PFN4 is required for manchette development and acrosome biogenesis during mouse spermiogenesis.

Profilin 4 (Pfn4) is expressed during spermiogenesis and localizes to the acrosome-acroplaxome-manchette complex. Here, we generated PFN4-deficient mice, with sperm displaying severe impairment in manchette formation. Interestingly, HOOK1 staining suggests that the perinuclear ring is established; however, ARL3 staining is disrupted, suggesting that lack of PFN4 does not interfere with the formation of the perinuclear ring and initial localization of HOOK1, but impedes microtubular organization of the manchette. Furthermore, amorphous head shape and flagellar defects were detected, resulting in reduced sperm motility. Disrupted cis- and trans-Golgi networks and aberrant production of proacrosomal vesicles caused impaired acrosome biogenesis. Proteomic analysis showed that the proteins ARF3, SPECC1L and FKBP1, which are involved in Golgi membrane trafficking and PI3K/AKT pathway, are more abundant in Pfn4-/- testes. Levels of PI3K, AKT and mTOR were elevated, whereas AMPK level was reduced, consistent with inhibition of autophagy. This seems to result in blockage of autophagic flux, which could explain the failure in acrosome formation. In vitro fertilization demonstrated that PFN4-deficient sperm is capable of fertilizing zona-free oocytes, suggesting a potential treatment for PFN4-related human infertility.

Nuclear Architecture Organized by Rif1 Underpins the Replication-Timing Program.

DNA replication is temporally and spatially organized in all eukaryotes, yet the molecular control and biological function of the replication-timing program are unclear. Rif1 is required for normal genome-wide regulation of replication timing, but its molecular function is poorly understood. Here we show that in mouse embryonic stem cells, Rif1 coats late-replicating domains and, with Lamin B1, identifies most of the late-replicating genome. Rif1 is an essential determinant of replication timing of non-Lamin B1-bound late domains. We further demonstrate that Rif1 defines and restricts the interactions between replication-timing domains during the G1 phase, thereby revealing a function of Rif1 as organizer of nuclear architecture. Rif1 loss affects both number and replication-timing specificity of the interactions between replication-timing domains. In addition, during the S phase, Rif1 ensures that replication of interacting domains is temporally coordinated. In summary, our study identifies Rif1 as the molecular link between nuclear architecture and replication-timing establishment in mammals.

A novel serum extracellular vesicle protein signature to monitor glioblastoma tumor progression.

Detection of tumor progression in patients with glioblastoma remains a major challenge. Extracellular vesicles (EVs) are potential biomarkers and can be detected in the blood of patients with glioblastoma. In our study, we evaluated the potential of serum-derived EVs from glioblastoma patients to serve as biomarker for tumor progression. EVs from serum of glioblastoma patients and healthy volunteers were separated by size exclusion chromatography and ultracentrifugation. EV markers were defined by using a proximity-extension assay and bead-based flow cytometry. Tumor progression was defined according to modified RANO criteria. EVs from the serum of glioblastoma patients (n = 67) showed an upregulation of CD29, CD44, CD81, CD146, C1QA and histone H3 as compared to serum EVs from healthy volunteers (P value range: <.0001 to .08). For two independent cohorts of glioblastoma patients, we noted upregulation of C1QA, CD44 and histone H3 upon tumor progression, but not in patients with stable disease. In a multivariable logistic regression analysis, a combination of CD29, CD44, CD81, C1QA and histone H3 correlated with RANO-defined tumor progression with an AUC of 0.76. Measurement of CD29, CD44, CD81, C1QA and histone H3 in serum-derived EVs of glioblastoma patients, along with standard MRI assessment, has the potential to improve detection of true tumor progression and thus could be a useful biomarker for clinical decision making.

Mutations in SREBF1, Encoding Sterol Regulatory Element Binding Transcription Factor 1, Cause Autosomal-Dominant IFAP Syndrome.

