Unveiling mitophagy-mediated molecular heterogeneity and development of a risk signature model for colorectal cancer by integrated scRNA-seq and bulk RNA-seq analysis.

Background: Accumulating researchers have recognized mitophagy as a key player in tumors, but few studies have investigated its role in the tumor microenvironment (TME). Advances in the technology of single-cell RNA sequencing (scRNA-seq) have allowed unveiling the concealed features of the TME at cellular resolution. This study aimed to elucidate the role of mitophagy within the TME of colorectal cancer (CRC) and to establish a mitophagy-mediated risk model. Methods: We assessed mitophagy-related pathway activities at both single-cell and tissue levels. Subsequently, an unsupervised clustering algorithm was employed to identify mitophagy-mediated subtypes. Furthermore, we developed a mitophagy-mediated risk signature (MMRS) using least absolute shrinkage and selection operator (LASSO) Cox analysis and constructed a MMRS model incorporating the risk score and clinical variables. Subsequently, we used quantitative reverse transcription polymerase chain reaction analysis to verify the expression of the screened genes. Results: We retrieved and annotated a total of 14,719 cells from eight samples in the scRNA-seq GSE132465 data set. The activities of mitophagy-related pathways were uniformly upregulated in cancer cells. Integrating with bulk RNA-seq data, we identified two mitophagy-mediated clusters (C1 and C2) with distinct characteristics and prognoses. C2 was identified as a mitophagy-high cluster. Then, we developed a five-gene MMRS via LASSO Cox analysis in The Cancer Genome Atlas (TCGA) cohort. We utilized the GSE39582 cohort to validate the efficacy of our model. The expression of CX3CL1 and INHBB was upregulated in CRC tissues. Conclusions: The present study identified two mitophagy-mediated CRC subtypes with distinct features. Our MMRS may provide potential therapeutic strategies for CRC. The findings of our work offer novel insights into the involvement of mitophagy in CRC.

Unraveling dynamic interactions between tumor-associated macrophages and consensus molecular subtypes in colorectal cancer: An integrative analysis of single-cell and bulk RNA transcriptome.

Background: Accumulating research substantiated that tumor-associated macrophages (TAMs) have a significant impact on the tumorigenesis, progression, and distant metastasis, representing a novel target for various cancers. However, the underlying dynamic changes and interactions between TAMs and tumor cells remain largely elusive in colorectal cancer (CRC). Methods: We depicted the dynamic changes of macrophages using sing-cell RNA-seq data and extracted TAM differentiation-related genes. Next, we utilized the weighted gene co-expression network analysis (WGCNA) to acquire CMS-related modular genes using bulk RNA-seq data. Finally, we utilized univariate Cox and Lasso Cox regression analyses to identify TAM differentiation-related biomarkers and established a novel risk signature model. We employed quantitative real-time polymerase chain reaction (qRT-PCR) on CRC tissue samples and used immunohistochemistry (IHC) data frome the HPA database to validate the mRNA and protein expression of prognostic genes. The interaction of TAMs and each consensus molecular subtype (CMS) subpopulation was analyzed at the cellular level. Results: A total of 47,285 cells from single-cell dataset and 1197 CRC patients from bulk dataset were obtained. Among those, 6400 myeloid cells were re-clustered and annotated. RNASE1, F13A1, DAPK1, CLEC10A, RPN2, REG4 and RGS19 were identified as prognostic genes and the risk signature model was established based on the above genes. The qRT-PCR analysis indicated that the expression of RNASE1 and DAPK1 were significantly up-regulated in CRC tumor tissues. The cell-cell communication analysis demonstrated complex interactions between TAMs and CMS malignant cell subpopulations. Conclusion: This study presents an in-depth dissection of the dynamic features of TAMs in the tumor microenvironment and provides promising therapeutic targets for CRC.

Analysis of aristolochic acids and analogues in medicinal plants and their commercial products by HPLC-PAD-ESI/MS.

An HPLC-UV-MS method for the analysis of aristolochic acids A, B, C and D, 7-OH-aristolochic acid A, and aristolic acid in a number of plant materials and their commercial products has been developed. HPLC with photodiode array detection and electrospray ionisation-MS in the selected ion monitoring mode allowed the identification of the target compounds and increased the selectivity of complex analyses such as those associated with multi-botanical preparations. The presented method was used to analyse 10 plant samples and six commercial products that possibly contained aristolochic acids. The resulting chromatographic profiles of the samples were significantly different from each other, and the method was directly transferred to HPLC-MS, which was used to confirm the presence of the six aristolochic acids mentioned above.

Antiinflammatory triterpenoid saponins from the seeds of Aesculus chinensis.

Phytochemical study of the ethanol extract of the seeds of Aesculus chinensis led to the isolation of a new triterpenoid saponin (6), together with five known triterpenoid saponins (1-5). The structure of the new compound was elucidated on the basis of spectral data to be 21,28-di-O-acetylprotoaescigenin-3-O-[beta-D-glucopyranosyl(1-2)][beta-D-glucopyranosyl(1-4)]-beta-D-glucopyranosiduronic acid (aesculiside A, 6). The antiinflammatory activities of the four main saponins (1-4) were compared with those of total saponin extracts, and single saponins showed more potent activity than total saponin extracts in mice.

Antiviral flavonoids from the seeds of Aesculus chinensis.

A bioassay-guided fractionation of an ethanol extract of the seeds of Aesculus chinensis led to the isolation of two new flavanoids (1 and 2), along with eight known ones (3-10). The structures of the new compounds were elucidated by spectroscopic methods including 2D NMR. All compounds were tested for antiviral activity against respiratory syncytial virus (RSV), parainfluenza virus type 3 (PIV 3), and influenza virus type A (Flu A). Compounds 1, 2, and 6 showed significant antiviral activities against RSV with IC(50) values of 4.5, 6.7, and 4.1 microg/mL and selective index (SI) values of 15.8, 32, and 63.8, respectively. Compound 8 demonstrated significant antiviral activity against Flu A with an IC(50) of 24.5 microg/mL and a SI of 16.0, respectively.