Genomic hallmarks and therapeutic targets of ribosome biogenesis in cancer.

Hyperactive ribosome biogenesis (RiboSis) fuels unrestricted cell proliferation, whereas genomic hallmarks and therapeutic targets of RiboSis in cancers remain elusive, and efficient approaches to quantify RiboSis activity are still limited. Here, we have established an in silico approach to conveniently score RiboSis activity based on individual transcriptome data. By employing this novel approach and RNA-seq data of 14 645 samples from TCGA/GTEx dataset and 917 294 single-cell expression profiles across 13 cancer types, we observed the elevated activity of RiboSis in malignant cells of various human cancers, and high risk of severe outcomes in patients with high RiboSis activity. Our mining of pan-cancer multi-omics data characterized numerous molecular alterations of RiboSis, and unveiled the predominant somatic alteration in RiboSis genes was copy number variation. A total of 128 RiboSis genes, including EXOSC4, BOP1, RPLP0P6 and UTP23, were identified as potential therapeutic targets. Interestingly, we observed that the activity of RiboSis was associated with TP53 mutations, and hyperactive RiboSis was associated with poor outcomes in lung cancer patients without TP53 mutations, highlighting the importance of considering TP53 mutations during therapy by impairing RiboSis. Moreover, we predicted 23 compounds, including methotrexate and CX-5461, associated with the expression signature of RiboSis genes. The current study generates a comprehensive blueprint of molecular alterations in RiboSis genes across cancers, which provides a valuable resource for RiboSis-based anti-tumor therapy.

Risk modeling of single-cell transcriptomes reveals the heterogeneity of immune infiltration in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is one of the most common primary hepatic malignancies. E2F transcription factors play an important role in the tumorigenesis and progression of HCC, mainly through the RB/E2F pathway. Prognostic models for HCC based on gene signatures have been developed rapidly in recent years; however, their discriminating ability at the single-cell level remains elusive, which could reflect the underlying mechanisms driving the sample bifurcation. In this study, we constructed and validated a predictive model based on E2F expression, successfully stratifying patients with HCC into two groups with different survival risks. Then we used a single-cell dataset to test the discriminating ability of the predictive model on infiltrating T cells, demonstrating remarkable cellular heterogeneity as well as altered cell fates. We identified distinct cell subpopulations with diverse molecular characteristics. We also found that the distribution of cell subpopulations varied considerably across onset stages among patients, providing a fundamental basis for patient-oriented precision evaluation. Moreover, single-sample gene set enrichment analysis revealed that subsets of CD8+ T cells with significantly different cell adhesion levels could be associated with different patterns of tumor cell dissemination. Therefore, our findings linked the conventional prognostic gene signature to the immune microenvironment and cellular heterogeneity at the single-cell level, thus providing deeper insights into the understanding of HCC tumorigenesis.

An updated overview of experimental and computational approaches to identify non-canonical DNA/RNA structures with emphasis on G-quadruplexes and R-loops.

Multiple types of non-canonical nucleic acid structures play essential roles in DNA recombination and replication, transcription, and genomic instability and have been associated with several human diseases. Thus, an increasing number of experimental and bioinformatics methods have been developed to identify these structures. To date, most reviews have focused on the features of non-canonical DNA/RNA structure formation, experimental approaches to mapping these structures, and the association of these structures with diseases. In addition, two reviews of computational algorithms for the prediction of non-canonical nucleic acid structures have been published. One of these reviews focused only on computational approaches for G4 detection until 2020. The other mainly summarized the computational tools for predicting cruciform, H-DNA and Z-DNA, in which the algorithms discussed were published before 2012. Since then, several experimental and computational methods have been developed. However, a systematic review including the conformation, sequencing mapping methods and computational prediction strategies for these structures has not yet been published. The purpose of this review is to provide an updated overview of conformation, current sequencing technologies and computational identification methods for non-canonical nucleic acid structures, as well as their strengths and weaknesses. We expect that this review will aid in understanding how these structures are characterised and how they contribute to related biological processes and diseases.

Comprehensive evaluation of computational methods for predicting cancer driver genes.

