IGFBP-4 tumor and serum levels are increased across all stages of epithelial ovarian cancer

Design and Fabrication of a 3D-Printed Microfluidic Immunoarray for Ultrasensitive Multiplexed Protein Detection

Microfluidic technology has revolutionized device fabrication by merging principles of fluid dynamics with technologies from chemistry, physics, biology, material science, and microelectronics. Microfluidic systems manipulate small volumes of fluids to perform automated tasks with applications ranging from chemical syntheses to biomedical diagnostics. The advent of low-cost 3D printers has revolutionized the development of microfluidic systems. For measuring molecules, 3D printing offers cost-effective, time, and ease-of-designing benefits. In this paper, we present a comprehensive tutorial for design, optimization, and validation for creating a 3D-printed microfluidic immunoarray for ultrasensitive detection of multiple protein biomarkers. The target is the development of a point of care array to determine five protein biomarkers for aggressive cancers. The design phase involves defining dimensions of microchannels, reagent chambers, detection wells, and optimizing parameters and detection methods. In this study, the physical design of the array underwent multiple iterations to optimize key features, such as developing open detection wells for uniform signal distribution and a flap for covering wells during the assay. Then, full signal optimization for sensitivity and limit of detection (LOD) was performed, and calibration plots were generated to assess linear dynamic ranges and LODs. Varying characteristics among biomarkers highlighted the need for tailored assay conditions. Spike-recovery studies confirmed the assay's accuracy. Overall, this paper showcases the methodology, rigor, and innovation involved in designing a 3D-printed microfluidic immunoarray. Optimized parameters, calibration equations, and sensitivity and accuracy data contribute valuable metrics for future applications in biomarker analyses.

Development and Validation of a Prognostic Risk Model Based on Nature Killer Cells for Serous Ovarian Cancer

Nature killer (NK) cells are increasingly considered important in tumor microenvironment, but their role in predicting the prognosis of ovarian cancer has not been revealed. This study aimed to develop a prognostic risk model for ovarian cancer based on NK cells. Firstly, differentially expressed genes (DEGs) of NK cells were found by single-cell RNA-sequencing dataset analysis. Based on six NK-cell DEGs identified by univariable, Lasso and multivariable Cox regression analyses, a prognostic risk model for serous ovarian cancer was developed in the TCGA cohort. This model was then validated in three external cohorts, and evaluated as an independent prognostic factor by multivariable Cox regression analysis together with clinical characteristics. With the investigation of the underlying mechanism, a relation between a higher risk score of this model and more immune activities in tumor microenvironment was revealed. Furthermore, a detailed inspection of infiltrated immunocytes indicated that not only quantity, but also the functional state of these immunocytes might affect prognostic risk. Additionally, the potential of this model to predict immunotherapeutic response was exhibited by evaluating the functional state of cytotoxic T lymphocytes. To conclude, this study introduced a novel prognostic risk model based on NK-cell DEGs, which might provide assistance for the personalized management of serous ovarian cancer patients.

Transforming Diagnosis and Therapeutics Using Cancer Genomics

In past quarter of the century, much has been understood about the genetic variation and abnormal genes that activate cancer in humans. All the cancers somehow possess alterations in the DNA sequence of cancer cell's genome. In present, we are heading toward the era where it is possible to obtain complete genome of the cancer cells for their better diagnosis, categorization and to explore treatment options.

Wnt antagonist as therapeutic targets in ovarian cancer

Ovarian cancer is a fatal malignancy in women with a low survival rate that demands new therapeutic paradigms. Cancer cells acquire various exclusive alterations to proliferate, invade, metastasize, and escape cell death, acting independently of growth-inducing or growth-inhibiting signals. The nature of cellular signaling in tumorigenesis is interwoven. Wnt signaling is an evolutionarily conserved signaling cascade that has been shown to regulate ovarian cancer pathogenesis. The molecular mechanism of Wnt signaling underlying the development of ovarian cancer, drug resistance, and relapse is not completely understood. Extracellularly secreted Wnt signaling inhibitors are crucial regulators of ovarian cancer tumorigenesis and malignant properties of cancer stem cells. Wnt inhibitors arbitrated modifications affecting Wnt pathway proteins on the cell membranes, in the cytoplasm, and in the nucleus have been shown to span essential contributions in the initiation, progression, and chemoresistance of ovarian cancer. Although many extrinsic inhibitors developed targeting the downstream components of the Wnt signaling pathway, investigating the molecular mechanisms of endogenous secreted inhibitors might substantiate prognostic or therapeutic biomarkers development. Given the importance of Wnt signaling in ovarian cancer, more systematic studies combined with clinical studies are requisite to probe the precise mechanistic interactions of Wnt antagonists in ovarian cancer. This review outlines the latest progress on the Wnt antagonists and ovarian cancer-specific regulators such as micro-RNAs, small molecules, and drugs regulating these Wnt antagonists in ovarian tumourigenesis.

