Using heterogeneity of the patient-derived xenograft model to identify the chemoresistant population in ovarian cancer

Creation and Validation of Patient-Derived Cancer Model Using Peritoneal and Pleural Effusion in Patients with Advanced Ovarian Cancer: An Early Experience

Background: The application of personalized cancer treatment based on genetic information and surgical samples has begun in the field of cancer medicine. However, a biopsy may be painful for patients with advanced diseases that do not qualify for surgical resection. Patient-derived xenografts (PDXs) are cancer models in which patient samples are transplanted into immunodeficient mice. PDXs are expected to be useful for personalized medicine. The aim of this study was to establish a PDX from body fluid (PDX-BF), such as peritoneal and pleural effusion samples, to provide personalized medicine without surgery. Methods: PDXs-BF were created from patients with ovarian cancer who had positive cytology findings based on peritoneal and pleural effusion samples. PDXs were also prepared from each primary tumor. The pathological findings based on immunohistochemistry were compared between the primary tumor, PDX, and PDX-BF. Further, genomic profiles and gene expression were evaluated using DNA and RNA sequencing to compare primary tumors, PDXs, and PDX-BF. Results: Among the 15 patients, PDX-BF was established for 8 patients (5 high-grade serous carcinoma, 1 carcinosarcoma, 1 low-grade serous carcinoma, and 1 clear cell carcinoma); the success rate was 53%. Histologically, PDXs-BF have features similar to those of primary tumors and PDXs. In particular, PDXs-BF had similar gene mutations and expression patterns to primary tumors and PDXs. Conclusions: PDX-BF reproduced primary tumors in terms of pathological features and genomic profiles, including gene mutation and expression. Thus, PDX-BF may be a potential alternative to surgical resection for patients with advanced disease.

Patient-Derived Xenograft Models in Cancer Research: Methodology, Applications, and Future Prospects

Patient-derived xenografts (PDXs) have emerged as a pivotal tool in translational cancer research, addressing limitations of traditional methods and facilitating improved therapeutic interventions. These models involve engrafting human primary malignant cells or tissues into immunodeficient mice, allowing for the investigation of cancer mechanobiology, validation of therapeutic targets, and preclinical assessment of treatment strategies. This chapter provides an overview of PDXs methodology and their applications in both basic cancer research and preclinical studies. Despite current limitations, ongoing advancements in humanized xenochimeric models and autologous immune cell engraftment hold promise for enhancing PDX model accuracy and relevance. As PDX models continue to refine and extend their applications, they are poised to play a pivotal role in shaping the future of translational cancer research.

Establishment and characterization of a non-gestational choriocarcinoma patient-derived xenograft model

BACKGROUND

Non-gestational choriocarcinoma (NGC) is a rare subtype of malignant germ cell tumour and there is no consensus on its treatment. The lack of suitable preclinical models for NGC is a challenge in drug discovery research. Patient-derived xenograft (PDX) models recapitulate the tumour microenvironment of the original cancer tissue. Therefore, they have received considerable attention for studies on rare cancer. Here, we aimed to establish a PDX model from a patient with recurrent NGC.

METHODS

Fresh NGC tumour tissue was immediately transplanted into a severely immune-deficient mouse (NOD.Cg-Prkdcscid1l2rgtm1Wjl/SzJ) and maintained for more than three in vivo passages. Subsequently, we evaluated the molecular characteristics of the PDX model using immunohistochemistry, polymerase chain reaction, and RNA sequencing. Moreover, the PDX tumours were transplanted into BALB/c nude mice, and we evaluated their sensitivity for cisplatin and methotrexate.

RESULTS

The PDX tumour maintained the morphological features of NGC. Moreover, Immunohistochemistry revealed that the human chorionic gonadotropin, cytokeratin 7, and EpCAM expression levels were similar to those in the primary tumour. Furthermore, serum human chorionic gonadotropin levels were elevated in both the primary tumour and the PDX models. Additionally, using PCR analysis with species-specific primers, we confirmed that the PDX tumour contained human genes and was derived from human tissue. Moreover, the gene expression profile of the NGC was compared with that of epithelial ovarian cancer samples and cell lines, and 568 dysregulated genes in the NGC were extracted. The expression of the dysregulated genes in PDX was significantly correlated with that in the primary tumour (R2 = 0.873, P < 0.001). Finally, we demonstrated that the PDX tumour was sensitive to cisplatin and methotrexate; therefore, its clinical response to the agents was similar to that of the primary tumour.

CONCLUSIONS

We successfully established a PDX model of NGC, to the best of our knowledge, for the first time. The established PDX retained the molecular and transcriptome characteristics of the primary tumour and can be used to predict drug effects. It may facilitate further research and the development of novel therapeutic agents for NGC.

Antitumor effect of toosendanin on oral squamous cell carcinoma via suppression of p-STAT3

BACKGROUND

Toosendanin (TSN) exhibits potent antitumor activity against various tumor cell lines. However, its efficacy against oral squamous cell carcinoma (OSCC) remains unknown. Here, we investigated the effects of TSN on OSCC cells in vitro and verified them in vivo using a patient-derived xenograft (PDX) model.

METHODS

The effect of TSN on OSCC cells was investigated by cytotoxicity assays and flow cytometry. The expression of proteins was detected by western blotting. An OSCC PDX model was constructed to further investigate the role of TSN in regulating the function of OSCC.

RESULTS

The cell viability of CAL27 and HN6 cells decreased as the concentration of TSN increased within the experimental range. Compared with controls, TSN at lower doses inhibited cell proliferation and induced apoptosis through S-phase cell cycle arrest. TSN inhibited OSCC cell proliferation by downregulating the STAT3 pathway through the inhibition of STAT3 phosphorylation. After successful construction of the OSCC PDX model with high pathological homology to the primary tumor and treatment with an intraperitoneal injection of TSN, we showed that TSN significantly reduced the tumor size of the PDX model mice without obvious toxicity.

CONCLUSIONS

Both in vitro and in vivo, TSN significantly inhibits the proliferation and promoted apoptosis of OSCC cells. Furthermore, TSN demonstrates potent inhibition of STAT3 phosphorylation, indicating its potential as a promising therapeutic agent for OSCC. Therefore, TSN holds great promise as a viable drug candidate for the treatment of OSCC.

Gynecologic and Breast Cancers: What's New in Chemoresistance and Chemosensitivity Tests?

Gynecological and breast cancers affect women's health worldwide. Although chemotherapy is one of the principal treatments for cancer, it also has limitations owing to toxicity and tumor resistance to the drugs used. Thus, individualized treatment based on personal tumor characteristics is essential for improving therapeutic outcomes and patient survival. Chemoresistance and chemosensitivity tests can be useful for predicting tumor response and guiding chemotherapy choices. This methodology has already been applied to breast, ovarian, cervical, and endometrial cancers, identifying successfully which drugs cause resistance and sensitivity responses for each individual person, influencing their progression-free survival and overall response. In addition, more recent techniques, such as organoids and patient-derived xenografts, can also recapitulate patients' tumor characteristics and contribute to chemo response evaluation. Therefore, this review compiles information on chemoresistance and chemosensitivity tests performed in gynecologic and breast cancers and their main results for women's health improvement.

