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Chromosome segregation requires that centromeres properly attach to spindle microtubules. This essential step regulates the accuracy of cell division and must therefore be precisely regulated. One of the main centromeric regulatory signaling pathways is the haspin-H3T3ph-chromosomal passenger complex (CPC) cascade, which is responsible for the recruitment of the CPC to the centromeres. During mitosis, the haspin kinase phosphorylates histone H3 at threonine 3 (H3T3ph), an essential epigenetic mark that recruits the CPC, in which the catalytic component is Aurora B kinase (AURKB). However, the centromeric haspin-H3T3ph-CPC pathway remains largely uncharacterized in mammalian male meiosis. We have analyzed haspin functions by either its chemical inhibition with LDN-192960 in cultured spermatocytes, or the ablation of the Haspin gene in Haspin−/− mice. Our studies suggest that haspin kinase activity is required for proper chromosome congression both during meiotic divisions and for the recruitment of Aurora B and kinesin MCAK (also known as KIF2C) to meiotic centromeres. However, the absence of H3T3ph histone mark does not alter borealin (or CDCA8) and SGO2 centromeric localization. These results add new and relevant information regarding the regulation of the haspin-H3T3ph-CPC pathway and centromere function during meiosis.

Metabolic reprogramming is one of the crucial hallmarks of cancer. Hepatocellular carcinoma (HCC) resulting from hepatitis B has various altered metabolic features. However, the impact of such alterations on the tumor microenvironment (TME) and immunotherapy efficacy is still unclear. Here, a prognostic signature of metabolism-related gene (MRG) composition was constructed, and the immune profile of different subgroups and potential response to immunotherapy were described. Based on the HCC gene dataset, we used weighted gene coexpression network analysis for identifying MRGs linked to hepatitis B. An MRG prognostic index (MRGPI) with two genes, ATIC and KIF2C, was constructed using Cox regression analysis, an independent prognostic factor. In addition, the model was validated using the GEO dataset. The immune profile and prediction of HCC response to immunotherapy in different subgroups were analyzed using CIBERSORT and TIDE. Based on the outcomes, the distributions of memory B cells, monocytes, resting mast cells, and M0 macrophages in TME were different with a greater benefit of immunotherapy in the low MRGPI risk group. In addition, the MRGPI risk groups showed substantial differences in sensitivity to conventional drug therapy. This study concludes that MRGPI is an effective biomarker for predicting the prognoses of patients with HCC resulting from hepatitis B virus infections and determining the efficacy of immunotherapy and conventional medical therapy.

Background: Increasing evidence has revealed that kinesin family member 20A (KIF20A) is highly expressed in a variety of cancers and is related to the occurrence and prognosis of cancer. However, a pan-cancer analysis has not been performed.Methods and results: Based on data from The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), Clinical Proteomic Tumor Analysis Consortium (CPTAC) and Human Protein Atlas (HPA) databases, we clarified the expression of KIF20A in 33 tumor types using a series of bioinformatics analyses. KIF20A is highly expressed in the majority of malignancies, and there were distinct connections between KIF20A expression and pathological stage and prognosis in tumor patients. KIF20A overexpression was associated with poor overall survival (OS) and disease-free survival (DFS) in patients with certain cancers, such as adrenocortical carcinoma, kidney renal clear cell carcinoma and brain lower grade glioma. The associations of KIF20A expression with immune cell infiltration, including the levels of infiltrating B cells, T cells, and dendritic cells, varied among tumors. Moreover, we found a positive association between KIF20A expression and cancer-associated fibroblast infiltration in patients with esophageal carcinoma (ESCA), mesothelioma (MESO) and thyroid carcinoma (THCA). In addition, we identified five genes, KIF2C, KIF23, CDC25, CCNB1 and DLGAP5, whose expression was positively related to KIF20A expression.Conclusions: This pan-cancer study provides a comprehensive understanding of KIF20A's oncogenic functions in a variety of human tumors.

Das vollsynthetische Epothilon Sagopilon wird derzeit in der klinischen Phase II zur Behandlung solider Tumore erprobt. Im Rahmen dieser Arbeit wurde der molekulare Wirkmechanismus Sagopilons im Vergleich zu anderen Epothilonen und ähnlich wirkenden Taxanen untersucht. Ziel war es, Biomarker zur Abschätzung des Therapieerfolgs zu identifizieren. Ein weiteres Ziel war die rationale Identifizierung und mechanistische Beurteilung von Kombinationsstrategien. Als ausschließliche Angriffsstelle Sagopilons wurde Tubulin, Baustein der Mikrotubuli, identifiziert. Sagopilon stabilisiert Mikrotubuli in stärkerem Maße als Taxane und andere Epothilone. Dies fördert die Bildung von de novo Nukleationszentren für Mikrotubuli und führt zur Bildung multipolarer statt bipolarer mitotischer Spindeln. Die Teilung tripolarer Spindeln resultiert in vitalen Zellen mit vermindertem, aneuploiden DNA-Gehalt, die seneszenzähnlich in der G1-Phase arretiert sind. Diese Art der Proliferationshemmung wurde in den Tumorzellinien SKBR3, MDA-MB231, MCF7, T47D, A549 und MDA-MB435s bei subnanomolaren Sagopilonkonzentrationen beobachtet. Das Risiko, dass Zellen aus dem G1-Arrest austreten und erneut proliferieren, steigt mit ihrem Polyploidisierungsgrad. Unter niedrigen Paclitaxelkonzentrationen hingegen bilden sich weniger stabile tripolare Spindeln, stattdessen auch monopolare Spindeln, die nach Mitoseabbruch zu vitalen, tetraploiden Zellen führen können. Höhere Sagopilon- und Paclitaxelkonzentrationen stören die Mikrotubulidynamik derart, das die Zellen in der Mitose blockiert werden. Dies führt meist zu Apoptose, jedoch zellinienabhängig auch zu fehlerhaften Mitosen oder Polyploidisierung. Zwischen verschiedenen Tumorzellinien und zwischen Zellen der gleichen Linie wurden Unterschiede im Verlauf nach dem mitotischen Arrest beobachtet. Entscheidend war hierbei die Stärke des mitotischen Arrests sowie die Balance pro-und antiapoptotischer Faktoren. In einem 300 Gene und vier Zellinien umfassenden RNAi-Screen wurden Defekte im mitotischen Kontrollpunkt des Spindelaufbaus (Spindle assembly checkpoint) als Ursache von Resistenz gegen die Apoptoseinduktion infolge mitotischen Arrests identifiziert. Potentielle Resistenz-Biomarker sind SAC-Defekte, wie z. B. Mutationen in der zentralen Kinase BUB1B, sowie ein reduziertes Apoptosepotenzial der Zellen durch niedrige Expression proapoptotischer Proteine (z. B. Bak, Caspasen) und erhöhte Expression antiapoptotischer Proteine (z. B. BCL2). Chromosomale Heterogenität und Polyploidisierung zeugen von einer erhöhten Toleranz gegenüber aberranten Mitosen und sind daher potentielle prädiktive Resistenzbiomarker. Die häufigste Resistenzursache gegen Taxane ist die Hochregulation von ABC-Transportern. Der RNAi-Screen bestätigte erneut, dass Sagopilon kein Substrat für ABC-Transporter ist. Außerdem verstärkte die siRNA-vermittelte Herabregulation epothilonmetabolisierender Enzyme nicht die Wirkung von Sagopilon in den untersuchten Tumorzellinien. Ein rationaler Kombinationsansatz ist die Verstärkung des sagopilon-induzierten mitotischen Arrests, z. B. durch die Hemmung von Kinesinen, den Motorproteinen der mitotischen Spindel. Entscheidend für die Kombinationswirkung von Sagopilon und Kinesininhibition ist der Aktionszeitpunkt der Kinesine. So wirken Sagopilon und die Hemmung des in der Prophase aktiven Kinesins KIF11 (Eg-5) antagonistisch, während Sagopilon und die Hemmung des in der Meta-phase aktiven Kinesins KIF2C (MCAK) synergistisch wirken. Für die Klinik wird für Sagopilon ein breiteres Anwendungsspektrum als für vergleichbar wirkende Taxane erwartet. Ein Resistenzrisiko besteht für polyploide und chromosomal heterogene Tumore. Die zytotoxische Wirkung Sagopilons kann vermutlich durch Kombination mit Inhibitoren des Kinesins KIF2C gesteigert werden. Chemotherapy of cancers is complicated by tumor heterogeneity and development of resistances. In the clinic, combination therapies are usually employed to overcome these obstacles. Sagopilone, a fully synthetic epothilone, is currently evaluated in clinical phase II trials. Here, the molecular mode of action of sagopilone was compared to that of other epothilones and the functionally related taxanes. This work aimed to identify biomarkers predictive of tumor response to sagopilone. Another aim was to identify rational combination strategies and to evaluate these mechanistically. Tubulin was identified as unique target of sagopilone. Sagopilone stabilizes microtubuli more effectively than taxanes and other epothilones. This leads to the formation of centrosome-independent microtubule-organizing centers and results in multipolar instead of bipolar mitotic spindles. Tripolar mitosis produces vital cells with reduced, aneuploid DNA-content arrested in a senescence-like G1-state. This mechanism of proliferation inhibition was observed in the tumor cell lines MCF7, T47D, MDA-MB231, SKBR3, A549 and MDA-MB435s at subnanomolar sagopilone concentrations. The risk of cells escaping the G1-arrest increases with polyploidy, as seen for MCF7-cells. Paclitaxel on the other hand causes monopolar spindles besides multipolar ones. After mitotic exit, this leads to vital, proliferating tetraploid cells. Higher concentrations of sagopilone and paclitaxel perturb microtubuli dynamics to the point of mitotic arrest. Mitotically arrested cells usually undergo apoptosis but may also undergo aberrant mitosis or mitotic slippage and endoreduplication. Cell lines and cells of the same line differed in the outcome following mitotic arrest depending on the strength of the mitotic arrest and a balance of proand anti-apoptotic factors. An RNAi-modifier screen comprising 300 genes in four cell lines identified defects of the spindle assembly checkpoint (SAC) to cause resistance against sagopilone-induced mitotic arrest and apoptosis. Potential biomarkers for resistancy are SAC-defects like mutations in the central SAC-kinase BUB1B or low apoptotic potential due to high expression of anti-apoptotic proteins such as BCL2 and low expression of pro-apoptotic proteins like Bak or Caspases. Chromosomal heterogeneity and polyploidy are also potential biomarkers of resistance since they imply an increased tolerance for aberrant mitosis. The most frequent development or resistancy against taxanes is the upregulation of ABC-Transporters. The RNAi-modifier screen showed yet again that sagopilone is not a substrate of ABC-transporters. In addition, sagopilone is not metabolized by the analyzed tumor cells. The RNAi-modifier screen also identified the enhancement of sagopilone-induced mitotic arrest by inhibition of mitotic kinesins, as potential combination strategy. The combination effect depends on the action of individual kinesins within the mitotic progression. On one hand, the combination of sagopilone and inhibition of the prophase kinesin KIF11 (Eg-5) is antagonistic. On the other hand, sagopilon and inhibition of the metaphase kinesin KIF2C (MCAK) synergize. Clinically, sagopilone is expected to be show broader activity than taxanes. Polyploid and chromosomal heterogeneous tumors are likely to have an increased intrinsic risk for resistancy. Combination with inhibitors of kinesin KIF2C is likely to enhance the cytotoxicity of sagopilone.

