A deep learning approach predicting the activity of COVID-19 therapeutics and vaccines against emerging variants.

Understanding which viral variants evade neutralization is crucial for improving antibody-based treatments, especially with rapidly evolving viruses like SARS-CoV-2. Yet, conventional assays are labor intensive and cannot capture the full spectrum of variants. We present a deep learning approach to predict changes in neutralizing antibody activity of COVID-19 therapeutics and vaccine-elicited sera/plasma against emerging viral variants.

Establishment of human post-vaccination SARS-CoV-2 standard reference sera.

There is a critical need to understand the effectiveness of serum elicited by different SARS-CoV-2 vaccines against SARS-CoV-2 variants. We describe the generation of reference reagents comprised of post-vaccination sera from recipients of different primary vaccines with or without different vaccine booster regimens in order to allow standardized characterization of SARS-CoV-2 neutralization in vitro. We prepared and pooled serum obtained from donors who received a either primary vaccine series alone, or a vaccination strategy that included primary and boosted immunization using available SARS-CoV-2 mRNA vaccines (BNT162b2, Pfizer and mRNA-1273, Moderna), replication-incompetent adenovirus type 26 vaccine (Ad26.

The histone deacetylase inhibitor M344 as a multifaceted therapy for pancreatic cancer.

The histone deacetylase (HDAC) inhibitor vorinostat, used with gemcitabine and other therapies, has been effective in treatment of experimental models of pancreatic cancer. In this study, we demonstrated that M344, an HDAC inhibitor, is efficacious against pancreatic cancer in vitro and in vivo, alone or with gemcitabine. By 24 hours post-treatment, M344 augments the population of pancreatic cancer cells in G1, and at a later time point (48 hours) it increases apoptosis.

Amyloid Precursor-like Protein 2 Expression Increases during Pancreatic Cancer Development and Shortens the Survival of a Spontaneous Mouse Model of Pancreatic Cancer.

In the United States, pancreatic cancer is a major cause of cancer-related deaths. Although substantial efforts have been made to understand pancreatic cancer biology and improve therapeutic efficacy, patients still face a bleak chance of survival. A greater understanding of pancreatic cancer development and the identification of novel treatment targets are desperately needed.

The role of tumor heterogeneity in immune-tumor interactions.

The development of cancer stems from genetic instability and changes in genomic sequences, and hence, the heterogeneity exhibited by tumors is integral to the nature of cancer itself. Tumor heterogeneity can be further altered by factors that are not cancer cell intrinsic, i.e.

Nanoformulation of CCL21 greatly increases its effectiveness as an immunotherapy for neuroblastoma.

Neuroblastoma is the most commonly diagnosed extracranial solid tumor in children. The patients with aggressive metastatic disease or refractory/relapsed neuroblastoma currently face a dismally low chance of survival. Thus, there is a great need for more effective therapies for this illness.

Beta 2-microglobulin regulates amyloid precursor-like protein 2 expression and the migration of pancreatic cancer cells.

Beta 2-microglobulin (βm) is a component of the major histocompatibility complex (MHC) class I molecule, which presents tumor antigens to T lymphocytes to trigger cancer cell destruction. Notably, βm has been reported as persistently expressed, rather than down regulated, in some tumor types. For renal cell and oral squamous cell carcinomas, βm expression has been linked to increased migratory capabilities.

Emerging trends in the immunotherapy of pancreatic cancer.

Pancreatic cancer (PC) is the fourth leading cause of cancer-related deaths in the U.S., claiming approximately 43,000 lives every year.