Synergistic combination therapy delivered via layer-by-layer nanoparticles induces solid tumor regression of ovarian cancer

The majority of patients with high grade serous ovarian cancer (HGSOC) develop recurrent disease and chemotherapy resistance. To identify drug combinations that would be effective in treatment of chemotherapy resistant disease, we examined the efficacy of drug combinations that target the three antiapoptotic proteins most commonly expressed in HGSOC-BCL2, BCL-XL, and MCL1. Co-inhibition of BCL2 and BCL-XL (ABT-263) with inhibition of MCL1 (S63845) induces potent synergistic cytotoxicity in multiple HGSOC models. Since this drug combination is predicted to be toxic to patients due to the known clinical morbidities of each drug, we developed layer-by-layer nanoparticles (LbL NPs) that co-encapsulate these inhibitors in order to target HGSOC tumor cells and reduce systemic toxicities. We show that the LbL NPs can be designed to have high association with specific ovarian tumor cell types targeted in these studies, thus enabling a more selective uptake when delivered via intraperitoneal injection. Treatment with these LbL NPs displayed better potency than free drugs in vitro and resulted in near-complete elimination of solid tumor metastases of ovarian cancer xenografts. Thus, these results support the exploration of LbL NPs as a strategy to deliver potent drug combinations to recurrent HGSOC. While these findings are described for co-encapsulation of a BCL2/XL and a MCL1 inhibitor, the modular nature of LbL assembly provides flexibility in the range of therapies that can be incorporated, making LbL NPs an adaptable vehicle for delivery of additional combinations of pathway inhibitors and other oncology drugs.

Translation Potential and Challenges of In Vitro and Murine Models in Cancer Clinic

As one of the leading causes of death from disease, cancer continues to pose a serious threat to human health globally. Despite the development of novel therapeutic regimens and drugs, the long-term survival of cancer patients is still very low, especially for those whose diagnosis is not caught early enough. Meanwhile, our understanding of tumorigenesis is still limited. Suitable research models are essential tools for exploring cancer mechanisms and treatments. Herein we review and compare several widely used in vitro and in vivo murine cancer models, including syngeneic tumor models, genetically engineered mouse models (GEMM), cell line-derived xenografts (CDX), patient-derived xenografts (PDX), conditionally reprogrammed (CR) cells, organoids, and MiniPDX. We will summarize the methodology and feasibility of various models in terms of their advantages and limitations in the application prospects for drug discovery and development and precision medicine.

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.

Preclinical models of epithelial ovarian cancer: practical considerations and challenges for a meaningful application

Despite many improvements in ovarian cancer diagnosis and treatment, until now, conventional chemotherapy and new biological drugs have not been shown to cure the disease, and the overall prognosis remains poor. Over 90% of ovarian malignancies are categorized as epithelial ovarian cancers (EOC), a collection of different types of neoplasms with distinctive disease biology, response to chemotherapy, and outcome. Advances in our understanding of the histopathology and molecular features of EOC subtypes, as well as the cellular origins of these cancers, have given a boost to the development of clinically relevant experimental models. The overall goal of this review is to provide a comprehensive description of the available preclinical investigational approaches aimed at better characterizing disease development and progression and at identifying new therapeutic strategies. Systems discussed comprise monolayer (2D) and three-dimensional (3D) cultures of established and primary cancer cell lines, organoids and patient-derived explants, animal models, including carcinogen-induced, syngeneic, genetically engineered mouse, xenografts, patient-derived xenografts (PDX), humanized PDX, and the zebrafish and the laying hen models. Recent advances in tumour-on-a-chip platforms are also detailed. The critical analysis of strengths and weaknesses of each experimental model will aid in identifying opportunities to optimize their translational value.

Patient-Derived Organoid Model in the Prediction of Chemotherapeutic Drug Response in Colorectal Cancer

As an emerging technology in precision medicine, the patient-derived organoid (PDO) technology has been indicated to provide novel modalities to judge the sensitivity of individual tumors to cancer drugs. In this work, an in vitro model of colorectal cancer (CRC) was established using the PDO culture, and it is demonstrated that the PDO samples preserved, to a great extent, the histologic features and marker expression of the original tumor tissues. Subsequently, cancer drugs 5-FU, oxaliplatin, and irinotecan were selected and screened on five CRC PDO samples, while the patient-derived organoid xenograft (PDOX) model was applied for comparison. The receiver operating characteristic (ROC) curve was drawn according to the IC₅₀ data from the PDO model and the relative tumor proliferation rate (T/C%) from PDOX. Interestingly, the area under the ROC curve was 0.84 (95% CI, 0.64-1.04, P value = 0.028), which suggested that the IC₅₀ of cancer drugs from the PDO model was strongly correlated with PDOX responses. In addition, the optimal sensitivity cutoff value for drug screening in CRC PDOs was identified at 10.35 μM, which could act as a reference value for efficacy evaluation of 5-FU, oxaliplatin, and irinotecan in the colorectal cancer drug screening. Since there are no unified criteria to judge the sensitivity of drugs in vitro, our work provides a method for establishing in vitro evaluation criteria via PDO and PDOX model using the patient tissues received from local hospitals, exhibiting potential in clinical cancer therapy and precision medicine.

A role for microfluidic systems in precision medicine

Precision oncology continues to challenge the "one-size-fits-all" dogma. Under the precision oncology banner, cancer patients are screened for molecular tumor alterations that predict treatment response, ideally leading to optimal treatments. Functional assays that directly evaluate treatment efficacy on the patient's cells offer an alternative and complementary tool to improve the accuracy of precision oncology. Unfortunately, traditional Petri dish-based assays overlook much tumor complexity, limiting their potential as predictive functional biomarkers. Here, we review past applications of microfluidic systems for precision medicine and discuss the present and potential future role of functional microfluidic assays as treatment predictors.

Patient-derived tumor models are attractive tools to repurpose drugs for ovarian cancer treatment: Pre-clinical updates

Despite advances in understanding of ovarian cancer biology, the progress in translation of research findings into new therapies is still slow. It is associated in part with limitations of commonly used cancer models such as cell lines and genetically engineered mouse models that lack proper representation of diversity and complexity of actual human tumors. In addition, the development of de novo anticancer drugs is a lengthy and expensive process. A promising alternative to new drug development is repurposing existing FDA-approved drugs without primary oncological purpose. These approved agents have known pharmacokinetics, pharmacodynamics, and toxicology and could be approved as anticancer drugs quicker and at lower cost. To successfully translate repurposed drugs to clinical application, an intermediate step of pre-clinical animal studies is required. To address challenges associated with reliability of tumor models for pre-clinical studies, there has been an increase in development of patient-derived xenografts (PDXs), which retain key characteristics of the original patient’s tumor, including histologic, biologic, and genetic features. The expansion and utilization of clinically and molecularly annotated PDX models derived from different ovarian cancer subtypes could substantially aid development of new therapies or rapid approval of repurposed drugs to improve treatment options for ovarian cancer patients.

Syzygium cumini (jamun) fruit-extracted phytochemicals exert anti-proliferative effect on ovarian cancer cells

Background

The medicinal properties of Syzygium sp., especially the antidiabetic property, date back to the ancient times. However, in the recent past, extracts from different parts of the Syzygium sp. have demonstrated promising anticancer activities in diverse cancer types, and now, attempts are being made to identify the active phytochemicals.

Aims and Objectives

In this study, we intended to test the anticancer properties of phytochemicals extracted from the fruit of Syzygium cumini plant in ovarian cancer cells.

Materials and Methods

A total of nine phytochemicals extracted from the S. cumini fruits using chloroform were tested for their anticancer activity in the ovarian cancer cell line PA-1. 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide tetrazolium assay was performed to calculate the 50% inhibition (IC50) concentration and cell cytotoxicity values. Cell scratch assay was performed to assess the proliferation inhibition activity of the phytochemicals. Cisplatin was used as positive control.

