Propagation of human naïve pluripotent stem cells (nPSCs) relies on the inhibition of MEK/ERK signalling. However, MEK/ERK inhibition also promotes differentiation into trophectoderm (TE). Therefore, robust self-renewal requires suppression of TE fate. Tankyrase inhibition using XAV939 has been shown to stabilise human nPSCs and is implicated in TE suppression. Here, we dissect the mechanism of this effect. Tankyrase inhibition is known to block canonical Wnt/β-catenin signalling. However, we show that nPSCs depleted of β-catenin remain dependent on XAV939. Rather than inhibiting Wnt, we found that XAV939 prevents TE induction by reducing activation of YAP, a co-factor of TE-inducing TEAD transcription factors. Tankyrase inhibition stabilises angiomotin, which limits nuclear accumulation of YAP. Upon deletion of angiomotin-family members AMOT and AMOTL2, nuclear YAP increases and XAV939 fails to prevent TE induction. Expression of constitutively active YAP similarly precipitates TE differentiation. Conversely, nPSCs lacking YAP1 or its paralog TAZ (WWTR1) resist TE differentiation and self-renewal efficiently without XAV939. These findings explain the distinct requirement for tankyrase inhibition in human but not in mouse nPSCs and highlight the pivotal role of YAP activity in human naïve pluripotency and TE differentiation. This article has an associated ‘The people behind the papers’ interview.

Given that the sterility of urine and the urinary tract has been questioned by research, urinary microbiome dysbiosis has been recognized as one of the potential cancer-promoting factors. The composition of the urinary microbial community in healthy individuals has a relatively high similarity at the phylum level, with factors like age and gender influencing the expression and distribution. In contrast, the urinary microbiome of patients with urologic cancers shows significant variability and diversity depending on the type of cancer. Most of the early studies focused on the distribution, aggregation, and expression of microbiota in urologic cancers, warranting advanced studies on the causal relationship between microbes and urologic cancers. Bladder and prostate cancer tumorigenesis and progression can be influenced by microbes through chronic inflammatory or immunomodulatory pathways making them cancer models strongly associated with the urinary microbiome. Here, we summarize the expression characteristics of the microbiomes associated with these cancers and analyze the pathophysiological mechanisms and signaling pathways of the microbiome in the tumor promotion or suppression. By examining the role played by the urinary microbiome in the pathogenesis of urologic cancers, we assess the potential of specific microbial groups as biomarkers for diagnosis and surveillance. Additionally, involving the microbiome or using adjunctive participation in tumor therapy is becoming an emerging cancer treatment option. Improving urinary microbial homeostasis in urinary cancers by direct treatment with microbial products, microbial co-immunotherapy, probiotic-assisted therapy, and fecal microbial transplantation may broaden the scope of therapy and enhance the efficacy of conventional medicines.

Kidney renal clear cell carcinoma (KIRC) is increasing in incidence worldwide, with poor and unpredictable patient prognosis limited by diagnostic and therapeutic approaches. New genes are urgently needed to improve this situation. The ankyrin repeat and suppressor of the cytokine signaling (SOCS) box (ASB) family are a promising class of tumorigenesis-related genes. We examined the expression and mutation of 18 ASB genes in various tumors for this study. The findings revealed that ASB genes exhibit significant copy number variation (CNV) and single nucleotide variation (SNV). There were substantial variations in ASB gene expression in different tumor tissues, and different levels of methylation of ASB genes affected the gene expression and tumor progression. By applying LASSO regression analysis, we established a KIRC survival model based on five ASB genes (ASB6, ASB7, ASB8, ASB13, and ASB17). Additionally, ROC curve analysis was used to assess the survival model’s accuracy. Through univariate and multivariate COX regression analysis, we demonstrated that the model’s risk score might be an independent risk factor for individuals with KIRC. In summary, our KIRC survival model could accurately predict patients’ future survival. Further, we also quantified the survival model through a nomogram. This series of findings confirmed that ASB genes are potential predictive markers and targeted therapies for KIRC. Our KIRC survival model based on five ASB genes can help more clinical practitioners make accurate judgments about the prognosis of KIRC patients.