Background/Objectives: Upper tract urothelial carcinoma (UTUC) is a rare and biologically distinct subset of urothelial malignancies, comprising approximately 5–10% of urothelial cancers. UTUC presents unique diagnostic and therapeutic challenges, with both a higher likelihood of invasive disease at presentation and a less favorable prognosis compared to urothelial carcinoma of the bladder. Current treatment strategies for UTUC are largely derived from bladder cancer studies, underscoring the need for UTUC-directed research. This review provides a comprehensive overview of UTUC, encompassing diagnostic approaches, systemic and intraluminal therapies, surgical management, and future directions. Methods: A narrative review was conducted synthesizing evidence from guideline-based recommendations, retrospective and prospective clinical studies, and ongoing trials focused on UTUC. Results: Neoadjuvant cisplatin-based chemotherapy is increasingly preferred in UTUC due to the risk of postoperative renal impairment that may preclude adjuvant cisplatin use. Surgical management includes kidney-sparing approaches and radical nephroureterectomy (RNU), with selection guided by tumor risk and patient comorbidities. While endoscopic management (EM) preserves renal function, it carries a higher recurrence and surveillance burden; RNU remains standard for high-risk cases. Systemic therapy for advanced and metastatic UTUC mirrors that of bladder urothelial carcinoma. Enfortumab vedotin (EV) plus pembrolizumab showed superior efficacy over chemotherapy in the EV-302 trial, with improved response rate, progression-free survival, and overall survival across subgroups, including UTUC. For patients ineligible for EV, the CheckMate-901 study supported first-line chemoimmunotherapy with gemcitabine, cisplatin, and nivolumab. Further systemic therapy strategies include maintenance avelumab post-chemotherapy (JAVELIN Bladder 100), targeted therapies such as erdafitinib (THOR trial), and trastuzumab deruxtecan (DESTINY-PanTumor02) in FGFR2/3-altered and HER2-positive disease, respectively. Conclusions: Historically, the therapeutic landscape of UTUC has been extrapolated from bladder cancer; however, ongoing research specific to UTUC is deriving more precise regimens involving the use of immune checkpoint inhibitors, antibody–drug conjugates, and biomarker-driven therapies.

Population-scale single-cell transcriptomic technologies (scRNA-seq) enable characterizing variant effects on gene regulation at the cellular level (e.g., single-cell eQTLs; sc-eQTLs). However, existing sc-eQTL mapping approaches are either not designed for analyzing sparse counts in scRNA-seq data or can become intractable in extremely large datasets. Here, we propose jaxQTL, a flexible and efficient sc-eQTL mapping framework using highly efficient count-based models given pseudobulk data. Using extensive simulations, we demonstrated that jaxQTL with a negative binomial model outperformed other models in identifying sc-eQTLs, while maintaining a calibrated type I error. We applied jaxQTL across 14 cell types of OneK1K scRNA-seq data ( N =982), and identified 11-16% more eGenes compared with existing approaches, primarily driven by jaxQTL ability to identify lowly expressed eGenes. We observed that fine-mapped sc-eQTLs were further from transcription starting site (TSS) than fine-mapped eQTLs identified in all cells (bulk-eQTLs; P =1×10 ⁻⁴ ) and more enriched in cell-type-specific enhancers ( P =3×10 ⁻¹⁰ ), suggesting that sc-eQTLs improve our ability to identify distal eQTLs that are missed in bulk tissues. Overall, the genetic effect of fine-mapped sc-eQTLs were largely shared across cell types, with cell-type-specificity increasing with distance to TSS. Lastly, we observed that sc-eQTLs explain more SNP-heritability ( h ² ) than bulk-eQTLs (9.90 ± 0.88% vs. 6.10 ± 0.76% when meta-analyzed across 16 blood and immune-related traits), improving but not closing the missing link between GWAS and eQTLs. As an example, we highlight that sc-eQTLs in T cells (unlike bulk-eQTLs) can successfully nominate IL6ST as a candidate gene for rheumatoid arthritis. Overall, jaxQTL provides an efficient and powerful approach using count-based models to identify missing disease-associated eQTLs.