An emerging family of innate lymphoid cells (termed ILCs) has an essential role in the initiation and regulation of inflammation. However, it is still unclear how ILCs are regulated in the duration of intestinal inflammation. Here, we identify a regulatory subpopulation of ILCs (called ILCregs) that exists in the gut and harbors a unique gene identity that is distinct from that of ILCs or regulatory T cells (Tregs). During inflammatory stimulation, ILCregs can be induced in the intestine and suppress the activation of ILC1s and ILC3s via secretion of IL-10, leading to protection against innate intestinal inflammation. Moreover, TGF-β1 is induced by ILCregs during the innate intestinal inflammation, and autocrine TGF-β1 sustains the maintenance and expansion of ILCregs. Therefore, ILCregs play an inhibitory role in the innate immune response, favoring the resolution of intestinal inflammation.

In vitro models of the blood brain barrier (BBB) are crucial tools for the study of BBB transport and development of drugs that can reach the CNS. Brain endothelial cells grown in culture are often used to model the BBB however it is challenging to maintain reproducible BBB properties and function. “BBB organoids” are obtained following co-culture of endothelial cells, pericytes and astrocytes under low adhesion conditions. These organoids reproduce many features of the BBB, including the expression of tight junctions, molecular transporters and drug efflux pumps and hence can be used to model drug transport across the BBB. This protocol provides a comprehensive description of the techniques required to culture and maintaina BBB organoids. We also describe two separate detection approaches that can be used to analyze drug penetration into the organoids: confocal fluorescence microscopy and mass spectrometry imaging. Using our protocol, BBB organoids can be established within 2–3 days. An additional day is required to analyse drug permeability. The BBB organoid platform represents an accurate, versatile and cost-effective in vitro tool. It can easily be scaled to a high-throughput format, offering a tool for BBB modeling that could accelerate therapeutic discovery for the treatment of various neuro-pathologies.

Disrupting the balance between self-renewal and differentiation of hematopoietic stem cells (HSCs) leads to bone marrow failure or hematologic malignancy. However, how HSCs sustain their quiescent state and avoid type I interferon (IFN)-mediated exhaustion remains elusive. Here we defined a circular RNA that we named cia-cGAS that was highly expressed in the nucleus of long-term (LT)-HSCs. Cia-cGAS deficiency in mice caused elevated expression of type I IFNs in bone marrow and led to decreased numbers of dormant LT-HSCs. Under homeostatic conditions, cia-cGAS bound DNA sensor cGAS in the nucleus to block its synthase activity, thereby protecting dormant LT-HSCs from cGAS-mediated exhaustion. Moreover, cia-cGAS harbored a stronger binding affinity to cGAS than self-DNA did and consequently suppressed cGAS-mediated production of type I IFNs in LT-HSCs. Our findings reveal a mechanism by which cia-cGAS inhibits nuclear cGAS by blocking its enzymatic activity and preventing cGAS from recognizing self-DNA to maintain host homeostasis.

Growing evidence has highlighted the immune response as an important feature of carcinogenesis and therapeutic efficacy in clear cell renal cell carcinoma (ccRCC). This study categorized ccRCC cases into high and low score groups based on their immune/stromal scores generated by the ESTIMATE algorithm, and identified an association between these scores and prognosis. Differentially expressed tumor environment (TME)-related genes extracted from common upregulated components in immune and stromal scores were described using functional annotations and protein–protein interaction (PPI) networks. Most PPIs were selected for further prognostic investigation. Many additional previously neglected signatures, including AGPAT9, AQP7, HMGCS2, KLF15, MLXIPL, PPARGC1A, exhibited significant prognostic potential. In addition, multivariate Cox analysis indicated that MIXIPL and PPARGC1A were the most significant prognostic signatures, and were closely related to immune infiltration in TCGA cohort. External prognostic validation of MIXIPL and PPARGC1A was undertaken in 380 ccRCC cases from a real-world cohort. These findings indicate the relevance of monitoring and manipulation of the microenvironment for ccRCC prognosis and precision immunotherapy.

