bioRxiv Science⌕ Search

Biology subjects

Modliszewski, J.

Publications and source records attributed to Modliszewski, J..

3 recordsLinked to original sources

Latent Regulatory Programs Generate Synthetic T Cell States with Enhanced Therapeutic Potential

Transcription factors (TFs) govern cell fate through coordinated gene-regulatory networks, yet the full potential of these networks to generate non-native, therapeutically advantageous cell states in vivo remains largely unexplored. We hypothesized that systematic gain-of-function (GOF) overexpression of TFs in CD8 T cells, central mediators of immune protection, could reveal latent, or "hidden," regulatory programs capable of generating synthetic T cell states with therapeutic utility. To test this, we developed single-cell GOF sequencing (scGOF-seq), a multiplexed platform for unbiased, in vivo mapping of GOF effects on T cell fate in immunocompetent mouse models of infection and cancer. scGOF-seq uncovered unexpected regulators of T cell differentiation and accumulation, including SOX2, OCT4, and GATA2, which are normally silenced during T cell differentiation. Notably, outside its native regulatory context, supraphysiologic cMyc GOF reprogrammed CD8 T cells into a synthetic stem-effector hybrid state, enabling >5,000-fold antigen-dependent expansion and antitumor activity, contrasting sharply with its native function in driving terminal differentiation. scGOF-seq further identified TF modules that cooperate with cMyc GOF to promote robust CD8 T cell responses in solid tumors. Together, these findings establish GOF perturbation as a powerful strategy for revealing latent immune regulatory programs and engineering synthetic immune states with therapeutic potential. One-Sentence SummaryIn vivo single-cell gain-of-function screening reveals latent transcriptional programs that can reprogram T cells into highly functional synthetic states.

immunology↗

Adaptive IRE1 Signaling Elicits T Cell Metabolic Remodeling and Tumor Control

The efficacy of cancer immunotherapies is limited by the metabolic instability of the tumor microenvironment (TME) that disables T cell antitumor immunity. Metabolic imbalances within the TME are sensed and responded to by stress sensors of the endoplasmic reticulum (ER) unfolded protein response (UPR). The UPR comprises three integrated signaling pathways harboring both adaptive and deleterious phases based on the extent and duration of cell stress. Here, we elucidate the differential contributions of adaptive and deleterious signaling downstream of the UPR IRE1 pathway in T cell-regulated tumor control. T cells in murine and patient cancers experience persistent ER stress, leading to hyperactive IRE1 signaling that limits tumor control. However, amplifying the adaptive arm of the IRE1 UPR serves to eliminate mitochondrial toxicity and protect T cells from chronic ER stress, yielding robust tumor engraftment and long-term tumor immunity. Our findings establish the UPRs essential protective role in antitumor immunity.

immunology↗

A Precision Medicine Approach to Stress Testing Using Metabolomics and MicroRibonucleic Acids

BackgroundAcute coronary syndrome (ACS) is a growing global health problem, and precision medicine techniques hold promise for the development of diagnostic indicators of ACS. In this pilot, we sought to assess the utility of an integrated analysis of metabolomic and microRNA data in peripheral blood to distinguish patients with abnormal cardiac stress testing from matched controls. MethodsWe used prospectively collected samples from emergency department (ED) patients placed in an ED-based observation unit who underwent stress testing for ACS. We isolated microRNA and quantified metabolites from plasma collected before and after stress testing in patients with myocardial ischemia on stress testing versus those with normal stress tests. The combined metabolomic and microRNA data were analyzed jointly for case (ischemia) and 1:1 matched control patients in a supervised, dimension-reducing discriminant analysis. Two integrative models were implemented: a baseline model utilizing data collected prior to stress-testing (T0) and a stress-delta model, which included the difference between post-stress test (T1) and pre-stress test (T0). ResultsSeven case patients with myocardial ischemia on ED cardiac stress testing (6 females, 85% Caucasian, mean Thrombolysis In Myocardial Infarction Score=3, 4 patients ultimately received percutaneous coronary intervention) were 1:1 age and sex-matched to controls. Several metabolites and microRNAs were differentially expressed between cases and controls. Integrative analysis of the baseline levels of metabolites and microRNA expression showed modest performance for distinguishing cases from controls with an overall error rate of 0.143. The stress-delta model showed worse performance for distinguishing cases from controls, with an overall error rate of 0.500. ConclusionsGiven our small sample size, results are hypothesis-generating. However, this pilot study shows a potential method for a precision medicine approach to cardiac stress testing in patients undergoing workup for ACS.

physiology↗