Frequent miRNA-convergent fusion gene events in breast cancer

Cancer fusion transcripts with human non-coding RNAs

Cancer chimeric, or fusion, transcripts are thought to most frequently appear due to chromosomal aberrations that combine moieties of unrelated normal genes. When being expressed, this results in chimeric RNAs having upstream and downstream parts relatively to the breakpoint position for the 5'- and 3'-fusion components, respectively. As many other types of cancer mutations, fusion genes can be of either driver or passenger type. The driver fusions may have pivotal roles in malignisation by regulating survival, growth, and proliferation of tumor cells, whereas the passenger fusions most likely have no specific function in cancer. The majority of research on fusion gene formation events is concentrated on identifying fusion proteins through chimeric transcripts. However, contemporary studies evidence that fusion events involving non-coding RNA (ncRNA) genes may also have strong oncogenic potential. In this review we highlight most frequent classes of ncRNAs fusions and summarize current understanding of their functional roles. In many cases, cancer ncRNA fusion can result in altered concentration of the non-coding RNA itself, or it can promote protein expression from the protein-coding fusion moiety. Differential splicing, in turn, can enrich the repertoire of cancer chimeric transcripts, e.g. as observed for the fusions of circular RNAs and long non-coding RNAs. These and other ncRNA fusions are being increasingly recognized as cancer biomarkers and even potential therapeutic targets. Finally, we discuss the use of ncRNA fusion genes in the context of cancer detection and therapy.

Decoding the Versatile Landscape of Autophagic Protein VMP1 in Cancer: A Comprehensive Review across Tissue Types and Regulatory Mechanisms

Autophagy, a catabolic process orchestrating the degradation of proteins and organelles within lysosomes, is pivotal for maintaining cellular homeostasis. However, its dual role in cancer involves preventing malignant transformation while fostering progression and therapy resistance. Vacuole Membrane Protein 1 (VMP1) is an essential autophagic protein whose expression, per se, triggers autophagy, being present in the whole autophagic flux. In pancreatic cancer, VMP1-whose expression is linked to the Kirsten Rat Sarcoma Virus (KRAS) oncogene-significantly contributes to disease promotion, progression, and chemotherapy resistance. This investigation extends to breast cancer, colon cancer, hepatocellular carcinoma, and more, highlighting VMP1's nuanced nature, contingent on specific tissue contexts. The examination of VMP1's interactions with micro-ribonucleic acids (miRNAs), including miR-21, miR-210, and miR-124, enhances our understanding of its regulatory network in cancer. Additionally, this article discusses VMP1 gene fusions, especially with ribosomal protein S6 kinase B1 (RPS6KB1), shedding light on potential implications for tumor malignancy. By deciphering the molecular mechanisms linking VMP1 to cancer progression, this exploration paves the way for innovative therapeutic strategies to disrupt these pathways and potentially improve treatment outcomes.

A smartphone-assisted electrochemiluminescent detection of miRNA-21 in situ using Ru(bpy)32+@MOF

We have proposed a signal dual-amplification electrochemiluminescence (ECL) strategy based on tris(2,2'-bipyridyl)ruthenium(II) (Ru(bpy)32+) as chromophores confined with three-dimensional (3D) zinc oxalate metal-organic frameworks (Ru(bpy)32+@MOFs) for the detection of miRNA-21. The three-dimensional chromophore connectivity in zinc oxalate MOFs provided a network among Ru(bpy)32+ units, shielding the chromophores from solvent molecules and resulting in high Ru(II) complex emission efficiency. Additionally, we discovered that magnetic beads (MBs) used as carrier for enriched signals contribute to enhanced ECL intensity of the chromophore. To evaluate its clinical application, we applied this method to determine the concentration of miRNA-21 solutions ranging from 1.56 to 100 nM, obtaining a calibration curve of ECL intensity versus logarithm of concentration (logC) of miRNA-21 with a high correlation coefficient. This work demonstrates the construction of a signal amplification strategy ECL biosensor for miRNA using Ru(bpy)32+@MOF systems and its application in ECL detection for analyte methodology.

