AURKA is one of the downstream targets of MAPK1/ERK2 in pancreatic cancer

Differential Response and Resistance to KRAS-Targeted Therapy

KRAS is the most frequently mutated oncogene. In epithelial malignancies such as lung, colorectal, and pancreatic tumors, KRAS is mutated in 25 to above 90% cases. KRAS was considered undruggable for over three decades until the recent development of covalent inhibitors targeting the KRAS G12C mutant. The recent approval of the KRAS G12C inhibitors sotorasib and adagrasib has ushered in a new era of KRAS-targeted therapy. Despite this success, a major challenge in KRAS-targeted therapy is intrinsic and acquired resistance to KRAS inhibitors. Clinical studies have shown that many patients with KRAS G12C cancers did not respond to sotorasib and adagrasib. Colorectal cancer, in particular, has a markedly lower response rate to KRAS G12C inhibitors compared to non-small cell lung cancer. Furthermore, the therapeutic response to KRAS G12C inhibition was short-lived, with quick emergence of acquired resistance. In this review, we summarize several major themes that have emerged from recent clinical and preclinical studies on the mechanisms of intrinsic and acquired resistance to KRAS-targeted therapy in colorectal, lung, and pancreatic cancers. We also discuss various combination strategies for targeting these mechanisms to overcome resistance to KRAS inhibitors.

Transcriptional regulation of ETV5 by mitogen-activated protein kinase via ETS-1 in human pancreatic cancer cells

Pancreatic cancer is characterized by constitutive activation of mitogen-activated protein kinase /extracellular signal-regulated kinase 1/2 (ERK1/2) driven by gain-of-function mutations of KRAS. Our previous transcriptome sequencing of ERK1/2-attenuated cultured pancreatic cancer cells unveiled numerous downstream genes activated by ERK1/2 including ETV5. In this study, we explored the mechanism of transcriptional regulation of ETV5 by ERK1/2 in human pancreatic cancer cells. Detailed reporter assays uncovered a core promoter region spanning between - 350 and - 985 from the transcription start site of ETV5 as a strong responsive element to ERK1/2 activity. Moreover, ETS proto-oncogene 1, transcription factor (ETS-1) was found to bind to one of consensus binding sites in the core region and to promote ERK1/2-mediated upregulation of ETV5. Investigation of functional significances of ETS variant transcription factor 5 (ETV5) expression in the pancreatic cancer cells revealed that ETV5 was associated with resistance to gemcitabine; while no significance in proliferation, migration, and invasion. ETV5 expression in pancreatic ductal adenocarcinoma tissues resected from patients undergoing neoadjuvant chemotherapy was associated with KRAS mutations, which was consistent with ETV5 as a downstream upregulated molecule of RAS-ERK1/2 pathway. This study elucidated the mechanism of ERK1/2-mediated transcriptional regulation of ETV5 in human cancer cells, which could contribute to understand pancreatic cancer pathobiology.

Identification of ferroptosis-related signature predicting prognosis and therapeutic responses in pancreatic cancer

Ferroptosis plays a role in tumorigenesis by affecting lipid peroxidation and metabolic pathways; however, its prognostic or therapeutic relevance in pancreatic adenocarcinoma (PAAD) remains poorly understood. In this study, we developed a prognostic ferroptosis-related gene (FRG)-based risk model using cohorts of The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC), proposing plausible therapeutics. Differentially expressed FRGs between tumors from TCGA-PAAD and normal pancreatic tissues from Genotype-Tissue Expression were analyzed to construct a prognostic risk model using univariate and multivariate Cox regression and LASSO analyses. A model incorporating AURKA, CAV1, and PML gene expression effectively distinguished survival differences between high- and low-risk groups among TCGA-PAAD patients, with validation in two ICGC cohorts. The high-risk group was enriched in gene sets involving mTOR, MAPK, and E2F signaling. The immune and stromal cells infiltration score did not differ between the groups. Analysis of PRISM datasets using our risk model to classify pancreatic cell lines suggested the dasatinib's efficacy in the high-risk group, which was experimentally confirmed in four cell lines with a high- or low-risk signature. In conclusion, this study proposed a robust FRG-based prognostic model that may help stratify PAAD patients with poor prognoses and select potential therapeutic avenues.

Developing a Predictive Model for Metastatic Potential in Pancreatic Neuroendocrine Tumor

CONTEXT

Pancreatic neuroendocrine tumors (PNETs) exhibit a wide range of behavior from localized disease to aggressive metastasis. A comprehensive transcriptomic profile capable of differentiating between these phenotypes remains elusive.

OBJECTIVE

Use machine learning to develop predictive models of PNET metastatic potential dependent upon transcriptomic signature.

METHODS

RNA-sequencing data were analyzed from 95 surgically resected primary PNETs in an international cohort. Two cohorts were generated with equally balanced metastatic PNET composition. Machine learning was used to create predictive models distinguishing between localized and metastatic tumors. Models were validated on an independent cohort of 29 formalin-fixed, paraffin-embedded samples using NanoString nCounter®, a clinically available mRNA quantification platform.

RESULTS

Gene expression analysis identified concordant differentially expressed genes between the 2 cohorts. Gene set enrichment analysis identified additional genes that contributed to enriched biologic pathways in metastatic PNETs. Expression values for these genes were combined with an additional 7 genes known to contribute to PNET oncogenesis and prognosis, including ARX and PDX1. Eight specific genes (AURKA, CDCA8, CPB2, MYT1L, NDC80, PAPPA2, SFMBT1, ZPLD1) were identified as sufficient to classify the metastatic status with high sensitivity (87.5-93.8%) and specificity (78.1-96.9%). These models remained predictive of the metastatic phenotype using NanoString nCounter® on the independent validation cohort, achieving a median area under the receiving operating characteristic curve of 0.886.

CONCLUSION

We identified and validated an 8-gene panel predictive of the metastatic phenotype in PNETs, which can be detected using the clinically available NanoString nCounter® system. This panel should be studied prospectively to determine its utility in guiding operative vs nonoperative management.

Recent Updates on Oncogenic Signaling of Aurora Kinases in Chemosensitive, Chemoresistant Cancers: Novel Medicinal Chemistry Approaches for Targeting Aurora Kinases

The Aurora Kinase family (AKI) is composed of serine-threonine protein kinases involved in the modulation of the cell cycle and mitosis. These kinases are required for regulating the adherence of hereditary-related data. Members of this family can be categorized into aurora kinase A (Ark-A), aurora kinase B (Ark-B), and aurora kinase C (Ark-C), consisting of highly conserved threonine protein kinases. These kinases can modulate cell processes such as spindle assembly, checkpoint pathway, and cytokinesis during cell division. The main aim of this review is to explore recent updates on the oncogenic signaling of aurora kinases in chemosensitive/chemoresistant cancers and to explore the various medicinal chemistry approaches to target these kinases. We searched Pubmed, Scopus, NLM, Pubchem, and Relemed to obtain information pertinent to the updated signaling role of aurora kinases and medicinal chemistry approaches and discussed the recently updated roles of each aurora kinases and their downstream signaling cascades in the progression of several chemosensitive/chemoresistant cancers; subsequently, we discussed the natural products (scoulerine, Corynoline, Hesperidin Jadomycin-B, fisetin), and synthetic, medicinal chemistry molecules as aurora kinase inhibitors (AKIs). Several natural products' efficacy was explained as AKIs in chemosensitization and chemoresistant cancers. For instance, novel triazole molecules have been used against gastric cancer, whereas cyanopyridines are used against colorectal cancer and trifluoroacetate derivatives could be used for esophageal cancer. Furthermore, quinolone hydrazine derivatives can be used to target breast cancer and cervical cancer. In contrast, the indole derivatives can be preferred to target oral cancer whereas thiosemicarbazone-indole could be used against prostate cancer, as reported in an earlier investigation against cancerous cells. Moreover, these chemical derivatives can be examined as AKIs through preclinical studies. In addition, the synthesis of novel AKIs through these medicinal chemistry substrates in the laboratory using in silico and synthetic routes could be beneficial to develop prospective novel AKIs to target chemoresistant cancers. This study is beneficial to oncologists, chemists, and medicinal chemists to explore novel chemical moiety synthesis to target specifically the peptide sequences of aurora kinases in several chemoresistant cancer cell types.

ERK1-mediated immunomodulation of mesenchymal stem cells ameliorates inflammatory disorders

Immune system disorders, especially T cell disorders, are important therapeutic targets of mesenchymal stem cells (MSCs) in many autoimmune diseases (ADs). Although extracellular regulated protein kinases (ERKs) play a role in MSC therapy by promoting T cell apoptosis, the mechanism remains unclear. Our findings indicate that ERK1-/- bone marrow MSCs (BMMSCs), but not ERK2-/- BMMSCs, failed to promote T cell apoptosis due to incapacity to activate the ETS2/AURKA/NF-κB/Fas/MCP-1 cascade. Moreover, ERK1-/- BMMSCs were unable to upregulate regulatory T cells and suppress T helper 17 cells. Licochalcone A (LA), which promotes ERK pathway activation, enhanced the therapeutic efficacy of MSC therapy in ulcerative colitis and collagen-induced arthritis mice. Our findings suggest that ERK1, but not ERK2, plays a crucial role in regulating T cells in MSCs. LA-treated MSCs provide a strategy to improve the efficacy of MSC-based treatments for ADs.

