Biology subjects

Krieger, T. G.

Publications and source records attributed to Krieger, T. G..

6 recordsLinked to original sources

bioRxiv2026

Tumor-versus-non-tumor T cell enrichment supported by single-cell and spatial phenotyping enables antigen-agnostic prioritization of candidate tumor-reactive TCRs

Introduction: Tumor-reactive T cell receptors (TCRs) are promising candidates for the manufacturing of safe and effective adoptive TCR-T cell therapies, but their efficient identification remains a major challenge. We previously established an antigen-agnostic TCR-repertoire analysis workflow that prioritizes candidate TCRs based on intratumoral clonal expansion and high tumor-to-non-tumor (T/N) frequency ratios. Here, we investigated whether T/N-selected clonotypes show independent transcriptional and spatial features consistent with tumor association. Methods: Bulk and single-cell TCR repertoire sequencing of paired tumor and adjacent non-tumor tissues was used to identify clonotypes with high T/N ratios across 15 cancer cases, comprising six non-small cell lung cancers, five pancreatic cancers, two breast cancers, and two colorectal cancers. Candidate clonotypes were further characterized by paired single-cell TCR and gene expression profiling and, in two PDAC cases, by Xenium spatial transcriptomics to assess their cellular phenotype, spatial localization, and proximity to malignant cells. Results: High T/N ratios consistently marked T cell clonotypes with features of tumor reactivity across the studied solid tumor entities. The analysis included Cluster-A, a lead T cell cluster comprising highly similar TCRs shared among 14 HLA-A*02:01-positive patients in the present cohort. Cluster-A clonotypes were consistently enriched in tumor relative to matched non-tumor tissue, and previous functional studies demonstrated tumor recognition by Cluster-A members. In a focused analysis of a pancreatic cancer case, Cluster-A CD8 T cells were selectively detected in tumor tissue, preferentially localized near malignant epithelial cells, and displayed an antigen-experienced effector-memory phenotype with prominent expression of granzymes A and K (GZMA/GZMK). Importantly, in another PDAC case that lacked Cluster-A clonotypes, these features extended to independent clonotypes, revealing a continuous tumor-association axis in which increasing T/N ratios were associated with progressively closer localization to malignant cells and increased GZMA/GZMK expression. Thus, repertoire enrichment, spatial tumor proximity, and effector-associated transcriptional states converged across independent tumor-enriched clonotypes. Outlook: These findings support the T/N ratio as a robust primary criterion for identifying candidate tumor-reactive TCRs. Integration of single-cell and spatial transcriptomics provides supporting biological evidence of tumor association and a framework for prioritizing therapeutic TCR candidates when functional validation is limited.

immunology↗

bioRxiv2022

Transcriptionally defined morphological subtypes of pancreatic ductal adenocarcinoma

Tumour heterogeneity remains a major obstacle to effective and precise therapy for pancreatic ductal adenocarcinoma (PDAC), the most common pancreatic cancer. Several transcriptional subtypes of PDAC with differential prognosis have been described, but they co-occur within tumours and are difficult to distinguish in routine clinical workflows. To investigate the relationship between transcriptional PDAC subtypes, local tissue morphology and the tumour microenvironment, we employed in situ sequencing to profile single cells in their spatial tissue context. We identify five transcriptional subtypes of PDAC cells occurring in three distinct morphological patterns, including secretory tumour cell monolayers, invasive tumour cells with high expression of cell adhesion molecules CEACAM5 and CEACAM6, and spatially distributed tumour cells associated with inflammatory-type fibroblasts. Analysis of bulk RNA-sequencing datasets of the TCGA-PAAD and PACA-AU cohorts according to these spatio-transcriptional subtypes confirmed their prognostic significance. Our results thus indicate an automatable substratification based on spatially-resolved transcriptomics of PDAC and identify distinct subtypes of classical PDAC, representing most cases of this devastating malignancy.

cancer biology↗

bioRxiv2020

Single-cell analysis of patient-derived PDAC organoids reveals cell state heterogeneity and a conserved developmental hierarchy