Results

Out of the nine phytochemicals tested, quercetin (QC), gallic acid (GA), and oleanolic acid (OA) were found active. QC and GA were most effective with more than 90% cell cytotoxicity at 2.5 µ g/ml and above concentrations and OA moderately effective up to 5 µg/ml serial concentrations. Cell proliferation was significantly inhibited by QC and GA and moderately but significantly by OA.

Conclusion

Our data demonstrate the anticancer activity of QC, GA, and OA phytochemicals, which is consistent with the previous reports. However, this is the first report showing the anticancer activity of these phytochemicals derived from S. cumini in the ovarian cancer cells. These data suggest that there is a potential to develop these phytochemicals as anticancer therapeutic agents either as monotherapeutic agents or in combination with commonly used chemotherapeutic agents, which needs to be explored.

Modeling the Tumor Microenvironment of Ovarian Cancer: The Application of Self-Assembling Biomaterials

Ovarian cancer (OvCa) is one of the leading causes of gynecologic malignancies. Despite treatment with surgery and chemotherapy, OvCa disseminates and recurs frequently, reducing the survival rate for patients. There is an urgent need to develop more effective treatment options for women diagnosed with OvCa. The tumor microenvironment (TME) is a key driver of disease progression, metastasis and resistance to treatment. For this reason, 3D models have been designed to represent this specific niche and allow more realistic cell behaviors compared to conventional 2D approaches. In particular, self-assembling peptides represent a promising biomaterial platform to study tumor biology. They form nanofiber networks that resemble the architecture of the extracellular matrix and can be designed to display mechanical properties and biochemical motifs representative of the TME. In this review, we highlight the properties and benefits of emerging 3D platforms used to model the ovarian TME. We also outline the challenges associated with using these 3D systems and provide suggestions for future studies and developments. We conclude that our understanding of OvCa and advances in materials science will progress the engineering of novel 3D approaches, which will enable the development of more effective therapies.

Patient-Derived Xenografts Are a Reliable Preclinical Model for the Personalized Treatment of Epithelial Ovarian Cancer

To generate robust patient-derived xenograft (PDX) models for epithelial ovarian cancer (EOC), analyze the resemblance of PDX models to the original tumors, and explore factors affecting engraftment rates, fresh cancer tissues from a consecutive cohort of 158 patients with EOC were collected to construct subcutaneous PDX models. Paired samples of original tumors and PDX tumors were compared at the genome, transcriptome, protein levels, and the platinum-based chemotherapy response was evaluated to ensure the reliability of the PDXs. Univariate and multivariate analyses were used to determine the factors affecting the engraftment rates. The engraftment success rate was 58.23% (92/158) over 3–6 months. The Ki-67 index and receiving neoadjuvant chemotherapy can affect the engraftment rate in primary patients. The PDX models generated in this study were found to retain the histomorphology, protein expression, and genetic alteration patterns of the original tumors, despite the transcriptomic differences observed. Clinically, the PDX models demonstrated a high degree of similarity with patients in terms of the chemotherapy response and could predict prognosis. Thus, the PDX model can be considered a promising and reliable preclinical tool for personalized and precise treatment.

Patient-Derived Xenograft Models in Cervical Cancer: A Systematic Review

BACKGROUND

Patient-derived xenograft (PDX) models have been a focus of attention because they closely resemble the tumor features of patients and retain the molecular and histological features of diseases. They are promising tools for translational research. In the current systematic review, we identify publications on PDX models of cervical cancer (CC-PDX) with descriptions of main methodological characteristics and outcomes to identify the most suitable method for CC-PDX.

METHODS

We searched on PubMed to identify articles reporting CC-PDX. Briefly, the main inclusion criterion for papers was description of PDX created with fragments obtained from human cervical cancer specimens, and the exclusion criterion was the creation of xenograft with established cell lines.

RESULTS

After the search process, 10 studies were found and included in the systematic review. Among 98 donor patients, 61 CC-PDX were established, and the overall success rate was 62.2%. The success rate in each article ranged from 0% to 75% and was higher when using severe immunodeficient mice such as severe combined immunodeficient (SCID), nonobese diabetic (NOD) SCID, and NOD SCID gamma (NSG) mice than nude mice. Subrenal capsule implantation led to a higher engraftment rate than orthotopic and subcutaneous implantation. Fragments with a size of 1-3 mm3 were suitable for CC-PDX. No relationship was found between the engraftment rate and characteristics of the tumor and donor patient, including histology, staging, and metastasis. The latency period varied from 10 days to 12 months. Most studies showed a strong similarity in pathological and immunohistochemical features between the original tumor and the PDX model.

CONCLUSION

Severe immunodeficient mice and subrenal capsule implantation led to a higher engraftment rate; however, orthotopic and subcutaneous implantation were alternatives. When using nude mice, subrenal implantation may be better. Fragments with a size of 1-3 mm3 were suitable for CC-PDX. Few reports have been published about CC-PDX; the results were not confirmed because of the small sample size.

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.

Establishment and characterization of an ovarian yolk sac tumor patient-derived xenograft model

OBJECTIVE

The lack of appropriate preclinical models of ovarian yolk sac tumor (OYST) is currently hindering the pursuit of new methods of treatment and investigation of the pathogenesis of the disease. We developed and characterized an OYST patient-derived xenograft (PDX) model in this study.

METHODS

Tumor fragments from a patient with an OYST were implanted subcutaneously into BALB/c Nude mice. Engrafted xenografts were compared with the original tumor according to histology, immunohistochemistry, humanized identified, and drug efficacy testing with in vivo treatment programs.

RESULTS

There was a high degree of histologic and immunohistochemical (IHC) resemblance between the established PDX model and its corresponding human tumors. Bleomycin, etoposide, and cisplatin (JEB) chemotherapy regimens were effective in clinical patients and were effective in the OYST PDX model; therefore, the effect of PDX intervention was consistent with clinical outcomes of OYSTs.

CONCLUSION

We have successfully established an OYST PDX model. This OYST model preserves the basic molecular features of the primary human tumor, thereby providing a valuable method to preclinically evaluate new treatments and explore disease pathogenesis.

Patient-Derived Xenograft Models for Intrahepatic Cholangiocarcinoma and Their Application in Guiding Personalized Medicine

Background

Intrahepatic cholangiocarcinoma (ICC) remains one of the most intractable malignancies. The development of effective drug treatments for ICC is seriously hampered by the lack of reliable tumor models. At present, patient derived xenograft (PDX) models prove to accurately reflect the genetic and biological diversity required to decipher tumor biology and therapeutic vulnerabilities. This study was designed to investigate the establishment and potential application of PDX models for guiding personalized medicine and identifying potential biomarker for lenvatinib resistance.

Methods

We generated PDX models from 89 patients with ICC and compared the morphological and molecular similarities of parental tumors and passaged PDXs. The clinicopathologic features affecting PDX engraftment and the prognostic significance of PDX engraftment were analyzed. Drug treatment responses were analyzed in IMF-138, IMF-114 PDX models and corresponding patients. Finally, lenvatinib treatment response was examined in PDX models and potential drug resistance mechanism was revealed.

