Transcriptomic Analysis Reveals the Regulatory Mechanism of Color Diversity in Rhododendron pulchrum Sweet (Ericaceae)

Rhododendron pulchrum Sweet is a traditional ornamental plant cultivated in China and presents a great variation in petal coloration. However, few studies have been performed to reveal the genes involved and the regulatory mechanism of flower color formation in this plant. In this study, to explore the underlying genetic basis of flower color formation, transcriptome analysis was performed by high-throughput sequencing techniques on four petal samples of different colors: purple, pink, light pink, and white. Results show that a total of 35.55 to 40.56 million high-quality clean reads were obtained, of which 28.56 to 32.65 million reads were mapped to the reference genome. For their annotation, 28,273, 18,054, 24,301, 19,099, and 11,507 genes were allocated to Nr, Swiss-Prot, Pfam, GO, and KEGG databases, correspondingly. There were differentially expressed genes among the four different petal samples, including signal-transduction-related genes, anthocyanin biosynthesis genes, and transcription factors. We found that the higher expressed levels of genes associated with flavonol synthase (FLS) might be the key to white formation, and the formation of red color may be related to the higher expression of flavanone 4-reductase (DFR) families. Overall, our study provides some valuable information for exploring and understanding the flower color intensity variation in R. pulchrum.

Identification of a four-microRNA panel in serum for screening renal cell carcinoma

BACKGROUND

The aim of the study was to identify serum microRNAs (miRNAs) as potential biomarkers for screening renal cell carcinoma.

METHODS

The study was divided into three stages, including screening stage, training stage, and validation stage. In the screening stage, we examined the expression of 30 serum miRNAs from healthy controls (HCs) and renal cell carcinoma (RCC) patients. We further studied the dysregulated miRNAs in training (30 RCC and 26 HCs) and validation (73 RCC and 80 HCs) stages. We estimated the diagnostic value of miRNAs by receiver operating characteristic (ROC) curves and the area under the ROC curve (AUC). Finally, bioinformatics analysis were performed towards target genes of differentially expressed miRNAs.

RESULTS

Six serum miRNAs (miR-17-5p, miR-20a-5p, miR-21-5p, miR-150-5p, miR-145-5p and miR-146a-5p) in RCC patients were obviously differentially expressed compared to those in HCs in training stage and validation stage. To increase diagnostic value, we combined these six serum miRNAs and made a four-microRNA (miR-21-5p, miR-150-5p, miR-145-5p and miR-146a-5p) panel, and AUC of the panel was 0.938 (95% CI: 0.889-0.971; sensitivity=90.79%, specificity=93.75%). The genes targeted by these miRNAs were suggested that they may be involved in the process of cancers by the bioinformatics analysis.

CONCLUSIONS

Our study was performing a four-microRNA panel in serum for screening enal cell carcinoma. The four-miRNA panel (miR-21-5p, miR-150-5p, miR-145-5p and miR-146a-5p) may be perform as a biomarker without invasiveness for RCC screening.

A panel of eight autophagy-related long non-coding RNAs is a good predictive parameter for clear cell renal cell carcinoma

Clear-cell renal cell carcinoma (ccRCC) carries a variable prognosis. Prognostic biomarkers can stratify patients according to risk, and can provide crucial information for clinical decision-making. We screened for an autophagy-related long non-coding lncRNA (lncRNA) signature to improve postoperative risk stratification in The Cancer Genome Atlas (TCGA) database. We confirmed this model in ICGC and SYSU cohorts as a significant and independent prognostic signature. Western blotting, autophagic-flux assay and transmission electron microscopy were used to verify that regulation of expression of 8 lncRNAs related to autophagy affected changes in autophagic flow in vitro. Our data suggest that 8-lncRNA signature related to autophagy is a promising prognostic tool in predicting the survival of patients with ccRCC. Combination of this signature with clinical and pathologic parameters could aid accurate risk assessment to guide clinical management, and this 8-lncRNAs signature related to autophagy may serve as a therapeutic target.

Targeting Strategies for Renal Cancer Stem Cell Therapy

Renal cell carcinoma (RCC) is an intractable genitourinary malignancy that accounts for approximately 4% of adult malignancies. Currently, there is no approved targeted therapy for RCC that has yielded durable remissions, and they remain palliative in intent. Emerging evidence has indicated that renal tumorigenesis and RCC treatment-resistance may originate from renal cancer stem cells (CSCs) with tumor-initiating capacity (CSC hypothesis). A better understanding of the mechanism underlying renal CSCs will help to dissect RCC heterogeneity and drug treatment efficiency, to promote more personalized and targeted therapies. In this review, we summarized the stem cell characteristics of renal CSCs. We outlined the targeting strategies and challenges associated with developing therapies that target renal CSCs angiogenesis, immunosuppression, signaling pathways, surface biomarkers, microRNAs and nanomedicine. In conclusion, CSCs are an important role in renal carcinogenesis and represent a valid target for treatment of RCC patients.