Background. We recently reported that the biosynthetic mevalonate (MVA) pathway that produces cholesterol and isoprenoid intermediates, regulates the YAP/TAZ (Y/T) transcriptional co-activators to promote resistance to treatment regimens that effectively inhibit HER2 signaling in HER2+ BC. We further showed that the mTORC1 complex and survivin protein, which contribute to HER2-elicited oncogenic signaling in HER2-driven BC cells, are alternatively activated by the MVA pathway-Y/T axis in anti-HER2 therapy resistant cell models. Of note, other recent reports also showed that increased Y/T activity enables resistant cells to proliferate when other oncogenic pathways (e.g., RAS, EGFR, and FGFR) were effectively inhibited. Here, we sought to further determine the molecular underpinnings of MVA-Y/T axis-driven anti-HER2 therapy resistance to discover novel therapeutic targets and predictive biomarkers for HER2+ BC.Methods. SKBR3 HER2+ BC parental (P) cells and their lapatinib plus trastuzumab (LT) resistant (LTR) derivatives with sustained HER2 inhibition were treated with the MVA pathway inhibitor simvastatin (Sim), with or without the MVA metabolite to rescue Sim’s inhibitory effects. P and LTR cells were also transfected with control or combined Y/T siRNAs. The transcriptomes of all treatment groups were assessed by RNA-seq. Integrative bioinformatics analyses were used to identify differentially expressed (DE) genes and gene sets with functional annotations in LTR vs. P cells upon different interventions.Results. We found that cell cycle and cell proliferation processes were among the top common DE molecular signatures preferentially downregulated (DN) in LTR vs. P cells by both Sim and Y/T knockdown (KD). The top common genes preferentially DN in LTR vs. P cells include the cell cycle regulatory genes CDCA3 and ERCC6L, and the nucleotide metabolism genes TYMS and RRM2. Interestingly, 20% of the genes preferentially DN in LTR vs. P cells by Sim or Y/T KD were predicted to be direct Y/T transcriptional targets based on previously reported ChIP-seq data (PMID: 26258633). Of the Y/T-dependent genes, a significant enrichment of Sim-repressed genes was observed in both P and LTR cells (P = 1.2e-115 and P = 5.5e-138, respectively). The proportion of these enriched genes was higher in LTR vs. P cells (61% vs. 29%). Of note, we found that the global inhibited genes in LTR cells upon Sim or Y/T KD were significantly enriched for the genes DN by short-term LT treatment in P cells (P < 2.2e-16). Likewise, of the genes nominated as putative molecular players in the MVA pathway-Y/T-mediated resistance, BIRC5 (survivin), CDC6, KIF2C, RRM2, and TYMS were recently also reported to be DN in HER2+ tumors treated with neo-adjuvant LT in the PAMELA trial (NCT01973660), a finding that is in line with what we observed in our P cells treated with short-term LT. Conclusions. Upon acquisition of resistance to sustained HER2 inhibition, the MVA pathway-Y/T axis takes over the regulation of pro-proliferative transcriptional programs that are generally downstream of HER2 signaling in treatment-naïve HER2+ BC. The MVA pathway-Y/T axis leads to Y/T-driven transcriptional reprogramming, an emerging mechanism of therapy resistance to anti-HER2 and other targeted therapies that warrants further investigation. The identification of multiple cell cycle related processes as putative targets of the MVA pathway-Y/T axis presents additional targetable vulnerabilities and implies that inhibitors of Y/T and cell cycle checkpoints may help circumvent anti-HER2 resistance in the clinical setting. Citation Format: Vidyalakshmi Sethunath, Xiaoyong Fu, Pamela L Luna, Sarmistha Nanda, Martin Shea, Jamunarani Veeraraghavan, Carmine De Angelis, Huizhong Hu, Chad Shaw, Mothaffar Rimawi, C. Kent Osborne, Rachel Schiff. Insights into the molecular underpinnings of the mevalonate pathway-YAP/TAZ-driven anti-HER2 therapy resistance in HER2+ breast cancer (BC) [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS5-29.

Background The tumorigenesis of prostate cancer involves genetic mutations. Tumour mutational burden (TMB) is an emerging biomarker for predicting the efficacy of immunotherapy. Results Single-nucleotide polymorphisms were the most common variant type, and C>T transversion was the most commonly presented type of single-nucleotide variant. The high-TMB group had lower overall survival (OS) than the low-TMB group. TMB was associated with age, T stage and N stage. Functional enrichment analysis of differentially expressed genes (DEGs) showed that they are involved in pathways related to the terms spindle, chromosomal region, nuclear division, chromosome segregation, cell cycle, oocyte meiosis and other terms associated with DNA mutation and cell proliferation. Six hub genes, PLK1, KIF2C, MELK, EXO1, CEP55 and CDK1, were identified. All the genes were associated with disease-free survival, and CEP55 and CDK1 were associated with OS. Conclusions The present study provides a comprehensive analysis of the significance of TMB and DEGs and infiltrating immune cells related to TMB, which provides helpful information for exploring the significance of TMB in prostate cancer.

The screening and treatment of laryngeal squamous cell carcinoma (LSCC) still perplexes clinicians, making it necessary to explore new markers. To this end, this research examined the underlying molecular mechanism of LSCC based on high-throughput datasets (n = 249) from multiple databases. It also identified transcription factors (TFs) independently associated with LSCC prognosis. Through Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses, differential expression genes of LSCC were deemed relevant to the extracellular matrix and its related structures or pathways, suggesting that the extracellular matrix plays an important role in LSCC. At the same time, several hub genes that may also have important roles in LSCC were identified via protein–protein interaction analysis, including CDC45, TPX2, AURKA, KIF2C, NUF, MUC1, MUC7, MUC4, MUC15, and MUC21. Eight unreported LSCC prognostic TFs – BCAT1, CHD4, FOXA2, GATA6, HNF1A, HOXB13, MAFF, and TCF4 – were screened via Kaplan–Meier curves. Cox analysis determined for the first time that HOXB13 expression and gender were independently associated with LSCC prognosis. Compared to control tissues, elevated expression of HOXB13 was found in LSCC tissues (standardized mean difference = 0.44, 95% confidence interval [0.13–0.76]). HOXB13 expression also makes it feasible to screen LSCC from non-LSCC (area under the curve = 0.77), and HOXB13 may play an essential role in LSCC by regulating HOXB7. In conclusion, HOXB13 may be a novel marker for LSCC clinical screening and treatment.

Background Cutaneous squamous cell carcinoma (cSCC) is a relatively common cancer that accounts for nearly 50% of non-melanoma skin cancer cases. However, the genotypes that are linked with poor prognosis and/or high relapse rates and pathogenic mechanisms of cSCC are not fully understood. To address these points, three gene expression datasets were analyzed to identify candidate biomarker genes in cSCC. Methods The GSE117247, GSE32979, and GSE98767 datasets comprising a total of 32 cSCC samples and 31 normal skin tissue samples were obtained from the National Center for Biotechnology Information Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified and underwent pathway enrichment analyses with the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG). A putative DEG protein–protein interaction (PPI) network was also established that included hub genes. The expression of CDK1, MAD2L1, BUB1 ans CDC20 were examined in the study. Results A total of 335 genes were identified, encompassing 219 found to be upregulated and 116 genes that were downregulated in cSCC, compared to normal tissue. Enriched functions of these DEGs were associated with Ephrin receptor signaling and cell division; cytosol, membrane, and extracellular exosomes; ATP-, poly(A) RNA-, and identical protein binding. We also established a PPI network comprising 332 nodes and identified KIF2C, CDC42, AURKA, MAD2L1, MYC, CDK1, FEN1, H2AFZ, BUB1, BUB1B, CKS2, CDC20, CCT2, ACTR2, ACTB, MAPK14, and HDAC1 as candidate hub genes. The expression of CDK1 are significantly higher in the cSCC tissues than that in normal skin. Conclusions The DEGs identified in this study are potential therapeutic targets and biomarkers for cSCC. CDK1 is a gene closely related to the occurrence and development of cSCC, which may play an important role. Bioinformatics analysis shows that it is involved in the important pathway of the pathogenesis of cSCC, and may be recognized and applied as a new biomarker in the future diagnosis and treatment of cSCC.

