Introduction: In a previous study, we examined the effect of atDCS on working memory task performance and modulation of the inhibitory neurotransmitter, gamma-aminobutyric acid (GABA), in the dorsolateral prefrontal cortex (dlPFC). The present study investigates whether tDCS modulates effective connectivity during the task, specifically assessing whether tDCS alters interactions between neuronal populations. Methods: Eighteen adolescents with Neurofibromatosis Type 1 (NF1) completed a single-blind sham-controlled cross-over randomised tDCS trial (with the anode at F3 and cathode at Cz). Dynamic causal modelling was used to estimate the effective connectivity between regions that showed working memory effects from the fMRI. Group-level inferences for between sessions (pre- and post-stimulation) and stimulation type (tDCS and sham) effects were carried out using the parametric empirical Bayes approach. A correlation analysis was performed to relate the estimated effective connectivity parameters of left dlPFC pre-tDCS and post-tDCS to the concentration of GABA measured via magnetic resonance spectroscopy (MRS-GABA). Next, correlation analysis was repeated using all working memory performance and all pre-tDCS and post-tDCS connectivity parameters. Results: It was found that tDCS decreased average excitatory connectivity from dlPFC to left superior frontal gyrus and increased average excitatory connectivity to left globus pallidus. Further, reduced average intrinsic (inhibitory) connectivity of left dlPFC was associated with lower MRS-GABA. However, none of the connectivity parameters of dlPFC showed any association with performance on a working memory task. Conclusions: These findings suggest that tDCS reorganised connectivity from frontal to fronto-striatal connectivity. As tDCS-related changes were not specific to the effect of working memory, they may have impacted general cognitive control processes. In addition, by reducing MRS-GABA, tDCS might make dlPFC more sensitive and responsive to external stimulation, such as performance of cognitive tasks.

Introduction GABA (gamma-aminobutyric acid) is the major inhibitory neurotransmitter in the brain. In response to injury within the central nervous system, GABA promotes cortical plasticity and represents a potential pharmacological target to improve functional recovery. However, it is unclear how GABA changes in the brain after traumatic brachial plexus injuries (tBPIs) which represents the rationale for this pilot study. Methods We serially scanned seven males (mean age 42 years [SD 19] without head injury) up to 19 months after tBPIs. T1-weighted images (1-mm isotropic resolution) and J-edited spectra (MEscher-GArwood Point RESolved Spectroscopy [MEGA-PRESS], TE 68 ms, TR 2,000 ms, 2 cm isotropic voxels) were acquired using a MAGNETOM Prisma 3T (Siemens Healthcare, Erlangen, Germany). Data were analyzed in jMRUI blind to clinical information to quantify GABA, creatine plus phosphocreatine (Cr), and N-acetylaspartate (NAA) concentrations. Additionally, gray matter and white matter proportions were assessed using SPECTRIM software. Interhemispheric means were compared using linear methods. Confidence intervals (CIs) were generated to the 95% level. Results Within weeks of injury, the hemisphere representing the injured upper limb had a significantly lower GABA:NAA ratio (mean difference 0.23 [CI 0.06-0.40]) and GABA:Cr ratio (mean difference 0.75 [CI 0.24-1.25]) than the uninjured side. There were no interhemispheric differences in NAA:Cr. By 12 months post-injury, interhemispheric differences in metabolite concentrations equalized. There was no difference in the proportion of gray matter, white matter, or cerebrospinal fluid between the injured and uninjured hemispheres. Conclusion After brachial plexus injuries, there are interhemispheric differences in GABA concentrations within the sensory and motor cortex. This represents a potential pharmacological target that warrants further investigation.

