Structured 3' UTRs destabilize mRNAs in plants.

BACKGROUND: RNA secondary structure (RSS) can influence the regulation of transcription, RNA processing, and protein synthesis, among other processes. 3' untranslated regions (3' UTRs) of mRNA also hold the key for many aspects of gene regulation. However, there are often contradictory results regarding the roles of RSS in 3' UTRs in gene expression in different organisms and/or contexts. RESULTS: Here, we incidentally observe that the primary substrate of miR159a (pri-miR159a), when embedded in a 3' UTR, could promote mRNA accumulation. The enhanced expression is attributed to the earlier polyadenylation of the transcript within the hybrid pri-miR159a-3' UTR and, resultantly, a poorly structured 3' UTR. RNA decay assays indicate that poorly structured 3' UTRs could promote mRNA stability, whereas highly structured 3' UTRs destabilize mRNA in vivo. Genome-wide DMS-MaPseq also reveals the prevailing inverse relationship between 3' UTRs' RSS and transcript accumulation in the transcriptomes of Arabidopsis, rice, and even human. Mechanistically, transcripts with highly structured 3' UTRs are preferentially degraded by 3'-5' exoribonuclease SOV and 5'-3' exoribonuclease XRN4, leading to decreased expression in Arabidopsis. Finally, we engineer different structured 3' UTRs to an endogenous FT gene and alter the FT-regulated flowering time in Arabidopsis. CONCLUSIONS: We conclude that highly structured 3' UTRs typically cause reduced accumulation of the harbored transcripts in Arabidopsis. This pattern extends to rice and even mammals. Furthermore, our study provides a new strategy of engineering the 3' UTRs' RSS to modify plant traits in agricultural production and mRNA stability in biotechnology.

H3.1K27me1 loss confers Arabidopsis resistance to Geminivirus by sequestering DNA repair proteins onto host genome.

The H3 methyltransferases ATXR5 and ATXR6 deposit H3.1K27me1 to heterochromatin to prevent genomic instability and transposon re-activation. Here, we report that atxr5 atxr6 mutants display robust resistance to Geminivirus. The viral resistance is correlated with activation of DNA repair pathways, but not with transposon re-activation or heterochromatin amplification. We identify RAD51 and RPA1A as partners of virus-encoded Rep protein. The two DNA repair proteins show increased binding to heterochromatic regions and defense-related genes in atxr5 atxr6 vs wild-type plants. Consequently, the proteins have reduced binding to viral DNA in the mutant, thus hampering viral amplification. Additionally, RAD51 recruitment to the host genome arise via BRCA1, HOP2, and CYCB1;1, and this recruitment is essential for viral resistance in atxr5 atxr6. Thus, Geminiviruses adapt to healthy plants by hijacking DNA repair pathways, whereas the unstable genome, triggered by reduced H3.1K27me1, could retain DNA repairing proteins to suppress viral amplification in atxr5 atxr6.

Intrinsically disordered proteins SAID1/2 condensate on SERRATE for dual inhibition of miRNA biogenesis in Arabidopsis.

Intrinsically disordered proteins (IDPs) SAID1/2 are hypothetic dentin sialophosphoprotein-like proteins, but their true functions are unknown. Here, we identified SAID1/2 as negative regulators of SERRATE (SE), a core factor in miRNA biogenesis complex (microprocessor). Loss-of-function double mutants of said1; said2 caused pleiotropic developmental defects and thousands of differentially expressed genes that partially overlapped with those in se. said1; said2 also displayed increased assembly of microprocessor and elevated accumulation of microRNAs (miRNAs). Mechanistically, SAID1/2 promote pre-mRNA processing 4 kinase A-mediated phosphorylation of SE, causing its degradation in vivo. Unexpectedly, SAID1/2 have strong binding affinity to hairpin-structured pri-miRNAs and can sequester them from SE. Moreover, SAID1/2 directly inhibit pri-miRNA processing by microprocessor in vitro. Whereas SAID1/2 did not impact SE subcellular compartmentation, the proteins themselves exhibited liquid-liquid phase condensation that is nucleated on SE. Thus, we propose that SAID1/2 reduce miRNA production through hijacking pri-miRNAs to prevent microprocessor activity while promoting SE phosphorylation and its destabilization in Arabidopsis.