Breast cancer (BC) is a malignancy with high incidence among women in the world. This study aims to screen key genes and potential prognostic biomarkers for BC using bioinformatics analysis. Total 58 normal tissues and 203 cancer tissues were collected from three Gene Expression Omnibus (GEO) gene expression profiles, and then the differential expressed genes (DEGs) were identified. Subsequently, the Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genome (KEGG) pathway were analyzed to investigate the biological function of DEGs. Additionally, hub genes were screened by constructing a protein–protein interaction (PPI) network. Then, we explored the prognostic value and molecular mechanism of these hub genes using Kaplan–Meier (KM) curve and Gene Set Enrichment Analysis (GSEA). As a result, 42 up-regulated and 82 down-regulated DEGs were screened out from GEO datasets. The DEGs were mainly related to cell cycles and cell proliferation by GO and KEGG pathway analysis. Furthermore, 12 hub genes (FN1, AURKA, CCNB1, BUB1B, PRC1, TPX2, NUSAP1, TOP2A, KIF20A, KIF2C, RRM2, ASPM) with a high degree were identified initially, among which, 11 hub genes were significantly correlated with the prognosis of BC patients based on the Kaplan–Meier-plotter. GSEA reviewed that these hub genes correlated with KEGG_CELL_CYCLE and HALLMARK_P53_PATHWAY. In conclusion, this study identified 11 key genes as BC potential prognosis biomarkers on the basis of integrated bioinformatics analysis. This finding will improve our knowledge of the BC progress and mechanisms.

The precise regulation of microtubule length during mitosis is essential to assemble and position the mitotic spindle and segregate chromosomes. The kinesin-13 Kif2C or MCAK acts as a potent microtubule depolymerase that diffuses short distances on microtubules, whereas the kinesin-8 Kif18b is a processive motor with weak depolymerase activity. However, the individual activities of these factors cannot explain the dramatic increase in microtubule dynamics in mitosis. Using in vitro reconstitution and single-molecule imaging, we demonstrate that Kif18b, MCAK and the plus-end tracking protein EB3 (also known as MAPRE3) act in an integrated manner to potently promote microtubule depolymerization at very low concentrations. We find that Kif18b can transport EB3 and MCAK and promotes their accumulation to microtubule plus ends through multivalent weak interactions. Together, our work defines the mechanistic basis for a cooperative Kif18b–MCAK–EB network at microtubule plus ends, that acts to efficiently shorten and regulate microtubules in mitosis, essential for correct chromosome segregation.

Mounting evidence has revealed the key role of cancer stem cells in hepatocellular carcinoma (HCC) metastasis and therapy resistance, yet the genes maintaining HCC stem cell features remain to be explored. This study aimed to identify and validate the key biomarkers associated with HCC stemness. mRNA expression-based stemness index (mRNAsi) was calculating using one-class logistic regression algorithm. RNA-sequencing data and clinical information of HCC samples were downloaded from the cancer genome atlas (TCGA) and merged with the corresponding mRNAsi. We investigated the correlation between mRNAsi and HCC clinical characteristics, including tumor grades, pathologic stages, vascular invasion, and survival outcomes. Significant genes associated HCC stemness features were screened through weighted gene co-expression network analysis (WGCNA) and were functionally annotated using enrichment analysis. Protein-protein interaction network was constructed among significant genes and the key biomarkers were finally identified based on the maximal clique centrality (MCC) method. The expression of key biomarkers and its correlation with HCC clinical outcomes were validated using oncomine and gene expression omnibus (GEO) database. mR-NAsi was significantly higher in HCC tissues and gradually increased according to tumor grades and pathologic stages. Patients with vascular invasion or poor survival exhibited higher mRNAsi. Forty-four highly-correlated significant gens were screened through WGCNA and functionally related to cell cycle, cellular senescence, p53 signaling pathway, DNA replication, and mismatch repair. Four different GEO datasets confirmed that the expression levels of these 44 genes were notably higher in HCC tissues. We finally identified 15 key biomarkers (KIF4A, TTK, CCNB1, CDC20, NCAPG, CCNB2, CDC45, UBE2C, CENPA, AURKB, RRM2, CDCA8, BIRC5, TPX2, and KIF2C) through MCC method. The expression of these biomarkers was up-regulated in multiple types of cancers and showed a gradually increasing trend with HCC tumor grades. Furthermore, high expression levels of these biomarkers were also correlated with HCC metastasis, recurrence, sorafenib resistance, and poor overall survival. We identified 15 key biomarkers associated with HCC stemness features and these genes might serve as promising therapeutic targets for HCC.

Previous studies have suggested potential signature genes for lung cancer, however, due to factors such as sequencing platform, control, data selection and filtration conditions, the results of lung cancer-related gene expression analysis are quite different. Here, we performed a meta-analysis on existing lung cancer gene expression results to identify Meta-signature genes without noise. In this study, functional enrichment, protein-protein interaction network, the DAVID, String, TfactS, and transcription factor binding were performed based on the gene expression profiles of lung adenocarcinoma and non-small cell lung cancer deposited in the GEO database. As a result, a total of 574 differentially expressed genes (DEGs) affecting the pathogenesis of lung cancer were identified (207 up-regulated expression and 367 down-regulated expression in lung cancer tissues). A total of 5,093 interactions existed among the 507 (88.3%) proteins, and 10 Meta-signatures were identified: AURKA, CCNB1, KIF11, CCNA2, TOP2A, CENPF, KIF2C, TPX2, HMMR, and MAD2L1. The potential biological functions of Meta-signature DEGs were revealed. In summary, this study identified key genes involved in the process of lung cancer. Our results would help the developing of novel biomarkers for lung cancer.

ObjectiveTo investigate the expression, clinical significance, and potential mechanism of action of DUXAP8 in hepatocellular carcinoma. MethodsThe expression data of liver cancer and related clinical data published up to June 2019 were collected from TCGA database to screen out the differentially expressed long non-coding RNAs (lncRNAs) between liver cancer tissue and adjacent tissue which affected the prognosis of patients. The association of the expression level of DUXAP8 with clinicopathological features and prognosis was analyzed. Gene ontology (GO) and KEGG pathway enrichment analysis was used to investigate the biological functions and biological processes of DUXAP8-related genes. The STRING database and Cytoscape were used to analyze protein-protein interactions and screen out key genes, and then the expression levels of key genes and prognosis were analyzed and a literature search analysis was performed. The Wilcoxon signed-rank test and the Wilcoxon rank-sum test were used to compare the expression of DUXAP8 between liver cancer tissue and adjacent tissue, and the Wilcoxon rank-sum test was used to compare the expression of DUXAP8 between the patients with different clinicopathological features. The Kaplan-Meier method was used to plot survival curves and the log-rank test was used for survival comparison between groups; a Cox regression analysis was used to identify the influencing factors for prognosis. A Pearson correlation analysis was used to analyze DUXAP8-related genes. ResultsAs for the matched and unmatched samples, there was a significant difference in the expression of DUXAP8 between liver cancer tissue and adjacent tissue (P＜0.001), and the expression of DUXAP8 in liver cancer tissue was significantly higher than that in adjacent tissue. There was a significant difference in the expression of DUXAP8 between the patients with different ages or T stages (P＜0.05), and the patients with an age of ≥60 years or a T stage of T3 or T4 tended to have higher expression of DUXAP8. The univariate analysis showed that clinical stage, T stage, and expression of DUXAP8 were associated with patients’ overall survival (all P＜0001), and the multivariate Cox regression analysis showed that an advanced clinical stage (hazard ratio ［HR］=1.648, 95% confidence interval ［CI］: 1.330-2.709, P＜0.001) and high expression of DUXAP8 (HR=1.849, 95%CI: 1.262-2.713, P＜0.01) were independent risk factors for poor prognosis. The genes involved in the maintenance of tumor cell proliferation and cell cycle were enriched in the samples with high expression of DUXAP8. TOP2A, KIF2C, TTK, PLK1, CDCA8, CDC20, NCAPG, BUB1B, BUB1, and CCNA2 were the Hub genes of DUXAP8-related genes and were mainly involved in the processes such as cell mitosis and cell cycle, and they were the factors for poor prognosis of patients with liver cancer (all P＜0.05). ConclusionThe high expression of DUXAP8 is a risk factor for poor prognosis in patients with liver cancer and DUXAP8 may promote the development and progression of liver cancer by affecting the processes of cell proliferation and cell cycle.

Breast cancer is the most common cancer type in females, and exploring the mechanisms of disease progression is playing a crucial role in the development of potential therapeutics. Pituitary tumor-transforming gene (PTTG) family members are well documented to be involved in cell-cycle regulation and mitosis, and contribute to cancer development by their involvement in cellular transformation in several tumor types. The critical roles of PTTG family members as crucial transcription factors in diverse types of cancers are recognized, but how they regulate breast cancer development still remains mostly unknown. Meanwhile, a holistic genetic analysis exploring whether PTTG family members regulate breast cancer progression via the cell cycle as well as the energy metabolism-related network is lacking. To comprehensively understand the messenger RNA expression profiles of PTTG proteins in breast cancer, we herein conducted a high-throughput screening approach by integrating information from various databases such as Oncomine, Kaplan-Meier Plotter, Metacore, ClueGo, and CluePedia. These useful databases and tools provide expression profiles and functional analyses. The present findings revealed that PTTG1 and PTTG3 are two important genes with high expressions in breast cancer relative to normal breast cells, implying their unique roles in breast cancer progression. Results of our coexpression analysis demonstrated that PTTG family genes were positively correlated with thiamine triphosphate (TTP), deoxycytidine triphosphate (dCTP) metabolic, glycolysis, gluconeogenesis, and cell-cycle related pathways. Meanwhile, through Cytoscape analyzed indicated that in addition to the metastasis markers AURKA, AURKB, and NDC80, many of the kinesin superfamily (KIF) members including KIFC1, KIF2C, KIF4A, KIF14, KIF20A, KIF23, were also correlated with PTTG family transcript expression. Finally, we revealed that high levels of PTTG1 and PTTG3 transcription predicted poor survival, which provided useful insights into prospective research of cancer associated with the PTTG family. Therefore, these members of the PTTG family would serve as distinct and essential prognostic biomarkers in breast cancer.

