Citations

Stem cell-derived kidney organoids enable human genetic disease modeling to identify the parathyroid hormone 1 receptor as a potential new therapeutic target for developmental polycystic kidney disease.

Tuberous sclerosis complex (TSC) is a highly variable autosomal dominant disease characterized by dysregulated organ development and growth. Benign tumors, termed hamartomas, may occur across organ systems but typically involve the kidney, brain, skin, heart, and lung. The diagnosis, surveillance, and clinical management of TSC requires a multidisciplinary approach, adopted by dedicated multispecialty centers worldwide. Nephrology involvement predominantly stems from the morbidity and mortality related to the prototypical kidney lesion, angiomyolipomas, whose presence and degree confers risk of CKD, hypertension, retroperitoneal bleeding, and possibly renal cell carcinoma. Surveillance of kidney structural lesions, kidney function, and BP may enable early interventions that limit kidney-related morbidity and mortality, such as mammalian target of rapamycin inhibitor therapy. We review the epidemiology, genetics, and pathogenesis of TSC and how these inform the evaluation, diagnosis, and clinical management of TSC from the vantage point of the treating nephrologist.

Kidney organoids are an increasingly established model of polycystic kidney disease (PKD). Derived from human pluripotent stem cells (hPSCs), organoids may be generated from induced pluripotent stem cells (iPSCs) of patients that bear naturally occurring mutations or from CRISPR mutant hPSCs by virtue of their genetic tractability. PKD is the leading inheritable cause of kidney failure (KF), accounting for ∼5%–10% of the kidney transplant and dialysis needs worldwide. PKD is a disorder of considerable genetic heterogeneity, composed of typical adult-onset autosomal dominant (ADPKD) and fetal-onset autosomal recessive (ARPKD) forms, which share pathomechanisms. Despite advances in our understanding of the genetic and molecular underpinnings of PKD, the limited clinical treatment options have raised concerns regarding the faithfulness of preclinical models. Kidney organoids have emerged as a promising platform to study PKD by mimicking human-specific responses, enabling personalized medicine, and supporting high-throughput screens. Yet, valid criticisms have related to the relative immaturity of kidney organoids for modeling adult-onset forms of PKD, the faithfulness of organoids in modeling the cystic distribution of afflicted patients, and their batch-to-batch variability limiting experimental reproducibility. Here, we summarize a decade of kidney organoid models of PKD, emphasizing their role in advancing translational and therapeutic applications while addressing their limitations and future potential.

Breast cancer is the second-leading cause of mortality among women around the world. Ultrasound (US) is one of the noninvasive imaging modalities used to diagnose breast lesions and monitor the prognosis of cancer patients. It has the highest sensitivity for diagnosing breast masses, but it shows increased false negativity due to its high operator dependency. Underserved areas do not have sufficient US expertise to diagnose breast lesions, resulting in delayed management of breast lesions. Deep learning neural networks may have the potential to facilitate early decision-making by physicians by rapidly yet accurately diagnosing and monitoring their prognosis. This article reviews the recent research trends on neural networks for breast mass ultrasound, including and beyond diagnosis. We discussed original research recently conducted to analyze which modes of ultrasound and which models have been used for which purposes, and where they show the best performance. Our analysis reveals that lesion classification showed the highest performance compared to those used for other purposes. We also found that fewer studies were performed for prognosis than diagnosis. We also discussed the limitations and future directions of ongoing research on neural networks for breast ultrasound.