Ancient and modern: hints of a core post-transcriptional network driving chemotherapy resistance in ovarian cancer

Bioactive compounds from Morchella esculenta as potential inhibitors of RNA-binding protein La in ovarian cancer: a molecular modeling and quantum mechanics approach

La protein is significantly expressed in various malignant tumors, including ovarian cancer (OC), which is related to the poor response to platinum-based chemotherapy. Thus, inhibiting La protein could control the expression of the potential downstream genes involved in promoting proliferation and chemotherapy resistance to OC, which could serve as a therapeutic intervention. Through a molecular docking approach, 12 compounds from Morchella esculenta were screened against the crystal structure of La protein and four hit compounds were identified, including beta-carotene, p-hydroxybenzoic acid, gamma-tocopherol, and alpha-tocopherol, with a binding affinity of - 10.7, - 8.1, - 7.9, and - 7.6 kcal/mol, respectively, higher than pyridine-2-carboxylate (control), with a binding affinity of - 5.2 kcal/mol. To explore the interaction of the hit compounds with the target receptor, they were selected for a molecular dynamic simulation and post-simulation analysis for 100 ns. The result showed promising reliability of the ligands due to a stable interaction with the La protein crystal structure. Furthermore, the drug-likeness and physicochemical chemical properties of the compounds were investigated using ADMET study and density functional theory analysis, respectively, and the result shows that the hit compounds could serve as a promising starting for the development of novel LA protein inhibitors for OC therapeutics. Finally, this study compared HOMO and LUMO values from global hybrids with long-range corrected DFAs, and the result from the two followed the same qualitative pattern while calculating HOMO values; however, MO62X/cc-pVTZ could better predict LUMO values when considering a global hybrid.

Immunogenic cell death-related gene landscape predicts the overall survival and immune infiltration status of ovarian cancer

Background: Ovarian cancer (OC) is the most troubling malignant tumor of the female reproductive system. It has a low early diagnosis rate and a high tumor recurrence rate after treatment. Immunogenic cell death (ICD) is a unique form of regulated cell death that can activate the adaptive immune system through the release of DAMPs and cytokines in immunocompromised hosts and establish long-term immunologic memory. Therefore, this study aims to explore the prognostic value and underlying mechanisms of ICD-related genes in OC on the basis of characteristics. Methods: The gene expression profiles and related clinical information of OC were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. ICD-related genes were collected from the Genecards database. ICD-related prognostic genes were obtained by intersecting ICD-related genes with the OC prognostic-related genes that were analyzed in the TCGA database. Functional enrichment, genetic mutation, and immune infiltration correlation analyses were further performed to identify underlying mechanisms. Subsequently, we developed a TCGA cohort-based prognostic risk model that included a nine-gene signature through univariate and multivariate Cox regression and LASSO regression analyses. Meanwhile, external validation was performed on two sets of GEO cohorts and the TCGA training cohort for three other common tumors in women. In addition, a nomogram was established by integrating clinicopathological features and ICD-related gene signature to predict survival probability. Finally, functional enrichment and immune infiltration analyses were performed on the two risk subgroups. Results: By utilizing nine genes (ERBB2, RB1, CCR7, CD38, IFNB1, ANXA2, CXCL9, SLC9A1, and SLAMF7), we constructed an ICD-related prognostic signature. Subsequently, patients were subdivided into high- and low-risk subgroups in accordance with the median value of the risk score. In multivariate Cox regression analyses, risk score was an independent prognostic factor (hazard ratio = 2.783; p < 0.01). In the TCGA training cohort and the two GEO validation cohorts, patients with high-risk scores had worse prognosis than those with low-risk scores (p < 0.05). The time-dependent receiver operating characteristic curve further validated the prognostic power of the gene signature. Finally, gene set enrichment analysis indicated that multiple oncological pathways were significantly enriched in the high-risk subgroup. By contrast, the low-risk subgroup was strongly related to the immune-related signaling pathways. Immune infiltration analysis further illustrated that most immune cells showed higher levels of infiltration in the low-risk subgroup than in the high-risk subgroup. Conclusion: We constructed a novel ICD-related gene model for forecasting the prognosis and immune infiltration status of patients with OC. In the future, new ICD-related genes may provide novel potential targets for the therapeutic intervention of OC.

