Biology subjects

Bueno, R.

Publications and source records attributed to Bueno, R..

9 recordsLinked to original sources

bioRxiv2024

Comprehensive multi-site profiling of the malignant pleural mesothelioma micro-environment identifies candidate molecular determinants of histopathologic type

Pleural mesothelioma (PM) comprises sarcomatoid, epithelioid and biphasic histologic subtypes. Bulk PM RNA-sequencing identifies a histology-associated molecular gradient with features of epithelial-mesenchymal (EM) transition but cannot parse malignant, stromal, and immune tumor components. The mechanisms driving PM malignant cell phenotype and associated histology is not well-characterized. Here, we use single-cell RNA-sequencing (scRNA-seq) paired with exome, bulk RNA-sequencing, and histologic analysis of adjacent samples to characterize malignant cell EM state, parse the tumor microenvironment (TME), and identify candidate drivers of PM cell fate. We observe EM variation in malignant cells analogous to bulk samples. We characterize epithelioid and sarcomatoid malignant cell programs and identify a new uncommitted malignant cell EM phenotype enriched in biphasic histology samples. Using inferred CNVs we observe that single individual PM clones consist of cells exhibiting all three EM cell states. We find that distinct non-malignant microenvironments associated with tumors consisting of mostly cells in each state, and identify WNT inhibition, GAS6-AXL, and HBEGF-EGFR signaling as pathways associated with distinct EM cell states. These findings provide deeper insight into the molecular drivers of PM malignant cells and identify non-malignant cell signals as potential EMT and growth drivers in PM.

cancer biology↗

bioRxiv2023

A cellular and spatial atlas of TP53-associated tissue remodeling in lung adenocarcinoma

TP53 is the most frequently mutated gene across many cancers and is associated with shorter survival in lung adenocarcinoma (LUAD). To define how TP53 mutations affect the LUAD tumor microenvironment (TME), we constructed a multi-omic cellular and spatial tumor atlas of 23 treatment-naive human lung tumors. We found that TP53-mutant (TP53mut) malignant cells lose alveolar identity and upregulate highly proliferative and entropic gene expression programs consistently across resectable LUAD patient tumors, genetically engineered mouse models, and cell lines harboring a wide spectrum of TP53 mutations. We further identified a multicellular tumor niche composed of SPP1+ macrophages and collagen-expressing fibroblasts that coincides with hypoxic, pro-metastatic expression programs in TP53mut tumors. Spatially correlated angiostatic and immune checkpoint interactions, including CD274-PDCD1 and PVR-TIGIT, are also enriched in TP53mut LUAD tumors, which may influence response to checkpoint blockade therapy. Our methodology can be further applied to investigate mutation-specific TME changes in other cancers.

cancer biology↗

bioRxiv2023

Mitigation of chromosome loss in clinical CRISPR-Cas9-engineered T cells

CRISPR-Cas9 genome editing has enabled advanced T cell therapies, but occasional loss of the targeted chromosome remains a safety concern. To investigate whether Cas9-induced chromosome loss is a universal phenomenon and evaluate its clinical significance, we conducted a systematic analysis in primary human T cells. Arrayed and pooled CRISPR screens revealed that chromosome loss was generalizable across the genome and resulted in partial and entire loss of the chromosome, including in pre-clinical chimeric antigen receptor T cells. T cells with chromosome loss persisted for weeks in culture, implying the potential to interfere with clinical use. A modified cell manufacturing process, employed in our first-in-human clinical trial of Cas9-engineered T cells,1 dramatically reduced chromosome loss while largely preserving genome editing efficacy. Expression of p53 correlated with protection from chromosome loss observed in this protocol, suggesting both a mechanism and strategy for T cell engineering that mitigates this genotoxicity in the clinic.

cell biology↗

bioRxiv2022

Modular Pooled Discovery of Synthetic Knockin Sequences to Program Durable Cell Therapies

