Biology subjects

Wilmott, J. S.

Publications and source records attributed to Wilmott, J. S..

7 recordsLinked to original sources

bioRxiv2025

AdSI-MIMO: Adaptive stain imputation with multi-input and multi-output learning for multiplex immunofluorescence imaging

Multiplex immunofluorescence (mIF) imaging plays a crucial role in studying multiple biomarkers and their interactions within the tumour microenvironment. However, acquiring mIF images that include all desired biomarkers presents significant challenges due to the need for specialised equipment and costly reagents, which increase technical complexity, time and expense. Stain imputation offers a promising solution by synthesising target biomarker images using generative models, thereby eliminating the need for additional staining procedures. Existing deep learning-based stain imputation methods lack flexibility in generating multiple biomarker images from various input combinations. To overcome this limitation, we propose AdSI-MIMO, a novel stain imputation framework for mIF images. Our method features a multibranch deep learning architecture capable of generating multiple outputs and incorporates an adaptive progressive masking strategy to accommodate the varying combinations of input biomarkers. This approach not only improves the quality of the generated biomarker images, but also eliminates the need to train separate models for each target biomarker. We evaluated AdSI-MIMO using two datasets, including a local dataset comprising mIF images from 257 melanoma patients and a public dataset of 55 urothelial carcinoma samples. Our method achieved substantial improvements over state-of-the-art methods, particularly in the imputation of key T-cell and activation biomarkers, such as CD8 and PD-L1. Specifically, across both public and proprietary datasets, our model achieved a 18.4% improvement in Pearson Correlation Coefficient (Pearson-r) for CD8 imputation and a 48.1% improvement for PD-L1 imputation under various input biomarker configurations on the external test set.

bioinformatics↗

bioRxiv2022

Spatial mapping of human lung tissue reveals granuloma diversity and histopathological superstructure in tuberculosis

The histopathological hallmark of tuberculosis (TB) is the formation of immune cell enriched aggregates called granulomas, but the scope of granuloma heterogeneity in human TB is unknown. By spatially mapping individual immune cells across large regions of TB lung tissue, we report that in addition to necrotizing granulomas, the human TB lung contains abundant non-necrotizing leukocyte aggregates surrounding areas of necrotizing tissue. These cellular lesions were more diverse in composition than necrotizing lesions and could be stratified into four general classes based on cellular composition and spatial distribution of B cells and macrophages, indicating there are foci of distinct immune reactions adjacent to necrotizing granulomas. We further show that the specific cellular composition of non-necrotizing structures correlates with their proximity to necrotizing lesions. Together, our study shows that during tuberculosis diseased lung tissue develops a histopathological superstructure comprising at least four different types of non-necrotizing cellular aggregates organized as satellites of necrotizing granulomas.

immunology↗

bioRxiv2020

Anatomic position determines oncogenic specificity in melanoma

Oncogenic alterations to DNA are not transforming in all cellular contexts1,2. This may be due to pre-existing transcriptional programs in the cell of origin. Here, we define anatomic position as a major determinant of why cells respond to specific oncogenes. Cutaneous melanoma arises throughout the body, whereas the acral subtype arises on the palms of the hands, soles of the feet, or under the nails3. We sequenced the DNA of cutaneous and acral melanomas from a large cohort of human patients and found a specific enrichment for BRAF mutations in cutaneous melanoma but CRKL amplifications in acral melanoma. We modeled these changes in transgenic zebrafish models and found that CRKL-driven tumors predominantly formed in the fins of the fish. The fins are the evolutionary precursors to tetrapod limbs, indicating that melanocytes in these acral locations may be uniquely susceptible to CRKL. RNA profiling of these fin/limb melanocytes, compared to body melanocytes, revealed a positional identity gene program typified by posterior HOX13 genes. This positional gene program synergized with CRKL to drive tumors at acral sites. Abrogation of this CRKL-driven program eliminated the anatomic specificity of acral melanoma. These data suggest that the anatomic position of the cell of origin endows it with a unique transcriptional state that makes it susceptible to only certain oncogenic insults.

cancer biology↗

bioRxiv2020

The deacylase SIRT5 supports melanoma viability by regulating chromatin dynamics

Cutaneous melanoma remains the most lethal skin cancer, and ranks third among all malignancies in terms of years of life lost. Despite the advent of immune checkpoint and targeted therapies, only roughly half of patients with advanced melanoma achieves a durable remission. SIRT5 is a member of the sirtuin family of protein deacylases that regulate metabolism and other biological processes. Germline Sirt5 deficiency is associated with mild phenotypes in mice. Here we show that SIRT5 is required for proliferation and survival across all cutaneous melanoma genotypes tested, as well as uveal melanoma, a genetically distinct melanoma subtype that arises in the eye and is incurable once metastatic. Likewise, SIRT5 is required for efficient tumor formation by melanoma xenografts and in an autochthonous mouse Braf;Pten-driven melanoma model. Via metabolite and transcriptomic analyses, we find that SIRT5 is required to maintain histone acetylation and methylation levels in melanoma cells, thereby promoting proper gene expression. SIRT5-dependent genes notably include MITF, a key lineage-specific survival oncogene in melanoma, and the c-MYC proto-oncogene. SIRT5 may represent a novel, druggable genotype-independent addiction in melanoma.

