Comparison of Clinical Features and Outcomes in Epithelial Ovarian Cancer according to Tumorigenicity in Patient-Derived Xenograft Models

TOWARDS Study: Patient-Derived Xenograft Engraftment Predicts Poor Survival in Patients With Newly Diagnosed Triple-Negative Breast Cancer

PURPOSE

Assessing risk of recurrence for nonmetastatic triple-negative breast cancer (TNBC) is a key determinant of therapeutic strategy. The best predictor of recurrence risk is failure to achieve a pathologic complete response after preoperative chemotherapy, but it imperfectly correlates with the definitive end points of relapse-free and overall survival (OS). The inability to accurately predict recurrence has led to increasingly toxic treatment regimens for patients with early-stage TNBC. Better assays for recurrence risk are needed to tailor aggressive therapy for patients who need it and avoid overtreatment and unnecessary toxicity for those at low risk. The purpose of this study was to determine if patient-derived xenograft (PDX) engraftment of newly diagnosed breast tumors can serve as an accurate predictor of recurrence and death from breast cancer.

METHODS

This study was a blinded noninterventional trial comprising 80 patients with newly diagnosed, nonmetastatic, estrogen receptor (ER)-negative or ER-low breast cancer.

RESULTS

PDX engraftment was strongly associated with relapse in 1 year: 8 of 18 (44.4%) patients whose tumors engrafted relapsed versus 1 of 62 (1.6%) patients whose tumors did not engraft (P < .0001). Patients whose tumors engrafted had a hazard ratio (HR) for relapse of 17.5. HRs for OS and breast cancer-specific survival in PDX+ patients were 21.1 and 39.5, respectively.

CONCLUSION

We report that the ability of a tumor to engraft as a PDX predicts early recurrence by serving as a functional readout of aggressiveness and prospectively identifies the most devastating tumors. This provides new opportunity to develop surrogate assays, such as biomarkers of engraftment, which will extend the clinical feasibility of this finding.

Cancer "Avatars": Patient-Derived Xenograft Growth Correlation with Postoperative Recurrence and Survival in Pancreaticobiliary Cancer

BACKGROUND

Pancreaticobiliary (PB) cancers are a diverse group of cancers with poor prognoses and high rates of recurrence after resection. Patient-derived xenografts (PDX), created from surgical specimens, provide a reliable preclinical research platform and high-fidelity cancer model from which to study these malignancies with consistent recapitulation of their original patient tumors in vivo. However, the relationship between PDX engraftment success (growth or no growth) and patient oncologic outcomes has not been well studied. We sought to evaluate the correlation between successful PDX engraftment and survival in several PB exocrine carcinomas, including the pancreatic and biliary tract.

STUDY DESIGN

In accordance with IRB and Institutional Animal Care and Use Committee protocols and with appropriate consent and approval, excess tumor tissue obtained from surgical patients was implanted into immunocompromised mice. Mice were monitored for tumor growth to determine engraftment success. PDX tumors were verified to recapitulate their tumors of origin by a hepatobiliary pathologist. Xenograft growth was correlated with clinical recurrence and overall survival data.

RESULTS

A total of 384 PB xenografts were implanted. The successful engraftment rate was 41% (158/384). We found that successful PDX engraftment was highly associated with both recurrence-free survival (p < 0.001) and overall survival (p < 0.001) outcomes. Successful PDX tumor generation occurs significantly in advance of clinical recurrences in their corresponding patients (p < 0.001).

CONCLUSIONS

Successful PB cancer PDX models predict recurrence and survival across tumor types and may provide critical lead time to alter patients' surveillance or treatment plans before cancer recurrence.

