Interferon regulatory factor 1 is an independent predictor of platinum resistance and survival in high-grade serous ovarian carcinoma. Gynecol Oncol. 2014;134:591-598. [PMID: 24995581 DOI: 10.1016/j.ygyno.2014.06.025]

Increased IFN-β indicates better survival in hepatocellular carcinoma treated with radiotherapy

Preclinical data suggest that type I interferon (IFN) responsiveness is essential for the antitumor effects of radiotherapy (RT). However, its clinical value remains unclear. This study aimed to explore this from a clinical perspective. In cohort 1, data from 152 hepatocellular carcinoma (HCC) patients who received RT were analyzed. Blood samples were taken 1 day before and 2 weeks after RT. RT was found to increase serum levels of IFN-β (a subtype of IFN-I) in HCC patients (3.42 ± 1.57 to 5.51 ± 2.11 pg/ml, P < 0.01), particularly in those with favorable responses. Higher post-RT serum IFN-β levels (≥4.77 pg/ml) were associated with better progression-free survival (HR = 0.58, P < 0.01). Cohort 2 included 46 HCC patients, including 23 who underwent preoperative RT and 23 matched control HCC who received surgical resection without RT. Formalin-fixed paraffin-embedded samples were obtained. Neoadjuvant RT significantly increased IFN-β expression in tumor tissues compared to direct surgery (8.13% ± 5.19% to 15.10% ± 5.89%, P < 0.01). Higher post-RT IFN-β (>median) indicated better disease-free survival (P = 0.049). Additionally, increased CD11c+MHCII+CD141+ antigen-presenting cell subsets and CD103+CD39+CD8+ tumor-infiltrating lymphocytes were found in the higher IFN-β group (P = 0.02, P = 0.03), which may contribute to the favorable prognosis in higher IFN-β group. Collectively, these findings suggest that IFN-β response activated by radiation may serve as a prognostic biomarker for HCC patients undergoing RT.

The multiple roles of interferon regulatory factor family in health and disease

Interferon Regulatory Factors (IRFs), a family of transcription factors, profoundly influence the immune system, impacting both physiological and pathological processes. This review explores the diverse functions of nine mammalian IRF members, each featuring conserved domains essential for interactions with other transcription factors and cofactors. These interactions allow IRFs to modulate a broad spectrum of physiological processes, encompassing host defense, immune response, and cell development. Conversely, their pivotal role in immune regulation implicates them in the pathophysiology of various diseases, such as infectious diseases, autoimmune disorders, metabolic diseases, and cancers. In this context, IRFs display a dichotomous nature, functioning as both tumor suppressors and promoters, contingent upon the specific disease milieu. Post-translational modifications of IRFs, including phosphorylation and ubiquitination, play a crucial role in modulating their function, stability, and activation. As prospective biomarkers and therapeutic targets, IRFs present promising opportunities for disease intervention. Further research is needed to elucidate the precise mechanisms governing IRF regulation, potentially pioneering innovative therapeutic strategies, particularly in cancer treatment, where the equilibrium of IRF activities is of paramount importance.

Prediction of Chemoresistance-How Preclinical Data Could Help to Modify Therapeutic Strategy in High-Grade Serous Ovarian Cancer

High-grade serous ovarian cancer (HGSOC) is one of the most lethal tumors generally and the most fatal cancer of the female genital tract. The approved standard therapy consists of surgical cytoreduction and platinum/taxane-based chemotherapy, and of targeted therapy in selected patients. The main therapeutic problem is chemoresistance of recurrent and metastatic HGSOC tumors which results in low survival in the group of FIGO III/IV. Therefore, the prediction and monitoring of chemoresistance seems to be of utmost importance for the improvement of HGSOC management. This type of cancer has genetic heterogeneity with several subtypes being characterized by diverse gene signatures and disturbed peculiar epigenetic regulation. HGSOC develops and metastasizes preferentially in the specific intraperitoneal environment composed mainly of fibroblasts, adipocytes, and immune cells. Different HGSOC subtypes could be sensitive to distinct sets of drugs. Moreover, primary, metastatic, and recurrent tumors are characterized by an individual biology, and thus diverse drug responsibility. Without a precise identification of the tumor and its microenvironment, effective treatment seems to be elusive. This paper reviews tumor-derived genomic, mutational, cellular, and epigenetic biomarkers of HGSOC drug resistance, as well as tumor microenvironment-derived biomarkers of chemoresistance, and discusses their possible use in the novel complex approach to ovarian cancer therapy and monitoring.

