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The potential role of DNA methylation from paracancerous tissues in cancer diagnosis has not been explored until now. In this study, we built classification models using well-known machine learning models based on DNA methylation profiles of paracancerous tissues. We evaluated our methods on nine cancer datasets collected from The Cancer Genome Atlas (TCGA) and utilized fivefold cross-validation to assess the performance of models. Additionally, we performed gene ontology (GO) enrichment analysis on the basis of the significant CpG sites selected by feature importance scores of XGBoost model, aiming to identify biological pathways involved in cancer progression. We also exploited the XGBoost algorithm to classify cancer types using DNA methylation profiles of paracancerous tissues in external validation datasets. Comparative experiments suggested that XGBoost achieved better predictive performance than the other four machine learning methods in predicting cancer stage. GO enrichment analysis revealed key pathways involved, highlighting the importance of paracancerous tissues in cancer progression. Furthermore, XGBoost model can accurately classify nine different cancers from TCGA, and the feature sets selected by XGBoost can also effectively predict seven cancer types on independent GEO datasets. This study provided new insights into cancer diagnosis from an epigenetic perspective and may facilitate the development of personalized diagnosis and treatment strategies. [ABSTRACT FROM AUTHOR]

Stimulator of interferon genes (STING) activation induces type I interferons and pro-inflammatory cytokines which stimulate tumor antigen cross presentation and the adaptive immune responses against tumor. The first-generation of STING agonists, cyclic di-nucleotide (CDN), mimicked the endogenous STING ligand cyclic guanosine monophosphate adenosine monophosphate, and displayed limited clinical efficacy. Here we report the discovery of SHR1032, a novel small molecule non-CDN STING agonist. Compared to the clinical CDN STING agonist ADU-S100, SHR1032 has much higher activity in human cells with different STING haplotypes and robustly induces interferon β (IFNβ) production. When dosed intratumorally, SHR1032 induced strong anti-tumor effects in the MC38 murine syngeneic tumor model. Pharmacodynamic studies showed induction of IFNβ, tumor necrosis factor α (TNFα) and interleukin-6 (IL-6) in the tumors and, to a lower extent, in the plasma. More importantly, we found SHR1032 directly causes cell death in acute myeloid leukemia (AML) cells. In conclusion, our findings demonstrate that in addition to their established ability to boost anti-tumor immune responses, STING agonists can directly eradicate AML cells, and SHR1032 may present a new and promising therapeutic agent for cancer patients. [ABSTRACT FROM AUTHOR]

Clinical success of IL-17/IL-23 pathway biologics for the treatment of moderate to severe psoriasis suggests that targeting RORγt, a master regulator for the proliferation and function of Th17 cells, could be an effective alternative. However, oral RORγ antagonists (VTP43742, TAK828) with high systemic exposure showed toxicity in phase I/II clinical trials and terminated development. To alleviate the potential safety concerns, identifying compounds with skin-restricted exposure amenable for topical use is of great interest. Systematic structure activity relationship study and multi-parameter optimization led to the discovery of a novel RORγ antagonist (SHR168442) with desired properties for a topical drug. It suppressed the transcription of IL-17 gene, leading to reduction of IL-17 cytokine secretion. It showed high exposure in skin, but low in plasma. Topical application of SHR168442 in Vaseline exhibited excellent efficacy in the imiquimod-induced and IL-23-induced psoriasis-like skin inflammation mouse models and correlated with the reduction of Th17 pathway cytokines, IL-6, TNFα and IL-17A. This work demonstrated restricted skin exposure of RORγ antagonist may provide a new topical treatment option as targeted therapeutics for mild to moderate psoriasis patients and may be suitable for the treatment of any other inflammatory disorders that are accessible locally. [ABSTRACT FROM AUTHOR]

The Cancer Genome Atlas (TCGA) has accrued RNA-Seq-based transcriptome data for more than 4000 cancer tissue samples across 12 cancer types, translating these data into biological insights remains a major challenge. We analyzed and compared the transcriptomes of 4043 cancer and 548 normal tissue samples from 21 TCGA cancer types, and created a comprehensive catalog of gene expression alterations for each cancer type. By clustering genes into co-regulated gene sets, we identified seven cross-cancer gene signatures altered across a diverse panel of primary human cancer samples. A 14-gene signature extracted from these seven cross-cancer gene signatures precisely differentiated between cancerous and normal samples, the predictive accuracy of leave-one-out cross-validation (LOOCV) were 92.04%, 96.23%, 91.76%, 90.05%, 88.17%, 94.29%, and 99.10% for BLCA, BRCA, COAD, HNSC, LIHC, LUAD, and LUSC, respectively. A lung cancer-specific gene signature, containing SFTPA1 and SFTPA2 genes, accurately distinguished lung cancer from other cancer samples, the predictive accuracy of LOOCV for TCGA and GSE5364 data were 95.68% and 100%, respectively. These gene signatures provide rich insights into the transcriptional programs that trigger tumorigenesis and metastasis, and many genes in the signature gene panels may be of significant value to the diagnosis and treatment of cancer. [ABSTRACT FROM AUTHOR]

Efficient transparent quantum-dot light emitting diodes (QD-LEDs) are demonstrated by using a silver nanowire (AgNW) cathode. The devices are fabricated through a solution technique, not any vacuum processes are involved. Almost identical performance is obtained for both sides of the transparent device, which is primary due to the high transmittance of AgNW cathode. The maximum luminance (efficiency) for ITO and AgNW side is 25,040 cd/m2 (5.6 cd/A) and 23,440 cd/m2 (5.2 cd/A), respectively. The average specular transmittance of the device (involving the glass substrate) is over 60% in the visible range. This study indicates that AgNW electrodes can serve as a cost-effective, flexible alternative to ITO, and thereby improve the economic viability and mechanical stability of QD-LEDs. All the results suggest that this is an important progress toward producing transparent QD-LEDs based displays and lighting sources. [ABSTRACT FROM AUTHOR]

A correction to the article "The work mechanism and sub-bandgap-voltage electroluminescence in inverted quantum dot light-emitting diodes" is presented in which contain a typographical error.