Single cell RNA-seq analysis identifies a noncoding RNA mediating resistance to sorafenib treatment in HCC.
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ABSTRACT:
SUBMITTER: Zhou K
PROVIDER: S-EPMC8722008 | biostudies-literature | 2022 Jan
REPOSITORIES: biostudies-literature
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Single cell RNA-seq analysis identifies a noncoding RNA mediating resistance to sorafenib treatment in HCC.
Zhou Kevin K Nguyen Romario R Qiao Liang L George Jacob J
Molecular cancer 20220103 1
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Project description:Huntington Disease (HD) is an inherited movement disorder caused by expanded CAG repeats in the Huntingtin gene. We have used single nucleus RNASeq (snRNASeq) to uncover cellular phenotypes that change in the disease, investigating single cell gene expression in cingulate cortex of patients with HD and comparing the gene expression to that of patients with no neurological disease. In this study, we focused on astrocytes, although we found significant gene expression differences in neurons, oligodendrocytes, and microglia as well. In particular, the gene expression profiles of astrocytes in HD showed multiple signatures, varying in phenotype from cells that had markedly upregulated metallothionein and heat shock genes, but had not completely lost the expression of genes associated with normal protoplasmic astrocytes, to astrocytes that had substantially upregulated glial fibrillary acidic protein (GFAP) and had lost expression of many normal protoplasmic astrocyte genes as well as metallothionein genes. When compared to astrocytes in control samples, astrocyte signatures in HD also showed downregulated expression of a number of genes, including several associated with protoplasmic astrocyte function and lipid synthesis. Thus, HD astrocytes appeared in variable transcriptional phenotypes, and could be divided into several different "states", defined by patterns of gene expression. Ultimately, this study begins to fill the knowledge gap of single cell gene expression in HD and provide a more detailed understanding of the variation in changes in gene expression during astrocyte "reactions" to the disease.
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Project description:Hepatocellular carcinoma (HCC) is the most familiar primary hepatic malignancy with a poor prognosis. The incidence of HCC and the associated deaths have risen in recent decades. Sorafenib is the first drug to be approved by the Food and Drug Administration (FDA) for routine use in the first-line therapy of patients with advanced HCC. However, only about 30% of patients with HCC will be benefited from sorafenib therapy, and drug resistance typically develops within 6 months. In recent years, the mechanisms of resistance to sorafenib have gained the attention of a growing number of researchers. A promising field of current studies is ferroptosis, which is a novel form of cell death differing from apoptosis, necroptosis, and autophagy. This process is dependent on the accumulation of intracellular iron and reactive oxygen species (ROS). Furthermore, the increase in intracellular iron levels and ROS can be significantly observed in cells resistant to sorafenib. This article reviews the mechanisms of resistance to sorafenib that are related to ferroptosis, evaluates the relationship between ferroptosis and sorafenib resistance, and explores new therapeutic approaches capable of reversing sorafenib resistance in HCC through the modulation of ferroptosis.
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Project description:Hepatocellular carcinoma (HCC) has risen as the villain of cancer-related death globally, with a usual cruel forecasting. Sorafenib was officially approved by the FDA as first-line treatment for advanced HCC. Despite the brilliant promise revealed in research, actual clinical results are limited due to the widespread appearance of drug resistance. The tumor microenvironment (TME) has been correlated to pharmacological resistance, implying that existing cellular level strategies may be insufficient to improve therapy success. The role of autophagy in cancer is a two-edged sword. On one hand, autophagy permits malignant cells to overcome stress, such as hypoxic TME and therapy-induced starvation. Autophagy, on the other hand, plays an important role in damage suppression, which can reduce carcinogenesis. As a result, controlling autophagy is certainly a viable technique in cancer therapy. The goal of this study was to investigate at the impact of autophagy manipulation with sorafenib therapy by analyzing autophagy induction and inhibition to sorafenib monotherapy in rats with HCC. Western blot, ELISA, immunohistochemistry, flow cytometry, and quantitative-PCR were used to investigate autophagy, apoptosis, and the cell cycle. Routine biochemical and pathological testing was performed. Ultracellular features and autophagic entities were observed using a transmission electron microscope (TEM). Both regimens demonstrated significant reductions in chemotherapeutic resistance and hepatoprotective effects. According to the findings, both autophagic inhibitors and inducers are attractive candidates for combating sorafenib-induced resistance in HCC.
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Project description:Single-cell RNA-seq's (scRNA-seq) unprecedented cellular resolution at a genome-wide scale enables us to address questions about cellular heterogeneity that are inaccessible using methods that average over bulk tissue extracts. However, scRNA-seq data sets also present additional challenges such as high transcript dropout rates, stochastic transcription events, and complex population substructures. Here, we present a single-cell RNA-seq analysis and klustering evaluation (SAKE), a robust method for scRNA-seq analysis that provides quantitative statistical metrics at each step of the analysis pipeline. Comparing SAKE to multiple single-cell analysis methods shows that most methods perform similarly across a wide range of cellular contexts, with SAKE outperforming these methods in the case of large complex populations. We next applied the SAKE algorithms to identify drug-resistant cellular populations as human melanoma cells respond to targeted BRAF inhibitors (BRAFi). Single-cell RNA-seq data from both the Fluidigm C1 and 10x Genomics platforms were analyzed with SAKE to dissect this problem at multiple scales. Data from both platforms indicate that BRAF inhibitor-resistant cells can emerge from rare populations already present before drug application, with SAKE identifying both novel and known markers of resistance. These experimentally validated markers of BRAFi resistance share overlap with previous analyses in different melanoma cell lines, demonstrating the generality of these findings and highlighting the utility of single-cell analysis to elucidate mechanisms of BRAFi resistance.
