Tumor microenvironment-associated lactate metabolism regulates the prognosis and precise checkpoint immunotherapy outcomes of patients with lung adenocarcinoma.

BACKGROUND: Despite the wide clinical application of checkpoint inhibitor immunotherapy in lung adenocarcinoma, its limited benefit to patients remains puzzling to researchers. One of the mechanisms of immunotherapy resistance may be the dysregulation of lactate metabolism in the immunosuppressive tumor microenvironment (TME), which can inhibit dendritic cell maturation and prevent T-cell invasion into tumors. However, the key genes related to lactate metabolism and their influence on the immunotherapeutic effects in lung adenocarcinoma have not yet been investigated in depth. METHODS: In this study, we first surveyed the dysregulated expression of genes related to lactate metabolism in lung adenocarcinoma and then characterized their biological functions. Using machine learning methods, we constructed a lactate-associated gene signature in The Cancer Genome Atlas cohort and validated its effectiveness in predicting the prognosis and immunotherapy outcomes of patients in the Gene Expression Omnibus cohorts. RESULTS: A 7-gene signature based on the metabolomics related to lactate metabolism was found to be associated with multiple important clinical features of cancer and was an independent prognostic factor. CONCLUSIONS: These results suggest that rather than being simply a metabolic byproduct of glycolysis, lactate in the TME can affect immunotherapy outcomes. Therefore, the mechanism underlying this effect of lactate is worthy of further study.

OTO-Net: An Automated MRA Image Segmentation Network for Intracranial Aneurysms.

Intracranial aneurysms are local dilations of the cerebral blood vessels; people with intracranial aneurysms have a high risk to cause bleeding in the brain, which is related to high mortality and morbidity rates. Accurate detection and segmentation of intracranial aneurysms from Magnetic Resonance Angiography (MRA) images are essential in the clinical routine. Manual annotations used to assess the intracranial aneurysms on MRA images are substantial interobserver variability for both aneurysm detection and assessment of aneurysm size and growth. Many prior automated segmentation works have focused their efforts on tackling the problem, but there is still room for performance improvement due to the significant variability of lesions in the location, size, structure, and morphological appearance. To address these challenges, we propose a novel One-Two-One Fully Convolutional Networks (OTO-Net) for intracranial aneurysms automated segmentation in MRA images. The OTO-Net uses full convolution to achieve intracranial aneurysms automated segmentation through the combination of downsampling, upsampling, and skip connection. In addition, loss ensemble is used as the objective function to steadily improve the backpropagation efficiency of the network structure during the training process. We evaluated the proposed OTO-Net on one public benchmark dataset and one private dataset. Our proposed model can achieve the automated segmentation accuracy with 98.37% and 97.86%, average surface distances with 1.081 and 0.753, dice similarity coefficients with 0.9721 and 0.9813, and Hausdorff distance with 0.578 and 0.642 on these two datasets, respectively.

DNA sensors, crucial receptors to resist pathogens, are deregulated in colorectal cancer and associated with initiation and progression of the disease.

Background: DNA sensors are innate immune receptors that detect intracellular endogenous or exogenous DNA. They are critical to trigger immune response against DNA viral and intracellular bacterial infection, and are involved in inflammatory diseases and tumorigenesis. Recent accumulating evidences indicated that DNA sensors are also crucial for controlling the development of colorectal cancer (CRC). However, a systematic study on the expression profile of DNA sensors in CRC and their clinical significance are still lacking. Methods: We investigated the expression profile of DNA sensors in CRC and their clinical significance by taking advantage of clinical CRC samples, mouse AOM/DSS treatment model, and Oncomine ® bioinformatics platform. Results: Our study identified that the expression of DNA sensors, including AIM2, DAI, as well as inflammasome molecules ASC/IL-18, TLR9 and adaptor MyD88, and DDX60 decreased in human CRC, whereas the expression of DHX9, DHX36, and DDX41 significantly increased. Among them, the expression of AIM2/ASC/IL-18, MyD88, DAI, DHX36, and DDX60 were associated with cancer stages. In addition, we also performed correlation analysis between DNA sensors and their main signaling molecules to explore the possible mechanisms. The results showed that there were positive correlations between AIM2 and ASC/IL-18, DHX9 and MAVS, and TLR9 and MyD88 expression. In addition, the gene expression patterns of some DNA sensors were confirmed by Western-blot analysis. Conclusions: Our study revealed that the expression of multiple DNA sensors was deregulated in CRC and might be involved in tumor development. More importantly, the study identified that, among all these DNA sensors, AIM2, DAI, and DDX60 could be potentially critical for diagnosis, prognosis, and therapy of CRC and deserve further investigation.

Performance of THz fiber-scanning near-field microscopy to diagnose breast tumors.

Based on tissues from 20 female patients (mean age: 53 years; rang: 36-72 years), we examine the performance of a room-temperature-operated terahertz (THz) fiber-scanning near-field microscopy to diagnose slices of breast tissues. The specimens were frozen sliced and then measured in a thawed state without dehydration. We performed the imaging at 320 GHz. Our study indicates that images acquired in the THz transmission-illumination mode can all clearly distinguish breast tumor tissues from normal tissues without H&E staining. Due to its capability to perform quantitative analysis and to allow follow-up staining and traditional pathohistological analysis, our study indicates great potential of the THz fiber-scanning near-field microscopy for future automation, which is critical for fast and complete pre-screening on breast tumor pathological examinations and for assisting quick definition of the tumor margins during the surgical procedure such as breast-conserving surgery.

Anti-Thy-1 antibody-induced neurite outgrowth in cultured dorsal root ganglionic neurons is mediated by the c-Src-MEK signaling pathway.

Our previous study has shown that anti-Thy-1 antibody promotes neurite outgrowth of cultured dorsal root ganglion (DRG) neurons in a protein kinase A (PKA)-dependent manner. The present study provided another intracellular signaling pathway for the neurotrophic effect of anti-Thy-1 antibody. In DMSO-treated control cells, Thy-1 was enriched in microdomain-like structures on cell membranes by immunofluorescence observation. Treatment of DRG neurons with anti-Thy-1 antibody not only stimulated neurite outgrowth, but also increased the branching complexity of the neurites in both small and large neurons. We have previously shown that anti-Thy-1 antibody causes a time-dependent activation of mitogen-activated protein kinase (MEK) and of cyclic AMP response-element binding protein (CREB). Here, anti-Thy-1 antibody elicited a transient activation of c-Src kinase, and the activation of c-Src kinase appeared occurring upstream of the activation of MEK and CREB, since pretreatment with the Src kinase inhibitor, PP2, effectively abolished the anti-Thy-1 antibody-induced neurite outgrowth and the phosphorylation of MEK and CREB. CREB phosphorylation might result in upregulation of certain neurite outgrowth-related proteins. We therefore conclude that anti-Thy-1 antibody activates the c-Src kinase-MEK-CREB cascade and overcomes the inhibitory effect of Thy-1 on neurite outgrowth in DRG neurons.