Abstract Background Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a chronic and debilitating condition, which core symptoms are fatigue not caused by exertion and not alleviated by rest, post- exertional malaise, decline in functioning, and cognitive symptoms, often described as 'brain fog’ (1). Similar symptoms are also present in 'long-COVID’, a sequela of the acute infection with the SARS-CoV- 2 virus (2). While underlying pathogenetic processes are still largely unknown impaired mitochondrial function and energy metabolism in both conditions, and clotting problems in long-COVID, have been suggested. Aims & Objectives the aim was to investigate differences in the biochemistry of the brain and muscle between patients with ME/CFS, long-COVID and healthy volunteers (HV), using the state-of-art ultra- high-field proton magnetic resonance spectroscopy (H1-MRS) at 7 Tesla (7T). In particular, we aimed to assess metabolites involved in energy processing (creatine and lactate). Additionally, we aimed to explore the relationship between MRS findings with the cognitive function. Method: 24 CFS/ME patients, 25 long-COVID patients with predominant fatigue, and 24 healthy volunteers underwent H1-MRS scanning of the brain and calf muscle at 7 Tesla. Voxels were positioned in the pregenual and dorsal ACC (pgACC and dACC, respectively). Participants completed the Stroop Color and Word Test, testing ability to inhibit cognitive interference, related to the ACC function. Other cognitive functions tested included verbal memory and learning, working memory, verbal fluency and executive function. Results Compared to HV, participants with ME/CFS had increased levels of lactate in both pgACC (ME/CFS 1.52 mM, HV 1.22; p=0.003) and dACC (ME/CFS 1.45 mM, HV 1.40 mM; p=0.005), while participants with long-COVID had decreased concentrations of total choline in dACC as compared to healthy individuals (long-COVID 2.25 mM, HV 2.77 mM; p=0.0002). In the ME/CFS group, we observed a negative correlation between verbal fluency and both pgACC and dACC lactate concentrations (pgACCr=-0.614, p=0.01; dACC r=-0,623, p=0.008), while in the long-COVID group we observed a correlation between total choline concentrations and executive function (r=-0.592, p=0.005). There were no significant between-group differences in terms of muscle metabolites. Discussion & Conclusions In ME/CFS, increased levels of lactate suggest dysfunction in energy metabolism, with lactate accumulation suggesting ill mitochondrial health and a shift towards anaerobic metabolism (3). Low levels of total choline in long-COVID patients are interesting in the context of the recently reported association between blood clots and 'brain fog’ in long COVID (4), and reports of neuroprotective effects of choline in animal models, preventing disseminated intravascular coagulation (5). Importantly, differences in findings between ME/CFS and long COVID suggest that the underlying neurobiological mechanisms, while leading to similar clinical presentations with fatigue and brain fog, may differ. This has implications for future research, suggesting that patients with ME/CFS and those with fatigue in the course of long COVID should not be studied as a single group, at least until the mechanisms are better understood, and that different treatments may be needed despite similarity of symptoms. References 1) Prins, J.B., van der Meer, J.W., Bleijenberg, G. (2006) 'Chronic fatigue syndrome.’ Lancet, 367, pp.346–355. 2) Kelly, J.D., Curteis, T., Rawal, A., et al. (2023) 'SARS-CoV-2 post-acute sequelae in previously hospitalised patients: systematic literature review and meta-analysis.’ Eur Respir Rev, 32, pp.220254. 3) Brooks, G.A. (2018) 'The Science and Translation of Lactate Shuttle Theory.’ Cell Metab, 27, pp.757- 785. 4) Taquet, M., Skorniewska, Z., Hampshire, A., et al. (2023) 'Acute blood biomarker profiles predict cognitive deficits 6 and 12 months after COVID-19 hospitalization.’ Nat Med, 29, pp.2498-2508 5)Blusztajn, J.K., Slack, B.E. and Mellott, T.J. (2017) 'Neuroprotective actions of dietary choline.’ Nutrients, 9, p.815.

A comprehensive understanding of cellular behavior and response to the tumor microenvironment (TME) in colorectal cancer (CRC) remains elusive. Here, we introduce the high-definition Visium spatial transcriptomic technology (Visium HD) and investigate formalin-fixed paraffin-embedded human CRC samples (n = 5). We demonstrate the high sensitivity, single-cell-scale resolution and spatial accuracy of Visium HD, generating a highly refined whole-transcriptome spatial profile of CRC samples. We identify transcriptomically distinct macrophage subpopulations in different spatial niches with potential pro-tumor and anti-tumor functions via interactions with tumor and T cells. In situ gene expression analysis validates our findings and localizes a clonally expanded T cell population close to macrophages with anti-tumor features. Our study demonstrates the power of high-resolution spatial technologies to understand cellular interactions in the TME and paves the way for larger studies that will unravel mechanisms and biomarkers of CRC biology, improving diagnosis and disease management strategies.

