Therapy-induced stress response is associated with downregulation of pre-mRNA splicing in cancer cells

Abstract Background Abnormal pre-mRNA splicing regulation is common in cancer, but the effects of chemotherapy on this process remain unclear. Methods To evaluate the effect of chemotherapy on slicing regulation, we performed meta-analyses of previously published transcriptomic, proteomic, phosphoproteomic, and secretome datasets. Our findings were verified by LC-MS/MS, western blotting, immunofluorescence, and FACS analyses of multiple cancer cell lines treated with cisplatin and pladienolide B. Results Our results revealed that different types of chemotherapy lead to similar changes in alternative splicing by inducing intron retention in multiple genes. To determine the mechanism underlying this effect, we analyzed gene expression in 101 cell lines affected by ɣ-irradiation, hypoxia, and 10 various chemotherapeutic drugs. Strikingly, оnly genes involved in the cell cycle and pre-mRNA splicing regulation were changed in a similar manner in all 335 tested samples regardless of stress stimuli. We revealed significant downregulation of gene expression levels in these two pathways, which could be explained by the observed decrease in splicing efficiency and global intron retention. We showed that the levels of active spliceosomal proteins might be further post-translationally decreased by phosphorylation and export into the extracellular space. To further explore these bioinformatics findings, we performed proteomic analysis of cisplatin-treated ovarian cancer cells. Finally, we demonstrated that the splicing inhibitor pladienolide B impairs the cellular response to DNA damage and significantly increases the sensitivity of cancer cells to chemotherapy. Conclusions Decreased splicing efficiency and global intron retention is a novel stress response mechanism that may promote survival of malignant cells following therapy. We found that this mechanism can be inhibited by pladienolide B, which significantly increases the sensitivity of cancer cells to cisplatin which makes it a good candidate drug for improving the efficiency of cancer therapy

New Insights into Therapy-Induced Progression of Cancer

The malignant tumor is a complex heterogeneous set of cells functioning in a no less heterogeneous microenvironment. Like any dynamic system, cancerous tumors evolve and undergo changes in response to external influences, including therapy. Initially, most tumors are susceptible to treatment. However, remaining cancer cells may rapidly reestablish the tumor after a temporary remission. These new populations of malignant cells usually have increased resistance not only to the first-line agent, but also to the second- and third-line drugs, leading to a significant decrease in patient survival. Multiple studies describe the mechanism of acquired therapy resistance. In past decades, it became clear that, in addition to the simple selection of pre-existing resistant clones, therapy induces a highly complicated and tightly regulated molecular response that allows tumors to adapt to current and even subsequent therapeutic interventions. This review summarizes mechanisms of acquired resistance, such as secondary genetic alterations, impaired function of drug transporters, and autophagy. Moreover, we describe less obvious molecular aspects of therapy resistance in cancers, including epithelial-to-mesenchymal transition, cell cycle alterations, and the role of intercellular communication. Understanding these molecular mechanisms will be beneficial in finding novel therapeutic approaches for cancer therapy

Table3_Deeper insights into transcriptional features of cancer-associated fibroblasts: An integrated meta-analysis of single-cell and bulk RNA-sequencing data.XLSX

Cancer-associated fibroblasts (CAFs) have long been known as one of the most important players in tumor initiation and progression. Even so, there is an incomplete understanding of the identification of CAFs among tumor microenvironment cells as the list of CAF marker genes varies greatly in the literature, therefore it is imperative to find a better way to identify reliable markers of CAFs. To this end, we summarized a large number of single-cell RNA-sequencing data of multiple tumor types and corresponding normal tissues. As a result, for 9 different types of cancer, we identified CAF-specific gene expression signatures and found 10 protein markers that showed strongly positive staining of tumor stroma according to the analysis of IHC images from the Human Protein Atlas database. Our results give an insight into selecting the most appropriate combination of cancer-associated fibroblast markers. Furthermore, comparison of different approaches for studying differences between cancer-associated and normal fibroblasts (NFs) illustrates the superiority of transcriptome analysis of fibroblasts obtained from fresh tissue samples. Using single-cell RNA sequencing data, we identified common differences in gene expression patterns between normal and cancer-associated fibroblasts, which do not depend on the type of tumor.</p

Table1_Deeper insights into transcriptional features of cancer-associated fibroblasts: An integrated meta-analysis of single-cell and bulk RNA-sequencing data.XLSX

