Biology subjects

Shaw, T. I.

Publications and source records attributed to Shaw, T. I..

5 recordsLinked to original sources

bioRxiv2026

BCL11B targeting in tumor CD8+ T cells amplifies anti-tumor response by blocking exhaustion while promoting stemness and cytotoxicity

Tumor infiltrating CD8+ T cells (TILs) progress to a state of terminal exhaustion (Ttex) which have impaired functionality and are nonrenewable. However their precursors (Tpex) are renewable and can generate efficient effector cells. We started from the observation that melanoma patients undergoing therapy with checkpoint inhibitors show increased survival when their T cells have low BCL11B mRNA. In line with this, ablation of Bcl11b in CD8+ TILs conferred a superior anti-tumor response in murine melanoma and ovarian cancer models. Bcl11b KO TILs failed to progress to the Ttex state and retained elevated stemness. Bcl11b exerted its role by repressing expression of essential transcription factors (TF) controlling stemness, and conversely by promoting expression of exhaustion-associated TFs and inhibitory receptor genes, through complex epigenetic control. In addition, Bcl11b KO CD8+ T cells showed increased Ag-specific cytolytic activity and elevated Gzmb and Prf1 proteins, but no increase in their mRNAs, however presented higher expression of genes with role in translation. Furthermore, CRISPR-CAS9-mediated deletion of BCL11B in human TILs from a patient with poor response to adoptive cell therapy with autologous TILs, improved their cytolytic activity and promoted expression of the stemness-associated TF TCF1, underlying its potential therapeutic use. HIGHLIGHTS- Adoptive transfer of Bcl11b KO CD8+ TILs surpasses WT in tumor burden reduction - Bcl11b ablation reprograms TILs and impairs the progression to Ttex state - Bcl11b KO CD8+ T cells have elevated cytotoxicity and kill only Ag-MHCI targets - BCL11B deletion in nonresponder ACT-TIL improves cytolytic activity and elevates TCF1 GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=64 SRC="FIGDIR/small/742578v1_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@c3b965org.highwire.dtl.DTLVardef@1c09d75org.highwire.dtl.DTLVardef@a19748org.highwire.dtl.DTLVardef@d2fd6b_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2024

Effector T Cells under Hypoxia have an Altered Transcriptome Similar to Tumor-Stressed T Cells Found in Non-Responsive Melanoma Patients

BackgroundIn the Tumor Microenvironment (TME), hypoxia stands as a significant factor that modulates immune responses, especially those driven by T cells. As T cell-based therapies often fail to work in solid tumors, this study aims to investigate the effects of hypoxia on T cell topo-distribution in the TME, gene expression association with T cell states, and clinical responses in melanoma. MethodsTo generate detailed information on tumor oxygenation and T cell accessibility, we utilized mathematical modeling of human melanoma tissue microarrays (TMAs) that incorporate oxygen supply from vessels, intratumoral diffusion, and cellular uptake. We created tumor maps and derived plots showing the fraction of CD4 and CD8 T cells against the distance to the nearest vessel and oxygen pressure. To assess their function and transcriptional changes caused by hypoxia, effector T cells were generated and cultured under hypoxia (0.5% oxygen) or normoxia (21% oxygen). The T cell hypoxia-transcriptional signature was compared against datasets from msigDB, iATLAS (clinical trials of melanoma patients treated with immune checkpoint inhibitors), ORIEN AVATAR (real-world melanoma patients treated with immune checkpoint inhibitors, ICIs), and a single-cell atlas of tumor-infiltrating lymphocytes (TILs). ResultsWe made three specific observations: 1) in melanoma T cells preferentially accumulated in oxygenated areas close to blood vessels (50-100 micrometers from the vasculature in the regions of high oxygen availability) but not in hypoxic areas far from blood vessels. 2) Our analysis confirmed that under hypoxia, T cell functions were significantly reduced compared to normoxic conditions and accompanied by a unique gene signature. Furthermore, this hypoxic gene signature was prevalent in resting and non-activated T cells. Notably and clinically relevant, the hypoxic T cell gene set was found to correlate with reduced Overall Survival (OS) and reduced progression-free survival (PFS) in melanoma patients, which was more pronounced in non-responder patients undergoing ICI therapy. 3) Finally, compared with a single-cell atlas of tumor-infiltrating T cells, our hypoxia signature aligned with a population of cells at a state termed stress response state (TSTR). ConclusionOur study highlights the critical role of hypoxia in shaping T cell distribution and its correlation with clinical outcomes in melanoma. We revealed a preferential accumulation of T cells in oxygenated areas. Moreover, hypoxic T cells develop a distinct hypoxic gene signature prevalent in resting, non-activated T cells and TSTR that was also associated with poorer outcomes, particularly pronounced among non-responders to ICIs. Key MessagesWhat is already known on this topic: Hypoxia significantly impairs T cell functions, including reduced proliferation and cytokine production. This impairment may contribute to immune evasion and resistance to immune therapies, such as ICIs, adoptive transfer of TILs, and Chimeric Antigen Receptor (CAR) T cells. Despite the established impact of hypoxia on T cell function, the precise spatial distribution of T cells in relation to oxygen availability within the TME and how this affects clinical outcomes in melanoma patients remains unclear. Additionally, the specific transcriptional changes in T cells induced by hypoxia and their prevalence in different T cell states, as well as the implications for resistance to ICIs, have not been thoroughly investigated. Understanding these aspects is crucial for developing targeted therapies to overcome hypoxia-induced resistance and improve immunotherapy efficacy. What this study adds: This study elucidates the profound impact of hypoxia on T cells in melanoma. Our findings reveal that T cells accumulate in well-oxygenated regions near blood vessels, whereas hypoxic conditions significantly impair their proliferation and cytokine production. By addressing the transcriptional changes induced by hypoxia, we demonstrated its prevalence in resting and non-activated T cells and TSTR. Moreover, we found that hypoxia is associated with shorter OS and PFS in melanoma patients, particularly in non-responders to ICIs. This research highlights the critical role of hypoxia in modulating T cell spatial behavior, contributing to immune evasion and poor clinical outcomes in melanoma. How this study might affect research, practice, or policy: The findings emphasizes hypoxias critical role in modulating T cell behavior and its potential as a biomarker for treatment outcomes. These insights could inform the development of therapeutic strategies aimed at improving T cell function in hypoxic TMEs, thereby enhancing the efficacy of immunotherapies for melanoma and other solid tumors. Additionally, the studys results may influence policies regarding the evaluation and implementation of combination therapies that target hypoxia to improve patient outcomes.