Myalgic encephalitis/chronic fatigue syndrome (ME/CFS) is a common debilitating medical condition, whose main symptoms - fatigue, post-exertional malaise and cognitive dysfunction - are also present in many cases of long COVID. Magnetic resonance spectroscopy (MRS) allows the insight into their pathophysiology through exploration of a range of biochemicals putatively relevant to aetiological processes, in particular mitochondrial dysfunction and energy metabolism. 24 patients with ME/CFS, 25 patients with long COVID and 24 healthy controls (HC) underwent brain (pregenual and dorsal anterior cingulate cortex, respectively, pgACC and dACC) and calf muscle MRS scanning at 7 Tesla, followed by a computerised cognitive assessment. Compared to HC, ME/CFS patients had elevated levels of lactate in both pgACC and dACC, while long COVID patients had lowered levels of total choline in dACC. By contrast, skeletal muscle metabolites at rest did not significantly differ between the groups. The changes in lactate in ME/CFS are consistent with the presence of energetic stress and mitochondrial dysfunction. A reduction in total choline in long COVID is of interest in the context of the recently reported association between blood clots and 'brain fog', and earlier animal studies showing that choline might prevent intravascular coagulation. Importantly, differences in findings between ME/CFS and long COVID suggest that the underlying neurobiological mechanisms, while leading to similar clinical presentations, may differ. An important implication is that patients with ME/CFS and those with fatigue in the course of long COVID should not be studied as a single group, at least until the mechanisms are better understood.

We investigated the longstanding idea that the onset of psychotic symptoms in schizophrenia arises from an early phase of glutamate neurotoxicity, possibly related to loss of GABA restraint, oxidative stress or inflammation, that cumulatively results in a later phase of synaptic loss in keeping with magnetic resonance spectroscopy (MRS) evidence of reduced glutamate in schizophrenia, especially in older patients. We evaluated this hypothesis in a 3-centre MRS study to determine whether abnormalities in glutamate in dorsal anterior cingulate cortex (dACC) differed between people with minimally treated ‘Recent’ onset schizophrenia and an ‘Established’ group with > 10 years of illness. We tested the hypothesised mechanisms of reduced GABA in either or both dACC and occipital cortex, and depletion of dACC glutathione, a measure of central inflammation. We explored predicted associations between MRS variables, circulating cytokines and clinical symptoms. The Established group showed significantly greater dACC glutamate deficit than the Recent group which was not accounted for by lifetime exposure to antipsychotic drugs or by their greater CRP or IL-6 levels nor was the deficit associated with glutathione depletion. The greater dACC glutamate deficit in established illness is compatible with loss of synapses occurring after onset of symptoms but there was little to suggest underpinning excitotoxicity, inflammation, or oxidative stress. GABA was reduced in patients versus controls across dACC and occipital voxels. Only dACC GABA content correlated significantly with symptoms, lower content with greater positive and negative symptoms across both groups and this is supportive of a pathophysiological role of GABA in psychosis.

Functional magnetic resonance spectroscopy (fMRS) measures dynamic changes in metabolite concentration in response to neural stimulation. The biophysical basis of these changes remains unclear. One hypothesis suggests that an increase or decrease in the glutamate signal detected by fMRS could be due to neurotransmitter movements between cellular compartments with different T2 relaxation times. Previous studies reporting glutamate (Glu) T2 values have generally sampled at echo times (TEs) within the range of 30-450 ms, which is not adequate to observe a component with short T2 (<20 ms). Here, we acquire MRS measurements for Glu, (t) total creatine (tCr) and total N-acetylaspartate (tNAA) from the visual cortex in 14 healthy participants at a range of TE values between 9.3-280 ms during short blocks (64 s) of flickering checkerboards and rest to examine both the short- and long-T2 components of the curve. We fit monoexponential and biexponential Glu, tCr and tNAA T2 relaxation curves for rest and stimulation and use Akaike information criterion to assess best model fit. We also include power calculations for detection of a 2% shift of Glu between compartments for each TE. Using pooled data over all participants at rest, we observed a short Glu T2-component with T2 = 10 ms and volume fraction of 0.35, a short tCr T2-component with T2 = 26 ms and volume fraction of 0.25 and a short tNAA T2-component around 15 ms with volume fraction of 0.34. No statistically significant change in Glu, tCr and tNAA signal during stimulation was detected at any TE. The volume fractions of short-T2 component between rest and active conditions were not statistically different. This study provides evidence for a short T2-component for Glu, tCr and tNAA but no evidence to support the hypothesis of task-related changes in glutamate distribution between short and long T2 compartments.