RNA-binding proteins in ovarian cancer: a novel avenue of their roles in diagnosis and treatment

Ovarian cancer (OC), an important cause of cancer-related death in women worldwide, is one of the most malignant cancers and is characterized by a poor prognosis. RNA-binding proteins (RBPs), a class of endogenous proteins that can bind to mRNAs and modify (or even determine) the amount of protein they can generate, have attracted great attention in the context of various diseases, especially cancers. Compelling studies have suggested that RBPs are aberrantly expressed in different cancer tissues and cell types, including OC tissues and cells. More specifically, RBPs can regulate proliferation, apoptosis, invasion, metastasis, tumorigenesis and chemosensitivity and serve as potential therapeutic targets in OC. Herein, we summarize what is currently known about the biogenesis, molecular functions and potential roles of human RBPs in OC and their prospects for application in the clinical treatment of OC.

KHDRBS3 promotes paclitaxel resistance and induces glycolysis through modulated MIR17HG/CLDN6 signaling in epithelial ovarian cancer

Paclitaxel (PTX) resistance contributes to mortality in epithelial ovarian cancer (EOC). Aerobic glycolysis is elevated in the tumor environment and may influence resistance to PTX in EOC. KH domain-containing, RNA-binding signal transduction-associated protein 3 (KHDRBS3) is an RNA binding protein that is up-regulated in EOC, but its underlying mechanism in EOC is unclear. Here, we investigate the role of KHDRBS3 in glycolysis and increased resistance to PTX. Expression of KHDRBS3 and Claudin (CLDN6) were measured in EOC tissue and cells by quantitative real-time PCR, western blotting and immunohistochemistry. The biological functions of KHDRBS3, MIR17HG and CLDN6 were examined using MTT, colony formation, apoptosis and seahorse assays in vitro. For in vivo experiments, a xenograft model was used to investigate the effects of KHDRBS3 and MIR17HG in EOC. Here, we investigate the role of KHDRBS3 in glycolysis and increased resistance to PTX. The expression of KHDRBS3 was up-regulated in PTX-resistant cells. KHDRBS3 knockdown restrained the IC₅₀ of PTX, cell proliferation, colony formation and glycolysis in SKOV3-R and A2780-R cells in vitro and enhanced PTX sensitivity in a xenograft mouse model in vivo. KHDRBS3 interacts with lncRNA MIR17HG, which is down-regulated in EOC tissue and cells. The effect of KHDRBS3 overexpression on PTX resistance and glycolysis was rescued by MIR17HG overexpression. Additionally, MIR17HG interacts with the 3'UTR of CLDN6 and negatively regulates CLDN6 expression. MIR17HG overexpression suppressed the IC₅₀ of PTX and glycolysis by targeting CLDN6. Our results reveal a KHDRBS3-MIR17HG-CLDN6 regulatory axis that contributes to enhanced glycolysis in EOC and represents a potential target for therapy.

RNA-binding proteins modulate drug sensitivity of cancer cells

As our understanding of the complex network of regulatory pathways for gene expression continues to grow, avenues of investigation for how these new findings can be utilised in therapeutics are emerging. The recent growth of interest in the RNA binding protein (RBP) interactome has revealed it to be rich in targets linked to, and causative of diseases. While this is, in and of itself, very interesting, evidence is also beginning to arise for how the RBP interactome can act to modulate the response of diseases to existing therapeutic treatments, especially in cancers. Here we highlight this topic, providing examples of work that exemplifies such modulation of chemotherapeutic sensitivity.