Optimal methods could effectively improve the accuracy of predicting and identifying candidate driver genes. Various computational methods based on mutational frequency, network and function approaches have been developed to identify mutation driver genes in cancer genomes. However, a comprehensive evaluation of the performance levels of network-, function- and frequency-based methods is lacking. In the present study, we assessed and compared eight performance criteria for eight network-based, one function-based and three frequency-based algorithms using eight benchmark datasets. Under different conditions, the performance of approaches varied in terms of network, measurement and sample size. The frequency-based driverMAPS and network-based HotNet2 methods showed the best overall performance. Network-based algorithms using protein-protein interaction networks outperformed the function- and the frequency-based approaches. Precision, F1 score and Matthews correlation coefficient were low for most approaches. Thus, most of these algorithms require stringent cutoffs to correctly distinguish driver and non-driver genes. We constructed a website named Cancer Driver Catalog (http://159.226.67.237/sun/cancer_driver/), wherein we integrated the gene scores predicted by the foregoing software programs. This resource provides valuable guidance for cancer researchers and clinical oncologists prioritizing cancer driver gene candidates by using an optimal tool.

A new approach to decode DNA methylome and genomic variants simultaneously from double strand bisulfite sequencing.

Genetic and epigenetic contributions to various diseases and biological processes have been well-recognized. However, simultaneous identification of single-nucleotide variants (SNVs) and DNA methylation levels from traditional bisulfite sequencing data is still challenging. Here, we develop double strand bisulfite sequencing (DSBS) for genome-wide accurate identification of SNVs and DNA methylation simultaneously at a single-base resolution by using one dataset. Locking Watson and Crick strand together by hairpin adapter followed by bisulfite treatment and massive parallel sequencing, DSBS simultaneously sequences the bisulfite-converted Watson and Crick strand in one paired-end read, eliminating the strand bias of bisulfite sequencing data. Mutual correction of read1 and read2 can estimate the amplification and sequencing errors, and enables our developed computational pipeline, DSBS Analyzer (https://github.com/tianguolangzi/DSBS), to accurately identify SNV and DNA methylation. Additionally, using DSBS, we provide a genome-wide hemimethylation landscape in the human cells, and reveal that the density of DNA hemimethylation sites in promoter region and CpG island is lower than that in other genomic regions. The cost-effective new approach, which decodes DNA methylome and genomic variants simultaneously, will facilitate more comprehensive studies on numerous diseases and biological processes driven by both genetic and epigenetic variations.

OncoVar: an integrated database and analysis platform for oncogenic driver variants in cancers.

The prevalence of neutral mutations in cancer cell population impedes the distinguishing of cancer-causing driver mutations from passenger mutations. To systematically prioritize the oncogenic ability of somatic mutations and cancer genes, we constructed a useful platform, OncoVar (https://oncovar.org/), which employed published bioinformatics algorithms and incorporated known driver events to identify driver mutations and driver genes. We identified 20 162 cancer driver mutations, 814 driver genes and 2360 pathogenic pathways with high-confidence by reanalyzing 10 769 exomes from 33 cancer types in The Cancer Genome Atlas (TCGA) and 1942 genomes from 18 cancer types in International Cancer Genome Consortium (ICGC). OncoVar provides four points of view, 'Mutation', 'Gene', 'Pathway' and 'Cancer', to help researchers to visualize the relationships between cancers and driver variants. Importantly, identification of actionable driver alterations provides promising druggable targets and repurposing opportunities of combinational therapies. OncoVar provides a user-friendly interface for browsing, searching and downloading somatic driver mutations, driver genes and pathogenic pathways in various cancer types. This platform will facilitate the identification of cancer drivers across individual cancer cohorts and helps to rank mutations or genes for better decision-making among clinical oncologists, cancer researchers and the broad scientific community interested in cancer precision medicine.

Retrospective Study of Vascular Complications Caused by Hyaluronic Acid Injection.

BACKGROUND: Complications from intravascular embolization of hyaluronic acid (HA) are not only no longer uncommon but also devastating. This study aimed to examine clinical aspects of patients referred to our hospital for care following complications from intravascular filler embolization. METHODS: We retrospectively reviewed data from all patients referred to our medical center for the management of complications associated with intravascular embolization of HA fillers including demographics, medical history, clinical features, and treatment between November 2013 and June 2022. RESULTS: A total of 116 patients with vascular complications (27 cases with vision loss and 89 cases with skin necrosis) were assessed. The highest risk injection sites for skin necrosis included the nasal region (58/115, 50.4%), temple (16/115, 13.9%), and forehead (11/115, 9.6%) and for vision loss included the nasal region (18/30, 60.0%) and forehead (7/30, 23.3%). In skin necrosis cases, a needle (60/89, 67.4%) carried a higher risk than that of a cannula (29/89, 32.6%), whereas in vision loss cases, nasal dorsum injections using a cannula (16/27, 59.3%) carried a higher risk than that observed using a needle (11/27, 40.7%). No treatment was completely successful in reversing these complications. CONCLUSION: Intravascular embolization of HA filler is a serious complication. Although some combination treatments have been proposed, there is no standard protocol for treating severe complications. LEVEL OF EVIDENCE III: This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors http://www.springer.com/00266 .

