Pan-cancer analysis identifies RNF43 as a prognostic, therapeutic and immunological biomarker.

BACKGROUND: RING finger protein 43 (RNF43), an E3 ubiquitin ligase, is a homologous gene mutated in several cancers. However, the pan-cancer panoramic picture of RNF43 and its predictive value for tumor immune phenotypes and immunotherapeutic efficacy are still largely unclear. Our study aims to clarify the functions of RNF43 in predicting the prognosis, immune signature, and immunotherapeutic efficacy in pan-cancer. METHODS: By using RNA-seq, mutation, and clinical data from the TCGA database, the expression levels and prognostic significance of RNF43 in pan-cancer were analyzed. The genetic alteration characteristics of RNF43 were displayed by the cBioPortal database. Gene Set Enrichment Analysis (GSEA) was performed to investigate the potential biological functions and signaling pathways modulated by RNF43 in cancers. The relationship of RNF43 expression with immune cell infiltration, and immune modulators expression was interpreted by the ESTIMATE algorithm, CIBERSORT algorithm, and TISIDB database. The correlations between RNF43, microsatellite instability (MSI), and tumor mutation burden (TMB) were also investigated. Furthermore, the predictive value of RNF43 for immunotherapeutic efficacy and drug sensitivity was further illustrated. Besides, immunohistochemistry (IHC) was employed to validate the expression of the RNF43 in different cancer types by our clinical cohorts, including patients with lung cancer, sarcoma, breast cancer, and kidney renal clear cell carcinoma. RESULTS: The results demonstrated that RNF43 was abnormally expressed in multiple cancers, and RNF43 is a critical prognosis-related factor in several cancers. RNF43 was frequently mutated in several cancers with a high frequency of 4%, and truncating mutation was the most frequent RNF43 mutation type. RNF43 expression was linked to the abundance of several immune cell types, including CD8+ T cells, B cells, and macrophages within the tumor immune microenvironment. Furthermore, RNF43 expression was significantly correlated with the efficacy of anti-PD-1/PD-L1 treatment, and it could predict the sensitivity of various anti-cancer drugs. Finally, IHC explored and validated the different expression levels of RNF43 in different cancers by our clinical samples. CONCLUSION: Our results first present the expression pattern and the mutation signature of RNF43, highlighting that RNF43 is an important prognostic biomarker in pan-cancer. Furthermore, RNF43 seems to be a critical modulator in the tumor immune microenvironment and can function as a promising biomarker for predicting the immunotherapeutic efficacy of anti-PD-1/PD-L1 treatment, and drug sensitivity in cancer treatment.

Ferroptosis-related gene HIC1 in the prediction of the prognosis and immunotherapeutic efficacy with immunological activity.

Background: Hypermethylated in Cancer 1 (HIC1) was originally confirmed as a tumor suppressor and has been found to be hypermethylated in human cancers. Although growing evidence has supported the critical roles of HIC1 in cancer initiation and development, its roles in tumor immune microenvironment and immunotherapy are still unclear, and no comprehensive pan-cancer analysis of HIC1 has been conducted. Methods: HIC1 expression in pan-cancer, and differential HIC1 expression between tumor and normal samples were investigated. Immunohistochemistry (IHC) was employed to validate HIC1 expression in different cancers by our clinical cohorts, including lung cancer, sarcoma (SARC), breast cancer, and kidney renal clear cell carcinoma (KIRC). The prognostic value of HIC1 was illustrated by Kaplan-Meier curves and univariate Cox analysis, followed by the genetic alteration analysis of HIC1 in pan-cancer. Gene Set Enrichment Analysis (GSEA) was conducted to illustrate the signaling pathways and biological functions of HIC1. The correlations between HIC1 and tumor mutation burden (TMB), microsatellite instability (MSI), and the immunotherapy efficacy of PD-1/PD-L1 inhibitors were analyzed by Spearman correlation analysis. Drug sensitivity analysis of HIC1 was performed by extracting data from the CellMiner™ database. Results: HIC1 expression was abnormally expressed in most cancers, and remarkable associations between HIC1 expression and prognostic outcomes of patients in pan-cancer were detected. HIC1 was significantly correlated with T cells, macrophages, and mast cell infiltration in different cancers. Moreover, GSEA revealed that HIC1 was significantly involved in immune-related biological functions and signaling pathways. There was a close relationship of HIC1 with TMB and MSI in different cancers. Furthermore, the most exciting finding was that HIC1 expression was significantly correlated with the response to PD-1/PD-L1 inhibitors in cancer treatment. We also found that HIC1 was significantly correlated with the sensitivity of several anti-cancer drugs, such as axitinib, batracylin, and nelarabine. Finally, our clinical cohorts further validated the expression pattern of HIC1 in cancers. Conclusions: Our investigation provided an integrative understanding of the clinicopathological significance and functional roles of HIC1 in pan-cancer. Our findings suggested that HIC1 can function as a potential biomarker for predicting the prognosis, immunotherapy efficacy, and drug sensitivity with immunological activity in cancers.