A New RBPs-Related Signature Predicts the Prognosis of Colon Adenocarcinoma Patients

The dysregulation of RNA binding proteins (RBPs) is closely related to tumorigenesis and development. However, the role of RBPs in Colon adenocarcinoma (COAD) is still poorly understood. We downloaded COAD’s RNASeq data from the Cancer Genome Atlas (TCGA) database, screened the differently expressed RBPs in normal tissues and tumor, and constructed a protein interaction network. COAD patients were randomly divided into a training set (N = 315) and a testing set (N = 132). In the training set, univariate Cox analysis identified 12 RBPs significantly related to the prognosis of COAD. By multivariate COX analysis, we constructed a prognostic model composed of five RBPs (CELF4, LRRFIP2, NOP14, PPARGC1A, ZNF385A) based on the lowest Akaike information criterion. Each COAD patient was scored according to the model formula. Further analysis showed that compared with the low-risk group, the overall survival rate (OS) of patients in the high-risk group was significantly lower. The area under the curve of the time-dependent receiver operator characteristic (ROC) curve was 0.722 in the training group and 0.738 in the test group, which confirmed a good prediction feature. In addition, a nomogram was constructed based on clinicopathological characteristics and risk scores. C-index and calibration curve proved the accuracy in predicting the 1-, 3-, and 5-year survival rates of COAD patients. In short, we constructed a superior prognostic and diagnostic signature composed of five RBPs, which indicates new possibilities for individualized treatment of COAD patients.

The RNA-Binding Protein CELF2 Inhibits Ovarian Cancer Progression by Stabilizing FAM198B

An increasing number of studies have clarified the functional roles of RNA-binding proteins (RBPs) in driving post-transcriptional mechanisms of cancer progression. In this study, we integrated data from the RBP database and Gene Expression Omnibus (GEO) data with RNA sequencing (RNA-seq) data from 10 ovarian cancer tissues and 8 normal ovarian tissues and identified an RBP, CUGBP- and ETR-3-like family 2 (CELF2). We found that CELF2 expression was downregulated in ovarian cancer and positively correlated with the overall survival (OS) and progression-free survival (PFS) of patients with ovarian cancer. Altered CELF2 expression led to changes in the proliferation, migration, and invasion of ovarian cancer cells in vitro and in vivo. CELF2 expression increased the stability of its target, FAM198B, by binding to AU/U-rich elements (AREs) in the 3' untranslated region (3' UTR). FAM198B knockdown restored the CELF2-mediated suppression of proliferation and migration. We also found that CELF2/FAM198B may repress ovarian cancer progression by inhibiting the mitogen-activated protein kinase/extracellular-regulated protein kinase (MAPK/ERK) signaling pathway. Finally, a curcumin-induced increase in CELF2 expression resulted in increased ovarian cancer cell sensitivity to cisplatin. Our study elucidated a novel mechanism by which the CELF2/FAM198B axis regulates proliferation and metastasis in ovarian cancer, providing novel, potential therapeutic targets for ovarian cancer.

Tumor-intrinsic and -extrinsic (immune) gene signatures robustly predict overall survival and treatment response in high grade serous ovarian cancer patients

In the present study, we developed a transcriptomic signature capable of predicting prognosis and response to primary therapy in high grade serous ovarian cancer (HGSOC). Proportional hazard analysis was performed on individual genes in the TCGA RNAseq data set containing 229 HGSOC patients. Ridge regression analysis was performed to select genes and develop multigenic models. Survival analysis identified 120 genes whose expression levels were associated with overall survival (OS) (HR = 1.49-2.46 or HR = 0.48-0.63). Ridge regression modeling selected 38 of the 120 genes for development of the final Ridge regression models. The consensus model based on plurality voting by 68 individual Ridge regression models classified 102 (45%) as low, 23 (10%) as moderate and 104 patients (45%) as high risk. The median OS was 31 months (HR = 7.63, 95% CI = 4.85-12.0, P < 1.0-10) and 77 months (HR = ref) in the high and low risk groups, respectively. The gene signature had two components: intrinsic (proliferation, metastasis, autophagy) and extrinsic (immune evasion). Moderate/high risk patients had more partial and non-responses to primary therapy than low risk patients (odds ratio = 4.54, P < 0.001). We concluded that the overall survival and response to primary therapy in ovarian cancer is best assessed using a combination of gene signatures. A combination of genes which combines both tumor intrinsic and extrinsic functions has the best prediction. Validation studies are warranted in the future.