Improved detection of clinically relevant fusion transcripts in cancer by machine learning classification

BACKGROUND

Genomic rearrangements in cancer cells can create fusion genes that encode chimeric proteins or alter the expression of coding and non-coding RNAs. In some cancer types, fusions involving specific kinases are used as targets for therapy. Fusion genes can be detected by whole genome sequencing (WGS) and targeted fusion panels, but RNA sequencing (RNA-Seq) has the advantageous capability of broadly detecting expressed fusion transcripts.

RESULTS

We developed a pipeline for validation of fusion transcripts identified in RNA-Seq data using matched WGS data from The Cancer Genome Atlas (TCGA) and applied it to 910 tumors from 11 different cancer types. This resulted in 4237 validated gene fusions, 3049 of them with at least one identified genomic breakpoint. Utilizing validated fusions as true positive events, we trained a machine learning classifier to predict true and false positive fusion transcripts from RNA-Seq data. The final precision and recall metrics of the classifier were 0.74 and 0.71, respectively, in an independent dataset of 249 breast tumors. Application of this classifier to all samples with RNA-Seq data from these cancer types vastly extended the number of likely true positive fusion transcripts and identified many potentially targetable kinase fusions. Further analysis of the validated gene fusions suggested that many are created by intrachromosomal amplification events with microhomology-mediated non-homologous end-joining.

CONCLUSIONS

A classifier trained on validated fusion events increased the accuracy of fusion transcript identification in samples without WGS data. This allowed the analysis to be extended to all samples with RNA-Seq data, facilitating studies of tumor biology and increasing the number of detected kinase fusions. Machine learning could thus be used in identification of clinically relevant fusion events for targeted therapy. The large dataset of validated gene fusions generated here presents a useful resource for development and evaluation of fusion transcript detection algorithms.

Exploring the Relationship between Fusion Genes and MicroRNAs in Cancer

Fusion genes are key cancer driver genes that can be used as potential drug targets in precision therapies, and they can also serve as accurate diagnostic and prognostic biomarkers. The fusion genes can cause microRNA (miRNA/miR) aberrations in many types of cancer. Nevertheless, whether fusion genes incite miRNA aberrations as one of their many critical oncogenic functionalities for driving carcinogenesis needs further investigation. Recent discoveries of miRNA genes that are present within the regions of genomic rearrangements that initiate fusion gene-based intronic miRNA dysregulation have brought the fusion genes into the limelight and revealed their unexplored potential in the field of cancer biology. Fusion gene-based 'promoter-switch' event aberrantly activate the miRNA-related upstream regulatory signals, while fusion-based coding region alterations disrupt the original miRNA coding loci. Fusion genes can potentially regulate the miRNA aberrations regardless of the protein-coding capability of the resultant fusion transcript. Studies on out-of-frame fusion and nonrecurrent fusion genes that cause miRNA dysregulation have attracted the attention of researchers on fusion genes from an oncological perspective and therefore could have potential implications in cancer therapies. This review will provide insights into the role of fusion genes and miRNAs, and their possible interrelationships in cancer.

Fast and sensitive validation of fusion transcripts in whole-genome sequencing data

BACKGROUND

In cancer, genomic rearrangements can create fusion genes that either combine protein-coding sequences from two different partner genes or place one gene under the control of the promoter of another gene. These fusion genes can act as oncogenic drivers in tumor development and several fusions involving kinases have been successfully exploited as drug targets. Expressed fusions can be identified in RNA sequencing (RNA-Seq) data, but fusion prediction software often has a high fraction of false positive fusion transcript predictions. This is problematic for both research and clinical applications.

RESULTS

We describe a method for validation of fusion transcripts detected by RNA-Seq in matched whole-genome sequencing (WGS) data. Our pipeline uses discordant read pairs to identify supported fusion events and analyzes soft-clipped read alignments to determine genomic breakpoints. We have tested it on matched RNA-Seq and WGS data for both tumors and cancer cell lines and show that it can be used to validate both new predicted gene fusions and experimentally validated fusion events. It was considerably faster and more sensitive than using BreakDancer and Manta, software that is instead designed to detect many different types of structural variants on a genome-wide scale.

CONCLUSIONS

We have developed a fast and very sensitive pipeline for validation of gene fusions detected by RNA-Seq in matched WGS data. It can be used to identify high-quality gene fusions for further bioinformatic and experimental studies, including validation of genomic breakpoints and studies of the mechanisms that generate fusions. In a clinical setting, it could help find expressed gene fusions for personalized therapy.

