Citations

Abstract A variety of genetic diseases of the kidney tubule are amenable to correction via gene therapy. However, gene delivery to renal tubule epithelial cells mediated by viral vectors via the blood is inefficient due to the permselectivity of the glomerular barrier. We hypothesized that effacement of podocyte foot processes would disrupt typical glomerular limitations on filtration and make renal tubule epithelial cells susceptible to transduction from viral vectors delivered intravenously. We determined that adeno-associated virus serotype 8 (AAV8) transduced significantly more epithelial cells in the kidney under the conditions of LPS-induced proteinuria. Use of AAV1 in tandem with LPS-induced proteinuria yielded an ideal two-pronged effect of both partially detargeting the liver and transducing the kidney with a higher bioluminescent signal than AAV8 did, and at half of the dose. Using adenovirus serotype 5 (Ad5) in conjunction with LPS-induced proteinuria showed that kidney transduction was enhanced, but only in glomerular cells. These studies mechanistically test the efficacy of different viral vectors and demonstrate their capacity to transduce kidney epithelial cells. This is a fundamental step in designing future treatments for kidney gene therapy. Significance Statement The slit diaphragms in the glomerulus of the kidney are too narrow to allow most solute from the blood to enter the nephron. As a result, large particles such as viral vectors generally cannot access tubule epithelial cells necessary to correct genetic disorders. In this study, mice are induced into a state of proteinuria and subsequently administered viral vectors intravenously. This group of mice had higher levels of transduced kidney epithelial cells than the control (non-proteinuria) group. The induction of transient proteinuria before intravenous viral vector administration is a novel approach that could make tubulopathies treatable via gene therapy in both animal models and humans.

Abstract Introduction: We previously developed a urine liquid biopsy assay to measure urine tumor DNA (utDNA) levels in bladder cancer (BC) patients. Here, we extended this approach significantly by layering in cell-free DNA fragmentomic and cell-free RNA analysis, and extending the method to the full spectrum of genitourinary (GU) cancers, to enable both GU cancer detection and tumor tissue of origin prediction. Methods: A total of 155 GU cancer patients and 34 healthy adults were enrolled in this prospective study. Preoperative urine was collected from 94 bladder cancer (BC) patients, including 65 with muscle-invasive disease, all undergoing cystectomy. Additionally, urine samples were collected from 18 renal cell carcinoma (RCC) patients undergoing nephrectomy and 42 metastatic prostate cancer (mPC) patients. Urine cfDNA and cfRNA were isolated and sequenced, with cfRNA sequenced to 100 million reads per sample on an Illumina NovaSeq X and cfDNA sequenced at 5x genome-wide coverage on a Novoseq S4 flow cell. To identify malignant tissue of origin, we analyzed somatic copy number alterations (CNAs), genome-wide fragment length ratios, and 4-mer end motifs. Tumor fraction (TFx) was estimated using ichorCNA, while DELFI was employed for fragment length ratios in 5 megabase bins across the genome and chromosome arm-level z-scores. Individual logistic regression models were developed based on each fragmentomic feature, and validated using a training and held-out testing approach. Outputs from these models were combined into a single comprehensive model, also trained and held-out tested using the same approach. Urine cfRNA transcript isoform abundance was quantified using Salmon and normalized to Transcripts Per Million (TPM) to account for sequencing depth variations. Results: Bladder cancer (BC) showed the highest mean tumor fraction (TFx, 10.5%), followed by RCC (3.8%) and mPC (3.4%). Among 94 BC patients, 42% achieved a pCR, while 58% had residual disease and did not. Patients without pCR had significantly higher urine TFx compared to those with pCR (14.7% vs. 4.7%, p=0.0008). A machine learning model based on genome-wide fragment length ratios achieved an ROC AUC of 0.74, while models using genome-wide CNAs and end motifs achieved AUCs of 0.81 and 0.88, respectively. Combining all features into a single model yielded an AUC of 0.92, with classification accuracies of 89% for bladder cancer, 80% for RCC, and 60% for prostate cancer. Additionally, urine cfRNA analysis using the top 1, 000 coding transcripts achieved an AUC of 0.95, with classification accuracies of 100% for mPC, 87% for BC, and 78% for RCC. Conclusion: Fragmentomic features from urine cfDNA and transcriptomic features from urine cfRNA demonstrate strong potential for predicting tumor tissue-of-origin in GU cancers, underscoring the promise of non-invasive diagnosis across the spectrum of GU malignancies through urine liquid biopsy. Citation Format: Pradeep Singh Chauhan, Irfan Alahi, Jessica Linford, Arpit Panda, Nathan Colon, Ryan Mueller, Faridi Qaium, Peter K. Harris, John Sheng, Eric H. Kim, Melissa A. Reimers, Zachary L. Smith, Woodson W. Smelser, Aadel A. Chaudhuri. Predicting genitourinary cancer tissue-of-origin using urine cell-free DNA fragmentomics and cell-free RNA [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 3258.

