Biology subjects

Jaffee, E.

Publications and source records attributed to Jaffee, E..

3 recordsLinked to original sources

bioRxiv2022

Inferring cellular and molecular processes in single-cell data with non-negative matrix factorization using Python, R, and GenePattern Notebook implementations of CoGAPS

Non-negative matrix factorization (NMF) is an unsupervised learning method well suited to high-throughput biology. Still, inferring biological processes requires additional post hoc statistics and annotation for interpretation of features learned from software packages developed for NMF implementation. Here, we aim to introduce a suite of computational tools that implement NMF and provide methods for accurate, clear biological interpretation and analysis. A generalized discussion of NMF covering its benefits, limitations, and open questions in the field is followed by three vignettes for the Bayesian NMF algorithm CoGAPS (Coordinated Gene Activity across Pattern Subsets). Each vignette will demonstrate NMF analysis to quantify cell state transitions in public domain single-cell RNA-sequencing (scRNA-seq) data of malignant epithelial cells in 25 pancreatic ductal adenocarcinoma (PDAC) tumors and 11 control samples. The first uses PyCoGAPS, our new Python interface for CoGAPS that we developed to enhance runtime of Bayesian NMF for large datasets. The second vignette steps through the same analysis using our R CoGAPS interface, and the third introduces two new cloud-based, plug-and-play options for running CoGAPS using GenePattern Notebook and Docker. By providing Python support, cloud-based computing options, and relevant example workflows, we facilitate user-friendly interpretation and implementation of NMF for single-cell analyses.

systems biology↗

bioRxiv2020

Aging interacts with tumor biology to produce major changes in the immune tumor microenvironment

Advanced age is strongly correlated with both increased cancer incidence and general immune decline. The immune tumor microenvironment (ITME) has been established as an important prognostic of both therapeutic efficacy and overall patient survival. Thus, age-related immune decline is an important consideration for the treatment of a large subset of cancer patients. Current studies of aging-related immune alterations are predominantly performed on non-cancerous tissue, requiring additional study into the effects of age on tumor immune infiltration. We leverage large scale transcriptional data sets from The Cancer Genome Atlas and the Genotype-Tissue Expression project to distinguish normal age-related immune alterations from age-related changes in tumor immune infiltration. We demonstrate that while there is overlap between the normal immune aging phenotype and that of the ITME, there are several changes in immune cell abundance that are specific to the ITME, particularly in T cell, NK cell, and Macrophage populations. These results suggest that aged immune cells are more susceptible to tumor suppression of cytotoxic immune cell infiltration and activity than normal tissues, which creates an unfavorable ITME in older patients in excess of normal immune decline with age and may inform the application of existing and emerging immunotherapies for this large population of patients. We additionally identify that age-related increases in tumor mutational burden are associated with decreased DNA methylation and increased expression of the immune checkpoint genes PDL1, CD80, and LAG3 which may have implications for therapeutic application of immune checkpoint blockade in older patients.

cancer biology↗

bioRxiv2017

Harnessing the adaptive potential of mechanoresponsive proteins to overwhelm pancreatic cancer dissemination and invasion

Metastatic disease is often characterized by altered cellular contractility and deformability, lending cells and groups of cells the flexibility to navigate through different microenvironments. This ability to change cell shape is driven in large part by the structural elements of the mechanobiome, which includes cytoskeletal proteins that sense and respond to mechanical stimuli. Here, we demonstrate that key mechanoresponsive proteins (those which accumulate in response to mechanical stress), specifically nonmuscle myosin IIA and IIC, -actinin 4, and filamin B, are highly upregulated in pancreatic ductal adenocarcinoma cancer (PDAC) and in patient-derived pancreatic cancer cell lines. Their less responsive sister paralogs (myosin IIB, -actinin 1, and filamin A) show a smaller dynamic range or disappear with PDAC progression. We demonstrate that these mechanoresponsive proteins directly impact cell mechanics using knock-down and overexpression cell lines. We further quantify the nonmuscle myosin II family members in patient-derived cell lines and identify a role for myosin IIC in the formation of transverse actin arcs in single cells and cortical actin belts in tissue spheroids. We harness the upregulation of myosin IIC and its impact of cytoskeletal architecture through the use of the mechanical modulator 4-hydroxyacetophenone (4-HAP), which increases myosin IIC assembly and stiffens cells. Here, 4-HAP decreases dissemination, induces cortical actin belts, and slows retrograde actin flow in spheroids. Finally, mice having undergone hemi-splenectomies with PDAC cells and then treated with 4-HAP have a reduction in liver metastases. Thus, increasing the activity of these mechanoresponsive proteins (in this case, by increasing myosin IIC assembly) to overwhelm the ability of cells to polarize and invade may be an effective strategy to improve the five-year survival rate of pancreatic cancer patients, currently hovering around 6%.

cancer biology↗