Immune aging impairs T cell-mediated tumor control as well as cancer immunotherapy outcomes. The most important drivers of T cell dysfunction in aged tumors remain unknown. We performed single-cell CRISPR screens to identify Dusp5 and Zfp219 as key regulators of CD8+ T cell persistence and effector differentiation within aged tumors. Loss of Dusp5 increased extracellular signal-regulated kinase (ERK) phosphorylation and globally enhanced T cell proliferation. Conversely, Zfp219 deletion induced epigenetic reprogramming and increased expression of cytotoxic molecules, enhancing antitumor immunity specifically in aging. Levels of the human ortholog ZNF219 were higher within intratumoral CD8+ T cells from older cancer patients, which correlates with worse survival following immunotherapy. Zfp219 ablation synergized with immune checkpoint inhibitors to expand effector-like CD8+ T cells, leading to tumor clearance in aged mice. Our findings highlight Dusp5 and Zfp219 as critical drivers of age-related T cell dysfunction that can be targeted to rejuvenate antitumor immunity in older cancer patients.
Alex C. Y. Chen, Keely Y. Ji, C. Yerinde et al.· Cell· 0 citations
The alpha-variant wave of the COVID-19 pandemic provided a unique opportunity to study, at single-cell resolution, how near-universal exposure to the same pathogen can lead to either effective or dysfunctional immune responses in humans.
We analyzed 2.5 million circulating immune cells from 428 patients across time points (840 PBMC samples), encompassing three contemporaneous SARS-CoV-2 cohorts: acutely infected patients at five WHO disease severity levels and three time points, patients from the first randomized control trial to study efficacy of tocilizumab in management of COVID-19, and convalescent patients three months after infection. We used linear modeling to integrate multiple data types – single-cell RNA-seq, CITE-seq, TCR and BCR sequencing, viral load measurements, viral neutralization assays, detection of 75 autoantibodies, HLA genotype data, and serum proteomics covering 1,463 targets – to derive the most comprehensive view to-date of the biological features of COVID-19 disease severity.
We show that myeloid-derived suppressor cells (MDSCs) act as a key immunologic pivot point in severe COVID-19. Myeloid dysfunction is marked by impaired antigen presentation and drives a non-productive adaptive immune response. Severe disease is also linked to autoantibodies targeting type I interferons, specific HLA-DQB1 allelic variants, and serum IL-6 levels. Tocilizumab treatment eliminates CLU-expressing MDSCs and ISG-positive myeloid subsets, restores antigen presentation, and reactivates productive adaptive immunity. In convalescence 3-months post-infection, we found persistently high ICOS expression in regulatory T cells.
Overall, we define distinct innate and adaptive host immune responses associated with acute, IL-6—responsive, and convalescent SARS-CoV-2 infection. Our multimodal and high-dimensional dataset with curated clinical metadata provides a foundational and clinically relevant resource for modeling host immune response biology in health and disease.
We acknowledge the following funding sources: this work was supported by several training grants, including a NIAID grant T32AR007258 (to KS), three NHLBI grants 5T32HL116275-13 (to CC), 5T32HL129970-09 (to APN), and the K08HL157725 (to PS), as well as the American Heart Association Career Development Award (to PS). PS was also supported by the Brigham and Women’s Hospital Innovation Evergreen Fund. EY was supported by funding from the Stanford Medical Scholars program. RJX acknowledges supports from NIH DK43351 and U19AI142784. RJX and AR were supported by the Manton Foundation and the Klarman Cell Observatory. PJU was supported by Third Rock Ventures; Henry Gustav Floren Trust; Stanford Department of Medicine Team Science Program; Stanford Medicine Office of the Dean; and National Institutes of Health R01 grants AI175771 and AI182319-02. RPB acknowledges funding support from the Massachusetts General Hospital Executive Committee on Research, the American Lung Association, and the Broad Institute’s Next Generation Scholar award. MBG, MRF, and NH were supported by an American Lung Association COVID-19 Action Initiative grant. MBG and MRF were supported by a grant from the Executive Committee on Research at MGH. NH acknowledges was supported by NIH/NIAID U19 AI082630, a Chair and gift from Sandra, Sarah, and Arthur Irving. ACV acknowledges funding support from the COVID-19 Clinical Trials Pilot grant from the Executive Committee on Research at MGH; a COVID-19 Chan Zuckerberg Initiative grant (2020-216954); the funds from the Manton Foundation and the Klarman Family Foundation; the Broad Institute’s Next Generation Scholar award; the MGH Howard M. Goodman Fellowship; the National Institutes of Health (DP2CA247831); work at the Broad Institute was supported by a gift from an anonymous donor.
