Identification of conserved gene expression changes across common glomerular diseases by spatial transcriptomics.

Introduction: Glomerular disease is one of the most common forms of renal disease and can have many different clinical presentations. However there is variation in the prevalence in the type of glomerular disease according to geographical location and race of population. The aim of the study was to find the overall distribution pattern of glomerular disease based on renal biopsies. Material and Methods: The medical records of all children who underwent kidney biopsy (n=29) between January 2012-june 2014 were analyzed. In this retrospective study we review children from Kanti Children’s Hospital, Nephrology Department. Demographic data including age, sex and indication of kidney biopsy as well as complication of the procedures were recorded. Result: A total number of thirty one biopsies were done. Two children were excluded from the study due to inadequate tissue and artifacts defects in preservative. The remaining twenty nine biopsies were included in the study and analyzed. Renal disease was found nearly equal in both male and female (51.72% vs. 48.27%).Mean age was 10.95±3.30 years. Maximum number of biopsies (75.86%) was performed between 10- 15 years. The most common indication of the kidney biopsy was nephrotic syndrome (steroid resistant nephrotic syndrome and steroid dependent nephrotic syndrome, 31.02% followed by lupus nephritis 27.58%.The most common glomerular disease were focal segmental glomerulosclerosis and lupus nephritis both contribute 27.58%. Among lupus nephritis class III was found more common (44.44%) in children. IgA nephropathy was also contribute (17.24%) in all glomerular disease. Regarding the kidney biopsy complication gross hematuria was observed in 6.89% of children which was self-limited. Conclusion: FSGS and lupus nephritis is becoming the most common glomerular disease in children attending the Kanti Children Hospital. IgA nephropathy was also contribute the glomerular disease in the children. J Nepal Paediatr Soc 2014;34(3):225-229 DOI: http://dx.doi.org/10.3126/jnps.v34i3.11162

The role of MAP infection on the epigenetic modeling of gut immunity during the progression of Johne’s Disease (JD) is still unknown. This study investigated the DNA methylation patterns in ileal (IL) and ileal lymph node (ILLN) tissues from cows diagnosed with persistent subclinical MAP infection over a one to four years period. DNA samples from IL and ILLN tissues from cows negative (MAPneg) (n=3) or positive for MAP infection (MAPinf) (n=4) were subjected to whole genome bisulfite sequencing. A total of 11,263 and 62,459 differentially methylated cytosines (DMCs), and 1259 and 8086 differentially methylated regions (DMRs) (FDR<0.1) were found between MAPinf and MAPneg IL and ILLN tissues, respectively. The DMRs were found on 394 genes (denoted DMR genes) in the IL and on 1305 genes in the ILLN. DMR genes with hypermethylated promoters/5’UTR (43 (IL) and 88 (ILLN)) or hypomethylated promoters/5’UTR (10 (IL) and 25 (ILLN)) and having multiple functions including response to stimulus/immune response (BLK, BTC, CCL21, AVPR1A, CHRNG, GABRA4, TDGF1), cellular processes (H2AC20, TEX101, GLA, NCKAP5L) and metabolic processes (GSTO2, H2AC20, SUV39H1, PPA1, UBE2D2) are potential DNA methylation candidate genes of MAP infection. The ILLN DMR genes were enriched for more biological process (BP) gene ontology (GO) terms (n=374), most of which were related to cellular processes (27.6%), biological regulation (16.6%), metabolic processes (15.4%) and response to stimulus/immune response (8.2%) compared to 75 BP GO terms (related to cellular processes, metabolic processes and transport, and system development) enriched for IL DMR genes. ILLN DMR genes were enriched for more pathways (n=47) including 13 disease pathways compared with 36 enriched pathways, including 7 disease/immune pathways for IL DMR genes. In conclusion, the results show tissue specific responses to MAP infection with more epigenetic changes (DMCs and DMRs) in the ILLN than in the IL tissue, suggesting that the ILLN and immune processes were more responsive to regulation by methylation of DNA relative to IL tissue. Our data is the first to demonstrate a potential role for DNA methylation in the pathogenesis of MAP infection in dairy cattle.

