Establishment and characterization of a platinum- and paclitaxel-resistant high grade serous ovarian carcinoma cell line

On the need for standardized reporting of photophysical parameters of in vitro photodynamic therapy studies

In vitro dose escalation experiments are one of the first gatekeepers in therapeutic evaluation and development. This also holds for evaluating novel photosensitizers (PS) and Photodynamic Therapy (PDT) co-therapies as needed to provide dose response guidelines before engaging in further pre-clinical studies. The dose needed to achieve 50% cell kill (LD₅₀) is a standard metric to report the potency of a therapeutic agents that is widely accepted for single-drug therapies. In reporting results of PDT experiments, which involve delivery of both drug and light, it is inherently more complicated to identify such a convenient dose response metric that actually captures the larger space of treatment parameters. In addition to ubiquitous sources of biological variability that apply broadly in biomedical research, PDT treatment efficacy is determined by multiple key parameters that may or may not have been documented, including PS concentration and light fluence, where the latter is itself a function of the spectral properties of the light source used (often not described), not to mention dose rate, fractionation and other parameters that potentially vary between individual studies. It is impossible to compare results between two study when, for example one reports LD₅₀ PS concentration without providing essential light dosimetry details. Motivated by this challenge in comparing outcomes and establishing reproducibility of in vitro PDT studies, we endeavored to perform a meta-analysis of the reporting of PDT results by converting, where possible, the disparately reported experimental details into a consistent metric that could be used to compare across studies. In this context we adopt here the number of photons absorbed by photosensitizers per unit volume to affect a 50% decline in cell survival as a standardized metric. By choosing this metric one can acknowledge the quantum-based generation of cytotoxins. While this metric does not cover every possible source of variability between any two studies, for a PS with known optical properties, this does encapsulate PS concentration as well as irradiance and spectral properties of light delivered. For the sake of focus we adopt this approach for study of reported results with two photosensitizers, Protoporphyrin IX, either synthesized in the cells by aminolevulinic acid or administered exogenously, and Chlorin e6. A literature search was performed to identify in vitro studies with these two photosensitizers and collect necessary information to calculate the absorbed photon LD₅₀ threshold for each study. Only approximately 1/10 of the manuscripts reporting on in vitro studies provide the minimum required information to calculate the threshold values. While the majority of the determined threshold values are within a factor of 10, the range of threshold values spanned close to 7 orders of magnitude for both photosensitizers. To contrast with single-agent therapies, a similar exercise was performed for chemotherapeutic drugs targeting cellular mitosis or tyrosine kinase inhibitors resulted in an LD₅₀ or IC₅₀ range of 1-2 orders of magnitude, with LD₅₀ or IC₅₀ values for a single cell line being within a factor of 5. This review underscores challenges in the reporting of in vitro PDT efficacy. In many cases it takes considerable effort to extract the necessary methodology information to make meaningful comparison between PDT studies. Only when results between studies can be compared is it possible to begin to assess reproducibility which, as shown here, can be a major issue. Hence, guidelines need to be developed and enforced through the peer review process for meaningful reporting of preclinical PDT results in order for the most promising sensitizers and co-therapies to be identified and translated into the clinic.

Harnessing preclinical models for the interrogation of ovarian cancer

Ovarian cancer (OC) is a heterogeneous malignancy with various etiology, histopathology, and biological feature. Despite accumulating understanding of OC in the post-genomic era, the preclinical knowledge still undergoes limited translation from bench to beside, and the prognosis of ovarian cancer has remained dismal over the past 30 years. Henceforth, reliable preclinical model systems are warranted to bridge the gap between laboratory experiments and clinical practice. In this review, we discuss the status quo of ovarian cancer preclinical models which includes conventional cell line models, patient-derived xenografts (PDXs), patient-derived organoids (PDOs), patient-derived explants (PDEs), and genetically engineered mouse models (GEMMs). Each model has its own strengths and drawbacks. We focus on the potentials and challenges of using these valuable tools, either alone or in combination, to interrogate critical issues with OC.

