for the treatment of PC and are expected to become an important part in any future clinical trials. In this review we will provide background information on the current state of PC research, the reasons for drug failure and how to overcome these issues using systems sciences. We conclude this review with an example on how systems and network methodologies can help in the design efficacious drug combinations for this deadly and by far incurable disease.

Network pharmacology: reigning in drug attrition?

In the process of drug development, there has been an exceptionally high attrition rate in oncological compounds entering late phases of testing. This has seen a concurrent reduction in approved NCEs (new chemical entities) reaching patients. Network pharmacology has become a valuable tool in understanding the fine details of drug-target interactions as well as painting a more practical picture of phenotype relationships to patients and drugs. By utilizing all the tools achieved through molecular medicine and combining it with high throughput data analysis, interactions and mechanisms can be elucidated and treatments reasonably tailored to patients expressing specific phenotypes (or genotypes) of disease, essentially reigning in the phenomenon of drug attrition.

Network insights on oxaliplatin anti-cancer mechanisms.

Oxaliplatin has been a crucial component of combination therapies since admission into the clinic causing modest gains in survival across multiple malignancies. However, oxaliplatin functions in a non-targeted manner, posing a difficulty in ascertaining precise efficacy mechanisms. While previously thought to only affect DNA repair mechanisms, Platinum-protein adducts (Pt-Protein) far outnumber Pt-DNA adducts leaving a big part of oxaliplatin function unknown. Through preliminary network modeling of high throughput data, this article critically reviews the efficacy of oxaliplatin as well as proposes a better model for enhanced efficacy based on a network approach. In our study, not only oxaliplatin's function in interrupting DNA-replication was confirmed, but also its role in initiating or intensifying tumorigenesis pathways was uncovered. From our data we present a novel picture of competing signaling networks that collectively provide a plausible explanation of chemotherapeutic resistance, cancer stem cell survival, as well as invasiveness and metastases. Here we highlight oxaliplatin signaling networks, their significance and the clinical implications of these interactions that verifies the importance of network modeling in rational drug design.