Renal Cell Tumors: Uncovering the Biomarker Potential of ncRNAs

Renal cell tumors (RCT) remain as one of the most common and lethal urological tumors worldwide. Discrimination between (1) benign and malignant disease, (2) indolent and aggressive tumors, and (3) patient responsiveness to a specific therapy is of major clinical importance, allowing for a more efficient patient management. Nonetheless, currently available tools provide limited information and novel strategies are needed. Over the years, a putative role of non-coding RNAs (ncRNAs) as disease biomarkers has gained relevance and is now one of the most prolific fields in biological sciences. Herein, we extensively sought the most significant reports on ncRNAs as potential RCTs' diagnostic, prognostic, predictive, and monitoring biomarkers. We could conclude that ncRNAs, either alone or in combination with currently used clinical and pathological parameters, might represent key elements to improve patient management, potentiating the implementation of precision medicine. Nevertheless, most ncRNA biomarkers require large-scale validation studies, prior to clinical implementation.

MicroRNA profile in stage I clear cell renal cell carcinoma predicts progression to metastatic disease

OBJECTIVE

This study sought to identify microRNA (miRNA) profiles of small, pathologically confirmed stage 1 clear cell renal cell carcinoma (ccRCC) tumors that are associated with progression to metachronous metastatic disease.

MATERIALS AND METHODS

Fifty-five pathologic stage 1 ccRCC tumors ≤5cm, from 2 institutions, were examined in a miRNA screening, followed by a validation study. For the screening phase 752 miRNA were evaluated on each sample to identify those with differential expression between tumors that subsequently did (n = 10) or did not (n = 10) progress to metastatic disease. For the validation, 35 additional samples (20 nonprogressors and 15 with distant progression) were utilized to investigate 20 miRNA to determine if a miRNA panel could differentiate aggressive tumors: associations of miRNA expression with cancer specific survival was also investigated.

RESULTS

In the screening analysis, 35 miRNA were differentially expressed (P < 0.05, FDR < 0.1) between the groups. In the validation, 11 miRNA were confirmed to have differential expression. The miRNA -10a-5p, -23b-3p, and -26a-5p differentiated nonprogressive and distant progressive disease with a sensitivity of 73.3% and a specificity of 85% (AUC=0.893). In addition, levels of miR-30a-3p and -145-5p were identified as independent prognostic factors of cancer specific survival.

CONCLUSIONS

This investigation identified miRNA biomarkers that may differentiate between non-progressive ccRCC tumors and those that progress to metastatic disease in this group of stage I tumors. The miRNA profiles determined in this study have the potential to identify patients with small renal masses who are likely to have progressive ccRCC. Such information may be valuable to incorporate into predictive models.

Machine learning with autophagy-related proteins for discriminating renal cell carcinoma subtypes

Machine learning techniques have been previously applied for classification of tumors based largely on morphological features of tumor cells recognized in H&E images. Here, we tested the possibility of using numeric data acquired from software-based quantification of certain marker proteins, i.e. key autophagy proteins (ATGs), obtained from immunohistochemical (IHC) images of renal cell carcinomas (RCC). Using IHC staining and automated image quantification with a tissue microarray (TMA) of RCC, we found ATG1, ATG5 and microtubule-associated proteins 1A/1B light chain 3B (LC3B) were significantly reduced, suggesting a reduction in the basal level of autophagy with RCC. Notably, the levels of the ATG proteins expressed did not correspond to the mRNA levels expressed in these tissues. Applying a supervised machine learning algorithm, the K-Nearest Neighbor (KNN), to our quantified numeric data revealed that LC3B provided a strong measure for discriminating clear cell RCC (ccRCC). ATG5 and sequestosome-1 (SQSTM1/p62) could be used for classification of chromophobe RCC (crRCC). The quantitation of particular combinations of ATG1, ATG16L1, ATG5, LC3B and p62, all of which measure the basal level of autophagy, were able to discriminate among normal tissue, crRCC and ccRCC, suggesting that the basal level of autophagy would be a potentially useful parameter for RCC discrimination. In addition to our observation that the basal level of autophagy is reduced in RCC, our workflow from quantitative IHC analysis to machine learning could be considered as a potential complementary tool for the classification of RCC subtypes and also for other types of tumors for which precision medicine requires a characterization.