IFAP syndrome is a rare genetic disorder characterized by ichthyosis follicularis, atrichia, and photophobia. Previous research found that mutations in MBTPS2, encoding site-2-protease (S2P), underlie X-linked IFAP syndrome. The present report describes the identification via whole-exome sequencing of three heterozygous mutations in SREBF1 in 11 unrelated, ethnically diverse individuals with autosomal-dominant IFAP syndrome. SREBF1 encodes sterol regulatory element-binding protein 1 (SREBP1), which promotes the transcription of lipogenes involved in the biosynthesis of fatty acids and cholesterols. This process requires cleavage of SREBP1 by site-1-protease (S1P) and S2P and subsequent translocation into the nucleus where it binds to sterol regulatory elements (SRE). The three detected SREBF1 mutations caused substitution or deletion of residues 527, 528, and 530, which are crucial for S1P cleavage. In vitro investigation of SREBP1 variants demonstrated impaired S1P cleavage, which prohibited nuclear translocation of the transcriptionally active form of SREBP1. As a result, SREBP1 variants exhibited significantly lower transcriptional activity compared to the wild-type, as demonstrated via luciferase reporter assay. RNA sequencing of the scalp skin from IFAP-affected individuals revealed a dramatic reduction in transcript levels of low-density lipoprotein receptor (LDLR) and of keratin genes known to be expressed in the outer root sheath of hair follicles. An increased rate of in situ keratinocyte apoptosis, which might contribute to skin hyperkeratosis and hypotrichosis, was also detected in scalp samples from affected individuals. Together with previous research, the present findings suggest that SREBP signaling plays an essential role in epidermal differentiation, skin barrier formation, hair growth, and eye function.

GenRisk: a tool for comprehensive genetic risk modeling.

SUMMARY: The genetic architecture of complex traits can be influenced by both many common regulatory variants with small effect sizes and rare deleterious variants in coding regions with larger effect sizes. However, the two kinds of genetic contributions are typically analyzed independently. Here, we present GenRisk, a python package for the computation and the integration of gene scores based on the burden of rare deleterious variants and common-variants-based polygenic risk scores. The derived scores can be analyzed within GenRisk to perform association tests or to derive phenotype prediction models by testing multiple classification and regression approaches. GenRisk is compatible with VCF input file formats. AVAILABILITY AND IMPLEMENTATION: GenRisk is an open source publicly available python package that can be downloaded or installed from Github (https://github.com/AldisiRana/GenRisk). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Machine Learning for Decision-Support in Acute Abdominal Pain - Proof of Concept and Central Considerations.

Acute abdominal pain is a common presenting symptom in the emergency department and represents heterogeneous causes and diagnoses. There is often a decision to be made regarding emergency surgical care. Machine learning (ML) could be used here as a decision-support and relieve the time and personnel resource shortage.Patients with acute abdominal pain presenting to the Department of Surgery at Bonn University Hospital in 2020 and 2021 were retrospectively analyzed. Clinical parameters as well as laboratory values were used as predictors. After randomly splitting into a training and test data set (ratio 80 to 20), three ML algorithms were comparatively trained and validated. The entire procedure was repeated 20 times.A total of 1357 patients were identified and included in the analysis, with one in five (n = 276, 20.3%) requiring emergency abdominal surgery within 24 hours. Patients operated on were more likely to be male (p = 0.026), older (p = 0.006), had more gastrointestinal symptoms (nausea: p < 0.001, vomiting p < 0.001) as well as a more recent onset of pain (p < 0.001). Tenderness (p < 0.001) and guarding (p < 0.001) were more common in surgically treated patients and blood analyses showed increased inflammation levels (white blood cell count: p < 0.001, CRP: p < 0.001) and onset of organ dysfunction (creatinine: p < 0.014, quick p < 0.001). Of the three trained algorithms, the tree-based methods (h2o random forest and cforest) showed the best performance. The algorithms classified patients, i.e., predicted surgery, with a median AUC ROC of 0.81 and 0.79 and AUC PRC of 0.56 in test sets.A proof-of-concept was achieved with the development of an ML model for predicting timely surgical therapy for acute abdomen. The ML algorithm can be a valuable tool in decision-making. Especially in the context of heavily used medical resources, the algorithm can help to use these scarce resources more effectively. Technological progress, especially regarding artificial intelligence, increasingly enables evidence-based approaches in surgery but requires a strictly interdisciplinary approach. In the future, the use and handling of ML should be integrated into surgical training.

Machine learning to guide clinical decision-making in abdominal surgery-a systematic literature review.

