Biology subjects

Jones, P. S.

Publications and source records attributed to Jones, P. S..

8 recordsLinked to original sources

bioRxiv2026

Single-Cell Analysis of Non-Functioning Gonadotroph Tumors Identifies Lineage Infidelity and Tumor Growth Programs

Non-functioning gonadotroph (NFG) tumors are the most common type of non-functioning pituitary adenomas and can cause significant symptoms due to mass effect. However, the molecular programs underlying NFG tumor growth and their relationship to the normal anterior pituitary gland (APG) are poorly understood. To gain a deeper understanding of NFG tumor biology in the context of the normal APG, we performed single-cell/nucleus RNA-sequencing on 21 NFG tumors and 8 APG samples in human, generating the largest transcriptomic dataset of its kind. Single-cell/nucleus sequencing yielded 77,342, cells from APG samples and 152,649 cells from NFG tumor samples. Differential expression analysis within the APG identified novel marker genes of each neuroendocrine cell type and defined distinct transcriptional signatures of anterior and posterior pituitary stem cell populations. Comparison with tumor transcriptomes revealed that NFG tumor cells most closely resemble gonadotrophs, while also showing significant enrichment of thyrotroph and somatotroph markers. Notably, there was no significant overlap with stem cell markers, suggesting that NFG tumors most likely originate from differentiated gonadotrophs but can take on transcriptional characteristics of other neuroendocrine cell types. Pseudobulk profiling of NFG tumor cells demonstrated that tumor volume is significantly positively correlated with 83 genes including known oncogenes CAD, BRF2, and SOX12, along with 16 zinc finger transcription factors. Lastly, analysis of the tumor microenvironment revealed proportional increases in myeloid, endothelial, and mural cell populations in tumor samples compared to APG samples and highlighted cross talk between tumor and endothelial, mesenchymal, and immune populations via VEGF, PDGF, and MIF signaling pathways respectively. This study identifies novel transcriptomic signatures determining cell type identity in both APG neuroendocrine and NFG tumor cells. Our findings elucidate molecular programs driving NFG lineage infidelity and tumor growth, highlighting candidate predictors of patient outcomes and potential targets for therapeutic intervention.

cancer biology↗

bioRxiv2024

The inactive X chromosome drives sex differences in microglial inflammatory activity in human glioblastoma

Whether an individual is a biological female or male affects cancer risk, but the responsible mechanisms and cell types remain obscure. Glioblastoma multiforme (GBM) is a male-biased cancer that is highly aggressive, and resistant to treatment, with poor patient survival. Dismal prognoses in GBM are due in part to the specialized immune system of the brain, consisting largely of microglia, which regulate GBM development and progression. We hypothesized that microglia function differently in females and males and thereby contribute to the observed male bias in GBM. We sorted TAM-MGs (tumor-associated macrophages - microglia) from human GBMs and low-grade gliomas and performed bulk transcriptomic and epigenomic assays to identify sex-biased gene expression. We used published single-cell transcriptomic data from human GBMs to predict sex-biased TAM-MG interactions with other cell types. We found that female and male TAM-MGs mount different inflammatory responses, with female TAM-MGs displaying stronger interferon signaling and cytotoxic T-cell interactions that should enhance anti-tumor immunity in GBM. We validated these sex-differential inflammatory responses experimentally, and determined that genes on the sex chromosomes, specifically those expressed by Xi (the "inactive" X chromosome), drive these differences. Together, our results suggest that sex-differential TAM-MG inflammatory responses contribute to the higher incidence and mortality of GBM in males.

genomics↗

bioRxiv2023

Glioblastoma-infiltrating CD8+ T cells are predominantly a clonally expanded GZMK+ effector population

Recent clinical trials have highlighted the limited efficacy of T cell-based immunotherapy in patients with glioblastoma (GBM). To better understand the characteristics of tumor-infiltrating lymphocytes (TIL) in GBM, we performed cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) and single-cell RNA sequencing (scRNA-seq) with paired V(D)J sequencing, respectively, on TIL from two cohorts of patients totaling 15 patients with high grade glioma, including GBM or astrocytoma, IDH mutant, grade 4 (G4A). Analysis of the CD8+ TIL landscape reveals an enrichment of clonally expanded GZMK+ effector T cells in the tumor compared to matched blood, which was validated at the protein level. Furthermore, integration with other cancer types highlights the lack of a canonically exhausted CD8+ T cell population in GBM TIL. These data suggest that GZMK+ effector T cells represent an important T cell subset within the GBM microenvironment and which may harbor potential therapeutic implications. SignificanceIn order to understand the limited efficacy of immune checkpoint blockade in GBM, we endeavor to understand the TIL landscape through a multi-omics approach. In this study, by highlighting the enrichment of GZMK+ effector T cells and lack of exhausted T cells, we provide a new potential mechanism of resistance to immunotherapy in GBM.

