Transforming treatment paradigms: Focus on personalized medicine for high-grade serous ovarian cancer

Abstract

High-grade serous ovarian cancer (HGSOC) is the most common and aggressive subtype of ovarian cancer, accounting for approximately 70% of all ovarian cancer cases and contributing significantly to the high mortality rates associated with this disease. Because of the asymptomatic nature of early stage disease, most patients are diagnosed at advanced stages when the cancer has already spread into the abdominal cavity, requiring complex and intensive surgical and chemotherapeutic interventions followed by maintenance therapies. Although a minority of cases are associated with well defined genetic syndromes, specific risk factors and a clear etiology in many cases remain elusive. HGSOC tumors are characterized by a high frequency of somatic gene copy number alterations, often associated with defects in homologous recombination repair of DNA. All attempts to introduce an effective screening for HGSOC to date have been unsuccessful. This review elucidates the complexities surrounding HGSOC and encompasses its etiology, epidemiology, classification, pathogenesis, and the current array of treatment strategies. Understanding molecular underpinnings is crucial for the development of targeted therapies and personalized multimodal treatment approaches in centralized therapeutic structures. This review also examines the importance of the tumor microenvironment. In addition, the authors' objective is to underscore the critical importance of placing the patient's perspective and diversity at the forefront of therapeutic strategies, thereby fostering a genuinely participatory decision-making process and ultimately improving patient quality of life.

Keywords: diversity; high‐grade serous ovarian cancer; personalized medicine; quality of life; treatment; tumor microenvironment.

FIGURE 1

Common presenting symptoms of patients with high‐grade serous ovarian cancer. The symptoms and early signs of high‐grade serous ovarian cancer are typically vague and nonspecific, contributing to the challenges in early detection. Common symptoms include abdominal bloating, pelvic pain, early satiety, and urinary urgency or frequency. These symptoms are often mistaken for benign conditions, such as gastrointestinal disorders, leading to diagnostic delayed diagnosis. As the disease progresses, symptoms become more pronounced and may include weight loss, fatigue, postmenopausal bleeding, and changes in bowel habits. Thrombosis, paraneoplastic cerebellar symptoms, or paraneoplastic dermatitis are rare symptoms. The insidious onset of symptoms underscores the importance of raising awareness and promoting early diagnostic initiatives to improve outcomes. Created with Biorender (License No. EL27ZKGY7G).

FIGURE 2

Diversity in gynecologic oncology. This scheme depicts the ultimate need to include underrepresented minorities and to promote diversity. Racial inequities are well known and particularly striking in the gynecologic oncology care continuum. There is a strong need to include racial and ethnic minority groups in clinical trials. We call for a circumscribed interpretation of high‐grade serous ovarian cancer studies, with inadequate representation of the patient pool. Understanding health care disparities in gynecologic oncology is critical for developing effective, personalized therapeutic approaches. Diversity in patients with high‐grade serous ovarian cancer and in gynecologic oncology should be respected and will be a benefit for the scientific community, leading to more robust data for publications based on innovative and creative research generated in an excellent team. Created with Biorender (License No. RD27ZKH4P1).

FIGURE 3

High‐grade serous ovarian cancer origin and development. This scheme depicts the precursor lesions of HGSOC and the invasion of STICs on the ovarian surface in the distal fallopian tube epithelium. Immunophenotypic classification: the T‐cell inflamed or hot category means that T cells infiltrate deposits (islets) of malignant cells and the surrounding and intervening stroma; whereas the noninflamed category, also known as immune‐desert or cold tumors, lack this feature. The excluded classification means that T cells remain confined to the stroma, and there are no deposits of malignant cells. + indicates positive; HGSOC, high‐grade serous ovarian carcinoma; IGF, insulin‐like growth factor; ROS, reactive oxygen species; SCOUT, secretory cell outgrowth; SEE‐FIM, Sectioning and Extensively Examining the FIMbriated End; STICs, serous tubal intraperitoneal carcinomas; TAM, tumor‐associated macrophage. Created with Biorender (License No. MB27ZKHB14).

FIGURE 4

The microenvironment of high‐grade serous ovarian cancer. In the tumor microenvironment, cancer‐associated fibroblasts (CAFs) are particularly important because they support tumor growth and metastasis. Tumor cells with increased DNA damage show signs of inflammation upon sensing DNA damage and the upregulation of stimulator of interferon genes (STING) and tumor‐intrinsic type I interferon signaling pathways. BRCA1/BRCA2 and TP53 gene mutations are common. Several mechanisms contribute to immunosuppression within tumors, including the secretion of IL‐10/IL‐6 with inhibition of the PD‐1 receptor and the immunosuppressive actions of myeloid‐derived suppressor cells (MDSCs), tumor‐associated macrophages (TAMs), or CAFs. CAFs indicates cancer‐associated fibroblasts; DC, dendritic cells; PD1, programmed death 1; PD‐L1, programmed death‐ligand 1; Treg, regulatory T cells. Created in Biorender (License No. VN27ZKHGXA).

FIGURE 5

Algorithm for the diagnosis of histologic types. The scheme shows the diagnostic algorithm based on additional immunohistochemistry examinations. − indicates negative; +, positive; WT, wild type.

FIGURE 6

Patient management. Scheme showing the proposed personalized prehabilitation therapeutic strategy that is combined with an enhanced recovery after surgery (ERAS) to decrease postoperative morbidity. For the prediction of cancer therapy success, patients should be precategorized according to their general status into the following groups: prefrail, frail, and nonfrail.

FIGURE 7

Summary box I. Key points for shared decision‐making during treatment selection in patients with high‐grade squamous ovarian cancer (HGSOC).

FIGURE 8

Summary box II. Key points of maintenance therapy for patients with high‐grade squamous ovarian cancer. HR indicates homologous recombination; HRD, homologous recombination deficiency; PARP, poly(adenosine diphosphate‐ribose) polymerase.

FIGURE 9

Summary box III. Key points of recurrence therapy for patients with high‐grade squamous ovarian cancer. ER, estrogen therapy; ET, endocrine therapy; PARP, poly(adenosine diphosphate‐ribose) polymerase; TMB‐H, high tumor mutational burden.

FIGURE 10

Summary box IV. Key points of a cancer survivorship care plan for patients with high‐grade squamous ovarian cancer. PARP indicates poly(adenosine diphosphate‐ribose) polymerase.