Platinum-resistant ovarian cancer: From drug resistance mechanisms to liquid biopsy-based biomarkers for disease management

Deciphering the Molecular Mechanisms behind Drug Resistance in Ovarian Cancer to Unlock Efficient Treatment Options

Ovarian cancer is a highly lethal form of gynecological cancer. This disease often goes undetected until advanced stages, resulting in high morbidity and mortality rates. Unfortunately, many patients experience relapse and succumb to the disease due to the emergence of drug resistance that significantly limits the effectiveness of currently available oncological treatments. Here, we discuss the molecular mechanisms responsible for resistance to carboplatin, paclitaxel, polyadenosine diphosphate ribose polymerase inhibitors, and bevacizumab in ovarian cancer. We present a detailed analysis of the most extensively investigated resistance mechanisms, including drug inactivation, drug target alterations, enhanced drug efflux pumps, increased DNA damage repair capacity, and reduced drug absorption/accumulation. The in-depth understanding of the molecular mechanisms associated with drug resistance is crucial to unveil new biomarkers capable of predicting and monitoring the kinetics during disease progression and discovering new therapeutic targets.

Spotlight on New Hallmarks of Drug-Resistance towards Personalized Care for Epithelial Ovarian Cancer

Epithelial ovarian cancer (EOC) is the deadliest gynecological malignancy worldwide. Despite the latest advances, a major clinical issue in EOC is the disappointing prognosis related to chemoresistance in almost one-third of cases. Drug resistance relies on heterogeneous cancer stem cells (CSCs), endowed with tumor-initiating potential, leading to relapse. No biomarkers of chemoresistance have been validated yet. Recently, major signaling pathways, micro ribonucleic acids (miRNAs), and circulating tumor cells (CTCs) have been advocated as putative biomarkers and potential therapeutic targets for drug resistance. However, further investigation is mandatory before their routine implementation. In accordance with the increasing rate of therapeutic efforts in EOC, the need for biomarker-driven personalized therapies is growing. This review aims to discuss the emerging hallmarks of drug resistance with an in-depth insight into the underlying molecular mechanisms lacking so far. Finally, a glimpse of novel therapeutic avenues and future challenges will be provided.

Current trends and emerging patterns in the application of nanomaterials for ovarian cancer research: a bibliometric analysis

Introduction: Ovarian cancer remains to be a significant cause of global cancer-related mortality. In recent years, there has been a surge of studies in investigating the application of nanomaterials in the diagnosis and treatment of ovarian cancer. This study aims to conduct a comprehensive bibliometric analysis regarding nanomaterial-based researches on ovarian cancer to evaluate the current state and emerging patterns in this field. Methods: A thorough literature search on the Web of Science Core Collection database was conducted to identify articles focused on nanomaterial-based ovarian cancer researches. The studies that met the inclusion criteria were selected for further analysis. VOSviewer and CiteSpace were applied for the bibliometric and visual analyses of the selected publications. Results: A total of 2,426 studies were included in this study. The number of annual publications showed a consistent upward trend from 2003 to 2023. Notably, China, the United States, and India have emerged as the leading contributors in this field, accounting for 37.39%, 34.04%, and 5.69% of the publications, respectively. The Chinese Academy of Sciences and Anil K. Sood were identified as the most influential institution and author, respectively. Furthermore, the International Journal of Nanomedicine was the most frequently cited journal. In terms of the research focus, significant attention has been directed towards nanomaterial-related drug delivery, while the exploration of immunogenic cell death and metal-organic frameworks represented recent areas of interest. Conclusion: Through comprehensive analyses, an overview of current research trends and emerging areas of interest regarding the application of nanomaterials in ovarian cancer was illustrated. These findings offered valuable insights into the status and future directions of this dynamic field.

5-Hydroxymethylcytosine signals in serum are a predictor of chemoresistance in high-grade serous ovarian cancer

OBJECTIVE

The genome-wide profiling of 5-hydroxymethylcytosines (5hmC) on circulating cell-free DNA (cfDNA) has revealed promising biomarkers for various diseases. The purpose of this study was to investigate 5hmC signals in serum cfDNA and identify novel predictive biomarkers for the development of chemoresistance in high-grade serous ovarian cancer (HGSOC). We hypothesized that 5hmC profiles in cfDNA reflect the development of chemoresistance and elucidate pathways that may drive chemoresistance in HGSOC. Moreover, we sought to identify predictors that would better stratify outcomes for women with intermediate-sensitive HGSOC.

METHODS

Women diagnosed with HGSOC and known platinum sensitivity status were selected for this study. Nano-hmC-Seal was performed on cfDNA isolated from archived serum samples, and differential 5hmC features were identified using DESeq2 to establish a model predictive of chemoresistance.

