Biology subjects

Park, S. M.

Publications and source records attributed to Park, S. M..

4 recordsLinked to original sources

bioRxiv2024

A novel approach to digital characterisation of Tertiary Lymphoid Structures in colorectal cancer

Tertiary Lymphoid Structures (TLS) in cancer tissue are potential sites for the organisation of immune responses to cancer, and correlate positively with improved clinical outcomes for patients including in colorectal cancer (CRC). However it has proven challenging to standardise assessment of TLS due to the highly variable appearances of circumscribed domains of TLS within tissue sections. A recent three-dimensional reconstruction of TLS in CRC tissue showed that TLS are often large, multi-lobular structures, suggesting that assessing TLS across whole sections may be necessary to provide an accurate view of TLS activity in a patients tumour. In a pilot study we therefore used whole slide scans of multiplexed immunofluorescence images to characterise TLS from 22 subjects with CRC. Multiplexed staining for CD20, CD3, CD8, FoxP3 and Ki-67 enabled us to identify B-cells, CD8+ T cells, FoxP3- CD4 T-cells, and Foxp3+ CD4 T cells in all sections, and quantify both the presence of these cell subsets in lymphocytic clusters and their degree of proliferation within those clusters. In total we identified 524 lymphocytic clusters with morphology consistent with TLS. The count of TLS domains varied substantially between samples (from 4 to 100, mean 24) as did the proportion of total section area occupied by TLS (0.2%-7.8%) as well as size, morphology and cellular constituents; reflecting the intersection of the section plane with complex 3-dimensional structures. We quantified proliferation of B-cells and T-cell subsets within TLS domains across entire sections and compared to the canonical approach of counting and phenotyping individual TLS domains. The whole-slide approach proved far simpler than the canonical approach, generating digital summaries across our sample set clearly identifying patients with strikingly different levels of immune activity within their TLS. It also allowed us to demonstrate strong correlations between the proliferation of B-cells within CRC TLS and that of T-cell subsets. In summary we find that whole-section digital quantification of immune cell activity within TLS has major advantages over canonical approaches. Such whole-section approaches should accelerate research into correlations between TLS status and clinical outcomes, and ultimately enable standardised clinical tests based on automated analysis of multiplexed images.

cancer biology↗

bioRxiv2023

Threshold of somatic mosaicism disrupting the brain function

Somatic mosaicism in a fraction of brain cells causes neurodevelopmental disorders, including childhood intractable epilepsy. However, the threshold for somatic mosaicism leading to brain dysfunction is unknown. In this study, we induced various mosaic burdens in mice of focal cortical dysplasia type II (FCD II), featuring mTOR somatic mosaicism and spontaneous behavioral seizures. Mosaic burdens ranged from approximately 1,000 to 40,000 neurons expressing the mTOR mutant in the somatosensory (SSC) or medial prefrontal (PFC) cortex. Surprisingly, just [~]8,000-9,000 neurons expressing the MTOR mutant were sufficient to trigger epileptic seizures. Mutational burden correlated with seizure frequency and onset, with a higher tendency for electrographic inter-ictal spikes and beta- and gamma-frequency oscillations in FCD II mice exceeding the threshold. Moreover, mutation-negative FCD II patients in deep sequencing of their bulky brain tissues revealed somatic mosaicism of mTOR pathway genes as low as 0.07% in resected brain tissues through ultra-deep targeted sequencing (up to 20 million reads). Thus, our study suggests that extremely low levels of somatic mosaicism can contribute to brain dysfunction.

genetics↗

bioRxiv2022

Cyclization studies of Japanese encephalitis virus non-coding RNA terminal regions.

Numerous viruses utilize essential long-range RNA-RNA genome interactions, specifically flaviviruses. Using Japanese encephalitis virus (JEV) as a model system, we computationally predicted and then biophysically validated and characterized its long-range RNA-RNA genomic interaction. Using multiple RNA computation assessment programs, we determine the primary RNA-RNA interacting site among JEV isolates and numerous related viruses. Following in vitro transcription of RNA, we provide, for the first time, characterization of an RNA-RNA interaction using multi-angle light scattering (SEC-MALS) and analytical ultra-centrifugation (AUC). Next, we report the first RNA-RNA interaction study quantified by microscale thermophoresis (MST), demonstrating that the 5 and 3 TR of JEV interact with nM affinity, which is significantly reduced when the conserved cyclization sequence is not present. Furthermore, we perform computational kinetic analyses validating the cyclization sequence as the primary driver of this RNA-RNA interaction. Finally, we examined the 3-dimensional structure of the interaction using small-angle X-ray scattering, revealing a flexible yet stable interaction. This pathway can be adapted and utilized to study various viral and human long-non-coding RNA-RNA interactions, and determine their binding affinities, a critical pharmacological property of designing potential therapeutics. Graphical Abstract O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

biochemistry↗

bioRxiv2019

Single-cell transcriptome analysis revealed a role of the transcription factor TOX in promoting CD8+ T-cell exhaustion in cancer

BackgroundT cells exhibit heterogeneous functional states in the tumor microenvironment. Immune checkpoint inhibitors (ICIs) can reinvigorate only the stem cell-like progenitor exhausted T cells, which suggests that inhibiting the exhaustion progress will improve the efficacy of immunotherapy. Thus, regulatory factors promoting T-cell exhaustion could serve as potential targets for delaying the process and improving ICI efficacy. MethodsWe analyzed the single-cell transcriptome data derived from human melanoma and non-small cell lung cancer (NSCLC) samples and classified the tumor-infiltrating (TI) CD8+ T-cell population based on PDCD1 (PD-1) levels, i.e. PDCD1-high and PDCD1-low cells. Additionally, we identified differentially expressed genes as candidate factors regulating intra-tumoral T-cell exhaustion. The co-expression of candidate genes with immune checkpoint (IC) molecules in the TI CD8+ T cells was confirmed by single-cell trajectory and flow-cytometry analyses. The loss-of-function effect of the candidate regulator was examined by a cell-based knockdown assay. The clinical effect of the candidate regulator was evaluated based on the overall survival and anti-PD-1 responses. ResultsWe retrieved many known factors for regulating T-cell exhaustion among the differentially expressed genes between PDCD1-high and PDCD1-low subsets of the TI CD8+ T cells in human melanoma and NSCLC. TOX was the only transcription factor (TF) predicted in both tumor types. TOX levels tend to increase as CD8+ T cells become more exhausted. Flow-cytometry analysis revealed a correlation between TOX expression and severity of intra-tumoral T-cell exhaustion. TOX knockdown in the human TI CD8+ T cells resulted in downregulation of PD-1, TIM-3, TIGIT, and CTLA-4, which suggests that TOX promotes intra-tumoral T-cell exhaustion by upregulating IC proteins in cancer. Finally, the TOX level in the TI T cells was found to be highly predictive of overall survival and anti-PD-1 efficacy in melanoma and NSCLC. ConclusionsWe predicted the regulatory factors involved in T-cell exhaustion using single-cell transcriptome profiles of human TI lymphocytes. TOX promoted intra-tumoral CD8+ T-cell exhaustion via upregulation of IC molecules. This suggested that TOX inhibition can potentially impede T-cell exhaustion and improve ICI efficacy. Additionally, TOX expression in the TI T cells can be used for patient stratification during anti-tumor treatments, including anti-PD-1 immunotherapy.

cancer biology↗