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.

Current Achievements and Applications of Transcriptomics in Personalized Cancer Medicine

Over the last decades, transcriptome profiling emerged as one of the most powerful approaches in oncology, providing prognostic and predictive utility for cancer management. The development of novel technologies, such as revolutionary next-generation sequencing, enables the identification of cancer biomarkers, gene signatures, and their aberrant expression affecting oncogenesis, as well as the discovery of molecular targets for anticancer therapies. Transcriptomics contribute to a change in the holistic understanding of cancer, from histopathological and organic to molecular classifications, opening a more personalized perspective for tumor diagnostics and therapy. The further advancement on transcriptome profiling may allow standardization and cost reduction of its analysis, which will be the next step for transcriptomics to become a canon of contemporary cancer medicine.

The Prognostic Values of the Insulin-Like Growth Factor Binding Protein Family in Ovarian Cancer

Purpose

To assess the expression of insulin-like growth factor binding protein (IGFBP) family and its prognostic impact in ovarian cancer (OC) patients.

Materials and Methods

The mRNA expression and protein expression of individual IGFBPs in healthy ovarian samples and OC tissues were explored through Oncomine, Gene Expression Profiling Interactive Analysis, and Human Protein Atlas database. Additionally, the prognostic values of the six IGFBP members in patients with OC were evaluated by Kaplan-Meier plotter.

Results

IGFBP2 and IGFBP4 mRNA expression were remarkably upregulated in patients with OC. To be specific, the mRNA expression of IGFBP2 was upregulated in patients with serous ovarian cancer (SOC), while IGFBP1/3/4/5/6 mRNA levels were downregulated. In addition, the IGFBP4 protein expression was upregulated in SOC, and the IGFBP6 protein expression was upregulated in both of SOC and endometrioid ovarian cancer (EOC) tissues. High IGFBP1 mRNA levels showed favorable overall survival (OS) and progression-free survival (PFS) in all OC. Meanwhile, increased IGFBP5/6 mRNA levels revealed worsen OS and PFS in all OC patients. IGFBP4/6 mRNA levels predicted unfavorable OS and PFS only in SOC patients. Moreover, the aberrant mRNA expression of IGFBP1/2/4/5/6 was correlated with significantly prognosis in patients receiving different chemotherapeutic regimens.

Conclusion

This study indicates that the IGFBP family reveals distinct prognosis in patients with OC. IGFBP1/2/4/5/6 are useful prognostic predictors for chemotherapeutic effect in OC patients, and IGFBP2/4 are potential tumor markers for the diagnosis of OC.

Loss of tumor suppressor IGFBP4 drives epigenetic reprogramming in hepatic carcinogenesis

Genomic sequencing of hepatocellular carcinoma (HCC) uncovers a paucity of actionable mutations, underscoring the necessity to exploit epigenetic vulnerabilities for therapeutics. In HCC, EZH2-mediated H3K27me3 represents a major oncogenic chromatin modification, but how it modulates the therapeutic vulnerability of signaling pathways remains unknown. Here, we show EZH2 acts antagonistically to AKT signaling in maintaining H3K27 methylome through epigenetic silencing of IGFBP4. ChIP-seq revealed enrichment of Ezh2/H3K27me3 at silenced loci in HBx-transgenic mouse-derived HCCs, including Igfbp4 whose down-regulation significantly correlated with EZH2 overexpression and poor survivals of HCC patients. Functional characterizations demonstrated potent growth- and invasion-suppressive functions of IGFBP4, which was associated with transcriptomic alterations leading to deregulation of multiple signaling pathways. Mechanistically, IGFBP4 stimulated AKT/EZH2 phosphorylation to abrogate H3K27me3-mediated silencing, forming a reciprocal feedback loop that suppressed core transcription factor networks (FOXA1/HNF1A/HNF4A/KLF9/NR1H4) for normal liver homeostasis. Consequently, the in vivo tumorigenicity of IGFBP4-silenced HCC cells was vulnerable to pharmacological inhibition of EZH2, but not AKT. Our study unveils chromatin regulation of a novel liver tumor suppressor IGFBP4, which constitutes an AKT-EZH2 reciprocal loop in driving H3K27me3-mediated epigenetic reprogramming. Defining the aberrant chromatin landscape of HCC sheds light into the mechanistic basis of effective EZH2-targeted inhibition.

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.