Multifaceted Effects of Kinase Inhibitors on Pancreatic Cancer Cells Reveals Pivotal Entities with Therapeutic Implications

Pancreatic cancer is one of the most aggressive forms of cancer and is the seventh leading cause of cancer deaths worldwide. Pancreatic ductal adenocarcinoma (PDAC) accounts for over 90% of pancreatic cancers. Most pancreatic cancers are recalcitrant to radiation, chemotherapy, and immunotherapy, highlighting the urgent need for novel treatment options for this deadly disease. To this end, we screened a library of kinase inhibitors in the PDAC cell lines PANC-1 and BxPC-3 and identified two highly potent molecules: Aurora kinase inhibitor AT 9283 (AT) and EGFR kinase inhibitor WZ 3146 (WZ). Both AT and WZ exhibited a dose-dependent inhibition of viability in both cell lines. Thus, we conducted an in-depth multilevel (cellular, molecular, and proteomic) analysis with AT and WZ in PANC-1 cells, which harbor KRAS mutation and exhibit quasimesenchymal properties representing pancreatic cancer cells as having intrinsic chemoresistance and the potential for differential response to therapy. Elucidation of the molecular mechanism of action of AT and WZ revealed an impact on the programmed cell death pathway with an increase in apoptotic, multicaspase, and caspase 3/7 positive cells. Additionally, the key survival molecule Bcl-2 was impacted. Moreover, cell cycle arrest was observed with both kinase inhibitors. Additionally, an increase in superoxide radicals was observed in the AT-treated group. Importantly, proteomic profiling revealed differentially regulated key entities with multifaceted effects, which could have a deleterious impact on PDAC. These findings suggest potential targets for efficacious treatment, including a possible increase in the efficacy of immunotherapy using PD-L1 antibody due to the upregulation of lactoferrin and radixin. Furthermore, combination therapy outcomes with gemcitabine/platinum drugs may also be more effective due to an increase in the NADH dehydrogenase complex. Notably, protein-protein interaction analysis (STRING) revealed possible enrichment of reactome pathway entities. Additionally, novel therapy options, such as vimentin-antibody--drug conjugates, could be explored. Therefore, future studies with the two kinases as monotherapy/combination therapy are warranted.

Signatures of Co-Deregulated Genes and Their Transcriptional Regulators in Kidney Cancers

There are several studies on the deregulated gene expression profiles in kidney cancer, with varying results depending on the tumor histology and other parameters. None of these, however, have identified the networks that the co-deregulated genes (co-DEGs), across different studies, create. Here, we reanalyzed 10 Gene Expression Omnibus (GEO) studies to detect and annotate co-deregulated signatures across different subtypes of kidney cancer or in single-gene perturbation experiments in kidney cancer cells and/or tissue. Using a systems biology approach, we aimed to decipher the networks they form along with their upstream regulators. Differential expression and upstream regulators, including transcription factors [MYC proto-oncogene (MYC), CCAAT enhancer binding protein delta (CEBPD), RELA proto-oncogene, NF-kB subunit (RELA), zinc finger MIZ-type containing 1 (ZMIZ1), negative elongation factor complex member E (NELFE) and Kruppel-like factor 4 (KLF4)] and protein kinases [Casein kinase 2 alpha 1 (CSNK2A1), mitogen-activated protein kinases 1 (MAPK1) and 14 (MAPK14), Sirtuin 1 (SIRT1), Cyclin dependent kinases 1 (CDK1) and 4 (CDK4), Homeodomain interacting protein kinase 2 (HIPK2) and Extracellular signal-regulated kinases 1 and 2 (ERK1/2)], were computed using the Characteristic Direction, as well as GEO2Enrichr and X2K, respectively, and further subjected to GO and KEGG pathways enrichment analyses. Furthermore, using CMap, DrugMatrix and the LINCS L1000 chemical perturbation databases, we highlight putative repurposing drugs, including Etoposide, Haloperidol, BW-B70C, Triamterene, Chlorphenesin, BRD-K79459005 and β-Estradiol 3-benzoate, among others, that may reverse the expression of the identified co-DEGs in kidney cancers. Of these, the cytotoxic effects of Etoposide, Catecholamine, Cyclosporin A, BW-B70C and Lasalocid sodium were validated in vitro. Overall, we identified critical co-DEGs across different subtypes in kidney cancer, and our results provide an innovative framework for their potential use in the future.

Aurora Kinase A Regulation by Cysteine Oxidative Modification

Aurora kinase A (AURKA), which is a member of serine/threonine kinase family, plays a critical role in regulating mitosis. AURKA has drawn much attention as its dysregulation is critically associated with various cancers, leading to the development of AURKA inhibitors, a new class of anticancer drugs. As the spatiotemporal activity of AURKA critically depends on diverse intra- and inter-molecular factors, including its interaction with various protein cofactors and post-translational modifications, each of these pathways should be exploited for the development of a novel class of AURKA inhibitors other than ATP-competitive inhibitors. Several lines of evidence have recently shown that redox-active molecules can modify the cysteine residues located on the kinase domain of AURKA, thereby regulating its activity. In this review, we present the current understanding of how oxidative modifications of cysteine residues of AURKA, induced by redox-active molecules, structurally and functionally regulate AURKA and discuss their implications in the discovery of novel AURKA inhibitors.

Long Non-Coding RNAs Associated with Mitogen-Activated Protein Kinase in Human Pancreatic Cancer

Long non-coding RNAs (lncRNAs) have emerged as a significant player in various cancers, including pancreatic cancer. However, how lncRNAs are aberrantly expressed in cancers is largely unknown. We hypothesized that lncRNAs would be regulated by signaling pathways and contribute to malignant phenotypes of cancer. In this study, to understand the significance of mitogen-activated protein kinase/extracellular signal-regulated kinase (MAPK/ERK), which is a major aberrant signaling pathway in pancreatic cancer, for the expression of lncRNAs, we performed comparative transcriptome analyses between pancreatic cancer cell lines with or without activation of MAPK. We identified 45 lncRNAs presumably associated with MAPK in pancreatic cancer cells; among these, LINC00941 was consistently upregulated by MAPK. The immediate genomic upstream region flanking LINC00941 was identified as a promoter region, the activity of which was found to be preferentially associated with MAPK activity via ETS-1 binding site. LINC00941 promoted cell proliferation in vitro. Moreover, TCGA data analysis indicated that high expression of LINC00941 was associated with poor prognosis of patients with pancreatic cancer. Transcriptomes comparing transcriptions between cells with and without LINC00941 knockdown revealed 3229 differentially expressed genes involved in 44 biological processes, including the glycoprotein biosynthetic process, beta-catenin-TCF complex assembly, and histone modification. These results indicate that MAPK mediates the aberrant expression of lncRNAs. LINC00941 is the lncRNA by MAPK most consistently promoted, and is implicated in the dismal prognosis of pancreatic cancer. MAPK-associated lncRNAs may play pivotal roles in malignant phenotypes of pancreatic cancer, and as such might represent both potentially valid therapeutic targets and diagnostic biomarkers.

DUSP6 mediates resistance to JAK2 inhibition and drives leukemic progression

Myeloproliferative neoplasms (MPNs) exhibit a propensity for transformation to secondary acute myeloid leukemia (sAML), for which the underlying mechanisms remain poorly understood, resulting in limited treatment options and dismal clinical outcomes. Here, we performed single-cell RNA sequencing on serial MPN and sAML patient stem and progenitor cells, identifying aberrantly increased expression of DUSP6 underlying disease transformation. Pharmacologic dual-specificity phosphatase (DUSP)6 targeting led to inhibition of S6 and Janus kinase (JAK)-signal transducer and activator of transcription (STAT) signaling while also reducing inflammatory cytokine production. DUSP6 perturbation further inhibited ribosomal S6 kinase (RSK)1, which we identified as a second indispensable candidate associated with poor clinical outcome. Ectopic expression of DUSP6 mediated JAK2-inhibitor resistance and exacerbated disease severity in patient-derived xenograft (PDX) models. Contrastingly, DUSP6 inhibition potently suppressed disease development across Jak2V617F and MPLW515L MPN mouse models and sAML PDXs without inducing toxicity in healthy controls. These findings underscore DUSP6 in driving disease transformation and highlight the DUSP6-RSK1 axis as a vulnerable, druggable pathway in myeloid malignancies.

