The sup. Excel file for the comprehensive analysis of Hsp90-Cdc37’s client proteins. Comprehensive Analysis of Hsp90-Cdc37’s client proteins by using FunRich tool. (XLSX 313 kb)
Considerable efforts have been devoted to exploring the breast cancer mutational landscape to understand its genetic complexity. However, no studies have yet comprehensively elucidated the molecular characterization of breast tumors in Chinese women. This study aimed to determine the potential clinical utility of peripheral blood assessment for circulating tumor-derived DNA (ctDNA) and comprehensively characterize the female Chinese population's genetic mutational spectrum. We used Omi-Seq to create cancer profiles of 273 patients enrolled at The First Affiliated Hospital of Wenzhou Medical University. The gene landscape results indicate PIK3CA and TP53 as the most frequently detected genes, followed by ERBB2, in Chinese breast cancer patients. The accuracy of ERBB2 copy number variations in tissue/formalin-fixed and paraffin-embedded samples was 95% with 86% sensitivity and 99% specificity. Moreover, mutation numbers varied between different molecular cell-free DNA subtypes, with the basal-like patients harboring a higher number of variants than the luminal patients. Furthermore, ratio changes in the max ctDNA allele fraction highly correlated with clinical response measurements, including cancer relapse and metastasis. Our data demonstrate that ctDNA characterization using the Omi-Seq platform can extend the capacity of personalized clinical cancer management.
Circular RNAs (circRNAs) are a novel class of non-coding RNA that, unlike linear RNAs, form a covalently closed loop without the 5' and 3' ends. Growing evidence shows that circular RNAs play important roles in life processes and have great potential implications in clinical and research fields. The accurate modeling of circRNAs structure and stability has far-reaching impact on our understanding of their functions and our ability to develop RNA-based therapeutics. The cRNAsp12 server offers a user-friendly web interface to predict circular RNA secondary structures and folding stabilities from the sequence. Through the helix-based landscape partitioning strategy, the server generates distinct ensembles of structures and predicts the minimal free energy structures for each ensemble with the recursive partition function calculation and backtracking algorithms. For structure predictions in the limited structural ensemble, the server also provides users with the option to set the structural constraints of forcing the base pairs and/or forcing the unpaired bases, such that only structures that meet the criteria are enumerated recursively.
Abstract Previous studies have shown that both Forkhead Box M1 (FoxM1) and pituitary tumor transforming gene 1 (PTTG1) were associated with cancer development and metastases. This study aims to investigate the relation between FoxM1 and PTTG1 and its role in colorectal cancer cell behavior. The microarray data of colorectal cancer were analyzed to determine the association of FoxM1 and PTTG1 expression. Luciferase reporter assay, ChIP and EMSA were used to identify the regulatory mechanisms between FoxM1 and PTTG1. PTTG1 mRNA and protein levels were examined using real-time PCR and western blot after knocking down or over expressing FoxM1. The roles of FoxM1 and PTTG in tumor metastasis were investigated by cell migration and invasion assays. Gene expression microarray data indicated that FoxM1 and PTTG1 are concordantly up-regulated in colorectal cancer tissues. Over-expression of FoxM1 up-regulated PTTG1 expression and knock-down of FoxM1 did the opposite, indicating that PTTG1 was regulated by FoxM1. Luciferase reporter assay indicated that -391 to +50 bps of PTTG1 promoter are important for FoxM1 to enhance PTTG1 promoter activity. Sequence analysis identified two potential FoxM1 binding sites. EMSA indicated that FoxM1 directly binds to PTTG1 promoter at the -350 to -343 binding motif. This binding was confirmed by chromatin immunoprecipitation in HCT116 and SW620 cells. Boyden chamber assay indicated that FoxM1 and PTTG1 concordantly regulate migration and invasion of HCT116 and SW620 colorectal cancer cells. In summary, our results elucidate that FoxM1 up-regulates PTTG1 transcription through binding to PTTG1 promoter. PTTG1 likely mediates effects of FoxM1 on colorectal cancer cell migration and invasion. Citation Format: Jinjun Guo, Yun Zheng, Yunguang Tong, H Philip Koeffler. FoxM1 transactivates PTTG1 and promotes colorectal cancer cell migration and invasion. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 2081. doi:10.1158/1538-7445.AM2014-2081
Abstract Motivation Circular RNAs (circRNAs) have been found to have the potential to code proteins. Internal ribosome entry sites (IRESs) are key RNA regulatory elements for the translation of proteins by circRNAs through a cap-independent mechanism. IRES can be identified by bicistronic assay, but the method is time-consuming and laborious. Therefore, it is important to develop computational methods for facilitating IRES identification, evaluation, and design in circRNAs. Results In this study, we proposed DeepCIP, a multimodal deep learning approach for circRNA IRES prediction, by exploiting both sequence and structure information. As far as we know, DeepCIP is the first predictor for circRNA IRESs, which consists of an RNA processing module, an S-LSTM module, a GCN module, a feature fusion module, and an ensemble module. The comparative studies show that DeepCIP outperforms other comparative methods and justify the effectiveness of the sequence model and structure model of DeepCIP for extracting features. We found that the integration of structural information on the basis of sequence information effectively improves predictive performance. For the real circRNA IRES prediction, DeepCIP also outperforms other methods. DeepCIP may facilitate the study of the coding potential of circRNAs as well as the design of circRNA drugs. DeepCIP as a standalone program is freely available at https://github.org/zjupgx/DeepCIP .