Results

Forty-nine PDX models were established (take rate: 55.1%). Successful PDX engraftment was associated with negative HbsAg (P = 0.031), presence of mVI (P = 0.001), poorer tumor differentiation (P = 0.023), multiple tumor number (P = 0.003), presence of lymph node metastasis (P = 0.001), and later TNM stage (P = 0.039). Moreover, patients with tumor engraftment had significantly shorter time to recurrence (TTR) (P < 0.001) and worse overall survival (OS) (P < 0.001). Multivariate analysis indicated that PDX engraftment was an independent risk factor for shortened TTR (HR = 1.84; 95% CI, 1.05–3.23; P = 0.034) and OS (HR = 2.13; 95% CI, 1.11–4.11; P = 0.024). PDXs were histologically and genetically similar to their parental tumors. We also applied IMF-138 and IMF-114 PDX drug testing results to guide clinical treatment for patients with ICC and found similar treatment responses. PDX models also facilitated personalized medicine for patients with ICC based on drug screening results using whole exome sequencing data. Additionally, PDX models reflected the heterogeneous sensitivity to lenvatinib treatment and CDH1 might be vital to lenvatinib-resistance.

Conclusion

PDX models provide a powerful platform for preclinical drug discovery, and potentially facilitate the implementation of personalized medicine and improvement of survival of ICC cancer patient.

Establishment and preclinical application of a patient-derived xenograft model for uterine cancer

BACKGROUND

The patient-derived xenograft (PDX) model is a promising translational platform for duplicating the characteristics of primary tumors. Here, we established and characterized PDX models of uterine cancer to demonstrate their utility for preclinical drug testing.

MATERIALS AND METHODS

We generated PDX tumors surgically derived from 58 cases of uterine cancer. Subrenal capsule xenografts and primary tumors were compared using microscopic examination, short tandem repeat analyses, and targeted sequencing analyses. A phosphatidylinositol 3-kinase (PI3K) inhibitor was administered to mice whose PDX tumors harbored a PTEN deletion or PIK3CA mutation. We also generated an orthotopic PDX model using uterine horn implantation.

RESULTS

Thirty-three (56.9%) PDXs were successfully generated and passaged to maintain tumors. The histological features of the PDX tumors were stable over subsequent passages. By contrast, the proportions of epithelial and mesenchymal components of carcinosarcoma PDX models varied by generation. Targeted sequencing analyses revealed that all mutated cancer-related genes were stable during establishment and subgrafting. Treatment with a PI3K inhibitor cased a significant decrease in tumor weight in the clear cell carcinoma PDX harboring a frameshift PTEN deletion (p = 0.049) and in the serous carcinoma PDX harboring a missense PI3KCA mutation (p = 0.003) compared with matched controls. We also successfully established orthotopic PDX models (3/3; 100.0%).

CONCLUSIONS

The histological and genetic features of PDXs were similar to those of primary tumors. This model is a promising translational platform for preclinical testing of new anticancer drugs and will enable the personalized development of therapeutic options for uterine cancer.

Organoids of the Female Reproductive Tract: Innovative Tools to Study Desired to Unwelcome Processes

The pelviperineal organs of the female reproductive tract form an essential cornerstone of human procreation. The system comprises the ectodermal external genitalia, the Müllerian upper-vaginal, cervical, endometrial and oviductal derivatives, and the endodermal ovaries. Each of these organs presents with a unique course of biological development as well as of malignant degeneration. For many decades, various preclinical in vitro models have been employed to study female reproductive organ (patho-)biology, however, facing important shortcomings of limited expandability, loss of representativeness and inadequate translatability to the clinic. The recent emergence of 3D organoid models has propelled the field forward by generating powerful research tools that in vitro replicate healthy as well as diseased human tissues and are amenable to state-of-the-art experimental interventions. Here, we in detail review organoid modeling of the different female reproductive organs from healthy and tumorigenic backgrounds, and project perspectives for both scientists and clinicians.

Sphingolipids as multifaceted mediators in ovarian cancer

Ovarian cancer is the most lethal gynaecological malignancy. It is commonly diagnosed at advanced stage when it has metastasised to the abdominal cavity and treatment becomes very challenging. While current standard therapy involving debulking surgery and platinum + taxane-based chemotherapy is associated with high response rates initially, the large majority of patients relapse and ultimately succumb to chemotherapy-resistant disease. In order to improve survival novel strategies for early detection and therapeutics against treatment-refractory disease are urgently needed. A promising new target against ovarian cancer is the sphingolipid pathway which is commonly hijacked in cancer to support cell proliferation and survival and has been shown to promote chemoresistance and metastasis in a wide range of malignant neoplasms. In particular, the sphingosine kinase 1-sphingosine 1-phosphate receptor 1 axis has been shown to be altered in ovarian cancer in multiple ways and therefore represents an attractive therapeutic target. Here we review the roles of sphingolipids in ovarian cancer progression, metastasis and chemoresistance, highlighting novel strategies to target this pathway that represent potential avenues to improve patient survival.

The organoid: A research model for ovarian cancer

Epithelial ovarian cancer (EOC) is a heterogeneous disease with a variety of distinct clinical and molecular characteristics. The currently available and common research models for EOC include tumor cell lines and patient-derived xenografts. However, these models have certain shortcomings: establishing a cell line is time-consuming, loss of genetic traits after long-term culture is a possibility, and investment is required in terms of animal care facilities. Therefore, better research models are required. Organoid technology was originally developed from colorectal cancer. Tumor organoid is a three-dimensional culture system and can help accurately recapture the tumor phenotype from the original tumor. Tumor organoid systems can overcome the above-mentioned shortcomings of the currently available research models. The organoid model can be used for culturing ovarian cancer subtypes, screening drugs, assessing genomes, and establishing biobanks. However, the currently available organoid models can only culture one type of cells, epithelial cells. Therefore, an organoid-on-a-chip device can be developed in the future to provide a microenvironment for cell–cell, cell–matrix, and cell–media interactions. Thus, organoid models can be used in ovarian cancer research and can generate a simulated in vivo system, enabling studies on the heterogeneity of ovarian cancer.

Pharmacologic profiling of patient-derived xenograft models of primary treatment-naïve triple-negative breast cancer

Triple-negative breast cancer (TNBC) accounts for 15-20% of breast cancer cases in the United States, lacks targeted therapeutic options, and is associated with a 40-80% risk of recurrence. Thus, identifying actionable targets in treatment-naïve and chemoresistant TNBC is a critical unmet medical need. To address this need, we performed high-throughput drug viability screens on human tumor cells isolated from 16 patient-derived xenograft models of treatment-naïve primary TNBC. The models span a range of TNBC subtypes and exhibit a diverse set of putative driver mutations, thus providing a unique patient-derived, molecularly annotated pharmacologic resource that is reflective of TNBC. We identified therapeutically actionable targets including kinesin spindle protein (KSP). The KSP inhibitor targets the mitotic spindle through mechanisms independent of microtubule stability and showed efficacy in models that were resistant to microtubule inhibitors used as part of the current standard of care for TNBC. We also observed subtype selectivity of Prima-1^Met, which showed higher levels of efficacy in the mesenchymal subtype. Coupling pharmacologic data with genomic and transcriptomic information, we showed that Prima-1^Met activity was independent of its canonical target, mutant p53, and was better associated with glutathione metabolism, providing an alternate molecularly defined biomarker for this drug.

A Biobank of Colorectal Cancer Patient-Derived Xenografts

Colorectal cancer (CRC) is a challenging disease, with a high mortality rate and limited effective treatment options, particularly for late-stage disease. Patient-derived xenografts (PDXs) have emerged as an informative, renewable experimental resource to model CRC architecture and biology. Here, we describe the generation of a biobank of CRC PDXs from stage I to stage IV patients. We demonstrate that PDXs within our biobank recapitulate the histopathological and mutation features of the original patient tumor. In addition, we demonstrate the utility of this resource in pre-clinical chemotherapy and targeted treatment studies, highlighting the translational potential of PDX models in the identification of new therapies that will improve the overall survival of CRC patients.