Ferroptosis-Related Long Noncoding RNAs as Prognostic Biomarkers for Ovarian Cancer

Ovarian cancer (OC) is a highly malignant gynecologic tumor with few treatments available and poor prognosis with the currently available diagnostic markers and interventions. More effective methods for diagnosis and treatment are urgently needed. Although the current evidence implicates ferroptosis in the development and therapeutic responses of various types of tumors, it is unclear to what extent ferroptosis affects OC. To explore the potential of ferroptosis-related genes as biomarkers and molecular targets for OC diagnosis and intervention, this study collected several datasets from The Cancer Genome Atlas-OC (TCGA-OC), analyzed and identified the coexpression profiles of 60 ferroptosis-related genes and two subtypes of OC with respect to ferroptosis and further examined and analyzed the differentially expressed genes between the two subtypes. The results indicated that the expression levels of ferroptosis genes were significantly correlated with prognosis in patients with OC. Single-factor Cox and LASSO analysis identified eight lncRNAs from the screened ferroptosis-related genes, including lncRNAs RP11-443B7.3, RP5-1028K7.2, TRAM2-AS1, AC073283.4, RP11-486G15.2, RP11-95H3.1, RP11-958F21.1, and AC006129.1. A risk scoring model was constructed from the ferroptosis-related lncRNAs and showed good performance in the evaluation of OC patient prognosis. The high- and low-risk groups based on tumor scores presented obvious differences in clinical characteristics, tumor mutation burden, and tumor immune cell infiltration, indicating that the risk score has a good ability to predict the benefit of immunotherapy and may provide data to support the implementation of precise immunotherapy for OC. Although in vivo tests and research are needed in the future, our bioinformatics analysis powerfully supported the effectiveness of the risk signature of ferroptosis-related lncRNAs for prognosis prediction in OC. The findings suggest that these eight identified lncRNAs have great potential for development as diagnostic markers and intervention targets for OC and that patients with high ferroptosis-related lncRNA expression will receive greater benefits from conventional chemotherapy or treatment with ferroptosis inducers.

Generation of Two Paclitaxel-Resistant High-Grade Serous Carcinoma Cell Lines With Increased Expression of P-Glycoprotein

Debulking surgery followed by chemotherapy are the standard of care for high-grade serous carcinoma. After an initial good response to treatment, the majority of patients relapse with a chemoresistant profile, leading to a poor overall survival. Chemotherapy regimens used in high-grade serous carcinomas are based in a combination of classical chemotherapeutic drugs, namely, Carboplatin and Paclitaxel. The mechanisms underlying drug resistance and new drug discovery are crucial to improve patients’ survival. To uncover the molecular mechanisms of chemoresistance and test drugs capable of overcoming this resistant profile, it is fundamental to use good cellular models capable of mimicking the chemoresistant disease. Herein, we established two high-grade serous carcinoma cell lines with intrinsic resistance to Carboplatin and induced Paclitaxel resistance (OVCAR8 PTX R C and OVCAR8 PTX R P) derived from the OVCAR8 cell line. These two chemoresistant cell line variants acquired an enhanced resistance to Paclitaxel-induced cell death by increasing the drug efflux capacity, and this resistance was stable in long-term culture and following freeze/thaw cycles. The mechanism underlying Paclitaxel resistance resides in a significant increase in P-glycoprotein expression and, when this drug efflux pump was blocked with Verapamil, cells re-acquired Paclitaxel sensitivity. We generated two high-grade serous carcinoma cell lines, with a double-chemoresistant (Carboplatin and Paclitaxel) phenotype that mimics the majority of tumor recurrences in ovarian cancer context. This robust tool is suitable for preliminary drug testing towards the development of therapeutic strategies to overcome chemoresistance.

Nuclear Enolase-1/ MBP-1 expression and its association with the Wnt signaling in epithelial ovarian cancer

BACKGROUND

Enolase-1, primarily known for its role in glucose metabolism, is overexpressed in various cancer entities. In contrast its alternative spliced nuclear isoform MBP-1 acts as a tumor suppressor. The aim of this study is to analyze the prognostic impact of Enolase-1/ MBP-1 and its functional significance in epithelial ovarian cancer (EOC).