PURPOSE: An indication for surgical therapy includes balancing benefits against risk, which remains a key task in all surgical disciplines. Decisions are oftentimes based on clinical experience while guidelines lack evidence-based background. Various medical fields capitalized the application of machine learning (ML), and preliminary research suggests promising implications in surgeons' workflow. Hence, we evaluated ML's contemporary and possible future role in clinical decision-making (CDM) focusing on abdominal surgery. METHODS: Using the PICO framework, relevant keywords and research questions were identified. Following the PRISMA guidelines, a systemic search strategy in the PubMed database was conducted. Results were filtered by distinct criteria and selected articles were manually full text reviewed. RESULTS: Literature review revealed 4,396 articles, of which 47 matched the search criteria. The mean number of patients included was 55,843. A total of eight distinct ML techniques were evaluated whereas AUROC was applied by most authors for comparing ML predictions vs. conventional CDM routines. Most authors (N = 30/47, 63.8%) stated ML's superiority in the prediction of benefits and risks of surgery. The identification of highly relevant parameters to be integrated into algorithms allowing a more precise prognosis was emphasized as the main advantage of ML in CDM. CONCLUSIONS: A potential value of ML for surgical decision-making was demonstrated in several scientific articles. However, the low number of publications with only few collaborative studies between surgeons and computer scientists underpins the early phase of this highly promising field. Interdisciplinary research initiatives combining existing clinical datasets and emerging techniques of data processing may likely improve CDM in abdominal surgery in the future.

Extending the allelic spectrum at noncoding risk loci of orofacial clefting.

Genome-wide association studies (GWAS) have generated unprecedented insights into the genetic etiology of orofacial clefting (OFC). The moderate effect sizes of associated noncoding risk variants and limited access to disease-relevant tissue represent considerable challenges for biological interpretation of genetic findings. As rare variants with stronger effect sizes are likely to also contribute to OFC, an alternative approach to delineate pathogenic mechanisms is to identify private mutations and/or an increased burden of rare variants in associated regions. This report describes a framework for targeted resequencing at selected noncoding risk loci contributing to nonsyndromic cleft lip with/without cleft palate (nsCL/P), the most frequent OFC subtype. Based on GWAS data, we selected three risk loci and identified candidate regulatory regions (CRRs) through the integration of credible SNP information, epigenetic data from relevant cells/tissues, and conservation scores. The CRRs (total 57 kb) were resequenced in a multiethnic study population (1061 patients; 1591 controls), using single-molecule molecular inversion probe technology. Combining evidence from in silico variant annotation, pedigree- and burden analyses, we identified 16 likely deleterious rare variants that represent new candidates for functional studies in nsCL/P. Our framework is scalable and represents a promising approach to the investigation of additional congenital malformations with multifactorial etiology.

Macrophage frequency in the bone marrow correlates with morphologic subtype of myeloproliferative neoplasm.

Bone marrow (BM) fibrosis in myeloproliferative neoplasms (MPNs) is associated with a poor prognosis. The development of myelofibrosis and differentiation of mesenchymal stromal cells to profibrotic myofibroblasts depends on macrophages. Here, we compared macrophage frequencies in BM biopsies of MPN patients and controls (patients with non-neoplastic processes), including primary myelofibrosis (PMF, n = 18), essential thrombocythemia (ET, n = 14), polycythemia vera (PV, n = 12), and Philadelphia chromosome-positive chronic myeloid leukemia (CML, n = 9). In PMF, CD68-positive macrophages were greatly increased compared to CML (p = 0.017) and control BM (p < 0.001). Similar findings were observed by CD163 staining (PMF vs. CML: p = 0.017; PMF vs. control: p < 0.001). Moreover, CD68-positive macrophages were increased in PV compared with ET (p = 0.009) and reactive cases (p < 0.001). PMF had higher frequencies of macrophages than PV (CD68: p < 0.001; CD163: p < 0.001) and ET (CD68: p < 0.001; CD163: p < 0.001). CD163 and CD68 were often co-expressed in macrophages with stellate morphology in Philadelphia chromosome-negative MPN, resulting in a sponge-like reticular network that may be a key regulator of unbalanced hematopoiesis in the BM space and may explain differences in cellularity and clinical course.

Endogenous Mouse Dicer Is an Exclusively Cytoplasmic Protein.