An extensive bioinformatics study on the role of mitochondrial solute carrier family 25 in PC and its mechanism behind affecting immune infiltration and tumor energy metabolism

BACKGROUND

Several metabolic disorders and malignancies are directly related to abnormal mitochondrial solute carrier family 25 (SLC25A) members activity. However, its biological role in pancreatic cancer (PC) is not entirely understood.

METHODS

The lasso method was used to create a novel prognostic risk model for PC based on SLC25A members, and its roles in tumor immunology and energy metabolism were explored. Furthermore, co-expression networks were constructed for SLC25A11, SLC25A29, and SLC25A44. Single-cell RNA sequencing (ScRNA-seq) revealed the distribution of gene expression in PC. Tumor immune infiltration was examined with the TIMER database. Lastly, drug sensitivity was investigated, and co-transcriptional factors were predicted.

RESULTS

In the present study, a novel prognostic risk model was established and validated for PC based on SLC25A members. The high-risk group had a lower activation of oxidative phosphorylation and a more abundant immune infiltration phenotype than the low-risk group. According to co-expression network studies, SLC25A11, SLC25A29, and SLC25A44 were involved in the energy metabolism of PC and prevented tumor growth, invasion, and metastasis. ScRNA-seq research also pointed to their contribution to the tumor microenvironment. Moreover, the recruitment of numerous immune cells was positively correlated with SLC25A11 and SLC25A44 but negatively correlated with SLC25A29. Additionally, the sensitivity to 20 Food and Drug Administration-approved antineoplastic medicines was strongly linked to the aforementioned genes, where cisplatin sensitivity increased with the up-regulation of SLC25A29. Finally, the Scleraxis BHLH Transcription Factor (SCX) and other proteins were hypothesized to co-regulate the mRNA transcription of the genes.

CONCLUSION

SLC25A members are crucial for tumor immune and energy metabolism in PC, and SLC25A11, SLC25A29, and SLC25A44 can be used as favorable prognostic markers. The use of these markers will provide new directions to unravel their action mechanisms in PC.

BI-847325, a selective dual MEK and Aurora kinases inhibitor, reduces aggressive behavior of anaplastic thyroid carcinoma on an in vitro three-dimensional culture

BACKGROUND

Anaplastic thyroid carcinoma (ATC) is the most aggressive subtype of thyroid cancer. In this study, we used a three-dimensional in vitro system to evaluate the effect of a dual MEK/Aurora kinase inhibitor, BI-847325 anticancer drug, on several cellular and molecular processes involved in cancer progression.

METHODS

Human ATC cell lines, C643 and SW1736, were grown in alginate hydrogel and treated with IC₅₀ values of BI-847325. The effect of BI-847325 on inhibition of kinases function of MEK1/2 and Aurora kinase B (AURKB) was evaluated via Western blot analysis of phospho-ERK1/2 and phospho-Histone H3 levels. Sodium/iodide symporter (NIS) and thyroglobulin (Tg), as two thyroid-specific differentiation markers, were measured by qRT-PCR as well as flow cytometry and immunoradiometric assay. Apoptosis was assessed by Annexin V/PI flow cytometry and BIM, NFκB1, and NFκB2 expressions. Cell cycle distribution and proliferation were determined via P16, AURKA, and AURKB expressions as well as PI and CFSE flow cytometry assays. Multidrug resistance was evaluated by examining the expression of MDR1 and MRP1. Angiogenesis and invasion were investigated by VEGF expression and F-actin labeling with Alexa Fluor 549 Phalloidin.

RESULTS

Western blot results showed that BI-847325 inhibits MEK1/2 and AURKB functions by decreasing phospho-ERK1/2 and phospho-Histone H3 levels. BI-847325 induced thyroid differentiation markers and apoptosis in ATC cell lines. Inversely, BI-847325 intervention decreased multidrug resistance, cell cycle progression, proliferation, angiogenesis, and invasion at the molecular and/or cellular levels.

CONCLUSION

The results of the present study suggest that BI-857,325 might be an effective multi-targeted anticancer drug for ATC treatment.

An integrated analysis of the cancer genome atlas data discovers a hierarchical association structure across thirty three cancer types

Cancer cells harbor molecular alterations at all levels of information processing. Genomic/epigenomic and transcriptomic alterations are inter-related between genes, within and across cancer types and may affect clinical phenotypes. Despite the abundant prior studies of integrating cancer multi-omics data, none of them organizes these associations in a hierarchical structure and validates the discoveries in extensive external data. We infer this Integrated Hierarchical Association Structure (IHAS) from the complete data of The Cancer Genome Atlas (TCGA) and compile a compendium of cancer multi-omics associations. Intriguingly, diverse alterations on genomes/epigenomes from multiple cancer types impact transcriptions of 18 Gene Groups. Half of them are further reduced to three Meta Gene Groups enriched with (1) immune and inflammatory responses, (2) embryonic development and neurogenesis, (3) cell cycle process and DNA repair. Over 80% of the clinical/molecular phenotypes reported in TCGA are aligned with the combinatorial expressions of Meta Gene Groups, Gene Groups, and other IHAS subunits. Furthermore, IHAS derived from TCGA is validated in more than 300 external datasets including multi-omics measurements and cellular responses upon drug treatments and gene perturbations in tumors, cancer cell lines, and normal tissues. To sum up, IHAS stratifies patients in terms of molecular signatures of its subunits, selects targeted genes or drugs for precision cancer therapy, and demonstrates that associations between survival times and transcriptional biomarkers may vary with cancer types. These rich information is critical for diagnosis and treatments of cancers.

Mechanisms of development and progression of pancreatic neoplasms

Pancreatic ductal adenocarcinoma (PDAC) develops via dysplastic changes in the epithelia graded as low- and high-grade with accumulation of molecular alterations. Constitutive activation of mitogen-activated protein kinase (MAPK) contributed by attenuation of DUSP6 plays a key role in sustaining PDAC. Active MAPK induces various molecules that function as effectors to sustain PDAC. AURKA and SON are downstream effectors that contribute substantially to the proliferation and survival of PDAC cells and are potentially useful as therapeutic targets. Active MAPK also promote microRNAs that modulate the proliferation of PDAC cells and are useful as diagnostic markers. Familial pancreatic cancer kindreds in Japan show various germline mutations supposed to increase a pancreatic cancer risk. Intraductal papillary mucinous neoplasms (IPMNs) consist of dilated ducts lined by papillary neoplastic epithelia of various shapes and varying grades of atypia. Various papillae of IPMNs are classified into four subtypes that are associated with clinicopathological features, including patient prognosis. GNAS is a specific driver gene for the development of IPMN through gain-of-function mutations. Tracing of molecular alterations has elucidated the mechanism of progression of IPMN from dysplasia to carcinoma, as well as one type of papillae. Intraductal tubulopapillary neoplasms belong to a distinct class of pancreatic neoplasms.

Integrated analysis of senescence-associated genes in pancreatic ductal adenocarcinoma

Background: Cellular senescence plays a critical role in the occurrence and development, and immune modulation of cancer. This research primarily investigated the role of senescence-associated genes (SAGs) in the survival and tumor microenvironment of pancreatic ductal adenocarcinoma (PDAC).

Methods: From the Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) database, the gene expression profiles and clinical data of PDAC samples were downloaded. SAGs in the TCGA cohort were used to build a novel prognostic model and validated in the ICGC cohort. The relationship of signature with the immune landscape, tumor mutational burden (TMB), as well as the sensitivity of different therapies, was explored. Moreover, a nomogram was developed to predict the overall survival of PDAC patients.

Results: A prognostic signature was constructed on basis of three SAGs, and patients in the low-risk score group had a longer survival time. The accuracy of the signature to distinguish different score groups was confirmed through principal component analysis (PCA) and the Receiver operator curves curve. The mRNA expression of the three signature genes was also verified in normal pancreatic and PDAC cell lines by RT-qPCR. The signature could independently predict the prognosis of PDAC patients and had broad applicability. Meanwhile, the nomogram predicted that 1- and 3-years survival rates were in good agreement with the observed overall survival rates. Low-risk patients had lower tumor mutational burden, and low-TMB patients had a better prognosis. Low- and high-risk patients exhibit distinct immune cell infiltration and immune checkpoint changes. By further analyzing the risk score, patients in the low-risk group were more responsive to immunotherapy and a variety of commonly used chemotherapeutic drugs.

Conclusion: The prognostic signature can well predict the prognosis and assess the possibility of immunotherapy in personalized PDAC treatment.

Analyses of selected tumour-associated factors expression in normotensive and preeclamptic placenta

INTRODUCTION

Human placenta is often considered a controlled-tumour because of shared properties such as invasion and angiogenesis. We assessed the status of a few selected tumour-associated factors (TAFs) in late onset pre-eclamptic (PE) and normotensive (NT) placentae, to understand their involvement in trophoblast invasion. These molecules include aldehyde dehydrogenase (ALDH3A1), aurora kinases (AURK-A/C), platelet derived growth factor receptor-α (PDGFRα), jagged-1 (JAG1) and twist related protein-1 (TWIST1).