CD200 as a Potential New Player in Inflammation during Rotator Cuff Tendon Injury/Repair: An In Vitro Model

Rotator cuff tendon (RCT) disease results from multifactorial mechanisms, in which inflammation plays a key role. Pro-inflammatory cytokines and tendon stem cell/progenitor cells (TSPCs) have been shown to participate in the inflammatory response. However, the underlying molecular mechanism is still not clear. In this study, flow cytometry analyses of different subpopulations of RCT-derived TSPCs demonstrate that after three days of administration, TNFα alone or in combination with IFNγ significantly decreases the percentage of CD146+CD49d+ and CD146+CD49f+ but not CD146+CD109+ TSPCs populations. In parallel, the same pro-inflammatory cytokines upregulate the expression of CD200 in the CD146+ TSPCs population. Additionally, the TNFα/IFNγ combination modulates the protein expression of STAT1, STAT3, and MMP9, but not fibromodulin. At the gene level, IRF1, CAAT (CAAT/EBPbeta), and DOK2 but not NF-κb, TGRF2 (TGFBR2), and RAS-GAP are modulated. In conclusion, although our study has several important limitations, the results highlight a new potential role of CD200 in regulating inflammation during tendon injuries. In addition, the genes analyzed here might be new potential players in the inflammatory response of TSPCs.

Construction of miRNA-lncRNA-mRNA co-expression network affecting EMT-mediated cisplatin resistance in ovarian cancer

Platinum resistance is one of the major concerns in ovarian cancer treatment. Recent evidence shows the critical role of epithelial-mesenchymal transition (EMT) in this resistance. Epithelial-like ovarian cancer cells show decreased sensitivity to cisplatin after cisplatin treatment. Our study prospected the association between epithelial phenotype and response to cisplatin in ovarian cancer. Microarray dataset GSE47856 was acquired from the GEO database. After identifying differentially expressed genes (DEGs) between epithelial-like and mesenchymal-like cells, the module identification analysis was performed using weighted gene co-expression network analysis (WGCNA). The gene ontology (GO) and pathway analyses of the most considerable modules were performed. The protein-protein interaction network was also constructed. The hub genes were specified using Cytoscape plugins MCODE and cytoHubba, followed by the survival analysis and data validation. Finally, the co-expression of miRNA-lncRNA-TF with the hub genes was reconstructed. The co-expression network analysis suggests 20 modules relating to the Epithelial phenotype. The antiquewhite4, brown and darkmagenta modules are the most significant non-preserved modules in the Epithelial phenotype and contain the most differentially expressed genes. GO, and KEGG pathway enrichment analyses on these modules divulge that these genes were primarily enriched in the focal adhesion, DNA replication pathways and stress response processes. ROC curve and overall survival rate analysis show that the co-expression pattern of the brown module's hub genes could be a potential prognostic biomarker for ovarian cancer cisplatin resistance.

Leveraging Genomics, Transcriptomics, and Epigenomics to Understand the Biology and Chemoresistance of Ovarian Cancer

Ovarian cancer is a major cause of fatality due to a gynecological malignancy. This lethality is largely due to the unspecific clinical manifestations of ovarian cancer, which lead to late detection and to high resistance to conventional therapies based on platinum. In recent years, we have advanced our understanding of the mechanisms provoking tumor relapse, and the advent of so-called omics technologies has provided exceptional tools to evaluate molecular mechanisms leading to therapy resistance in ovarian cancer. Here, we review the contribution of genomics, transcriptomics, and epigenomics techniques to our knowledge about the biology and molecular features of ovarian cancers, with a focus on therapy resistance. The use of these technologies to identify molecular markers and mechanisms leading to chemoresistance in these tumors is discussed, as well as potential further applications.

