Bladder cancer (BC) is a heterogeneous disease with varying clinical outcomes. Recent evidence suggests that cancer progression involves the acquisition of stem-like signatures, and assessing stemness indices help uncover patterns of intra-tumor molecular heterogeneity. We used the one-class logistic regression algorithm to compute the mRNAsi for each sample in BLCA cohort. We subsequently classified BC patients into two subtypes based on 189 mRNAsi-related genes, using the unsupervised consensus clustering. Then, we identified nine hub genes to construct a stemness-related prognostic index (SRPI) using Cox regression, LASSO regression and Random Forest methods. We further validated SRPI using two independent datasets. Afterwards, we examined the molecular and immune characterized of SRPI. Finally, we conducted multiply drug screening and experimental approaches to identify and confirm the most proper agents for patients with high SRPI. Based on the mRNAsi-related genes, BC patients were classified into two stemness subtypes with distinct prognosis, functional annotations, genomic variations and immune profiles. Using the SRPI, we identified a specific subgroup of BC patients with high SRPI, who had a poor response to immunotherapy, and were less sensitive to commonly used chemotherapeutic agents, FGFR inhibitors, and EGFR inhibitors. We further identified that dasatinib was the most promising therapeutic agent for this subgroup of patients. This study provides further insights into the stemness classification of BC, and demonstrates that SRPI is a promising tool for predicting prognosis and therapeutic opportunities for BC patients.

To understand how brain regions form and work, it is important to explore the spatially variable genes (SVGs) enriched in specific brain regions during development. Spatial transcriptomics techniques provide opportunity to select SVGs in the high-throughput way. However, previous methods neglected the ranking order and combinatorial effect of SVGs, making them difficult to automatically select the high-priority SVGs from spatial transcriptomics data. Here, we proposed a novel computational pipeline, called SVGbit, to rank the individual and combinatorial SVGs for marker selection in various brain regions, which was tested in different kinds of public datasets for both human and mouse brains. We then generated the spatial transcriptomics and immunohistochemistry data from mouse brain at critical embryonic and neonatal stages. The results show that our ranking and clustering scheme captures the key SVGs which coincide with known anatomic regions in the developing mouse brain. More importantly, SVGbit can facilitate the identification of multiple gene combination sets in different brain regions. We identified three dynamical sub-regions which can be segregated by the staining of Sox2 and Calb2 in thalamus, and we also found that Nr4a2 expression gradually segregates the neocortex and hippocampus during the development. In summary, our work not only reveals the spatiotemporal dynamics of individual and combinatorial SVGs in developing mouse brain, but also provides a novel computational pipeline to facilitate the selection of marker genes from spatial transcriptomics data.

The fetal membranes are equipped with high capacity of cortisol regeneration through the reductase activity of 11β-hydroxysteroid dehydrogenase 1 (11β-HSD1). The expression of 11β-HSD1 in the fetal membranes is under the feedforward induction by cortisol, which is potentiated by proinflammatory cytokines. As a result, the abundance of 11β-HSD1 increases with gestational age and furthermore at parturition with an escalation of cortisol concentration in the fetal membranes. Accumulated cortisol takes parts in a number of crucial events pertinent to the onset of labor in the fetal membranes, including extracellular matrix (ECM) remodeling and stimulation of prostaglandin output. Cortisol remodels the ECM through multiple approaches including induction of collagen I, III, and IV degradation, as well as inhibition of their cross-linking. These effects of cortisol are executed through activation of the autophagy, proteasome, and matrix metalloprotease 7 pathways, as well as inhibition of the expression of cross-linking enzyme lysyl oxidase in mesenchymal cells of the membranes. With regard to prostaglandin output, cortisol not only increases prostaglandin E2 and F2α syntheses through induction of their synthesizing enzymes such as cytosolic phospholipase A2, cyclooxygenase 2, and carbonyl reductase 1 in the amnion, but also decreases their degradation through inhibition of their metabolizing enzyme 15-hydroxyprostaglandin dehydrogenase in the chorion. Taking all together, data accumulated so far denote that the feedforward cortisol regeneration by 11β-HSD1 in the fetal membranes is a requisite event in the onset of parturition, and the effects of cortisol on prostaglandin synthesis and ECM remodeling may be enhanced by proinflammatory cytokines in chorioamnionitis.

Hematopoiesis ensures tissue oxygenation, and remodeling as well as immune protection in vertebrates. During embryogenesis, hemangioblasts are the source of all blood cells. Gata1a and pu.1 are co-expressed in hemangioblasts before hemangioblasts are differentiated into blood cells. However, the genes that determine the differentiation of hemangioblasts into myeloid or erythroid cell lineages have not been fully uncovered. Here we showed that miRNA-7145, a miRNA with previously unknown function, was enriched in erythrocytes at the definitive wave, but not expressed in myeloid cells. Overexpression and loss-of-function analysis of miRNA-7145 revealed that miRNA-7145 functions as a strong inhibitor for myeloid progenitor cell differentiation while driving erythropoiesis during the primitive wave. Furthermore, we confirmed that cuedc2 is one of miRNA-7145 targeted-genes. Overexpression or knock-down of cuedc2 partially rescues the phenotype caused by miRNA-7145 overexpression or loss-of-function. As well, overexpression and loss-of-function analysis of cuedc2 showed that cuedc2 is required for myelopoiesis at the expense of erythropoiesis. Finally, we found that overexpression of zebrafish cuedc2 in 293 T cell inhibits the JAK1/STAT3 signaling pathway. Collectively, our results uncover a previously unknown miRNA-7145-cuedc2 axis, which regulate hematopoiesis through inhibiting the JAK1/STAT3 signaling pathway.

ARID1A is among the most frequently mutated genes in bladder cancer, yet no targeted therapy exists for this molecular subset. Here, we identify ferroptosis induction as a synthetic lethal strategy in ARID1A-deficient bladder cancer. We found that ARID1A loss impaired the NRF2-SLC7A11-glutathione (GSH) axis, leading to redox imbalance and profound sensitivity to the ferroptosis inducer RSL-3. In vitro, ARID1A knockdown depleted intracellular GSH and enhanced RSL-3-induced lipid peroxidation and cell death. Mechanistically, ARID1A directly regulated NRF2 transcription and its target SLC7A11, and restoring SLC7A11 or NRF2 activity or GSH levels rescued ferroptosis sensitivity. In vivo, RSL-3 treatment delayed tumor progression, reduced muscle invasion, and improved survival in two types of Arid1a -deficient mouse models. Furthermore, patient-derived organoids from ARID1A-low human tumors exhibited heightened RSL-3 sensitivity rather than ARID1A-high tumor. Our findings establish ferroptosis as a targetable vulnerability in ARID1A-deficient bladder cancer and provide a compelling rationale for clinical translation of ferroptosis-based therapies in this molecularly defined population.