The Application of Patient-Derived Xenograft Models in Gynecologic Cancers

Recently, due to the limitations of cell line models and animal models in the preclinical research with insufficient reflecting the physiological situation of humans, patient-derived xenograft (PDX) models of many cancers have been widely developed because of their better representation of the tumor heterogeneity and tumor microenvironment with retention of the cellular complexity, cytogenetics, and stromal architecture. PDX models now have been identified as a powerful tool for determining cancer characteristics, developing new treatment, and predicting drug efficacy. An increase in attempts to generate PDX models in gynecologic cancers has emerged in recent years to understand tumorigenesis. Hence, this review summarized the generation of PDX models and engraftment success of PDX models in gynecologic cancers. Furthermore, we illustrated the similarity between PDX model and original tumor, and described preclinical utilization of PDX models in gynecologic cancers. It would help supply better personalized therapy for gynecologic cancer patients.

Unique miRNA profiling of squamous cell carcinoma arising from ovarian mature teratoma: comprehensive miRNA sequence analysis of its molecular background

Owing to its rarity, the carcinogenesis and molecular biological characteristics of squamous cell carcinoma arising from mature teratoma remain unclear. This study aims to elucidate the molecular background of malignant transformation from the aspects of microRNA (miRNA) profiling. We examined 7 patients with squamous cell carcinoma and 20 patients with mature teratoma and extracted their total RNA from formalin-fixed paraffin-embedded tissues. Then we prepared small RNA libraries and performed comprehensive miRNA sequencing. Heatmap and principal component analysis revealed markedly different miRNA profiling in cancer, normal ovarian and mature teratoma tissues. Then we narrowed down cancer-related miRNAs, comparing paired-cancer and normal ovaries. Comparisons of cancer and mature teratoma identified two markedly upregulated miRNAs (miR-151a-3p and miR-378a-3p) and two markedly downregulated miRNAs (miR-26a-5p and miR-99a-5p). In addition, these findings were validated in fresh cancer tissues of patient-derived xenograft (PDX) models. Moreover, several miRNAs, including miR-151a-3p and miR-378a-3p, were elevated in the murine plasma when tumor tissues were enlarged although miR-26a-5p and miR-99a-5p were not elucidated in the murine plasma. Finally, we performed target prediction and functional annotation analysis in silico and indicated that targets genes of these miRNAs markedly correlated with cancer-related pathways, including 'pathway in cancer' and 'cell cycle'. In conclusion, this is the first study on miRNA sequencing for squamous cell carcinoma arising from mature teratoma. The study identified four cancer-related miRNAs that were considered to be related to the feature of malignant transformation. Moreover, miRNAs circulating in the murine plasma of the PDX model could be novel diagnostic biomarkers.

PIK3R1W624R Is an Actionable Mutation in High Grade Serous Ovarian Carcinoma

Identifying cancer drivers and actionable mutations is critical for precision oncology. In epithelial ovarian cancer (EOC) the majority of mutations lack biological or clinical validation. We fully characterized 43 lines of Patient-Derived Xenografts (PDXs) and performed copy number analysis and whole exome sequencing of 12 lines derived from naïve, high grade EOCs. Pyrosequencing allowed quantifying mutations in the source tumours. Drug response was assayed on PDX Derived Tumour Cells (PDTCs) and in vivo on PDXs. We identified a PIK3R1W624R variant in PDXs from a high grade serous EOC. Allele frequencies of PIK3R1W624R in all the passaged PDXs and in samples of the source tumour suggested that it was truncal and thus possibly a driver mutation. After inconclusive results in silico analyses, PDTCs and PDXs allowed the showing actionability of PIK3R1W624R and addiction of PIK3R1W624R carrying cells to inhibitors of the PI3K/AKT/mTOR pathway. It is noteworthy that PIK3R1 encodes the p85α regulatory subunit of PI3K, that is very rarely mutated in EOC. The PIK3R1W624R mutation is located in the cSH2 domain of the p85α that has never been involved in oncogenesis. These data show that patient-derived models are irreplaceable in their role of unveiling unpredicted driver and actionable variants in advanced ovarian cancer.

The Complexities of Metastasis

Therapies that prevent metastatic dissemination and tumor growth in secondary organs are severely lacking. A better understanding of the mechanisms that drive metastasis will lead to improved therapies that increase patient survival. Within a tumor, cancer cells are equipped with different phenotypic and functional capacities that can impact their ability to complete the metastatic cascade. That phenotypic heterogeneity can be derived from a combination of factors, in which the genetic make-up, interaction with the environment, and ability of cells to adapt to evolving microenvironments and mechanical forces play a major role. In this review, we discuss the specific properties of those cancer cell subgroups and the mechanisms that confer or restrict their capacity to metastasize.

ALDH1A1 Contributes to PARP Inhibitor Resistance via Enhancing DNA Repair in BRCA2-/- Ovarian Cancer Cells

Poly (ADP-ribose) polymerase (PARP) inhibitors (PARPi) are approved to treat recurrent ovarian cancer with BRCA1 or BRCA2 mutations, and as maintenance therapy for recurrent platinum-sensitive ovarian cancer (BRCA wild-type or mutated) after treatment with platinum. However, the acquired resistance against PARPi remains a clinical hurdle. Here, we demonstrated that PARP inhibitor (olaparib)-resistant epithelial ovarian cancer (EOC) cells exhibited an elevated aldehyde dehydrogenase (ALDH) activity, mainly contributed by increased expression of ALDH1A1 due to olaparib-induced expression of BRD4, a member of bromodomain and extraterminal (BET) family protein. We also revealed that ALDH1A1 enhanced microhomology-mediated end joining (MMEJ) activity in EOC cells with inactivated BRCA2, a key protein that promotes homologous recombination (HR) by using an intrachromosomal MMEJ reporter. Moreover, NCT-501, an ALDH1A1-selective inhibitor, can synergize with olaparib in killing EOC cells carrying BRCA2 mutation in both in vitro cell culture and the in vivo xenograft animal model. Given that MMEJ activity has been reported to be responsible for PARPi resistance in HR-deficient cells, we conclude that ALDH1A1 contributes to the resistance to PARP inhibitors via enhancing MMEJ in BRCA2^-/- ovarian cancer cells. Our findings provide a novel mechanism underlying PARPi resistance in BRCA2-mutated EOC cells and suggest that inhibition of ALDH1A1 could be exploited for preventing and overcoming PARPi resistance in EOC patients carrying BRCA2 mutation.

Primary Tumor Site Specificity is Preserved in Patient-Derived Tumor Xenograft Models

Patient-derived tumor xenograft (PDX) mouse models are widely used for drug screening. The underlying assumption is that PDX tissue is very similar with the original patient tissue, and it has the same response to the drug treatment. To investigate whether the primary tumor site information is well preserved in PDX, we analyzed the gene expression profiles of PDX mouse models originated from different tissues, including breast, kidney, large intestine, lung, ovary, pancreas, skin, and soft tissues. The popular Monte Carlo feature selection method was employed to analyze the expression profile, yielding a feature list. From this list, incremental feature selection and support vector machine (SVM) were adopted to extract distinctively expressed genes in PDXs from different primary tumor sites and build an optimal SVM classifier. In addition, we also set up a group of quantitative rules to identify primary tumor sites. A total of 755 genes were extracted by the feature selection procedures, on which the SVM classifier can provide a high performance with MCC 0.986 on classifying primary tumor sites originated from different tissues. Furthermore, we obtained 16 classification rules, which gave a lower accuracy but clear classification procedures. Such results validated that the primary tumor site specificity was well preserved in PDX as the PDXs from different primary tumor sites were still very different and these PDX differences were similar with the differences observed in patients with tumor. For example, VIM and ABHD17C were highly expressed in the PDX from breast tissue and also highly expressed in breast cancer patients.