RESULTS

A multivariate model consisting of three features (preoperative CA-125, largest residual implant after surgery, 5hmC level of OSGEPL), stratified samples from intermediate sensitive, chemo-naive women diagnosed with HGSOC into chemotherapy-resistant- and sensitive-like strata with a significant difference in overall survival (OS). Independent analysis of The Cancer Genome Atlas data further confirmed that high OSGEPL1 expression is a favorable prognostic factor for HGSOC.

CONCLUSIONS

We have developed a novel multivariate model based on clinico-pathologic data and a cfDNA-derived 5hmC modified gene, OSGEPL1, that predicted response to platinum-based chemotherapy in intermediate-sensitive HGSOC. Our multivariate model applies to chemo-naïve samples regardless if the patint was treated with adjuvant or neoadjuvant chemotherapy. These results merit further investigation of the predictive capability of our model in larger cohorts.

Current Applications and Challenges of Next-Generation Sequencing in Plasma Circulating Tumour DNA of Ovarian Cancer

Circulating tumour DNA (ctDNA) facilitates longitudinal study of the tumour genome, which, unlike tumour tissue biopsies, globally reflects intratumor and intermetastatis heterogeneity. Despite its costs, next-generation sequencing (NGS) has revolutionised the study of ctDNA, ensuring a more comprehensive and multimodal approach, increasing data collection, and introducing new variables that can be correlated with clinical outcomes. Current NGS strategies can comprise a tumour-informed set of genes or the entire genome and detect a tumour fraction as low as 10-5. Despite some conflicting studies, there is evidence that ctDNA levels can predict the worse outcomes of ovarian cancer (OC) in both early and advanced disease. Changes in those levels can also be informative regarding treatment efficacy and tumour recurrence, capable of outperforming CA-125, currently the only universally utilised plasma biomarker in high-grade serous OC (HGSOC). Qualitative evaluation of sequencing shows that increasing copy number alterations and gene variants during treatment may correlate with a worse prognosis in HGSOC. However, following tumour clonality and emerging variants during treatment poses a more unique opportunity to define treatment response, select patients based on their emerging resistance mechanisms, like BRCA secondary mutations, and discover potential targetable variants. Sequencing of tumour biopsies and ctDNA is not always concordant, likely as a result of clonal heterogeneity, which is better captured in the plasma samples than it is in a large number of biopsies. These incoherences may reflect tumour clonality and reveal the acquired alterations that cause treatment resistance. Cell-free DNA methylation profiles can be used to distinguish OC from healthy individuals, and NGS methylation panels have been shown to have excellent diagnostic capabilities. Also, methylation signatures showed promise in explaining treatment responses, including BRCA dysfunction. ctDNA is evolving as a promising new biomarker to track tumour evolution and clonality through the treatment of early and advanced ovarian cancer, with potential applicability in prognostic prediction and treatment selection. While its role in HGSOC paves the way to clinical applicability, its potential interest in other histological subtypes of OC remains unknown.

Combined radiomics-clinical model to predict platinum-sensitivity in advanced high-grade serous ovarian carcinoma using multimodal MRI

Introduction

We aimed to predict platinum sensitivity using routine baseline multimodal magnetic resonance imaging (MRI) and established clinical data in a radiomics framework.

Methods

We evaluated 96 patients with ovarian cancer who underwent multimodal MRI and routine laboratory tests between January 2016 and December 2020. The patients underwent diffusion-weighted, contrast-enhanced T1-weighted, and T2-weighted MRI. Subsequently, 293 radiomic features were extracted by manually identifying tumor regions of interest. The features were subjected to the least absolute shrinkage and selection operators, leaving only a few selected features. We built the first prediction model with a tree-based classifier using selected radiomics features. A second prediction model was built by combining the selected radiomic features with four established clinical factors: age, disease stage, initial tumor marker level, and treatment course. Both models were built and tested using a five-fold cross-validation.

Results

Our radiomics model predicted platinum sensitivity with an AUC of 0.65 using a few radiomics features related to heterogeneity. The second combined model had an AUC of 0.77, confirming the incremental benefits of the radiomics model in addition to models using established clinical factors.

Conclusion

Our combined radiomics-clinical data model was effective in predicting platinum sensitivity in patients with advanced ovarian cancer.

Machine learning-derived identification of prognostic signature for improving prognosis and drug response in patients with ovarian cancer