Prevalence and architecture of posttranscriptionally impaired synonymous mutations in 8,320 genomes across 22 cancer types.

Somatic synonymous mutations are one of the most frequent genetic variants occurring in the coding region of cancer genomes, while their contributions to cancer development remain largely unknown. To assess whether synonymous mutations involved in post-transcriptional regulation contribute to the genetic etiology of cancers, we collected whole exome data from 8,320 patients across 22 cancer types. By employing our developed algorithm, PIVar, we identified a total of 22,948 posttranscriptionally impaired synonymous SNVs (pisSNVs) spanning 2,042 genes. In addition, 35 RNA binding proteins impacted by these identified pisSNVs were significantly enriched. Remarkably, we discovered markedly elevated ratio of somatic pisSNVs across all 22 cancer types, and a high pisSNV ratio was associated with worse patient survival in five cancer types. Intriguing, several well-established cancer genes, including PTEN, RB1 and PIK3CA, appeared to contribute to tumorigenesis at both protein function and posttranscriptional regulation levels, whereas some pisSNV-hosted genes, including UBR4, EP400 and INTS1, exerted their function during carcinogenesis mainly via posttranscriptional mechanisms. Moreover, we predicted three drugs associated with two pisSNVs, and numerous compounds associated with expression signature of pisSNV-hosted genes. Our study reveals the prevalence and clinical relevance of pisSNVs in cancers, and emphasizes the importance of considering posttranscriptional impaired synonymous mutations in cancer biology.

A comparative study of the genetic components of three subcategories of autism spectrum disorder.

The fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) controversially combined previously distinct subcategories of autism spectrum disorder (ASD) into a single diagnostic category. However, genetic convergences and divergences between different ASD subcategories are unclear. By retrieving 1725 exonic de novo mutations (DNMs) from 1628 subjects with autistic disorder (AD), 1873 from 1564 subjects with pervasive developmental disorder not otherwise specified (PDD-NOS), 276 from 247 subjects with Asperger's syndrome (AS), and 2077 from 2299 controls, we found that rates of putative functional DNMs (loss-of-function, predicted deleterious missense, and frameshift) in all three subcategories were significantly higher than those in control. We then investigated the convergences and divergences of the three ASD subcategories based on four genetic aspects: whether any two ASD subcategories (1) shared significantly more genes with functional DNMs, (2) exhibited similar spatio-temporal expression patterns, (3) shared significantly more candidate genes, and (4) shared some ASD-associated functional pathways. It is revealed that AD and PDD-NOS were broadly convergent in terms of all four genetic aspects, suggesting these two ASD subcategories may be genetically combined. AS was divergent to AD and PDD-NOS for aspects of functional DNMs and expression patterns, whereas AS and AD/PDD-NOS were convergent for aspects of candidate genes and functional pathways. Our results indicated that the three ASD subcategories present more genetic convergences than divergences, favouring DSM-5's new classification. This study suggests that specifically defined genotypes and their corresponding phenotypes should be integrated analyzed for precise diagnosis of complex disorders, such as ASD.

Improvement of Surgical Scars by Early Intervention With Carbon Dioxide Fractional Laser.

BACKGROUND AND OBJECTIVES: Laser therapy during the early stage of wound healing can reduce surgical scar formation. Previous clinical trials showed that ablative fractional laser (AFL) therapy might have achieved the best outcomes; however, there was no consensus on the laser therapy protocol. The current study investigated the efficacy of early intervention with carbon dioxide FL (CO2 FL) in reducing the surgical scars in patients of all age groups to understand the effects of specific intervention timing, light dose, number of treatments, treatment interval on the therapeutic outcome, and side effects. STUDY DESIGN/MATERIALS AND METHODS: Within 1 week after suture removal, 18 patients received low-energy CO2 FL therapy on their incisional wounds from facial or neck surgery. The treatments were performed once every 3 months for 1-3 sessions. After the surgical treatment, we applied a topical gel that contained recombinant human epidermal growth factor (EGF) on the incisional wounds to facilitate wound healing. The outcomes were evaluated by the Vancouver Scar Scale (VSS) and a satisfaction survey (the quartile grading scale) before and 3 months after completing the therapy was conducted. During the same period, 15 patients who had not received any treatment for about one year after face and neck surgery were randomly selected as the untreated control group. RESULTS: In the treatment group, 18 patients had no obvious scar marks after the laser therapy. The satisfaction survey showed excellent outcomes in 16 (88.9%) patients and good outcomes in two (11.1%). After treatment, the average VSS scale and satisfaction score of the treatment group were 1.11 and 3.89, respectively; while the average VSS scale of the control group was 3.07 and the satisfaction score was 1.93. There were significant differences in VSS scale and satisfaction score between the treatment group and the control group (P < 0.01). No adverse effects were observed. CONCLUSIONS: Early intervention with CO2 FL on surgical wounds achieved satisfactory outcomes in improving the surgical scars. Lasers Surg. Med. © 2019 Wiley Periodicals, Inc.