Proteomic Studies on the Management of High-Grade Serous Ovarian Cancer Patients: A Mini-Review

High-grade serous ovarian cancer (HGSC) remains the most common and deadly subtype of ovarian cancer. It is characterized by its late diagnosis and frequent relapse despite standardized treatment with cytoreductive surgery and platinum-based chemotherapy. The past decade has seen significant advances in the clinical management and molecular understanding of HGSC following the publication of the Cancer Genome Atlas (TCGA) researchers and the introduction of targeted therapies with anti-angiogenic drugs and poly(ADP-ribose) polymerase inhibitors in specific subgroups of patients. We provide a comprehensive review of HGSC, focusing on the most important molecular advances aimed at providing a better understanding of the disease and its response to treatment. We emphasize the role that proteomic technologies are now playing in these two aspects of the disease, through the identification of proteins and their post-translational modifications in ovarian cancer tumors. Finally, we highlight how the integration of proteomics with genomics, exemplified by the work performed by the Clinical Proteomic Tumor Analysis Consortium (CPTAC), can guide the development of new biomarkers and therapeutic targets.

Integrin-Linked Kinase Is a Novel Therapeutic Target in Ovarian Cancer

OBJECTIVE

The objective of this study is to identify and validate novel therapeutic target(s) in ovarian cancer.

BACKGROUND

Development of targeted therapeutics in ovarian cancer has been limited by molecular heterogeneity. Although gene expression datasets are available, most of them lack appropriate pair-matched controls to define the alterations that result in the transformation of normal ovarian cells to cancerous cells.

METHODS

We used microarray to compare the gene expression of treatment-naïve ovarian cancer tissue samples to pair-matched normal adjacent ovarian tissue from 24 patients. Ingenuity Pathway Analysis (IPA) was used to identify target pathways for further analysis. Integrin-linked kinase (ILK) expression in SKOV3 and OV90 cells was determined using Western blot. ILK was knocked down using CRISPR/Cas9 constructs. Subcutaneous xenograft study to determine the effect of ILK knockdown on tumor growth was performed in NOD SCID gamma mice.

RESULTS

Significant upregulation of the ILK pathway was identified in 22 of the 24 cancer specimens, identifying it as a potential player that could contribute to the transformation of normal ovarian cells to cancerous cells. Knockdown of ILK in SKOV3 cells resulted in decreased cell proliferation and tumor growth, and inhibition of downstream kinase, AKT (protein kinase B). These results were further validated using an ILK-1 chemical inhibitor, compound 22.

CONCLUSION

Our initial findings validate ILK as a potential therapeutic target for molecular inhibition in ovarian cancer, which warrants further investigation.

Prognostic implication of proteomic profiles in head and neck squamous cell carcinoma

BACKGROUND AND OBJECTIVE

Head and neck squamous cell carcinoma (HNSCC) is one of the malignant cancers with poor prognosis. However, clinicopathologic and histological criteria were finite to predict the prognosis of HNSCC. We aimed to characterize the proteomic profile of prognosis from HNSCC patients.

MATERIAL AND METHODS

Reverse phase protein array (RPPA) data in HNSCC were downloaded from The Cancer Proteome Atlas (TCPA). Independent prognostic-related proteins (IPP) were screened by Cox regression model and Kaplan-Meier methods. IPP signature (IPPS) including selected proteins was conducted for prognostic prediction for HNSCC. Protein-protein network analysis and gene ontology (GO) enrichment were used to identify related functional proteins and pathways.

RESULTS

Based on the IPP, IPPS for HNSCC was constructed: risk score = (1.541* IRF1) + (1.460 * SMAD4) + (1.396 * LKB1) + (0.746* Cyclin E2) + (0.618* Paxillin) + (0.499* p-PEA-15 (Ser116)). The IPPS in HNSCC showed good predictive performance (area under curve = 0.779) with moderate sensitivity and specificity. Protein-protein network analysis and functional enrichment indicated an implication of response to decreased oxygen levels in HNSCC.

CONCLUSION

The identified proteomic signature might function as a prognostic tool for the management of HNSCC and provide novel target for the treatment of HNSCC.