immunology↗

bioRxiv2023

BERLIN: Basic Explorer for single-cell RNAseq analysis and cell Lineage Determination.

Single-cell RNA sequencing has revolutionized the study of immuno-oncology, cancer biology, and developmental biology by enabling the joint characterization of gene expression and cellular heterogeneity in a single platform. As of July 2023, the Gene Expression Omnibus now contains over 4000 published single-cell data sets, providing an invaluable opportunity for reanalysis to identify new cell types or cellular states as well as their defining transcriptional programs. To facilitate the reprocessing of these public datasets, we have devised a single-cell RNA sequencing analysis framework for data retrieval, quality control, expression normalization, dimension reduction, cell clustering, and data integration. Additionally, we have developed a Shiny App visualization platform that enables the exploration of gene expression, cell type annotations, and cell lineages through a user interface. We performed a re-analysis of single-cell RNAseq data generated from acute myeloid leukemia and tumor-reactive lymphocytes and found our pipeline to faithfully recapitulated the cell type assignment as well as expected lineage trajectories. Altogether, we present BERLIN, a single-cell RNAseq analysis pipeline that facilitates the integration and public dissemination of results from the reanalysis.

bioinformatics↗

bioRxiv2022

CBFA2T3-GLIS2-dependent pediatric acute megakaryoblastic leukemia is driven by GLIS2 and sensitive to Navitoclax

Pediatric acute megakaryoblastic leukemia (AMKL) is an aggressive, uncurable blood cancer associated with poor therapeutic response and high mortality. We developed CBFA2T3-GLIS2-driven mouse models of AMKL that recapitulate the phenotypic and transcriptional signatures of the human disease. We show that an activating Ras mutation, which occurs in human AMKL, increased the penetrance and decreased the latency of CBF2AT3-GLIS2-driven AMKL. CBFA2T3-GLIS2 and GLIS2 modulate similar transcriptional networks. We uncover the dominant oncogenic properties of GLIS2, which trigger AMKL in cooperation with oncogenic Ras. We find that both CBFA2T3-GLIS2 and GLIS2 alter the expression of numerous BH3-only proteins, causing AMKL cell sensitivity to the BCL-2 inhibitor navitoclax both in vitro and in vivo, suggesting a novel therapeutic option for pediatric patients suffering from CBFA2T3-GLIS2-driven AMKL. Key pointsGLIS2 cooperates with activated Nras to promote the development of acute megakaryoblastic leukemia. CBFA2T3-GLIS2 and GLIS2 alter the expression of BCL2 family members rendering AMKL cells sensitive to navitoclax.

cancer biology↗

bioRxiv2019

Adapterama II: Universal amplicon sequencing on Illumina platforms (TaggiMatrix)

Next-generation sequencing (NGS) of amplicons is used in a wide variety of contexts. Most NGS amplicon sequencing remains overly expensive and inflexible, with library preparation strategies relying upon the fusion of locus-specific primers to full-length adapter sequences with a single identifying sequence or ligating adapters onto PCR products. In Adapterama I, we presented universal stubs and primers to produce thousands of unique index combinations and a modifiable system for incorporating them into Illumina libraries. Here, we describe multiple ways to use the Adapterama system and other approaches for amplicon sequencing on Illumina instruments. In the variant we use most frequently for large-scale projects, we fuse partial adapter sequences (TruSeq or Nextera) onto the 5 end of locus-specific PCR primers with variable-length tag sequences between the adapter and locus-specific sequences. These fusion primers can be used combinatorially to amplify samples within a 96-well plate (eight forward primers + 12 reverse primers yield 8 x 12 = 96 combinations), and the resulting amplicons can be pooled. The initial PCR products then serve as template for a second round of PCR with dual-indexed iTru or iNext primers (also used combinatorially) to make full-length libraries. The resulting quadruple-indexed amplicons have diversity at most base positions and can be pooled with any standard Illumina library for sequencing. The number of sequencing reads from the amplicon pools can be adjusted, facilitating deep sequencing when required or reducing sequencing costs per sample to an economically trivial amount when deep coverage is not needed. We demonstrate the utility and versatility of our approaches with results from six projects using different implementations of our protocols. Thus, we show that these methods facilitate amplicon library construction for Illumina instruments at reduced cost with increased flexibility. A simple web page to design fusion primers compatible with iTru primers is available at: http://baddna.uga.edu/tools-taggi.html. A fast and easy to use program to demultiplex amplicon pools with internal indexes is available at: https://github.com/lefeverde/Mr_Demuxy.

genomics↗