Extracellular miRNAs as Predictive Biomarkers for Glypican-3-Derived Peptide Vaccine Therapy Response in Ovarian Clear Cell Carcinoma

Exploration and prognostic analysis of two types of high-risk ovarian cancers: clear cell vs. serous carcinoma: a population-based study

BACKGROUND

Ovarian clear cell carcinoma (OCCC) is a rare pathological histotype in ovarian cancer, while the survival rate of advanced OCCC (Stage III-IV) is substantially lower than that of the advanced serous ovarian cancer (OSC), which is the most common histotype. The goal of this study was to identify high-risk OCCC by comparing OSC and OCCC, with investigating potential risk and prognosis markers.

METHODS

Patients diagnosed with ovarian cancer from 2009 to 2018 were identified from the Surveillance, Epidemiology, and End Results (SEER) Program. Logistic and Cox regression models were used to identify risk and prognostic factors in high-risk OCCC patients. Cancer-specific survival (CSS) and overall survival (OS) were assessed using Kaplan-Meier curves. Furthermore, Cox analysis was employed to build a nomogram model. The performance evaluation results were displayed using the C-index, calibration plots, receiver operating characteristic (ROC) curve, and decision curve analysis (DCA). Immunohistochemically approach was used to identify the expression of the novel target (GPC3).

RESULTS

In the Cox analysis for advanced OCCC, age (45-65 years), tumor numbers (total number of in situ/malignant tumors for patient), T3-stage, bilateral tumors, and liver metastases could be defined as prognostic variables. Nomogram showed good predictive power and clinical practicality. Compared with OSC, liver metastases had a stronger impact on the prognosis of patients with OCCC. T3-stage, positive distant lymph nodes metastases, and lung metastases were risk factors for developing liver metastases. Chemotherapy was an independent prognostic factor for patient with advanced OCCC, but had no effect on CSS in patients with liver metastases (p = 0.0656), while surgery was significantly related with better CSS in these patients (p < 0.0001) (p = 0.0041). GPC3 expression was detected in all tissue sections, and GPC3 staining was predominantly found in the cytoplasm and membranes.

CONCLUSION

Advanced OCCC and OCCC with liver metastases are two types of high-risk OCCC. The constructed nomogram exhibited a satisfactory survival prediction for patients with advanced OCCC. GPC3 immunohistochemistry is expected to accumulate preclinical evidence to support the inclusion of GPC3 in OCCC targeted therapy.

Non-coding RNAs in cancer immunotherapy: Predictive biomarkers and targets

BACKGROUND

To date, standardising clinical predictive biomarkers for assessing the response to immunotherapy remains challenging due to variations in personal genetic signatures, tumour microenvironment complexities and epigenetic onco-mechanisms.

MAIN BODY

Early monitoring of key non-coding RNA (ncRNA) biomarkers may help in predicting the clinical efficacy of cancer immunotherapy and come up with standard predictive ncRNA biomarkers. For instance, reduced miR-125b-5p level in the plasma of non-small cell lung cancer patients treated with anti-PD-1 predicts a positive outcome. The level of miR-153 in the plasma of colorectal cancer patients treated with chimeric antigen receptor T lymphocyte (CAR-T) cell therapy may indicate the activation of T-cell killing activity. miR-148a-3p and miR-375 levels may forecast favourable responses to CAR-T-cell therapy in B-cell acute lymphoblastic leukaemia. In cancer patients treated with the GPC3 peptide vaccine, serum levels of miR-1228-5p, miR-193a-5p and miR-375-3p were reported as predictive biomarkers of good response and improved overall survival. Therefore, there is a critical need for further studies to elaborate on the key ncRNA biomarkers that have the potential to predict early clinical responses to immunotherapy.

CONCLUSION

This review summarises important predictive ncRNA biomarkers that were reported in cancer patients treated with different immunotherapeutic modalities, including monoclonal antibodies, small molecule inhibitors, cancer vaccines and CAR-T cells. In addition, a concise discussion on forthcoming perspectives is provided, outlining technical approaches for the optimal utilisation of immunomodulatory ncRNA biomarkers as predictive tools and therapeutic targets.

Current Understanding on Why Ovarian Cancer Is Resistant to Immune Checkpoint Inhibitors

The standard treatment of ovarian cancer (OC) patients, including debulking surgery and first-line chemotherapy, is unsatisfactory because of recurrent episodes in the majority (~70%) of patients with advanced OC. Clinical trials have shown only a modest (10-15%) response of OC individuals to treatment based on immune checkpoint inhibitors (ICIs). The resistance of OC to therapy is caused by various factors, including OC heterogeneity, low density of tumor-infiltrating lymphocytes (TILs), non-cellular and cellular interactions in the tumor microenvironment (TME), as well as a network of microRNA regulating immune checkpoint pathways. Moreover, ICIs are the most efficient in tumors that are marked by high microsatellite instability and high tumor mutation burden, which is rare among OC patients. The great challenge in ICI implementation is connected with distinguishing hyper-, pseudo-, and real progression of the disease. The understanding of the immunological, molecular, and genetic mechanisms of OC resistance is crucial to selecting the group of OC individuals in whom personalized treatment would be beneficial. In this review, we summarize current knowledge about the selected factors inducing OC resistance and discuss the future directions of ICI-based immunotherapy development for OC patients.

