Identifying patients eligible for PARP inhibitor treatment: from NGS-based tests to 3D functional assays

The OVAREX study: Establishment of ex vivo ovarian cancer models to validate innovative therapies and to identify predictive biomarkers

BACKGROUND

Ovarian cancer is the first cause of death from gynecological malignancies mainly due to development of chemoresistance. Despite the emergence of PARP inhibitors, which have revolutionized the therapeutic management of some of these ovarian cancers, the 5-year overall survival rate remains around 45%. Therefore, it is crucial to develop new therapeutic strategies, to identify predictive biomarkers and to predict the response to treatments. In this context, functional assays based on patient-derived tumor models could constitute helpful and relevant tools for identifying efficient therapies or to guide clinical decision making.

METHOD

The OVAREX study is a single-center non-interventional study which aims at investigating the feasibility of establishing in vivo and ex vivo models and testing ex vivo models to predict clinical response of ovarian cancer patients. Patient-Derived Xenografts (PDX) will be established from tumor fragments engrafted subcutaneously into immunocompromised mice. Explants will be generated by slicing tumor tissues and Ascites-Derived Spheroids (ADS) will be isolated following filtration of ascites. Patient-derived tumor organoids (PDTO) will be established after dissociation of tumor tissues or ADS, cell embedding into extracellular matrix and culture in specific medium. Molecular and histological characterizations will be performed to compare tumor of origin and paired models. Response of ex vivo tumor-derived models to conventional chemotherapy and PARP inhibitors will be assessed and compared to results of companion diagnostic test and/or to the patient's response to evaluate their predictive value.

DISCUSSION

This clinical study aims at generating PDX and ex vivo models (PDTO, ADS, and explants) from tumors or ascites of ovarian cancer patients who will undergo surgical procedure or paracentesis. We aim at demonstrating the predictive value of ex vivo models for their potential use in routine clinical practice as part of precision medicine, as well as establishing a collection of relevant ovarian cancer models that will be useful for the evaluation of future innovative therapies.

TRIAL REGISTRATION

The clinical trial has been validated by local research ethic committee on January 25th 2019 and registered at ClinicalTrials.gov with the identifier NCT03831230 on January 28th 2019, last amendment v4 accepted on July 18, 2023.

Integration of pan-omics technologies and three-dimensional in vitro tumor models: an approach toward drug discovery and precision medicine

Despite advancements in treatment protocols, cancer is one of the leading cause of deaths worldwide. Therefore, there is a need to identify newer and personalized therapeutic targets along with screening technologies to combat cancer. With the advent of pan-omics technologies, such as genomics, transcriptomics, proteomics, metabolomics, and lipidomics, the scientific community has witnessed an improved molecular and metabolomic understanding of various diseases, including cancer. In addition, three-dimensional (3-D) disease models have been efficiently utilized for understanding disease pathophysiology and as screening tools in drug discovery. An integrated approach utilizing pan-omics technologies and 3-D in vitro tumor models has led to improved understanding of the intricate network encompassing various signalling pathways and molecular cross-talk in solid tumors. In the present review, we underscore the current trends in omics technologies and highlight their role in understanding genotypic-phenotypic co-relation in cancer with respect to 3-D in vitro tumor models. We further discuss the challenges associated with omics technologies and provide our outlook on the future applications of these technologies in drug discovery and precision medicine for improved management of cancer.