&lt;p&gt;Johne’s Disease (JD), caused by Mycobacterium avium subsp paratuberculosis (MAP), is an incurable disease of ruminants and other animal species and is characterized by an imbalance of gut immunity. The role of MAP infection on the epigenetic modeling of gut immunity during the progression of JD is still unknown. This study investigated the DNA methylation patterns in ileal (IL) and ileal lymph node (ILLN) tissues from cows diagnosed with persistent subclinical MAP infection over a one to 4 years period. DNA samples from IL and ILLN tissues from cows negative (MAPneg) (n = 3) or positive for MAP infection (MAPinf) (n = 4) were subjected to whole genome bisulfite sequencing. A total of 11,263 and 62,459 differentially methylated cytosines (DMCs), and 1259 and 8086 differentially methylated regions (DMRs) (FDR&lt;0.1) were found between MAPinf and MAPneg IL and ILLN tissues, respectively. The DMRs were found on 394 genes (denoted DMR genes) in the IL and on 1305 genes in the ILLN. DMR genes with hypermethylated promoters/5′UTR [3 (IL) and 88 (ILLN)] or hypomethylated promoters/5′UTR [10 (IL) and 25 (ILLN)] and having multiple functions including response to stimulus/immune response (BLK, BTC, CCL21, AVPR1A, CHRNG, GABRA4, TDGF1), cellular processes (H2AC20, TEX101, GLA, NCKAP5L, RBM27, SLC18A1, H2AC20BARHL2, NLGN3, SUV39H1, GABRA4, PPA1, UBE2D2) and metabolic processes (GSTO2, H2AC20, SUV39H1, PPA1, UBE2D2) are potential DNA methylation candidate genes of MAP infection. The ILLN DMR genes were enriched for more biological process (BP) gene ontology (GO) terms (n = 374), most of which were related to cellular processes (27.6%), biological regulation (16.6%), metabolic processes (15.4%) and response to stimulus/immune response (8.2%) compared to 75 BP GO terms (related to cellular processes, metabolic processes and transport, and system development) enriched for IL DMR genes. ILLN DMR genes were enriched for more pathways (n = 47) including 13 disease pathways compared with 36 enriched pathways, including 7 disease/immune pathways for IL DMR genes. In conclusion, the results show tissue specific responses to MAP infection with more epigenetic changes (DMCs and DMRs) in the ILLN than in the IL tissue, suggesting that the ILLN and immune processes were more responsive to regulation by methylation of DNA relative to IL tissue. Our data is the first to demonstrate a potential role for DNA methylation in the pathogenesis of MAP infection in dairy cattle.&lt;/p&gt;

Spatial transcriptomic technology enables resolving a tumor microenvironment heterogeneity of colorectal cancer (CRC) tissue samples. However, there is limited evidence regarding the relative strengths and weaknesses of different CRC sample types and preservation methods, including formalin-fixed paraffin-embedded (FFPE), fresh frozen (FF) and snap frozen (SF). Here, we examine gene expression profiles in 36 tissue areas, FFPE, FF and SF samples, derived from a patient with stage IV CRC, using spatial analysis of the whole transcriptome. The tissue samples obtained from surgical resection of the cancer were subjected to a detailed histological evaluation and spatial transcriptomics analysis to compare the quality of the sample between different preservation methods. Spatial transcriptomic analysis demonstrated that FFPE tissue samples offered improved resolution of cellular morphology in the tumor microenvironment, facilitating greater detail of gene expression and cell types. In contrast, gene expression analysis of FF and SF tissues embedded in optimal cutting temperature compound revealed a high level of CRC gene expression. FFPE, FF and SF samples shared a significant overlap among the top 300 genes that were strongly associated with key biological processes in CRC. In summary, the spatial analysis of the whole transcriptome across FFPE, FF and SF CRC tissues revealed intratumoral heterogeneity and highlighted key transcriptomic signatures, suggesting the specific value of different tissue preservation methods in the profiling of CRC.

Cutaneous squamous cell carcinoma (cSCC) and basal cell carcinoma (BCC) are the most prevalent types of nonmelanoma skin cancer (NMSC) and exhibit significant inter- and intra-tumor heterogeneity. cSCC has a higher metastatic potential than BCC, accompanied by a considerable mortality rate. However, the detailed mechanisms of tumor evolution in cSCC have not yet been described. We performed single-cell RNA sequencing (scRNA-seq) and T cell receptor (TCR) clonal analysis of skin biopsies from five BCCs, three squamous cell carcinomas insitu (SCCIS), and two invasive squamous cell carcinomas (SCC). Independent SCC specimens were used for spatial transcriptomic (ST) analysis using GeoMx Digital Spatial Profiler (DSP). Using scRNA-seq, we analyzed a total of 117,663 cells. We distinguished cancer cells using copy number variation and identified SCC-specific genes that potentially contribute to tumor progression. Analysis of tumor clones revealed SCC-specific COL6A1+/ITGA5+ carcinoma cells which produce CXCL16. We also annotated CXCR6+ regulatory T cells (Tregs) which potentially move toward the tumor site by CXCL16, shaping the immunosuppressive TME. ST analysis supported these clones were located at the invasion site of SCC. We suggest COL6A1 and ITGA5 promote the invasive and metastatic property of SCC. We also uncovered how SCC recruits Tregs via the CXCL16/CXCR6 axis to create a TME favorable for its survival. These molecules can be used as potential therapeutic targets for treatment of SCC.