Endometrial carcinoma(EC) is the most common cancer of female reproductive system, thus requiring for new effective biomarkers which could predict the onset of EC and poor prognosis. Our study integrated two GEO datasets(i.e.GSE63678, GSE17025) and TCGA(The Cancer Genome Atlas ) UCEC data to screen out 344 common differentially expressed genes(DEGs), which were further analyzed by GO(gene ontology) functions and KEGG(Kyoto Encyclopedia of Gene and Genome) pathways. KEGG analysis results showed these DEGs were mainly enriched in cell cycle, oocyte meiosis, cellular senescence, carbon metabolism and p53 signaling pathway. Top 20 hub genes with higher degree were selected from PPI(protein-protein interaction) network and 15 of them were associated with the prognosis of EC, that is, CCNB2, CDC20, BUB1B, UBE2C, AURKB, FOXM1, NCAPG, RRM2, TPX2, DLGAP5, CDCA8, CDC45, MKI67, BUB1, KIF2C. UBE2C(Ubiquitin Conjugating Enzyme E2 C) was chosen for further validation in TCGA cohort on mRNA level and in our patient samples on protein level by immunohistochemistry. UBE2C was significantly highly expressed in endometrial carcinoma, and its expression level was associated with advanced FIGO staging and poor prognosis. Cox risk model demonstrated high UBE2C expression was an independent risk factor. Somatic mutations, elevated copy number, DNA hypomethylation all contributed to its overexpression. Therefore, by combination of bioinformatics and experiment, our study provided a unique insight into the pathogenesis and molecular mechanisms underlying EC and discovered new biomarkers for early diagnosis and prognostic prediction. UBE2C could serve as a potential marker to predict poor prognosis and as a therapeutic target.

Purpose: When glioma is in WHO grade II-III, glioma is of low grade. Gliomas in this period have the opportunity for surgical treatment and can be treated with a range of targeted therapies to enhance patient survival. Methods: In this study, we downloaded low-grade glioma data from TCGA database and GSEA database. Cancer subtypes were classified by GSVA enrichment method.Results: By GSVA enrichment analysis, we obtain three low-grade gliomas (LGG) cancer subtypes. After further survival prognosis analysis and biological function analysis, we obtained 21 tumor microenvironment gene sets and 17 core genes that affect patients' survival prognosis, and these genes have the potential to become targets for targeted therapies and disease detection.Conclusion: We screened a total of 21 gene sets through a series of enrichment analyses, statistical and prognostic analyses, etc. Among them, 17 core genes were identified, namely: TOP2A, KIF20A, CCNB2, AURKA, KIF11, CDK1, BUB1B, CCNA2, BUB1, CDC20, CDCA8, TPX2, KIF2C, POLA2, POLE2, POLA1 and POLE. TOP2A.

Background: Hepatocellular carcinoma (HCC) is one of the fastest-growing malignancies globally. The impact of surgical treatment is limited, and molecular targeted therapy has not yielded a consistent efficacy. This warrants for identification of novel molecular targets. The anti-silencing function of 1B histone chaperone (ASF1B) previously studied in numerous cancers. However, the understanding of its role in HCC is limited. Methods: The TIMER database used to analyze the ASF1B expression in pan-cancer and para-carcinoma tissues. ASF1B expression in HCC confirmed by using the HCCDB database, Quantitative real-time PCR (q-PCR), and Western blot (WB) assays. The relationship between clinicopathological parameters and ASF1B expression analyzed by using UALCAN, whereas the prognostic value of ASF1B was evaluated using the GEPIA database. Linkedomics and cBioportal databases used to validate the ASF1B co-expression associated with immune infiltration by the TIMER database. Moreover, cell proliferation after ASF1B-knockdown was determined through CCK8 and clone formation assays. Results: ASF1B was highly expressed in HCC tissues and the expression levels were linked to tumor grade, race, and disease stage. Univariate and multivariate Cox models showed that ASF1B is an independent prognostic factor in HCC. CCK8 and clone formation assays demonstrated that ASF1B promotes cell proliferation. Gene co-expression analysis in Linkedomics demonstrated that HJURP, KIF2C, KIF4A, KIF18B, and KIFC1 expression were intimately associated with ASF1B and immune infiltrate cells. Conclusion: This study shows that ASF1B promotes the proliferation of HCC. Besides, ASF1B could be a potential prognostic biomarker for HCC patients.

From the standpoint of the ER (endoplasmic reticulum), we were interested in identifying hub genes that impact clinical prognosis for HCC (hepatocellular carcinoma) patients and developing an ER-related prognostic model. Using TCGA-LIHC (The Cancer Genome Atlas-Liver Hepatocellular Carcinoma) and GSE14520 datasets, we conducted a series of analyses, which included differential gene screening, clinical prognostic analysis, Lasso regression, nomogram prediction, tumour clustering, gene functional enrichment, and tumour infiltration of immune cells. Following our screening for ER-related genes ( n = 1975 ), we conducted a Lasso regression model to obtain five hub genes, KPNA2, FMO3, SPP1, KIF2C, and LPCAT1, using TCGA-LIHC as a training set. According to risk scores, HCC samples within either the TCGG-LIHC or GSE14520 cohort were categorized into high- and low-risk groups. Compared to the high-risk group of HCC patients, patients in the low-risk group had a better prognosis of OS (overall survival) or RFS (relapse-free survival). For TCGA-LIHC training set, with the factors of risk score, stage, age, and sex, we plotted a nomogram for 1-, 3-, and 5-year survival predictions. Our model demonstrated better clinical validity in both TCGA-LIHC and GSE14520 cohorts. Additionally, events related to biological enzyme activity, biological metabolic processes, or the cell cycle were associated with the prognostic risk of ER. Furthermore, two HCC prognosis-associated tumour clusters were identified by ER hub gene-based consensus clustering. Our findings indicated a link between ER prognostic signature-related high/low risk and tumour infiltration levels of several immune cells, such as “macrophages M2/M0” and “regulatory T cells (Tregs).” Overall, we developed a novel ER-related clinical prognostic model for HCC patients.

Purpose Super-enhancer (SE)-associated oncogenes extensively potentiate the uncontrolled proliferation capacity of cancer cells. In this study, we aimed to identify the SE-associated hub genes associated with the clinical characteristics of chronic myeloid leukemia (CML). Methods Eigengenes from CML clinical modules were determined using weighted gene co-expression network analysis (WGCNA). Overlapping genes between eigengenes and SE-associated genes were used to construct protein-protein interaction (PPI) networks and annotate for pathway enrichment analysis. Expression patterns of the top-ranked SE-associated hub genes were further determined in CML patients and healthy controls via real-time PCR. After treatment of K562 cells with the BRD4 inhibitor, JQ1, for 24 hrs, mRNA and protein levels of SE-associated hub genes were evaluated using real-time PCR and Western blotting, respectively. H3K27ac, H3K4me1 and BRD4 ChIP-seq signal peaks were used to predict and identify SEs visualized by the Integrative Genomics Viewer. Results The yellow module was significantly related to the status and pathological phase of CML. SE-associated hub candidate genes were mainly enriched in the cell cycle pathway. Based on the PPI networks of hub genes and the top rank of degree, five SE-associated genes were identified: specifically, BUB1, CENPO, KIF2C, ORC1, and RRM2. Elevated expression of these five genes was not only related to CML status and phase but also positively regulated by SE and suppressed by the BRD4 inhibitor, JQ1, in K562 cells. Strong signal peaks of H3K27ac, H3K4me1 and BRD4 ChIP-seq of the five genes were additionally observed close to the predicted SE regions. Conclusion This is the first study to characterize SE-associated genes linked to clinical characteristics of CML via weighted gene co-expression network analysis. Our results support a novel mechanism involving aberrant expression of hub SE-associated genes in CML patients and K562 cells, and these genes will be potential new therapeutic targets for human leukemia.

Purpose Enterococcus faecalis (E. faecalis) is an important commensal microbiota member of the human gastrointestinal tract. It has been shown in many studies that infection rates with E. faecalis in gastric cancer significantly increase. It has been scientifically proven that some infections develop during the progression of cancer, but it is still unclear whether this infection factor is beneficial (reduction in metastasis) or harmful (increase in proliferation, invasion, stem cell-like phenotype) of the host. These opposed data can significantly contribute to the understanding of cancer progress when analyzed in detail. Methods The gene expression data were retrieved from Array Express (E-MEXP-3496). Variance, t test and linear regression analysis, hierarchical clustering, network, and pathway analysis were performed. Results In this study, we identified altered genes involved in E. faecalis infection in the gastric cell line MKN74 and the relevant pathways to understand whether the infection slows down cancer progression. Twelve genes corresponding 15 probe sets were downregulated following the live infection of gastric cancer cells with E. faecalis. We identified a network between these genes and pathways they belong to. Pathway analysis showed that these genes are mostly associated with cancer cell proliferation. Conclusion NDC80, NCAPG, CENPA, KIF23, BUB1B, BUB1, CASC5, KIF2C, CENPF, SPC25, SMC4, and KIF20A genes were found to be associated with gastric cancer pathogenesis. Almost all of these genes are effective in the proliferation of cancer cells, especially during the infection process. Therefore, it is hypothesized that downregulation of these genes may affect gastric cancer pathogenesis by reducing cell proliferation. And, it is predicted that E. faecalis infection may be an important factor for gastric cancer.