Background: Multicellular programs in the tumor microenvironment (TME) drive cancer pathogenesis and response to therapy but remain challenging to identify and profile clinically. Here, we present Spatial EcoTyper, a multimodal machine learning framework for large-scale profiling of spatially dependent cell states and multicellular ecosystems, termed spatial ecotypes (SEs). Methods and Findings: By integrating five million single-cell and spot-level spatial transcriptomes from 10 diverse human neoplasms, including carcinomas and melanomas, we identified a rich tapestry of conserved regional plasticity across nine TME cell types. We then applied Spatial EcoTyper to deeply dissect these data, revealing nine novel SEs with broad conservation - each with unique biology, TME cell states, geospatial features, and clinical outcome associations. SEs were linked to specific biogeographic domains, including the tumor core, margin, and adjacent stroma, and were remarkably well-validated in 235 held-out tumor samples profiled by either single-cell RNA sequencing, sequencing-based spatial transcriptomics (10x Visium), or high-resolution imaging-based spatial transcriptomics (Vizgen MERSCOPE and NanoString CosMx). By deconvolving SEs from over 1,200 bulk tumor RNA-seq profiles, we discovered striking associations between SE levels and response to immune checkpoint inhibitors (ICIs), outperforming nearly 40 potential correlates of ICI response, including previously described signatures of tertiary lymphoid structures and tumor tissue PD-L1 expression. Notably, baseline levels of a proinflammatory SE - localized to the tumor core and defined by a hub of unique T cell, macrophage, fibroblast, and endothelial cell states - strongly forecasted ICI benefit, while another SE - localized to the tumor margin and defined by myofibroblast and hypoxia-associated endothelial cell states - portended ICI resistance. Conclusion: Our data reveal fundamental units of TME organization and demonstrate a platform for large-scale profiling of spatial cellular ecosystems in any tissue, with implications for improved forecasting of immunotherapy response and the development of novel therapeutic strategies. Citation Format: Wubing Zhang,Erin L. Brown,Abul Usmani,Noah Earland,Hyun Soo Jeon,Irfan Alahi,Nicholas P. Semenkovich,Janella C. Schwab,Chloé B. Steen,Chloe M. Sachs,Bilge Gungoren,Faridi Qaium,Peter K. Harris,Jacqueline Mudd,Qingyuan Cai,Antonella Bacchiocchi,Ryan C. Fields,Mario Sznol,Ruth Halaban,David Y. Chen,Aadel A. Chaudhuri,Aaron M. Newman. High-resolution profiling of the tumor microenvironment with spatial ecotypes [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 153.