Chronic stimulation can cause T cell dysfunction and limit efficacy of cellular immunotherapies. CRISPR screens have nominated gene targets for engineered T cells, but improved methods are required to compare large numbers of synthetic knockin sequences to reprogram cell functions. Here, we developed Modular Pooled Knockin Screening (ModPoKI), an adaptable platform for modular construction of DNA knockin libraries using barcoded multicistronic adaptors. We built two ModPoKI libraries of 100 transcription factors (TFs) and 129 natural and synthetic surface receptors. Over 20 ModPoKI screens across human TCR and CAR T cells in diverse conditions identified a transcription factor AP4 (TFAP4) construct to enhance long-term T cell fitness and anti-cancer function in vitro and in vivo. ModPoKIs modularity allowed us to generate a [~]10,000-member library of TF combinations. Non-viral knockin of a combined BATF-TFAP4 polycistronic construct further enhanced function in vivo. ModPoKI facilitates discovery of complex gene constructs to program cellular functions. HighlightsO_LIModular pooled knockins of hundreds of TF and surface receptor constructs combined with different antigen receptors C_LIO_LIChronic stimulation screens discover programs to improve T cell persistence C_LIO_LICombinatorial knockin screens with [~]10,000 transcription factor combinations C_LIO_LIBATF-TFAP4 dual knockin construct improves CAR T cell function in vitro and in vivo C_LI

immunology↗

bioRxiv2022

Persistent postnatal migration of interneurons into the human entorhinal cortex

The entorhinal cortex (EC) is a highly-interconnected hub for multisensory integration and memory processing1-3, containing diverse neuronal subtypes4,5 including subpopulations that are uniquely spatially-tuned6,7. Although many spatial and memory functions develop in infancy, it is considered that neurogenesis and neuronal migration to the EC occurs prenatally. Here we show that the postnatal human temporal lobe contains a prominent stream with large chains of young migrating neurons and many individual neurons breaking away directed into the EC. The EC stream forms between the second and third trimesters of prenatal development when the lateral ventricle walls in the temporal lobe collapse, displacing the subventricular zone (SVZ) and dividing radial glia. At birth, the EC stream follows a path of radial glial [fi]bers in the site of the collapsed ventricle. Migratory chains persist up to 11 months postnatally; however, many individually migrating young neurons can still be detected in the EC at 2 years of age and a few isolated cells at 3 years of age. Within the EC at birth, immature neurons are a mixed population expressing markers of the medial ganglionic eminence (MGE) and caudal ganglionic eminence (CGE), but postnatally rapidly become primarily CGE-derived. Using single-nuclei RNAseq we identified these lineages and found that the MGE-derived neurons matured at earlier postnatal ages compared to those derived from the CGE. The CGE interneurons arriving and maturing the latest included subtypes expressing calretinin (CR), reelin (RELN), and vasoactive intestinal protein (VIP) many of which settle in layer II of the entorhinal cortex. This study reveals that the human EC is still being constructed during the first years of life revealing the largest known postnatal stream of migratory neurons in humans. The protracted postnatal arrival of a diverse population of interneurons could contribute to plasticity8,9 and proper excitation-inhibition balance10,11 within these highly connected brain circuits.

neuroscience↗

bioRxiv2022

Tensor decomposition reveals coordinated multicellular patterns of transcriptional variation that distinguish and stratify disease individuals

Tissue- and organism-level biological processes often involve coordinated action of multiple distinct cell types. Current computational methods for the analysis of single-cell RNA-sequencing (scRNA-seq) data, however, are not designed to capture co-variation of cell states across samples, in part due to the low number of biological samples in most scRNA-seq datasets. Recent advances in sample multiplexing have enabled population-scale scRNA-seq measurements of tens to hundreds of samples. To take advantage of such datasets, here we introduce a computational approach called single-cell Interpretable Tensor Decomposition (scITD). This method extracts "multicellular gene expression patterns" that capture how sample-specific expression states of a cell type are correlated with the expression states of other cell types. Such multicellular patterns can reveal molecular mechanisms underlying coordinated changes of different cell types within the tissue, and can be used to stratify individuals in a clinically-relevant and reproducible manner. We first validated the performance of scITD using in vitro experimental data and simulations. We then applied scITD to scRNA-seq data on peripheral blood mononuclear cells (PBMCs) from 115 patients with systemic lupus erythematosus and 56 healthy controls. We recapitulated a well-established pan-cell-type signature of interferon-signaling that was associated with the presence of anti-dsDNA autoantibodies and a disease activity index. We further identified a novel multicellular pattern linked to nephritis, which was characterized by an expansion of activated memory B cells along with helper T cell activation. Our approach also sheds light on ligand-receptor interactions potentially mediating these multicellular patterns. As validation, we demonstrated that these expression patterns also stratified donors from a pediatric SLE dataset by the same phenotypic attributes. Lastly, we found the interferon multicellular pattern and others to be conserved in a COVID-19 dataset, pointing to the presence of both general and disease-specific patterns of inter-individual immune variation. Overall, scITD is a flexible method for exploring co-variation of cell states in multi-sample single-cell datasets, which can yield new insights into complex non-cell-autonomous dependencies that define and stratify disease.