Application of Highly Immunocompromised Mice for the Establishment of Patient-Derived Xenograft (PDX) Models

Patient-derived xenograft (PDX) models are created by engraftment of patient tumor tissues into immunocompetent mice. Since a PDX model retains the characteristics of the primary patient tumor including gene expression profiles and drug responses, it has become the most reliable in vivo human cancer model. The engraftment rate increases with the introduction of Non-obese diabetic Severe combined immunodeficiency (NOD/SCID)-based immunocompromised mice, especially the NK-deficient NOD strains NOD/SCID/interleukin-2 receptor gamma chain(IL2Rγ)null (NOG/NSG) and NOD/SCID/Jak3(Janus kinase 3)null (NOJ). Success rates differ with tumor origin: gastrointestinal tumors acquire a higher engraftment rate, while the rate is lower for breast cancers. Subcutaneous transplantation is the most popular method to establish PDX, but some tumors require specific environments, e.g., orthotropic or renal capsule transplantation. Human hormone treatment is necessary to establish hormone-dependent cancers such as prostate and breast cancers. PDX mice with human hematopoietic and immune systems (humanized PDX) are powerful tools for the analysis of tumor-immune system interaction and evaluation of immunotherapy response. A PDX biobank equipped with patients' clinical data, gene-expression patterns, mutational statuses, tumor tissue architects, and drug responsiveness will be an authoritative resource for developing specific tumor biomarkers for chemotherapeutic predictions, creating individualized therapy, and establishing precise cancer medicine.

Establishment of patient-derived xenograft model in ovarian cancer and its influence factors analysis

AIM

Patient-derived xenograft (PDX) model has been applied to the study of breast cancer, lung cancer, colon cancer and other cancers. However, its feasibility in ovarian cancer has not been understood. This study aimed to establish ovarian cancer PDX model and reveal its influence factors.

METHODS

In this study, 27 patients in Obstetrics and Gynecology Hospital affiliated to Fudan University from May 2015 to May 2016 were employed to explore the method of PDX model in ovarian cancer and verify its feasibility.

RESULTS

Finally, five cases of PDX models were successfully established, and the tumor formation rate (TFR) was 18.52%. In addition, immunohistochemistry and transcriptome sequencing analysis showed that tumor of PDX model have similar gene expression, gene splicing, gene fusion and single nucleotide polymorphisms with primary tumor (R² = 0.741). Furthermore, it was revealed that compared to epithelial ovarian cancer, the TFR of PDX models with nonepithelial ovarian cancer was higher, while other factors such as the initiation site of tumor, the degree of tumor malignancy, the stage of tumor, the type of tumor and the species of experimental animals were not associated with the TFR.

CONCLUSION

Ovarian cancer PDX model, as a new scientific research model, can better keep the biological characteristics of primary tumor, which has great research value in ovarian cancer.

Engineered 3D Model of Cancer Stem Cell Enrichment and Chemoresistance

Intraperitoneal dissemination of ovarian cancers is preceded by the development of chemoresistant tumors with malignant ascites. Despite the high levels of chemoresistance and relapse observed in ovarian cancers, there are no in vitro models to understand the development of chemoresistance in situ. Method: We describe a highly integrated approach to establish an in vitro model of chemoresistance and stemness in ovarian cancer, using the 3D hanging drop spheroid platform. The model was established by serially passaging non-adherent spheroids. At each passage, the effectiveness of the model was evaluated via measures of proliferation, response to treatment with cisplatin and a novel ALDH1A inhibitor. Concomitantly, the expression and tumor initiating capacity of cancer stem-like cells (CSCs) was analyzed. RNA-seq was used to establish gene signatures associated with the evolution of tumorigenicity, and chemoresistance. Lastly, a mathematical model was developed to predict the emergence of CSCs during serial passaging of ovarian cancer spheroids. Results: Our serial passage model demonstrated increased cellular proliferation, enriched CSCs, and emergence of a platinum resistant phenotype. In vivo tumor xenograft assays indicated that later passage spheroids were significantly more tumorigenic with higher CSCs, compared to early passage spheroids. RNA-seq revealed several gene signatures supporting the emergence of CSCs, chemoresistance, and malignant phenotypes, with links to poor clinical prognosis. Our mathematical model predicted the emergence of CSC populations within serially passaged spheroids, concurring with experimentally observed data. Conclusion: Our integrated approach illustrates the utility of the serial passage spheroid model for examining the emergence and development of chemoresistance in ovarian cancer in a controllable and reproducible format.

Current Status of Patient-Derived Ovarian Cancer Models

Ovarian cancer (OC) is one of the leading causes of female cancer death. Recent studies have documented its extensive variations as a disease entity, in terms of cell or tissue of origin, pre-cancerous lesions, common mutations, and therapeutic responses, leading to the notion that OC is a generic term referring to a whole range of different cancer subtypes. Despite such heterogeneity, OC treatment is stereotypic; aggressive surgery followed by conventional chemotherapy could result in chemo-resistant diseases. Whereas molecular-targeted therapies will become shortly available for a subset of OC, there still remain many patients without effective drugs, requiring development of groundbreaking therapeutic agents. In preclinical studies for drug discovery, cancer cell lines used to be the gold standard, but now this has declined due to frequent failure in predicting therapeutic responses in patients. In this regard, patient-derived cells and tumors are gaining more attention in precise and physiological modeling of in situ tumors, which could also pave the way to implementation of precision medicine. In this article, we comprehensively overviewed the current status of various platforms for patient-derived OC models. We highly appreciate the potentials of organoid culture in achieving high success rate and retaining tumor heterogeneity.

DNA topoisomerase IIα and RAD21 cohesin complex component are predicted as potential therapeutic targets in bladder cancer

Cancer is essentially a genetic disease. Accumulated gene mutations accelerate genome instability, which eventually leads to uncontrollable growth of the tumor. Bladder cancer is the most common form of urinary tract cancer. This form of cancer has a poor prognosis due to its clinical heterogeneity and molecular diversity. Despite recent scientific advances, the knowledge and treatment of bladder cancer still lags behind that of other types of solid tumor. In the present study, available large data portals and other studies were used to obtain clinically relevant information, and the data were systematically processed to decipher the genes associated with bladder cancer. Genes associated with the survival time of patients with bladder cancer were successfully identified. The genes were enriched in common biological processes and pathways, and upregulated in tumor samples from patients. Among the top genes identified as associated with good or poor survival in bladder cancer, DNA topoisomerase IIα (TOP2α) and RAD21 cohesin complex component (RAD21) were also increased in bladder cancer tissues and cell lines. Therefore, TOP2α and RAD21 could be used as potential therapeutic targets in bladder cancer.

A Pan-ALDH1A Inhibitor Induces Necroptosis in Ovarian Cancer Stem-like Cells

Ovarian cancer is typified by the development of chemotherapy resistance. Chemotherapy resistance is associated with high aldehyde dehydrogenase (ALDH) enzymatic activity, increased cancer "stemness," and expression of the stem cell marker CD133. As such, ALDH activity has been proposed as a therapeutic target. Although it remains controversial which of the 19 ALDH family members drive chemotherapy resistance, ALDH1A family members have been primarily linked with chemotherapy resistant and stemness. We identified two ALDH1A family selective inhibitors (ALDH1Ai). ALDH1Ai preferentially kills CD133+ ovarian cancer stem-like cells (CSCs). ALDH1Ai induce necroptotic CSC death, mediated, in part, by the induction of mitochondrial uncoupling proteins and reduction in oxidative phosphorylation. ALDH1Ai is highly synergistic with chemotherapy, reducing tumor initiation capacity and increasing tumor eradication in vivo. These studies link ALDH1A with necroptosis and confirm the family as a critical therapeutic target to overcome chemotherapy resistance and improve patient outcomes.