Ensemble machine learning algorithm for predicting acute kidney injury in patients admitted to the neurointensive care unit following brain surgery.

Acute kidney injury (AKI) is a common postoperative complication among patients in the neurological intensive care unit (NICU), often resulting in poor prognosis and high mortality. In this retrospective cohort study, we established a model for predicting AKI following brain surgery based on an ensemble machine learning algorithm using data from 582 postoperative patients admitted to the NICU at the Dongyang People's Hospital from March 1, 2017, to January 31, 2020. Demographic, clinical, and intraoperative data were collected. Four machine learning algorithms (C5.0, support vector machine, Bayes, and XGBoost) were used to develop the ensemble algorithm. The AKI incidence in critically ill patients after brain surgery was 20.8%. Intraoperative blood pressure; postoperative oxygenation index; oxygen saturation; and creatinine, albumin, urea, and calcium levels were associated with the postoperative AKI occurrence. The area under the curve value for the ensembled model was 0.85. The accuracy, precision, specificity, recall, and balanced accuracy values were 0.81, 0.86, 0.44, 0.91, and 0.68, respectively, indicating good predictive ability. Ultimately, the models using perioperative variables exhibited good discriminatory ability for early prediction of postoperative AKI risk in patients admitted to the NICU. Thus, the ensemble machine learning algorithm may be a valuable tool for forecasting AKI.

3-Pentanol glycosides from root nodules of the actinorhizal plant Alnus cremastogyne.

Alnus cremastogyne Burkill (Betulaceae), an actinorhizal plant, can enter a mutualistic symbiosis with Frankia species that leads to the formation of nitrogen fixing root nodules. Some primary metabolites (carbohydrates, dicarboxylic acids, amino acids, citrulline and amides) involved in carbon and nitrogen metabolism in actinorhizal nodules have been identified, while specialized metabolites in A. cremastogyne root nodules are yet to be characterized. In this study, we isolated and identified three undescribed 3-pentanol glycosides, i.e., 3-pentyl α-l-arabinofuranosyl-(1''→6')-ß-d-glucopyranoside, 3-pentyl α-l-rhamnopyranosyl-(1''→6')-ß-d-glucopyranoside, and 3-pentyl 6'-(3-hydroxy3-methylglutaryl)-ß-d-glucopyranoside, as well as seventeen known compounds from A. cremastogyne root nodules. 3-Pentanol glycosides are abundantly distributed in root nodules, while they are distributed in stems, roots, leaves and fruits at low/zero levels. A. cremastogyne plants treated by root nodule suspension emit 3-pentanol. This study enriches the knowledge about specialized metabolites in the actinorhizal host, and provides preliminarily information on the signal exchange in the actinorhizal symbiosis between A. cremastogyne and Frankia.

Micropyrones A and B, two new α-pyrones from the actinomycete Microbacterium sp. GJ312 isolated from Glycyrrhiza uralensis Fisch.

Two new α-pyrones, micropyrones A (1) and B (2), along with four known γ-pyrones, nocapyrone D (3), nocapyrone A (4), marinactinone A (5), and nocapyrone H (6), were isolated from the culture extract of actinomycete Microbacterium sp. GJ312, which was isolated from Glycyrrhiza uralensis. The structures of these compounds were identified by analysis of spectral data. They are the first α- and γ-pyrones reported from the genus Microbacterium. The antibacterial activity of all compounds against Staphylococcus aureus and methicillin resistant S. aureus was evaluated. However, none of them showed significant activity. This study represents the first phytochemical example of a Glycyrrhiza-derived actinomycete.

Turing-Hopf Bifurcation Analysis in a Diffusive Ratio-Dependent Predator-Prey Model with Allee Effect and Predator Harvesting.