BackgroundImmune checkpoint inhibitors (ICIs) significantly improve patient outcome, almost doubling progression-free survival (PFS) in patients with advanced non-small cell lung cancer (NSCLC). Unfortunately, most advanced NSCLC patients are non-responders and...

PD09-11 SPATIAL TRANSCRIPTOME ANALYSIS REVEALS THE TUMOR HETEROGENEITY AND NICHE FACTORS IN PROGRESSIVE PROSTATE CANCER

In chromosome 11, 71 out of its 1254 proteins remain functionally uncharacterized on the basis of their existence evidence (uPE1s) following the latest version of neXtProt (release 2020-01-17). Because in vivo and in vitro experimental strategies are often time-consuming and labor-intensive, there is a need for a bioinformatics tool to predict the function annotation. Here, we used I-TASSER/COFACTOR provided on the neXtProt web site, which predicts gene ontology (GO) terms based on the 3D structure of the protein. I-TASSER/COFACTOR predicted 2413 GO terms with a benchmark dataset of the 22 proteins belonging to PE1 of chromosome 11. In this study, we developed a filtering algorithm in order to select specific GO terms using the GO map generated by I-TASSER/COFACTOR. As a result, 187 specific GO terms showed a higher average precision-recall score at the least cellular component term compared to 2413 predicted GO terms. Next, we applied 65 proteins belonging to uPE1s of chromosome 11, and then 409 out of 6684 GO terms survived, where 103 and 142 GO terms of molecular function and biological process, respectively, were included. Representatively, the cellular component GO terms of CCDC90B, C11orf52, and the SMAP were predicted and validated using the overexpression system into 293T cells and immunofluorescence staining. We will further study their biological and molecular functions toward the goal of the neXt-CP50 project as a part of C-HPP. We shared all results and programs in Github (https://github.com/heeyounh/I-TASSER-COFACTOR-filtering.git).

Background and Aims Glomerulonephritis is an autoimmune glomerular inflammation that can lead to severe morbidity and mortality if left untreated. Conventional treatment for this condition involves the use of glucocorticoids and immunosuppressive drugs. In recent years, Rituximab has gained popularity as a treatment for several types of glomerular diseases. Rituximab is a monoclonal antibody that targets the CD20 protein expressed on the surface of B cells. Rituximab has shown promising results in the treatment of a variety of glomerular diseases, including minimal change disease, focal segmental glomerulosclerosis, membranous nephropathy, ANCA vasculitis, and lupus nephritis. This work was performed to study the efficacy and safety of Rituximab in patients with different glomerular diseases managed with the drug in our renal unit. Method This work was conducted in 2022–2023, retrospectively collecting data of adult patients with different glomerular disease treated with Rituximab between January 2019 and October 2022 in a large teaching hospital in the United Kingdom. Data of patients were collected from the electronic patient records system and patient notes. Results A total of 83 patients were included in the analysis 40 Females and 43 Males. The mean age of all the patients was 56 years with range being 20–89 years. Patients had a range of glomerular diseases for which they were treated. The cohort of patients included patients with different glomerular diseases presenting with nephritic (28 patients) and nephrotic presentations (55 patients). Number of patients according to the disease : ANCA Glomerulonephritis (25), Membranous Nephropathy (18), Minimal Change Disease (15), Lupus Nephritis (10) , Focal Segmental Glomerulosclerosis (9), Immune Complex GN(3), and C1q Nephropathy (2) and mesangial proliferative glomerulonephritis (1). Patients with nephrotic presentations had significant improvement in their Urinary Protein Creatinine Ratio (UPCR) (P = &amp;lt;0.001). There was also significant suppression of B cell load (P = &amp;lt;0.001). We analysed patients presented with both nephritic and nephrotic presentations (81 patients) looking at kidney survival (2 patients excluded as they were on dialysis and had Rituximab for relapse with pulmonary haemorrhage). Only 7 patients (9%) progressed to end stage renal disease (ESRD) and dialysis suggesting Rituximab had (91%) success rate in preserving renal survival and preventing progression to ESRD and dialysis treatment. The length of time B cells stayed suppressed (&amp;lt;1%) was analysed. B cells stayed suppressed for a significant amount of time longer than the six-month dosing schedule of Rituximab (P = &amp;lt;0.001). This suppression was significantly longer in males than females (P &amp;lt; 0.01). The safety of Rituximab was also assessed. Patients received 263 doses during the study period. Fifteen adverse effects were recorded. Five patients sadly died during the study period. Of significance, one patient died due to COVID-19 infection and another one due to septic colonic perforation. Conclusion Rituximab was effective in preserving renal survival and stopping progression to ESRD in patients with the different studied glomerular diseases. It was highly effective in treating proteinuria and suppressing B cells for a significantly longer time than the known six-month period. This point at the possible use of longer dosing interval regimens for patients may be appropriate. Rituximab is a safe drug to use in the patients with glomerulonephritis with clear efficacy in managing renal disease and a good safety profile.