Dicer is a large multi-domain protein responsible for the ultimate step of microRNA and short-interfering RNA biogenesis. In human and mouse cell lines, Dicer has been shown to be important in the nuclear clearance of dsRNA as well as the establishment of chromatin modifications. Here we set out to unambiguously define the cellular localization of Dicer in mice to understand if this is a conserved feature of mammalian Dicer in vivo. To this end, we utilized an endogenously epitope tagged Dicer knock-in mouse allele. From primary mouse cell lines and adult tissues, we determined with certainty by biochemical fractionation and confocal immunofluorescence microscopy that endogenous Dicer is exclusively cytoplasmic. We ruled out the possibility that a fraction of Dicer shuttles to and from the nucleus as well as that FGF or DNA damage signaling induce Dicer nuclear translocation. We also explored Dicer localization during the dynamic and developmental context of embryogenesis, where Dicer is ubiquitously expressed and strictly cytoplasmic in all three germ layers as well as extraembryonic tissues. Our data exclude a direct role for Dicer in the nuclear RNA processing in the mouse.

Retention of ES cell-derived 129S genome drives NLRP1 hypersensitivity and transcriptional deregulation in Nlrp3tm1Flv mice.

Immune response genes are highly polymorphic in humans and mice, with heterogeneity amongst loci driving strain-specific host defence responses. The inadvertent retention of polymorphic loci can introduce confounding phenotypes, leading to erroneous conclusions, and impeding scientific advancement. In this study, we employ a combination of RNAseq and variant calling analyses to identify a substantial region of 129S genome, including the highly polymorphic Nlrp1 locus, proximal to Nlrp3, in one of the most commonly used mouse models of NLRP3 deficiency (Nlrp3tm1Flv). We show that the presence of the Nlrp1129S locus leads to an increase in NLRP1B protein expression, and a sensitising of Nlrp3tm1Flv macrophages to NLRP1 inflammasome activation, independent of NLRP3 deficiency. Retention of 129S genome further leads to protein sequence differences and altered gene regulation across multiple cell types, including of the key tissue-resident macrophage marker, TIM4. Using alternative models of NLRP3 deficiency, including a previously undescribed conditional Nlrp3 allele enabling precise temporal and cell-type specific control over Nlrp3 deletion, we further show that NLRP3 contributes to Talabostat-driven IL-1ß release. Our study also establishes a generic framework to identify functionally relevant SNPs and assess genomic contamination in transgenic mice using RNAseq data. This allows for unambiguous attribution of phenotypes to the target gene and advances the precision and reliability of research in the field of host defence responses.

Neuropilin2 in Mesenchymal Stromal Cells as a Potential Novel Therapeutic Target in Myelofibrosis.

Bone marrow fibrosis in myeloproliferative neoplasm (MPN), myelodysplastic syndromes (MDS), MPN/MDS overlap syndromes and acute myeloid leukemia (AML) is associated with poor prognosis and early treatment failure. Myelofibrosis (MF) is accompanied by reprogramming of multipotent bone marrow mesenchymal stromal cells (MSC) into osteoid and fiber-producing stromal cells. We demonstrate NRP2 and osteolineage marker NCAM1 (neural cell adhesion molecule 1) expression within the endosteal niche in normal bone marrow and aberrantly in MPN, MDS MPN/MDS overlap syndromes and AML (n = 99), as assessed by immunohistochemistry. Increased and diffuse expression in mesenchymal stromal cells and osteoblasts correlates with high MF grade in MPN (p < 0.05 for NRP2 and NCAM1). Single cell RNA sequencing (scRNAseq) re-analysis demonstrated NRP2 expression in endothelial cells and partial co-expression of NRP2 and NCAM1 in normal MSC and osteoblasts. Potential ligands included transforming growth factor ß1 (TGFB1) from osteoblasts and megakaryocytes. Murine ThPO and JAK2V617F myelofibrosis models showed co-expression of Nrp2 and Ncam1 in osteolineage cells, while fibrosis-promoting MSC only express Nrp2. In vitro experiments with MC3T3-E1 pre-osteoblasts and analysis of Nrp2-/- mouse femurs suggest that Nrp2 is functionally involved in osteogenesis. In summary, NRP2 represents a potential novel druggable target in patients with myelofibrosis.

Gene-based burden scores identify rare variant associations for 28 blood biomarkers.