Innate lymphoid cells (ILCs) reside in mucosal surfaces to potentiate immune responses, sustain mucosal integrity and maintain tissue homeostasis. However, how tumor infiltrating ILCs modulate tumor development and progression is unclear. Here we profiled tumor infiltrating ILCs during colorectal cancer (CRC) progression by single-cell RNA sequencing. We identified six clusters of tumor infiltrating ILCs with unique features. ILC1s expressed inhibitory receptors and underwent inhibitory functional conversion at the late stage of CRC. ILC2s were classified into three subsets (called ILC2-A,-B,-C), of which ILC2-C subset could facilitate tumor progression. HS3ST1 and PD1 were highly expressed in ILC2s of late stage CRC tumors and deficiency of HS3ST1 or PD1 in ILC2s suppressed tumor growth. Moreover, ILC3s transdifferentiated into ILCregs during CRC progression and ILCregs promoted tumor growth. Of note, TGF-β signaling initiated the conversion of ILC3s to ILCregs and blockade of TGF-β signaling could disrupt the ILCreg transdifferentiation and inhibited tumor growth. Thus, intervention of ILC conversions might be a potential strategy for CRC immunotherapy.

In cancer cells, the mammalian target of rapamycin complex 1 (mTORC1) that requires hormonal and nutrient signals for its activation, is constitutively activated. We found that overexpression of pyruvate kinase M2 (PKM2) activates mTORC1 signaling through phosphorylating mTORC1 inhibitor AKT1 substrate 1 (AKT1S1). An unbiased quantitative phosphoproteomic survey identified 974 PKM2 substrates, including serine202 and serine203 (S202/203) of AKT1S1, in the proteome of renal cell carcinoma (RCC). Phosphorylation of S202/203 of AKT1S1 by PKM2 released AKT1S1 from raptor and facilitated its binding to 14-3-3, resulted in hormonal- and nutrient-signals independent activation of mTORC1 signaling and led accelerated oncogenic growth and autophagy inhibition in cancer cells. Decreasing S202/203 phosphorylation by TEPP-46 treatment reversed these effects. In RCCs and breast cancers, PKM2 overexpression was correlated with elevated S202/203 phosphorylation, activated mTORC1 and inhibited autophagy. Our results provided the first phosphorylome of PKM2 and revealed a constitutive mTORC1 activating mechanism in cancer cells.

The tumorigenic role and underlying mechanisms of lipid accumulation, commonly observed in many cancers, remain insufficiently understood. In this study, we identified an AMP-activated protein kinase (AMPK)-GATA-binding protein 3 (GATA3)enoyl-CoA hydratase short-chain 1 (ECHS1) pathway that induces lipid accumulation and promotes cell proliferation in clear cell renal cell carcinoma (ccRCC). Decreased expression of ECHS1, which is responsible for inactivation of fatty acid (FA) oxidation and activation of de novo FA synthesis, positively associated with ccRCC progression and predicted poor patient survival. Mechanistically, ECHS1 downregulation induced FA and branched-chain amino acid (BCAA) accumulation, which inhibited AMPK-promoted expression of GATA3, a transcriptional activator of ECHS1. BCAA accumulation induced activation of mTORC1 and de novo FA synthesis, and promoted cell proliferation. Furthermore, GATA3 expression phenocopied ECHS1 in predicting ccRCC progression and patient survival. The AMPK-GATA3-ECHS1 pathway may offer new therapeutic approaches and prognostic assessment for ccRCC in the clinic. Significance: These findings uncover molecular mechanisms underlying lipid accumulation in ccRCC, suggesting the AMPK-GATA3-ECHS1 pathway as a potential therapeutic target and prognostic biomarker.

Background:We developed a computational model integrating clinical data and imaging features extracted from contrast-enhanced computed tomography (CECT) images, to predict lymph node (LN) metastasis in patients with pancreatic ductal adenocarcinoma (PDAC).Methods: This retrospective study included 159 patients with PDAC (118 in the primary cohort and 41 in the validation cohort) who underwent preoperative contrast-enhanced computed tomography examination between 2012 and 2015. All patients underwent surgery and lymph node status was determined. A total of 2041 radiomics features were extracted from venous phase images in the primary cohort, and optimal features were extracted to construct a radiomics signature. A combined prediction model was built by incorporating the radiomics signature and clinical characteristics selected by using multivariable logistic regression. Clinical prediction models were generated and used to evaluate both cohorts. Results: Fifteen features were selected for constructing the radiomics signature based on the primary cohort. The combined prediction model for identifying preoperative lymph node metastasis reached a better discrimination power than the clinical prediction model, with an area under the curve of 0.944 vs. 0.666 in the primary cohort, and 0.912 vs. 0.713 in the validation cohort.Conclusions: This pilot study demonstrated that a noninvasive radiomics signature extracted from contrastenhanced computed tomography imaging can be conveniently used for preoperative prediction of lymph node metastasis in patients with PDAC.