METHODS

The expression of TAF was compared in 13 NT and 11 PE (late onset) placentae using immunoblotting/immunohistochemistry. We then used a novel spheroidal cell model developed from transformed human first trimester trophoblast cell lines HTR8/SVneo and TEV-1 to determine the expression and localization of these six factors during invasion. We also compared the expression of these TAFs during migration and invasion.

RESULTS

Our results suggest that expressions of ALDH3A1, AURK-A, PDGFRα, and TWIST1 are significantly upregulated in PE placentae (p < 0.05) when compared to NT placentae, whereas AURK-C and JAG1 are down-regulated (p < 0.05). The protein expression pattern of all the six factors were found to be similar in spheroids in comparison to their parental counterparts. The invasive potential of the spheroids was also enhanced when compared with the parental cells.

DISCUSSION

Collectively, data from our present study suggests that these TAFs are involved in placental invasion and their altered expressions may be regarded as a compensatory mechanism against reduced invasion.

Bisphenol A-sulfate conjugate disrupts AURKA transcription and cell cycle in BeWo cytotrophoblasts

Bisphenol A (BPA) has been shown to exhibit various toxic effects, including the induction of reproductive disorders. Generally, BPA is converted to conjugated metabolites, leading to bio-inactivation. On the other hand, the toxicity of conjugated metabolites is not fully understood. Notably, the placenta develops the sulfate-sulfatase pathway, which transports and reactivates sulfated steroids. Therefore, we investigated the potential adverse effects of the BPA-sulfate conjugate (BPA-S) on human placenta-derived BeWo cytotrophoblasts. In the present study, high-concentration BPA-S (100 μM) induced significant inhibition of BeWo growth, with effects similar to those seen with unconjugated BPA (100 μM and 100 nM). This growth inhibition was restored by treatment of the cells with an inhibitor of the organic anion-transporting peptides (OATPs) (bromosulphophthalein) or with a sulfatase (STS) inhibitor (STX64). BeWo exhibits expression of the genes encoding OATP1A2 and OATP4A1 as known sulfated steroid transporters and STS, suggesting that BPA-S suppresses cell growth activity via the sulfate-sulfatase pathway. In addition, cell cycle analysis revealed that BPA-S (100 μM) increased the fraction of cytotrophoblasts in the G2/M phases and significantly decreased the accumulation of the transcript encoding Aurora kinase A (AURKA), which is a critical regulator of cellular division. These results suggested that BPA-S triggers cell cycle arrest and inhibits proliferation of BeWo cytotrophoblasts by decreased AURKA, an effect that is mediated by the sulfate-sulfatase pathway. Overall, these findings provide insights into the reactivation of sulfated endocrine-disrupting chemicals and subsequent adverse effects.

Transcriptome-Guided Drug Repurposing for Aggressive SCCs

Despite a significant rise in the incidence of cutaneous squamous cell carcinoma (SCC) in recent years, most SCCs are well treatable. However, against the background of pre-existing risk factors such as immunosuppression upon organ transplantation, or conditions such as recessive dystrophic epidermolysis bullosa (RDEB), SCCs arise more frequently and follow a particularly aggressive course. Notably, such SCC types display molecular similarities, despite their differing etiologies. We leveraged the similarities in transcriptomes between tumors from organ transplant recipients and RDEB-patients, augmented with data from more common head and neck (HN)-SCCs, to identify drugs that can be repurposed to treat these SCCs. The in silico approach used is based on the assumption that SCC-derived transcriptome profiles reflect critical tumor pathways that, if reversed towards healthy tissue, will attenuate the malignant phenotype. We determined tumor-specific signatures based on differentially expressed genes, which were then used to mine drug-perturbation data. By leveraging recent efforts in the systematic profiling and cataloguing of thousands of small molecule compounds, we identified drugs including selumetinib that specifically target key molecules within the MEK signaling cascade, representing candidates with the potential to be effective in the treatment of these rare and aggressive SCCs.

Application of Molecular Nanoprobes in the Analysis of Differentially Expressed Genes and Prognostic Models of Primary Hepatocellular Carcinoma

Analyzing hub genes related to tumorigenesis based on biological big data has recently become a hotspot in biomedicine. Nanoprobes, nanobodies and theranostic molecules targeting hub genes delivered by nanocarriers have been widely applied in tumor theranostics. Hepatocellular carcinoma (HCC) is one of the most common cancers, with a poor prognosis and high mortality. Identifying hub genes according to the gene expression levels and constructing prognostic signatures related to the onset and outcome of HCC will be of great significance. In this study, the expression profiles of HCC and normal tissue were obtained from the GEO database and analyzed by GEO₂R to identify DEGs. GO terms and KEGG pathways were enriched in DAVID software. The STRING database was consulted to find protein-protein interactions between proteins encoded by the DEGs, which were visualized by Cytoscape. Then, overall survival associated with the hub genes was calculated by the Kaplan-Meier plotter online tool, and verification of the results was carried out on TCGA samples and their corresponding clinical information. A total of 603 DEGs were obtained, of which 479 were upregulated and 124 were downregulated. PPI networks including 603 DEGs and 18 clusters were constructed, of which 7 clusters with MCODE score ≥3 and nodes ≥5 were selected. The 5 genes with the highest degrees of connectivity were identified as hub genes, and a prognostic model was constructed. The expression and prognostic potential of this model was validated on TCGA clinical data. In conclusion, a five-gene signature (TOP2A, PCNA, AURKA, CDC20, CCNB2) overexpressed inHCC was identified, and a prognostic model was constructed. This gene signature may act as a prognostic model for HCC and provide potential targets of nanotechnology.

Inhibiting of TACC3 Promotes Cell Proliferation, Cell Invasion and the EMT Pathway in Breast Cancer

Accumulating evidences indicate that transforming acidic coiled-coil 3 (TACC3) is a tumor-related gene, was highly expressed in a variety of human cancers, which is involved in cancer development. However, the potential role of TACC3 in breast cancer remains largely unknown. In the present study, we found that TACC3 was highly-expressed in breast cancer tissues, and its level was positively correlated with the clinical features of breast cancer patients. Specifically, TACC3 expression was significantly associated with the estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) status, nodal status, the scarff-bloom-richardson (SBR) grade, nottingham prognostic index (NPI), age, subtypes, and triple-negative and basal-like status, suggesting that TACC3 may be a potential diagnostic indicator of breast cancer. Furthermore, functional studies have shown that inhibition of TACC3 can significantly promote the cell proliferation and viability of breast cancer cells. Moreover, TACC3 knockdown suppressed the expression of E-cadherin, but increased the expression of N-cadherin, Snail, ZEB1, and TWIST, which indicate that TACC3 may impact the migration of breast cancer cells in vitro. Taken together, these findings indicate that TACC3 may serve as a prognostic and therapeutic indicator of breast cancer.

Covariance thresholding to detect differentially co-expressed genes from microarray gene expression data

Gene set analysis aims to identify differentially expressed or co-expressed genes within a biological pathway between two experimental conditions, so that it can eventually reveal biological processes and pathways involved in disease development. In the last few decades, various statistical and computational methods have been proposed to improve statistical power of gene set analysis. In recent years, much attention has been paid to differentially co-expressed genes since they can be potentially disease-related genes without significant difference in average expression levels between two conditions. In this paper, we propose a new statistical method to identify differentially co-expressed genes from microarray gene expression data. The proposed method first estimates co-expression levels of paired genes using covariance regularization by thresholding, and then significance of difference in covariance estimation between two conditions is evaluated. We demonstrated that the proposed method is more powerful than the existing main-stream methods to detect co-expressed genes through extensive simulation studies. Also, we applied it to various microarray gene expression datasets related with mutant p53 transcriptional activity, and epithelium and stroma breast cancer.

Control Analysis of Protein-Protein Interaction Network Reveals Potential Regulatory Targets for MYCN

BACKGROUND

MYCN is an oncogenic transcription factor of the MYC family and plays an important role in the formation of tissues and organs during development before birth. Due to the difficulty in drugging MYCN directly, revealing the molecules in MYCN regulatory networks will help to identify effective therapeutic targets.

METHODS

We utilized network controllability theory, a recent developed powerful tool, to identify the potential drug target around MYCN based on Protein-Protein interaction network of MYCN. First, we constructed a Protein-Protein interaction network of MYCN based on public databases. Second, network control analysis was applied on network to identify driver genes and indispensable genes of the MYCN regulatory network. Finally, we developed a novel integrated approach to identify potential drug targets for regulating the function of the MYCN regulatory network.

RESULTS

We constructed an MYCN regulatory network that has 79 genes and 129 interactions. Based on network controllability theory, we analyzed driver genes which capable to fully control the network. We found 10 indispensable genes whose alternation will significantly change the regulatory pathways of the MYCN network. We evaluated the stability and correlation analysis of these genes and found EGFR may be the potential drug target which closely associated with MYCN.