bioinformatics↗

bioRxiv2021

Antibodies to ILT3 abrogate myeloid immunosuppression and enable tumor killing

Tumor myeloid suppressor cells impede response to T cell checkpoint immunotherapy. Immunoglobulin-like transcript 3 (ILT3, gene name, LILRB4) expressed on dendritic cells (DCs) promotes antigen-specific tolerance. Circulating monocytic MDSCs that express ILT3 have been linked to clinical outcomes and a soluble form of ILT3 is elevated in certain cancers. We find that LILRB4 expression is correlated with Gene Expression Profile of T-cell inflamed tumor microenvironment shown to be significantly associated with response to the anti-PD1 antibody pembrolizumab across several tumor types. A potent and selective anti-ILT3 mAb effectively antagonized IL-10 polarization of DCs and enabled T cell priming. In an MLR assay anti-ILT3 combined with pembrolizumab afforded greater CD8+ T cell activation compared to either agent alone. Anti-ILT3 antibodies impaired the acquisition of a suppressive phenotype of monocytes co-cultured with SK-MEL-5 cancer cells, accompanied by a reduction in surface detection of peptidase inhibitor 16, a cis interaction candidate for ILT3. Growth of myeloid cell-abundant SK-MEL-5 tumors was abrogated by ILT3 blockade and remodeling of the immune tumor microenvironment was evident by CyTOF. These data support the testing of anti-ILT3 antibodies for the treatment of a wide range of solid tumors replete with myeloid cells.

cancer biology↗

bioRxiv2021

Longitudinal single-cell epitope and RNA-sequencing reveals the immunological impact of type 1 interferon autoantibodies in critical COVID-19

Type I interferon (IFN-I) neutralizing autoantibodies have been found in some critical COVID-19 patients; however, their prevalence and longitudinal dynamics across the disease severity scale, and functional effects on circulating leukocytes remain unknown. Here, in 284 COVID-19 patients, we found IFN-I autoantibodies in 19% of critical, 6% of severe and none of the moderate cases. Longitudinal profiling of over 600,000 peripheral blood mononuclear cells using multiplexed single-cell epitope and transcriptome sequencing from 54 COVID-19 patients, 15 non-COVID-19 patients and 11 non-hospitalized healthy controls, revealed a lack of IFN-I stimulated gene (ISG-I) response in myeloid cells from critical cases, including those producing anti-IFN-I autoantibodies. Moreover, surface protein analysis showed an inverse correlation of the inhibitory receptor LAIR-1 with ISG-I expression response early in the disease course. This aberrant ISG-I response in critical patients with and without IFN-I autoantibodies, supports a unifying model for disease pathogenesis involving ISG-I suppression via convergent mechanisms.

immunology↗

bioRxiv2019

A single-cell and single-nucleus RNA-seq toolbox for fresh and frozen human tumors

Single cell genomics is essential to chart the complex tumor ecosystem. While single cell RNA-Seq (scRNA-Seq) profiles RNA from cells dissociated from fresh tumor tissues, single nucleus RNA-Seq (snRNA-Seq) is needed to profile frozen or hard-to-dissociate tumors. Each strategy requires modifications to fit the unique characteristics of different tissue and tumor types, posing a barrier to adoption. Here, we developed a systematic toolbox for profiling fresh and frozen clinical tumor samples using scRNA-Seq and snRNA-Seq, respectively. We tested eight tumor types of varying tissue and sample characteristics (resection, biopsy, ascites, and orthotopic patient-derived xenograft): lung cancer, metastatic breast cancer, ovarian cancer, melanoma, neuroblastoma, pediatric sarcoma, glioblastoma, pediatric high-grade glioma, and chronic lymphocytic leukemia. Analyzing 212,498 cells and nuclei from 39 clinical samples, we evaluated protocols by cell quality, recovery rate, and cellular composition. We optimized protocols for fresh tissue dissociation for different tumor types using a decision tree to account for the technical and biological variation between clinical samples. We established methods for nucleus isolation from OCT embedded and fresh-frozen tissues, with an optimization matrix varying mechanical force, buffer, and detergent. scRNA-Seq and snRNA-Seq from matched samples recovered the same cell types and intrinsic expression profiles, but at different proportions. Our work provides direct guidance across a broad range of tumors, including criteria for testing and selecting methods from the toolbox for other tumors, thus paving the way for charting tumor atlases.

genomics↗