Clinical assessments relying on pathology classification demonstrate limited effectiveness in predicting clinical outcomes and providing optimal treatment for patients with ovarian cancer (OV). Consequently, there is an urgent requirement for an ideal biomarker to facilitate precision medicine. To address this issue, we selected 15 multicentre cohorts, comprising 12 OV cohorts and 3 immunotherapy cohorts. Initially, we identified a set of robust prognostic risk genes using data from the 12 OV cohorts. Subsequently, we employed a consensus cluster analysis to identify distinct clusters based on the expression profiles of the risk genes. Finally, a machine learning-derived prognostic signature (MLDPS) was developed based on differentially expressed genes and univariate Cox regression genes between the clusters by using 10 machine-learning algorithms (101 combinations). Patients with high MLDPS had unfavourable survival rates and have good prediction performance in all cohorts and in-house cohorts. The MLDPS exhibited robust and dramatically superior capability than 21 published signatures. Of note, low MLDIS have a positive prognostic impact on patients treated with anti-PD-1 immunotherapy by driving changes in the level of infiltration of immune cells. Additionally, patients suffering from OV with low MLDIS were more sensitive to immunotherapy. Meanwhile, patients with low MLDIS might benefit from chemotherapy, and 19 compounds that may be potential agents for patients with low MLDIS were identified. MLDIS presents an appealing instrument for the identification of patients at high/low risk. This could enhance the precision treatment, ultimately guiding the clinical management of OV.

Roles of TRPM7 in ovarian cancer

Ovarian cancer stands as the prevailing gynecologic malignancy, afflicting over 313,959 individuals annually worldwide, accompanied by more than 207,252 fatalities. Perturbations in calcium signaling contribute significantly to the pathogenesis of numerous cancers, including ovarian cancer, wherein alterations in calcium transporter expression have been reported. Overexpression of TRPM7, a prominent calcium transporter, has been linked to adverse prognostic outcomes in various cancer types. The focus of this comprehensive review centers around delineating the oncogenic role of TRPM7 in cancer development and exploring its therapeutic potential as a target in combating this disease. Notably, TRPM7 fosters cancer invasion, metastasis, and uncontrolled cell proliferation, thereby perpetuating the expansion and reinforcement of these malignant entities. Furthermore, this review takes ovarian cancer as an example and summarizes the "dual-mode" regulatory role of TRPM7 in cancer. Within the domain of ovarian cancer, TRPM7 assumes the role of a harsh tyrant, firmly controlling the calcium ion signaling pathway and metabolic reprogramming pathways.

HLF promotes ovarian cancer progression and chemoresistance via regulating Hippo signaling pathway

Hepatic leukemia factor (HLF) is aberrantly expressed in human malignancies. However, the role of HLF in the regulation of ovarian cancer (OC) remains unknown. Herein, we reported that HLF expression was upregulated in OC tissues and ovarian cancer stem cells (CSCs). Functional studies have revealed that HLF regulates OC cell stemness, proliferation, and metastasis. Mechanistically, HLF transcriptionally activated Yes-associated protein 1 (YAP1) expression and subsequently modulated the Hippo signaling pathway. Moreover, we found that miR-520e directly targeted HLF 3'-UTR in OC cells. miR-520e expression was negatively correlated with HLF and YAP1 expression in OC tissues. The combined immunohistochemical (IHC) panels exhibited a better prognostic value for OC patients than any of these components alone. Importantly, the HLF/YAP1 axis determines the response of OC cells to carboplatin treatment and HLF depletion or the YAP1 inhibitor verteporfin abrogated carboplatin resistance. Analysis of patient-derived xenografts (PDXs) further suggested that HLF might predict carboplatin benefits in OC patients. In conclusion, these findings suggest a crucial role of the miR-520e/HLF/YAP1 axis in OC progression and chemoresistance, suggesting potential therapeutic targets for OC.

Angiotensin-converting enzyme inhibitors for ovarian cancer? - a new adjuvant option or a silent trap

Background

Ovarian cancer is a huge therapeutic and financial problem for which approved treatments have already achieved their limit of efficiency. A cost-effective strategy to extend therapeutic options in this malignancy is drug repurposing aimed at overcoming chemoresistance. Here, angiotensin-converting enzyme inhibitors (ACE-I) are worth considering.

Materials and methods

We searched literature for publications supporting the idea of adjuvant application of ACE-Is in ovarian malignancy. Then, we searched The Cancer Genome Atlas databases for relevant alternations of gene expression patterns. We also performed in silico structure-activity relationship evaluation for predicting ACE-Is' cytotoxicity against ovarian cancer cell lines. Finally, we reviewed the potential obstacles in ACE-Is repurposing process.

Results

The alternation of angiotensin receptor expression in ovarian cancer translates into poorer patient survival. This confirms the participation of the renin-angiotensin system in ovarian carcinogenesis. In observational studies, ACE-Is were shown synergize with both, platinum-based chemotherapy as well as with antiangiogenic therapy. Consistently, our in silico simulation showed that ACE-Is are probably cytotoxic against ovarian cancer cells. However, the publications on their chemopreventive properties were inconclusive. In addition, some reports correlated ACE-Is use with increased general cancer incidence. We hypothesized that this effect could be associated with mutagenic nitrosamine formation in ACE-Is' pharmaceutical formulations, as was the case with angiotensin receptor blockers (ARBs) and other well-established pharmaceuticals.

Conclusions

Available data warrant further research into repositioning ACE-Is to ovarian cancer as chemosensitizers. Prior to this, however, a special research program is needed to detect possible genotoxic contaminants of ACE-Is.