Generation, evolution, interfering factors, applications, and challenges of patient-derived xenograft models in immunodeficient mice

Establishing appropriate preclinical models is essential for cancer research. Evidence suggests that cancer is a highly heterogeneous disease. This follows the growing use of cancer models in cancer research to avoid these differences between xenograft tumor models and patient tumors. In recent years, a patient-derived xenograft (PDX) tumor model has been actively generated and applied, which preserves both cell-cell interactions and the microenvironment of tumors by directly transplanting cancer tissue from tumors into immunodeficient mice. In addition to this, the advent of alternative hosts, such as zebrafish hosts, or in vitro models (organoids and microfluidics), has also facilitated the advancement of cancer research. However, they still have a long way to go before they become reliable models. The development of immunodeficient mice has enabled PDX to become more mature and radiate new vitality. As one of the most reliable and standard preclinical models, the PDX model in immunodeficient mice (PDX-IM) exerts important effects in drug screening, biomarker development, personalized medicine, co-clinical trials, and immunotherapy. Here, we focus on the development procedures and application of PDX-IM in detail, summarize the implications that the evolution of immunodeficient mice has brought to PDX-IM, and cover the key issues in developing PDX-IM in preclinical studies.

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.

Identification of Prognostic Markers of Gynecologic Cancers Utilizing Patient-Derived Xenograft Mouse Models

Patient-derived xenografts (PDXs) are important in vivo models for the development of precision medicine. However, challenges exist regarding genetic alterations and relapse after primary treatment. Thus, PDX models are required as a new approach for preclinical and clinical studies. We established PDX models of gynecologic cancers and analyzed their clinical information. We subcutaneously transplanted 207 tumor tissues from patients with gynecologic cancer into nude mice from 2014 to 2019. The successful engraftment rate of ovarian, cervical, and uterine cancer was 47%, 64%, and 56%, respectively. The subsequent passages (P2 and P3) showed higher success and faster growth rates than the first passage (P1). Using gynecologic cancer PDX models, the tumor grade is a common clinical factor affecting PDX establishment. We found that the PDX success rate correlated with the patient’s prognosis, and also that ovarian cancer patients with a poor prognosis had a faster PDX growth rate (p < 0.0001). Next, the gene sets associated with inflammation and immune responses were shown in high-ranking successful PDX engraftment through gene set enrichment analysis and RNA sequencing. Up-regulated genes in successful engraftment were found to correlate with ovarian clear cell cancer patient outcomes via Gene Expression Omnibus dataset analysis.

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.

Prognostic value of patient-derived xenograft engraftment in pediatric sarcomas

The goals of this work were to identify factors favoring patient-derived xenograft (PDX) engraftment and study the association between PDX engraftment and prognosis in pediatric patients with Ewing sarcoma, osteosarcoma, and rhabdomyosarcoma. We used immunodeficient mice to establish 30 subcutaneous PDX from patient tumor biopsies, with a successful engraftment rate of 44%. Age greater than 12 years and relapsed disease were patient factors associated with higher engraftment rate. Tumor type and biopsy location did not associate with engraftment. PDX models retained histology markers and most chromosomal aberrations of patient samples during successive passages in mice. Model treatment with irinotecan resulted in significant activity in 20 of the PDXs and replicated the response of rhabdomyosarcoma patients. Successive generations of PDXs responded similarly to irinotecan, demonstrating functional stability of these models. Importantly, out of 68 tumor samples from 51 patients with a median follow-up of 21.2 months, PDX engraftment from newly diagnosed patients was a prognostic factor significantly associated with poor outcome (p = 0.040). This association was not significant for relapsed patients. In the subgroup of patients with newly diagnosed Ewing sarcoma classified as standard risk, we found higher risk of relapse or refractory disease associated with those samples that produced stable PDX models (p = 0.0357). Overall, our study shows that PDX engraftment predicts worse outcome in newly diagnosed pediatric sarcoma patients.

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.

Biliary tract cancer patient-derived xenografts: Surgeon impact on individualized medicine

BACKGROUND & AIMS

Biliary tract tumors are uncommon but highly aggressive malignancies with poor survival outcomes. Due to their low incidence, research into effective therapeutics has been limited. Novel research platforms for pre-clinical studies are desperately needed. We sought to develop a patient-derived biliary tract cancer xenograft catalog.