MTAP-ANRIL gene fusion promotes melanoma epithelial-mesenchymal transition-like process by activating the JNK and p38 signaling pathways

Gene fusions caused by cytogenetic aberrations play important roles in the initiation and progression of cancers. The recurrent MTAP-ANRIL fusion gene was reported to have a frequency of greater than 7% in melanoma in our previous study. However, its functions remain unclear. Truncated MTAP proteins resulting from point mutations in the last three exons of MTAP can physically interact with the wild-type MTAP protein, a tumor suppressor in several human cancers. Similarly, MTAP-ANRIL, which is translated into a truncated MTAP protein, would influence wild-type MTAP to act as an oncogene. Here, we found that MTAP-ANRIL gene fusion downregulated the expression of wild-type MTAP and promoted epithelial-mesenchymal transition-like process through the activation of JNK and p38 MAPKs in vitro and in vivo. Our results suggest that MTAP-ANRIL is a potential molecular prognostic biomarker and therapeutic target for melanoma.

The role of miRNAs as a big master regulator of signaling pathways involved in lymphoblastic leukemia

MicroRNAs (miRNAs) belong to small noncoding RNAs, which have long attracted researchers' attention because of their potency in acting either as oncogenes or tumor-suppressors in cancers. acute lymphocytic leukemia (ALL) and chronic lymphocytic leukemia (CLL) are two known types of leukemia with high mortality rates in adults and children. On a molecular basis, various signaling pathways are active in both types, making researchers consider the potential role of miRNAs in activating or suppressing these pathways to further hinder cancer development. In this review, we summarized the potential miRNAs, especially circulating ones, involved in essential signaling pathways in the ALL and CLL patients which serve as biomarkers and valuable targets in the treatment fields.

Regulatory networks and 5' partner usage of miRNA host gene fusions in breast cancer

Genomic rearrangements in cancer cells can create gene fusions where the juxtaposition of two different genes leads to the production of chimeric proteins or altered gene expression through promoter‐swapping. We have previously shown that fusion transcripts involving microRNA (miRNA) host genes contribute to deregulation of miRNA expression regardless of the protein‐coding potential of these transcripts. Many different genes can also be used as 5′ partners by a miRNA host gene in what we named recurrent miRNA‐convergent fusions. Here, we have explored the properties of 5′ partners in fusion transcripts that involve miRNA hosts in breast tumours from The Cancer Genome Atlas (TCGA). We hypothesised that firstly, 5′ partner genes should belong to pathways and transcriptional programmes that reflect the tumour phenotype and secondly, there should be a selection for fusion events that shape miRNA expression to benefit the tumour cell through the known hallmarks of cancer. We found that the set of 5′ partners in miRNA host fusions is non‐random, with overrepresentation of highly expressed genes in pathways active in cancer including epithelial‐to‐mesenchymal transition, translational regulation and oestrogen signalling. Furthermore, many miRNAs were upregulated in samples with host gene fusions, including established oncogenic miRNAs such as mir‐21 and the mir‐106b~mir‐93~mir‐25 cluster. To the list of mechanisms for deregulation of miRNA expression, we have added fusion transcripts that change the promoter region. We propose that this adds material for genetic selection and tumour evolution in cancer cells and that miRNA host fusions can act as tumour ‘drivers’.

Hsa-miR-21-3p associates with breast cancer patient survival and targets genes in tumor suppressive pathways