Liquid biopsy in ovarian cancer: advantages and limitations for prognosis and diagnosis

Ovarian cancer (OC) is a highly fatal gynecologic malignancy, often diagnosed at an advanced stage which presents significant challenges for disease management. The clinical application of conventional tissue biopsy methods and serological biomarkers has limitations for the diagnosis and prognosis of OC patients. Liquid biopsy is a novel sampling method that involves analyzing distinctive tumor elements secreted into the peripheral blood. Growing evidence suggests that liquid biopsy methods such as circulating tumor cells, cell-free RNA, circulating tumor DNA, exosomes, and tumor-educated platelets may improve early prognosis and diagnosis of OC, leading to enhanced therapeutic management of the disease. This study reviewed the evidence demonstrating the utility of liquid biopsy components in OC prognosis and diagnosis, and evaluated the current advantages and limitations of these methods. Additionally, the existing obstacles and crucial topics for future studies utilizing liquid biopsy in OC patients were discussed.

Pegylated liposomal doxorubicin for relapsed epithelial ovarian cancer

BACKGROUND

Cancer of ovarian, fallopian tube and peritoneal origin, referred to collectively as ovarian cancer, is the eighth most common cancer in women and is often diagnosed at an advanced stage. Women with relapsed epithelial ovarian cancer (EOC) are less well and have a limited life expectancy, therefore maintaining quality of life with effective symptom control is an important aim of treatment. However, the unwanted effects of chemotherapy agents may be severe, and optimal treatment regimens are unclear. Pegylated liposomal doxorubicin (PLD), which contains a cytotoxic drug called doxorubicin hydrochloride, is one of several treatment modalities that may be considered for treatment of relapsed EOCs. This is an update of the original Cochrane Review which was published in Issue 7, 2013.

OBJECTIVES

To evaluate the efficacy and safety of PLD, with or without other anti-cancer drugs, in women with relapsed high grade epithelial ovarian cancer (EOC).

SEARCH METHODS

We searched CENTRAL, MEDLINE (via Ovid) and Embase (via Ovid) from 1990 to January 2022. We also searched online registers of clinical trials, abstracts of scientific meetings and reference lists of included studies.

SELECTION CRITERIA

We included randomised controlled trials (RCTs) that evaluated PLD in women diagnosed with relapsed epithelial ovarian cancer.

DATA COLLECTION AND ANALYSIS

Two review authors independently extracted data to a pre-designed data collection form and assessed the risk of bias according to the Cochrane Handbook for Systematic Reviews of Interventions guidelines. Where possible, we pooled collected data in meta-analyses.

MAIN RESULTS

This is an update of a previous review with 12 additional studies, so this updated review includes a total of 26 RCTs with 8277 participants that evaluated the effects of PLD alone or in combination with other drugs in recurrent EOC: seven in platinum-sensitive disease (2872 participants); 11 in platinum-resistant disease (3246 participants); and eight that recruited individuals regardless of platinum sensitivity status (2079 participants). The certainty of the evidence was assessed for the three most clinically relevant comparisons out of eight comparisons identified in the included RCTs. Recurrent platinum-sensitive EOC PLD with conventional chemotherapy agent compared to alternative combination chemotherapy likely results in little to no difference in overall survival (OS) (hazard ratio (HR) 0.93, 95% confidence interval (CI) 0.83 to 1.04; 5 studies, 2006 participants; moderate-certainty evidence) but likely increases progression-free survival (PFS) (HR 0.81, 95% CI 0.74 to 0.89; 5 studies, 2006 participants; moderate-certainty evidence). The combination may slightly improve quality of life at three months post-randomisation, measured using European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire C30 (mean difference 4.80, 95% CI 0.92 to 8.68; 1 study, 608 participants; low-certainty evidence), but this may not represent a clinically meaningful difference. PLD in combination with another chemotherapy agent compared to alternative combination chemotherapy likely results in little to no difference in the rate of overall severe adverse events (grade ≥ 3) (risk ratio (RR) 1.11, 95% CI 0.95 to 1.30; 2 studies, 834 participants; moderate-certainty evidence). PLD with chemotherapy likely increases anaemia (grade ≥ 3) (RR 1.37, 95% CI 1.02 to 1.85; 5 studies, 1961 participants; moderate-certainty evidence). The evidence is very uncertain about the effect of PLD with conventional chemotherapy on hand-foot syndrome (HFS)(grade ≥ 3) (RR 4.01, 95% CI 1.00 to 16.01; 2 studies, 1028 participants; very low-certainty evidence) and neurological events (grade ≥ 3) (RR 0.38, 95% CI 0.20 to 0.74; 4 studies, 1900 participants; very low-certainty evidence). Recurrent platinum-resistant EOC PLD alone compared to another conventional chemotherapy likely results in little to no difference in OS (HR 0.96, 95% CI 0.77 to 1.19; 6 studies, 1995 participants; moderate-certainty evidence). The evidence is very uncertain about the effect of PLD on PFS (HR 0.94, 95% CI 0.85 to 1.04; 4 studies, 1803 participants; very low-certainty evidence), overall severe adverse events (grade ≥ 3) (RR ranged from 0.61 to 0.97; 2 studies, 964 participants; very low-certainty evidence), anaemia (grade ≥ 3) (RR ranged from 0.19 to 0.82; 5 studies, 1968 participants; very low-certainty evidence), HFS (grade ≥ 3) (RR ranged from 15.19 to 109.15; 6 studies, 2184 participants; very low-certainty evidence), and the rate of neurological events (grade ≥ 3)(RR ranged from 0.08 to 3.09; 3 studies, 1222 participants; very low-certainty evidence). PLD with conventional chemotherapy compared to PLD alone likely results in little to no difference in OS (HR 0.92, 95% CI 0.70 to 1.21; 1 study, 242 participants; moderate-certainty evidence) and it may result in little to no difference in PFS (HR 0.94, 95% CI 0.73 to 1.22; 2 studies, 353 participants; low-certainty evidence). The combination likely increases overall severe adverse events (grade ≥ 3) (RR 2.48, 95% CI 1.98 to 3.09; 1 study, 663 participants; moderate-certainty evidence) and anaemia (grade ≥ 3) (RR 2.38, 95% CI 1.46 to 3.87; 2 studies, 785 participants; moderate-certainty evidence), but likely results in a large reduction in HFS (grade ≥ 3) (RR 0.24, 95% CI 0.14 to 0.40; 2 studies, 785 participants; moderate-certainty evidence). It may result in little to no difference in neurological events (grade ≥ 3) (RR 1.40, 95% CI 0.85 to 2.31; 1 study, 663 participants; low-certainty evidence).

