Quantitative traits show abundant genetic, environmental, and phenotypic variance, yet if they are subject to stabilizing selection for an optimal phenotype, both the genetic and environmental components are expected to decline. The mechanisms that determine the level and maintenance of phenotypic variance are not yet fully understood. While there has been extensive study of mechanisms maintaining genetic variability, it has generally been assumed that environmental variance is not dependent on the genotype and therefore not subject to change. However, accumulating data suggest that the environmental variance is under some degree of genetic control. In this study, it is assumed accordingly that both the genotypic value (i.e., mean phenotypic value) and the variance of phenotypic value given genotypic value depend on the genotype. Two models are investigated as potentially able to explain the protected maintenance of environmental variance of quantitative traits under stabilizing selection. One is varying environment among generations, such that both the optimal phenotype and the strength of the stabilizing selection vary between generations. The other is the cost of homogeneity, which is based on an assumption of an engineering cost of minimizing variability in development. It is shown that a small homogeneity cost is enough to maintain the observed levels of environmental variance, whereas a large amount of temporal variation in the optimal phenotype and the strength of selection would be necessary.
Pancreatic ductal adenocarcinoma (PDAC) is a highly metastatic disease. Tumors are poorly immunogenic and immunosuppressive, preventing T cell activation in the tumor microenvironment. Here, we present a microbial-based immunotherapeutic treatment for selective delivery of an immunogenic tetanus toxoid protein (TT 856-1313 ) into PDAC tumor cells by attenuated Listeria monocytogenes . This treatment reactivated preexisting TT-specific memory T cells to kill infected tumor cells in mice. Treatment of KrasG12D,p53R172H, Pdx1-Cre (KPC) mice with Listeria -TT resulted in TT accumulation inside tumor cells, attraction of TT-specific memory CD4 T cells to the tumor microenvironment, and production of perforin and granzyme B in tumors. Low doses of gemcitabine (GEM) increased immune effects of Listeria -TT, turning immunologically cold into hot tumors in mice. In vivo depletion of T cells from Listeria -TT + GEM–treated mice demonstrated a CD4 T cell–mediated reduction in tumor burden. CD4 T cells from TT-vaccinated mice were able to kill TT-expressing Panc-02 tumor cells in vitro. In addition, peritumoral lymph node–like structures were observed in close contact with pancreatic tumors in KPC mice treated with Listeria -TT or Listeria -TT + GEM. These structures displayed CD4 and CD8 T cells producing perforin and granzyme B. Whereas CD4 T cells efficiently infiltrated the KPC tumors, CD8 T cells did not. Listeria -TT + GEM treatment of KPC mice with advanced PDAC reduced tumor burden by 80% and metastases by 87% after treatment and increased survival by 40% compared to nontreated mice. These results suggest that Listeria -delivered recall antigens could be an alternative to neoantigen-mediated cancer immunotherapy.
Identification and quantification of somatic alterations in plasma-derived, circulating tumor DNA (ctDNA) is gaining traction as a non-invasive and cost effective method of disease monitoring in cancer patients, particularly to evaluate response to treatment and monitor for disease recurrence. To our knowledge, genetic analysis of ctDNA in osteosarcoma has not yet been studied. To determine whether somatic alterations can be detected in ctDNA and perhaps applied to patient management in this disease, we collected germline, tumor, and serial plasma samples from pediatric, adolescent, and young adult patients with osteosarcoma and used targeted Next Generation Sequencing (NGS) to identify somatic single nucleotide variants (SNV), insertions and deletions (INDELS), and structural variants (SV) in 7 genes commonly mutated in osteosarcoma. We demonstrate that patient-specific somatic alterations identified through comparison of tumor-germline pairs can be detected and quantified in cell-free DNA of osteosarcoma patients.
The mechanisms underlying retinal development have not been completely elucidated. Extracellular vesicles (EVs) are novel essential mediators of cell-to-cell communication with emerging roles in developmental processes. Nevertheless, the identification of EVs in human retinal tissue, characterization of their cargo, and analysis of their potential role in retina development has not been accomplished. Three-dimensional retinal tissue derived from human induced pluripotent stem cells (hiPSC) provide an ideal developmental system to achieve this goal. Here we report that hiPSC-derived retinal organoids release exosomes and microvesicles with small noncoding RNA cargo. EV miRNA cargo-predicted targetome correlates with Gene Ontology (GO) pathways involved in mechanisms of retinogenesis relevant to specific developmental stages corresponding to hallmarks of native human retina development. Furthermore, uptake of EVs by human retinal progenitor cells leads to changes in gene expression correlated with EV miRNA cargo predicted gene targets, and mechanisms involved in retinal development, ganglion cell and photoreceptor differentiation and function.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.