Performance evaluation of pathogenicity-computation methods for missense variants.

With expanding applications of next-generation sequencing in medical genetics, increasing computational methods are being developed to predict the pathogenicity of missense variants. Selecting optimal methods can accelerate the identification of candidate genes. However, the performances of different computational methods under various conditions have not been completely evaluated. Here, we compared 12 performance measures of 23 methods based on three independent benchmark datasets: (i) clinical variants from the ClinVar database related to genetic diseases, (ii) somatic variants from the IARC TP53 and ICGC databases related to human cancers and (iii) experimentally evaluated PPARG variants. Some methods showed different performances under different conditions, suggesting that they were not always applicable for different conditions. Furthermore, the specificities were lower than the sensitivities for most methods (especially, for the experimentally evaluated benchmark datasets), suggesting that more rigorous cutoff values are necessary to distinguish pathogenic variants. Furthermore, REVEL, VEST3 and the combination of both methods (i.e. ReVe) showed the best overall performances with all the benchmark data. Finally, we evaluated the performances of these methods with de novo mutations, finding that ReVe consistently showed the best performance. We have summarized the performances of different methods under various conditions, providing tentative guidance for optimal tool selection.

EpiDenovo: a platform for linking regulatory de novo mutations to developmental epigenetics and diseases.

De novo mutations (DNMs) have been shown to be a major cause of severe early-onset genetic disorders such as autism spectrum disorder and intellectual disability. Over one million DNMs have been identified in developmental disorders by next generation sequencing, but linking these DNMs to the genes that they impact remains a challenge, as the majority of them are embedded in non-coding regions. As most developmental diseases occur in the early stages of development or during childhood, it is crucial to clarify the details of epigenetic regulation in early development in order to interpret the mechanisms underlying developmental disorders. Here, we develop EpiDenovo, a database that is freely available at http://www.epidenovo.biols.ac.cn/, and which provides the associations between embryonic epigenomes and DNMs in developmental disorders, including several neuropsychiatric disorders and congenital heart disease. EpiDenovo provides an easy-to-use web interface allowing users rapidly to find the epigenetic signatures of DNMs and the expression patterns of the genes that they regulate during embryonic development. In summary, EpiDenovo is a useful resource for selecting candidate genes for further functional studies in embryonic development, and for investigating regulatory DNMs as well as other genetic variants causing or underlying developmental disorders.

VarCards: an integrated genetic and clinical database for coding variants in the human genome.

A growing number of genomic tools and databases were developed to facilitate the interpretation of genomic variants, particularly in coding regions. However, these tools are separately available in different online websites or databases, making it challenging for general clinicians, geneticists and biologists to obtain the first-hand information regarding some particular variants and genes of interest. Starting with coding regions and splice sties, we artificially generated all possible single nucleotide variants (n = 110 154 363) and cataloged all reported insertion and deletions (n = 1 223 370). We then annotated these variants with respect to functional consequences from more than 60 genomic data sources to develop a database, named VarCards (http://varcards.biols.ac.cn/), by which users can conveniently search, browse and annotate the variant- and gene-level implications of given variants, including the following information: (i) functional effects; (ii) functional consequences through different in silico algorithms; (iii) allele frequencies in different populations; (iv) disease- and phenotype-related knowledge; (v) general meaningful gene-level information; and (vi) drug-gene interactions. As a case study, we successfully employed VarCards in interpretation of de novo mutations in autism spectrum disorders. In conclusion, VarCards provides an intuitive interface of necessary information for researchers to prioritize candidate variations and genes.

CirGRDB: a database for the genome-wide deciphering circadian genes and regulators.