High-Grade Serous Ovarian Cancer: Basic Sciences, Clinical and Therapeutic Standpoints

Among a litany of malignancies affecting the female reproductive tract, that of the ovary is the most frequently fatal. Moreover, while the steady pace of scientific discovery has fuelled recent ameliorations in the outcomes of many other cancers, the rates of mortality for ovarian cancer have been stagnant since around 1980. Yet despite the grim outlook, progress is being made towards better understanding the fundamental biology of this disease and how its biology in turn influences clinical behaviour. It has long been evident that ovarian cancer is not a unitary disease but rather a multiplicity of distinct malignancies that share a common anatomical site upon presentation. Of these, the high-grade serous subtype predominates in the clinical setting and is responsible for a disproportionate share of the fatalities from all forms of ovarian cancer. This review aims to provide a detailed overview of the clinical-pathological features of ovarian cancer with a particular focus on the high-grade serous subtype. Along with a description of the relevant clinical aspects of this disease, including novel trends in treatment strategies, this text will inform the reader of recent updates to the scientific literature regarding the origin, aetiology and molecular-genetic basis of high-grade serous ovarian cancer (HGSOC).

High-Grade Serous Ovarian Cancer: Basic Sciences, Clinical and Therapeutic Standpoints

Among a litany of malignancies affecting the female reproductive tract, that of the ovary is the most frequently fatal. Moreover, while the steady pace of scientific discovery has fuelled recent ameliorations in the outcomes of many other cancers, the rates of mortality for ovarian cancer have been stagnant since around 1980. Yet despite the grim outlook, progress is being made towards better understanding the fundamental biology of this disease and how its biology in turn influences clinical behaviour. It has long been evident that ovarian cancer is not a unitary disease but rather a multiplicity of distinct malignancies that share a common anatomical site upon presentation. Of these, the high-grade serous subtype predominates in the clinical setting and is responsible for a disproportionate share of the fatalities from all forms of ovarian cancer. This review aims to provide a detailed overview of the clinical-pathological features of ovarian cancer with a particular focus on the high-grade serous subtype. Along with a description of the relevant clinical aspects of this disease, including novel trends in treatment strategies, this text will inform the reader of recent updates to the scientific literature regarding the origin, aetiology and molecular-genetic basis of high-grade serous ovarian cancer (HGSOC).

High-Grade Serous Ovarian Cancer: Basic Sciences, Clinical and Therapeutic Standpoints

Among a litany of malignancies affecting the female reproductive tract, that of the ovary is the most frequently fatal. Moreover, while the steady pace of scientific discovery has fuelled recent ameliorations in the outcomes of many other cancers, the rates of mortality for ovarian cancer have been stagnant since around 1980. Yet despite the grim outlook, progress is being made towards better understanding the fundamental biology of this disease and how its biology in turn influences clinical behaviour. It has long been evident that ovarian cancer is not a unitary disease but rather a multiplicity of distinct malignancies that share a common anatomical site upon presentation. Of these, the high-grade serous subtype predominates in the clinical setting and is responsible for a disproportionate share of the fatalities from all forms of ovarian cancer. This review aims to provide a detailed overview of the clinical-pathological features of ovarian cancer with a particular focus on the high-grade serous subtype. Along with a description of the relevant clinical aspects of this disease, including novel trends in treatment strategies, this text will inform the reader of recent updates to the scientific literature regarding the origin, aetiology and molecular-genetic basis of high-grade serous ovarian cancer (HGSOC).

Genetic Profiles Associated with Chemoresistance in Patient-Derived Xenograft Models of Ovarian Cancer

PURPOSE

Recurrence and chemoresistance (CR) are the leading causes of death in patients with high-grade serous carcinoma (HGSC) of the ovary. The aim of this study was to identify genetic changes associated with CR mechanisms using a patient-derived xenograft (PDX) mouse model and genetic sequencing.

MATERIALS AND METHODS

To generate a CR HGSC PDX tumor, mice bearing subcutaneously implanted HGSC PDX tumors were treated with paclitaxel and carboplatin. We compared gene expression and mutations between chemosensitive (CS) and CR PDX tumors with whole exome and RNA sequencing and selected candidate genes. Correlations between candidate gene expression and clinicopathological variables were explored using the Cancer Genome Atlas (TCGA) database and the Human Protein Atlas (THPA).

RESULTS

Three CR and four CS HGSC PDX tumor models were successfully established. RNA sequencing analysis of the PDX tumors revealed that 146 genes were significantly up-regulated and 54 genes down-regulated in the CR group compared with the CS group. Whole exome sequencing analysis showed 39 mutation sites were identified which only occurred in CR group. Differential expression of SAP25, HLA-DPA1, AKT3, and PIK3R5 genes and mutation of TMEM205 and POLR2A may have important functions in the progression of ovarian cancer chemoresistance. According to TCGA data analysis, patients with high HLA-DPA1 expression were more resistant to initial chemotherapy (p=0.030; odds ratio, 1.845).

CONCLUSION

We successfully established CR ovarian cancer PDX mouse models. PDX-based genetic profiling study could be used to select some candidate genes that could be targeted to overcome chemoresistance of ovarian cancer.

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.

NEAT1 contributes to the CSC-like traits of A549/CDDP cells via activating Wnt signaling pathway

Long non-coding RNAs (lncRNAs) have been identified to exert crucial roles in tumorigenesis and can serve as novel biomarkers for cancer therapy including lung cancer. Cisplatin is a first-line chemotherapeutic agent in non-small cell lung cancer (NSCLC), but the therapeutic effect is unsatisfactory, partly due to drug resistance. Emerging evidence showed that chemo-resistance is associated with acquisition of cancer stem cell (CSC)-like properties. Cisplatin resistance remains a major obstacle in the treatment of lung cancer, and its mechanism is still not fully elucidated. Meanwhile, CSCs have been involved in tumor metastasis, tumor recurrence and chemotherapy resistance. So far, the mechanism of nuclear enriched abundant transcript 1 (NEAT1) in modulating CSCs in lung cancer remains barely known. Therefore, we aimed to explore the correlation between NEAT1 and cancer stem cells in lung cancer. In our current study, we observed that CSC-like traits were much more enriched in cisplatin-resistant A549/CDDP cells. In addition, NEAT1 was obviously up-regulated in A549/CDDP cells compared with parental A549 cells. Knockdown of NEAT1 decreased the CSC-like properties of A549/CDDP cells through inhibiting tumor cell sphere volume, repressing CSC-like biomarkers levels and restraining CD44 positive cell ratios. Oppositely, overexpression of NEAT1 enhanced the stemness respectively. Moreover, it has been reported that Wnt pathway is implicated in many vital cellular functions including cancer stem cells. Here, it was exhibited that Wnt signal pathway was inactivated by knockdown of NEAT1 whereas activated by NEAT1 overexpression in A549/CDDP cells. Taken these together, it was indicated that NEAT1 could exert a novel biological role in NSCLC chemo-resistance.

