Integrative analysis of single-cell and bulk RNA-sequencing data revealed T cell marker genes based molecular sub-types and a prognostic signature in lung adenocarcinoma.

Immunotherapy has emerged as a promising modality for addressing advanced or conventionally drug-resistant malignancies. When it comes to lung adenocarcinoma (LUAD), T cells have demonstrated significant influence on both antitumor activity and the tumor microenvironment. However, their specific contributions remain largely unexplored. This investigation aimed to delineate molecular subtypes and prognostic indicators founded on T cell marker genes, thereby shedding light on the significance of T cells in LUAD prognosis and precision treatment. The cellular phenotypes were identified by scrutinizing the single-cell data obtained from the GEO repository. Subsequently, T cell marker genes derived from single-cell sequencing analyses were integrated with differentially expressed genes from the TCGA repository to pinpoint T cell-associated genes. Utilizing Cox analysis, molecular subtypes and prognostic signatures were established and subsequently verified using the GEO dataset. The ensuing molecular and immunological distinctions, along with therapy sensitivity between the two sub-cohorts, were examined via the ESTIMATE, CIBERSORT, and ssGSEA methodologies. Compartmentalization, somatic mutation, nomogram development, chemotherapy sensitivity prediction, and potential drug prediction analyses were also conducted according to the risk signature. Additionally, real-time qPCR and the HPA database corroborated the mRNA and protein expression patterns of signature genes in LUAD tissues. In summary, this research yielded an innovative T cell marker gene-based signature with remarkable potential to prognosis and anticipate immunotherapeutic outcomes in LUAD patients.

Identification and validation of a m7G-related lncRNA signature for predicting the prognosis and therapy response in hepatocellular carcinoma.

BACKGROUND: N7-methylguanosine (m7G) is one of the most common RNA posttranscriptional modifications; however, its potential role in hepatocellular carcinoma (HCC) remains unknown. We developed a prediction signature based on m7G-related long noncoding RNAs (lncRNAs) to predict HCC prognosis and provide a reference for immunotherapy and chemotherapy. METHODS: RNA-seq data from The Cancer Genome Atlas (TCGA) database and relevant clinical data were used. Univariate and multivariate Cox regression analyses were conducted to identify m7G-related lncRNAs with prognostic value to build a predictive signature. We evaluated the prognostic value and clinical relevance of this signature and explored the correlation between the predictive signature and the chemotherapy treatment response of HCC. Moreover, an in vitro study to validate the function of CASC19 was performed. RESULTS: Six m7G-related lncRNAs were identified to create a signature. This signature was considered an independent risk factor for the prognosis of patients with HCC. TIDE analyses showed that the high-risk group might be more sensitive to immunotherapy. ssGSEA indicated that the predictive signature was strongly related to the immune activities of HCC. HCC in high-risk patients was more sensitive to the common chemotherapy drugs bleomycin, doxorubicin, gemcitabine, and lenalidomide. In vitro knockdown of CASC19 inhibited the proliferation, migration and invasion of HCC cells. CONCLUSION: We established a 6 m7G-related lncRNA signature that may assist in predicting the prognosis and response to chemotherapy and immunotherapy of HCC.

Integrated Analysis of Single-Cell RNA-Seq and Bulk RNA-Seq Combined with Multiple Machine Learning Identified a Novel Immune Signature in Diabetic Nephropathy.