Circadian rhythms govern various kinds of physiological and behavioral functions of the living organisms, and disruptions of the rhythms are highly detrimental to health. Although several databases have been built for circadian genes, a resource for comprehensive post-transcriptional regulatory information of circadian RNAs and expression patterns of disease-related circadian RNAs is still lacking. Here, we developed CirGRDB (http://cirgrdb.biols.ac.cn) by integrating more than 4936 genome-wide assays, with the aim of fulfilling the growing need to understand the rhythms of life. CirGRDB presents a friendly web interface that allows users to search and browse temporal expression patterns of interested genes in 37 human/mouse tissues or cell lines, and three clinical disorders including sleep disorder, aging and tumor. More importantly, eight kinds of potential transcriptional and post-transcriptional regulators involved in the rhythmic expression of the specific genes, including transcription factors, histone modifications, chromatin accessibility, enhancer RNAs, miRNAs, RNA-binding proteins, RNA editing and RNA methylation, can also be retrieved. Furthermore, a regulatory network could be generated based on the regulatory information. In summary, CirGRDB offers a useful repository for exploring disease-related circadian RNAs, and deciphering the transcriptional and post-transcriptional regulation of circadian rhythms.

The Relationships Between Stress, Mental Disorders, and Epigenetic Regulation of BDNF.

Brain-derived neurotrophic factor (BDNF), a critical member of the neurotrophic family, plays an important role in multiple stress-related mental disorders. Although alterations in BDNF in multiple brain regions of individuals experiencing stress have been demonstrated in previous studies, it appears that a set of elements are involved in the complex regulation. In this review, we summarize the specific brain regions with altered BDNF expression during stress exposure. How various environmental factors, including both physical and psychological stress, affect the expression of BDNF in specific brain regions are further summarized. Moreover, epigenetic regulation of BDNF, including DNA methylation, histone modification, and noncoding RNA, in response to diverse types of stress, as well as sex differences in the sensitivity of BDNF to the stress response, is also summarized. Clarification of the underlying role of BDNF in the stress process will promote our understanding of the pathology of stress-linked mental disorders and provide a potent target for the future treatment of stress-related illness.

Population Genomics Reveals Speciation and Introgression between Brown Norway Rats and Their Sibling Species.

Murine rodents are excellent models for study of adaptive radiations and speciation. Brown Norway rats (Rattus norvegicus) are successful global colonizers and the contributions of their domesticated laboratory strains to biomedical research are well established. To identify nucleotide-based speciation timing of the rat and genomic information contributing to its colonization capabilities, we analyzed 51 whole-genome sequences of wild-derived Brown Norway rats and their sibling species, R. nitidus, and identified over 20 million genetic variants in the wild Brown Norway rats that were absent in the laboratory strains, which substantially expand the reservoir of rat genetic diversity. We showed that divergence of the rat and its siblings coincided with drastic climatic changes that occurred during the Middle Pleistocene. Further, we revealed that there was a geographically widespread influx of genes between Brown Norway rats and the sibling species following the divergence, resulting in numerous introgressed regions in the genomes of admixed Brown Norway rats. Intriguing, genes related to chemical communications among these introgressed regions appeared to contribute to the population-specific adaptations of the admixed Brown Norway rats. Our data reveals evolutionary history of the Brown Norway rat, and offers new insights into the role of climatic changes in speciation of animals and the effect of interspecies introgression on animal adaptation.

Chronic exposure to air pollution particles increases the risk of obesity and metabolic syndrome: findings from a natural experiment in Beijing.

Epidemiologic evidence suggests that air pollution is a risk factor for childhood obesity. Limited experimental data have shown that early-life exposure to ambient particles either increases susceptibility to diet-induced weight gain in adulthood or increases insulin resistance, adiposity, and inflammation. However, no data have directly supported a link between air pollution and non-diet-induced weight increases. In a rodent model, we found that breathing Beijing's highly polluted air resulted in weight gain and cardiorespiratory and metabolic dysfunction. Compared to those exposed to filtered air, pregnant rats exposed to unfiltered Beijing air were significantly heavier at the end of pregnancy. At 8 wk old, the offspring prenatally and postnatally exposed to unfiltered air were significantly heavier than those exposed to filtered air. In both rat dams and their offspring, after continuous exposure to unfiltered air we observed pronounced histologic evidence for both perivascular and peribronchial inflammation in the lungs, increased tissue and systemic oxidative stress, dyslipidemia, and an enhanced proinflammatory status of epididymal fat. Results suggest that TLR2/4-dependent inflammatory activation and lipid oxidation in the lung can spill over systemically, leading to metabolic dysfunction and weight gain.-Wei, Y., Zhang, J., Li, Z., Gow, A., Chung, K. F., Hu, M., Sun, Z., Zeng, L., Zhu, T., Jia, G., Li, X., Duarte, M., Tang, X. Chronic exposure to air pollution particles increases the risk of obesity and metabolic syndrome: findings from a natural experiment in Beijing.