BACKGROUND: A relevant part of the genetic architecture of complex traits is still unknown; despite the discovery of many disease-associated common variants. Polygenic risk score (PRS) models are based on the evaluation of the additive effects attributable to common variants and have been successfully implemented to assess the genetic susceptibility for many phenotypes. In contrast, burden tests are often used to identify an enrichment of rare deleterious variants in specific genes. Both kinds of genetic contributions are typically analyzed independently. Many studies suggest that complex phenotypes are influenced by both low effect common variants and high effect rare deleterious variants. The aim of this paper is to integrate the effect of both common and rare functional variants for a more comprehensive genetic risk modeling. METHODS: We developed a framework combining gene-based scores based on the enrichment of rare functionally relevant variants with genome-wide PRS based on common variants for association analysis and prediction models. We applied our framework on UK Biobank dataset with genotyping and exome data and considered 28 blood biomarkers levels as target phenotypes. For each biomarker, an association analysis was performed on full cohort using gene-based scores (GBS). The cohort was then split into 3 subsets for PRS construction and feature selection, predictive model training, and independent evaluation, respectively. Prediction models were generated including either PRS, GBS or both (combined). RESULTS: Association analyses of the cohort were able to detect significant genes that were previously known to be associated with different biomarkers. Interestingly, the analyses also revealed heterogeneous effect sizes and directionality highlighting the complexity of the blood biomarkers regulation. However, the combined models for many biomarkers show little or no improvement in prediction accuracy compared to the PRS models. CONCLUSION: This study shows that rare variants play an important role in the genetic architecture of complex multifactorial traits such as blood biomarkers. However, while rare deleterious variants play a strong role at an individual level, our results indicate that classical common variant based PRS might be more informative to predict the genetic susceptibility at the population level.

NCBench: providing an open, reproducible, transparent, adaptable, and continuous benchmark approach for DNA-sequencing-based variant calling.

We present the results of the human genomic small variant calling benchmarking initiative of the German Research Foundation (DFG) funded Next Generation Sequencing Competence Network (NGS-CN) and the German Human Genome-Phenome Archive (GHGA). In this effort, we developed NCBench, a continuous benchmarking platform for the evaluation of small genomic variant callsets in terms of recall, precision, and false positive/negative error patterns. NCBench is implemented as a continuously re-evaluated open-source repository. We show that it is possible to entirely rely on public free infrastructure (Github, Github Actions, Zenodo) in combination with established open-source tools. NCBench is agnostic of the used dataset and can evaluate an arbitrary number of given callsets, while reporting the results in a visual and interactive way. We used NCBench to evaluate over 40 callsets generated by various variant calling pipelines available in the participating groups that were run on three exome datasets from different enrichment kits and at different coverages. While all pipelines achieve high overall quality, subtle systematic differences between callers and datasets exist and are made apparent by NCBench.These insights are useful to improve existing pipelines and develop new workflows. NCBench is meant to be open for the contribution of any given callset. Most importantly, for authors, it will enable the omission of repeated re-implementation of paper-specific variant calling benchmarks for the publication of new tools or pipelines, while readers will benefit from being able to (continuously) observe the performance of tools and pipelines at the time of reading instead of at the time of writing.

Deficiency for SAMHD1 activates MDA5 in a cGAS/STING-dependent manner.

Defects in nucleic acid metabolizing enzymes can lead to spontaneous but selective activation of either cGAS/STING or RIG-like receptor (RLR) signaling, causing type I interferon-driven inflammatory diseases. In these pathophysiological conditions, activation of the DNA sensor cGAS and IFN production are linked to spontaneous DNA damage. Physiological, or tonic, IFN signaling on the other hand is essential to functionally prime nucleic acid sensing pathways. Here, we show that low-level chronic DNA damage in mice lacking the Aicardi-Goutières syndrome gene SAMHD1 reduced tumor-free survival when crossed to a p53-deficient, but not to a DNA mismatch repair-deficient background. Increased DNA damage did not result in higher levels of type I interferon. Instead, we found that the chronic interferon response in SAMHD1-deficient mice was driven by the MDA5/MAVS pathway but required functional priming through the cGAS/STING pathway. Our work positions cGAS/STING upstream of tonic IFN signaling in Samhd1-deficient mice and highlights an important role of the pathway in physiological and pathophysiological innate immune priming.

Identification of de novo variants in nonsyndromic cleft lip with/without cleft palate patients with low polygenic risk scores.