AUTHORS' CONCLUSIONS

In platinum-sensitive relapsed EOC, including PLD in a combination chemotherapy regimen probably makes little to no difference in OS compared to other combinations, but likely improves PFS. Choice of chemotherapy will therefore be guided by symptoms from previous chemotherapy and other patient considerations. Single-agent PLD remains a useful agent for platinum-resistant relapsed EOC and choice of agent at relapse will depend on patient factors, e.g. degree of bone marrow suppression or neurotoxicity from previous treatments. Adding another agent to PLD likely increases overall grade ≥ 3 adverse events with little to no improvement in survival outcomes. The limited evidence relating to PLD in combination with other agents in platinum-resistant relapsed EOC does not indicate a benefit, but there is some evidence of increased side effects.

The evolving role of DNA damage response in overcoming therapeutic resistance in ovarian cancer

Epithelial ovarian cancer (EOC) is treated in the first-line setting with combined platinum and taxane chemotherapy, often followed by a maintenance poly (ADP-ribose) polymerase inhibitor (PARPi). Responses to first-line treatment are frequent. For many patients, however, responses are suboptimal or short-lived. Over the last several years, multiple new classes of agents targeting DNA damage response (DDR) mechanisms have advanced through clinical development. In this review, we explore the preclinical rationale for the use of ATR inhibitors, CHK1 inhibitors, and WEE1 inhibitors, emphasizing their application to chemotherapy-resistant and PARPi-resistant ovarian cancer. We also present an overview of the clinical development of the leading drugs in each of these classes, emphasizing the rationale for monotherapy and combination therapy approaches.

Bibliometric and visualized analysis of drug resistance in ovarian cancer from 2013 to 2022

Objective

As one of the cancers that seriously threatens women's health, ovarian cancer has a high morbidity and mortality rate. Surgery and chemotherapy are the basic treatment strategies for ovarian cancer, and chemotherapy resistance is a significant factor in affecting the prognosis, survival cycle, and recurrence of ovarian cancer. This article aims to analyze articles about ovarian cancer and drug resistance via bibliometric software, offering new ideas and directions for researchers in this field.

Methods

Both Citespace and Vosviewer are bibliometric software on the Java platform. Articles were collected on ovarian cancer and drug resistance in the Web of Science Core Collection database from 2013 to 2022. The countries, institutions, journals, authors, keywords, and references were analyzed, and the development status of this field was indicated from multiple perspectives.

Results

Studies on ovarian cancer and drug resistance generally showed an increasing trend from 2013 to 2022. The People's Republic of China and Chinese institutions contributed more to this field. Gynecologic Oncology published the most articles, and the journal with the most citations was Cancer Research. Li Li was the author with the most publications, and Siegel RL was the author with the most citations. Through burst detection, it can be found that the research hotspots in this field mainly focused on the in-depth exploration of the drug resistance mechanism of ovarian cancer and the progress of PARP inhibitors and bevacizumab in the treatment of ovarian cancer.