IGFBP-4 and PAPP-A in normal physiology and disease

Insulin-like growth factor (IGF) binding protein-4 (IGFBP-4) is a modulator of the IGF system, exerting both inhibitory and stimulatory effects on IGF-induced cellular growth. IGFBP-4 is the principal substrate for the enzyme pregnancy-associated plasma protein-A (PAPP-A). Through IGF-dependent cleavage of IGFBP-4 in the vicinity of the IGF receptor, PAPP-A is able to increase IGF bioavailability and stimulate IGF-mediated growth. Recently, the stanniocalcins (STCs) were identified as novel inhibitors of PAPP-A proteolytic activity, hereby adding additional members to the seemingly endless list of proteins belonging to the IGF family. Our understanding of these proteins has advanced throughout recent years, and there is evidence to suggest that the role of IGFBP-4 and PAPP-A in defining the relationship between total IGF and IGF bioactivity can be linked to a number of pathological conditions. This review provides an overview of the experimental and clinical findings on the IGFBP-4/PAPP-A/STC axis as a regulator of IGF activity and examines the conundrum surrounding extrapolation of circulating concentrations to tissue action of these proteins. The primary focus will be on the biological significance of IGFBP-4 and PAPP-A in normal physiology and in pathophysiology with emphasis on metabolic disorders, cardiovascular diseases, and cancer. Finally, the review assesses current new trajectories of IGFBP-4 and PAPP-A research.

IGFBP-4 expression is adversely associated with lung cancer prognosis

Insulin-like growth factor binding protein-4 (IGFBP-4) was reported to be associated with prognosis in several types of cancer; however, to the best of our knowledge, whether it is correlated with lung cancer has yet to be reported. In the present study, 102 pairs of lung cancer tissues and surrounding non-cancerous tissues (SNCTs) were collected. The IGFBP-4 levels in tissues were detected with immunohistochemistry. The relevance of IGFBP-4 to the survival of patients was assessed. The IGFBP-4 gene was knocked down, and its function in the proliferation of lung cancer cells was measured. The percentage of lung cancer tissues with higher IGFBP-4 expression than SNCTs (51.9%) was increased compared with the percentage with similar (11.76%) or lower (36.27%) IGFBP-4 expression. Patients with higher IGFBP-1 expression exhibited a shorter median survival time. IGFBP-1 was associated with metastasis, lung cancer stages and malignancy, but not with age, sex or tumor size. Lung cancer cells with stably knocked down IGFBP-4 showed an inhibitory proliferation rate. The present study identified that IGFBP-4 was adversely associated with the prognosis of lung cancer patients. IGFBP-4 knockdown prohibited lung cancer cell growth. The present study provides a potential marker for lung cancer diagnosis and a possible target for lung cancer therapy.

IGF system targeted therapy: Therapeutic opportunities for ovarian cancer

The insulin-like growth factor (IGF) system comprises multiple growth factor receptors, including insulin-like growth factor 1 receptor (IGF-1R), insulin receptor (IR) -A and -B. These receptors are activated upon binding to their respective growth factor ligands, IGF-I, IGF-II and insulin, and play an important role in development, maintenance, progression, survival and chemotherapeutic response of ovarian cancer. In many pre-clinical studies anti-IGF-1R/IR targeted strategies proved effective in reducing growth of ovarian cancer models. In addition, anti-IGF-1R targeted strategies potentiated the efficacy of platinum based chemotherapy. Despite the vast amount of encouraging and promising pre-clinical data, anti-IGF-1R/IR targeted strategies lacked efficacy in the clinic. The question is whether targeting the IGF-1R/IR signaling pathway still holds therapeutic potential. In this review we address the complexity of the IGF-1R/IR signaling pathway, including receptor heterodimerization within and outside the IGF system and downstream signaling. Further, we discuss the implications of this complexity on current targeted strategies and indicate therapeutic opportunities for successful targeting of the IGF-1R/IR signaling pathway in ovarian cancer. Multiple-targeted approaches circumventing bidirectional receptor tyrosine kinase (RTK) compensation and prevention of system rewiring are expected to have more therapeutic potential.

Integration of Breast Cancer Secretomes with Clinical Data Elucidates Potential Serum Markers for Disease Detection, Diagnosis, and Prognosis

Cancer cells secrete factors that influence adjacent cell behavior and can lead to enhanced proliferation and metastasis. To better understand the role of these factors in oncogenesis and disease progression, estrogen and progesterone receptor positive MCF-7 cells, triple negative breast cancer MDA-MB-231, DT22, and DT28 cells, and MCF-10A non-transformed mammary epithelial cells were grown in 3D cultures. A special emphasis was placed on triple negative breast cancer since these tumors are highly aggressive and no targeted treatments are currently available. The breast cancer cells secreted factors of variable potency that stimulated proliferation of the relatively quiescent MCF-10A cells. The conditioned medium from each cell line was subjected to mass spectrometry analysis and a variety of secreted proteins were identified including glycolytic enzymes, proteases, protease inhibitors, extracellular matrix proteins, and insulin-like growth factor binding proteins. An investigation of the secretome from each cell line yielded clues about strategies used for breast cancer proliferation and metastasis. Some of the proteins we identified may be useful in the development of a serum-based test for breast cancer detection, diagnosis, prognosis, and monitoring.