This study examined the effects of anodal transcranial direct current stimulation (atDCS) on effective connectivity during a working memory task. Eighteen adolescents with Neurofibromatosis Type 1 (NF1) completed a single blind sham controlled cross over randomised atDCS trial. Dynamic causal modelling was used to estimate the effective connectivity between regions that showed working memory effects from the fMRI. Group-level inferences for between sessions (pre- and post-stimulation) and stimulation type (atDCS and sham) effects were carried out using the parametric empirical Bayes approach. A correlation analysis was performed to relate the estimated effective connectivity parameters of left dlPFC pre-atDCS and post-atDCS to the concentration of gamma-aminobutyric acid (GABA) measured via magnetic resonance spectroscopy (MRS-GABA). Next, correlation analysis was repeated using all working memory performance and all pre-atDCS and post-atDCS connectivity parameters. It was found that atDCS decreased average excitatory connectivity from left dorsolateral prefrontal cortex (dlPFC) to left superior frontal gyrus and increased average excitatory connectivity to left globus pallidus. Further, reduced average intrinsic (inhibitory) connectivity of left dlPFC was associated with lower MRS-GABA. However, none of the connectivity parameters of dlPFC showed any association with performance on a working memory task. These findings suggest that atDCS reorganised connectivity from frontal to fronto-striatal connectivity. As atDCS-related changes were not specific to the effect of working memory, they may have impacted general cognitive control processes. In addition, by reducing MRS-GABA, atDCS might make dlPFC more sensitive and responsive to external stimulation, such as performance of cognitive tasks. ### Competing Interest Statement The authors have declared no competing interest.

Background: Recent evidence suggests that patients with schizophrenia may show advanced brain ageing, particularly evident after the first year of onset. However, it is unclear if accelerated ageing relents, persists or continues to increase over time. The underlying causal factors are also poorly understood. Disruptions in glutamate function, oxidative stress, and inflammation may all contribute to progressive brain changes in people with schizophrenia. We examine whether brain ageing differs between early and established stages of schizophrenia, correlates with symptom severity and varies with markers of brain function, oxidative status and inflammatory burden. Methods: Two brain-age prediction models assessed 112 participants (34 recent onset psychosis, 36 established schizophrenia, 42 healthy controls). Brain age gap (BAG) was calculated by subtracting chronological age from predicted age. Shapley's additive explanations (SHAP) identified influential structural magnetic resonance imaging (MRI) features driving brain-age prediction. Linear regression models and partial correlations, adjusting for age, explored associations between BAG and neurometabolites, inflammatory markers, medication exposure and clinical scores in the whole sample. Results: The established schizophrenia group showed higher BAG (Mean = 6.21, SD = 7.30) compared to healthy individuals (Mean = -0.01, SD = 9.10), while recent-onset patients (Mean = 4.23, SD = 9.25) did not differ significantly from healthy individuals. The top 10 SHAP features diving the BAG included ventricular enlargement and total grey matter volume, which was similar in psychosis to healthy individuals. In a combined psychosis group (established + recent-onset), higher BAG correlated with more severe symptoms (PANSS total, general, and anxiodepressive subscales). BAG positively associated with Magnetic Resonance Spectroscopy measured glutathione and negatively with N-Acetyl Aspartate. Discussion: Accelerated brain age in schizophrenia may be related to illness severity and poor defence against oxidative stress. The lack of differences in SHAP features between schizophrenia and healthy individuals suggests that the pattern of brain ageing is in keeping with advanced normal ageing. Findings suggest potential treatment targets to improve brain health in schizophrenia, warranting further research. ### Competing Interest Statement LP reports personal fees for serving as chief editor from the Canadian Medical Association Journals, speaker/consultant fee from Janssen Canada and Otsuka Canada, SPMM Course Limited, UK, Canadian Psychiatric Association; book royalties from Oxford University Press; investigator-initiated educational grants from Janssen Canada, Sunovion and Otsuka Canada outside the submitted work. All other authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. ### Funding Statement AM was supported by funding from the Medical Research Council (MRC) for doctoral training with RU, MK, and PL related to this manuscript (MR/2434208). RU acknowledges funding from MRC (MR/S037675/1) related to this manuscript. This research is also supported by the NIHR Oxford Health Biomedical Research Centre. The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care. LP acknowledges research support from Monique H. Bourgeois Chair in Developmental Disorders and Graham Boeckh Foundation (Douglas Research Centre, McGill University) and salary award from the Fonds de recherche du Quebec-Sante ́ (FRQS). ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The National Research Ethics Service Committe Northwest - Lancaster UK gave ethical approval for this work. Reference 14/NW/0298, Approval date 18/06/2014 I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data produced in the present study are available upon reasonable request to the authors

