Beyond playing games: nephrologist vs machine in pediatric dialysis prescribing

In a recent article in Pediatric Nephrology, Olivier Niel and colleagues applied an artificial intelligence algorithm to a clinical problem that continues to challenge experienced pediatric nephrologists: optimizing the target weight of children on dialysis. They compared blood pressure, antihypertensive medication and intradialytic symptoms in children whose target weight was prescribed firstly by a nephrologist, then subsequently using a machine learning algorithm. Improvements in all outcome measures are reported. Their innovative approach to tackling this important clinical problem appears promising. In this editorial, we discuss the strengths and weaknesses of their study and consider to what extent machine learning strategies are suited to optimizing pediatric dialysis outcomes

Acute kidney injury promotes development of papillary renal cell adenoma and carcinoma from renal progenitor cells.

Acute tissue injury causes DNA damage and repair processes involving increased cell mitosis and polyploidization, leading to cell function alterations that may potentially drive cancer development. Here, we show that acute kidney injury (AKI) increased the risk for papillary renal cell carcinoma (pRCC) development and tumor relapse in humans as confirmed by data collected from several single-center and multicentric studies. Lineage tracing of tubular epithelial cells (TECs) after AKI induction and long-term follow-up in mice showed time-dependent onset of clonal papillary tumors in an adenoma-carcinoma sequence. Among AKI-related pathways, NOTCH1 overexpression in human pRCC associated with worse outcome and was specific for type 2 pRCC. Mice overexpressing NOTCH1 in TECs developed papillary adenomas and type 2 pRCCs, and AKI accelerated this process. Lineage tracing in mice identified single renal progenitors as the cell of origin of papillary tumors. Single-cell RNA sequencing showed that human renal progenitor transcriptome showed similarities to PT1, the putative cell of origin of human pRCC. Furthermore, NOTCH1 overexpression in cultured human renal progenitor cells induced tumor-like 3D growth. Thus, AKI can drive tumorigenesis from local tissue progenitor cells. In particular, we find that AKI promotes the development of pRCC from single progenitors through a classical adenoma-carcinoma sequence