Breast cancer is the cancer most often diagnosed in women. MicroRNAs (MIRs) are short RNA molecules that bind mRNA resulting in their downregulation. MIR21 has been shown to be an oncomiR in most cancer types, including breast cancer. Most of the effects of miR-21 have been attributed to hsa-miR-21-5p that is transcribed from the leading strand of MIR21, but hsa-miR-21-3p (miR-21-3p), transcribed from the lagging strand, is much less studied. The aim of the study is to analyze whether expression of miR-21-3p is prognostic for breast cancer. MiR-21-3p association with survival, clinical and pathological characteristics was analyzed in a large breast cancer cohort and validated in three separate cohorts, including TCGA and METABRIC. Analytical tools were also used to infer miR-21-3p function and to identify potential target genes and functional pathways. The results showed that in the exploration cohort, high miR-21-3p levels associated with shorter survival and lymph node positivity. In the three validation cohorts, high miR-21-3p levels associated with pathological characteristics that predict worse prognosis. Specifically, in the largest validation cohort, METABRIC (n = 1174), high miR-21-3p levels associated with large tumors, a high grade, lymph node and HER2 positivity, and shorter breast-cancer-specific survival (HR = 1.38, CI 1.13–1.68). This association remained significant after adjusting for confounding factors. The genes with expression levels that correlated with miR-21-3p were enriched in particular pathways, including the epithelial-to-mesenchymal transition and proliferation. Among the most significantly downregulated targets were MAT2A and the tumor suppressive genes STARD13 and ZNF132. The results from this study emphasize that both 3p- and 5p-arms from a MIR warrant independent study. The data show that miR-21-3p overexpression in breast tumors is a marker of worse breast cancer progression and it affects genes in pathways that drive breast cancer by down-regulating tumor suppressor genes. The results suggest miR-21-3p as a potential biomarker.

MiR-205 suppressed the malignant behaviors of breast cancer cells by targeting CLDN11 via modulation of the epithelial-to-mesenchymal transition

Some Aberrant expression of miRNAs plays an important role in the occurrence and distant metastasis of breast cancer. This study aimed to identify crucial miRNA signatures for breast cancer using microarray data from the Gene Expression Omnibus database, including ductal carcinoma in situ and invasive duct carcinoma. In this study, we founded that miR-205 was significantly down-regulated in breast cancer, and the low expression of miR-205 was significantly associated with the TNM stage of breast cancer. In vitro, functional studies revealed that over-expression of miR-205 inhibited the proliferation and promoted apoptosis of breast cancer cells MDA-MB-231. Mechanistically, claudin 11 (CLDN11) was found to be the direct target of miR-205; the function of miR-205 could be exerted via downregulation of the target gene CLDN11 in breast cancer cells. Furthermore, the over-expression of miR-205 promoted the expression of the epithelial marker E-cadherin but reduced the mesenchymal markers in breast cancer cells. These results collectively indicated the tumor-suppressive role of miR-205 in breast cancer by targeting CLDN11; implying miR-205 may serve as a novel therapeutic target for breast cancer.

miRNA as promising theragnostic biomarkers for predicting radioresistance in cancer: A systematic review and meta-analysis

Radioresistance remains as an obstacle in cancer treatment. This systematic review and meta-analysis aimed to evaluate the association between the expression of miRNAs and responses to radiotherapy and the prognosis of different tumors. In total, 77 miRNAs in 19 cancer types were studied, in which 24 miRNAs were upregulated and 58 miRNAs were downregulated in cancer patients. Five miRNAs were differentially expressed. Moreover, 75 miRNAs were found to be related to radioresistance, while 5 were observed to be related to radiosensitivity. The pooled HR and 95 % confidence interval for the combined studies was 1.135 (0.819-1.574; P-value = 0.4). The HR values of the subgroup analysis for miR-21 (HR = 2.344; 95 % CI: 1.927-2.850; P-value = 0.000), nasopharyngeal carcinoma (HR = 0.448; 95 % CI: 0.265-0.760; P = 0.003) and breast cancer (HR = 1.131; 95 % CI: 0.311-4.109; P = .85) were obtained. Our results highlighted that across the published literature, miRNAs can modulate tumor radioresistance or sensitivity by affecting radiation-related signaling pathways. It seems that miRNAs could be considered as a theragnostic biomarker to predict and monitor clinical response to radiotherapy. Thus, the prediction of radioresistance in malignant patients will improve radiotherapy outcomes and radiotherapeutic resistance.