Conclusions

Many studies on the mechanism of drug resistance in ovarian cancer have been discovered; however, the deeper mechanism remains to be explored. Compared with traditional chemotherapy drugs, PARP inhibitors and bevacizumab have shown better efficacy, but PARP inhibitors have initially shown drug resistance. The future direction of this field should be to overcome the resistance of existing drugs and actively develop new ones.

Label-Free Quantification Mass Spectrometry Identifies Protein Markers of Chemotherapy Response in High-Grade Serous Ovarian Cancer

Eighty percent of ovarian cancer patients initially respond to chemotherapy, but the majority eventually experience a relapse and die from the disease with acquired chemoresistance. In addition, 20% of patients do not respond to treatment at all, as their disease is intrinsically chemotherapy resistant. Data-independent acquisition nano-flow liquid chromatography-mass spectrometry (DIA LC-MS) identified the three protein markers: gelsolin (GSN), calmodulin (CALM1), and thioredoxin (TXN), to be elevated in high-grade serous ovarian cancer (HGSOC) tissues from patients that responded to chemotherapy compared to those who did not; the differential expression of the three protein markers was confirmed by immunohistochemistry. Analysis of the online GENT2 database showed that mRNA levels of GSN, CALM1, and TXN were decreased in HGSOC compared to fallopian tube epithelium. Elevated levels of GSN and TXN mRNA expression correlated with increased overall and progression-free survival, respectively, in a Kaplan-Meier analysis of a large online repository of HGSOC patient data. Importantly, differential expression of the three protein markers was further confirmed when comparing parental OVCAR-5 cells to carboplatin-resistant OVCAR-5 cells using DIA LC-MS analysis. Our findings suggest that GSN, CALM1, and TXN may be useful biomarkers for predicting chemotherapy response and understanding the mechanisms of chemotherapy resistance. Proteomic data are available via ProteomeXchange with identifier PXD033785.

Multiparameter single-cell proteomic technologies give new insights into the biology of ovarian tumors

High-grade serous ovarian cancer (HGSOC) is the most lethal gynecological malignancy. Its diagnosis at advanced stage compounded with its excessive genomic and cellular heterogeneity make curative treatment challenging. Two critical therapeutic challenges to overcome are carboplatin resistance and lack of response to immunotherapy. Carboplatin resistance results from diverse cell autonomous mechanisms which operate in different combinations within and across tumors. The lack of response to immunotherapy is highly likely to be related to an immunosuppressive HGSOC tumor microenvironment which overrides any clinical benefit. Results from a number of studies, mainly using transcriptomics, indicate that the immune tumor microenvironment (iTME) plays a role in carboplatin response. However, in patients receiving treatment, the exact mechanistic details are unclear. During the past decade, multiplex single-cell proteomic technologies have come to the forefront of biomedical research. Mass cytometry or cytometry by time-of-flight, measures up to 60 parameters in single cells that are in suspension. Multiplex cellular imaging technologies allow simultaneous measurement of up to 60 proteins in single cells with spatial resolution and interrogation of cell-cell interactions. This review suggests that functional interplay between cell autonomous responses to carboplatin and the HGSOC immune tumor microenvironment could be clarified through the application of multiplex single-cell proteomic technologies. We conclude that for better clinical care, multiplex single-cell proteomic technologies could be an integral component of multimodal biomarker development that also includes genomics and radiomics. Collection of matched samples from patients before and on treatment will be critical to the success of these efforts.

Turning Adversity into Strength and Transferring It to the Uninitiated: The Tricks Cancer Cells Play to Survive Hypoxic Stress and Fight Chemotherapy

Despite significant progress during the past few decades, cancer remains the second most common cause of death in the US after heart disease [...].

The application of circulating tumor cell and cell-free DNA liquid biopsies in ovarian cancer

Ovarian cancer is the deadliest gynecological cancer. 70% of the cases are diagnosed at late stages with already developed metastases due to the absence of easily noticeable symptoms. Early-stage ovarian cancer has a good prognosis with a 5-year survival rate reaching 95%, hence the identification of effective biomarkers for early diagnosis is important. Advances in liquid biopsy-based methods can have a significant impact not just on the development of an efficient screening strategy, but also in clinical decision-making with additional molecular profiling and genetic alterations linked to therapy resistance. Despite the well-known advantages of liquid biopsy, there are still challenges that need to be addressed before its routine use in clinical practice. Various liquid biopsy-based biomarkers have been investigated in ovarian cancer; however, in this review, we are concentrating on the current use of cell-free DNA (cfDNA) and circulating tumor cells (CTCs) in disease management, focusing on their emerging importance in clinical practice. We also discuss the technical aspects of these workflows. The analysis of cfDNA is often chosen for the detection of mutations, copy number aberrations, and DNA methylation changes, whereas CTC analysis provides a unique opportunity to study whole cells, thus allowing DNA, RNA, and protein-based molecular profiling as well as in vivo studies. Combined solutions which merge the strengths of cfDNA and CTC approaches should be developed to maximize the potential of liquid biopsy technology.