CONCLUSION

Together, our findings indicate that EGFR plays an important role in the regulatory network and pathways of MYCN and therefore may represent an attractive therapeutic target for cancer treatment.

A gene module identification algorithm and its applications to identify gene modules and key genes of hepatocellular carcinoma

To further improve the effect of gene modules identification, combining the Newman algorithm in community detection and K-means algorithm framework, a new method of gene module identification, GCNA-Kpca algorithm, was proposed. The core idea of the algorithm was to build a gene co-expression network (GCN) based on gene expression data firstly; Then the Newman algorithm was used to initially identify gene modules based on the topology of GCN, and the number of clusters and clustering centers were determined; Finally the number of clusters and clustering centers were input into the K-means algorithm framework, and the secondary clustering was performed based on the gene expression profile to obtain the final gene modules. The algorithm took into account the role of modularity in the clustering process, and could find the optimal membership module for each gene through multiple iterations. Experimental results showed that the algorithm proposed in this paper had the best performance in error rate, biological significance and CNN classification indicators (Precision, Recall and F-score). The gene module obtained by GCNA-Kpca was used for the task of key gene identification, and these key genes had the highest prognostic significance. Moreover, GCNA-Kpca algorithm was used to identify 10 key genes in hepatocellular carcinoma (HCC): CDC20, CCNB1, EIF4A3, H2AFX, NOP56, RFC4, NOP58, AURKA, PCNA, and FEN1. According to the validation, it was reasonable to speculate that these 10 key genes could be biomarkers for HCC. And NOP56 and NOP58 are key genes for HCC that we discovered for the first time.

Identification of hub genes and biological pathways in hepatocellular carcinoma by integrated bioinformatics analysis

Background

Hepatocellular carcinoma (HCC), the main type of liver cancer in human, is one of the most prevalent and deadly malignancies in the world. The present study aimed to identify hub genes and key biological pathways by integrated bioinformatics analysis.

Methods

A bioinformatics pipeline based on gene co-expression network (GCN) analysis was built to analyze the gene expression profile of HCC. Firstly, differentially expressed genes (DEGs) were identified and a GCN was constructed with Pearson correlation analysis. Then, the gene modules were identified with 3 different community detection algorithms, and the correlation analysis between gene modules and clinical indicators was performed. Moreover, we used the Search Tool for the Retrieval of Interacting Genes (STRING) database to construct a protein protein interaction (PPI) network of the key gene module, and we identified the hub genes using nine topology analysis algorithms based on this PPI network. Further, we used the Oncomine analysis, survival analysis, GEO data set and random forest algorithm to verify the important roles of hub genes in HCC. Lastly, we explored the methylation changes of hub genes using another GEO data (GSE73003).

Results

Firstly, among the expression profiles, 4,130 up-regulated genes and 471 down-regulated genes were identified. Next, the multi-level algorithm which had the highest modularity divided the GCN into nine gene modules. Also, a key gene module (m1) was identified. The biological processes of GO enrichment of m1 mainly included the processes of mitosis and meiosis and the functions of catalytic and exodeoxyribonuclease activity. Besides, these genes were enriched in the cell cycle and mitotic pathway. Furthermore, we identified 11 hub genes, MCM3, TRMT6, AURKA, CDC20, TOP2A, ECT2, TK1, MCM2, FEN1, NCAPD2 and KPNA2 which played key roles in HCC. The results of multiple verification methods indicated that the 11 hub genes had highly diagnostic efficiencies to distinguish tumors from normal tissues. Lastly, the methylation changes of gene CDC20, TOP2A, TK1, FEN1 in HCC samples had statistical significance (P-value < 0.05).

Conclusion

MCM3, TRMT6, AURKA, CDC20, TOP2A, ECT2, TK1, MCM2, FEN1, NCAPD2 and KPNA2 could be potential biomarkers or therapeutic targets for HCC. Meanwhile, the metabolic pathway, the cell cycle and mitotic pathway might played vital roles in the progression of HCC.

Identification of Spindle and Kinetochore-Associated Family Genes as Therapeutic Targets and Prognostic Biomarkers in Pancreas Ductal Adenocarcinoma Microenvironment

Aim

The role of spindle and kinetochore-associated (SKA) genes in tumorigenesis and cancer progression has been widely studied. However, so far, the oncogenic involvement of SKA family genes in pancreatic cancer and their prognostic potential remain unknown.

Methods

Here, we carried out a meta-analysis of the differential expression of SKA genes in normal and tumor tissue. Univariate and multivariate survival analyses were done to evaluate the correlation between SKA family gene expression and pancreas ductal adenocarcinoma (PDAC) prognosis. Joint-effect and stratified survival analysis as well as nomogram analysis were used to estimate the prognostic value of genes. The underlying regulatory and biological mechanisms were identified by Gene set enrichment analysis. Interaction between SKA prognosis-related genes and immune cell infiltration was assessed using the Tumor Immune Estimation Resource tool.

Results

We find that SKA1-3 are highly expressed in PDAC tissues relative to non-cancer tissues. Survival analysis revealed that high expression of SKA1 and SKA3 independently indicate poor prognosis but they are not associated with relapse-free survival. The prognostic value of SKA1 and SKA3 was further confirmed by the nomogram, joint-effect, and stratified survival analysis. Analysis of underlying mechanisms reveals that these genes influence cancer-related signaling pathways, kinases, miRNA, and E2F family genes. Notably, prognosis-related genes are inversely correlated with several immune cells infiltrating levels.

Conclusion

We find that SKA1 and SKA3 expression correlates with prognosis and immune cell infiltration in PDAC, highlighting their potential as pancreatic cancer prognostic biomarkers.

Ciliogenesis and Hedgehog signalling are suppressed downstream of KRAS during acinar-ductal metaplasia in mouse

Pancreatic ductal adenocarcinoma (PDAC) is the third leading cause of cancer-related deaths worldwide, but has a 5-year survival rate of only 7% primarily due to late diagnosis and ineffective therapies. To treat or even prevent PDAC, it is vital that we understand the initiating events that lead to tumour onset. PDAC develops from preneoplastic lesions, most commonly pancreatic intraepithelial neoplasias (PanINs), driven by constitutive activation of KRAS. In patients, PanINs are associated with regions of acinar-to-ductal metaplasia (ADM) where, in response to inflammation, acini dedifferentiate to a pancreatic progenitor-like fate. In healthy tissue this process is reversible leading to regeneration of the pancreas; however, in the presence of oncogenic KRAS, regeneration is blocked and ADM can give rise to PanIN lesions. Here, we used a 3D mouse acinar culture that recapitulates ADM in vitro to explore how KRAS prevents regeneration. Regeneration is regulated by Hedgehog (Hh) signalling, which is transduced via the primary cilium. In wild-type acini, cilia assemble upon ADM and Hh target gene expression is upregulated; however, ciliogenesis and Hh signalling are suppressed during ADM in cells expressing oncogenic KRAS. We show that ciliogenesis fails due to ectopic activation of the cilium disassembly pathway, which is mediated by AurkA, a direct transcriptional target of KRAS. Inhibition of AurkA is able to rescue primary cilia and restore Hh signalling. We suggest that this could be used as a mechanism to prevent the formation of early lesions and thereby prevent progression to PDAC.

Integrative Analysis of Cancer Omics Data for Prognosis Modeling

Prognosis modeling plays an important role in cancer studies. With the development of omics profiling, extensive research has been conducted to search for prognostic markers for various cancer types. However, many of the existing studies share a common limitation by only focusing on a single cancer type and suffering from a lack of sufficient information. With potential molecular similarity across cancer types, one cancer type may contain information useful for the analysis of other types. The integration of multiple cancer types may facilitate information borrowing so as to more comprehensively and more accurately describe prognosis. In this study, we conduct marginal and joint integrative analysis of multiple cancer types, effectively introducing integration in the discovery process. For accommodating high dimensionality and identifying relevant markers, we adopt the advanced penalization technique which has a solid statistical ground. Gene expression data on nine cancer types from The Cancer Genome Atlas (TCGA) are analyzed, leading to biologically sensible findings that are different from the alternatives. Overall, this study provides a novel venue for cancer prognosis modeling by integrating multiple cancer types.