A Machine Learning Approach for the Classification of Kidney Cancer Subtypes Using miRNA Genome Data

Kidney cancer is one of the deadliest diseases and its diagnosis and subtype classification are crucial for patients’ survival. Thus, developing automated tools that can accurately determine kidney cancer subtypes is an urgent challenge. It has been confirmed by researchers in the biomedical field that miRNA dysregulation can cause cancer. In this paper, we propose a machine learning approach for the classification of kidney cancer subtypes using miRNA genome data. Through empirical studies we found 35 miRNAs that possess distinct key features that aid in kidney cancer subtype diagnosis. In the proposed method, Neighbourhood Component Analysis (NCA) is employed to extract discriminative features from miRNAs and Long Short Term Memory (LSTM), a type of Recurrent Neural Network, is adopted to classify a given miRNA sample into kidney cancer subtypes. In the literature, only a couple of kidney subtypes have been considered for classification. In the experimental study, we used the miRNA quantitative read counts data, which was provided by The Cancer Genome Atlas data repository (TCGA). The NCA procedure selected 35 of the most discriminative miRNAs. With this subset of miRNAs, the LSTM algorithm was able to group kidney cancer miRNAs into five subtypes with average accuracy around 95% and Matthews Correlation Coefficient value around 0.92 under 10 runs of randomly grouped 5-fold cross-validation, which were very close to the average performance of using all miRNAs for classification.

Oncogenic miR-663a is associated with cellular function and poor prognosis in renal cell carcinoma

BACKGROUND

MicroRNA(miRNA) plays a key regulatory role in various stages of tumorigenesis, including cell growth, cell cycle control, apoptosis avoidance, tissue invasion, and metastasis. Several microRNAs are involved in the development of renal cell carcinoma (RCC) and the malignant transformation process. However, the effects of miR-663a on RCC have rarely been reported.

METHODS

In the present study, the expression of miR-663a was examined in RCC using matched normal kidney tissues and four cell lines (786-O, Caki-1, ACHN and HK-2). MicroRNA mimics were transiently transfected into RCC cells and the effects of over expression on proliferation, migration, invasion, and apoptosis was observed. In addition, the relationship between miR-663a expression in 42 formalin-fixed paraffin-embedded (FFPE) clear cell renal carcinoma (ccRCC) samples and clinical pathological variables and overall survival was investigated. We evaluated the prognostic value of miR-663a expression in ccRCC by experimental results.

RESULTS

The results showed that the expression of miR-663a was up-regulated in RCC cells and tissues and miR-663a was associated with proliferation, migration, invasion, and apoptosis of RCC. Cox proportional hazard regression analysis showed that a high expression of miR-663a patients had a significantly shorter overall survival in univariate and multivariate analysis. Kaplan-Meier survival curves showed that a high expression of miR-663a patients had a significantly shorter overall survival.

CONCLUSIONS

These results indicate that miR-663a can be used as an independent marker for the poor prognosis of ccRCC, and may also play an important role as a tumor oncogene in the occurrence and development of RCC.

Transcriptome analysis and identification of genes associated with flower development in Rhododendron pulchrum Sweet (Ericaceae)

Flowering process is essential for plant development. However, the molecular mechanisms driving flower development of ornamental woody Rhododendron pulchrum Sweet are difficult to elucidate due to the lack of genomic data. In this research, high-throughput sequencing and comparative transcriptome analyses of R. pulchrum flowers collected at three key stages were performed: floral bud stage, early flowering stage, and full-flowering stage. Furthermore, expression of genes involved in flower development was also validated with quantitative real-time PCR (qRT-PCR). RNA-seq yielded 96,350,697 bp of clean reads, which were assembled into 98,610 unigenes with an average length of 717 bp. 58,279 (59.10%) unigenes could be annotated, including 324 major unigenes associated with floral development. In addition, ten modules (20,443 mRNAs) were dissected in the co-expression network. Especially, Flowering Locus (FLC) and Flowering Locus T (FT) were co-expressed. 9493 differentially expressed genes (DEGs) were scanned among three stages, and most DEGs existed between flower bud stage and early flowering stage. In particular, 79 DGEs associated with flowering process were enriched in 28 GO terms. Moreover, the expression levels of MYC2, EIN3, and ARR-B were all lowest at early flowering stage, while transcripts of MYC2, TIR1, CYCD3, COL-1, and EIN3 were all peaked at flower bud stage. Transcriptome profile presented here will benefit deep insights into molecular mechanism underlying R. pulchrum flowering process.