Understanding the Key to Targeting the IGF Axis in Cancer: A Biomarker Assessment

Type 1 insulin like growth factor receptor (IGF-1R) targeted therapies showed compelling pre-clinical evidence; however, to date, this has failed to translate into patient benefit in Phase 2/3 trials in unselected patients. This was further complicated by the toxicity, including hyperglycemia, which largely results from the overlap between IGF and insulin signaling systems and associated feedback mechanisms. This has halted the clinical development of inhibitors targeting IGF signaling, which has limited the availability of biopsy samples for correlative studies to understand biomarkers of response. Indeed, a major factor contributing to lack of clinical benefit of IGF targeting agents has been difficulty in identifying patients with tumors driven by IGF signaling due to the lack of predictive biomarkers. In this review, we will describe the IGF system, rationale for targeting IGF signaling, the potential liabilities of targeting strategies, and potential biomarkers that may improve success.

Insulin-like growth factor system in cancer: novel targeted therapies

Insulin-like growth factors (IGFs) are essential for growth and survival that suppress apoptosis and promote cell cycle progression, angiogenesis, and metastatic activities in various cancers. The IGFs actions are mediated through the IGF-1 receptor that is involved in cell transformation induced by tumour. These effects depend on the bioavailability of IGFs, which is regulated by IGF binding proteins (IGFBPs). We describe here the role of the IGF system in cancer, proposing new strategies targeting this system. We have attempted to expand the general viewpoint on IGF-1R, its inhibitors, potential limitations of IGF-1R, antibodies and tyrosine kinase inhibitors, and IGFBP actions. This review discusses the emerging view that blocking IGF via IGFBP is a better option than blocking IGF receptors. This can lead to the development of novel cancer therapies.

Interferon regulatory factor 1 is an independent predictor of platinum resistance and survival in high-grade serous ovarian carcinoma

OBJECTIVE

High-grade serous ovarian cancer (HGSOC) that is resistant to platinum-based chemotherapy has a particularly poor prognosis. Response to platinum has both prognostic survival value and dictates secondary treatment strategies. Using transcriptome analysis, we sought to identify differentially expressed genes/pathways based on a tumor's platinum response for discovering novel predictive biomarkers.

METHODS

Seven primary HGSOC tumor samples, representing two extremes of platinum sensitivity/timing of disease recurrence, were analyzed by RNA-Seq, Ingenuity Pathways Analysis (IPA) and Upstream Regulator Analysis (URA), and used to explore differentially expressed genes and prevalent molecular and cellular processes. Progression-free and overall survival (PFS, OS) was estimated using the Kaplan-Meier method in two different sample sets including GEO and TCGA data sets.

RESULTS

IPA and URA highlighted an IRF1-driven transcriptional program (P=0.0017; z-score of 3.091) in the platinum sensitive improved PFS group. QRT-PCR analysis of 31 HGSOC samples demonstrated a significant difference in PFS between low and high IRF1 expression groups (P=0.048) and between groups that were platinum sensitive versus not (P=0.016). In a larger validation data set, increased levels of IRF1 were associated with both increased PFS (P=0.043) and OS (P=0.019) and the effect on OS was independent of debulking status (optimal debulking, P=0.025; suboptimal, P=0.041).

CONCLUSION

Transcriptome analysis identifies IRF1, a transcription factor that functions both in immune regulation and as a tumor suppressor, as being associated with platinum sensitivity and an independent predictor of both PFS and OS in HGSOC.

IGF binding proteins in cancer: mechanistic and clinical insights

The six members of the family of insulin-like growth factor (IGF) binding proteins (IGFBPs) were originally characterized as passive reservoirs of circulating IGFs, but they are now understood to have many actions beyond their endocrine role in IGF transport. IGFBPs also function in the pericellular and intracellular compartments to regulate cell growth and survival - they interact with many proteins, in addition to their canonical ligands IGF-I and IGF-II. Intranuclear roles of IGFBPs in transcriptional regulation, induction of apoptosis and DNA damage repair point to their intimate involvement in tumour development, progression and resistance to treatment. Tissue or circulating IGFBPs might also be useful as prognostic biomarkers.