The Effects of Plumbagin on Pancreatic Cancer: A Mechanistic Network Pharmacology Approach

BACKGROUND This study aimed to use a network pharmacology approach to establish the effects of plumbagin on pancreatic cancer (PC) and to predict core targets and biological functions, pathways, and mechanisms of action. MATERIAL AND METHODS Genes associated with the pathogenesis of PC were obtained from a database of gene-disease associations (DisGeNET). Putative genes associated with plumbagin were identified from the databases of drug target identification (PharmMapper), target prediction of bioactive components (SwissTargetPrediction), and comprehensive drug target information (DrugBank). PC targets of plumbagin were harvested by using a functional enrichment analysis tool (FunRich). The data of function-related protein-protein interactions (PPIs) with a confidence score >0.9 were obtained by using functional protein association networks (STRING). The network interactions of plumbagin and PC targets and function-related proteins were constructed through complex network analysis and visualization (Cytoscape). The Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analysis were used to identify the effects of plumbagin. RESULTS The most important biotargets for plumbagin in PC were identified as TP53, MAPK1, BCL2, and IL6. A total of 1,731 annotations and 121 enriched pathways for plumbagin and PC were identified by KEGG and GO analysis. The top 10 signaling pathways of plumbagin and PC were screened, followed by identification of biological components and functions. CONCLUSIONS Network pharmacology established the effects of plumbagin on PC, predicted core targets, biological functions, pathways, and mechanisms of action. Further studies are needed to validate these predictive biotargets in PC.

Loss of Primary Cilia Drives Switching from Hedgehog to Ras/MAPK Pathway in Resistant Basal Cell Carcinoma

Basal cell carcinomas (BCCs) rely on Hedgehog (HH) pathway growth signal amplification by the microtubule-based organelle, the primary cilium. Despite naive tumor responsiveness to Smoothened inhibitors (Smoⁱ), resistance in advanced tumors remains common. Although the resistant BCCs usually maintain HH pathway activation, squamous cell carcinomas with Ras/MAPK pathway activation also arise, and the molecular basis of tumor type and pathway selection are still obscure. Here, we identify the primary cilium as a critical determinant controlling tumor pathway switching. Strikingly, Smoothened inhibitor-resistant BCCs have an increased mutational load in ciliome genes, resulting in reduced primary cilia and HH pathway activation compared with naive or Gorlin syndrome patient BCCs. Gene set enrichment analysis of resistant BCCs with a low HH pathway signature showed increased Ras/MAPK pathway activation. Tissue analysis confirmed an inverse relationship between primary cilia presence and Ras/MAPK activation, and primary cilia removal in BCCs potentiated Ras/MAPK pathway activation. Moreover, activating Ras in HH-responsive cell lines conferred resistance to both canonical (vismodegib) and noncanonical (atypical protein kinase C and MRTF inhibitors) HH pathway inhibitors and conferred sensitivity to MAPK inhibitors. Our results provide insights into BCC treatment and identify the primary cilium as an important lineage gatekeeper, preventing HH-to-Ras/MAPK pathway switching.

Potential new biomarkers for endometrial cancer

BACKGROUND

Incidence of endometrial cancer are rising both in the United States and worldwide. As endometrial cancer becomes more prominent, the need to develop and characterize biomarkers for early stage diagnosis and the treatment of endometrial cancer has become an important priority. Several biomarkers currently used to diagnose endometrial cancer are directly related to obesity. Although epigenetic and mutational biomarkers have been identified and have resulted in treatment options for patients with specific aberrations, many tumors do not harbor those specific aberrations. A promising alternative is to determine biomarkers based on differential gene expression, which can be used to estimate prognosis.

METHODS

We evaluated 589 patients to determine differential expression between normal and malignant patient samples. We then supplemented these evaluations with immunohistochemistry staining of endometrial tumors and normal tissues. Additionally, we used the Library of Integrated Network-based Cellular Signatures to evaluate the effects of 1826 chemotherapy drugs on 26 cell lines to determine the effects of each drug on HPRT1 and AURKA expression.

RESULTS

Expression of HPRT1, Jag2, AURKA, and PGK1 were elevated when compared to normal samples, and HPRT1 and PGK1 showed a stepwise elevation in expression that was significantly related to cancer grade. To determine the prognostic potential of these genes, we evaluated patient outcome and found that levels of both HPRT1 and AURKA were significantly correlated with overall patient survival. When evaluating drugs that had the most significant effect on lowering the expression of HPRT1 and AURKA, we found that Topo I and MEK inhibitors were most effective at reducing HPRT1 expression. Meanwhile, drugs that were effective at reducing AURKA expression were more diverse (MEK, Topo I, MELK, HDAC, etc.). The effects of these drugs on the expression of HPRT1 and AURKA provides insight into their role within cellular maintenance.

CONCLUSIONS

Collectively, these data show that JAG2, AURKA, PGK1, and HRPT1 have the potential to be used independently as diagnostic, prognostic, or treatment biomarkers in endometrial cancer. Expression levels of these genes may provide physicians with insight into tumor aggressiveness and chemotherapy drugs that are well suited to individual patients.

A Four-gene Decision Tree Signature Classification of Triple-negative Breast Cancer: Implications for Targeted Therapeutics

The molecular complexity of triple-negative breast cancers (TNBCs) provides a challenge for patient management. We set out to characterize this heterogeneous disease by combining transcriptomics and genomics data, with the aim of revealing convergent pathway dependencies with the potential for treatment intervention. A Bayesian algorithm was used to integrate molecular profiles in two TNBC cohorts, followed by validation using five independent cohorts (n = 1,168), including three clinical trials. A four-gene decision tree signature was identified, which robustly classified TNBCs into six subtypes. All four genes in the signature (EXO1, TP53BP2, FOXM1, and RSU1) are associated with either genomic instability, malignant growth, or treatment response. One of the six subtypes, MC6, encompassed the largest proportion of tumors (∼50%) in early diagnosed TNBCs. In TNBC patients with metastatic disease, the MC6 proportion was reduced to 25%, and was independently associated with a higher response rate to platinum-based chemotherapy. In TNBC cell line data, platinum sensitivity was recapitulated, and a sensitivity to the inhibition of the phosphatase PPM1D was revealed. Molecularly, MC6-TNBCs displayed high levels of telomeric allelic imbalances, enrichment of CD4+ and CD8+ immune signatures, and reduced expression of genes negatively regulating the MAPK signaling pathway. These observations suggest that our integrative classification approach may identify TNBC patients with discernible and theoretically pharmacologically tractable features that merit further studies in prospective trials.

AURKA contributes to the progression of oral squamous cell carcinoma (OSCC) through modulating epithelial-to-mesenchymal transition (EMT) and apoptosis via the regulation of ROS

Oral squamous cell carcinoma (OSCC) is known as one of the most common cancer influencing the head and neck region. However, the molecular mechanisms revealing OSCC progression is largely unclear. Aurora kinase A (AURKA) is a serine-threonine kinase that functions in mitotic spindle formation and chromosome segregation, and is associated with the progression of human cancers. But its role in regulating OSCC development has not yet been investigated. In the study, we found that AURKA expression was up-regulated in OSCC cell lines and tumor specimens from patients. OSCC patients with high expression of AURKA exhibited a significant decreased overall survival rate. In vitro, AURKA knockdown markedly reduced the proliferation, migration and invasion of OSCC cells using cell counting kit-8 (CCK-8), EdU, colony formation and transwell analysis. EMT was suppressed by AURKA silence, as evidenced by the up-regulated expression of E-cadherin and down-regulated Vimentin in OSCC cells. In addition, apoptosis was markedly induced by AURKA inhibition through promoting the expression of cleaved Caspase-3 and poly (ADP)-ribose polymerase (PARP). Reactive oxygen species (ROS) production was also markedly enhanced in AURKA-knockdown OSCC cells. Importantly, we found that repressing ROS generation using its scavenger of n-acetylcysteine (NAC) significantly abolished AURKA silence-induced apoptosis, accompanied with restored proliferation and EMT. In vivo, AURKA knockdown notably inhibited tumor growth. Therefore, knockdown of AURKA suppressed cell proliferation, migration and invasion, and also induced apoptosis and ROS generation in OSCC possibly via the production of ROS, demonstrating that AURKA inhibition might represent a novel therapeutic target for the prevention of OSCC.

Identification of Core Biomarkers Associated with Outcome in Glioma: Evidence from Bioinformatics Analysis

Glioma is the most common neoplasm of the central nervous system (CNS); the progression and outcomes of which are affected by a complicated network of genes and pathways. We chose a gene expression profile of GSE66354 from GEO database to search core biomarkers during the occurrence and development of glioma. A total of 149 samples, involving 136 glioma and 13 normal brain tissues, were enrolled in this article. 1980 differentially expressed genes (DEGs) including 697 upregulated genes and 1283 downregulated genes between glioma patients and healthy individuals were selected using GeoDiver and GEO2R tool. Then, gene ontology (GO) analysis as well as Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were carried out using the Database for Annotation, Visualization and Integrated Discovery (DAVID). Moreover, Cytoscape with Search Tool for the Retrieval of Interacting Genes (STRING) and Molecular Complex Detection (MCODE) plug-in was employed to imagine protein-protein interaction (PPI) of these DEGs. The upregulated genes were enriched in cell cycle, ECM-receptor interaction, and p53 signaling pathway, while the downregulated genes were enriched in retrograde endocannabinoid signaling, glutamatergic synapse, morphine addiction, GABAergic synapse, and calcium signaling pathway. Subsequently, 4 typical modules were discovered by the PPI network utilizing MCODE software. Besides, 15 hub genes were chosen according to the degree of connectivity, including TP53, CDK1, CCNB1, and CCNB2, the Kaplan-Meier analysis of which was further identified. In conclusion, this bioinformatics analysis indicated that DEGs and core genes, such as TP53, might influence the development of glioma, especially in tumor proliferation, which were expected to be promising biomarkers for diagnosis and treatment of glioma.