Pancreatic ductal adenocarcinoma (PDAC) is projected to be the second leading cause of cancer mortality by 2030. Bulk transcriptomic analyses have distinguished classical pancreatic tumors from basal-like tumors with more aggressive clinical behaviour. We derived PDAC organoids from primary tumors of 18 patients, together with two matched samples from liver metastases. By single-cell RNA sequencing, we show that PDAC organoids consist of ductal cells with patient-specific expression of several gene groups, including genes which encode cell surface proteins. We report classical and basal-like cells coexisting within single primary tumors or metastases, with greater intratumor subtype heterogeneity linked to higher tumor grade. Single-cell transcriptome analysis of PDAC organoids and primary PDAC identified distinct tumor cell states shared across patients, including a cycling progenitor cell state and a differentiated secretory state. We show that these cell states are connected by a differentiation hierarchy, with classical subtype cells concentrated at the endpoint of this hierarchy. In an imaging-based drug screen, expression of classical subtype genes also correlates with better response to clinical drugs. Our results thus uncover a functional hierarchy of PDAC cell states linked to transcriptional tumor subtypes, and support the use of PDAC organoids as a clinically relevant model for in vitro studies of tumor heterogeneity.

cancer biology↗

bioRxiv2020

Automated screening by 3D light-sheet microscopy with high spatial and temporal resolution reveals mitotic phenotypes

3D cell cultures enable the in vitro study of dynamic biological processes such as the cell cycle, but their use in high-throughput screens remains impractical with conventional fluorescent microscopy. Here, we present a screening workflow for the automated evaluation of mitotic phenotypes in 3D cell cultures by light-sheet microscopy. After sample preparation by a liquid handling robot, three-dimensional cell spheroids are imaged for 24 hours in toto with a dual inverted selective plane illumination (diSPIM) microscope with a much improved signal-to-noise ratio, higher imaging speed, isotropic resolution and reduced light exposure compared to a spinning disc confocal microscope. A dedicated high-content image processing pipeline implements convolutional neural network based phenotype classification. We illustrate the potential of our approach by siRNA knock-down and epigenetic modification of 28 mitotic target genes for assessing their phenotypic role in mitosis. By rendering light-sheet microscopy operational for high-throughput screening applications, this workflow enables target gene characterization or drug candidate evaluation in tissue-like 3D cell culture models.

cell biology↗

bioRxiv2019

Modeling glioblastoma invasion using human brain organoids and single-cell transcriptomics

Glioblastoma multiforme (GBM) are devastating neoplasms with high invasive capacity. GBM has been difficult to study in vitro. Therapeutic progress is also limited by cellular heterogeneity within and between tumors. To address these challenges, we present an experimental model using human cerebral organoids as a scaffold for patient-derived glioblastoma cell invasion. By tissue clearing and confocal microscopy, we show that tumor cells within organoids extend a network of long microtubes, recapitulating the in vivo behavior of GBM. Single-cell RNA-seq of GBM cells before and after co-culture with organoid cells reveals transcriptional changes implicated in the invasion process that are coherent across patient samples, indicating that GBM cells reactively upregulate genes required for their dispersion. Functional therapeutic targets are identified by an in silico receptor-ligand pairing screen detecting potential interactions between GBM and organoid cells. Taken together, our model has proven useful for studying GBM invasion and transcriptional heterogeneity in vitro, with applications for both pharmacological screens and patient-specific treatment selection at a time scale amenable to clinical practice.

cancer biology↗

bioRxiv2019

Mutations in thyroid hormone receptor α1 cause premature neurogenesis and progenitor cell depletion in human cortical development

Mutations in the thyroid hormone receptor 1 gene (THRA) have recently been identified as a cause of intellectual deficit in humans. Patients present with structural abnormalities including microcephaly, reduced cerebellar volume and decreased axonal density. Here, we show that directed differentiation of THRA mutant patient-derived iPSCs to forebrain neural progenitors is markedly reduced, but mutant progenitor cells can generate deep and upper cortical layer neurons and form functional neuronal networks. Quantitative lineage tracing shows that THRA mutation-containing progenitor cells exit the cell cycle prematurely, resulting in reduced clonal output. Using a novel micropatterned chip assay, we find that spatial self-organisation of mutation-containing progenitor cells is impaired, consistent with downregulated expression of cell-cell adhesion genes. These results reveal for the first time that thyroid hormone receptor 1 is required for normal neural progenitor cell proliferation and organisation in human cerebral cortical development. They also exemplify novel quantitative approaches for studying neurodevelopmental disorders using patient-derived cells in vitro.

developmental biology↗