Although prolactinomas can be effectively treated with dopamine agonists, about 20% of patients develop dopamine resistance or tumor recurrence after surgery, indicating a need for better understanding of underlying disease mechanisms. Although estrogen-induced rat prolactinomas have been widely used to investigate the development of this tumor, the extent that the model recapitulates features of human prolactinomas is unclear. To prioritize candidate genes and gene sets regulating human and rat prolactinomas, microarray results derived from human prolactinomas and pituitaries of estrogen-treated ACI rats were integrated and analyzed. A total of 4545 differentially expressed pituitary genes were identified in estrogen-treated ACI rats [false discovery rate (FDR) < 0.01]. By comparing pituitary microarray results derived from estrogen-treated Brown Norway rats (a strain not sensitive to estrogen), 4073 genes were shown specific to estrogen-treated ACI rats. Human prolactinomas exhibited 1177 differentially expressed genes (FDR < 0.05). Combining microarray data derived from human prolactinoma and pituitaries of estrogen-treated ACI rat, 145 concordantly expressed genes, including E2F1, Myc, Igf1, and CEBPD, were identified. Gene set enrichment analysis revealed that 278 curated pathways and 59 gene sets of transcription factors were enriched (FDR < 25%) in estrogen-treated ACI rats, suggesting a critical role for Myc, E2F1, CEBPD, and Sp1 in this rat prolactinoma. Similarly increased Myc, E2F1, and Sp1 expression was validated using real-time PCR and Western blot in estrogen-treated Fischer rat pituitary glands. In summary, characterization of individual genes and gene sets in human and in estrogen-induced rat prolactinomas validates the model and provides insights into genomic changes associated with this commonly encountered pituitary tumor.
Metastasis is the major cause of cancer-related death. Forkhead Box M1 (FoxM1) is a master regulator of tumor metastasis. This study aims to identify new FoxM1 targets in regulating tumor metastasis using bioinformatics tools as well as biological experiments. Illumina microarray was used to profile WT and PTTG1 knockout HCT116 cells. R2 Genomics Analysis was used to identify PTTG1 as a potential FoxM1 targeted gene. Luciferase reporter array, EMSA and Chromatin Immunoprecipitation (ChIP) were used to determine the binding of FoxM1 to PTTG1 promoter. Boyden chamber assay was used to evaluate the effects of FoxM1-PTTG1 on cell migration and invasion. Splenic-injection induced liver metastasis model was used to evaluate the effects of FoxM1-PTTG1 on liver metastasis of colorectal cancer. Analyses of multiple microarray datasets derived from human colorectal cancer indicated that correlation levels of FoxM1 and pituitary tumor transforming gene (PTTG1) are highly concordant (R = 0.68 ~ 0.89, p = 2.1E-226 ~ 9.6E-86). FoxM1 over-expression increased and knock-down decreased PTTG1 expression. Luciferase reporter assay identified that the −600 to −300 bp region of PTTG1 promoter is important for FoxM1 to enhance PTTG1 promoter activity. EMSA and ChIP assays confirmed that FoxM1 directly binds to PTTG1 promoter at the −391 to −385 bp region in colorectal cancer cells. Boyden chamber assay indicated that both FoxM1 and PTTG1 regulate migration and invasion of HCT116 and SW620 colorectal cancer cells. Further in vivo assays indicated that PTTG1 knock out decreased the liver metastasis of FoxM1 over-expressing HCT116 cells. Microarray analyses identified 662 genes (FDR < 0.05) differentially expressed between WT and PTTG1−/− HCT116 cells. Among them, dickkopf homolog 1 (DKK1), a known WNT pathway inhibitor, was suppressed by PTTG1 and FoxM1. PTTG1 is a FoxM1 targeted gene. FoxM1 binds to PTTG1 promoter to enhance PTTG1 transcription, and FoxM1-PTTG1 pathway promotes colorectal cancer migration and invasion.
Hyperprolactinemia, usually caused by a pituitary lactotroph tumor, leads to galactorrhea and infertility. Increased prolactin (PRL) levels may be due to enhanced PRL expression or proliferation of PRL-secreting cells. We hypothesize that PRL expression and PRL-secreting cell proliferation are linked. Using microarray-based gene expression profiling, we identified CCAAT-enhancer-binding protein δ (CEBPD) transcription factor as a critical gene that regulates both PRL expression and lactotroph cell proliferation. CEBPD expression levels are decreased approximately 7-fold in experimental rat prolactinoma cells. Forced expression of this transcription factor in PRL-secreting cells (GH3 and MMQ) inhibited PRL expression and cellular proliferation, and CEBPD knockdown by small interfering RNA leads to increased PRL expression in both cell lines. To determine mechanisms underlying this observation, we determined binding of CEBPD to the PRL promoter and also showed marked suppression (96%) of PRL promoter activity. CEBPD and Pit1 interact and attenuate each other's binding to the PRL promoter. CEBPD also suppresses expression of proliferation-related genes, including c-Myc, survivin, as well as cyclins B1, B2, and D1. These results show that PRL expression and cell proliferation are controlled in part by CEBPD.
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