cancer biology↗

bioRxiv2020

Cryopreservation of human cancers conserves tumour heterogeneity for single-cell multi-omics analysis

BackgroundHigh throughput single-cell RNA sequencing (scRNA-Seq) has emerged as a powerful tool for exploring cellular heterogeneity amongst complex human cancers. scRNA-Seq studies using fresh human surgical tissue is logistically difficult, precludes histopathological triage of samples and limits the ability to perform batch processing. This hinderance can often introduce technical biases when integrating patient datasets and increase experimental costs. Although tissue preservation methods have been previously explored to address such issues, it is yet to be examined on complex human tissues, such as solid cancers, and on high throughput scRNA-Seq platforms. ResultsWe show that the viable cryopreservation of human cancers provides high quality single-cell transcriptomes using the Chromium 10X platform. We sequenced a total of [~]120,000 cells from fresh and cryopreserved replicates across three breast cancers, two prostate cancers and a cutaneous melanoma. Importantly, tumour heterogeneity identified from fresh tissues was largely conserved in cryopreserved replicates. We show that sequencing of single cells prepared from cryopreserved tissue fragments or from cryopreserved cell suspensions is comparable to sequenced cells prepared from fresh tissue, with cryopreserved cell suspensions displaying higher correlations with fresh tissue in gene expression. We then show that cryopreservation had minimal impacts on results of downstream analyses such as biological pathway enrichment. Further, we demonstrate the advantage of cryopreserving whole-cells for immunophenotyping methods such as CITE-Seq, which is impossible using other preservation methods such as single nuclei-sequencing. ConclusionsOur study guides new experimental designs for tissue biobanking for future clinical single-cell RNA sequencing studies.

cancer biology↗

bioRxiv2019

Temporal and spatial modulation of the immune response of the murine Gl261 glioma tumor microenvironment

Glioblastoma, the most aggressive form of glioma, has a 5-year survival rate of <5%. While radiation and immunotherapies are routinely studied in the murine Gl261 glioma model, little is known about its inherent immune response. This study quantifies the temporal and spatial localization of immune cell populations and mediators during glioma development. Eight-week old male C57Bl/6 mice were orthotopically inoculated with 1x106 Gl261 cells and tumor morphology, local and systemic immune cell populations, and plasma cytokines/chemokines assessed at Day-0, 1, 3, 7, 14, and 21 post-inoculation by magnetic resonance imaging, chromogenic immunohistochemistry, multiplex immunofluorescent immunohistochemistry, flow cytometry and multiplex immunoassay respectively. From Day-3 tumors were distinguishable with >30% Ki67 and increased tissue vascularization (p<0.05). Increasing tumor proliferation/malignancy and vascularization were associated with significant temporal changes in immune cell populations within the tumor (p<0.05) and systemic compartments (p=0.02 to p<0.0001). Of note, at Day-14 16/24 plasma cytokine/chemokines levels decreased coinciding with an increase in tumor cytotoxic T cells, natural killer and natural killer/T cells. Data derived provide baseline characterization of the local and systemic immune response during glioma development. They reveal that type II macrophages and myeloid-derived suppressor cells are more prevalent in tumors than regulatory T cells, highlighting these cell types for further therapeutic exploration.

cancer biology↗

bioRxiv2018

Epigenetic Profiling for the Molecular Classification of Metastatic Brain Tumors

Optimal treatment of brain metastases is often hindered by limitations in diagnostic capabilities. To meet these challenges, we generated genome-scale DNA methylomes of the three most frequent types of brain metastases: melanoma, breast, and lung cancers (n=96). Using supervised machine learning and integration of multiple DNA methylomes from normal, primary, and metastatic tumor specimens (n=1,860), we unraveled epigenetic signatures specific to each type of metastatic brain tumor and constructed a three-step DNA methylation-based classifier (BrainMETH) that categorizes brain metastases according to the tissue of origin and therapeutically-relevant subtypes. BrainMETH predictions were supported by routine histopathologic evaluation. We further characterized and validated the most predictive genomic regions in a large cohort of brain tumors (n=165) using quantitative methylation-specific PCR. Our study highlights the importance of brain tumor-defining epigenetic alterations, which can be utilized to further develop DNA methylation profiling as a critical tool in the histomolecular stratification of patients with brain metastases.

cancer biology↗