Immunomodulatory Protein from Nectria haematococca Induces Apoptosis in Lung Cancer Cells via the P53 Pathway

Mitochondria-related lncRNAs: predicting prognosis, tumor microenvironment and treatment response in lung adenocarcinoma

Lung cancer is the most common type of malignant tumor that affects people in China and even across the globe, as it exhibits the highest rates of morbidity and mortality. Lung adenocarcinoma (LUAD) is a type of lung cancer with a very high incidence. The purpose of this study was to identify potential biomarkers that could be used to forecast the prognosis and improve the existing therapy options for treating LUAD. Clinical and RNA sequencing data of LUAD patients were retrieved from the TCGA database, while the mitochondria-associated gene sets were acquired from the MITOMAP database. Thereafter, Pearson correlation analysis was carried out to screen mitochondria-associated lncRNAs. Furthermore, univariate Cox and Lasso regression analyses were used for the initial screening of the target lncRNAs for prognostic lncRNAs before they could be incorporated into a multivariate Cox Hazard ratio model. Then, the clinical data, concordance index, Kaplan-Meier (K-M) curves, and the clinically-relevant subjects that were approved by the Characteristic Curves (ROC) were employed for assessing the model's predictive value. Additionally, the differences in immune-related functions and biological pathway enrichment between high- and low-risk LUAD groups were examined. Nomograms were developed to anticipate the OS rates of the patients within 1-, 3-, and 5 years, and the differences in drug sensitivity and immunological checkpoints were compared. In this study, 2175 mitochondria-associated lncRNAs were screened. Univariate, multivariate, and Lasso Cox regression analyses were carried out to select 13 lncRNAs with an independent prognostic significance, and a prognostic model was developed. The OS analysis of the established prognostic prediction model revealed significant variations between the high- and low-risk patients. The AUC-ROC values after 1, 3, and 5 years were seen to be 0.746, 0.692, and 0.726, respectively. The results suggested that the prognostic model riskscore could be used as an independent prognostic factor that differed from the other clinical characteristics. After analyzing the findings of the study, it was noted that both the risk groups showed significant differences in their immune functioning, immunological checkpoint genes, and drug sensitivity. The prognosis of patients with LUAD could be accurately and independently predicted using a risk prediction model that included 13 mitochondria-associated lncRNAs.

Isolation, Purification, and Antitumor Activity of a Novel Active Protein from Antrodia cinnamomea Liquid Fermentation Mycelia

Antrodia cinnamomea, a rare medicinal fungus endemic to Taiwan, contains numerous active components and displays strong antitumor and anti-inflammatory effects. We isolated and purified a novel A. cinnamomea active protein (termed ACAP) from liquid fermentation mycelia and evaluated its antitumor activity. A homogeneous protein-eluted fraction was obtained by anion exchange chromatography and gel filtration chromatography, and ACAP was identified based on the antitumor activity screening of this fraction. An in vitro assay of three tumor cell lines (HeLa, Hep G2, and Hepa 1-6) revealed significant antiproliferative effects of ACAP at low concentrations, with IC50 values of 13.10, 10.70, and 18.69 µg/mL, respectively. Flow cytometric analysis showed that ACAP induced late apoptosis of Hep G2 cells. The apoptosis rate of 50 µg/mL ACAP-treated cells (60%) was significantly (p < 0.01) more than that of the control. A Western blotting assay of apoptotic pathway proteins showed that ACAP significantly upregulated p53 and downregulated caspase-3 expression levels. Our findings indicate that ACAP has strong antitumor activity and the potential for development as a therapeutic agent and/or functional food.

FIP-nha, a fungal immunomodulatory protein from Nectria haematococca, induces apoptosis and autophagy in human gastric cancer cells via blocking the EGFR-mediated STAT3/Akt signaling pathway

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FIP-nha, a new FIP discovered beyond Basidiomycota, has been demonstrated a broad spectrum of antitumor activity and cell selectivity against human cancers.

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FIP-nha inhibited the growth, induced apoptosis and autophagy of gastric cancer cells through competitively binding to EGFR with EGF to blocking the EGFR-mediated STAT3/Akt pathway.

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FIP-nha may be a potential chemotherapy drug that targeted EGFR to treat human gastric cancer.

