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Ovarian Cancer Immunotherapy and Personalized Medicine.

ABSTRACT: Ovarian cancer response to immunotherapy is limited; however, the evaluation of sensitive/resistant target treatment subpopulations based on stratification by tumor biomarkers may improve the predictiveness of response to immunotherapy. These markers include tumor mutation burden, PD-L1, tumor-infiltrating lymphocytes, homologous recombination deficiency, and neoantigen intratumoral heterogeneity. Future directions in the treatment of ovarian cancer include the utilization of these biomarkers to select ideal candidates. This paper reviews the role of immunotherapy in ovarian cancer as well as novel therapeutics and study designs involving tumor biomarkers that increase the likelihood of success with immunotherapy in ovarian cancer.

SUBMITTER: Morand S

PROVIDER: S-EPMC8234871 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature

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Ovarian Cancer Immunotherapy and Personalized Medicine.

Morand Susan S Devanaboyina Monika M Staats Hannah H Stanbery Laura L Nemunaitis John J

International journal of molecular sciences 20210618 12

Ovarian cancer response to immunotherapy is limited; however, the evaluation of sensitive/resistant target treatment subpopulations based on stratification by tumor biomarkers may improve the predictiveness of response to immunotherapy. These markers include tumor mutation burden, PD-L1, tumor-infiltrating lymphocytes, homologous recombination deficiency, and neoantigen intratumoral heterogeneity. Future directions in the treatment of ovarian cancer include the utilization of these biomarkers to ...[more]

PMID: 34207103

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Project description:BackgroundHigh grade serous ovarian cancer (HGSOC) is among the deadliest human cancers and its prognosis remains extremely poor. Tumor heterogeneity and rapid acquisition of resistance to conventional chemotherapeutic approaches strongly contribute to poor outcome of patients. The clinical landscape of HGSOC has been radically transformed since the advent of targeted therapies in the last decade. Nevertheless, the lack of predictive biomarkers informing on the differential clinical benefit in select subgroups, and allowing patient-centric approaches, currently limits the efficacy of these novel therapies. Thus, rational selection of the best possible treatment for each patient represents a clinical priority in order to improve outcome, while limiting undesirable effects.Main bodyIn this review, we describe the state of the art and the unmet needs in HGSOC management, illustrate the treatment options that are available and the biomarkers that are currently employed to orient clinical decisions. We also describe the ongoing clinical trials that are testing new therapeutic approaches for HGSOC. Next, we introduce the organoid technology as a promising, expanding strategy to study cancer and to develop personalized therapeutic approaches. In particular, we discuss recent studies that have characterized the translational potential of Patient's Derived Organoids (PDOs) to inform on drug sensitivity of HGSOC patients.ConclusionsPDOs can predict the response of patients to treatments and may therefore guide therapeutic decisions. Although preliminary results appear encouraging, organoids still need to be generated and expanded efficiently to enable drug screening in a clinically meaningful time window. A new generation of clinical trials based on the organoid technology should guarantee tailored approaches to ovarian cancer management, as it is now clear that the one-size-fits-all approach cannot lead to efficient and meaningful therapeutic advancements.

Project description:Colorectal cancer (CRC) is a very heterogeneous disease that is caused by the interaction of genetic and environmental factors. CRC develops through a gradual accumulation of genetic and epigenetic changes, leading to the transformation of normal colonic mucosa into invasive cancer. CRC is one of the most prevalent and incident cancers worldwide, as well as one of the most deadly. Approximately 1235108 people are diagnosed annually with CRC, and 609051 die from CRC annually. The World Health Organization estimates an increase of 77% in the number of newly diagnosed cases of CRC and an increase of 80% in deaths from CRC by 2030. The incidence of CRC can benefit from different strategies depending on its stage: health promotion through health education campaigns (when the disease is not yet present), the implementation of screening programs (for detection of the disease in its early stages), and the development of nearly personalized treatments according to both patient characteristics (age, sex) and the cancer itself (gene expression). Although there are different strategies for screening and although the number of such strategies is increasing due to the potential of emerging technologies in molecular marker application, not all strategies meet the criteria required for screening tests in population programs; the three most accepted tests are the fecal occult blood test (FOBT), colonoscopy and sigmoidoscopy. FOBT is the most used method for CRC screening worldwide and is also the primary choice in most population-based screening programs in Europe. Due to its non-invasive nature and low cost, it is one of the most accepted techniques by population. CRC is a very heterogeneous disease, and with a few exceptions (APC, p53, KRAS), most of the genes involved in CRC are observed in a small percentage of cases. The design of genetic and epigenetic marker panels that are able to provide maximum coverage in the diagnosis of colorectal neoplasia seems a reasonable strategy. In recent years, the use of DNA, RNA and protein markers in different biological samples has been explored as strategies for CRC diagnosis. Although there is not yet sufficient evidence to recommend the analysis of biomarkers such as DNA, RNA or proteins in the blood or stool, it is likely that given the quick progression of technology tools in molecular biology, increasingly sensitive and less expensive, these tools will gradually be employed in clinical practice and will likely be developed in mass.

Project description:Ovarian cancer has the highest mortality of all of the gynecological malignancies. There are several distinct histotypes of this malignancy characterized by specific molecular events and clinical behavior. These histotypes have differing responses to platinum-based drugs that have been the mainstay of therapy for ovarian cancer for decades. For histotypes that initially respond to a chemotherapeutic regime of carboplatin and paclitaxel such as high-grade serous ovarian cancer, the development of chemoresistance is common and underpins incurable disease. Recent discoveries have led to the clinical use of PARP (poly ADP ribose polymerase) inhibitors for ovarian cancers defective in homologous recombination repair, as well as the anti-angiogenic bevacizumab. While predictive molecular testing involving identification of a genomic scar and/or the presence of germline or somatic BRCA1 or BRCA2 mutation are in clinical use to inform the likely success of a PARP inhibitor, no similar tests are available to identify women likely to respond to bevacizumab. Functional tests to predict patient response to any drug are, in fact, essentially absent from clinical care. New drugs are needed to treat ovarian cancer. In this review, we discuss applications to address the currently unmet need of developing physiologically relevant in vitro and ex vivo models of ovarian cancer for fundamental discovery science, and personalized medicine approaches. Traditional two-dimensional (2D) in vitro cell culture of ovarian cancer lacks critical cell-to-cell interactions afforded by culture in three-dimensions. Additionally, modelling interactions with the tumor microenvironment, including the surface of organs in the peritoneal cavity that support metastatic growth of ovarian cancer, will improve the power of these models. Being able to reliably grow primary tumoroid cultures of ovarian cancer will improve the ability to recapitulate tumor heterogeneity. Three-dimensional (3D) modelling systems, from cell lines to organoid or tumoroid cultures, represent enhanced starting points from which improved translational outcomes for women with ovarian cancer will emerge.

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Ovarian Cancer Immunotherapy and Personalized Medicine.

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Ovarian Cancer Immunotherapy and Personalized Medicine.

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