A framework to predict the applicability of Oncotype DX, MammaPrint, and E2F4 gene signatures for improving breast cancer prognostic prediction.

To improve cancer precision medicine, prognostic and predictive biomarkers are critically needed to aid physicians in deciding treatment strategies in a personalized fashion. Due to the heterogeneous nature of cancer, most biomarkers are expected to be valid only in a subset of patients. Furthermore, there is no current approach to determine the applicability of biomarkers. In this study, we propose a framework to improve the clinical application of biomarkers. As part of this framework, we develop a clinical outcome prediction model (CPM) and a predictability prediction model (PPM) for each biomarker and use these models to calculate a prognostic score (P-score) and a confidence score (C-score) for each patient. Each biomarker's P-score indicates its association with patient clinical outcomes, while each C-score reflects the biomarker applicability of the biomarker's CPM to a patient and therefore the confidence of the clinical prediction. We assessed the effectiveness of this framework by applying it to three biomarkers, Oncotype DX, MammaPrint, and an E2F4 signature, which have been used for predicting patient response, pathologic complete response versus residual disease to neoadjuvant chemotherapy (a classification problem), and recurrence-free survival (a Cox regression problem) in breast cancer, respectively. In both applications, our analyses indicated patients with higher C scores were more likely to be correctly predicted by the biomarkers, indicating the effectiveness of our framework. This framework provides a useful approach to develop and apply biomarkers in the context of cancer precision medicine.

Impact of Oncotype DX testing on ER+ breast cancer treatment and survival in the first decade of use.

BACKGROUND: The Oncotype DX breast recurrence score has been introduced more than a decade ago to aid physicians in determining the need for systemic adjuvant chemotherapy in patients with early-stage, estrogen receptor (ER)+, lymph node-negative breast cancer. METHODS: In this study, we utilized data from The Surveillance, Epidemiology, and End Results (SEER) Program to investigate temporal trends in Oncotype DX usage among US breast cancer patients in the first decade after the introduction of the Oncotype DX assay. RESULTS: We found that the use of Oncotype DX has steadily increased in the first decade of use and that this increase is associated with a decreased usage of chemotherapy. Patients who utilized the Oncotype DX test tended to have improved survival compared to patients who did not use the assay even after adjusting for clinical variables associated with prognosis. In addition, chemotherapy usage in patients with high-risk scores is associated with significantly longer overall and breast cancer-specific survival compared to high-risk patients who did not receive chemotherapy. On the contrary, patients with low-risk scores who were treated with chemotherapy tended to have shorter overall survival compared to low-risk patients who forwent chemotherapy. CONCLUSION: We have provided a comprehensive temporal overview of the use of Oncotype DX in breast cancer patients in the first decade after Oncotype DX was introduced. Our results suggest that the use of Oncotype DX is increasing in ER+ breast cancer and that the Oncotype DX test results provide valuable information for patient treatment and prognosis.

Systematic computational identification of prognostic cytogenetic markers in neuroblastoma.

BACKGROUND: Neuroblastoma (NB) is the most common extracranial solid tumor found in children. The frequent gain/loss of many chromosome bands in tumor cells and absence of mutations found at diagnosis suggests that NB is a copy number-driven cancer. Despite the previous work, a systematic analysis that investigates the relationship between such frequent gain/loss of chromosome bands and patient prognosis has yet to be implemented. METHODS: First, we analyzed two NB CNV datasets to select chromosomal bands with a high frequency of gain or loss. Second, we applied a computational approach to infer sample-specific CNVs for each chromosomal band selected in step 1 based on gene expression data. Third, we applied univariate Cox proportional hazards models to examine the association between the resulting inferred copy number values (iCNVs) and patient survival. Finally, we applied multivariate Cox proportional hazards models to select chromosomal bands that remained significantly associated with prognosis after adjusting for critical clinical variables, including age, stage, gender, and MYCN amplification status. RESULTS: Here, we used a computational method to infer the copy number variations (CNVs) of sample-specific chromosome bands from NB patient gene expression profiles. The resulting inferred CNVs (iCNVs) were highly correlated with the experimentally determined CNVs, demonstrating CNVs can be accurately inferred from gene expression profiles. Using this iCNV metric, we identified 58 frequent gain/loss chromosome bands that were significantly associated with patient survival. Furthermore, we found that 7 chromosome bands were still significantly associated with patient survival even when clinical factors, such as MYCN status, were considered. Particularly, we found that the chromosome band chr11p14 has high potential as a novel candidate cytogenetic biomarker for clinical use. CONCLUSION: Our analysis resulted in a comprehensive list of prognostic chromosome bands supported by strong statistical evidence. In particular, the chr11p14 gain event provided additional prognostic value in addition to well-established clinical factors, including MYCN status, and thereby represents a novel candidate cytogenetic biomarker with high clinical potential. Additionally, this computational framework could be readily extended to other cancer types, such as leukemia.

