Prediction of resistance to chemotherapy in ovarian cancer: a systematic review

TMEM158, as plasma cfRNA marker, promotes proliferation and doxorubicin resistance in ovarian cancer

The current study aimed to identify the potential biomarker for the diagnosis of ovarian cancer within plasma cell-free RNA (cfRNA) species and to characterize their oncogenic properties. cfRNAs were isolated from the peripheral blood of ovarian cancer patients and sequenced using an NGS platform. Principal component analysis (PCA) was performed using Salmon software. Gene ontology (GO) analysis was conducted with clusterProfiler. The relative abundance of TMEM158 transcripts was determined by real-time PCR. Cell viability and proliferation was monitored using the MTT and cell counting assays, respectively. The protein levels of TMEM158 and ABCG2 were quantified by immunoblotting. We observed a clear separation of cfRNAs between ovarian cancer patients and healthy individuals. Additionally, we identified TMEM158 as the most significantly differential gene in both peripheral blood and tumor tissues. Overexpression of TMEM158 stimulated cell viability and promoted cell proliferation in ovarian cancer cells. Notably, the aberrant upregulation of TMEM158 was closely associated with doxorubicin resistance in ovarian cancer. Mechanistically, we demonstrated that TMEM158 positively regulates ABCG2 expression, which consequently contributes to drug resistance. In summary, we identified cfRNA TMEM158 as a potential diagnostic biomarker for ovarian cancer and elucidated the critical involvement of TMEM158-ABCG2 signaling axis in the development of doxorubicin resistance.

Identification of genes predicting chemoresistance and short survival in ovarian cancer

Background

Ovarian cancer (OC) is a kind of lethiferous cancer in gynecology, and the development of chemoresistance is the brief reason for treatment failure. The genes which contribute to chemoresistance are often leading to short survival. Thus, this study aims to identify predictive markers for chemoresistance and survival from chemoresistant-related genes.

Methods

Coremine was used to retrieve of genes linked to OC chemoresistance. The relationship of genes with patient survival was analyzed in 489 OC patients of The Cancer Genome Atlas (TCGA) cohort, which the subgroup of 90 resistant and 197 sensitive samples was used to determine gene expression. Kaplan-Meier (KM) plotter of 1,816 OC patients with survival data was retrieved for survival analysis. Survival analysis was carried out by the R survival package in R (version 3.3.1). KM and receiver operating characteristic (ROC) curve were respectively used to access the ability of a gene to predict survival and chemoresistance.

Results

In this study, a group of genes potentially linked to OC chemoresistance was identified, which dysregulated in 90 chemoresistant tissues compared with 197 sensitive tissues. Of them, thirteen genes could predict chemoresistance in 1,347 patients, especially SOS1, MSH6, STAT5A were excellent for predicting chemoresistance to any drugs, platin and taxane, CASP2 and PARD6B for any drugs and platin, and HSP90AA1 and HSP90B1 for taxane. Meanwhile, 44 genes linked to OC chemoresistance could predict short overall survival (OS) and/or disease-free survival (DFS) in 489 OC patients, and 10 of them could predict short OS in large cohort of up to 1,657 patients. Finally, it is noteworthy that CASP2 was down-regulated in 90 chemoresistant samples, and low expression of the gene predicted chemoresistance in 1,347 patients, short OS and DFS in 489 patients, and short OS and progression-free survival (PFS) in 1,657 patients.

Conclusions

The identified genes specifically the CASP2 might be potentially used as predictive marker, prognostic marker and therapeutic target in management of OC.

Comprehensive analysis of hub genes associated with cisplatin-resistance in ovarian cancer and screening of therapeutic drugs through bioinformatics and experimental validation

BACKGROUND

To identify key genes associated with cisplatin resistance in ovarian cancer, a comprehensive analysis was conducted on three datasets from the GEO database and through experimental validation.