Background: Increasing evidence suggests that immune modulation contributes to the pathogenesis and progression of diabetic nephropathy (DN). However, the role of immune modulation in DN has not been elucidated. The purpose of this study was to search for potential immune-related therapeutic targets and molecular mechanisms of DN. Methods: Gene expression datasets were obtained from the Gene Expression Omnibus (GEO) database. A total of 1793 immune-related genes were acquired from the Immunology Database and Analysis Portal (ImmPort). Weighted gene co-expression network analysis (WGCNA) was performed for GSE142025, and the red and turquoise co-expression modules were found to be key for DN progression. We utilized four machine learning algorithms, namely, random forest (RF), support vector machine (SVM), adaptive boosting (AdaBoost), and k-nearest neighbor (KNN), to evaluate the diagnostic value of hub genes. Immune infiltration patterns were analyzed using the CIBERSORT algorithm, and the correlation between immune cell type abundance and hub gene expression was also investigated. Results: A total of 77 immune-related genes of advanced DN were selected for subsequent analyzes. Functional enrichment analysis showed that the regulation of cytokine-cytokine receptor interactions and immune cell function play a corresponding role in the progression of DN. The final 10 hub genes were identified through multiple datasets. In addition, the expression levels of the identified hub genes were corroborated through a rat model. The RF model exhibited the highest AUC. CIBERSORT analysis and single-cell sequencing analysis revealed changes in immune infiltration patterns between control subjects and DN patients. Several potential drugs to reverse the altered hub genes were identified through the Drug-Gene Interaction database (DGIdb). Conclusion: This pioneering work provided a novel immunological perspective on the progression of DN, identifying key immune-related genes and potential drug targets, thus stimulating future mechanistic research and therapeutic target identification for DN.

Construction and validation of a prognostic signature based on necroptosis-related genes in hepatocellular carcinoma.

BACKGROUND: Necroptosis is a necrotic programmed cell death with potent immunogenicity. Due to the dual effects of necroptosis on tumor growth, metastasis and immunosuppression, we evaluated the prognostic value of necroptosis-related genes (NRGs) in hepatocellular carcinoma (HCC). METHODS: We first analyzed RNA sequencing and clinical HCC patient data obtained to develop an NRG prognostic signature based on the TCGA dataset. Differentially expressed NRGs were further evaluated by GO and KEGG pathway analyses. Next, we conducted univariate and multivariate Cox regression analyses to build a prognostic model. We also used the dataset obtained from the International Cancer Genome Consortium (ICGC) database to verify the signature. The Tumor Immune Dysfunction and Exclusion (TIDE) algorithm was used to investigate the immunotherapy response. Furthermore, we investigated the relationship between the prediction signature and chemotherapy treatment response in HCC. RESULTS: We first identified 36 differentially expressed genes out of 159 NRGs in hepatocellular carcinoma. Enrichment analysis showed that they were mainly enriched in the necroptosis pathway. Four NRGs were screened by Cox regression analysis to establish a prognostic model. The survival analysis revealed that the overall survival of patients with high-risk scores was significantly shorter than that of patients with low-risk scores. The nomogram demonstrated satisfactory discrimination and calibration. The calibration curves validated a fine concordance between the nomogram prediction and actual observation. The efficacy of the necroptosis-related signature was also validated by an independent dataset and immunohistochemistry experiments. TIDE analysis revealed that patients in the high-risk group were possibly more susceptible to immunotherapy. Furthermore, high-risk patients were found to be more sensitive to conventional chemotherapeutic medicines such as bleomycin, bortezomib, and imatinib. CONCLUSION: We identified 4 necroptosis-related genes and established a prognostic risk model that could potentially predict prognosis and response to chemotherapy and immunotherapy in HCC patients in the future.

Focal solitary necrotic nodules in fatty liver: characteristics on conventional and contrast-enhanced ultrasonography.

PURPOSE: Focal lesions in fatty liver are difficult to diagnose using conventional ultrasonography (CVUS). The aim of this study was to investigate the characteristics of solitary necrotic nodules (SNNs) in fatty liver using CVUS and contrast-enhanced ultrasonography (CEUS) and to evaluate the diagnostic value of CEUS for SNNs in fatty liver. METHODS: Fifteen SNNs in the fatty liver of fifteen patients were examined by both CVUS and CEUS. The contrast agent SonoVue was used for CEUS. The characterization and shape of these SNNs in the fatty liver were analyzed using CEUS. RESULTS: CVUS revealed eight oval-shaped, six irregularly shaped, and one wedge-shaped SNN in the fatty liver. The six irregularly shaped lesions on CVUS were revealed to comprise four gourd-shaped, one serpiginous, and one 3-pin socket-shaped nodule on CEUS. One of these SNNs showed a subcapsular wedge shape, with peripheral and distinct internal septal hyperenhancement in the arterial phases that washed out in the portal phase; moreover, most areas of th lesion showed no internal enhancement in any of the three phases. Fourteen of the lesions were characterized as lacking internal enhancement, and 12 of them had mild-moderate peripheral thin enhancement in the arterial phases. Twelve of the 15 nodules could be considered for diagnosis as SNNs by CEUS, which was further proved by US-guided biopsy and histopathology. However none of them could be considered for diagnosis as SNNs by CVUS. CONCLUSIONS: CEUS is a valuable tool for visualizing the characteristics of SNNs in fatty liver to improve the differential diagnosis.