A comprehensive clinicopathological evaluation of the differential expression of microRNA-331 in breast tumors and its diagnostic significance

OBJECTIVE

MicroRNA-331 (miR-331) has shown regulatory activity against several genes whose expression has been claimed to be deregulated in breast tumors, including that of epidermal growth factor receptor 2 (HER2). Herein, the clinical value of miR-331 expression was investigated by analyzing its levels in breast benign and malignant tumors.

METHODS

The expression levels of miR-331 were quantified via real-time PCR in 130 malignant and 66 benign breast tissue specimens collected after surgical resection of primary tumors. The generated data were analyzed by applying several statistical tests in order to examine the relationship of miR-331 expression with various established clinicopathological features and survival data of patients.

RESULTS

Our data showed that miR-331 was overexpressed in malignant breast tumors compared to their benign counterparts both overall (P = 0.026) and individually when the subgroups of fibroadenoma and invasive ductal carcinoma were analyzed with each other (P = 0.001). ROC curve analysis confirmed the diagnostic value of these variations, providing an AUC value equal to 0.597 (P = 0.026) and 0.663 (P = 0.001), respectively. Furthermore, miR-331 levels were elevated (P = 0.026) in ductal cancerous specimens compared to the lobular ones but failed to correlate with other clinicopathological features or survival data of the breast cancer patients.

CONCLUSIONS

Our results provide evidence that miR-331 levels might provide valuable information regarding the differential diagnosis of benign and malignant breast tumors but present no prognostic value for breast cancer.

miR-144-3p serves as a tumor suppressor for renal cell carcinoma and inhibits its invasion and metastasis by targeting MAP3K8

MicroRNAs (miRNAs) are important regulators involved in various cancers, including renal cell carcinoma (RCC). The role of the miRNAs involved in RCC progress and metastasis is largely unknown. Here, miRNA microarray analysis was performed to screen the significant miRNAs involved in RCC progress, and miR-144-3p was chosen for further study. We found that the expression of miR-144-3p was significantly lower in RCC specimens and cell lines. In addition, low expression level of miR-144-3p is correlated with tumor progression and poor survival in RCC patients. Based on in vitro assays, we found that miR-144-3p significantly inhibit cancer cell proliferation and progression. Furthermore, function studies revealed that miR-144-3p was significantly correlated with the metastasis potential by affecting the epithelial-mesenchymal transition (EMT). Moreover, Mitogen-activated protein kinase 8 (MAP3K8) is direct target of miR-144-3p, while the expression levels of MAP3K8 were inversely correlated with the expression levels of miR-144-3p in RCC tissues. Overall, our findings demonstrate that miR-144-3p targeted the MAP3K8 pathway to reduce tumor cells proliferation and metastasis in RCC, suggesting that this axis may provide a novel therapeutic target for RCC therapy.

Cooperative Effect of miR-141-3p and miR-145-5p in the Regulation of Targets in Clear Cell Renal Cell Carcinoma

Background

Due to the poor prognosis for advanced renal cell carcinoma (RCC), there is an urgent need for new therapeutic targets and for prognostic markers to identify high risk tumors. MicroRNAs (miRNAs) are frequently dysregulated in tumors, play a crucial role during carcinogenesis and therefore might be promising new biomarkers. In previous studies, we identified miR-141-3p and miR-145-5p to be downregulated in clear cell RCC (ccRCC). Our objective was to investigate the functional association of these miRNAs, focusing on the cooperative regulation of new specific targets and their role in ccRCC progression.

Methods

The effect of miR-141-3p and miR-145-5p on cell migration was examined by overexpression in 786-O cells. New targets of both miRNAs were identified by miRWalk, validated in 786-O and ACHN cells and additionally characterized in ccRCC tissue on mRNA and protein level.

Results

In functional analysis, a tumor suppressive effect of miR-141-3p and miR-145-5p by decreasing migration and invasion of RCC cells could be shown. Furthermore, co-overexpression of the miRNAs seemed to result in an increased inhibition of cell migration. Both miRNAs were recognized as post-transcriptional regulators of the targets EAPP, HS6ST2, LOX, TGFB2 and VRK2. Additionally, they showed a cooperative effect again as demonstrated by a significantly increased inhibition of HS6ST2 and LOX expression after simultaneous overexpression of both miRNAs. In ccRCC tissue, LOX mRNA expression was strongly increased compared to normal tissue, allowing also to distinguish between non-metastatic and already metastasized primary tumors. Finally, in subsequent tissue microarray analysis LOX protein expression showed a prognostic relevance for the overall survival of ccRCC patients.

Conclusion

These results illustrate a jointly strengthening effect of the dysregulated miR-141-3p and miR-145-5p in various tumor associated processes. Focusing on the cooperative effect of miRNAs provides new opportunities for the development of therapeutic strategies and offers novel prognostic and diagnostic capabilities.