METHODS

With appropriate consent and approval, surplus malignant tissues were obtained from surgical resection or radiographic biopsy and implanted into immunocompromised mice. Mice were monitored for xenograft growth. Established xenografts were verified by a hepatobiliary pathologist. Xenograft characteristics were correlated with original patient/tumor characteristics and oncologic outcomes. A subset of xenografts were then genomically characterized using Mate Pair sequencing (MPseq).

RESULTS

Between October 2013 and January 2018, 87 patients with histologically confirmed biliary tract carcinomas were enrolled. Of the 87 patients, 47 validated PDX models were successfully generated. The majority of the PDX models were created from surgical resection specimens (n = 44, 94%), which were more likely to successfully engraft when compared to radiologic biopsies (p = 0.03). Histologic recapitulation of original patient tumor morphology was observed in all xenografts. Successful engraftment was an independent predictor for worse recurrence-free survival. MPseq showed genetically diverse tumors with frequent alterations of CDKN2A, SMAD4, NRG1, TP53. Sequencing also identified worse survival in patients with tumors containing tetraploid genomes.

CONCLUSIONS

This is the largest series of biliary tract cancer xenografts reported to date. Histologic and genomic analysis of patient-derived xenografts demonstrates accurate recapitulation of original tumor morphology with direct correlations to patient outcomes. Successful development of biliary cancer tumografts is feasible and may be used to direct subsequent therapy in high recurrence risk patients.

LAY SUMMARY

Patient biliary tract tumors grown in immunocompromised mice are an invaluable resource in the treatment of biliary tract cancers. They can be used to guide individualized cancer treatment in high-risk patients.

Patient-derived xenograft model engraftment predicts poor prognosis after surgery in patients with pancreatic cancer

OBJECTIVES

To establish and evaluate a first generation patient-derived xenograft (PDX) model in nude mice using tumors resected from pancreatic cancer (PC) patients for the identification of key factors that influence xenograft success and prediction of patient prognosis.

METHODS

Primary tumor samples harvested from PC patients who underwent curative resection between May 2016 and April 2018 at our hospital were xenografted into nude mice. Tumor size was evaluated for 2 months. Patients' baseline characteristics and follow-up data were analyzed.

RESULTS

Tumor xenograft models were generated from 67 patients; 30 (44.8%) were successful and 37 (55.2%) failed. Xenograft models could recapitulate the pathology and genetic information of the primary tumors. Univariate analysis identified tumor engraftment, post-operation CA19-9, tumor size, lymph node status, and lymphovascular invasion as significant predictors (P=0.000, 0.023, 0.004, 0.035 and 0.005, respectively) of disease-free survival (DFS). Multivariate Cox regression analysis confirmed tumor engraftment, tumor size and lymphovascular invasion function as independent risk factors for DFS (P=0.000, 0.039 and 0.025, respectively). The hazard ratio of tumor engraftment for DFS was 0.239 (95% confidence interval, 0.109 to 0.524). Kaplan-Meier analysis of DFS indicated an unfavorable outcome in the engraftment group compared to that in the failed engraftment group (6.2 vs. 12.2 months, log rank P=0.000).

CONCLUSION

The pathology and genetic information of primary PC tumors are recapitulated in the PDX tumor model in nude mice. Furthermore, engraftment success is an effective predictor of disease recurrence in patients after surgery.

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.

Establishment of the PDTX model of gynecological tumors

OBJECTIVE

Fresh tumor tissues from patients with gynecological tumors were obtained by surgery or biopsy, and transplanted into NOD-Prkdcem26ll2rgem26Nju (NCG) mice to establish a patient-derived tumor xenograft (PDTX).

MATERIALS AND METHODS

A total of 15 patients with gynecologic tumors were enrolled into the present study. Among these patients, 12 patients had epithelial fallopian tube/ovarian/peritoneal cancer, one patient had metastatic ovarian cancer, and two patients had cervical cancer. Furthermore, among these patients, three patients were treated with puncture or microscopy biopsy, six patients underwent laparoscopic surgery, and six patients underwent robotic surgery. The tumor formation latency, tumor formation rate, tumor volume, tumor invasion and metastasis of the transplanted tumor were observed, the consistency of the PDTX model tumor tissue and patient's primary tumor tissue was compared by pathological H&E staining, and pharmacodynamics testing was performed.