Dysfunction of glutamate neurotransmission has been implicated in the pathophysiology of schizophrenia and may be particularly relevant in severe, treatment-resistant symptoms. The underlying mechanism may involve hypofunction of the NMDA receptor. We investigated whether schizophrenia-related pathway polygenic scores, composed of genetic variants within NMDA receptor encoding genes, are associated with cortical glutamate in schizophrenia. Anterior cingulate cortex (ACC) glutamate was measured in 70 participants across 4 research sites using Proton Magnetic Resonance Spectroscopy (1H-MRS). Two NMDA receptor gene sets were sourced from the Molecular Signatories Database and NMDA receptor pathway polygenic scores were constructed using PRSet. The NMDA receptor pathway polygenic scores were weighted by single nucleotide polymorphism (SNP) associations with treatment-resistant schizophrenia, and associations with ACC glutamate were tested. We then tested whether NMDA receptor pathway polygenic scores with SNPs weighted by associations with non-treatment-resistant schizophrenia were associated with ACC glutamate. A higher NMDA receptor complex pathway polygenic score was significantly associated with lower ACC glutamate (β = -0.25, 95 % CI = -0.49, -0.02, competitive p = 0.03). When SNPs were weighted by associations with non-treatment-resistant schizophrenia, there was no association between the NMDA receptor complex pathway polygenic score and ACC glutamate (β = 0.05, 95 % CI = -0.18, 0.27, competitive p = 0.79). These results provide initial evidence of an association between common genetic variation implicated in NMDA receptor function and ACC glutamate levels in schizophrenia. This association was specific to when the NMDA receptor complex pathway polygenic score was weighted by SNP associations with treatment-resistant schizophrenia.

The RNA modification N6-methyladenosine (m6A) regulates the interaction between RNA and various RNA binding proteins within the nucleus and other subcellular compartments and has recently been shown to be involved in experience-dependent plasticity, learning, and memory. Using m6A RNA-sequencing, we have discovered a distinct population of learning-related m6A- modified RNAs at the synapse, which includes the long noncoding RNA metastasis-associated lung adenocarcinoma transcript 1 (Malat1). RNA immunoprecipitation and mass spectrometry revealed 12 new synapse-specific learning-induced m6A readers in the mPFC of male C57/BL6 mice, with m6A-modified Malat1 binding to a subset of these, including CYFIP2 and DPYSL2. In addition, a cell type- and synapse-specific, and state-dependent, reduction of m6A on Malat1 impairs fear-extinction memory; an effect that likely occurs through a disruption in the interaction between Malat1 and DPYSL2 and an associated decrease in dendritic spine formation. These findings highlight the critical role of m6A in regulating the functional state of RNA during the consolidation of fear-extinction memory, and expand the repertoire of experience-dependent m6A readers in the synaptic compartment.SIGNIFICANCE STATEMENT We have discovered that learning-induced m6A-modified RNA (including the long noncoding RNA, Malat1) accumulates in the synaptic compartment. We have identified several new m6A readers that are associated with fear extinction learning and demonstrate a causal relationship between m6A-modified Malat1 and the formation of fear-extinction memory. These findings highlight the role of m6A in regulating the functional state of an RNA during memory formation and expand the repertoire of experience-dependent m6A readers in the synaptic compartment.

Single-cell and spatial technologies that profile gene expression across a whole tissue are revolutionizing the resolution of molecular states in clinical samples. Current commercially available technologies provide whole transcriptome single-cell, whole transcriptome spatial, or targeted in situ gene expression analysis. Here, we combine these technologies to explore tissue heterogeneity in large, FFPE human breast cancer sections. This integrative approach allowed us to explore molecular differences that exist between distinct tumor regions and to identify biomarkers involved in the progression towards invasive carcinoma. Further, we study cell neighborhoods and identify rare boundary cells that sit at the critical myoepithelial border confining the spread of malignant cells. Here, we demonstrate that each technology alone provides information about molecular signatures relevant to understanding cancer heterogeneity; however, it is the integration of these technologies that leads to deeper insights, ushering in discoveries that will progress oncology research and the development of diagnostics and therapeutics.