Efficacy of Retrobulbar Hyaluronidase Injection for Vision Loss Resulting from Hyaluronic Acid Filler Embolization.

BACKGROUND: Vision loss is a rare but serious complication of facial hyaluronic acid (HA) filler injection, for which there is no proven rescue therapy. Retrobulbar hyaluronidase injection is advocated by many plastic surgeons as an emergency treatment, but has not been carefully assessed for its efficacy. OBJECTIVES: To evaluate the efficacy of retrobulbar hyaluronidase injection as a rescue treatment for vision loss caused by HA filler embolization. METHODS: Patients with vision loss caused by HA filler embolization were treated with retrobulbar hyaluronidase injection. Their visual acuity and fundoscopic images before and after treatment were analyzed for efficacy assessment. RESULTS: One patient with branch retinal artery occlusion (BRAO), one patient with posterior ischemic optic neuropathy (PION), one patient with ophthalmic artery occlusion, and one patient with both BRAO and PION were treated with one or two retrobulbar injections of 1500 or 3000 units hyaluronidase. No patients demonstrated substantial retinal artery recanalization or vision acuity improvement after treatment. CONCLUSIONS: One or two retrobulbar injections of 1500 to 3000 IU hyaluronidase are unable to recanalize retinal artery occlusion or improve the visual outcome of patients who presented with vision loss caused by HA filler embolization at least four hours after onset. LEVEL OF EVIDENCE: 4.

Promoter DNA methylation is associated with KLF11 expression in epithelial ovarian cancer.

As a transforming growth factor-ß (TGF-ß)-inducible gene, the expression of Krüppel-like transcription factor 11 (KLF11) is altered in several types of cancer. In the current study, through using human 9K CpG island array, KLF11 was identified as one of hypermethylated genes in RAS-transformed ovarian T29H cells. Methylation of the KLF11 promoter was also observed in ovarian cancer tissue samples accompanied by significantly reduced KLF11 gene expression. Interestingly, the expression of SMAD2, SMAD3, and SMAD7 genes was reduced in the tumour, whilst no change was found in TGF-ß expression. Our data suggest a relationship between promoter DNA methylation and KLF11 gene expression in ovarian cancer tumorigenesis.

An evaluation and recommendation of the optimal methodologies to detect RET gene rearrangements in papillary thyroid carcinoma.

To recommend a reliable and clinically realistic RET/PTC rearrangement detection assay for papillary thyroid carcinoma (PTC), we compared multiplex quantitative polymerase chain reaction (qPCR), fluorescence in situ hybridization (FISH), and immunohistochemistry (IHC). RET/PTC rearrangement was detected using either RET break-apart FISH followed by multicolor FISH to confirm CCDC6/RET or NCOA4/RET fusions, or by multiplex qPCR to detect 14 RET/PTC subtypes with simultaneous RET mRNA expression. RET protein expression was detected by IHC. The specificity and sensitivity of multiplex qPCR and IHC were calculated using break-apart FISH as a reference. Among 73 PTC patients with sufficient tissue available for FISH and multiplex qPCR, 10 cases were defined as RET/PTC positive by both assays, including eight CCDC6/RET and two NCOA4/RET fusions with relatively high RET mRNA. In addition, multiplex qPCR identified another two CCDC6/RET fusion positive cases, but with low RET mRNA expression. IHC staining identified 11 RET positive cases among 39 patients with available samples. In comparison to FISH, multiplex qPCR displayed 100% sensitivity and 97% specificity to detect RET/PTC fusions, while IHC was neither sensitive nor specific. Our data reveal that both multiplex qPCR and FISH assays are equally applicable for detection of RET/PTC rearrangements. Break-apart FISH methodology is highly recommended for the wider screening of RET rearrangements (regardless of partner genes), while multiplex qPCR is preferred to identify all known fusion types using one assay, provided mRNA expression is also measured. IHC analysis could potentially provide an additional method of fusion detection dependent on further optimization of assay conditions and scoring cutoffs.