The mutational landscape of the SCAN-B real-world primary breast cancer transcriptome

Breast cancer is a disease of genomic alterations, of which the panorama of somatic mutations and how these relate to subtypes and therapy response is incompletely understood. Within SCAN‐B (ClinicalTrials.gov: NCT02306096), a prospective study elucidating the transcriptomic profiles for thousands of breast cancers, we developed a RNA‐seq pipeline for detection of SNVs/indels and profiled a real‐world cohort of 3,217 breast tumors. We describe the mutational landscape of primary breast cancer viewed through the transcriptome of a large population‐based cohort and relate it to patient survival. We demonstrate that RNA‐seq can be used to call mutations in genes such as PIK3CA,TP53, and ERBB2, as well as the status of molecular pathways and mutational burden, and identify potentially druggable mutations in 86.8% of tumors. To make this rich dataset available for the research community, we developed an open source web application, the SCAN‐B MutationExplorer (http://oncogenomics.bmc.lu.se/MutationExplorer). These results add another dimension to the use of RNA‐seq as a clinical tool, where both gene expression‐ and mutation‐based biomarkers can be interrogated in real‐time within 1 week of tumor sampling.

Non-coding RNAs in cancers with chromosomal rearrangements: the signatures, causes, functions and implications

Chromosomal translocation leads to the juxtaposition of two otherwise separate DNA loci, which could result in gene fusion. These rearrangements at the DNA level are catastrophic events and often have causal roles in tumorigenesis. The oncogenic DNA messages are transferred to RNA molecules, which are in most cases translated into cancerous fusion proteins. Gene expression programs and signaling pathways are altered in these cytogenetically abnormal contexts. Notably, non-coding RNAs have attracted increasing attention and are believed to be tightly associated with chromosome-rearranged cancers. These RNAs not only function as modulators in downstream pathways but also directly affect chromosomal translocation or the associated products. This review summarizes recent research advances on the relationship between non-coding RNAs and chromosomal translocations and on diverse functions of non-coding RNAs in cancers with chromosomal rearrangements.

Analysis of fusion transcripts indicates widespread deregulation of snoRNAs and their host genes in breast cancer

Genomic rearrangements in cancer can join the sequences of two separate genes. Studies of such gene fusion events have mainly focused on identification of fusion proteins from the chimeric transcripts. We have previously investigated how fusions instead can affect the expression of intronic microRNA (miRNA) genes that are encoded within fusion gene partners. Here, we extend our analysis to small nucleolar RNAs (snoRNAs) that also are embedded within protein-coding or noncoding host genes. We found that snoRNA hosts are selectively enriched in fusion transcripts, like miRNA host genes, and that this enrichment is associated with all snoRNA classes. These structural changes may have functional consequences for the cell; proteins involved in the protein translation machinery are overrepresented among snoRNA host genes, a gene architecture assumed to be needed for closely coordinated expression of snoRNAs and host proteins. Our data indicate that this structure is frequently disrupted in cancer. We furthermore observed that snoRNA genes involved in fusions tend to associate with stronger promoters than the natural host, suggesting a mechanism that selects for snoRNA overexpression. In summary, we highlight a previously unexplored frequent structural change in cancer that affects important components of cellular physiology.

AAV-Anti-miR-214 Prevents Collapse of the Femoral Head in Osteonecrosis by Regulating Osteoblast and Osteoclast Activities

Osteonecrosis of the femoral head, an intractable but common disease that eventually triggers collapse of the femoral head, is characterized by increased osteoclast activity and markedly decreased osteoblast activity in the necrotic region of the femoral head. MicroRNA (miRNA)-214 (miR-214) may play important roles in vertebrate skeletal development by inhibiting osteoblast function by targeting activating transcription factor 4 (ATF4) and promoting osteoclast function via phosphatase and tensin homolog (PTEN). This study revealed significantly increased levels of miR-214 in necrotic regions, with commensurate changes in the numbers of its target cells (both osteoblasts and osteoclasts). To investigate whether targeting miR-214 could prevent femoral head collapse, we constructed an adeno-associated virus (AAV)-associated anti-miR-214 (AAV-anti-miR-214) and evaluated its function in vivo. AAV-anti-miR-214 promoted osteoblast activity and diminished osteoclast activity, effectively preventing collapse of the femoral head in a rat model of osteonecrosis.

High expression of the vacuole membrane protein 1 (VMP1) is a potential marker of poor prognosis in HER2 positive breast cancer

Background

Fusion genes result from genomic structural changes, which can lead to alterations in gene expression that supports tumor development. The aim of the study was to use fusion genes as a tool to identify new breast cancer (BC) genes with a role in BC progression.