Molecular fingerprinting of the podocyte reveals novel gene and protein regulatory networks

Spatial transcriptomics has gained popularity over the past decade due to its ability to evaluate transcriptome data while preserving spatial information. Cell segmentation is a crucial step in spatial transcriptomic analysis, as it enables the avoidance of unpredictable tissue disentanglement steps. Although high-quality cell segmentation algorithms can aid in the extraction of valuable data, traditional methods are frequently non-spatial, do not account for spatial information efficiently, and perform poorly when confronted with the problem of spatial transcriptome cell segmentation with varying shapes. In this study, we propose ST-CellSeg, an image-based machine learning method for spatial transcriptomics that uses manifold for cell segmentation and is novel in its consideration of multi-scale information. We first construct a fully connected graph which acts as a spatial transcriptomic manifold. Using multi-scale data, we then determine the low-dimensional spatial probability distribution representation for cell segmentation. Using the adjusted Rand index (ARI), normalized mutual information (NMI), and Silhouette coefficient (SC) as model performance measures, the proposed algorithm significantly outperforms baseline models in selected datasets and is efficient in computational complexity.

Since its first application in 2016, spatial transcriptomics has become a rapidly evolving technology in recent years. Spatial transcriptomics enables transcriptomic data to be acquired from intact tissue sections and provides spatial distribution information and remedies the disadvantage of single-cell RNA sequencing (scRNA-seq), whose data lack spatially resolved information. Presently, spatial transcriptomics has been widely applied to various tissue types, especially for the study of tumor heterogeneity. In this review, we provide a summary of the research progress in utilizing spatial transcriptomics to investigate tumor heterogeneity and the microenvironment with a focus on solid tumors. We summarize the research breakthroughs in various fields and perspectives due to the application of spatial transcriptomics, including cell clustering and interaction, cellular metabolism, gene expression, immune cell programs and combination with other techniques. As a combination of multiple transcriptomics, single-cell multiomics shows its superiority and validity in single-cell analysis. We also discuss the application prospect of single-cell multiomics, and we believe that with the progress of data integration from various transcriptomics, a multilayered subcellular landscape will be revealed.

The progression and prognosis of early-stage lung adenocarcinoma are closely associated with histologic subtypes, yet the presence of mixed histologic patterns often complicates prognostic assessment. Currently, the correlation between molecular and histologic features remains poorly understood. Formalin-fixed paraffin-embedded (FFPE) samples were collected from patients with primary early-stage lung adenocarcinoma, encompassing three histologic subtypes: well-differentiated, moderately differentiated, and poorly differentiated. The GeoMx Digital Spatial Profiler platform was utilized to obtain spatial transcriptomic profiling. Regions of interest were carefully selected and further subdivided into three categories of areas of interest, specifically epithelial cell-enriched regions, macrophage-enriched regions, and other regions. Multiplex immunofluorescence (mIF) assays were employed to validate the obtained results. Distinct molecular characteristics were identified in tumor epithelial- and macrophage-enriched compartments spanning well-differentiated to poorly differentiated tumors. In poorly differentiated tumors, we observed enrichment of pathways related to humoral immune response, complement activation regulation, and extracellular matrix receptor interaction pathways, all of which are significantly associated with poorer prognosis. We integrated these pathways to develop a composite molecular signature that strongly correlate with adverse prognosis. Our results provide new insights into the link between molecular and histologic subtypes in mixed-type lung adenocarcinomas. Specifically, the identified molecular signatures offer potential biomarkers for predicting disease progression and prognosis, thus facilitating more precise and personalized therapeutic approaches. Poorly differentiated components in mixed-type early-stage lung adenocarcinoma (LUAD) are characterized by enrichment of humoral immune response, complementactivation regulation, and extracellular matrix receptor interaction pathways, which areassociated with worse prognosis. A composite molecular signature integrating the keypathways strongly correlates with adverse clinical outcomes, serving as apotential prognostic biomarker. Digital spatial transcriptomics reveals spatially resolvedmolecular heterogeneity in tumor epithelial- and macrophage-enrichedcompartments, bridging the gap between histologic subtypes and molecularmechanisms in LUAD.