Folate receptor genes were up-regulated in epithelial ovarian cancer and partly associated with patients’ prognosis

Objective

The present work aimed to investigate folate receptor (FOLR1, FOLR2, FOLR3) expression, functional enrichment, signaling pathway and prognosis in ovarian cancer patients by integrated bioinformatics analysis.

Methods

Folate receptor (FOLR1, FOLR2, and FOLR3) mRNA expression level between epithelial ovarian cancer and corresponding normal ovarian tissue of cancer patients was compared through the TCGA database by GEPIA online analysis tool. The protein–protein interaction (PPI) network of FOLR1, FOLR2, FOLR3, and related genes were constructed through the STRING database. GO and KEGG enrichment of FOLR1, FOLR2, FOLR3, and relevant genes were analyzed. Overall survival (OS) and progression-free survival (PFS) between FOLR1, FOLR2, and FOLR3 mRNA high and low expression epithelial ovarian cancer patients were compared by log-rank test.

Results

FOLR and FOLR3 mRNA expression in epithelial ovarian cancer tissue were significantly higher than that of corresponding normal ovarian tissue of cancer patients (P < 0.05) The PPI network showed 53 nodes and 298 edges with the average node degree of 11.2. The local clustering coefficient was 0.744, which indicated that the protein–protein enrichment was statistically significant (P < 1.0 × 10−16). Folate receptor (FOLR1, FOLR2, and FOLR3) and relevant genes were mainly enriched in folic acid transport, methotrexate transmembrane transporter activity, antifolate resistance for biological process, molecular function, and KEGG pathway, respectively. The PFS of FOLR1 and FOLR3 high expression epithelial ovarian cancer patients was significantly lower compared to low-expression subjects with statistical significance [hazard ratio (HRFOLR1) = 1.26, 95% confidence interval (CI): 1.09–1.45, P < 0.05, HRFOLR3 = 1.22, 95% CI: 1.06–1.40, P < 0.05]. However, the OS was not statistically different between FOLR1, FOLR2, and FOLR3 low and high expression groups.

Conclusion

Folate receptor (FOLR1, FOLR2, and FOLR3) genes were up-regulated in epithelial ovarian cancer and partly associated with patient’s poor prognosis.

The Long Non-Coding RNA SNHG12 as a Mediator of Carboplatin Resistance in Ovarian Cancer via Epigenetic Mechanisms

Simple Summary

Epithelial ovarian cancer is a lethal malignancy in which recurrence and therapy resistance are the major causes of death. We investigated the transcriptome and DNA methylation profile of ovarian cancer cell lines sensitive and resistant to carboplatin, aiming to identify genes associated with therapy resistance. We focused on long non-coding RNAs (lncRNAs), known as epigenetic regulators of several cellular and biological processes. We found 11 lncRNAs associated with carboplatin resistance, including SNHG12 (small nucleolar RNA host gene 12), also confirmed in an external dataset (The Cancer Genome Atlas). SNHG12 gene silencing increased the sensitivity to carboplatin, giving evidence that this lncRNA contributes to resistance to carboplatin in ovarian cancer cell lines. We also demonstrated that SNHG12 could control the expression of nearby genes probably by altering epigenetic markers and modifying the transcript levels.

Abstract

Genetic and epigenetic changes contribute to intratumor heterogeneity and chemotherapy resistance in several tumor types. LncRNAs have been implicated, directly or indirectly, in the epigenetic regulation of gene expression. We investigated lncRNAs that potentially mediate carboplatin-resistance of cell subpopulations, influencing the progression of ovarian cancer (OC). Four carboplatin-sensitive OC cell lines (IGROV1, OVCAR3, OVCAR4, and OVCAR5), their derivative resistant cells, and two inherently carboplatin-resistant cell lines (OVCAR8 and Ovc316) were subjected to RNA sequencing and global DNA methylation analysis. Integrative and cross-validation analyses were performed using external (The Cancer Genome Atlas, TCGA dataset, n = 111 OC samples) and internal datasets (n = 39 OC samples) to identify lncRNA candidates. A total of 4255 differentially expressed genes (DEGs) and 14529 differentially methylated CpG positions (DMPs) were identified comparing sensitive and resistant OC cell lines. The comparison of DEGs between OC cell lines and TCGA-OC dataset revealed 570 genes, including 50 lncRNAs, associated with carboplatin resistance. Eleven lncRNAs showed DMPs, including the SNHG12. Knockdown of SNHG12 in Ovc316 and OVCAR8 cells increased their sensitivity to carboplatin. The results suggest that the lncRNA SNHG12 contributes to carboplatin resistance in OC and is a potential therapeutic target. We demonstrated that SNHG12 is functionally related to epigenetic mechanisms.