Cancer immunotherapy with adoptive transfer of tumor infiltrating lymphocytes (TILs) represents an effective treatment for patients with metastatic melanoma, with the objective regressions in up to 72% of patients in three sequential pilot clinical trials. However, the antigen targets recognized by effective TILs remain largely unclear. Melanoma patients 2359 and 2591 both experienced durable complete regressions of metastases ongoing beyond five years following adoptive TIL transfer. A novel approach was developed to identify mutated T-cell antigens by screening a tandem minigene library, which comprised non-synonymous mutation sequences identified by whole-exome sequencing of autologous tumors. The screening of tandem minigene libraries resulted in the identification of mutated kinesin family member 2C (KIF2C) antigen as a target of TIL 2359, and mutated DNA polymerase alpha subunit B (POLA2) antigen as a target of TIL 2591. Both KIF2C and POLA2 have been found to play important roles in cell proliferation. These findings suggest that the minigene screening approach may facilitate the antigen repertoire analysis of tumor reactive T cells, and lead to the development of novel adoptive cell therapies based on the in vitro stimulation of T cells that recognize candidate mutated antigens derived from genes essential for the carcinogenesis.

Background: Recently, studies have shown that kinesins(KIF) play an important role in the occurrence and development of many tumors. However, there is no complete understanding of the role of KIF family in Pan cancer, and its role in the immunity and tumor microenvironment (TME) is unclear.Methods: Based on TCGA database and integrated several R packages, we explored the relationship between the expression of KIF genes and patient survival, immune subtypes, TME, tumor stem cell correlation, and drug sensitivity in cancer.Results: We use nine highly expressed KIF genes(KIF2C, KIF4A, KIF7, KIF11, KIF14, KIF18A, KIF18B, KIF20A, KIF20B) to represent whole KIF family. The change in KIF gene expression was significantly related to overall survival. The nine KIFs' high expression is accompanied by the up-regulation of C1 immune subtype, which is related to cell proliferation and interruption of immune process. Further, KIF gene expression showed significant correlation and cancer cell stemness characteristics. Top25 relevant KIF-drug pairs were displayed according to their P values. We further discussed KIF family influence in Mesothelioma(MESO) and Sarcoma(SARC). The CIBERSORT results manifested that increased level of infiltration of B cells naive, Mast cells resting and NK cells activated could be used as a protective factor to promote survival.Conclusions: Our study supplemented a complete map of the effect of KIF family in Pan cancer. We suggested that KIF family may be a potential target for cancer therapy.

Blood vessels in the brain tissue form a compact vessel structure and play an essential role in maintaining the homeostasis of the neurovascular system. The low dosage of photodynamic intervention (PDT) significantly affects the expression of cellular biomarkers. To understand the impact of photodynamic interventions on cerebrovascular endothelial cells, we evaluated the dosage-dependent impact of porfimer sodium-mediated PDT on B.END3 cells using flow cytometer, comet assay, RNA sequencing, and bioinformatics analysis. To examine whether PDT can induce disorder of intracellular organelles, we did not observe any significance damage of DNA and cellular skeleton. Moreover, expression levels of cellular transporters-related genes were significantly altered, implying the drawbacks of PDT on cerebrovascular functions. To address the potential molecular mechanisms of these phenotypes, RNA sequencing and bioinformatics analysis were employed to identify critical genes and pathways among these processes. The gene ontology (GO) analysis and protein-protein interaction (PPI) identified 15 hub genes, highly associated with cellular mitosis process (CDK1, CDC20, MCM5, MCM7, MCM4, CCNA2, AURKB, KIF2C, ESPL1, BUB1B) and DNA replication (POLE2, PLOE, CDC45, CDC6). Gene set enrichment analysis (GSEA) reveals that TNF-α/NF-κB and KRAS pathways may play a critical role in regulating expression levels of transporter-related genes. To further perform qRT-PCR assays, we find that TNF-α/NF-κB and KRAS pathways were substantially up-regulated, consistent with GSEA analysis. The current findings suggested that a low dosage of PDT intervention may be detrimental to the homeostasis of blood-brain barrier (BBB) by inducing the inflammatory response and affecting the expression of surface biomarkers.

Background: A serious issue derived from Prostate adenocarcinoma (PCa) is its propensity to metastasize to bone, which occurred in up to 90% of patients with advanced PCa. The kinesin superfamily (KIFs) is well-documented oncogenic protein implicated mainly in chromosomal and spindle movements and are involved in some cellular activities, such as mitosis, transport of vesicles, organelles, and mRNAs. However, the clinical significance and biological roles of KIF in bone metastasis of PCa still need further exploration.Method: We download three datasets from the Gene Expression Omnibus (GEO) data repository. Firstly, we merge the three datasets, and then obtain the gene modules most relevant with clinical traits(morbidity of the bone metastasis of PCa) by “WGCNA” R package. Functional enrichment analysis was performed by the DAVID tool and Metascape. Differentially expressed genes (DEGs) between bone metastasis of PCa and primary PCa tissue samples were identified by “limma” R package. Then we intersect the gene module with DEGs. Protein-protein interaction (PPI) network was constructed by Cytoscape, and hub genes were excavated. Immunohistochemistry (IHC) image was downloaded from The Human Protein Atlas (www.proteinatlas.org) to verify the feasibility of the target molecular marker identified by bioinformatics and statistical analysis.Result:16 gene modules were obtained through WGCNA analysis and the tan module is most related to the occurrence of bone metastasis, containing 147 genes. Thus, we selected the tan module for further analysis. 877 DEGs were detected by limma package of R software. After taking the intersection of the DEGs and tan module, we got 51 common genes. Protein-protein interaction network (PPI) was constructed for the 51 genes. 7 hub genes (BUB1, KIF2C, RACGAP1, CENPE, KIF11, TTK, KIF20A) were identified from the common results of four different algorithms (Betweenness, Closeness, EcCentricity, and Radiality). Survival analysis based on disease free survival (DFS) was carried out for the 7 hub genes, and all of them have significant poor prognostic performance (PConclusion: In current study, molecules strongly correlated with the occurrence of bone metastasis of PCa were excavated. And provide the evidence that KIF11 may serve as a potential bone metastasis marker in PCa, which might be used for the guidance of clinical practice.

Background: Cancer stem cells (CSCs), which are characterized by self-renewal and plasticity, are highly correlated with tumor metastasis and drug resistance. To fully understand the role of CSCs in colorectal cancer (CRC), we evaluated the stemness traits and prognostic value of stemness-related genes in CRC.Methods: In this study, the data from 616 CRC patients from The Cancer Genome Atlas (TCGA) were assessed and subtyped based on the mRNA expression-based stemness index (mRNAsi). The correlations of cancer stemness with the immune microenvironment, tumor mutational burden (TMB), and N6-methyladenosine (m6A) RNA methylation regulators were analyzed. Weighted gene co-expression network analysis (WGCNA) was performed to identify the crucial stemness-related genes and modules. Furthermore, a prognostic expression signature was constructed using the Lasso-penalized Cox regression analysis. The signature was validated via multiplex immunofluorescence staining of tissue samples in an independent cohort of 48 CRC patients.Results: This study suggests that high-mRNAsi scores are associated with poor overall survival in stage IV CRC patients. Moreover, the levels of TMB and m6A RNA methylation regulators were positively correlated with mRNAsi scores, and low-mRNAsi scores were characterized by increased immune activity in CRC. The analysis identified 34 key genes as candidate prognosis biomarkers. Finally, a three-gene prognostic signature (PARPBP, KNSTRN, and KIF2C) was explored together with specific clinical features to construct a nomogram, which was successfully validated in an external cohort.Conclusion: There is a unique correlation between CSCs and the prognosis of CRC patients, and the novel biomarkers related to cell stemness could accurately predict the clinical outcomes of these patients.

