Association of Per3 length polymorphism with susceptibility of Alzheimer disease (AD) in Chinese population

Objectives: The association of Per3 length polymorphism with susceptibility of Alzheimer Disease (AD) was examined in the present study. Methods: This study was constructed using the case-control method and investigated the association of Per3 length polymorphism with susceptibility of AD. Genotypes of APOE and Per3 length were determined by a PCR restriction fragment length polymorphism detection method. Results: In this study, we gathered 130 unrelated AD patients and 188 controls in performing an analysis the association of Per3 length polymorphism with susceptibility of AD. In the whole sample or APOE ε4 non-carriers, an increased prevalence of five repeat homozygotes of Per3 length in AD patients had significant higher than that in controls (in the whole sample: χ² = 7.261,= 0.0176; in APOE ε4 non-carriers: χ² = 6.086, p = 0.030). And, among APOE ε4 carriers, an increased prevalence of five repeat homozygotes of Per3 length in AD patients had also significant higher than that in controls (χ² = 3.893, p = 0.0319). Conclusions: Among APOE ε4 non-carriers, five repeat homozygotes of Per3 length was associated with a high susceptibility of AD among APOE ε4 carriers and non-carriers.     

In vitro machine learning-based CAR T immunological synapse quality measurements correlate with patient clinical outcomes

The human immune system consists of a highly intelligent network of billions of independent, self-organized cells that interact with each other. Machine learning (ML) is an artificial intelligence (AI) tool that automatically processes huge amounts of image data. Immunotherapies have revolutionized the treatment of blood cancer. Specifically, one such therapy involves engineering immune cells to express chimeric antigen receptors (CAR), which combine tumor antigen specificity with immune cell activation in a single receptor. To improve their efficacy and expand their applicability to solid tumors, scientists optimize different CARs with different modifications. However, predicting and ranking the efficacy of different "off-the-shelf" immune products (e.g., CAR or Bispecific T-cell Engager [BiTE]) and selection of clinical responders are challenging in clinical practice. Meanwhile, identifying the optimal CAR construct for a researcher to further develop a potential clinical application is limited by the current, time-consuming, costly, and labor-intensive conventional tools used to evaluate efficacy. Particularly, more than 30 years of immunological synapse (IS) research data demonstrate that T cell efficacy is not only controlled by the specificity and avidity of the tumor antigen and T cell interaction, but also it depends on a collective process, involving multiple adhesion and regulatory molecules, as well as tumor microenvironment, spatially and temporally organized at the IS formed by cytotoxic T lymphocytes (CTL) and natural killer (NK) cells. The optimal function of cytotoxic lymphocytes (including CTL and NK) depends on IS quality. Recognizing the inadequacy of conventional tools and the importance of IS in immune cell functions, we investigate a new strategy for assessing CAR-T efficacy by quantifying CAR IS quality using the glass-support planar lipid bilayer system combined with ML-based data analysis. Previous studies in our group show that CAR-T IS quality correlates with antitumor activities in vitro and in vivo. However, current manually quantified IS quality data analysis is time-consuming and labor-intensive with low accuracy, reproducibility, and repeatability. In this study, we develop a novel ML-based method to quantify thousands of CAR cell IS images with enhanced accuracy and speed. Specifically, we used artificial neural networks (ANN) to incorporate object detection into segmentation. The proposed ANN model extracts the most useful information to differentiate different IS datasets. The network output is flexible and produces bounding boxes, instance segmentation, contour outlines (borders), intensities of the borders, and segmentations without borders. Based on requirements, one or a combination of this information is used in statistical analysis. The ML-based automated algorithm quantified CAR-T IS data correlates with the clinical responder and non-responder treated with Kappa-CAR-T cells directly from patients. The results suggest that CAR cell IS quality can be used as a potential composite biomarker and correlates with antitumor activities in patients, which is sufficiently discriminative to further test the CAR IS quality as a clinical biomarker to predict response to CAR immunotherapy in cancer. For translational research, the method developed here can also provide guidelines for designing and optimizing numerous CAR constructs for potential clinical development.Trial Registration: ClinicalTrials.gov {"type":"clinical-trial","attrs":{"text":"NCT00881920","term_id":"NCT00881920"}}NCT00881920.     

