DOI: 10.5281/zenodo.18623202
title: Resistance to PRMT5-targeted therapy in mantle cell lymphoma.

description: Source reference: Blood advances • 2024 • DOI: 10.1182/bloodadvances.2023010554 • PMID: 37782774

Mantle cell lymphoma (MCL) is an incurable B-cell non-Hodgkin lymphoma, and patients who relapse on targeted therapies have poor prognosis. Protein arginine methyltransferase 5 (PRMT5), an enzyme essential for B-cell transformation, drives multiple oncogenic pathways and is overexpressed in MCL. Despite the antitumor activity of PRMT5 inhibition (PRT-382/PRT-808), drug resistance was observed in a patient-derived xenograft (PDX) MCL model. Decreased survival of mice engrafted with these PRMT5 inhibitor-resistant cells vs treatment-naive cells was observed (P = .005). MCL cell lines showed variable sensitivity to PRMT5 inhibition. Using PRT-382, cell lines were classified as sensitive (n = 4; 50% inhibitory concentration [IC50], 20-140 nM) or primary resistant (n = 4; 340-1650 nM). Prolonged culture of sensitive MCL lines with drug escalation produced PRMT5 inhibitor-resistant cell lines (n = 4; 200-500 nM). This resistant phenotype persisted after prolonged culture in the absence of drug and was observed with PRT-808. In the resistant PDX and cell line models, symmetric dimethylarginine reduction was achieved at the original PRMT5 inhibitor IC50, suggesting activation of alternative resistance pathways. Bulk RNA sequencing of resistant cell lines and PDX relative to sensitive or short-term-treated cells, respectively, highlighted shared upregulation of multiple pathways including mechanistic target of rapamycin kinase [mTOR] signaling (P < 10-5 and z score > 0.3 or < 0.3). Single-cell RNA sequencing analysis demonstrated a strong shift in global gene expression, with upregulation of mTOR signaling in resistant PDX MCL samples. Targeted blockade of mTORC1 with temsirolimus overcame the PRMT5 inhibitor-resistant phenotype, displayed therapeutic synergy in resistant MCL cell lines, and improved survival of a resistant PDX.

Instructions for use: README



Resistance to PRMT5 Targeted Therapy in Mantle Cell Lymphoma

This is a processed data package. Use this together with the companion analysis project to reproduce selected figures (scRNA-seq) from the manuscript.

Steps to Reproduce

1.  System Requirements



R v4.3 or greater

Rstudio

Loading the complete dataset occupies approximately 3.5 GB memory.


2.  Installation



download the source data (.tar.gz) to a convenient location on your computer.

clone the analysis project to your computer using git clone https://github.com/blaserlab/baiocchi_long.git

open the R project by double-clicking on the baiocchi_long.Rproj file

a list of the packages required for the project can be found in library_catalogs/blas02_baiocchi_long.tsv. Filter for packages with status == "active". Install these packages.

install custom packages from our R Universe repository using these commands:

install.packages('blaseRtools', repos = c('https://blaserlab.r-universe.dev', 'https://cloud.r-project.org'))

install.packages('blaseRtemplates', repos = c('https://blaserlab.r-universe.dev', 'https://cloud.r-project.org'))

install.packages('blaseRdata', repos = c('https://blaserlab.r-universe.dev', 'https://cloud.r-project.org'))

edit as needed and source R/dependencies.R

edit as needed and source R/configs.R

typical time required for the first installation and data loading is approximately 10 minutes.


3.  Instructions for use after installing and configuring



source R/dependencies.R

source R/configs.R

source R/manuscript_figures.R. This will generate all computationally-derived figures in the manuscript.

If properly configured, these scripts should run to completion in 1-2 minutes.


4.  Each computationally-generated figure panel is associated with processed data and code for visualization. Each processed data object has its own help manual and associated processing code within the data package. To access these resources do the following:



find the variable name for the panel you wish to review in R/manuscript_figures.R.

find the original data object used to generate that panel in the code

type ? to get the help manual

to review processing code, go to the installed location of baiocchi.long.datapkg on your system and look in the data-raw directory