Sequential Interferon β-Cisplatin Treatment Enhances the Surface Exposure of Calreticulin in Cancer Cells via an Interferon Regulatory Factor 1-Dependent Manner

Immunogenic cell death (ICD) refers to a unique form of cell death that activates an adaptive immune response against dead-cell-associated antigens. Accumulating evidence indicates that the efficacy of conventional anticancer agents relies on not only their direct cytostatic/cytotoxic effects but also the activation of antitumor ICD. Common anticancer ICD inducers include certain chemotherapeutic agents (such as anthracyclines, oxaliplatin, and bortezomib), radiotherapy, photodynamic therapy (PDT), and oncolytic virotherapies. However, most chemotherapeutic reagents are inefficient or fail to trigger ICD. Therefore, better understanding on the molecular determinants of chemotherapy-induced ICD will help in the development of more efficient combinational anticancer strategies through converting non- or relatively weak ICD inducers into bona fide ICD inducers. In this study, we found that sequential, but not concurrent, treatment of cancer cells with interferon β (IFNβ), a type I IFN, and cisplatin (an inefficient ICD inducer) can enhance the expression of ICD biomarkers in cancer cells, including surface translocation of an endoplasmic reticulum (ER) chaperone, calreticulin (CRT), and phosphorylation of the eukaryotic translation initiation factor alpha (eIF2α). These results suggest that exogenous IFNβ may activate molecular determinants that convert cisplatin into an ICD inducer. Further bioinformatics and in vitro experimental analyses found that interferon regulatory factor 1 (IRF1) acted as an essential mediator of surface CRT exposure by sequential IFNβ-cisplatin combination. Our findings not only help to design more effective combinational anticancer therapy using IFNβ and cisplatin, but also provide a novel insight into the role of IRF1 in connecting the type I IFN responses and ICD.

Interferons α and β in cancer: therapeutic opportunities from new insights

Over the past decade, preclinical and clinical research have confirmed the essential role of interferons for effective host immunological responses to malignant cells. Type I interferons (IFNα and IFNβ) directly regulate transcription of >100 downstream genes, which results in a myriad of direct (on cancer cells) and indirect (through immune effector cells and vasculature) effects on the tumour. New insights into endogenous and exogenous activation of type I interferons in the tumour and its microenvironment have given impetus to drug discovery and patient evaluation of interferon-directed strategies. When combined with prior observations or with other effective modalities for cancer treatment, modulation of the interferon system could contribute to further reductions in cancer morbidity and mortality. This Review discusses new interferon-directed therapeutic opportunities, ranging from cyclic dinucleotides to genome methylation inhibitors, angiogenesis inhibitors, chemoradiation, complexes with neoantigen-targeted monoclonal antibodies, combinations with other emerging therapeutic interventions and associations of interferon-stimulated gene expression with patient prognosis - all of which are strategies that have or will soon enter translational clinical evaluation.

Optimized Biobanking Procedures for Preservation of RNA in Tissue: Comparison of Snap-Freezing and RNAlater-Fixation Methods

Introduction: Personalized treatment, supported by biomarkers, would improve survival of ovarian cancer patients. RNA molecules are potentially important biomarkers. The Danish CancerBiobank provides an infrastructure for handling and storage of biological material, including RNA, from Danish cancer patients. The aim of this study was to investigate the effects of handling-time and fresh-freezing versus RNAlater^® fixation on RNA degradation in solid tissue from pelvic mass samples. Materials and Methods: We evaluated RNA quality in surgical tissue from patients with a pelvic mass. Corresponding samples were either fresh-frozen or fixed in RNAlater, at eight different time points after the surgery. Integrity was measured using a bioanalyzer, and the amount and quality were further investigated by quantitative reverse transcription-polymerase chain reaction measuring the expression of housekeeping genes B2M and HPRT1. Results: Our results show that tissue RNA is stable up to at least 180 minutes after the surgery, as the quality was comparable to the quality of RNA handled immediately. Likewise, patient RNA was of acceptable quality after both fresh-frezing and RNAlater fixation, but RNAlater fixation was slightly more effective for RNA preservation. Discussion and Conclusion: Our data suggest that RNA in pelvic mass samples is relatively stable. Knowledge about RNA stability is an important prerequisite for research in RNA biomarkers, where the challenge is to balance the need for careful RNA handling and storage with the need for effective large-scale biobanking in a busy clinical setting where patient treatment is the main priority.