FIP-nha, a fungal immunomodulatory protein from Nectria haematococca, has been demonstrated a broad spectrum of antitumor activity and cell selectivity against human cancers in our previous study. However, the effect and mechanism of FIP-nha on gastric cancer remains unclear. In this study, we systematically observed the cytotoxicity, biological effect, regulatory mechanism and interaction target of FIP-nha on human gastric cancer cell lines, AGS and SGC7901. Our results demonstrated that FIP-nha inhibited the growth of AGS and SGC7901 cells in a dose-dependent manner and exerted proapoptotic effects on both cells as confirmed by flow cytometry, DAPI staining and western blot analysis. Additionally, the exposure of AGS and SGC7901 to FIP-nha induced autophagy as indicated by western blot analysis, GFP-LC3 and mCherry-GFP-LC3 transfection and acridine orange staining. Furthermore, we found that FIP-nha decreased the phosphorylation of EGFR, STAT3 and Akt and inhibited activation effect of ligand factor EGF to EGFR and its downstream signal molecule STAT3 and Akt. Finally, we proved that FIP-nha located on the surface of gastric cancer cells and bound directly to the transmembrane protein of EGFR by immunoprecipitation, cellular localization, molecular docking, microscale thermophoresis assay. The above findings indicated that FIP-nha inhibited the growth of gastric cancer and induced apoptosis and autophagy through competitively binding to EGFR with EGF to blocking the EGFR-mediated STAT3/Akt pathway. In summary, our study provided novel insights regarding the activity of FIP-nha against gastric cancer and contributed to the clinical application of FIP-nha as a potential chemotherapy drugs that targeted EGFR for human gastric cancer.

A Seven Immune-Related lncRNAs Model to Increase the Predicted Value of Lung Adenocarcinoma

Background

Recent research has shown that immune-related lncRNA plays a crucial part in the tumor immune microenvironment. This study tried to identify immune-related lncRNAs and construct a robust prediction model to increase the predicted value of lung adenocarcinoma (LUAD).

Methods

RNA expression data of LUAD were download from the Cancer Genome Atlas (TCGA) database. Immune genes were acquired from the Molecular Signatures Database (MSigDB). The immune gene related lncRNAs were acquired by the “limma R” package and Cytoscape3.7.1. Cox regression analysis was applied to construct this forecast model. The prognostic model was validated by the testing cohort which was acquired by the bootstrap method.

Results

A total of 551 lncRNA expression profiles including 497 LUAD tissues and 54 non-LUAD tissues were obtained. A total of 331 immune genes were acquired. The result of the Cox regression analysis showed that seven lncRNAs (AC022784-1, NKILA, AC026355-1, AC068338-3, LINC01843, SYNPR-AS1, and AC123595-1) can be performed to construct the prediction model to forecast the prognosis of LUAD. Kaplan–Meier curves indicated that our prediction model can distribute LUAD patients into two different risk groups (high and low) with significant statistical significance (P = 1.484e-07). Cox analysis and independent analysis illustrated that the seven-lncRNAs prediction model was an isolated factor by comparing it with other clinical variables. We validated the accuracy of our model in the testing dataset. Furthermore, the prognostic model also showed higher predictive efficiency than three other published prognostic models. The two different survival groups represented diverse immune features according to principal components analysis. GSEA analysis (gene set enrichment analysis) indicated that seven-lncRNAs signatures may be involved in the progression of tumorigenesis.

Conclusions

We have established a seven immune-related lncRNAs prediction model. This prognostic model had significant clinical significance that increased the predicted value and guided the personalized treatment for LUAD patients.

Detection of miR-155-5p and imaging lung cancer for early diagnosis: in vitro and in vivo study

Purpose

Currently, the routine screening program has insufficient capacity for the early diagnosis of lung cancer. Therefore, a type of chitosan-molecular beacon (CS-MB) probe was developed to recognize the miR-155-5p and image the lung cancer cells for the early diagnosis.

Methods

Based on the molecular beacon (MB) technology and nanotechnology, the CS-MB probe was synthesized self-assembly. There are four types of cells—three kinds of animal models and one type of histopathological sections of human lung cancer were utilized as models, including A549, SPC-A1, H446 lung cancer cells, tumor-initiating cells (TICs), subcutaneous and lung xenografts mice, and lox-stop-lox(LSL) K-ras G12D transgenic mice. The transgenic mice dynamically displayed the process from normal lung tissues to atypical hyperplasia, adenoma, carcinoma in situ, and adenocarcinoma. The different miR-155-5p expression levels in these cells and models were measured by quantitative real-time polymerase chain reaction (qRT-PCR). The CS-MB probe was used to recognize the miR-155-5p and image the lung cancer cells by confocal microscopy in vitro and by living imaging system in vivo.

Results

The CS-MB probe could be used to recognize the miR-155-5p and image the lung cancer cells significantly in these cells and models. The fluorescence intensity trends detected by the CS-MB probe were similar to the expression levels trends of miR-155 tested by qRT-PCR. Moreover, the fluorescence intensity showed an increasing trend with the tumor progression in the transgenic mice model, and the occurrence and development of lung cancer were dynamically monitored by the differen fluorescence intensity. In addition, the miR-155-5p in human lung cancer tissues could be detected by the miR-155-5p MB.

Conclusion

Both in vivo and in vitro experiments demonstrated that the CS-MB probe could be utilized to recognize the miR-155-5p and image the lung cancer cells. It provided a novel experimental and theoretical basis for the early diagnosis of the disease. Also, the histopathological sections of human lung cancer research laid the foundation for subsequent preclinical studies. In addition, different MBs could be designed to detect other miRNAs for the early diagnosis of other tumors.