Analysis of potential genes associated with primary cilia in bladder cancer

Background

Dysfunction of primary cilia (PC), which could influence cell cycle and modulate cilia-related signaling transduction, has been reported in several cancers. However, there is no evidence of their function in bladder cancer (BLCA). This study was performed to investigate the presence of PC in BLCA and to explore the potential molecular mechanisms underlying the PC in BLCA.

Patients and methods

The presence of PC was assessed in BLCA and adjacent non-cancerous tissues. The gene expression dataset GSE52519 was employed to obtain differentially expressed genes (DEGs) associated with PC. The mRNA expression of the DEGs were confirmed by Gene Expression Profiling Interactive Analysis. The DEGs properties and pathways were analyzed by Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis. Genomatix software was used to predict putative transcription factor binding sites (TFBS) in the promoter region of DEGs, and the transcription factors were achieved according to the shared TFBS, which were supported by the ChIP-Sequence data.

Results

PC were found to be reduced in BLCA tissue samples in this study. Seven DEGs were observed to be associated with PC, and gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis indicated that these DEGs exhibited the properties and functions of PC, and that the Hedgehog signaling pathway probably participated in the pathogenesis and progression of BLCA. The mRNA expression of the seven DEGs in 404 BLCA and 28 normal tissue samples were analyzed, and five DEGs including CENPF, STIL, AURKA, STK39 and OSR1 were identified. Five TFBS including CREB, E2FF, EBOX, ETSF and HOXF in the promoter region of five DEGs were calculated and the transcription factors were obtained according to the shared TFBS.

Conclusion

PC were found to be reduced in BLCA, and the potential molecular mechanisms of PC in BLCA helped to provide novel diagnosis and therapeutic targets for BLCA.

Polymer Nanovesicle-Mediated Delivery of MLN8237 Preferentially Inhibits Aurora Kinase A To Target RalA and Anchorage-Independent Growth in Breast Cancer Cells

The small GTPase RalA is a known mediator of anchorage-independent growth in cancers and is differentially regulated by adhesion and aurora kinase A (AURKA). Hence, inhibiting AURKA offers a means of specifically targeting RalA (over RalB) in cancer cells. MLN8237 (alisertib) is a known inhibitor of aurora kinases; its specificity for AURKA, however, is compromised by its poor solubility and transport across the cell membrane. A polymer nanovesicle platform is used for the first time to deliver and differentially inhibit AURKA in cancer cells. For this purpose, polysaccharide nanovesicles made from amphiphilic dextran were used as nanocarriers to successfully administer MLN8237 (V_MLN) in cancer cells in 2D and 3D microenvironments. These nanovesicles (<200 nm) carry the drug in their intermembrane space with up to 85% of it released by the action of esterase enzyme(s). Lysotracker experiments reveal the polymer nanovesicles localize in the lysosomal compartment of the cell, where they are enzymatically targeted and MLN released in a controlled manner. Rhodamine B fluorophore trapped in the nanovesicles hydrophilic core (V_MLN+RhB) allows us to visualize its uptake and localization in cells in a 2D and 3D microenvironment. In breast cancer, MCF-7 cells V_MLN inhibits AURKA significantly better than the free drug at low concentrations (0.02-0.04 μM). This ensures that the drug in V_MLN at these concentrations can specifically inhibit up to 94% of endogenous AURKA without affecting AURKB. This targeting of AURKA causes the downstream differential inhibition of active RalA (but not RalB). Free MLN8237 at similar concentrations and conditions failed to affect RalA activation. V_MLN-mediated inhibition of RalA, in turn, disrupts the anchorage-independent growth of MCF-7 cells supporting a role for the AURKA-RalA crosstalk in mediating the same. These studies not only identify the polysaccharide nanovesicle to be an improved way to efficiently deliver low concentrations of MLN8237 to inhibit AURKA but, in doing so, also help reveal a role for AURKA and its crosstalk with RalA in anchorage-independent growth of MCF-7 cells.

Aurora kinase A (AURKA) interaction with Wnt and Ras-MAPK signalling pathways in colorectal cancer

Hyperactivation of Wnt and Ras-MAPK signalling are common events in development of colorectal adenomas. Further progression from adenoma-to-carcinoma is frequently associated with 20q gain and overexpression of Aurora kinase A (AURKA). Interestingly, AURKA has been shown to further enhance Wnt and Ras-MAPK signalling. However, the molecular details of these interactions in driving colorectal carcinogenesis remain poorly understood. Here we first performed differential expression analysis (DEA) of AURKA knockdown in two colorectal cancer (CRC) cell lines with 20q gain and AURKA overexpression. Next, using an exact algorithm, Heinz, we computed the largest connected protein-protein interaction (PPI) network module of significantly deregulated genes in the two CRC cell lines. The DEA and the Heinz analyses suggest 20 Wnt and Ras-MAPK signalling genes being deregulated by AURKA, whereof β-catenin and KRAS occurred in both cell lines. Finally, shortest path analysis over the PPI network revealed eight 'connecting genes' between AURKA and these Wnt and Ras-MAPK signalling genes, of which UBE2D1, DICER1, CDK6 and RACGAP1 occurred in both cell lines. This study, first, confirms that AURKA influences deregulation of Wnt and Ras-MAPK signalling genes, and second, suggests mechanisms in CRC cell lines describing these interactions.

Exact association test for small size sequencing data

Background

Recent statistical methods for next generation sequencing (NGS) data have been successfully applied to identifying rare genetic variants associated with certain diseases. However, most commonly used methods (e.g., burden tests and variance-component tests) rely on large sample sizes. Notwithstanding, due to its-still high cost, NGS data is generally restricted to small sample sizes, that cannot be analyzed by most existing methods.

Methods

In this work, we propose a new exact association test for sequencing data that does not require a large sample approximation, which is applicable to both common and rare variants. Our method, based on the Generalized Cochran-Mantel-Haenszel (GCMH) statistic, was applied to NGS datasets from intraductal papillary mucinous neoplasm (IPMN) patients. IPMN is a unique pancreatic cancer subtype that can turn into an invasive and hard-to-treat metastatic disease.

Results

Application of our method to IPMN data successfully identified susceptible genes associated with progression of IPMN to pancreatic cancer.

Conclusions

Our method is expected to identify disease-associated genetic variants more successfully, and corresponding signal pathways, improving our understanding of specific disease’s etiology and prognosis.

Aurora kinase A interacts with H-Ras and potentiates Ras-MAPK signaling

In cancer, upregulated Ras promotes cellular transformation and proliferation in part through activation of oncogenic Ras-MAPK signaling. While directly inhibiting Ras has proven challenging, new insights into Ras regulation through protein-protein interactions may offer unique opportunities for therapeutic intervention. Here we report the identification and validation of Aurora kinase A (Aurora A) as a novel Ras binding protein. We demonstrate that the kinase domain of Aurora A mediates the interaction with the N-terminal domain of H-Ras. Further more, the interaction of Aurora A and H-Ras exists in a protein complex with Raf-1. We show that binding of H-Ras to Raf-1 and subsequent MAPK signaling is enhanced by Aurora A, and requires active H-Ras. Thus, the functional linkage between Aurora A and the H-Ras/Raf-1 protein complex may provide a mechanism for Aurora A's oncogenic activity through direct activation of the Ras/MAPK pathway.

Dual-specificity phosphatase 6 (DUSP6): a review of its molecular characteristics and clinical relevance in cancer

Mitogen-activated protein kinases (MAPKs) are the main regulators of cellular proliferation, growth, and survival in physiological or pathological conditions. Aberrant MAPK signaling plays a pivotal role in carcinogenesis, which leads to development and progression of human cancer. Dual-specificity phosphatase 6 (DUSP6), a member of the MAPK phosphatase family, interacts with specifically targeted extracellular signal-regulated kinase 1/2 via negative feedback regulation in the MAPK pathway of mammalian cells. This phosphatase functions in a dual manner, pro-oncogenic or tumor-suppressive, depending on the type of cancer. To date, the tumor-suppressive role of DUSP6 has been demonstrated in pancreatic cancer, non-small cell lung cancer, esophageal squamous cell and nasopharyngeal carcinoma, and ovarian cancer. Its pro-oncogenic role has been observed in human glioblastoma, thyroid carcinoma, breast cancer, and acute myeloid carcinoma. Both roles of DUSP6 have been documented in malignant melanoma depending on the histological subtype of the cancer. Loss- or gain-of-function effects of DUSP6 in these cancers highlights the significance of this phosphatase in carcinogenesis. Development of methods that use the DUSP6 gene as a therapeutic target for cancer treatment or as a prognostic factor for diagnosis and evaluation of cancer treatment outcome has great potential. This review focuses on molecular characteristics of the DUSP6 gene and its role in cancers in the purview of development, progression, and cancer treatment outcome.