Cancer-associated adipocytes promote the invasion and metastasis in breast cancer through LIF/CXCLs positive feedback loop

Cancer-associated adipocytes (CAAs), which are adipocytes transformed by cancer cells, are of great importance in promoting the progression of breast cancer. However, the underlying mechanisms involved in the crosstalk between cancer cells and adipocytes are still unknown. Here we report that CAAs and breast cancer cells communicate with each other by secreting the cytokines leukemia inhibitory factor (LIF) and C-X-C subfamily chemokines (CXCLs), respectively. LIF is a pro-inflammatory cytokine secreted by CAAs, which promotes migration and invasion of breast cancer cells via the Stat3 signaling pathway. The activation of Stat3 induced the secretion of glutamic acid-leucine-arginine (ELR) motif CXCLs (CXCL1, CXCL2, CXCL3 and CXCL8) in tumor cells. Interestingly, CXCLs in turn activated the ERK1/2/NF-κB/Stat3 signaling cascade to promote the expression of LIF in CAAs. In clinical breast cancer pathology samples, the up-regulation of LIF in paracancerous adipose tissue was positively correlated with the activation of Stat3 in breast cancer. Furthermore, we verified that adipocytes enhanced lung metastasis of breast cancer cells, and the combination of EC330 (targeting LIF) and SB225002 (targeting C-X-C motility chemokine receptor 2 (CXCR2)) significantly reduced lung metastasis of breast cancer cells in vivo. Our findings reveal that the interaction of adipocytes with breast cancer cells depends on a positive feedback loop between the cytokines LIF and CXCLs, which promotes breast cancer invasion and metastasis.     

Duplex-Repair enables highly accurate sequencing,despite DNA damage

Accurate DNA sequencing is crucial in biomedicine. Underlying the most accurate methods is the assumption that a mutation is true if altered bases are present on both strands of the DNA duplex. We now show that this assumption can be wrong. We establish that current methods to prepare DNA for sequencing, via ‘End Repair/dA-Tailing,’ may substantially resynthesize strands, leading amplifiable lesions or alterations on one strand to become indiscernible from true mutations on both strands. Indeed, we discovered that 7–17% and 32–57% of interior ‘duplex base pairs’ from cell-free DNA and formalin-fixed tumor biopsies, respectively, could be resynthesized in vitro and potentially introduce false mutations. To address this, we present Duplex-Repair, and show that it limits interior duplex base pair resynthesis by 8- to 464-fold, rescues the impact of induced DNA damage, and affords up to 8.9-fold more accurate duplex sequencing. Our study uncovers a major Achilles’ heel in sequencing and offers a solution to restore high accuracy.     

A circular intronic RNA ciPVT1 delays endothelial cell senescence by regulating the miR‐24‐3p/CDK4/pRb axis

Circular RNAs (circRNAs) have been established to be involved in numerous processes in the human genome, but their function in vascular aging remains largely unknown. In this study, we aimed to characterize and analyze the function of a circular intronic RNA, ciPVT1, in endothelial cell senescence. We observed significant downregulation of ciPVT1 in senescent endothelial cells. In proliferating endothelial cells, ciPVT1 knockdown induced a premature senescence‐like phenotype, inhibited proliferation, and led to an impairment in angiogenesis. An in vivo angiogenic plug assay revealed that ciPVT1 silencing significantly inhibited endothelial tube formation and decreased hemoglobin content. Conversely, overexpression of ciPVT1 in old endothelial cells delayed senescence, promoted proliferation, and increased angiogenic activity. Mechanistic studies revealed that ciPVT1 can sponge miR‐24‐3p to upregulate the expression of CDK4, resulting in enhanced Rb phosphorylation. Moreover, enforced expression of ciPVT1 reversed the senescence induction effect of miR‐24‐3p in endothelial cells. In summary, the present study reveals a pivotal role for ciPVT1 in regulating endothelial cell senescence and may have important implications in the search of strategies to counteract the development of age‐associated vascular pathologies.