METHODS

Gene expression profiles were retrieved from the GEO database. DEGs were identified by comparing gene expression profiles between cisplatin-sensitive and resistant ovarian cancer cell lines. The identified genes were further subjected to GO, KEGG, and PPI network analysis. Potential inhibitors of key genes were identified through methods such as LibDock nuclear molecular docking. In vitro assays and RT-qPCR were performed to assess the expression levels of key genes in ovarian cancer cell lines. The sensitivity of cells to chemotherapy and proliferation of key gene knockout cells were evaluated through CCK8 and Clonogenic assays.

RESULTS

Results showed that 12 genes influenced the chemosensitivity of the ovarian cancer cell line SKOV3, and 9 genes were associated with the prognosis and survival outcomes of ovarian cancer patients. RT-qPCR results revealed NDRG1, CYBRD1, MT2A, CNIH3, DPYSL3, and CARMIL1 were upregulated, whereas ERBB4, ANK3, B2M, LRRTM4, EYA4, and SLIT2 were downregulated in cisplatin-resistant cell lines. NDRG1, CYBRD1, and DPYSL3 knock-down significantly inhibited the proliferation of cisplatin-resistant cell line SKOV3. Finally, photofrin, a small-molecule compound targeting CYBRD1, was identified.

CONCLUSION

This study reveals changes in the expression level of some genes associated with cisplatin-resistant ovarian cancer. In addition, a new small molecule compound was identified for the treatment of cisplatin-resistant ovarian cancer.

Potential drug repurposing of ruxolitinib to inhibit the JAK/STAT pathway for the treatment of patients with epithelial ovarian cancer

AIM

This review aimed to describe the potential for therapeutic targeting of the JAK/STAT signaling pathway by repurposing the clinically-approved JAK inhibitor ruxolitinib in the patients with epithelial ovarian cancer (OC) setting.

METHODS

We reviewed publications that focus on the inhibition of the JAK/STAT pathway in hematological and solid malignancies including OC.

RESULTS

Preclinical studies showed that ruxolitinib effectively reduces OC cell viability and metastasis and enhances the anti-tumor activity of chemotherapy drugs. There are a number of recent clinical trials exploring the role of JAK/STAT inhibition in solid cancers including OC. Early results have not adequately supported efficacy in solid tumors. However, there are preclinical data and clinical studies supporting the use of ruxolitinib in combination with both chemotherapy and other targeted drugs in OC setting.

CONCLUSION

Inflammatory conditions and persistent activation of the JAK/STAT pathway are associated with tumourigenesis and chemoresistance, and therapeutic blockade of this pathway shows promising results. For women with OC, clinical investigation exploring the role of ruxolitinib in combination with chemotherapy agents or other targeted therapeutics is warranted.

A chemotherapy response prediction model derived from tumor-promoting B and Tregs and proinflammatory macrophages in HGSOC

Background

Most patients with high-grade serous ovarian cancer (HGSOC) experienced disease recurrence with cumulative chemoresistance, leading to treatment failure. However, few biomarkers are currently available in clinical practice that can accurately predict chemotherapy response. The tumor immune microenvironment is critical for cancer development, and its transcriptomic profile may be associated with treatment response and differential outcomes. The aim of this study was to develop a new predictive signature for chemotherapy in patients with HGSOC.

Methods

Two HGSOC single-cell RNA sequencing datasets from patients receiving chemotherapy were reinvestigated. The subtypes of endoplasmic reticulum stress-related XBP1+ B cells, invasive metastasis-related ACTB+ Tregs, and proinflammatory-related macrophage subtypes with good predictive power and associated with chemotherapy response were identified. These results were verified in an independent HGSOC bulk RNA-seq dataset for chemotherapy. Further validation in clinical cohorts used quantitative real-time PCR (qRT-PCR).

Results

By combining cluster-specific genes for the aforementioned cell subtypes, we constructed a chemotherapy response prediction model containing 43 signature genes that achieved an area under the receiver operator curve (AUC) of 0.97 (p = 2.1e-07) for the GSE156699 cohort (88 samples). A huge improvement was achieved compared to existing prediction models with a maximum AUC of 0.74. In addition, its predictive capability was validated in multiple independent bulk RNA-seq datasets. The qRT-PCR results demonstrate that the expression of the six genes has the highest diagnostic value, consistent with the trend observed in the analysis of public data.