CMEP: a database for circulating microRNA expression profiling.

MOTIVATION: In recent years, several experimental studies have revealed that the microRNAs (miRNAs) in serum, plasma, exosome and whole blood are dysregulated in various types of diseases, indicating that the circulating miRNAs may serve as potential noninvasive biomarkers for disease diagnosis and prognosis. However, no database has been constructed to integrate the large-scale circulating miRNA profiles, explore the functional pathways involved and predict the potential biomarkers using feature selection between the disease conditions. Although there have been several studies attempting to generate a circulating miRNA database, they have not yet integrated the large-scale circulating miRNA profiles or provided the biomarker-selection function using machine learning methods. RESULTS: To fill this gap, we constructed the Circulating MicroRNA Expression Profiling (CMEP) database for integrating, analyzing and visualizing the large-scale expression profiles of phenotype-specific circulating miRNAs. The CMEP database contains massive datasets that were manually curated from NCBI GEO and the exRNA Atlas, including 66 datasets, 228 subsets and 10 419 samples. The CMEP provides the differential expression circulating miRNAs analysis and the KEGG functional pathway enrichment analysis. Furthermore, to provide the function of noninvasive biomarker discovery, we implemented several feature-selection methods, including ridge regression, lasso regression, support vector machine and random forests. Finally, we implemented a user-friendly web interface to improve the user experience and to visualize the data and results of CMEP. AVAILABILITY AND IMPLEMENTATION: CMEP is accessible at http://syslab5.nchu.edu.tw/CMEP.

Association between smoking, pancreatic insulin secretion and insulin resistance in Chinese subjects with or without glucose intolerance.

BACKGROUND: There are studies suggesting smoking may increase the risk of type 2 diabetes. Effects of smoking on insulin secretion and insulin resistance (IR) are, however, controversial. METHODS: This is a cross-sectional study. Since there were very few smokers among Hong Kong Chinese women, only men (n = 1068) were analyzed in this report. Fasting and 2-hour plasma glucose and insulin were measured. Insulinogenic index as well as beta-cell function and IR based on homeostatic model assessment (HOMA) by computer model (HOMA Calculator v2.2) were calculated. RESULTS: Of the 1068 men, 147 had newly diagnosed diabetes, 131 newly diagnosed impaired glucose tolerance (IGT) and 790 were non-diabetic normal controls. Smokers had similar fasting and 2-hour insulin levels, insulinogenic index and HOMA derived beta-cell function as compared to non-smokers in the groups with diabetes, IGT or normal oral glucose tolerance test (OGTT). IR was also similar between smokers, ex-smokers and non-smokers in those with normal OGTT. In men with IGT or diabetes, after adjustment for age and body mass index, smokers were more insulin resistant as compared to non-smokers (IR, IGT: 1.59 +/- 1.07 vs 1.03 +/- 0.54, P < 0.05; diabetes: 1.96 +/- 1.36 vs 1.06 +/- 0.45, P < 0.01). With Logistic regression analysis, comparing smokers and non-smokers, IR was independently associated with smoking (odds ratio (95% CI), IGT: 2.23 (1.05, 4.71); diabetes: 3.92 (1.22, 12.58)). None of the other insulin parameters enter into the model among those with normal OGTT or comparing ex-smokers and non-smoker or smokers and ex-smokers. CONCLUSIONS: In Chinese men, smoking did not show any direct association with insulin levels and pancreatic insulin secretion. Smoking men with IGT or diabetes appeared more insulin resistant than their non-smoking counterparts.