Computational and Systems Immunology (COMP)
Kamil Slowikowski, Pritha Sen, C. Cosgriff et al.· Journal of Immunology· 0 citations
Human leukocyte antigen (HLA) class I presents intracellular peptides to the immune system on the cell surface. Since this process is crucial for the recognition of cancer cells and the initiation of anti-tumor immunity, peptides presented by HLA are valuable immunotherapy targets. More stable peptide HLA (pHLA) complexes provoke superior immune responses. However, how peptide sequence motifs contribute to pHLA stability is not well understood.
We developed a high-throughput assay to quantify stability of thousands of user-defined pHLA produced in E. coli. Peptide libraries and the desired HLA are produced and form pHLA complexes in E. coli. pHLA are purified and stability is evaluated by treating pHLA with a thermal gradient and recovering only the peptides which remain HLA-bound after heat treatment. Peptide depletion over the temperature range is monitored by quantitative tandem mass tag (TMT) enabled mass spectrometry.
Our new E. coli-based method is reliable for assessing pHLA stability. Detected HLA-binding peptides have the expected binding motifs, and stability data strongly correlates with current gold-standard data. We are able to generate large peptide stability datasets (1,800+ peptides) in one scaled experiment — five times larger than currently available datasets. We show that peptide motifs and anchor residue combinations potentially drive pHLA stability. Additionally, peptides were included in user-defined libraries with public immunogenicity annotations. We observed that immunogenic peptides were significantly more stable than non-immunogenic peptides.
We generated customizable pHLA stability datasets which show how peptide sequence motifs affect pHLA stability, and may be helpful for improving our mechanistic understanding of pHLA stability. Further, since peptide stability is related to immunogenicity, these large-scale pHLA stability datasets will be useful for improving peptide immunogenicity predictions for the development of immunotherapeutics.
NIH R01CA155010, Mark Foundation for Cancer Research, Moderna
Classical and Non-Classical Antigen Presenting Cells (APC)
M. Wilbrink, Luis O Correa-Medero, Emma C Duggan et al.· Journal of Immunology· 0 citations
Single-cell RNA sequencing has transformed our understanding of cellular systems, yet the reliance on short-read sequencing restricts analysis to gene-level quantification and obscures the immense biological diversity generated by alternative splicing. While long-read sequencing technologies can capture full-length RNA and resolve transcript isoforms, current platforms remain constrained by throughput and high per-base costs, rendering them impractical for modern million-cell applications. To address this critical limitation, we developed and optimized sequencing-by-expansion (SBX) chemistry for high-throughput single-cell RNA isoform profiling. Integrated within the AXELIOS 1 sequencing platform, SBX employs a unique biochemical conversion process that transforms complementary DNA into expanded surrogate high signal-to-noise polymers called Xpandomers which are sequenced via translocation through a dense nanopore array yielding over 9.5 billion reads in a two-hour run. To leverage this unique data type for long-read single-cell RNA isoform sequencing, we developed the Consensus UMI Deduplication using Longest Length (CUDLL) algorithm, which computationally consolidates variable-length raw SBX reads into single, high-fidelity consensus reads, elevating sequence accuracy to 99.83% and maximizing per transcript read length. We demonstrate that this consensus approach successfully captures the vast isoform diversity of single-cell libraries and enables the accurate measure of differential isoform expression across distinct cell types in peripheral blood mononuclear cells. Furthermore, SBX coupled with CUDLL efficiently resolves T-cell and B-cell receptor clonotypes directly from whole-transcriptome libraries without the need for VDJ-specific target enrichment. Ultimately, this work establishes SBX and the AXELIOS 1 as a transformative platform for high-scale single-cell isoform sequencing.
Christophe H. Georgescu, Ghamdan Al-Eryani, Allison Brookhart et al.· bioRxiv· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