Cancer-associated fibroblasts (CAFs) have long been known as one of the most important players in tumor initiation and progression. Even so, there is an incomplete understanding of the identification of CAFs among tumor microenvironment cells as the list of CAF marker genes varies greatly in the literature, therefore it is imperative to find a better way to identify reliable markers of CAFs. To this end, we summarized a large number of single-cell RNA-sequencing data of multiple tumor types and corresponding normal tissues. As a result, for 9 different types of cancer, we identified CAF-specific gene expression signatures and found 10 protein markers that showed strongly positive staining of tumor stroma according to the analysis of IHC images from the Human Protein Atlas database. Our results give an insight into selecting the most appropriate combination of cancer-associated fibroblast markers. Furthermore, comparison of different approaches for studying differences between cancer-associated and normal fibroblasts (NFs) illustrates the superiority of transcriptome analysis of fibroblasts obtained from fresh tissue samples. Using single-cell RNA sequencing data, we identified common differences in gene expression patterns between normal and cancer-associated fibroblasts, which do not depend on the type of tumor.</p

Table2_Deeper insights into transcriptional features of cancer-associated fibroblasts: An integrated meta-analysis of single-cell and bulk RNA-sequencing data.XLSX

Cancer-associated fibroblasts (CAFs) have long been known as one of the most important players in tumor initiation and progression. Even so, there is an incomplete understanding of the identification of CAFs among tumor microenvironment cells as the list of CAF marker genes varies greatly in the literature, therefore it is imperative to find a better way to identify reliable markers of CAFs. To this end, we summarized a large number of single-cell RNA-sequencing data of multiple tumor types and corresponding normal tissues. As a result, for 9 different types of cancer, we identified CAF-specific gene expression signatures and found 10 protein markers that showed strongly positive staining of tumor stroma according to the analysis of IHC images from the Human Protein Atlas database. Our results give an insight into selecting the most appropriate combination of cancer-associated fibroblast markers. Furthermore, comparison of different approaches for studying differences between cancer-associated and normal fibroblasts (NFs) illustrates the superiority of transcriptome analysis of fibroblasts obtained from fresh tissue samples. Using single-cell RNA sequencing data, we identified common differences in gene expression patterns between normal and cancer-associated fibroblasts, which do not depend on the type of tumor.</p

Table4_Deeper insights into transcriptional features of cancer-associated fibroblasts: An integrated meta-analysis of single-cell and bulk RNA-sequencing data.xlsx

Cancer-associated fibroblasts (CAFs) have long been known as one of the most important players in tumor initiation and progression. Even so, there is an incomplete understanding of the identification of CAFs among tumor microenvironment cells as the list of CAF marker genes varies greatly in the literature, therefore it is imperative to find a better way to identify reliable markers of CAFs. To this end, we summarized a large number of single-cell RNA-sequencing data of multiple tumor types and corresponding normal tissues. As a result, for 9 different types of cancer, we identified CAF-specific gene expression signatures and found 10 protein markers that showed strongly positive staining of tumor stroma according to the analysis of IHC images from the Human Protein Atlas database. Our results give an insight into selecting the most appropriate combination of cancer-associated fibroblast markers. Furthermore, comparison of different approaches for studying differences between cancer-associated and normal fibroblasts (NFs) illustrates the superiority of transcriptome analysis of fibroblasts obtained from fresh tissue samples. Using single-cell RNA sequencing data, we identified common differences in gene expression patterns between normal and cancer-associated fibroblasts, which do not depend on the type of tumor.</p

DataSheet1_Deeper insights into transcriptional features of cancer-associated fibroblasts: An integrated meta-analysis of single-cell and bulk RNA-sequencing data.pdf

Cancer-associated fibroblasts (CAFs) have long been known as one of the most important players in tumor initiation and progression. Even so, there is an incomplete understanding of the identification of CAFs among tumor microenvironment cells as the list of CAF marker genes varies greatly in the literature, therefore it is imperative to find a better way to identify reliable markers of CAFs. To this end, we summarized a large number of single-cell RNA-sequencing data of multiple tumor types and corresponding normal tissues. As a result, for 9 different types of cancer, we identified CAF-specific gene expression signatures and found 10 protein markers that showed strongly positive staining of tumor stroma according to the analysis of IHC images from the Human Protein Atlas database. Our results give an insight into selecting the most appropriate combination of cancer-associated fibroblast markers. Furthermore, comparison of different approaches for studying differences between cancer-associated and normal fibroblasts (NFs) illustrates the superiority of transcriptome analysis of fibroblasts obtained from fresh tissue samples. Using single-cell RNA sequencing data, we identified common differences in gene expression patterns between normal and cancer-associated fibroblasts, which do not depend on the type of tumor.</p