Biological processes are accomplished by the coordinated action of gene products. Gene products often participate in multiple processes, and can therefore be annotated to multiple Gene Ontology (GO) terms. Nevertheless, processes that are functionally, temporally and/or spatially distant may have few gene products in common, and co-annotation to unrelated processes probably reflects errors in literature curation, ontology structure or automated annotation pipelines. We have developed an annotation quality control workflow that uses rules based on mutually exclusive processes to detect annotation errors, based on and validated by case studies including the three we present here: fission yeast protein-coding gene annotations over time; annotations for cohesin complex subunits in human and model species; and annotations using a selected set of GO biological process terms in human and five model species. For each case study, we reviewed available GO annotations, identified pairs of biological processes which are unlikely to be correctly co-annotated to the same gene products (e.g. amino acid metabolism and cytokinesis), and traced erroneous annotations to their sources. To date we have generated 107 quality control rules, and corrected 289 manual annotations in eukaryotes and over 52 700 automatically propagated annotations across all taxa.

Background: The SCRUM-Japan MONSTAR-SCREEN and CIRCULATE-Japan platforms have successfully implemented organ-agnostic liquid biopsy-based precision oncology and molecular residual disease (MRD)-guided therapeutic development, leading to multiple regulatory approvals of therapeutic agents and diagnostics through collection of quality-assured clinical data. Understanding tumor heterogeneity and microenvironment dynamics remains fundamental to advancing precision medicine. Here, we present MONSTAR-SCREEN-3, an innovative large-scale prospective study platform designed to integrate high-resolution spatial transcriptomics with multi-omics analysis across diverse cancer types. In our preliminary analyses, spatial transcriptomic analysis of HER2-amplified metastatic colorectal cancer revealed that treatment responses to anti-HER2 therapy are closely associated with tumor microenvironment characteristics, including increased T and B cell infiltration and interactions between cancer stem-like cells and HER2-expressing cells. Methods: MONSTAR-SCREEN-3 (UMIN000053975) is a large-scale multi-institutional study involving 55 centers across Japan, planning to enroll 3,200 patients stratified into three distinct cohorts: advanced solid tumors undergoing systemic therapy (n=1,700), resectable solid tumors receiving definitive treatment (n=1,100), and hematologic malignancies (n=400). The study implements systematic multi-sampling at strategically defined timepoints. Our comprehensive molecular characterization utilizes 5000Plex spatial transcriptomics integrated with circulating tumor DNA/RNA sequencing, bulk tissue WES/WTS, plasma proteomics, and microbiome analyses. Standardized longitudinal monitoring with WGS-based MRD analysis is implemented in resectable cases, while disease-specific MRD assessment approaches are applied to hematologic malignancies. Following SCRUM-Japan's established quality assurance system, standardized monitoring collects regulatory-grade clinical data, including objective response rate, progression-free survival, and overall survival. All molecular and clinical data will be integrated into our VAPOR CONE supercomputing infrastructure, creating an AI-driven ecosystem. This large-scale implementation of spatial transcriptomics analysis across multiple cancer types represents an unprecedented opportunity to comprehensively map the tumor microenvironment architecture and its dynamics during treatment. The integration of this spatial information with molecular and clinical data will provide unprecedented insights into tumor-immune interactions and resistance mechanisms, establishing an evidence-based framework for next-generation precision oncology. Citation Format: Mitsuho Imai, Shingo Sakashita, Junichiro Yuda, Shin Kobayashi, Riu Yamashita, Tadayoshi Hashimoto, Takao Fujisawa, Taro Shibuki, Shun-Ichiro Kageyama, Yoshikatsu Koga, Michiko Nagamine, Takeshi Kuwata, Hideaki Bando, Yoshiaki Nakamura, Woong-Yang Park, Takayuki Yoshino. SCRUM-Japan MONSTAR-SCREEN-3: A large-scale multi-institutional prospective study platform integrating spatial transcriptomics and multi-omics analysis for comprehensive understanding of tumor microenvironment dynamics [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 1154.