AURKA Overexpression Is Driven by FOXM1 and MAPK/ERK Activation in Melanoma Cells Harboring BRAF or NRAS Mutations: Impact on Melanoma Prognosis and Therapy

The cell cycle-related genes AURKA and FOXM1 are overexpressed in melanoma. We show here that AURKA overexpression is associated with poor prognosis in three independent cohorts of melanoma patients and correlates with the presence of genomic amplification of AURKA locus and BRAF^V600E mutation. AURKA overexpression may also be driven by increased promoter activation through elements such as ETS and FOXM1 found within the 5' proximal promoter region. Activated MAPK/ERK signaling pathway mediates robust AURKA promoter activation, thereby knockdown of BRAF^V600E and ERK inhibition results in reduced AURKA transcription and expression. We show a positive correlation between FOXM1 and AURKA expression in three independent cohorts of melanoma patients. FOXM1 silencing decreases expression of AURKA and late cell cycle genes in melanoma cells. We further found that FOXM1 expression levels are significantly higher in tumors carrying the BRAF^V600E mutation compared with the wild-type BRAF (BRAF^wt). Accordingly, the knockdown of BRAF^V600E also reduces the expression of FOXM1 in BRAF^V600E cells. Moreover, Aurora kinase A and FOXM1 inhibition by either genetic knockdown or pharmacologic inhibitors impair melanoma growth and survival both in culture and in vivo, underscoring their therapeutic value for melanoma patients who fail to benefit from BRAF/MEK signaling inhibition.

HDAC2 promotes loss of primary cilia in pancreatic ductal adenocarcinoma

Loss of primary cilia is frequently observed in tumor cells, including pancreatic ductal adenocarcinoma (PDAC) cells, suggesting that the absence of this organelle may promote tumorigenesis through aberrant signal transduction and the inability to exit the cell cycle. However, the molecular mechanisms that explain how PDAC cells lose primary cilia are still ambiguous. In this study, we found that inhibition or silencing of histone deacetylase 2 (HDAC2) restores primary cilia formation in PDAC cells. Inactivation of HDAC2 results in decreased Aurora A expression, which promotes disassembly of primary cilia. We further showed that HDAC2 controls ciliogenesis independently of Kras, which facilitates Aurora A expression. These studies suggest that HDAC2 is a novel regulator of primary cilium formation in PDAC cells.

Protective effects and mechanism of TPX2 on neurocyte apoptosis of rats in Alzheimer's disease model

We investigated the protective effects and mechanism of TPX2 on apoptosis of rat neurocytes. A total of 90 SD rats were randomly divided into the drug group, the control group and the blank group, with 30 rats in each group. The rats in the drug group and in the blank group were anesthetized with 10% chloral hydrate (at the dose of 0.5 ml/100 g) and Aβ_1-42, with the concentration of 5 µl (1 µg/µl), was injected in the exact position of bilateral hippocampal areas of rats to establish the model. The configured TPX2 inhibitors and edible benne oil were mixed and made into a suspension. After model establishment, the rats were given different treatment methods; the rats in the drug group were given gavage administration in the proportion of 75 mg/kg once a day. The rats in the control group were given intragastric administration with the same proportion of physiological saline once a day. The blank group was the normal healthy group and the rats in this group did not undergo any surgery or drug treatment. Brain tissue in rats were divided into two parts, one part was fixed, dehydrated, paraffin-embedded and made into slices of approximately 5 µm. TUNEL staining was used to examine the apoptosis of brain tissue, H&E staining was used to observe the brain tissue cells of each group, and western blotting for detecting the MAPK, Erk and expression levels of p38 and RT-polymerase chain reaction method was employed to examine mRNA expression levels of MAPK, Erk and p21. After one week, TUNEL staining showed that apoptosis of brain tissue in the drug group was significantly greater than those of the control and blank groups. The protein expression levels of MAPK, Erk and p38 were significantly higher than those of the control group and the normal healthy group; the differences were statistically significant (P<0.05). Western blotting showed that the protein expression levels of MAPK, Erk and p38 of the drug group were significantly lower than those of the control group but higher than those of the normal healthy group; the differences were statistically significant (P<0.05). TPX2 has a protective effect on the apoptosis of brain tissue processed by Aβ_1-42, which plays its role through the inhibition of the protein expression levels of MAPK, Erk and p38.

Epigenetic silencing of miR-137 induces drug resistance and chromosomal instability by targeting AURKA in multiple myeloma

Multiple myeloma (MM) is the second most prevalent hematologic malignancy. Aberrant microRNAs (miRNAs) expression has been shown to be involved in the pathogenesis of MM. In this study, we further demonstrated that miR-137 was significantly downregulated in MM and negatively correlated with clinical prognosis. Moreover, we described the epigenetic regulation of miR-137 and its association with progression-free survival in MM patients. Furthermore, overexpression of miR-137 in MM cell line (miR-137 OE) increased its sensitivity to bortezomib and eprirubicin in vitro. Also, some high-risk genetic abnormalities in MM, including deletion of chromosome 1p22.2, 14q or 17p13, and gain of chromosome 1p22.2 were detected in NCI-H929 empty vector (NCI-H929 EV) treated cells but not in the NCI-H929 miR-137 overexpression (NCI-H929 miR-137 OE) cells. Luciferase reporter assays demonstrated that miR-137 targeted AURKA. Ectopic expression of miR-137 strongly reduced the expression of AURKA and p-ATM/Chk2 in MM cells, and increased the expression of p53, and p21. Importantly, miR-137 overexpression together with bortezomib treatment significantly inhibited tumor growth in MM xenograft model. Taken together, this study demonstrates that miR-137 is epigenetically silenced in MM, and overexpression of miR-137 could reduce drug resistance and overcome chromosomal instability of the MM cells via affecting the apoptosis and DNA damage pathways.

Exome-Scale Discovery of Hotspot Mutation Regions in Human Cancer Using 3D Protein Structure

The impact of somatic missense mutation on cancer etiology and progression is often difficult to interpret. One common approach for assessing the contribution of missense mutations in carcinogenesis is to identify genes mutated with statistically nonrandom frequencies. Even given the large number of sequenced cancer samples currently available, this approach remains underpowered to detect drivers, particularly in less studied cancer types. Alternative statistical and bioinformatic approaches are needed. One approach to increase power is to focus on localized regions of increased missense mutation density or hotspot regions, rather than a whole gene or protein domain. Detecting missense mutation hotspot regions in three-dimensional (3D) protein structure may also be beneficial because linear sequence alone does not fully describe the biologically relevant organization of codons. Here, we present a novel and statistically rigorous algorithm for detecting missense mutation hotspot regions in 3D protein structures. We analyzed approximately 3 × 10(5) mutations from The Cancer Genome Atlas (TCGA) and identified 216 tumor-type-specific hotspot regions. In addition to experimentally determined protein structures, we considered high-quality structural models, which increase genomic coverage from approximately 5,000 to more than 15,000 genes. We provide new evidence that 3D mutation analysis has unique advantages. It enables discovery of hotspot regions in many more genes than previously shown and increases sensitivity to hotspot regions in tumor suppressor genes (TSG). Although hotspot regions have long been known to exist in both TSGs and oncogenes, we provide the first report that they have different characteristic properties in the two types of driver genes. We show how cancer researchers can use our results to link 3D protein structure and the biologic functions of missense mutations in cancer, and to generate testable hypotheses about driver mechanisms. Our results are included in a new interactive website for visualizing protein structures with TCGA mutations and associated hotspot regions. Users can submit new sequence data, facilitating the visualization of mutations in a biologically relevant context. Cancer Res; 76(13); 3719-31. ©2016 AACR.

Aurora kinase A in gastrointestinal cancers: time to target

Gastrointestinal (GI) cancers are a major cause of cancer-related deaths. During the last two decades, several studies have shown amplification and overexpression of Aurora kinase A (AURKA) in several GI malignancies. These studies demonstrated that AURKA not only plays a role in regulating cell cycle and mitosis, but also regulates a number of key oncogenic signaling pathways. Although AURKA inhibitors have moved to phase III clinical trials in lymphomas, there has been slower progress in GI cancers and solid tumors. Ongoing clinical trials testing AURKA inhibitors as a single agent or in combination with conventional chemotherapies are expected to provide important clinical information for targeting AURKA in GI cancers. It is, therefore, imperative to consider investigations of molecular determinants of response and resistance to this class of inhibitors. This will improve evaluation of the efficacy of these drugs and establish biomarker based strategies for enrollment into clinical trials, which hold the future direction for personalized cancer therapy. In this review, we will discuss the available data on AURKA in GI cancers. We will also summarize the major AURKA inhibitors that have been developed and tested in pre-clinical and clinical settings.