The tumor microenvironment is composed of highly heterogeneous structures and cell types that dynamically influence and communicate with each other. Although examination of singular biospecimens is sufficient for diagnostic purposes, it is inadequate and cost prohibitive when scaling for complex and overarching studies. Thus, high density multi-tumor tissue microarrays (TMAs) have been a practical and effective solution for high-throughput molecular analysis of tissues. Introduced more than a decade ago, TMAs have been instrumental in the recent study of tumor biology, the development of diagnostic tests, the establishment of quality control, and the investigation and identification of oncological biomarkers. Here, we demonstrate the pairing of the 10x Genomics Visium Cytassist Spatial Gene Expression Solution and Xenium In-Situ Platform on multi-tumor TMAs to screen for common biomarkers among a cohort of samples. Spatial transcriptomics technology has proven valuable in mapping the whole transcriptome with spatial context (Visium), whereas In Situ (Xenium) enables high-throughput cellular characterization at single-cell resolution. With the addition of our CytAssist platform, we expand on the pre-existing standard Visium solution by facilitating the retrieval of RNA transcriptomic information from tissues placed on standard or archival slides. On the other hand, the novel Xenium platform compliments whole transcriptome Visium data by unlocking the potential to assign transcripts to a particular cell with spatial context and subcellular resolution. The combination of spatial transcriptomics and targeted in situ data with FFPE TMAs promotes a high-throughput method to accelerate the uncovering of molecular signatures suitable to understanding the tumor microenvironment. We showcase the ability to spatially and comprehensively resolve individual oncogene and tumor suppressor genes associated with multiple tumors from a cohort of cancer patients and from multiple different tumor samples. In addition, these markers are mapped back to distinct morphological features within each tissue core, and use differential gene expression data to identify distinct cell types throughout the different patient tissues. By combining the throughput of TMA samples and depth of the Visium and Xenium platforms, the strategy enables greater insights into cell-type specifics while also expanding the spectrum of biospecimen types that can be analyzed. Citation Format: Syrus Mohabbat, Hardeep Singh, Stephen R. Williams, Lauren M M. Gutgesell, David J. Sukovich, Govinda M. Kamath, Hanyoup Kim, Amanda Janesick, Robert Shelansky, Ghezal Beliakoff, Augusto M. Tentori, Albert Kim, Cedric R. Uytingco, Sarah Taylor. Application of spatially resolved transcriptomics to screen multiple tumor biospecimens using tissue microarrays. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4708.

Recent advances in spatial transcriptomics (STs) enable gene expression measurements from a tissue sam-ple while retaining its spatial context. This technology enables unprecedented in situ resolution of the regu-latory pathways that underlie the heterogeneity in the tumor as well as the tumor microenvironment (TME). The direct characterization of cellular co-localization with spatial technologies facilities quantification of the molecular changes resulting from direct cell-cell interaction, as it occurs in tumor-immune interactions. We present SpaceMarkers, a bioinformatics algorithm to infer molecular changes from cell-cell interactions from latent space analysis of ST data. We apply this approach to infer the molecular changes from tumor -im-mune interactions in Visium spatial transcriptomics data of metastasis, invasive and precursor lesions, and immunotherapy treatment. Further transfer learning in matched scRNA-seq data enabled further quantifica-tion of the specific cell types in which SpaceMarkers are enriched. Altogether, SpaceMarkers can identify the location and context-specific molecular interactions within the TME from ST data.

Cholinergic interneurons are central hubs of the striatal neuronal network, controlling information processing in a behavioral-state-dependent manner. It remains unknown, however, how such state transitions influence the integrative properties of these neurons. To address this, we made simultaneous somato-dendritic recordings from identified rodent cholinergic interneurons, revealing that action potentials are initiated at dendritic sites because of a dendritic axonal origin. Functionally, this anatomical arrangement ensured that the action potential initiation threshold was lowest at axon-bearing dendritic sites, a privilege efficacy powerfully accentuated at the hyperpolarized membrane potentials achieved in cholinergic interneurons following salient behavioral stimuli. Experimental analysis revealed the voltage-dependent attenuation of the efficacy of non-axon-bearing dendritic excitatory input was mediated by the recruitment of dendritic potassium channels, a regulatory mechanism that, in turn, was controlled by the pharmacological activation of neurokinin receptors. Together, these results indicate that the neuropeptide microenvironment dynamically controls state- and compartment-dependent dendritic information processing in striatal cholinergic interneurons.