Conclusions

The developed chemotherapy response prediction model can be used as a valuable clinical decision tool to guide chemotherapy in HGSOC patients.

E26 transformation-specific transcription variant 5 in development and cancer: modification, regulation and function

E26 transformation-specific (ETS) transcription variant 5 (ETV5), also known as ETS-related molecule (ERM), exerts versatile functions in normal physiological processes, including branching morphogenesis, neural system development, fertility, embryonic development, immune regulation, and cell metabolism. In addition, ETV5 is repeatedly found to be overexpressed in multiple malignant tumors, where it is involved in cancer progression as an oncogenic transcription factor. Its roles in cancer metastasis, proliferation, oxidative stress response and drug resistance indicate that it is a potential prognostic biomarker, as well as a therapeutic target for cancer treatment. Post-translational modifications, gene fusion events, sophisticated cellular signaling crosstalk and non-coding RNAs contribute to the dysregulation and abnormal activities of ETV5. However, few studies to date systematically summarized the role and molecular mechanisms of ETV5 in benign diseases and in oncogenic progression. In this review, we specify the molecular structure and post-translational modifications of ETV5. In addition, its critical roles in benign and malignant diseases are summarized to draw a panorama for specialists and clinicians. The updated molecular mechanisms of ETV5 in cancer biology and tumor progression are delineated. Finally, we prospect the further direction of ETV5 research in oncology and its potential translational applications in the clinic.

Ovarian high-grade serous carcinoma cells with low SMARCA4 expression and high SMARCA2 expression contribute to platinum resistance

Platinum resistance is a major obstacle to the treatment of ovarian cancer and is correlated with poor clinical outcomes. Intratumor heterogeneity plays a key role in chemoresistance. Recent studies have emphasized the contributions of genetic and epigenetic factors to the development of intratumor heterogeneity. Although the clinical significance of multi-subunit chromatin remodeler, switch/sucrose nonfermenting (SWI/SNF) complexes in cancers has been reported, the impacts of SWI/SNF-related, matrix-associated, actin-dependent regulator of chromatin, subfamily A, member 4/subfamily A, member 2 (SMARCA4/A2) expression patterns in human cancer tissues have not been fully elucidated. Here, we show that low expression of SMARCA4 and high expression of SMARCA2 are associated with platinum resistance in ovarian high-grade serous carcinoma (HGSC) cells. We used fluorescence multiplex immunohistochemistry (fmIHC) to study resected specimens; we examined heterogeneity in human HGSC tissues at the single-cell level, which revealed that the proportion of cells with the SMARCA4^low /SMARCA2^high phenotype was positively correlated with clinical platinum-resistant recurrence. We used stable transfection of SMARCA2 and siRNA knockdown of SMARCA4 to generate HGSC cells with the SMARCA4^low /SMARCA2^high phenotype; these cells had the greatest resistance to carboplatin. Bioinformatics analyses revealed that the underlying mechanism involved in substantial alterations to chromatin accessibility and resultant fibroblast growth factor (FGF) signaling activation, MAPK pathway activation, BCL2 overexpression, and reduced carboplatin-induced apoptosis; these were confirmed by in vitro functional experiments. Furthermore, in vivo experiments in an animal model demonstrated that combination therapy with carboplatin and a fibroblast growth factor receptor (FGFR) inhibitor promoted cell death in HGSC xenografts. Taken together, these observations reveal a specific subpopulation of HGSC cells that is associated with clinical chemoresistance, which may lead to the establishment of a histopathological prediction system for carboplatin response. Our findings may facilitate the development of novel therapeutic strategies for platinum-resistant HGSC cells. © 2023 The Pathological Society of Great Britain and Ireland.

Predicting chemoresponsiveness in epithelial ovarian cancer patients using circulating small extracellular vesicle-derived plasma gelsolin

BACKGROUND

Resistance to chemotherapy continues to be a challenge when treating epithelial ovarian cancer (EOC), contributing to low patient survival rates. While CA125, the conventional EOC biomarker, has been useful in monitoring patients' response to therapy, there are no biomarkers used to predict treatment response prior to chemotherapy. Previous work in vitro showed that plasma gelsolin (pGSN) is highly expressed in chemoresistant EOC cell lines, where it is secreted in small extracellular vesicles (sEVs). Whether sEVs from tumour cells are secreted into the circulation of EOC patients and could be used to predict patient chemoresponsiveness is yet to be determined. This study aims to identify if sEV-pGSN in the circulation could be a predictive biomarker for chemoresistance in EOC.