Type I interferons and dendritic cells in cancer immunotherapy

Type I interferons (IFNs) facilitate cancer immunosurveillance, antitumor immunity and antitumor efficacy of conventional cell death-inducing therapies (chemotherapy/radiotherapy) as well as immunotherapy. Moreover, it is clear that dendritic cells (DCs) play a significant role in aiding type I IFN-driven immunity. Owing to these antitumor properties several immunotherapies involving, or inducing, type I IFNs have received considerable clinical attention, e.g., recombinant IFNα2 or agonists targeting pattern recognition receptor (PRR) pathways like Toll-like receptors (TLRs), cGAS-STING or RIG-I/MDA5/MAVS. A series of preclinical and clinical evidence concurs that the success of anticancer therapy hinges on responsiveness of both cancer cells and DCs to type I IFNs. In this article, we discuss this link between type I IFNs and DCs in the context of cancer biology, with particular attention to mechanisms behind type I IFN production, their impact on DC driven anticancer immunity, and the implications of this for cancer immunotherapy, including DC-based vaccines.

RNA sequencing (RNA-Seq) and its application in ovarian cancer

Despite the surgical and chemotherapeutic advances over the past few decades, ovarian cancer remains the leading cause of gynecological cancer-related mortality. The absence of biomarkers in early detection and the development of drug resistance are principal causes of treatment failure in ovarian cancer. Recent progress in RNA sequencing (RNA-Seq) with Next Generation Sequencing technology has expanded the understanding of the molecular pathogenesis of ovarian cancer. As compared to previous hybridization-based microarray and Sanger sequence-based methods, RNA-Seq provides multiple layers of resolutions and transcriptome complexity, with less background noise and a broader dynamic range of RNA expression. Beyond quantifying gene expression, the data generated by RNA-Seq accelerates the identification of alternatively spliced genes, fusion genes, mutations/SNPs, allele-specific expression, novel transcripts and non-coding RNAs. RNA-Seq has been successfully applied in ovarian cancer research for earlier detection, ascertaining pathological origin, and defining the aberrant genes and dysregulated molecular pathways across patient groups. This review outlines the distinct advantages of RNA-Seq compared to other transcriptomics methods and its recent applications in ovarian cancer.

The clinical significance and biological function of interferon regulatory factor 1 in cholangiocarcinoma

Interferon regulatory factor 1 (IRF1) has been suggested to act as a tumor suppressor in human cancers. However, the clinical significance and biological function of IRF1 in cholangiocarcinoma is poorly understood. In our results, IRF1 mRNA and protein expressions were decreased in cholangiocarcinoma tissues and cell lines compared with paired normal hepatic tissues and intrahepatic bile duct epithelial cell line. IRF1 protein low-expression was associated with tumor stage, tumor size, vascular invasion and metastasis and served as a poor independent prognostic parameter in cholangiocarcinoma patients. Up-regulation of IRF1 expression suppressed cholangiocarcinoma cells proliferation, migration and invasion, and blocked cell cycle progression, but has no effect on apoptosis. In conclusion, IRF1 is low-expressed in cholangiocarcinoma tissues and cell lines, and correlated with malignant status and prognosis in cholangiocarcinoma patients. IRF1 served as tumor suppressor in the regulation of cholangiocarcinoma cells proliferation, cell cycle, migration and invasion.