Importance Autosomal dominant polycystic kidney disease (ADPKD) is characterized by progressive development of kidney cysts and is the most common inherited kidney disorder worldwide. ADPKD accounts for 5% to 10% of kidney failure in the US and Europe, and its prevalence in the US is 9.3 per 10 000 individuals. Observations ADPKD is typically diagnosed in individuals aged 27 to 42 years and is primarily caused by pathogenic variants in the PKD1 (78%) or PKD2 (15%) genes. Most persons with ADPKD have an affected parent, but de novo disease is suggested in 10% to 25% of families. More than 90% of patients older than 35 years have hepatic cysts, which may cause abdominal discomfort and occasionally require medical or surgical intervention. Hypertension affects 70% to 80% of patients with ADPKD, and approximately 9% to 14% develop intracranial aneurysms, which have a rupture rate of 0.57 per 1000 patient-years. Approximately 50% of individuals with ADPKD require kidney replacement therapy by 62 years of age. The severity of kidney disease can be quantified using the Mayo Imaging Classification (MIC), which stratifies patients based on total kidney volume adjusted for height and age and ranges from 1A to 1E. Patients with MIC 1C to MIC 1E have larger kidneys because of more rapid growth (6%-10% per year) compared with those with MIC 1A and 1B (1%-5% per year) and have earlier progression to kidney replacement therapy, which occurs at a mean age of 58.4 years for MIC 1C, 52.5 years for MIC 1D, and 43.4 years for MIC 1E. Optimal management of ADPKD includes systolic blood pressure lower than 120 mm Hg for most patients, but lower than 110/75 mm Hg for patients with MIC 1C to 1E who have an estimated glomerular filtration rate (eGFR) greater than 60 mL/min/1.73 m 2 and are younger than 50 years, dietary sodium restriction (<2000 mg/d), weight management, and adequate hydration (>2.5 L daily). The vasopressin type 2 receptor antagonist tolvaptan reduces the annual rate of eGFR decline by 0.98 to 1.27 mL/min/1.73 m 2 and is indicated for patients with MIC 1C to 1E or an eGFR decline greater than 3 mL/min/1.73 m 2 per year to slow disease progression and delay the onset of kidney failure. Conclusion ADPKD is the most common genetic kidney disease worldwide and is characterized by progressive development of kidney cysts. Patients typically have hypertension and liver cysts, and 9% to 14% develop intracranial aneurysms. First-line treatment includes blood pressure control, dietary and weight management, and adequate hydration. Tolvaptan reduces the rate of eGFR decline for those at high risk of rapid progression to kidney failure.

Key Points Loss-of-function ALG8 and ALG9 variants were enriched in polycystic kidney/liver groups and International Classification of Diseases–coded cystic individuals in population cohorts. The ALG8 and ALG9 kidney phenotypes were usually mild to moderate, and lower eGFR or kidney failure was rare. ALG8 pathogenic variants sometimes resulted in severe polycystic liver disease. Background Autosomal dominant polycystic kidney disease (ADPKD) is a common, inherited nephropathy often resulting in kidney failure. It is genetically heterogeneous; along with the major genes, PKD1 and PKD2 , at least eight others have been suggested. ALG8 pathogenic variants have been associated with autosomal dominant polycystic liver disease and implicated in ADPKD, while ALG9 has been suggested as an ADPKD gene, but details of the phenotypes and penetrance are unclear. Methods We screened >3900 families with cystic kidneys and/or livers using global approaches to detect ALG8 or ALG9 pathogenic variants. In addition, population cohorts with sequence data (Genomics England 100K Genomics Project, UK Biobank, and Mayo Clinic Biobank [MCBB]) were screened for ALG8 / ALG9 pathogenic variants. Results Multicenter screening of individuals with polycystic kidney and/or liver disease identified 51 (1.3%) ALG8 (7 multiplex) and 23 (0.6%) ALG9 (5 multiplex) families—frequencies that were approximately 10× and approximately 24× greater than nonpolycystic kidney disease controls. Analysis of individuals with polycystic kidney disease phenotypes in 100K Genomics Project, UK Biobank, and MCBB identified nine ALG8 (0.39%) and nine ALG9 (0.39%) families, an enriched frequency over controls. Two individuals had PKD1 and ALG8 pathogenic changes. Eighty-nine percent of individuals with ALG8 mutations with imaging in the entire MCBB had kidney cysts (50%, >10 cysts), with greater median kidney and liver cyst numbers than controls. For ALG9, 78% had kidney cysts (27%, >10 cysts). Individuals with ALG8 mutations typically had mild cystic kidneys with limited enlargement. Liver cysts were common (71%), with enlarged livers (>2L) found in 11 of 62 patients, although surgical intervention was rare. The ALG9 kidney phenotype was also of mild cystic kidneys, but enlarged livers were rare; for both genes, CKD or kidney failure were rare. Conclusions ALG8 and ALG9 are defined as cystic kidney/liver genes but with limited penetrance for lower eGFR.