Methods

Fusion genes from breast tumors and BC cell lines were collected from publications. RNA-Seq data from tumors and cell lines were retrieved from databanks and analyzed for fusions with SOAPfuse or the analysis was purchased. Fusion genes identified in both tumors (n = 1724) and cell lines (n = 45) were confirmed by qRT-PCR and sequencing. Their individual genes were ranked by selection criteria that included correlation of their mRNA level with copy number. The expression of the top ranked gene was measured by qRT-PCR in normal tissue and in breast tumors from an exploratory cohort (n = 141) and a validation cohort (n = 277). Expression levels were correlated with clinical and pathological factors as well as the patients’ survival. The results were followed up in BC cohorts from TCGA (n = 818) and METABRIC (n = 2509).

Results

Vacuole membrane protein 1 (VMP1) was the most promising candidate based on specific selection criteria. Its expression was higher in breast tumor tissue than normal tissue (p = 1x10^-4), and its expression was significantly higher in HER2 positive than HER2 negative breast tumors in all four cohorts analyzed. High expression of VMP1 associated with breast cancer specific survival (BCSS) in cohort 1 (hazard ratio (HR) = 2.31, CI 1.27–4.18) and METABRIC (HR = 1.26, CI 1.02–1.57), and also after adjusting for HER2 expression in cohort 1 (HR = 2.03, CI 1.10–3.72). BCSS was not significant in cohort 2 or TCGA cohort, which may be due to differences in treatment regimens.

Conclusions

The results suggest that high VMP1 expression is a potential marker of poor prognosis in HER2 positive BC. Further studies are needed to elucidate how VMP1 could affect pathways supportive of tumorigenesis.

Refinement of breast cancer molecular classification by miRNA expression profiles

Background

Accurate classification of breast cancer using gene expression profiles has contributed to a better understanding of the biological mechanisms behind the disease and has paved the way for better prognostication and treatment prediction.

Results

We found that miRNA profiles largely recapitulate intrinsic subtypes. In the case of HER2-enriched tumors a small set of miRNAs including the HER2-encoded mir-4728 identifies the group with very high specificity. We also identified differential expression of the miR-99a/let-7c/miR-125b miRNA cluster as a marker for separation of the Luminal A and B subtypes. High expression of this miRNA cluster is linked to better overall survival among patients with Luminal A tumors. Correlation between the miRNA cluster and their precursor LINC00478 is highly significant suggesting that its expression could help improve the accuracy of present day’s signatures.

Conclusions

We show here that miRNA expression can be translated into mRNA profiles and that the inclusion of miRNA information facilitates the molecular diagnosis of specific subtypes, in particular the clinically relevant sub-classification of luminal tumors.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-5887-7) contains supplementary material, which is available to authorized users.

Genome-wide miRNA methylome analysis in oral cancer: possible biomarkers associated with patient survival

AIM

The methylome associated with miRNA loci was investigated in oral cancer to explore tobacco specific methylation and potential biomarkers for patient survival.

METHODS

Methylome data was generated from 16 pairs of cancer-normal tissues by reduced representation bisulfite sequencing method. Differentially methylated regions were identified using the DMAP pipeline. In silico validation and Kaplan-Meier survival analyses were performed on The Cancer Genome Atlas data based on our miRNA methylome data.

RESULTS

A total of 4310 unique differentially methylated regions, mapping to 144 miRNA loci, were identified. Three distinct groups of miRNAs were differentially methylated in cancer tissues from smokers, chewers and mixed habitués. Hypermethylation of miR-503, miR-200a/b, miR-320b and miR-489 was associated with worse 5-year survival.

CONCLUSION

Differential methylation patterns in miRNA loci are associated with poor survival underscoring their potential as predictive and prognostic biomarkers in oral cancer.