METHODS

By immunohistochemistry, Enolase-1 staining was examined in 156 EOC samples. Evaluation of Enolase-1 staining was conducted in the nucleus and the cytoplasm using the semi-quantitative immunoreactive score. Expression levels were correlated with clinical and pathological parameters as well as with overall survival to assess for prognostic impact.

RESULTS

Cytoplasmic and nuclear Enolase-1 expression did not show a significant difference between the histological subtypes (p = 0.1). High nuclear Enolase-1/ MBP-1 staining negativly correlated with the tumor grading (p<0.001; Cc= -0.318). Cytoplasmic Enolase-1 did not correlate with clinicopathological data. Higher nuclear Enolase-1/ MBP-1 staining was detected in low-grade serous cancer cases compared to high-grade ones (median IRS 3 (range 0-8) vs. median IRS 2 (range 0-4), p<0.001). Nuclear Enolase-1/ MBP-1 expression correlated with the Wnt signaling markers membranous beta-catenin (p = 0.007; Cc=0.235), serine residue 9-phosphorylated glycogen synthase kinase 3 beta (p<0.001; Cc=0.341) and snail/slug (p = 0.004; Cc= -0.257). High nuclear Enolase-1/ MBP-1 expression was associated with improved overall survival (88.6 vs. 33.1 months, median; p = 0.013).

CONCLUSION

Additional knowledge of Enolase-1/ MBP-1 as a biomarker and its interactions within the Wnt signaling pathway and epithelial-mesenchymal transition potentially improve the prognosis of therapeutic approaches in EOC.

Proteomic Technology "Lens" for Epithelial-Mesenchymal Transition Process Identification in Oncology

The epithelial-mesenchymal transition (EMT) is a complex transformation process that induces local and distant progression of many malignant tumours. Due to its complex array of proteins that are dynamically over-/underexpressed during this process, proteomic technologies gained their place in the EMT research in the last years. Proteomics has identified new molecular pathways of this process and brought important insights to develop new therapy targets. Various proteomic tools and multiple combinations were developed in this area. Out of the proteomic technology armentarium, mass spectrometry and array technologies are the most used approaches. The main characteristics of the proteomic technology used in this domain are high throughput and detection of minute concentration in small samples. We present herein, using various proteomic technologies, the identification in cancer cell lines and in tumour tissue EMT-related proteins, proteins that are involved in the activation of different cellular pathways. Proteomics has brought besides standard EMT markers (e.g., cell-cell adhesion proteins and transcription factors) other future potential markers for improving diagnosis, monitoring evolution, and developing new therapy targets. Future will increase the proteomic role in clinical investigation and validation of EMT-related biomarkers.

The irreversible ERBB1/2/4 inhibitor neratinib interacts with the PARP1 inhibitor niraparib to kill ovarian cancer cells

The irreversible ERBB1/2/4 inhibitor neratinib has been shown to rapidly down-regulate the expression of ERBB1/2/4 as well as the levels of c-MET, PDGFRα and mutant RAS proteins via autophagic degradation. Neratinib interacted in an additive to synergistic fashion with the approved PARP1 inhibitor niraparib to kill ovarian cancer cells. Neratinib and niraparib caused the ATM-dependent activation of AMPK which in turn was required to cause mTOR inactivation, ULK-1 activation and ATG13 phosphorylation. The drug combination initially increased autophagosome levels followed later by autolysosome levels. Preventing autophagosome formation by expressing activated mTOR or knocking down of Beclin1, or knock down of the autolysosome protein cathepsin B, reduced drug combination lethality. The drug combination caused an endoplasmic reticulum stress response as judged by enhanced eIF2α phosphorylation that was responsible for reducing MCL-1 and BCL-XL levels and increasing ATG5 and Beclin1 expression. Knock down of BIM, but not of BAX or BAK, reduced cell killing. Expression of activated MEK1 prevented the drug combination increasing BIM expression and reduced cell killing. Downstream of the mitochondrion, drug lethality was partially reduced by knock down of AIF, but expression of dominant negative caspase 9 was not protective. Our data demonstrate that neratinib and niraparib interact to kill ovarian cancer cells through convergent DNA damage and endoplasmic reticulum stress signaling. Cell killing required the induction of autophagy and was cathepsin B and AIF -dependent, and effector caspase independent.