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Elezkurtaj, S.

Publications and source records attributed to Elezkurtaj, S..

5 recordsLinked to original sources

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↗

A new clustering approach identifies tumor-specific common TCRs with pan-cancer reactivity

Tumor-specific T-cells are key in combating cancer as shown in adoptive cell therapy with tumor infiltrating lymphocytes (TILs) and checkpoint inhibitor therapy. Studies in many types of cancer have shown that preexisting tumor reactive T-cells are not only tumor-but typically also patient-specific, requiring personalized treatment options. For viral infections, public T-cell receptors (TCRs) with substantial sequence homologies suggest shared immune-dominant targets in human leucocyte antigen (HLA)-matched individuals. We hypothesized that also in the complex TCR repertoires of tumors subsets of tumor-specific TCRs exist that can be found in different patients with identical or near identical TCRs. This paper presents a TCR-V(D)J-sequence clustering approach identifying clusters of tumor-specific common TCRs mainly from TILs of non-small cell lung cancer (NSCLC) patients. Using two TCR-clusters as examples, we show that T-cells engineered genetically to only express those common TCRs recognized HLA-matched allogeneic tumor cell lines in a cluster typical manner. Recognition of allogeneic tumors was dependent on the HLA allele inferred by the cluster and could be blocked by HLA antibodies. In addition to NSCLC, TCR repertoire analyses in pancreatic ductal adenocarcinoma and a smaller number of breast and colorectal cancer samples revealed TCRs highly homologous or even identical to NSCLC cluster TCRs. TCR-T cells expressing TCRs from these tumors assigned to a specific cluster recognized allogeneic tumor lines in the expected cluster-typical manner. These findings suggest a pan-cancer therapeutic potential of tumor-specific common TCRs.

immunology↗

Osteopontin in colitis-associated carcinoma

Patients with ulcerative colitis (UC) and Crohns disease (CD) face a lifelong risk of developing colitis-associated carcinoma (CAC). Current insights into CAC development originate from murine CAC models, while human CAC studies primarily focus on mutational analysis of patient samples. Although the mutational landscape reveals distinct patterns and frequencies compared to colorectal cancer, it falls short in elucidating the inflammatory mechanisms of CAC development. Consequently, we adopted a multi-omics approach to unravel CAC carcinogenesis from an immunological perspective. Our data revealed a robust upregulation of SPP1 gene in CAC at both RNA and protein levels, expressed by CD68+ macrophages. In vitro OPN stimulation demonstrated no direct effect on intestinal epithelial organoids. However, the mutually exclusive spatial location of SPP1/OPN+ macrophages and CD8+ T cells suggests a crucial indirect role of SPP1/OPN in mediating an immunosuppressive tumour microenvironment.

cancer biology↗

VoltRon: A Spatial Omics Analysis Platform for Multi-Resolution and Multi-omics Integration using Image Registration

The growing number of spatial omic technologies have created a demand for computational tools capable of managing, storing, and analyzing spatial datasets with multiple modalities and spatial resolutions. Meanwhile, computer vision is becoming an integral part of processing spatial data readouts where image registration and spatial data alignment of tissue sections are essential prior to data integration. Hence, there is a need for computational platforms that analyze data across spatial datasets with diverse resolutions as well as those that manipulate and process images of microanatomical tissue structures. To this end, we have developed VoltRon, a novel R package for spatial omics analysis with a unique data structure that accommodates data readouts with many levels of spatial resolutions (i.e., multi-resolution) including regions of interest (ROIs), spots, single cells, and even subcellular entities such as molecules. To connect and integrate these spatially diverse omic profiles, VoltRon accounts for spatial organization of tissue blocks (samples), layers (sections) and assays given a multi-resolution collection of spatial data readouts. An easy-to-use computer vision toolbox, OpenCV, is fully embedded in VoltRon that allows users to both automatically and manually register spatial coordinates across adjacent layers for data transfer without the need for external software tools. VoltRon is implemented in the R programming language and is freely available at https://github.com/BIMSBbioinfo/VoltRon.

bioinformatics↗

Olfactory transmucosal SARS-CoV-2 invasion as port of Central Nervous System entry in COVID-19 patients

The newly identified severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes COVID-19, a pandemic respiratory disease presenting with fever, cough, and often pneumonia. Moreover, thromboembolic events throughout the body including the central nervous system (CNS) have been described. Given first indication for viral RNA presence in the brain and cerebrospinal fluid and in light of neurological symptoms in a large majority of COVID-19 patients, SARS-CoV-2-penetrance of the CNS is likely. By precisely investigating and anatomically mapping oro- and pharyngeal regions and brains of 32 patients dying from COVID-19, we not only describe CNS infarction due to cerebral thromboembolism, but also demonstrate SARS-CoV-2 neurotropism. SARS-CoV-2 enters the nervous system via trespassing the neuro-mucosal interface in the olfactory mucosa by exploiting the close vicinity of olfactory mucosal and nervous tissue including delicate olfactory and sensitive nerve endings. Subsequently, SARS-CoV-2 follows defined neuroanatomical structures, penetrating defined neuroanatomical areas, including the primary respiratory and cardiovascular control center in the medulla oblongata.

neuroscience↗