Treatment of Ovarian Cancer Beyond PARP Inhibition: Current and Future Options

Ovarian cancer is the leading cause of gynecological cancer death. Improved understanding of the biologic pathways and introduction of poly (ADP-ribose) polymerase inhibitors (PARPi) during the last decade have changed the treatment landscape. This has improved outcomes, but unfortunately half the women with ovarian cancer still succumb to the disease within 5 years of diagnosis. Pathways of resistance to PARPi and chemotherapy have been studied extensively, but there is an unmet need to overcome treatment failure and improve outcome. Major mechanisms of PARPi resistance include restoration of homologous recombination repair activity, alteration of PARP function, stabilization of the replication fork, drug efflux, and activation of alternate pathways. These resistant mechanisms can be targeted to sensitize the resistant ovarian cancer cells either by rechallenging with PARPi, overcoming resistance mechanism or bypassing resistance pathways. Augmenting the PARPi activity by combining it with other targets in the DNA damage response pathway, antiangiogenic agents and immune checkpoint inhibitors can potentially overcome the resistance mechanisms. Methods to bypass resistance include targeting non-cross-resistant pathways acting independent of homologous recombination repair (HRR), modulating tumour microenvironment, and enhancing drug delivery systems such as antibody drug conjugates. In this review, we will discuss the first-line management of ovarian cancer, resistance mechanisms and potential strategies to overcome these.

Assessment of Homologous Recombination Deficiency in Ovarian Cancer

Accurately assessing homologous recombination deficiency (HRD) to use as a predictive biomarker is an area of intense research in ovarian cancer. Validated assays have demonstrated utility in determining maintenance therapy following platinum sensitive chemotherapy. Novel functional assays promise the potential to reflect HRD in real time and predict response to PARP inhibitors. See related articles by Pikkusaari et al., p. 3110 and Blanc-Durand et al., p. 3124.

Clinical Utility of Genomic Tests Evaluating Homologous Recombination Repair Deficiency (HRD) for Treatment Decisions in Early and Metastatic Breast Cancer

Breast cancer is the most frequently occurring cancer worldwide. With its increasing incidence, it is a major public health problem, with many therapeutic challenges such as precision medicine for personalized treatment. Thanks to next-generation sequencing (NGS), progress in biomedical technologies, and the use of bioinformatics, it is now possible to identify specific molecular alterations in tumor cells-such as homologous recombination deficiencies (HRD)-enabling us to consider using DNA-damaging agents such as platinum salts or PARP inhibitors. Different approaches currently exist to analyze impairment of the homologous recombination pathway, e.g., the search for specific mutations in homologous recombination repair (HRR) genes, such as BRCA1/2; the use of genomic scars or mutational signatures; or the development of functional tests. Nevertheless, the role and value of these different tests in breast cancer treatment decisions remains to be clarified. In this review, we summarize current knowledge on the clinical utility of genomic tests, evaluating HRR deficiency for treatment decisions in early and metastatic breast cancer.

PARPi Decreased Primary Ovarian Cancer Organoid Growth Through Early Apoptosis and Base Excision Repair Pathway

Ovarian cancer (OC), particularly high-grade serous cancer (HGSC), is the leading cause of mortality among gynecological cancers owing to the treatment difficulty and high recurrence probability. As therapeutic drugs approved for OC, poly ADP-ribose polymerase inhibitors (PARPi) lead to synthetic lethality by inhibiting single-strand DNA repair, particularly in homologous recombination-deficient cancers. However, even PARPi have distinct efficacies and are prone to have drug resistance, the molecular mechanisms underlying the PARPi resistance in OC remain unclear. A patient-derived organoid platform was generated and treated with a PARPi to understand the factors associated with PARPi resistance. PARPi significantly inhibits organoid growth. After 72 h of treatment, both the size of organoids and the numbers of adherent cells decreased. Moreover, immunofluorescence results showed that the proportion of Ki67 positive cells significantly reduced. When the PARPi concentration reached 200 nM, the percentage of Ki67+/4',6-diamidino-2-phenylindole (DAPI) cells decreased approximately 50%. PARPi treatment also affected the expression of genes involved in base excision repair and cell cycle. Functional assays revealed that PARPi inhibits cell growth by upregulating early apoptosis. The expression levels of several key genes were validated. In addition to previously reported genes, some promising genes FEN1 and POLA2, were also be founded. The results demonstrate the complex effects of PARPi treatment on changes in potential genes relevant to PARPi resistance, and provide perspectives for further research on the PARPi resistance mechanisms.