Impaired cognition is associated with lower quality of life and poor outcomes in schizophrenia. Brain glutamate may contribute to both clinical outcomes and cognition, but these relationships are not well-understood. We studied a multicentre cohort of 85 participants with non-affective psychosis using proton magnetic resonance spectroscopy. Glutamate neurometabolites were measured in the anterior cingulate cortex (ACC). Cognition was assessed using the Brief Assessment for Cognition in Schizophrenia (BACS). Patients were categorised as antipsychotic responders or non-responders based on treatment history and current symptom severity. Inverted U-shaped associations between glutamate or Glx (glutamate + glutamine) with BACS subscale and total scores were examined with regression analyses. We then tested for an interaction effect of the antipsychotic response group on the relationship between glutamate and cognition. ACC glutamate and Glx had a positive linear association with verbal memory after adjusting for age, sex and chlorpromazine equivalent dose (glutamate, β = 3.73, 95% CI = 1.26–6.20, P = 0.004; Glx, β = 3.38, 95% CI = 0.84–5.91, P = 0.01). This association did not differ between good and poor antipsychotic response groups. ACC glutamate was also positively associated with total BACS score (β = 3.12, 95% CI = 0.01–6.23, P = 0.046), but this was not significant after controlling for antipsychotic dose. Lower glutamatergic metabolites in the ACC were associated with worse verbal memory, and this relationship was independent of antipsychotic response. Further research on relationships between glutamate and cognition in antipsychotic responsive and non-responsive illness could aid the stratification of patient groups for targeted treatment interventions.

The tumor microenvironment (TME) is composed of highly heterogeneous structures and cell types that dynamically influence and communicate with each other. The constant interaction between a tumor and its microenvironment plays a critical role in how the cancer develops, progresses, and responds to therapies. Traditionally, Hematoxylin and Eosin (H&E) and immunohistochemistry staining have been used to annotate and characterize tissues and associated pathologies. Recent single analyte approaches spatially interrogate targeted or transcriptome-wide expression of RNA in tissue sections, while others capture phenotypes using a limited number of protein markers. However, for a more comprehensive understanding of the unique characteristics of cell types, cell states, and cell-cell interactions within the TME, analysis of multiple analytes is necessary. Here we demonstrate a novel, streamlined multiomic spatial assay that integrates histological staining and imaging with simultaneous transcriptome-wide gene expression and highly multiplexed protein expression profiling from the same formalin-fixed paraffin embedded (FFPE) tissue section. In short, tissue sections from archived FFPE samples were placed on slides containing arrayed capture oligos with unique positional barcodes. The H&E stained tissues were then imaged, followed by incubation with transcriptome-wide probes and a high-plex DNA-barcoded antibody panel containing intra- and extracellular markers. Transcriptome probes and antibody-barcodes were then spatially captured on the slide and converted into sequencing-ready libraries. Our data analysis and interactive visualization software enable interrogation of all data layers (H&E morphology, RNA, protein) from the same tissue section. We apply this method to simultaneously measure gene and protein expression within the TME of human breast cancer and melanoma FFPE samples using whole transcriptome probes and an immune-oncology antibody panel. The data enables comparison and correlation of multiple analytes and their patterns within the same sample section. In addition, this simultaneous detection enables marker-guided regional selection and differential gene expression analysis on the defined areas. Taken together, our data demonstrates that a spatially resolved, multiomic approach provides a more comprehensive understanding of cellular behavior in and around tumors, yielding new insights into disease progression, predictive biomarkers, drug response and resistance, and therapeutic development.

SummaryThe RNA modification N6-methyladenosine (m6A) is critically involved in the regulation of gene activity underlying experience-dependent plasticity, and is necessary for the functional interplay between RNA and RNA binding proteins (RBPs) in the nucleus. However, the complete repertoire of m6A-modified RNA interacting RBPs in the synaptic compartment, and whether they are involved in fear extinction, have yet to be revealed. Using RNA immunoprecipitation followed by mass spectrometry, we discovered 12 novel, synapsespecific, learning-induced m6A readers in the medial prefrontal cortex of male C57/B6 mice. m6A RNA-sequencing also revealed a unique population of learning-related m6A-modified RNAs at the synapse, which includes a variant of the long non-coding RNA (lncRNA) metastasis associated lung adenocarcinoma transcript 1 (Malat1). m6A-modified Malat1 binds to a subset of novel m6A readers, including cytoplasmic FMR1 interacting protein 2 (CYFIP2) and dihydropyrimidase-related protein 2 (DPYSL2) and a cell-type-specific, state-dependent, and synapse-specific reduction in m6A-modified Malat1 disrupts the interaction between Malat1 and DPYSL2 and impairs fear extinction. The consolidation of fear-extinction memory therefore relies on an interaction between m6A-modified Malat1 and select RBPs in the synaptic compartment.