Establish of an Initial Platinum-Resistance Predictor in High-Grade Serous Ovarian Cancer Patients Regardless of Homologous Recombination Deficiency Status

Backgrounds

Ovarian cancer (OC) is still the leading aggressive and lethal disease of gynecological cancers, and platinum-based regimes are the standard treatments. However, nearly 20%–30% of patients with OC are initial platinum resistant (IPR), and there is a lack of valid tools to predict whether they will be primary platinum resistant or not prior to chemotherapy.

Methods

Transcriptome data from The Cancer Genome Atlas (TCGA) was downloaded as the training data, and transcriptome data of GSE15622, GSE102073, GSE19829, and GSE26712 were retrieved from Gene Expression Omnibus (GEO) as the validation cohorts. Differentially expressed genes (DEGs) were selected between platinum-sensitive and platinum-resistant patients from the training cohort, and multiple machine-learning algorithms [including random forest, XGboost, and least absolute shrinkage and selection operator (LASSO) regression] were utilized to determine the candidate genes from DEGs. Then, we applied logistic regression to establish the IPR signature based on the expression. Finally, comprehensive clinical, genomic, and survival feature were analyzed to understand the application value of the established IPR signature.

Results

A total of 532 DEGs were identified between platinum-resistant and platinum-sensitive samples, and 11 of them were shared by these three-machine learning algorithms and utilized to construct an IPR prediction signature. The area under receiver operating characteristic curve (AUC) was 0.841 and 0.796 in the training and validation cohorts, respectively. Notably, the prediction capacity of this signature was stable and robust regardless of the patients’ homologous recombination deficiency (HRD) and mutation burden status. Meanwhile, the genomic feature was concordant between samples with high- or low-IPR signature, except a significantly higher prevalence of gain at Chr19q.12 (regions including CCNE1) in the high-IPR signature samples. The efficacy of prediction of platinum resistance of IPR signature successfully transferred to the precise survival prediction, with the AUC of 0.71, 0.72, and 0.66 to predict 1-, 3-, and 5-year survival, respectively. At last, we found a significantly different tumor-infiltrated lymphocytes feature, including lower abundance of CD4+ naive T cells in the samples with high-IPR signature. A relatively lower tumor immune dysfunction and exclusion (TIDE) value and more sensitivity to multiple therapies including Gefitinib may suggest the potency to transfer from platinum-based therapy to immunotherapy or target therapies in patients with high-IPR signature.

Conclusion

Our study established an IPR signature based on the expression of 11 genes that could stably and robustly distinguish OC patients with IPR and/or poor outcomes, which may guide therapeutic regimes tailoring.

Emerging role of m6A methylation modification in ovarian cancer

m6A (N6-methyladenosine) methylation, a well-known modification in tumour epigenetics, dynamically and reversibly fine tunes the entire process of RNA metabolism. Aberrant levels of m6A and its regulators, which can predict the survival and outcomes of cancer patients, are involved in tumorigenesis, metastasis and resistance. Ovarian cancer (OC) ranks first among gynaecological tumours in the causes of death. At first diagnosis, patients with OC are usually at advanced stages owing to a lack of early biomarkers and effective targets. After treatment, patients with OC often develop drug resistance. This article reviews the recent experimental advances in understanding the role of m6A modification in OC, raising the possibility to treat m6A modification and its regulators as promising diagnostic markers and therapeutic targets for OC.

Sestrin2-Mediated Autophagy Contributes to Drug Resistance via Endoplasmic Reticulum Stress in Human Osteosarcoma

One contributor to the high mortality of osteosarcoma is its reduced sensitivity to chemotherapy, but the mechanism involved is unclear. Improving the sensitivity of osteosarcoma to chemotherapy is urgently needed to improve patient survival. We found that chemotherapy triggered apoptosis of human osteosarcoma cells in vitro and in vivo; this was accompanied by increased Sestrin2 expression. Importantly, autophagy was also enhanced with increased Sestrin2 expression. Based on this observation, we explored the potential role of Sestrin2 in autophagy of osteosarcoma. We found that Sestrin2 inhibited osteosarcoma cell apoptosis by promoting autophagy via inhibition of endoplasmic reticulum stress, and this process is closely related to the PERK-eIF2α-CHOP pathway. In addition, our study showed that low Sestrin2 expression can effectively reduce autophagy of human osteosarcoma cells after chemotherapy, increase p-mTOR expression, decrease Bcl-2 expression, promote osteosarcoma cell apoptosis, and slow down tumour progression in NU/NU mice. Sestrin2 activates autophagy by inhibiting mTOR via the PERK-eIF2α-CHOP pathway and inhibits apoptosis via Bcl-2. Therefore, our results explain one underlying mechanism of increasing the sensitivity of osteosarcoma to chemotherapy and suggest that Sestrin2 is a promising gene target.