The Interplay between Long Noncoding RNAs and Proteins of the Epigenetic Machinery in Ovarian Cancer

Comprehensive large-scale sequencing and bioinformatics analyses have uncovered a myriad of cancer-associated long noncoding RNAs (lncRNAs). Aberrant expression of lncRNAs is associated with epigenetic reprogramming during tumor development and progression, mainly due to their ability to interact with DNA, RNA, or proteins to regulate gene expression. LncRNAs participate in the control of gene expression patterns during development and cell differentiation and can be cell and cancer type specific. In this review, we described the potential of lncRNAs for clinical applications in ovarian cancer (OC). OC is a complex and heterogeneous disease characterized by relapse, chemoresistance, and high mortality rates. Despite advances in diagnosis and treatment, no significant improvements in long-term survival were observed in OC patients. A set of lncRNAs was associated with survival and response to therapy in this malignancy. We manually curated databases and used bioinformatics tools to identify lncRNAs implicated in the epigenetic regulation, along with examples of direct interactions between the lncRNAs and proteins of the epigenetic machinery in OC. The resources and mechanisms presented herein can improve the understanding of OC biology and provide the basis for further investigations regarding the selection of novel biomarkers and therapeutic targets.

Tandem RNA isolation reveals functional rearrangement of RNA-binding proteins on CDKN1B/p27Kip1 3'UTRs in cisplatin treated cells

Post-transcriptional control of gene expression is mediated via RNA-binding proteins (RBPs) that interact with mRNAs in a combinatorial fashion. While recent global RNA interactome capture experiments expanded the repertoire of cellular RBPs quiet dramatically, little is known about the assembly of RBPs on particular mRNAs; and how these associations change and control the fate of the mRNA in drug-treatment conditions. Here we introduce a novel biochemical approach, termed tobramycin-based tandem RNA isolation procedure (tobTRIP), to quantify proteins associated with the 3ʹUTRs of cyclin-dependent kinase inhibitor 1B (CDKN1B/p27^Kip1) mRNAs in vivo. P27^Kip1 plays an important role in mediating a cell’s response to cisplatin (CP), a widely used chemotherapeutic cancer drug that induces DNA damage and cell cycle arrest. We found that p27^Kip1 mRNA is stabilized upon CP treatment of HEK293 cells through elements in its 3ʹUTR. Applying tobTRIP, we further compared the associated proteins in CP and non-treated cells, and identified more than 50 interacting RBPs, many functionally related and evoking a coordinated response. Knock-downs of several of the identified RBPs in HEK293 cells confirmed their involvement in CP-induced p27 mRNA regulation; while knock-down of the KH-type splicing regulatory protein (KHSRP) further enhanced the sensitivity of MCF7 adenocarcinoma cancer cells to CP treatment. Our results highlight the benefit of specific in vivo mRNA-protein interactome capture to reveal post-transcriptional regulatory networks implicated in cellular drug response and adaptation.

Drug Delivery in Cancer Therapy, Quo Vadis?

The treatment of malignancies has undergone dramatic changes in the past few decades. Advances in drug delivery techniques and nanotechnology have allowed for new formulations of old drugs, so as to improve the pharmacokinetics, to enhance accumulation in solid tumors, and to reduce the significant toxic effects of these important therapeutic agents. Here, we review the published clinical data in cancer therapy of several major drug delivery systems, including targeted radionuclide therapy, antibody-drug conjugates, liposomes, polymer-drug conjugates, polymer implants, micelles, and nanoparticles. The clinical outcomes of these delivery systems from various phases of clinical trials are summarized. The success and limitations of the drug delivery strategies are discussed based on the clinical observations. In addition, the challenges in applying drug delivery for efficacious cancer therapy, including physical barriers, tumor heterogeneity, drug resistance, and metastasis, are discussed along with future perspectives of drug delivery in cancer therapy. In doing so, we intend to underscore that efficient delivery of cancer therapeutics to solid malignancies remains a major challenge in cancer therapy, and requires a multidisciplinary approach that integrates knowledge from the diverse fields of chemistry, biology, engineering, and medicine. The overall objective of this review is to improve our understanding of the clinical fate of commonly investigated drug delivery strategies, and to identify the limitations that must be addressed in future drug delivery strategies, toward the pursuit of curative therapies for cancer.