This paper investigates the complex dynamics of a ratio-dependent predator-prey model incorporating the Allee effect in prey and predator harvesting. To explore the joint effect of the harvesting effort and diffusion on the dynamics of the system, we perform the following analyses: (a) The stability of non-negative constant steady states; (b) The sufficient conditions for the occurrence of a Hopf bifurcation, Turing bifurcation, and Turing-Hopf bifurcation; (c) The derivation of the normal form near the Turing-Hopf singularity. Moreover, we provide numerical simulations to illustrate the theoretical results. The results demonstrate that the small change in harvesting effort and the ratio of the diffusion coefficients will destabilize the constant steady states and lead to the complex spatiotemporal behaviors, including homogeneous and inhomogeneous periodic solutions and nonconstant steady states. Moreover, the numerical simulations coincide with our theoretical results.

Discovery of Cyclic Diarylheptanoids as Inhibitors against Influenza A Virus from the Roots of Casuarina equisetifolia.

Four new cyclic diarylheptanoids, casuarinols A-C (1-3) and casuarinolide A (4), together with six known ones (5-10), were isolated from the roots of Casuarina equisetifolia. Structures were elucidated by extensive spectroscopic analysis, theoretical conformational, and electronic circular dichroism analyses. Casuarinol C (3) is a novel cyclic diarylheptanoid-aldehyde adduct. Casuarinolide A (4) represents the first structure of a seco-cyclic diarylheptanoid. Compounds 1-9 were evaluated for their anti-influenza A virus (IAV) activity against A/WSN/33 (H1N1). (-)-(M)-11-Oxo-3,12R,17-trihydroxy-9-ene-[7,0]-metacyclophane (5) displayed significant anti-IAV activity with an IC50 value of 8.64 ± 2.49 µM and a CC50 higher than 100 µM.

Metabolite pattern in root nodules of the actinorhizal plant Casuarina equisetifolia.

Casuarina equisetifolia L. (Casuarinaceae), an actinorhizal plant, exhibits mutualistic symbiosis with Frankia and promotes nitrogen fixation in root nodules. While the exchange of metabolites between host plant and microsymbiont is well understood in legume symbioses, the situation in the symbiosis between nitrogen-fixing Frankia and actinorhizal plants is less clear. In this study, a metabolomic approach was applied to root nodules of mature C. equisetifolia trees, leading to the identification of an undescribed taraxerane-type triterpenoid ester, 3-O-dihydrocoumaroyl ß-taraxerol, along with twelve known compounds. An abundant component was tyramine with a content of 2.76 ± 0.315 mg/g FW in mature nodules. Tyramine specifically and abundantly accumulated in mature nitrogen-fixing nodules compared to senescent nodules, stems, leaves, and seeds. In addition, the potential function of tyramine was preliminarily examined and discussed.

Association between enteral nutrition support and neurological outcome in patients with acute intracranial haemorrhage: A retrospective cohort study.

Association between the amount of enteral nutrition (EN) caloric intake and Glasgow coma scale scores at discharge (GCSdis) in intracranial haemorrhage (ICH) was retrospectively investigated in 230 patients in a single center from 2015 and 2017. GCSdis was used as a dichotomous outcome (≤8 or >8: 56/230 vs. 174/230) and its association with the amount of EN caloric intake within 48 hours was analysed in four logistic models. Model 1 used EN as a continuous variable and showed association with favourable GCSdis (odds ratio [OR], 1.04; 95% confidence interval [CI], 1.01-1.08). Models 2 and 3 categorized EN into two (≤25 and >25 kcal/kg/48 hrs) and three caloric intake levels (≤10, 10~25, and >25 kcal/kg/48 hrs) respectively, and compared them with the lowest level; highest EN level associated with favourable GCSdis in both model 2 (OR, 2.77; 95%CI, 1.25-6.13) and 3 (OR, 4.68; 95%CI, 1.61-13.61). Model 4 transformed EN into four quartiles (Q1-Q4). Compared to Q1, OR increased stepwise from Q2 (OR 1.80, 95%CI 0.59-5.44) to Q4 (OR 4.71, 95%CI 1.49-14.80). Propensity score matching analysis of 69 matched pairs demonstrated consistent findings. In the early stage of ICH, increased EN was associated with favourable GCSdis.