Sphingolipid metabolism and drug resistance in ovarian cancer

Despite progress in understanding molecular aberrations that contribute to the development and progression of ovarian cancer, virtually all patients succumb to drug resistant disease at relapse. Emerging data implicate bioactive sphingolipids and regulation of sphingolipid metabolism as components of response to chemotherapy or development of resistance. Increases in cytosolic ceramide induce apoptosis in response to therapy with multiple classes of chemotherapeutic agents. Aberrations in sphingolipid metabolism that accelerate the catabolism of ceramide or that prevent the production and accumulation of ceramide contribute to resistance to standard of care platinum- and taxane-based agents. The aim of this review is to highlight current literature and research investigating the influence of the sphingolipids and enzymes that comprise the sphingosine-1-phosphate pathway on the progression of ovarian cancer. The focus of the review is on the utility of sphingolipid-centric therapeutics as a mechanism to circumvent drug resistance in this tumor type.

FTY720 enhances the anti-tumor activity of carboplatin and tamoxifen in a patient-derived xenograft model of ovarian cancer

Ovarian cancer is the fifth leading cause of cancer-related deaths among women in the United States. Although most patients respond to frontline therapy, virtually all patients relapse with chemoresistant disease. This study addresses the hypothesis that carboplatin or tamoxifen + FTY720, a sphingosine analogue, will minimize or circumvent drug-resistance in ovarian cancer cells and tumor models. In vitro data demonstrate that FTY720 sensitized two drug-resistant (A2780. cp20, HeyA8. MDR) and two high-grade serous ovarian cancer cell lines (COV362, CAOV3) to carboplatin, a standard of care for patients with ovarian cancer, and to the selective estrogen receptor modulator tamoxifen. FTY720 + tamoxifen was synergistic in vitro, and combinations of FTY720 + carboplatin or + tamoxifen were more effective than each single agent in a patient-derived xenograft model of ovarian carcinoma. FTY720 + tamoxifen arrested tumor growth. FTY720 + carboplatin induced tumor regressions, with tumor volumes reduced by ∼86% compared to initial tumor volumes. Anti-tumor efficacy was concomitant with increases in intracellular proapoptotic lipid ceramide. The data suggest that FTY720 + tamoxifen or carboplatin may be effective in treating ovarian tumors.

Licofelone Enhances the Efficacy of Paclitaxel in Ovarian Cancer by Reversing Drug Resistance and Tumor Stem-like Properties

Drug development for first-line treatment of epithelial ovarian cancer (EOC) has been stagnant for almost three decades. Traditional cell culture methods for primary drug screening do not always accurately reflect clinical disease. To overcome this barrier, we grew a panel of EOC cell lines in three-dimensional (3D) cell cultures to form multicellular tumor spheroids (MCTS). We characterized these MCTS for molecular and cellular features of EOC and performed a comparative screen with cells grown using two-dimensional (2D) cell culture to identify previously unappreciated anticancer drugs. MCTS exhibited greater resistance to chemotherapeutic agents, showed signs of senescence and hypoxia, and expressed a number of stem cell-associated transcripts including ALDH1A and CD133, also known as PROM1 Using a library of clinically repurposed drugs, we identified candidates with preferential activity in MCTS over 2D cultured cells. One of the lead compounds, the dual COX/LOX inhibitor licofelone, reversed the stem-like properties of ovarian MCTS. Licofelone also synergized with paclitaxel in ovarian MCTS models and in a patient-derived tumor xenograft model. Importantly, the combination of licofelone with paclitaxel prolonged the median survival of mice (>141 days) relative to paclitaxel (115 days), licofelone (37 days), or vehicle (30 days). Increased efficacy was confirmed by Mantel-Haenszel HR compared with vehicle (HR = 0.037) and paclitaxel (HR = 0.017). These results identify for the first time an unappreciated, anti-inflammatory drug that can reverse chemotherapeutic resistance in ovarian cancer, highlighting the need to clinically evaluate licofelone in combination with first-line chemotherapy in primary and chemotherapy-refractory EOC.Significance: This study highlights the use of an in vitro spheroid 3D drug screening model to identify new therapeutic approaches to reverse chemotherapy resistance in ovarian cancer. Cancer Res; 78(15); 4370-85. ©2018 AACR.

Increasing aggressiveness of patient-derived xenograft models of cervix carcinoma during serial transplantation

Four patient-derived xenograft (PDX) models (BK-12, ED-15, HL-16, LA-19) of carcinoma of the uterine cervix have been developed in our laboratory, and their stability during serial transplantation in vivo was investigated in this study. Two frozen cell stocks were established, one from xenografted tumors in passage 2 (early generation) and the other from xenografted tumors transplanted serially in mice for approximately two years (late generation), and the biology of late generation tumors was compared with that of early generation tumors. Late generation tumors showed higher incidence of lymph node metastases than early generation tumors in three models (ED-15, HL-16, LA-19), and the increased metastatic propensity was associated with increased tumor growth rate, increased microvascular density, and increased expression of angiogenesis-related and cancer stem cell-related genes. Furthermore, late generation tumors showed decreased fraction of pimonidazole-positive tissue (i.e., decreased fraction of hypoxic tissue) in two models (HL-16, LA-19) and decreased fraction of collagen-I-positive tissue (i.e., less extensive extracellular matrix) in two models (ED-15, HL-16). This study showed that serially transplanted PDXs may not necessarily mirror the donor patients’ diseases, and consequently, proper use of serially transplanted PDX models in translational cancer research requires careful molecular monitoring of the models.

Enhanced antitumor efficacy of cisplatin for treating ovarian cancer in vitro and in vivo via transferrin binding

Cisplatin is a widely used anticancer drug, while non-targeted delivery, development of drug resistance, and serious side effects significantly limit its clinical use. In order to improve the tumor-targeting properties of cisplatin, transferrin (Tf) was employed as a carrier to transfer cisplatin into cancer cells via transferrin receptor 1 (TfR1) mediated endocytosis. The binding ability of cisplatin and Tf could be improved by pretreating Tf with 10% ethanol, and the binding number of cisplatin for each Tf molecule could reach to 40 without structural or functional impairment of Tf. The Tf-cisplatin complex could be delivered into human ovarian carcinoma cells high efficiently. In tumor-bearing nude-mice model, the Tf-cisplatin complex inhibited tumor growth in vivo more effectively than free cisplatin, with less toxicity in other tissues. Tumor targeting efficiency of the Tf-cisplatin complex was supported by in vivo and ex vivo imaging and platinum residues detected in each ex vivo organ. These data suggested that Tf-cisplatin  was more effective and less drug-resistance than cisplatin, with targeting to tumor cells. Therefore, Tf-mediated delivery of cisplatin is a potential strategy for targeted delivery into tumor cells.

Epigenetic modifiers upregulate MHC II and impede ovarian cancer tumor growth

Expression of MHC class II pathway proteins in ovarian cancer correlates with prolonged survival. Murine and human ovarian cancer cells were treated with epigenetic modulators - histone deacetylase inhibitors and a DNA methyltransferase inhibitor. mRNA and protein expression of the MHC II pathway were evaluated by qPCR and flow cytometry. Treatment with entinostat and azacytidine of ID8 cells in vitro increased mRNA levels of Cd74, Ciita, and H2-Aa, H2-Eb1. MHC II and CD74 protein expression were increased after treatment with either agent. A dose dependent response in mRNA and protein expression was seen with entinostat. Combination treatment showed higher MHC II protein expression than with single agent treatment. In patient derived xenografts, CIITA, CD74, and MHC II mRNA transcripts were significantly increased after combination treatment. Expression of MHC II on ovarian tumors in MISIIR-Tag mice was increased with both agents relative to control. Combination treatment significantly reduced ID8 tumor growth in immune-competent mice. Epigenetic treatment increases expression of MHC II on ovarian cancer cells and impedes tumor growth. This approach warrants further study in ovarian cancer patients.