A Self-Assembling Peptide as a Model for Detection of Colorectal Cancer

Patient-derived organoid (PDO) models have been widely used in precision medicine. The inability to standardize organoid creation in pre-clinical models has become apparent. The common mouse-derived extracellular matrix can no longer meet the requirements for the establishment of PDO models. Therefore, in order to develop effective methods for 3D cultures of organoids, we designed a self-assembling peptide, namely DRF3, which can be self-assembled into ordered fibrous scaffold structures. Here, we used the co-assembly of self-assembling peptide (SAP) and collagen type I, fibronectin, and laminin (SAP-Matrix) to co-simulate the extracellular matrix, which significantly reduced the culture time of PDO, improved the culture efficiency, and increased the self-assembly ability of cells. Compared with the results from the 2D cell line, the PDO showed a more significant expression of cancer-related genes. During organoid self-assembly, the expression of cancer-related genes is increased. These findings provide a theoretical basis for the establishment of precision molecular modeling platforms in the future.

Predictive biomarkers for molecularly targeted therapies and immunotherapies in breast cancer

Globally, breast cancer is the most common malignancy in women. Substantial efforts have been made to develop novel therapies, including targeted therapies and immunotherapies, for patients with breast cancer who do not respond to standard therapies. Consequently, new targeted therapies, such as cyclin-dependent kinase 4 and 6 inhibitors, poly (ADP-ribose) polymerase inhibitors, phosphoinositide 3-kinase inhibitor, and antibody-drug conjugates targeting human epidermal growth factor receptor 2 or trophoblast cell surface antigen-2, and immune checkpoint inhibitor targeting programmed cell death-1, have been developed and are now in clinical use. However, only some patients have benefited from these novel therapies; therefore, the identification and validation of reliable or more accurate biomarkers for predicting responses to these agents remain a major challenge. This review summarizes the currently available predictive biomarkers for breast cancer and describes recent efforts undertaken to identify potential predictive markers for molecularly targeted therapies and immune checkpoint inhibitors.

Predictive Biomarkers of Response to Neoadjuvant Chemotherapy in Breast Cancer: Current and Future Perspectives for Precision Medicine

Pathological complete response (pCR) after neoadjuvant chemotherapy in patients with early breast cancer is correlated with better survival. Meanwhile, an expanding arsenal of post-neoadjuvant treatment strategies have proven beneficial in the absence of pCR, leading to an increased use of neoadjuvant systemic therapy in patients with early breast cancer and the search for predictive biomarkers of response. The better prediction of response to neoadjuvant chemotherapy could enable the escalation or de-escalation of neoadjuvant treatment strategies, with the ultimate goal of improving the clinical management of early breast cancer. Clinico-pathological prognostic factors are currently used to estimate the potential benefit of neoadjuvant systemic treatment but are not accurate enough to allow for personalized response prediction. Other factors have recently been proposed but are not yet implementable in daily clinical practice or remain of limited utility due to the intertumoral heterogeneity of breast cancer. In this review, we describe the current knowledge about predictive factors for response to neoadjuvant chemotherapy in breast cancer patients and highlight the future perspectives that could lead to the better prediction of response, focusing on the current biomarkers used for clinical decision making and the different gene signatures that have recently been proposed for patient stratification and the prediction of response to therapies. We also discuss the intratumoral phenotypic heterogeneity in breast cancers as well as the emerging techniques and relevant pre-clinical models that could integrate this biological factor currently limiting the reliable prediction of response to neoadjuvant systemic therapy.

Interpatient Heterogeneity in Drug Response and Protein Biomarker Expression of Recurrent Ovarian Cancer