RESULTS

Seven of 15 PDTX models were successfully established, with a success rate of 46.7%. The tumor formation time ranged within 21-130 days, with a median tumor formation time of 73 days. The PDTX model maintained the differentiation, morphological and structural characteristics of tumor cells, and the pharmacodynamic test was completed in five patients.

CONCLUSION

The PDTX model is highly consistent with the pathology of the patient's tumor, and can be used as a substitute for clinical patients to guide the accurate treatment and scientific research of gynecological tumors.

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.

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).

A patient derived xenograft model of cervical cancer and cervical dysplasia

Aim

To develop a patient derived xenograft (PDX) model of cervical cancer and cervical dysplasia using the subrenal capsule.

Methods

Cervical cancer (12 Squamous Cell Carcinoma, 1 Adenocarcinoma, 1 Adenosquamous Carcinoma), 7 cervical dysplasia biopsy and normal cervical tissues were transplanted beneath the renal capsule of immunocompromised NOD/SCID/gamma mice. Resulting tumours were harvested and portions serially transplanted into new recipient mice for up to three in vivo passages. Parent and xenograft tumours were examined by immunohistochemistry for p16^INK41, HPV, and CD-45. Single cell suspensions of mixed mouse and human, or human only cell populations were also transplanted.

Results

The overall engraftment rate for the primary cervical cancer PDX model was 71.4 ±12.5% (n = 14). Tumours maintained morphological, histoarchitecture and immunohistochemical features of the parent tumour, and demonstrated invasiveness into local tissues. Single cell suspensions did not produce tumour growth in this model. Mean length of time (32.4 +/- 3.5 weeks) for the transplanted tissue to generate a tumour in the animal was similar between successive transplantations. Three of four xenografted cervical dysplasia tissues generated microscopic cystic structures resembling dysplastic cervical tissue. Normal cervical tissue (4 of 5 xenografted) also developed microscopic cervical tissue grafts.

Conclusion

The subrenal capsule can be used for a PDX model of human cervical cancer with a good engraftment rate and the ability to model in vivo characteristics of cervical cancer. For the first time we have demonstrated that cervical dysplasia and normal cervical tissue generated microscopic tissues in a PDX model.

Ovarian Cancers: Genetic Abnormalities, Tumor Heterogeneity and Progression, Clonal Evolution and Cancer Stem Cells

Four main histological subtypes of ovarian cancer exist: serous (the most frequent), endometrioid, mucinous and clear cell; in each subtype, low and high grade. The large majority of ovarian cancers are diagnosed as high-grade serous ovarian cancers (HGS-OvCas). TP53 is the most frequently mutated gene in HGS-OvCas; about 50% of these tumors displayed defective homologous recombination due to germline and somatic BRCA mutations, epigenetic inactivation of BRCA and abnormalities of DNA repair genes; somatic copy number alterations are frequent in these tumors and some of them are associated with prognosis; defective NOTCH, RAS/MEK, PI3K and FOXM1 pathway signaling is frequent. Other histological subtypes were characterized by a different mutational spectrum: LGS-OvCas have increased frequency of BRAF and RAS mutations; mucinous cancers have mutation in ARID1A, PIK3CA, PTEN, CTNNB1 and RAS. Intensive research was focused to characterize ovarian cancer stem cells, based on positivity for some markers, including CD133, CD44, CD117, CD24, EpCAM, LY6A, ALDH1. Ovarian cancer cells have an intrinsic plasticity, thus explaining that in a single tumor more than one cell subpopulation, may exhibit tumor-initiating capacity. The improvements in our understanding of the molecular and cellular basis of ovarian cancers should lead to more efficacious treatments.