Universal attenuators and their interactions with feedback loops in gene regulatory networks

Using a combination of mathematical modelling, statistical simulation and large-scale data analysis we study the properties of linear regulatory chains (LRCs) within gene regulatory networks (GRNs). Our modelling indicates that downstream genes embedded within LRCs are highly insulated from the variation in expression of upstream genes, and thus LRCs act as attenuators. This observation implies a progressively weaker functionality of LRCs as their length increases. When analyzing the preponderance of LRCs in the GRNs of Escherichia coli K12 and several other organisms, we find that very long LRCs are essentially absent. In both E. coli and M. tuberculosis we find that four-gene LRCs are intimately linked to identical feedback loops that are involved in potentially chaotic stress response, indicating that the dynamics of these potentially destabilising motifs are strongly restrained under homeostatic conditions. The same relationship is observed in a human cancer cell line (K562), and we postulate that four-gene LRCs act as ‘universal attenuators’. These findings suggest a role for long LRCs in dampening variation in gene expression, thereby protecting cell identity, and in controlling dramatic shifts in cell-wide gene expression through inhibiting chaos-generating motifs.

A network-pathway based module identification for predicting the prognosis of ovarian cancer patients

Background

This study aimed to screen multiple genes biomarkers based on gene expression data for predicting the survival of ovarian cancer patients.

Methods

Two microarray data of ovarian cancer samples were collected from The Cancer Genome Atlas (TCGA) database. The data in the training set were used to construct Reactome functional interactions network, which then underwent Markov clustering, supervised principal components, Cox proportional hazard model to screen significantly prognosis related modules. The distinguishing ability of each module for survival was further evaluated by the testing set. Gene Ontology (GO) functional and pathway annotations were performed to identify the roles of genes in each module for ovarian cancer.

Results

The network based approach identified two 7-gene functional interaction modules (31: DCLRE1A, EXO1, KIAA0101, KIN, PCNA, POLD3, POLD2; 35: DKK3, FABP3, IRF1, AIM2, GBP1, GBP2, IRF2) that are associated with prognosis of ovarian cancer patients. These network modules are related to DNA repair, replication, immune and cytokine mediated signaling pathways.

Conclusions

The two 7-gene expression signatures may be accurate predictors of clinical outcome in patients with ovarian cancer and has the potential to develop new therapeutic strategies for ovarian cancer patients.

Screening differentially expressed genes in hepatocellular carcinoma by cross-species and cross-carcinogenic factors strategy based on RNA-Seq

AIM: To identify key molecules involved in progression of hepatocellular carcinoma (HCC) by cross-species (human and tupaia) and cross-carcinogenic factors (HBV and AFB1) strategy based on RNA sequencing (RNA-Seq).

METHODS: The transcripts in human and tupaia HCC, tumor adjacent liver tissue (para-HCC) and normal liver tissue were thoroughly analyzed by RNA sequencing. Tupaia HCC was induced by HBV infection or aflatoxin B1 (AFB1). Differentially expressed genes were collected between these tissues, and common differential genes which cross human and Tupaia as well as HBV and AFB1 carcinogenic factors were identified.

RESULTS: Compared to human para-HCC and normal liver tissues, 68 differential genes were screened in human HCC, among which 14 were up-regulated and 54 down-regulated. Compared to Tupaia para-HCC and normal liver tissues, 314 differential genes were screened in HBV induced Tupaia HCC, and 20 were screened in AFB1 induced Tupaia HCC. There were 11 common differential genes between HBV and AFB1 induced Tupaia HCC, all of which were down-regulated. There were 2 common differential genes between human HCC and Tupaia HCC, and they were apolipoprotein F (APOF) and insulin-like growth factor binding protein, acid labile subunit (IGFALS), both of which were down-regulated in HCC.

CONCLUSION: The cross-species, cross-carcinogenic factors screening strategy based on RNA-Seq may promote the process of identifying key molecules for human HCC. APOF and IGFALS may be important factors for HCC.

Recently identified drug resistance biomarkers in ovarian cancer

Ovarian cancer, consisting mainly of ovarian carcinoma, is the most lethal gynecologic malignancy. Improvements in outcome for patients with advanced-stage disease are limited by intrinsic and acquired chemoresistance and by tumor heterogeneity at different anatomic sites and along disease progression. Molecules and cellular pathways mediating chemoresistance appear to be different for the different histological types of ovarian carcinoma, with most recent research focusing on serous and clear cell carcinoma. This review discusses recent data implicating various biomarkers in chemoresistance in this cancer, with focus on studies in which clinical specimens have been central.