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Project description:RNA-sequencing of hepatocellular carcinomas at various stages of sorafenib treatment
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Project description:High-throughput sequencing has revealed a tremendous complexity of cellular transcriptomes, which is partly due to the generation of multiple alternative transcripts from a single gene locus. Because alternative transcripts often have low abundance in bulk cells, the functions of most of these transcripts and their relationship with their canonical counterparts remain unclear. Here we applied single-cell RNA-Seq to analyze the transcriptome complexity of in vitro-differentiated, murine type 2 T helper (Th2) cells. We found that cytokine gene transcripts contribute most of the intercellular heterogeneity, with a group of universal cytokines, including interleukins 1a, 2, 3, and 16, being bimodally expressed. At the single-cell level, use of alternative promoters prevalently generated alternative transcripts. For instance, although undetectable in bulk cells, a noncoding RNA isoform of IL-4 (IL4nc), which was driven by an intronic promoter in the IL-4 locus, was predominantly expressed in a subset of Th2 cells. IL4nc displayed distinct temporal expression patterns compared with the canonical IL-4 mRNA and post-transcriptionally promoted the production of IL-4 protein in Th2 cells. In conclusion, our findings reveal a mechanism whereby minor noncanonical transcripts post-transcriptionally regulate expression of their cognate canonical genes.
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Project description:Large-scale transcriptomic data are crucial for understanding the molecular features of hepatocellular carcinoma (HCC). Integrated 15 transcriptomic datasets of HCC clinical samples, the first version of HCC database (HCCDB v1.0) was released in 2018. Through the meta-analysis of differentially expressed genes and prognosis-related genes across multiple datasets, it provides a systematic view of the altered biological processes and the inter-patient heterogeneities of HCC with high reproducibility and robustness. With four years having passed, the database now needs integration of recently published datasets. Furthermore, the latest single-cell and spatial transcriptomics have provided a great opportunity to decipher complex gene expression variations at the cellular level with spatial architecture. Here, we present HCCDB v2.0, an updated version that combines bulk, single-cell, and spatial transcriptomic data of HCC clinical samples. It dramatically expands the bulk sample size by adding 1656 new samples from 11 datasets to the existing 3917 samples, thereby enhancing the reliability of transcriptomic meta-analysis. A total of 182,832 cells and 69,352 spatial spots are added to the single-cell and spatial transcriptomics sections, respectively. A novel single-cell level and 2-dimension (sc-2D) metric is proposed as well to summarize cell type-specific and dysregulated gene expression patterns. Results are all graphically visualized in our online portal, allowing users to easily retrieve data through a user-friendly interface and navigate between different views. With extensive clinical phenotypes and transcriptomic data in the database, we show two applications for identifying prognosis-associated cells and tumor microenvironment. HCCDB v2.0 is available at http://lifeome.net/database/hccdb2.
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Project description:FSHD is characterized by the misexpression of DUX4 in skeletal muscle. Although DUX4 upregulation is thought to be the pathogenic cause of FSHD, DUX4 is lowly expressed in patient samples, and analysis of the consequences of DUX4 expression has largely relied on artificial overexpression. To better understand the native expression profile of DUX4 and its targets, we performed bulk RNA-seq on a 6-day differentiation time-course in primary FSHD2 patient myoblasts. We identify a set of 54 genes upregulated in FSHD2 cells, termed FSHD-induced genes. Using single-cell and single-nucleus RNA-seq on myoblasts and differentiated myotubes, respectively, we captured, for the first time, DUX4 expressed at the single-nucleus level in a native state. We identified two populations of FSHD myotube nuclei based on low or high enrichment of DUX4 and FSHD-induced genes ("FSHD-Lo" and "FSHD Hi", respectively). FSHD-Hi myotube nuclei coexpress multiple DUX4 target genes including DUXA, LEUTX and ZSCAN4, and also upregulate cell cycle-related genes with significant enrichment of E2F target genes and p53 signaling activation. We found more FSHD-Hi nuclei than DUX4-positive nuclei, and confirmed with in situ RNA/protein detection that DUX4 transcribed in only one or two nuclei is sufficient for DUX4 protein to activate target genes across multiple nuclei within the same myotube. DUXA (the DUX4 paralog) is more widely expressed than DUX4, and depletion of DUXA suppressed the expression of LEUTX and ZSCAN4 in late, but not early, differentiation. The results suggest that the DUXA can take over the role of DUX4 to maintain target gene expression. These results provide a possible explanation as to why it is easier to detect DUX4 target genes than DUX4 itself in patient cells and raise the possibility of a self-sustaining network of gene dysregulation triggered by the limited DUX4 expression.
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