Biology subjects

Chung, M.-i.

Publications and source records attributed to Chung, M.-i..

4 recordsLinked to original sources

bioRxiv2025

Overcoming myeloid-driven resistance to CAR T therapy by targeting SPP1

Chimeric antigen receptor (CAR) T cell therapy faces notable limitations in treatment of solid tumors. The suppressive tumor microenvironment (TME), characterized by complex interactions among immune and stromal cells, is gaining recognition in conferring resistance to CAR T cell therapy. Despite the abundance and diversity of macrophages in the TME, their intricate involvement in modulating responses to CAR T cell therapies remains poorly understood. Here, we conducted single-cell RNA sequencing (scRNA-seq) on tumors from 41 glioma patients undergoing IL13R2-targeted CAR T cell therapy, identifying elevated suppressive SPP1 signatures predominantly in macrophages from patients who were resistant to treatment. Further integrative scRNA-seq analysis of high-grade gliomas as well as an interferon-signaling deficient syngeneic mouse model--both resistant to CAR T therapy--demonstrated the role of congruent suppressive pathways in mediating resistance to CAR T cells and a dominant role for SPP1+ macrophages. SPP1 blockade with an anti-SPP1 antibody abrogates the suppressive TME effects and substantially prolongs survival in IFN signaling-deficient and glioma syngeneic mouse models resistant to CAR T cell therapy. These findings illuminate the role of SPP1+ macrophages in fueling a suppressive TME and driving solid tumor resistance to CAR cell therapies. Targeting SPP1 may serve as a universal strategy to reprogram immune dynamics in solid tumors mitigating resistance to CAR T cell therapies.

cancer biology↗

bioRxiv2024

Germline and somatic genetic effects on gene expression and outcome in patients with Multiple Myeloma

Multiple Myeloma (MM) is a hematological malignancy associated with poor prognosis and relapses. MM has a strong inherited component, and while the mutational and transcriptomic landscapes of MM have been characterized extensively, the molecular consequences of germline genetic variation in MM have not been previously explored. Here, we have leveraged matched genotype and expression data from 607 patients to map the germline and somatic regulatory variation in MM. We find that non-coding variation shapes the transcriptional landscape of MM, contributing to overall survival. These regulatory variants alter the binding of transcription factors with known importance in MM, such as IRF4, providing insights into the underlying mechanisms. These data contribute to the increasing understanding of the genetic, molecular, and cellular forces shaping MM risk and outcomes.

genomics↗

bioRxiv2023

Cell type-specific and disease-associated eQTL in the human lung

Common genetic variants confer substantial risk for chronic lung diseases, including pulmonary fibrosis (PF). Defining the genetic control of gene expression in a cell-type-specific and context-dependent manner is critical for understanding the mechanisms through which genetic variation influences complex traits and disease pathobiology. To this end, we performed single-cell RNA-sequencing of lung tissue from 67 PF and 49 unaffected donors. Employing a pseudo-bulk approach, we mapped expression quantitative trait loci (eQTL) across 38 cell types, observing both shared and cell type-specific regulatory effects. Further, we identified disease-interaction eQTL and demonstrated that this class of associations is more likely to be cell-type specific and linked to cellular dysregulation in PF. Finally, we connected PF risk variants to their regulatory targets in disease-relevant cell types. These results indicate that cellular context determines the impact of genetic variation on gene expression, and implicates context-specific eQTL as key regulators of lung homeostasis and disease.

genomics↗

bioRxiv2022

An integrated cell atlas of the human lung in health and disease

Organ- and body-scale cell atlases have the potential to transform our understanding of human biology. To capture the variability present in the population, these atlases must include diverse demographics such as age and ethnicity from both healthy and diseased individuals. The growth in both size and number of single-cell datasets, combined with recent advances in computational techniques, for the first time makes it possible to generate such comprehensive large-scale atlases through integration of multiple datasets. Here, we present the integrated Human Lung Cell Atlas (HLCA) combining 46 datasets of the human respiratory system into a single atlas spanning over 2.2 million cells from 444 individuals across health and disease. The HLCA contains a consensus re-annotation of published and newly generated datasets, resolving under- or misannotation of 59% of cells in the original datasets. The HLCA enables recovery of rare cell types, provides consensus marker genes for each cell type, and uncovers gene modules associated with demographic covariates and anatomical location within the respiratory system. To facilitate the use of the HLCA as a reference for single-cell lung research and allow rapid analysis of new data, we provide an interactive web portal to project datasets onto the HLCA. Finally, we demonstrate the value of the HLCA reference for interpreting disease-associated changes. Thus, the HLCA outlines a roadmap for the development and use of organ-scale cell atlases within the Human Cell Atlas.

cell biology↗