immunology↗

bioRxiv2020

An in vivo Probabilistic Atlas of the Human Locus Coeruleus at Ultra-high Field

Early and profound pathological changes are evident in the locus coeruleus (LC) in dementia and Parkinsons disease, with effects on arousal, attention, cognitive and motor control. The LC can be identified in vivo using non-invasive magnetic resonance imaging techniques which have potential as biomarkers for detecting and monitoring disease progression. Technical limitations of existing imaging protocols have impaired the sensitivity to regional contrast variance or the spatial variability on the rostrocaudal extent of the LC, with spatial mapping consistent with post mortem findings. The current study employs a sensitive magnetisation transfer sequence using ultrahigh field 7T MRI to investigate the LC structure in vivo at high-resolution (resolution 0.4x0.4x0.5 mm, duration seven minutes). Magnetisation transfer images from 53 healthy older volunteers (52-84 years) revealed the spatial features of the LC and were used to create a probabilistic LC atlas for older adults, appropriate for clinical research. Consistent rostrocaudal gradients of slice-wise volume, contrast and variance differences of the LC were observed, mirroring distinctive ex vivo spatial distributions of LC cells in its subregions. The contrast-to-noise ratios were calculated for the peak voxels, and for the averaged signals within the atlas, to accommodate the volumetric differences in estimated contrast. The probabilistic atlas is freely available, and the MRI dataset is available for researchers, for replication or to facilitate accurate LC localisation and unbiased contrast extraction in future studies.

neuroscience↗

bioRxiv2019

The effects of age on resting-state BOLD signal variability is explained by cardiovascular and neurovascular factors

Accurate identification of brain function is necessary to understand neurocognitive ageing, and thereby promote health and well-being. Many studies of neurocognitive aging have investigated brain function with the blood-oxygen level-dependent (BOLD) signal measured by functional magnetic resonance imaging. However, the BOLD signal is a composite of neural and vascular signals, which are differentially affected by aging. It is therefore essential to distinguish the age effects on vascular versus neural function. The BOLD signal variability at rest (known as resting state fluctuation amplitude, RSFA), is a safe, scalable and robust means to calibrate vascular responsivity, as an alternative to breath-holding and hypercapnia. However, the use of RSFA for normalization of BOLD imaging assumes that age differences in RSFA reflecting only vascular factors, rather than age-related differences in neural function (activity) or neuronal loss (atrophy). Previous studies indicate that two vascular factors, cardiovascular health and cerebrovascular function, are insufficient when used alone to fully explain age-related differences in RSFA. It remains possible that their joint consideration is required to fully capture age differences in RSFA. We tested the hypothesis that RSFA no longer varies with age after adjusting for a combination of cardiovascular and cerebrovascular measures. We also tested the hypothesis that RSFA variation with age is not associated with atrophy. We used data from the population-based, lifespan Cam-CAN cohort. After controlling for cardiovascular and cerebrovascular estimates alone, the residual variance in RSFA across individuals was significantly associated with age. However, when controlling for both cardiovascular and cerebrovascular estimates, the variance in RSFA was no longer associated with age. Grey matter volumes did not explain age-differences in RSFA, after controlling for cardiovascular health. The results were consistent between voxel-level analysis and independent component analysis. Our findings indicate that cardiovascular and cerebrovascular signals are together sufficient predictors of age differences in RSFA. We suggest that RSFA can be used to separate vascular from neuronal factors, to characterise neurocognitive aging. We discuss the implications and make recommendations for the use of RSFA in the research of aging.

neuroscience↗

bioRxiv2019

Microscale physiological events on the human cortical surface detected with PEDOT:PSS Electrodes

Despite ongoing advancements in our understanding of the local single-cellular and network-level activity of neuronal populations in the human brain, extraordinarily little is known about their intermediate microscale local circuit dynamics. Here, we utilized ultrahigh density microelectrode arrays and a rare opportunity to perform intracranial recordings across multiple cortical areas in human participants to discover three distinct classes of cortical activity that are not locked to ongoing natural brain rhythmic activity. The first included fast waveforms similar to extracellular single unit activity. The other two types were discrete events with slower waveform dynamics and were found preferentially in upper layers of the grey matter. They were also observed in rodents, non-human primates, and semi-chronic recordings in humans via laminar and Utah array microelectrodes. The rates of all three events were selectively modulated by auditory and electrical stimuli, pharmacological manipulation, and cold saline application and had small causal co-occurrences. These results suggest that with the proper combination of high resolution microelectrodes and analytic techniques it is possible to capture neuronal dynamics that lay between somatic action potentials and aggregate population activity and that understanding these intermediate microscale dynamics may reveal important details of the full circuit behavior in human cognition.