Recurrent ovarian-cancer patients face low 5-year survival rates despite chemotherapy. A variety of guideline-recommended second-line therapies are available, but they frequently result in trial-and-error treatment. Alterations and adjustments are common in the treatment of recurrent ovarian cancer. The drug response of 30 lesions obtained from 22 relapsed ovarian cancer patients to different chemotherapeutic and molecular agents was analyzed with the patient-derived ovarian-cancer spheroid model. The profile of druggable biomarkers was immunohistochemically assessed. The second-line combination therapy of carboplatin with gemcitabine was significantly superior to the combination of carboplatin with PEGylated liposomal doxorubicin (p < 0.0001) or paclitaxel (p = 0.0007). Except for treosulfan, all nonplatinum treatments tested showed a lesser effect on tumor spheroids compared to that of platinum-based therapies. Treosulfan showed the highest efficacy of all nonplatinum agents, with significant advantage over vinorelbine (p < 0.0001) and topotecan (p < 0.0001), the next best agents. The comparative testing of a variety of treatment options in the ovarian-cancer spheroid model resulted in the identification of more effective regimens for 30% of patients compared to guideline-recommended therapies. Recurrent cancers obtained from different patients revealed profound interpatient heterogeneity in the expression pattern of druggable protein biomarkers. In contrast, different lesions obtained from the same patient revealed a similar drug response and biomarker expression profile. Biological heterogeneity observed in recurrent ovarian cancers might explain the strong differences in the clinical drug response of these patients. Preclinical drug testing and biomarker profiling in the ovarian-cancer spheroid model might help in optimizing treatment management for individual patients.

RAD51 as a functional biomarker for homologous recombination deficiency in cancer: a promising addition to the HRD toolbox?

INTRODUCTION

Carcinomas with defects in the homologous recombination (HR) pathway are sensitive to PARP inhibitors (PARPi). A robust method to identify HR-deficient (HRD) carcinomas is therefore of utmost clinical importance. Currently available DNA-based HRD tests either scan HR-related genes such as BRCA1 and BRCA2 for the presence of pathogenic variants or identify HRD-related genomic scars or mutational signatures by using whole-exome or whole-genome sequencing data. As an alternative to DNA-based tests, functional HRD tests have been developed that assess the actual ability of tumors to accumulate RAD51 protein at DNA double strand breaks as a proxy for HR proficiency.

AREAS COVERED

This review presents an overview of currently available HRD tests and discuss the pros and cons of the different methodologies including their sensitivity for the identification of HRD tumors, their concordance with other HRD tests, and their capacity to predict therapy response.

EXPERT OPINION

With the increasing use of PARP inhibitors in the treatment of several cancers there is an urgent need to implement HRD testing in routine clinical practice. To this end, calibration of HRD thresholds and clinical validation of both DNA-based and RAD51-based HRD tests should have top-priority in the coming years.

Targeting DNA Damage Response Pathway in Ovarian Clear Cell Carcinoma

Ovarian clear cell carcinoma (OCCC) is one of the major types of ovarian cancer and is of higher relative prevalence in Asians. It also shows higher possibility of resistance to cisplatin-based chemotherapy leading to poor prognosis. This may be attributed to the relative lack of mutations and aberrations in homologous recombination-associated genes, which are crucial in DNA damage response (DDR), such as BRCA1, BRCA2, p53, RAD51, and genes in the Fanconi anemia pathway. On the other hand, OCCC is characterized by a number of genetic defects rendering it vulnerable to DDR-targeting therapy, which is emerging as a potent treatment strategy for various cancer types. Mutations of ARID1A, PIK3CA, PTEN, and catenin beta 1 (CTNNB1), as well as overexpression of transcription factor hepatocyte nuclear factor-1β (HNF-1β), and microsatellite instability are common in OCCC. Of particular note is the loss-of-function mutations in ARID1A, which is found in approximately 50% of OCCC. ARID1A is crucial for processing of DNA double-strand break (DSB) and for sustaining DNA damage signaling, rendering ARID1A-deficient cells prone to impaired DNA damage checkpoint regulation and hence sensitive to poly ADP ribose polymerase (PARP) inhibitors. However, while preclinical studies have demonstrated the possibility to exploit DDR deficiency in OCCC for therapeutic purpose, progress in clinical application is lagging. In this review, we will recapitulate the preclinical studies supporting the potential of DDR targeting in OCCC treatment, with emphasis on the role of ARID1A in DDR. Companion diagnostic tests (CDx) for predicting susceptibility to PARP inhibitors are rapidly being developed for solid tumors including ovarian cancers and may readily be applicable on OCCC. The potential of various available DDR-targeting drugs for treating OCCC by drawing analogies with other solid tumors sharing similar genetic characteristics with OCCC will also be discussed.