Structures, Chemical Conversions, and Cytotoxicity of Tricholopardins C and D, Two Tricholoma Triterpenoids from the Wild Mushroom Tricholoma pardinum.

Two undescribed Tricholoma triterpenoids, namely tricholopardins C (1) and D (2), were isolated from the wild mushroom Tricholoma pardinum. Their structures with absolute configurations were elucidated by spectroscopic methods, as well as the single crystal X-ray diffraction. Compounds 1 and 2 were further obtained by chemical conversions from the known analogues. Compound 1 showed significant cytotoxicity to MCF-7 and Hela cell lines with IC50 values of 4.7 µM and 9.7 µM, respectively. Its mechanism of inducing MCF-7 cell apoptosis was studied briefly.

Two highly oxygenated Ergosterols from cultures of the Basidiomycete Conocybe siliginea.

Two highly oxygenated ergosterols, (22E,24R)-3ß,5α,6ß,9α,14α,25-hexhydroxyergosta-7,22-diene (1), and (22E,24R)-3ß,5α,6ß,14α,25-pentahydroxyergosta-7,9(11),22-triene (2), together with two known ones, have been isolated from cultures of the basidiomycete Conocybe siliginea. Their structures were elucidated on the basis of extensive spectroscopic means. Two new compounds (1 and 2) were tested for their nitric oxide synthase inhibitory activities. However, none of them showed any activity (IC50 > 40 µM).

Isoindolinone-containing meroterpenoids with α-glucosidase inhibitory activity from mushroom Hericium caput-medusae.

Hericium caput-medusae is an edible and medicinal mushroom closely relative to H. erinaceus. According to our detailed chemical investigation, two novel isoindolinone-containing meroterpene dimers, caputmedusins A (1) and B (2), as well as nine analogues, caputmedusins C-K (3-11), were isolated from the fermentation broth of H. caput-medusae. Their structures were elucidated by analyses of 1D and 2D NMR spectroscopic methods. The absolute configurations of 1-4 were speculated based on the specific optical rotation and biogenetic consideration. The absolute configurations of 10 and 11 were rationalized by the calculation of 1H NMR chemical shifts. Caputmedusins A-C (1-3) showed moderate inhibitory activity against α-glucosidase with the IC50 values of 39.2, 36.2 and 40.8µM, respectively.

Race Composition of Puccinia striiformis f. sp. tritici in Tibet, China.

In Tibet, China, wheat stripe rust (caused by Puccinia striiformis f. sp. tritici) has recently become one of the most destructive diseases on winter wheat. To identify races of the pathogen in Tibet, 261 isolates were obtained in 2010 and tested on seedlings of a standard set of 19 wheat indicator genotypes. Of the 261 isolates, 248 were identified as members of 19 known races (CYR17, CYR20, CYR21, CYR22, CYR23, CYR29, CYR31, CYR32, CYR33, Lov13-6, Su11-1, Su11-2, Su11-3, Su11-4, Su11-5, Su11-6, Su11-7, Su11-8, and Su11-13), and 13 identified as representatives of 4 new races. CYR32 and CYR33 were the most predominant. The number of races and their frequencies in Tibet were more similar to the fungal populations in Sichuan and Gansu provinces than to those in Yunnan, Qinghai, and Shaanxi provinces. The results suggest that Tibet is also a possible center of inoculum source and genetic variation for the stripe rust pathogen in addition to Sichuan and Gansu.