A hallmark of aged mesenchymal stem/progenitor cells (MSCs) in bone marrow is the pivot of differentiation potency from osteoblast to adipocyte coupled with a decrease in self-renewal capacity. However, how these cellular events are orchestrated in the aging progress is not fully understood. In this study, we have used molecular and genetic approaches to investigate the role of forkhead box P1 (FOXP1) in transcriptional control of MSC senescence. In bone marrow MSCs, FOXP1 expression levels declined with age in an inverse manner with those of the senescence marker p16^INK4A. Conditional depletion of Foxp1 in bone marrow MSCs led to premature aging characteristics, including increased bone marrow adiposity, decreased bone mass, and impaired MSC self-renewal capacity in mice. At the molecular level, FOXP1 regulated cell-fate choice of MSCs through interactions with the CEBPβ/δ complex and recombination signal binding protein for immunoglobulin κ J region (RBPjκ), key modulators of adipogenesis and osteogenesis, respectively. Loss of p16^INK4A in Foxp1-deficient MSCs partially rescued the defects in replication capacity and bone mass accrual. Promoter occupancy analyses revealed that FOXP1 directly represses transcription of p16^INK4A. These results indicate that FOXP1 attenuates MSC senescence by orchestrating their cell-fate switch while maintaining their replicative capacity in a dose- and age-dependent manner.

Accumulating evidence indicates that cryptochrome circadian regulatory (CRY) proteins have emerged as crucial regulators of osteogenic differentiation. However, the associated mechanisms are quite elusive. In this study, we show that knockdown of CRY2 downregulated the expression of runt-related transcription factor 2 (Runx2), alkaline phosphatase (ALP), osteocalcin (OCN), and osteopontin (OPN) to facilitate osteoblast differentiation. Further study identified that CRY2 was directly targeted by microRNA (miR)-7-5p, which was highly induced during osteoblast differentiation. The expression of Runx2, ALP, collagen type I alpha 1 (Col1a1), and OCN was upregulated by overexpression of miR-7-5p and induction of osteoblast differentiation. Moreover, signal transducer and activator of transcription 3 (STAT3) transcriptionally activated miR-7-5p to significantly enhance the expression of above osteogenic marker genes and mineral formation. However, overexpression of CRY2 abolished the osteogenic differentiation induced by miR-7-5p overexpression. Silencing of CRY2 unraveled the binding of CRY2 with the circadian locomotor output cycles kaput (CLOCK)/brain and muscle ARNT-like 1 (BMAL1) complex to release CLOCK/BMAL1, which facilitated the binding of CLOCK/BMAL1 to the promoter region of the P300 E-box to stimulate the transcription of P300. P300 subsequently promoted the acetylation of histone 3 and the formation of a transcriptional complex with Runx2 to enhance osteogenesis. Taken together, our study revealed that CRY2 is repressed by STAT3/miR-7-5p to promote osteogenic differentiation through CLOCK/BMAL1/P300 signaling. The involved molecules may be potentially targeted for treatment of osteoporosis.

Rap1A is a member of small G proteins belonging to the Ras family. Recently, an integration of human genome-wide association studies (GWAS) and gene expression profiling study revealed that single-nucleotide polymorphisms (SNPs) within human Rap1A were strongly associated with narrow neck width in women. However, the regulatory role of Rap1A in osteoblasts remains to be elucidated. Here we report that Rap1A is a key regulator in osteoblast differentiation. Rap1A expression and activity were gradually enhanced during the induced differentiation of multipotent mesenchymal progenitor cells (C2C12) and preosteoblastic cells (MC3T3-E1). Knockdown of endogenous Rap1A significantly inhibited the osteogenic marker gene expression and matrix mineralization in cells with osteogenesis. In addition, knockdown of endogenous Rap1A suppressed the activation of extracellular signal-regulated kinase (ERK) and p38 mitogen-activated protein kinase (MAPK), while overexpression of Rap1A accelerated osteoblast differentiation and enhanced the phosphorylation of ERK and p38. Taken together, our study suggests that Rap1A regulates osteoblast differentiation through modulating the ERK/p38 signaling.

Background: Few models exist to predict mortality in cancer patients receiving immunotherapy. Our aim was to build a machine learning‐based risk stratification model for predicting mortality in atezolizumab‐treated cancer patients.Methods: Data from 2538 patients in eight atezolizumab‐treated cancer clinical trials across three cancer types (non‐small‐cell lung cancer, bladder transitional cell carcinoma, and renal cell carcinoma) were included. The whole cohort was randomly split into development and validation cohorts in a 7:3 ratio. Machine‐learning algorithms (extreme gradient boosting, random forest, logistic regression with lasso regularization, support vector machine, and K‐nearest neighbor) were applied to develop prediction models. Model performance was mainly assessed by area under the receiver operating characteristic curve (AUC) value, calibration plot, and decision curve analysis. The probability of death risk was then stratified.Results: One thousand and three hundred and seventy‐nine (54.33%) patients died. The random forest (RF) model was overall the best in terms of predictive performance, with the AUC of 0.844 (95% confidence interval [CI]: 0.826–0.862) in the development cohort and 0.786 (95% CI: 0.754–0.818) in the validation cohort for predicting mortality. Twelve baseline variables contributing to mortality prediction in the RF model were C‐reactive protein, PD‐L1 level, cancer type, prior liver metastasis, derived neutrophil‐to‐lymphocyte ratio, alkaline phosphatase, albumin, hemoglobin, white blood cell count, number of metastatic sites, pulse rate, and Eastern Cooperative Oncology Group (ECOG) performance status. A total of 1782 (70.2%) patients were separated into the high‐risk and 756 (29.8%) low‐risk groups. Patients in the high‐risk group were significantly more likely to die, experience disease progression, discontinue study, and discontinue treatment than patients in the low‐risk group (all p values < 0.001). Risk groups were not associated with immune‐related adverse events and grades 3–5 treatment‐related adverse events (all p values > 0.05).Conclusion: RF model has good performance in mortality prediction and risk stratification for cancer patients receiving atezolizumab monotherapy.

BACKGROUND:Circadian disruption is a potential cancer risk factor in humans. However, the role of the clock gene, cryptochrome 2 (CRY2), in osteosarcoma (OS) is still not clear. MATERIAL AND METHODS:To evaluate the potential role of CRY2 in HOS osteo...