BackgroundNo immunomodulatory drug has ever demonstrated its efficacy in primary Sjögren’s Syndrome (pSS). Drug repurposing, or drug repositioning, refers to the use in another disease of an existing drug, originally approved or evaluated in a different disease.ObjectivesThe objective of our study was to repurpose existing therapeutic drugs in pSS using a transcriptomic approach.MethodsWe generated pSS transcriptomic signatures from peripheral blood samples of patients with pSS compared to healthy controls in two cohorts (ASSESS and a Norwegian cohort) and data mined available pSS transcriptomic signatures in public databases. We compared each disease signature to transcriptomic signatures, obtained from the biological action of 2837 drugs, 2160 knock-in and 3799 knock-down genes, available in the Connectivity Map database. A median similarity score with regard to disease signatures was computed for each candidate drug/gene. Drugs and genes were selected if p│80│. If this score is sufficiently high and statistically significant (>80, pFigure 1.Methods of drug-repurposing transcriptomic analysis (adapted from Toro-Dominguez et al, Arthritis Res Ther 2017;19:54)Results1091 peripheral blood transcriptomes were analyzed from 6 independent studies (906 patients with pSS and 185 healthy controls). Our analysis identified 11 transcriptomic drug signatures significantly associated with pSS signature. We identified 72 transcriptomic knock-in (11) or knock-down (61) gene signatures significantly associated with that of pSS, including 21 with a negative similarity score (Table 1).Table 1.Knock-down and knock-in genes significantly associated with the pSS transcriptomic signaturesType ofexperimentSimilarity scoreGenesNumber of genesKnock-in+IFNG, DUSP28, IFNB1, LYN, BCL2L2, TNFRSF1A, CD40, BCL10, NLK, ZNF39810-SLC52A2111Knock-down+SLC25A14, GOLIM4, DTYMK, DCXR, RRM2, IMPA1, CLTB, F12, CAB39, ID1, ISOC1, UBAP1, HIGD2A, UFD1L, SOD2, BTG1, PRKCI, HIST2H2BE, NISCH, TEAD4, MTX2, TYK2, GTF2B, NDUFS7, NNT, ACADSB, GSTP1, HOMER2, SORBS3, PCK2, PHB2, PDXK, TES, TM9SF2, TBX2, HOXA6, KIF2C, MED1, NR2F6, CD14, BECN141-TM9SF3, E2F3, PRMT3, KD, PKN2, SUCLA2, CD44, GRN, SP3, ATP5S, MYCBP2, TRAF7, POLA2, ADRB2, PSMG1, PPP2R3C, PMAIP1, ETFA, ANKRD37, SPECC1L2061Type I and II interferons were highly ranked (similarity score >99), and their overexpression mimicked the disease signature. CD40 appeared also as a very relevant target (similarity score = 98.8). Three drugs had a significant negative similarity score: ampicillin (-88.69, p=0.0019), amylocaine (-88.28, p=0.0026), and droxinostat (-85.42, p=0.0027). Droxinostat is a HDAC inhibitor. HDAC activity has been shown to be an essential element of the coactivation system for IFN-induced gene regulation and the IFN-induced innate immune response.ConclusionThis first drug repositioning transcriptomic approach in Sjögren’s syndrome confirms the interest of targeting interferons and identifies histone deacetylases as potential therapeutic targets.AcknowledgementsInvestigators of the ASSESS cohort: Emmanuelle Dernis, Valerie Devauchelle-Pensec, Philippe Dieude, Jean-Jacques Dubost, Anne-Laure Fauchais, Vincent Goeb, Eric Hachulla, Pierre Yves Hatron, Claire Larroche, Véronique Le Guern, Jacques Morel, Aleth Perdriger, Carinne Salliot, Stephanie Rist, Alain Saraux, Jean Sibilia, Olivier Vittecoq, Gaétane Nocturne, Philippe Ravaud, Raphaèle SerorCentre de Ressources Biologiques de l’Hôpital Bichat: Sarah TubianaJohan G. Brun for contributing to the Norwegian cohort.Funding SourcesThis work was supported by the Innovative Medicines Initiative 2 Joint Undertaking (IMI 2 JU) (NECESSITY grant 806975). The Joint Undertaking received support from the European Union’s Horizon 2020 Research and Innovation Program and from the European Federation of Pharmaceutical Industries and Associations. This work was also supported by R01 AR065953 Beth the NIH, United States. The contents are the sole responsibility of the authors and do not necessarily the official views of the NIH.JEG received an unrestricted grant from Bristol-Myer-Squibbs to do the transcriptomic analysis of the ASSESS and Norwegian cohorts. JEG received a grant from Geneviève Garnier (Association Française du Syndrome de Gougerot-Sjögren et des syndromes secs).The ASSESS cohort is promoted by the French Society of Rheumatology and received two research grants from the French Society of Rheumatology.The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Disclosure of InterestsRenaud FELTEN: None declared, Tao Ye: None declared, Cédric Schleiss: None declared, Benno Schwikowski: None declared, Jean Sibilia: None declared, Fanny Monneaux: None declared, Hélène Dumortier: None declared, Roland Jonsson: None declared, Christopher Lessard: None declared, Wan Fai Ng: None declared, Tsutomu Takeuchi: None declared, Xavier Mariette: None declared, Jacques-Eric Gottenberg Grant/research support from: JEG received an unrestricted grant from Bristol-Myer-Squibbs to do the transcriptomic analysis of the ASSESS and Norwegian cohorts.

Background Basal-like breast cancer (BLBC) is the most aggressive subtype of breast cancer (BC) and links to poor outcomes. As the molecular mechanism of BLBC has not yet been completely discovered, identification of key pathways and hub genes of this disease is an important way for providing new insights into exploring the mechanisms of BLBC initiation and progression. Objective The aim of this study was to identify potential gene signatures of the development and progression of the BLBC via bioinformatics analysis. Methods and results The differential expressed genes (DEGs) including 40 up-regulated and 21 down-regulated DEGs were identified between GSE25066 and GSE21422 microarrays, and these DEGs were significantly enriched in the terms related to oncogenic or suppressive roles in BLBC progression. In addition, KEGG pathway and GSEA (Gene Set Enrichment Analysis) enrichment analyses were performed for DEGs between the basal type and non-basal-type breast cancer from GSE25066 microarray. These DEGs were enriched in pathways such as cell cycle, cytokine-cytokine receptor interaction, chemokine signaling pathway, central carbon metabolism signaling and TNF signaling pathway. Moreover, the protein-protein interaction (PPI) network was constructed with those 61 DEGs using the Cytoscape software, and the biological significance of putative modules was established using MCODE. The module 1 was found to be closely related with a term of mitosis regulation and enriched in cell cycle pathway, and thus confirmed the pathological characteristic of BLBC with a high mitotic index. Furthermore, prediction values of the top 10 hub genes such as CCNB2, BUB1, NDC80, CENPE, KIF2C, TOP2A, MELK, TPX2, CKS2 and KIF20A were validated using Oncomine and Kaplan-Meier plotter. Conclusion Our results suggest the intriguing possibility that the hub genes and modules in the PPI network contributed to in-depth knowledge about the molecular mechanism of BLBC, paving a way for more accurate discovery of potential treatment targets for BLBC patients.

Kaidi Yang,1,2 Jian Gao,3 Mao Luo1,4,5 1Key Laboratory of Medical Electrophysiology of Ministry of Education, Collaborative Innovation Center for Prevention and Treatment of Cardiovascular Disease of Sichuan Province, Southwest Medical University, Luzhou, China; 2Key Laboratory of Tumor Immunology, The First Affiliated Hospital, Army Medical University, Chongqing, China; 3Department of Life Sciences and Technology, Yangtze Normal University, Chongqing, China; 4Drug Discovery Research Center, Southwest Medical University, Luzhou, Sichuan, China; 5Laboratory for Cardiovascular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou, Sichuan, China Background: Basal-like breast cancer (BLBC) is the most aggressive subtype of breast cancer (BC) and links to poor outcomes. As the molecular mechanism of BLBC has not yet been completely discovered, identification of key pathways and hub genes of this disease is an important way for providing new insights into exploring the mechanisms of BLBC initiation and progression.Objective: The aim of this study was to identify potential gene signatures of the development and progression of the BLBC via bioinformatics analysis. Methods and results: The differential expressed genes (DEGs) including 40 up-regulated and 21 down-regulated DEGs were identified between GSE25066 and GSE21422 microarrays, and these DEGs were significantly enriched in the terms related to oncogenic or suppressive roles in BLBC progression. In addition, KEGG pathway and GSEA (Gene Set Enrichment Analysis) enrichment analyses were performed for DEGs between the basal type and non-basal-type breast cancer from GSE25066 microarray. These DEGs were enriched in pathways such as cell cycle, cytokine-cytokine receptor interaction, chemokine signaling pathway, central carbon metabolism signaling and TNF signaling pathway. Moreover, the protein-protein interaction (PPI) network was constructed with those 61 DEGs using the Cytoscape software, and the biological significance of putative modules was established using MCODE. The module 1 was found to be closely related with a term of mitosis regulation and enriched in cell cycle pathway, and thus confirmed the pathological characteristic of BLBC with a high mitotic index. Furthermore, prediction values of the top 10 hub genes such as CCNB2, BUB1, NDC80, CENPE, KIF2C, TOP2A, MELK, TPX2, CKS2 and KIF20A were validated using Oncomine and Kaplan-Meier plotter. Conclusion: Our results suggest the intriguing possibility that the hub genes and modules in the PPI network contributed to in-depth knowledge about the molecular mechanism of BLBC, paving a way for more accurate discovery of potential treatment targets for BLBC patients. Keywords: basal-like breast cancer, bioinformatics, differentially expressed genes, hub genes, molecular mechanism &nbsp

Background Recent evidences indicated that shear stress is critical in orchestrating gene expression in cardiovascular disease. It is necessary to identify the mechanism of shear stress influencing gene expression in physiology and pathophysiology conditions. This paper aimed to identify candidate hub genes and its transcription factors with bioinformatics. Methods We analyzed microarray expression profile of GSE16706 to identify differentially expressed genes (DEGs) in low shear stress (1 dyne/cm2) treated human umbilical vein endothelial cells (HUVECs) compared with static condition for 24 h. Results 652 DEGs, including 333 up-regulated and 319 down-regulated DEGs, were screen out. Functional enrichment analysis indicated enrichment items mainly included cytokine-cytokine receptor interaction and cell cycle. Five hub genes (CDC20, CCNA2, KIF11, KIF2C and PLK1) and one significant module (score = 17.39) were identified through protein–protein interaction (PPI) analysis. Key transcriptional factor FOXC1 displayed close interaction with all the hub genes via gene-transcriptional factor network. Single-gene GSEA analysis indicated that CDC20 was linked to the G2M_CHECKPOINT pathway and cell cycle pathway. Conclusions By using integrated bioinformatic analysis, a new transcriptional factor and hub-genes network related to HUVECs treated with low shear stress were identified. The new regulation mechanism we discovered may be a promising potential therapeutic target for cardiovascular disease.