BackgroundDespite years of studies and effort, the best strategies for treating prostate cancer and minimizing the complications of treatment remain unanswered questions. This gap in knowledge is partially due to the inability to dissect the complex heterogeneous tumor microenvironment (TME) and immune compartment. Spatially resolved molecular profiling of tumor sections will enhance our understanding of these complexities; However, it has been particularly challenging to do spatial molecular profiling in formalin-fixed paraffin-embedded (FFPE) tissues due to RNA degradation associated with this tissue-embedding method, which is routinely used in oncology workflows. The 10x Genomics Visium Spatial Gene Expression Solution for FFPE tissue overcomes these limitations, enabling spatial gene expression analysis of FFPE tissues combined with classical histology staining techniques such as Hematoxylin & Eosin (H&E) staining and immunofluorescence.MethodsWe used the 10x Genomics Visium Spatial Gene Expression Solution for FFPE tissue to analyze and resolve tumorigenic profiles in sections of normal and adenocarcinoma prostate samples. This assay incorporates ~5,000 molecularly barcoded, spatially encoded capture probes in spots over which the tissue is placed, imaged, and permeabilized. Imaging and sequencing data are processed together, resulting in a spatially resolved transcriptional readout.ResultsWe profiled the whole transcriptome in normal, invasive adenocarcinoma, and acinar cell carcinoma FFPE human prostate tissues. Unsupervised clustering of the whole transcriptome data from normal, invasive adenocarcinoma, and acinar cell prostate carcinoma FFPE sections enabled the identification of 2 different regions, which had a well defined spatial distribution within the tissues. Well known prostate gland and prostate-cancer markers were over-expressed in the corresponding healthy and cancerous portions of the tissue, validating the performance of this method. We found that, while in healthy tissues basal cells and luminal cells are spatially organized, this pattern is lost in tumor samples, where luminal cells are greatly expanded in the invasive carcinoma region and do not colocalize with basal cells. Moreover, T lymphocytes are dispersed throughout the whole tissue section in the adenocarcinoma, while plasma B cells are located in the peritumoral region which could impact prognosis.ConclusionsSpatial whole transcriptome analysis opens new opportunities for better understanding the TME which can not only help discover novel predictive tumor biomarkers, but also enable identifying cell type and tumor region specific drug targets.

The tumor microenvironment (TME) is composed of highly heterogeneous structures and cell types that dynamically influence and communicate with each other. The constant interaction between a tumor and its microenvironment plays a critical role in how the cancer develops, progresses, and responds to therapies. Traditionally, Hematoxylin and Eosin (H&E) staining has been used to annotate and characterize tissues and associated pathologies. Recent single analyte approaches spatially interrogate targeted or transcriptome-wide expression of RNA in tissue sections, while others capture phenotypes using a limited number of protein markers. However, for a more comprehensive understanding of the unique characteristics of cell types, cell states, and cell-cell interactions within the TME, multiple layers of information are needed and must be studied together. Here we demonstrate a novel, streamlined multiomic spatial assay that integrates histological staining and imaging with simultaneous transcriptome-wide gene expression and highly multiplexed protein expression profiling from the same formalin-fixed paraffin embedded (FFPE) tissue section. In short, tissue sections from archived FFPE samples were placed on slides containing arrayed capture oligos with unique positional barcodes. The H&E or immunofluorescence stained tissues were then imaged, followed by incubation with transcriptome-wide probes and a high-plex DNA-barcoded antibody panel containing intra- and extracellular markers. Transcriptome probes and antibody-barcodes were then spatially captured on the slide and converted into sequencing-ready libraries. Our data analysis and interactive visualization software enable interrogation of all data layers (H&E/immunofluorescence, RNA, protein) from the same tissue section. We apply this method to simultaneously measure gene and protein expression within the TME of human breast cancer and melanoma FFPE samples using whole transcriptome probes and an immune-oncology antibody panel. The data enables comparison and correlation of multiple analytes and their patterns within the same sample section. In addition, this simultaneous detection enables marker-guided regional selection and differential gene expression analysis on the defined regions. Taken together, our data demonstrates that a spatially resolved, multiomic approach provides a more comprehensive understanding of cellular behavior in and around tumors, yielding new insights into disease progression, predictive biomarkers, drug response and resistance, and therapeutic development. Citation Format: Cedric Uytingco, Jennifer Chew, Naishitha Anaparthy, Jun D. Chiang, Christina Galonska, Karthik Ganapathy, Ryo Hatori, Alexander Hermes, Layla Katiraee, Anna-Maria Katsori, William Nitsch, Patrick Roelli, Joe Shuga, Rapolas Spalinskas, Mesruh Turkekul, Benton Veire, Dan Walker, Neil Weisenfeld, Stephen R. Williams, Zachary Bent, Marlon Stoeckius. Multiomic characterization of the tumor microenvironment in FFPE tissue by simultaneous protein and gene expression profiling [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3814.