neuroscience↗

bioRxiv2019

Neuroinflammation and functional connectivity in Alzheimer's disease: interactive influences on cognitive performance

Neuroinflammation is a key part of the etio-pathogenesis of Alzheimers disease. We test the relationship between neuroinflammation and the disruption of functional connectivity in large-scale networks, and their joint influence on cognitive impairment. We combined [11C]PK11195 positron emission tomography (PET) and resting-state functional magnetic resonance imaging (rs-fMRI) in 28 humans (13 females/15 males) with clinical diagnosis of probable Alzheimers disease or mild cognitive impairment with positive PET biomarker for amyloid, and 14 age-, sex-, and education-matched healthy humans (8 females/6 males). Source-based inflammetry was used to extract principal components of [11C]PK11195 PET signal variance across all participants. rs-fMRI data were pre-processed via independent component analyses to classify neuronal and non-neuronal signals. Multiple linear regression models identified sources of signal co-variance between neuroinflammation and brain connectivity profiles, in relation to group and cognitive status. Patients showed significantly higher [11C]PK11195 binding relative to controls, in a distributed spatial pattern including the hippocampus, medial, and inferior temporal cortex. Patients with enhanced loading on this [11C]PK11195 binding distribution displayed diffuse abnormal functional connectivity. The expression of a stronger association between such abnormal connectivity and higher levels of neuroinflammation correlated with worse cognitive deficits. Our study suggests that neuroinflammation relates to the pathophysiological changes in network function that underlie cognitive deficits in Alzheimers disease. Neuroinflammation, and its association with functionally-relevant reorganisation of brain networks, is proposed as a target for emerging immuno-therapeutic strategies aimed at preventing or slowing the emergence of dementia. Significance StatementNeuroinflammation is an important aspect of Alzheimers disease (AD), but it was not known whether the influence of neuroinflammation on brain network function in humans was important for cognitive deficit. Our study provides clear evidence that in vivo neuroinflammation in AD impairs large-scale network connectivity; and that the link between inflammation and functional network connectivity is relevant to cognitive impairment. We suggest that future studies should address how neuroinflammation relates to network function as AD progresses; and whether the neuroinflammation in AD is reversible, as the basis of immunotherapeutic strategies to slow the progression of AD.

neuroscience↗

bioRxiv2019

Neuroinflammation and protein aggregation co-localize across the frontotemporal dementia spectrum.

The clinical syndromes of frontotemporal dementia are clinically and neuropathologically heterogeneous, but processes such as neuroinflammation may be common across the disease spectrum. We investigated how neuroinflammation relates to the aggregation of Tau and TDP-43 in frontotemporal dementia, and to the heterogeneity of clinical disease. We used positron emission tomography in vivo with (a) [11C]PK-11195, a marker of activated microglia and a proxy index of neuroinflammation, and (b) [18F]AV-1451, a radioligand with increased binding to pathologically affected regions in tauopathies and diseases associated with TDP-43 protein aggregation, and which is used as a surrogate marker of non-{beta}-amyloid protein aggregation. We assessed 31 patients with frontotemporal dementia (10 with behavioural variant frontotemporal dementia, 11 with the semantic variant of primary progressive aphasia and 10 with the non-fluent variant of primary progressive aphasia), 28 of whom underwent both [18F]AV-1451 and [11C]PK-11195 PET, and matched controls (14 for [18F]AV-1451 and 15 for [11C]PK-11195). We used univariate region-of-interest analyses, and multivariate analysis of the distribution of binding that explicitly control for individual differences in ligand affinity for TDP-43 and different Tau isoforms. We found differences between patients and controls in frontotemporal regions for both neuroinflammation and protein aggregation, and a strong positive correlation between these two processes in all disease groups. Despite this regional co-localisation, the multivariate distribution of [11C]PK-11195 binding related better to clinical heterogeneity than did the distribution of [18F]AV-1451: distinct spatial modes of neuroinflammation were associated with different frontotemporal dementia syndromes and supported accurate group classification of participants. These in vivo findings indicate a close association between neuroinflammation and protein aggregation in frontotemporal dementia. The inflammatory component may be important in shaping the clinical and neuropathological patterns of the diverse clinical syndromes of frontotemporal dementia.

neuroscience↗