Immunotherapeutic Approaches in Ovarian Cancer

Ovarian cancer (OC) is gynecological cancer, and diagnosis and treatment are continuously advancing. Next-generation sequencing (NGS)-based diagnoses have emerged as novel methods for identifying molecules and pathways in cancer research. The NGS-based applications have expanded in OC research for early detection and identification of aberrant genes and dysregulation pathways, demonstrating comprehensive views of the entire transcriptome, such as fusion genes, genetic mutations, and gene expression profiling. Coinciding with advances in NGS-based diagnosis, treatment strategies for OC, such as molecular targeted therapy and immunotherapy, have also advanced. Immunotherapy is effective against many other cancers, and its efficacy against OC has also been demonstrated at the clinical phase. In this review, we describe several NGS-based applications for therapeutic targets of OC, and introduce current immunotherapeutic strategies, including vaccines, checkpoint inhibitors, and chimeric antigen receptor (CAR)-T cell transplantation, for effective diagnosis and treatment of OC.

Peptides for diagnosis and treatment of ovarian cancer

Ovarian cancer is the most deadly gynecologic malignancy, and its incidence is gradually increasing. Despite improvements after treatment, the results are unsatisfactory and survival rates are relatively low. Therefore, early diagnosis and effective treatment remain two major challenges. Peptides have received significant attention in the search for new diagnostic and therapeutic approaches. Radiolabeled peptides specifically bind to cancer cell surface receptors for diagnostic purposes, while differential peptides in bodily fluids can also be used as new diagnostic markers. In terms of treatment, peptides can exert cytotoxic effects directly or act as ligands for targeted drug delivery. Peptide-based vaccines are an effective approach for tumor immunotherapy and have achieved clinical benefit. In addition, several advantages of peptides, such as specific targeting, low immunogenicity, ease of synthesis and high biosafety, make peptides attractive alternative tools for the diagnosis and treatment of cancer, particularly ovarian cancer. In this review, we focus on the recent research progress regarding peptides in the diagnosis and treatment of ovarian cancer, and their potential applications in the clinical setting.

Extracellular microRNA profiling for prognostic prediction in patients with high-grade serous ovarian carcinoma

High-grade serous ovarian carcinoma is a leading cause of death in female patients worldwide. MicroRNAs (miRNAs) are stable noncoding RNAs in the peripheral blood that reflect a patient's condition, and therefore, they have received substantial attention as noninvasive biomarkers in various diseases. We previously reported the usefulness of serum miRNAs as diagnostic biomarkers. Here, we investigated the prognostic impact of the serum miRNA profile. We used the GSE106817 dataset, which included preoperative miRNA profiles of patients with ovarian malignancies. Excluding patients with other malignancy or insufficient prognostic information, we included 175 patients with high-grade serous ovarian carcinoma. All patients except four underwent surgery and received chemotherapy as initial treatment. The median follow-up period was 54.6 months (range, 3.5-144.1 months). Univariate Cox regression analysis revealed that higher levels of miR-187-5p and miR-6870-5p were associated with both poorer progression-free survival (PFS) and overall survival (OS), and miR-1908-5p, miR-6727-5p, and miR-6850-5p were poor prognostic indicators of PFS. The OS and PFS prognostic indices were then calculated using the expression values of three prognostic miRNAs. Multivariate Cox regression analysis showed that both indices were significantly independent poor prognostic factors (hazard ratio for OS and PFS, 2.343 [P = .015] and 2.357 [P = .005], respectively). In conclusion, circulating miRNA profiles can potentially provide information to predict the prognosis of patients with high-grade serous ovarian carcinoma. Therefore, there is a strong demand for early clinical application of circulating miRNAs as noninvasive biomarkers.

MicroRNAs: immune modulators in cancer immunotherapy

MicroRNA (miRNA) is a class of endogenous small non-coding RNA of 18–25 nucleotides and plays regulatory roles in both physiological and pathological processes. Emerging evidence support that miRNAs function as immune modulators in tumors. MiRNAs as tumor suppressors or oncogenes are also found to be able to modulate anti-tumor immunity or link the crosstalk between tumor cells and immune cells surrounding. Based on the specific regulating function, miRNAs can be used as predictive, prognostic biomarkers, and therapeutic targets in immunotherapy. Here, we review new findings about the role of miRNAs in modulating immune responses, as well as discuss mechanisms underlying their dysregulation, and their clinical potentials as indicators of tumor prognosis or to sensitize cancer immunotherapy.