Background: Breast cancer (BC) is a malignancy with a high incidence among women in the world, and it is very urgent to identify significant biomarkers and molecular therapy methods.Methods: Total 58 normal tissues and 203 cancer tissues were collected from three Gene Expression Omnibus (GEO) gene expression profiles, and the differential expressed genes (DEGs) were identified. Subsequently, the Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genome (KEGG) pathway were analyzed. Additionally, hub genes were screened by constructing a protein-protein interaction (PPI) network. Then, we explored the prognostic values and molecular mechanism of these hub genes Kaplan-Meier (KM) curve and Gene Set Enrichment Analysis (GSEA). Results: 42 up-regulated and 82 down-regulated DEGs were screened out from GEO datasets. GO and KEGG pathway analysis revealed that DEGs were mainly related to cell cycles and cell proliferation. Furthermore, 12 hub genes (FN1, AURKA, CCNB1, BUB1B, PRC1, TPX2, NUSAP1, TOP2A, KIF20A, KIF2C, RRM2, ASPM) with a high degree of genes were selected, among which, 11 hub gene were significantly correlated with the prognosis of patients with BC. From GSEA reviewed correlated with KEGG_CELL_CYCLE and HALLMARK_P53_PATHWAY. Conclusion: this study identified 11 key genes as BC potential prognosis biomarkers on the basis of integrated bioinformatics analysis. This finding will improve our knowledge of the BC progress and mechanisms.

BRCA2 is an oncoprotein frequently mutated in hereditary breast cancers. To improve the diagnosis of these cancers, several molecular studies have identified BRCA2 key positions and characterized mutations in these regions causing a BRCA2 loss of function. However, these studies mainly focused on the C-terminal globular domain of BRCA2. Here, we characterized the N-terminal region of BRCA2 from aa 48 to aa 284 (BRCA2₄₈₋₂₈₄). This well-conserved region is disordered, i.e. it lacks stable secondary structure (Julien et al. 2020 Biomol. NMR Assign). It is also highly phosphorylated by the kinase Plk1 at the entry into mitosis. However, previous studies using mass spectrometry didn’t allow to precisely identify all the phosphorylation sites, limiting their characterization. To circumvent this problem, we used real-time NMR to monitor phosphorylations of the N-terminal region of BRCA2, at the residue level. We developed 2 protocols for disordered regions allowing phosphorylation in a large range of temperatures and pHs (Julien et al. 2020 Methods Mol. Biol; Alik et al. 2020 An- gew. Chem.). Then, we identified that Plk1 phosphorylates BRCA2 at 2 conserved positions: pS193 and pT207. We further searched for the function of these phosphoresidues. First, we identified by biophysical methods that BRCA2pT207 creates a docking site for the regulatory domain of Plk1. In collaboration with the group of Dr. Aura Carreira, we showed that this interaction contributes to the assembly of a quaternary complex involving BRCA2, Plk1, BubR1 and PP2A that regulates chromosome alignment in mitosis (Ehlen et al. 2020. Nat Commun.). We also demonstrated that breast cancer variants impact the phosphorylation of BRCA2 and the formation of the complex in vitro and in cell. Then, we per- formed proteomics experiments to identify new mitotic partners specific to phospho-BRCA2, and found Plk1 as well as other proteins involved in mitosis. I started the characterization of two new BRCA2 partners: Ki2C and Chk2. We also explored the role of Cdk1 phosphorylation of BRCA2T77 on further Plk1 phosphorylation. We found that early BRCA2T77 phosphorylation increases the phosphoryla- tion rate of BRCA2S193 by Plk1. Finally, we initiated a project about the Plk1 kinase, an interesting cancer-target as it is often overexpressed in several cancers, including breast cancers. Here, I produced several constructs of the kinase for further structural characterization., BRCA2 est une oncoprotéine fréquemment mutée dans les cancers du sein héréditaires. Pour améliorer le diagnostic de ces cancers, plusieurs études moléculaires ont localisées des régions clés de BRCA2 et ont caractérisées l’impact de mutations sur les fonctions portées par ces régions. Ici, je m’intéresse à la région aa 48 à aa 284 (BRCA2₄₈₋₂₈₄) de la protéine. Cette région conservée est désordonnée (Julien et al. 2020 Biomol. NMR Assign), c.à.d. qu’elle ne contient pas de structure secondaire stable. Cette région est également phosphorylée par la kinase Plk1 à l’entrée en mitose. Cependant, des études précédentes utilisant la spectrométrie de masse n’ont pas permis d’identifier précisément les sites phosphorylés, limitant ainsi leur caractérisation fonctionnelle. Pour contourner ce problème, nous avons utilisé la RMN en temps réel pour identifier et caractériser les phosphorylations de BRCA2₄₈₋₂₈₄, à l’échelle du résidu. Nous avons développé deux protocoles permettant d’étudier la phosphorylation de régions désordonnées pour une grande gamme de pH et températures (Julien et al. 2020 Methods Mol. Biol; Alik et al. 2020 Angew. Chem.). Ainsi, nous avons identifié que Plk1 phosphoryle BRCA2₄₈₋₂₈₄ sur deux sites conservés : pS193 et pT207. Ceci. Nous a servi de base pour la caractérisation de ces sites. D’abord, nous avons identifié grâce à des méthodes biophysiques que BRCA2pT207 est un site d’interaction pour le domaine régulateur de Plk1. En collaboration avec l’équipe de Dr. Aura Carreira, nous avons montré que cette interaction est à la base d’un complexe quaternaire (BRCA2, Plk1, BubR1 et PP2A) qui régule l’alignement des chromosomes en métaphase (Ehlen et al. 2020. Nat Commun.). Nous avons aussi démontré que des mutations de BRCA2 issues de patientes ont un impact sur la phosphorylation de BRCA2 et la formation du complexe. Puis, nous avons réalisé des expériences de protéomique pour identifier de nouveau partenaires mitotiques reconnaissant pBRCA2₄₈₋₂₈₄. Nous avons identifié Plk1 et d’autres protéines impliquées dans la mitose. J’ai débuté l’analyse structurale de deux nouveaux partenaires prometteurs: Kif2C et Chk2. Nous avons aussi étudié le rôle de la préphosphorylation de BRCA2T77 par Cdk sur la phosphorylation par Plk1. Nous avons trouvé que BRCA2pT77 favorisait la phosphorylation de BRCA2S193 par Plk1. Enfin, nous avons initié une étude structurale sur la kinase Plk1, surexprimée dans de nombreux cancers dont le cancer du sein. Ici, j’ai produit plusieurs constructions de la kinase qui serviront à sa caractérisation structurale.

BACKGROUND: Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer with high rates of metastasis and recurrence. Conventional clinical treatments are ineffective for it as it lacks therapeutic biomarkers. Figuring out the biomarkers related to TNBC will be beneficial for its clinical treatment and prognosis. METHODS: Five independent datasets downloaded from the Gene Expression Omnibus database were merged to identify differentially expressed genes between TNBC and non-TNBC samples by using the MetaDE.ES method followed by mapping the differentially expressed genes into a protein-protein interaction network. Meanwhile, the weighted gene co-expressed network analysis (WGCNA) of The Cancer Genome Atlas data was performed to screen the hub genes. The gene functional analyses were conducted by Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. The correlation between gene expression level and patient overall survival was evaluated by survival analysis. RESULTS: A total of 11 differentially expressed genes (CDH1, SP1, MYC, FAF2, IFI16, MDM2, AR, DBN1, HSPB1, FLNA, YWHAB) were obtained from the protein-protein interaction network with degree >10. WGCNA revealed 5 hub genes (TPX2, CTPS1, KIF2C, MELK, CDCA8) that were significantly associated with TNBC. Cell cycle, oocyte meiosis, spliceosome were the pathways significantly enriched in these genes according to GO functionally annotated terms and KEGG pathways analysis. The Kaplan-Meier curves showed that the expression levels of HSPB1, IFI16, TPX2 were significantly associated with the survival time of TNBC patients (P

Background: Liver hepatocellular carcinoma (LIHC) is one of the most common malignant cancers worldwide, the overall prognosis of LIHC remains unsatisfactory. Valuable prognostic biomarkers are still urgently needed for LIHC. This study aimed to explore hub genes associated with the prognosis of LIHC and tumor microenvironmental immune infiltration, providing potential prognostic biomarker and therapeutic target for LIHC. Methods: RNA-seq counts data for LIHC samples were obtained from TCGA database. RNA-seq counts data for normal liver samples were obtained from GTEx database. Weighted gene co-expression network analysis (WGCNA) was used to cluster differentially expressed genes with similar expression profiles to form modules and significant modules and key genes were screened. Next, these genes was verified by cox analyses and overall survival analysis. Further, CIBERSORT was used to explore the relationship between these genes and tumor infiltrating immune cells. Results: A total number of 2661 significant DEGs were included for consensus WGCNA analysis, which identified 6 modules. Blue module (r=0.85, p CDC20, CDCA5, CDCA8, KIF2C and KIFC1 were identified as five potential marker genes, which would result in an unfavorable prognosis in LIHC. Further CIBERSORT analysis showed these novel biomarkers expression levels in LIHC were positively correlated with activated memory CD4+ T cells, follicular helper T cells, regulatory T cells and macrophages M0. While, resting memory CD4+ T cells, monocytes, macrophages M2, resting mast cells showed a negative correlation with the 5 novel biomarkers expression levels. Conclusions: The study screened 5 genes with marked prognostic capability for LIHC and found these genes were correlated with the infiltration of immune cells in LIHC tumor microenvironment. The findings might provide a more detailed molecular mechanism underlying LIHC occurrence and progression, holding promise for acting as potential biomarkers and therapeutic targets.