Prognostic implications of decreased microRNA-101-3p expression in patients with non-small cell lung cancer

To investigate the expression level of microRNA-101-3p (miR-101-3p) and its possible association with progression, prognosis and chemotherapy in patients with non-small cell lung cancer (NSCLC), the Gene Expression Omnibus (GEO) database was used. Quantitative polymerase chain reaction was used to verify the expression in 327 NSCLC and 42 adjacent normal lung tissues, of which 42 viable tissues were paired with nearby normal lung tissues. Based on the Cox regression model, univariate and multivariate analyses were used to address the factors that had effects on overall survival (OS) and disease-free survival (DFS) rate. Data from the GEO database demonstrated that the miR-101-3p expression in NSCLC was downregulated, compared with normal lung cancer. Survival analysis through univariate and multivariate models indicated that the miR-101-3p expression level was a crucial risk factor for OS and DFS in patients with NSCLC. A number of clinical parameters were determined to be associated with miR-101-3p expression, including tumor diameter, lymph node metastasis and tumor-node-metastasis stage. Adjuvant chemotherapy with high expression of miR-101-3p was determined to increase OS and DFS in patients with NSCLC, compared with patients with de novo or low expression of miR-101-3p. The present results demonstrated that miR-101-3p expression levels were associated with NSCLC progression and prognosis, which indicated that miR-101-3p may serve as a biomarker for patients with NSCLC who have received adjuvant chemotherapy.

Synstable Fusion: A Network-Based Algorithm for Estimating Driver Genes in Fusion Structures

Gene fusion structure is a class of common somatic mutational events in cancer genomes, which are often formed by chromosomal mutations. Identifying the driver gene(s) in a fusion structure is important for many downstream analyses and it contributes to clinical practices. Existing computational approaches have prioritized the importance of oncogenes by incorporating prior knowledge from gene networks. However, different methods sometimes suffer different weaknesses when handling gene fusion data due to multiple issues such as fusion gene representation, network integration, and the effectiveness of the evaluation algorithms. In this paper, Synstable Fusion (SYN), an algorithm for computationally evaluating the fusion genes, is proposed. This algorithm uses network-based strategy by incorporating gene networks as prior information, but estimates the driver genes according to the destructiveness hypothesis. This hypothesis balances the two popular evaluation strategies in the existing studies, thereby providing more comprehensive results. A machine learning framework is introduced to integrate multiple networks and further solve the conflicting results from different networks. In addition, a synchronous stability model is established to reduce the computational complexity of the evaluation algorithm. To evaluate the proposed algorithm, we conduct a series of experiments on both artificial and real datasets. The results demonstrate that the proposed algorithm performs well on different configurations and is robust when altering the internal parameter settings.

Co-fuse: a new class discovery analysis tool to identify and prioritize recurrent fusion genes from RNA-sequencing data

Recurrent oncogenic fusion genes play a critical role in the development of various cancers and diseases and provide, in some cases, excellent therapeutic targets. To date, analysis tools that can identify and compare recurrent fusion genes across multiple samples have not been available to researchers. To address this deficiency, we developed Co-occurrence Fusion (Co-fuse), a new and easy to use software tool that enables biologists to merge RNA-seq information, allowing them to identify recurrent fusion genes, without the need for exhaustive data processing. Notably, Co-fuse is based on pattern mining and statistical analysis which enables the identification of hidden patterns of recurrent fusion genes. In this report, we show that Co-fuse can be used to identify 2 distinct groups within a set of 49 leukemic cell lines based on their recurrent fusion genes: a multiple myeloma (MM) samples-enriched cluster and an acute myeloid leukemia (AML) samples-enriched cluster. Our experimental results further demonstrate that Co-fuse can identify known driver fusion genes (e.g., IGH-MYC, IGH-WHSC1) in MM, when compared to AML samples, indicating the potential of Co-fuse to aid the discovery of yet unknown driver fusion genes through cohort comparisons. Additionally, using a 272 primary glioma sample RNA-seq dataset, Co-fuse was able to validate recurrent fusion genes, further demonstrating the power of this analysis tool to identify recurrent fusion genes. Taken together, Co-fuse is a powerful new analysis tool that can be readily applied to large RNA-seq datasets, and may lead to the discovery of new disease subgroups and potentially new driver genes, for which, targeted therapies could be developed. The Co-fuse R source code is publicly available at https://github.com/sakrapee/co-fuse .

miRNA-convergent gene fusions

In a recent study published in Nature Communications, we showed that intron-encoded microRNA genes (miRNA) are frequent partners of fusion genes in the cancer genome. Analyzed from a functional rather than structural perspective, these rearrangements represent a new class of fusions we called "miRNA-convergent fusions".