BACKGROUND: Nonsyndromic cleft lip with/without cleft palate (nsCL/P) is a congenital malformation of multifactorial etiology. Research has identified >40 genome-wide significant risk loci, which explain less than 40% of nsCL/P heritability. Studies show that some of the hidden heritability is explained by rare penetrant variants. METHODS: To identify new candidate genes, we searched for highly penetrant de novo variants (DNVs) in 50 nsCL/P patient/parent-trios with a low polygenic risk for the phenotype (discovery). We prioritized DNV-carrying candidate genes from the discovery for resequencing in independent cohorts of 1010 nsCL/P patients of diverse ethnicities and 1574 population-matched controls (replication). Segregation analyses and rare variant association in the replication cohort, in combination with additional data (genome-wide association data, expression, protein-protein-interactions), were used for final prioritization. CONCLUSION: In the discovery step, 60 DNVs were identified in 60 genes, including a variant in the established nsCL/P risk gene CDH1. Re-sequencing of 32 prioritized genes led to the identification of 373 rare, likely pathogenic variants. Finally, MDN1 and PAXIP1 were prioritized as top candidates. Our findings demonstrate that DNV detection, including polygenic risk score analysis, is a powerful tool for identifying nsCL/P candidate genes, which can also be applied to other multifactorial congenital malformations.

Genome-wide identification of disease-causing copy number variations in 450 individuals with anorectal malformations.

Anorectal malformations (ARM) represent a spectrum of rare malformations originating from a perturbated development of the embryonic hindgut. Approximately 60% occur as a part of a defined genetic syndrome or within the spectrum of additional congenital anomalies. Rare copy number variations (CNVs) have been associated with both syndromic and non-syndromic forms. The present study represents the largest study to date to explore the contribution of CNVs to the expression of ARMs. SNP-array-based molecular karyotyping was applied in 450 individuals with ARM and 4392 healthy controls. CNVs were identified from raw intensity data using PennCNV. Overlapping CNVs between cases and controls were discarded. Remaining CNVs were filtered using a stringent filter algorithm of nine filter steps. Prioritized CNVs were confirmed using qPCR. Filtering prioritized and qPCR confirmed four microscopic chromosomal anomalies and nine submicroscopic CNVs comprising seven microdeletions (del2p13.2, del4p16.2, del7q31.33, del9p24.1, del16q12.1, del18q32, del22q11.21) and two microduplications (dup2p13.2, dup17q12) in 14 individuals (12 singletons and one affected sib-pair). Within these CNVs, based on their embryonic expression data and function, we suggest FOXK2, LPP, and SALL3 as putative candidate genes. Overall, our CNV analysis identified putative microscopic and submicroscopic chromosomal rearrangements in 3% of cases. Functional characterization and re-sequencing of suggested candidate genes is warranted.

Overexpression of Parkin in clear cell renal cell carcinoma decreases tumor aggressiveness by regulating CKS2 levels.

Low expression levels of the E3 ubiquitin­protein ligase Parkin (PARK2) are exhibited in several cancer entities, including clear cell renal cell carcinoma (ccRCC), and are associated with poor prognosis; however, PARK2 can also function as a tumor suppressor gene. The aim of the present study was to thoroughly investigate the effects of PARK2 overexpression in ccRCC cell lines and to determine its effects on malignancy by conducting functional assays such as cell cycle analysis, apoptosis analysis, migration and invasion assays. Furthermore, liquid chromatography­mass spectrometry was used to decipher potential targets of PARK2 that may influence the behavior of ccRCC tumor cells. In addition, ccRCC tumor tissues from a patient cohort were examined in tissue microarrays to find correlations between different clinical parameters. In the present study, it was demonstrated that the induction of PARK2 resulted in a less aggressive phenotype, as indicated by lower migration and invasion in ccRCC cell lines. Mass spectrometry revealed decreased levels of 29 proteins in cells with PARK2 overexpression, including CDC28 protein kinase regulatory subunit 2 (CKS2), which is highly expressed in numerous types of cancer. The link between the function of PARK2 as an E3 ubiquitin ligase and the low expression levels of CKS2 was investigated by mutating the catalytic domain of the PARK2 gene, and it was found that the effect of decreased migration was abolished in 786­O and RCC­MH ccRCC cell lines. CKS2 silencing decreased migratory ability of the cells. Furthermore, it was revealed that high CKS2 levels are associated with high tumor grading in patient samples and lower patient survival. In conclusion, the results from the present study indicated that PARK2 may signal via CKS2 to affect tumor behavior. In consequence, CKS2 may be a biomarker in ccRCC and may also serve as potential target for ccRCC therapy.