Background: Cancer stem cells (CSCs), which are characterized by self-renewal and plasticity, are highly correlated with tumor metastasis and drug resistance. To fully understand the role of CSCs in colorectal cancer (CRC), we evaluated the stemness traits and prognostic value of stemness-related genes in CRC. Methods: In this study, the data from 616 CRC patients from The Cancer Genome Atlas (TCGA) were assessed and subtyped based on the mRNA expression-based stemness index (mRNAsi). The correlations of cancer stemness with the immune microenvironment, tumor mutational burden (TMB) and N6-methyladenosine (m6A) RNA methylation regulators were analyzed. Weighted gene co-expression network analysis (WGCNA) was performed to identify the crucial stemness-related genes and modules. Furthermore, a prognostic expression signature was constructed using Lasso-penalized Cox regression analysis. The signature was validated via multiplex immunofluorescence staining of tissue samples in an independent cohort of 48 CRC patients. Results: This study suggests that high mRNAsi scores are associated with poor overall survival in stage IV CRC patients. Moreover, the levels of TMB and m6A RNA methylation regulators were positively correlated with mRNAsi scores, and low mRNAsi scores were characterized by increased immune activity in CRC. The analysis identified 2 key modules and 34 key genes as prognosis-related candidate biomarkers. Finally, a 3-gene prognostic signature (PARPBP, KNSTRN and KIF2C) was explored together with specific clinical features to construct a nomogram, which was successfully validated in an external cohort. Conclusions: There is a unique correlation between CSCs and the prognosis of CRC patients, and the novel biomarkers related to cell stemness could accurately predict the clinical outcomes of these patients. Funding: None Declaration of Interest: The authors declare no conflict of interest. Ethical Approval: This study was approved by Institutional Review Board of National Cancer Center (NCC), Chinese Academy of Medical Sciences (approval no. 2017–20). All the patients’ samples used in this study have obtained necessary consent.

Breast cancer is one of the most common malignant tumors in women worldwide. Early diagnosis, treatment, and prognosis of breast cancer are global challenges. Identification of valid predictive diagnosis and prognosis biomarkers and drug targets are crucial for breast cancer prevention. This study characterizes differentially expressed genes (DEGs) based on the TCGA database by using DESeq2, edgeR, and limma. A total of 2032 DEGs, including 1026 up-regulated genes and 1006 down-regulated genes were screened. Followed with WGCNA, PPI analysis, GEPIA 2, and HPA database verification, thirteen hub genes including CDK1, BUB1, BUB1B, CDC20, CCNB2, CCNB1, KIF2C, NDC80, CDCA8, CENPF, BIRC5, AURKB, PLK1, MAD2L1, and CENPE were obtained, and they may serve as potential therapeutic targets of breast cancer. Especially, overexpression of CCNB1 and PLK1 are strongly associated with the low survival rate of breast cancer patients, demonstrating their potentiality as prognostic markers. Moreover, CCNB1 and PLK1 are highly expressed in all breast cancer stages, suggesting that they could be further studied as potential drug targets. Taken together, our study highlights CCNB1 and PLK1 as potential anti-breast cancer drug targets and prognostic markers.

Synovial sarcoma (SS) is a malignant soft tissue sarcoma and its natural history is a long, indolent clinical course followed by high rate of local recurrence and distant metastasis. Current therapies are still limited in increasing satisfactory of 5-year survival, especially for patients with recurrence and metastasis. Accordingly, finding new therapeutic drug for SS treatment is clinically urgent need. Diallyl trisulfide (DATS), a bioactive compound derived from garlic, is reported as a promising anti-cancer agent for various carcinomas. However, its effect on anti-SS remains unknown. This study investigated the anti-SS effect of DATS in human synovial sarcoma SW982 cells.CCK-8 assay were used to examine the cell viability. High-content Imaging System was used to examine the apoptosis, intracellular ROS and autophagy. Flow cytometry was used to detect cell cycle. qPCR and Western blot were used to examine the expression of related mRNA and protein. High-throughput RNA-sequencing and bio-information analysis were used to investigate the mRNA profiling.The results showed a suppressive effect of DATS on tumor biology of SW982 cells including inducing apoptosis, triggering G2/M cell cycle arrest, elevating intracellular ROS and damaging mitochondria. Further high-throughput RNA-sequencing analysis clarified a comprehensive molecular portrait for DATS-induced transcriptional regulation. Besides, protein-protein interaction (PPI) analysis demonstrated that a network consisted of FOXM1, CCNA2, CCNB1, MYBL2, PLK1 and CDK1 might be response for DATS-induced G2/M cell cycle arrest and increased intracellular ROS. Notably, protein feature analysis revealed structure enrichment in microtubule network like kinesin motors domain, and tubulin domain. Molecular function analysis suggested that DATS-induced dysfunction of microtubule network might be the major cause for its effect on cell cycle arrest and successive apoptosis. Furthermore, 28 hub genes (including KIF2C, PLK1, CDK1, BIRC5, CCNB2, CENPF, TPX2, TOP2A and so on) were determined. Finally, pathway analysis showed that DATS-induced differentially expressed genes were mainly involved in cell cycle.Collectively, our findings for the first time provided the DATS-induced cellular response and transcriptional profiling of SW982 cells, which proposes that suppression of DATS on SS is multi-targeted and represent a therapeutic evidence for SS.

The purpose of the study is to identify potential key genes and pathways, using bioinformatics, underlying the potentially common molecular mechanisms between endometriosis (EMS) and ovarian cancer (OC). Two datasets were collected from the Gene Expression Omnibus database, and the limma package identified common differentially expressed genes (DEGs) in the EMS and OC groups compared to controls. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, gene interaction network, and module analyses identified the enriched pathways associated with DEGs. A protein–protein interaction (PPI) network was then constructed, and the CytoHubba plugin of Cytoscape was used to calculate the degree of connectivity for proteins in the PPI network. A total of 571 overlapping DEGs were identified between EMS and OC (vs. controls). Enriched DEGs were associated with 36 gene ontology terms and 7 Kyoto Encyclopedia of Genes and Genomes pathways, which were mainly associated with deactivation of the p53 signaling pathway. The Kaplan–Meier plotter platform confirmed the expression of the identified hub genes, and survival analysis suggested that CCNB1, CCNB2, BUB1B, CCNA2, KIF2C, and TOP2A are associated with decreased survival and disease-free survival rates of OC. The key pathways identified herein elucidate the possible mechanism by which EMS evolves into OC; further, the identified hub genes may serve as potential biomarkers to predict OC occurrence and prognosis.

Aim: To investigate whether long non-coding RNAs (lncRNAs) can be utilized as molecular biomarkers in predicting the occurrence and progression of chromophobe renal cell carcinoma. Methods & results: Genetic and related clinical traits of chromophobe renal cell carcinoma were downloaded from the Cancer Genome Atlas and used to construct modules using weighted gene coexpression network analysis. In total, 44,889 genes were allocated into 21 coexpression modules depending on intergenic correlation. Among them, the green module was the most significant key module identified by module–trait correlation calculations ( R 2 = 0.43 and p = 4e-04). Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses demonstrated that genes in the green module were enriched in many pathways. Coexpression, protein–protein interaction networks, screening for differentially expressed genes, and survival analysis were used to select hub lncRNAs. Five hub lncRNAs ( TTK, CENPE, KIF2C, BUB1, and RAD51AP1) were selected out. Conclusion: Our findings suggest that the five lncRNAs may act as potential biomarkers for chromophobe renal cell carcinoma progression and prognosis.

Anaplastic thyroid carcinoma (ATC) is a rare type of thyroid cancer that results in fatal clinical outcomes; the pathogenesis of this life-threatening disease has yet to be fully elucidated. This study aims to identify the hub genes of ATC that may play key roles in ATC development and could serve as prognostic biomarkers or therapeutic targets. Two microarray datasets (GSE33630 and GSE53072) were obtained from the Gene Expression Omnibus database; these sets included 16 ATC and 49 normal thyroid samples. Differential expression analyses were performed for each dataset, and 420 genes were screened as common differentially expressed genes using the robust rank aggregation method. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were conducted to explore the potential bio-functions of these differentially expressed genes (DEGs). The terms and enriched pathways were primarily associated with cell cycle, cell adhesion, and cancer-related signaling pathways. Furthermore, a protein-protein interaction network of DEG expression products was constructed using Cytoscape. Based on the whole network, we identified 7 hub genes that included CDK1, TOP2A, CDC20, KIF11, CCNA2, NUSAP1, and KIF2C. The expression levels of these hub genes were validated using quantitative polymerase chain reaction analyses of clinical specimens. In conclusion, the present study identified several key genes that are involved in ATC development and provides novel insights into the understanding of the molecular mechanisms of ATC development.

Alternative splicing (AS) contributes to gene diversification in cells, but the importance of AS during germline development remains largely undefined. Here, we interrupted pre-mRNA splicing events controlled by epithelial splicing regulatory protein 1 (ESRP1) and found that it induced female infertility in mice. Germline-specific knockout of Esrp1 perturbed spindle organization, chromosome alignment, and metaphase-to-anaphase transformation in oocytes. The first polar body extrusion (PBE) was blocked during oocyte meiosis and was found to be due to abnormal activation of spindle assembly checkpoint (SAC) and insufficiency of anaphase-promoting complex/cyclosome (APC/C) in Esrp1-knockout oocytes. Esrp1-knockout in oocytes hampered follicular development and ovulation; eventually, premature ovarian failure (POF) occurred in six-month-old Esrp1-knockout mouse. Using single-cell RNA sequencing analysis, 528 aberrant AS events of maternal mRNA transcripts were revealed and were preferentially associated with microtubule cytoskeletal organization in Esrp1-knockout oocytes. Notably, we found that loss of ESRP1 disturbed a comprehensive set of gene-splicing sites—including those within Trb53bp1, Rac1, Bora, Kif2c, Kif23, Ndel1, Kif3a, Cenpa, and Lsm14b—that ultimately caused abnormal spindle organization. Taken together, our findings provide the first report elucidating the AS program of maternal mRNA transcripts, mediated by the splicing factor, ESRP1, that is required for oocyte meiosis and female fertility in mice.