METHODS

Sandwich ELISA was used to measure pGSN concentrations from plasma samples of 96 EOC patients (primarily high grade serous EOC). sEVs were isolated using ExoQuick ULTRA and characterized using western blot, nanoparticle tracking analysis, and electron microscopy after which pGSN was measured from the sEVs. Patients were stratified as platinum sensitive or resistant groups based on first progression free interval (PFI) of 6 or 12 months.

RESULTS

Total circulating pGSN was significantly decreased and sEV-pGSN increased in patients with a PFI ≤ 12 months (chemoresistant) compared to those with a PFI > 12 months (chemosensitive). The ratio of total pGSN to sEV-pGSN further differentiated these groups and was a strong predictive marker for chemoresistance (sensitivity: 73.91%, specificity: 72.46%). Predetermined CA125 was not different between chemosensitive and chemoresistant groups and was not predictive of chemoresponsiveness prior to treatment. When CA125 was combined with the ratio of total pGSN/sEV-pGSN, it was a significant predictor of chemoresponsiveness, but the test performance was not as robust as the total pGSN/sEV-pGSN alone.

CONCLUSIONS

Total pGSN/sEV-pGSN was the best predictor of chemoresponsiveness prior to treatment, outperforming the individual biomarkers (CA125, total pGSN, and sEV-pGSN). This multianalyte predictor of chemoresponsiveness could help to inform physicians' treatment and follow up plan at the time of EOC diagnosis, thus improving patients' outcomes.

CRAC and SK Channels: Their Molecular Mechanisms Associated with Cancer Cell Development

Cancer represents a major health burden worldwide. Several molecular targets have been discovered alongside treatments with positive clinical outcomes. However, the reoccurrence of cancer due to therapy resistance remains the primary cause of mortality. Endeavors in pinpointing new markers as molecular targets in cancer therapy are highly desired. The significance of the co-regulation of Ca2+-permeating and Ca2+-regulated ion channels in cancer cell development, proliferation, and migration make them promising molecular targets in cancer therapy. In particular, the co-regulation of the Orai1 and SK3 channels has been well-studied in breast and colon cancer cells, where it finally leads to an invasion-metastasis cascade. Nevertheless, many questions remain unanswered, such as which key molecular components determine and regulate their interplay. To provide a solid foundation for a better understanding of this ion channel co-regulation in cancer, we first shed light on the physiological role of Ca2+ and how this ion is linked to carcinogenesis. Then, we highlight the structure/function relationship of Orai1 and SK3, both individually and in concert, their role in the development of different types of cancer, and aspects that are not yet known in this context.

Gene co-expression network analysis revealed novel biomarkers for ovarian cancer

Ovarian cancer is the second most common gynecologic cancer and remains the leading cause of death of all gynecologic oncologic disease. Therefore, understanding the molecular mechanisms underlying the disease, and the identification of effective and predictive biomarkers are invaluable for the development of diagnostic and treatment strategies. In the present study, a differential co-expression network analysis was performed via meta-analysis of three transcriptome datasets of serous ovarian adenocarcinoma to identify novel candidate biomarker signatures, i.e. genes and miRNAs. We identified 439 common differentially expressed genes (DEGs), and reconstructed differential co-expression networks using common DEGs and considering two conditions, i.e. healthy ovarian surface epithelia samples and serous ovarian adenocarcinoma epithelia samples. The modular analyses of the constructed networks indicated a co-expressed gene module consisting of 17 genes. A total of 11 biomarker candidates were determined through receiver operating characteristic (ROC) curves of gene expression of module genes, and miRNAs targeting these genes were identified. As a result, six genes (CDT1, CNIH4, CRLS1, LIMCH1, POC1A, and SNX13), and two miRNAs (mir-147a, and mir-103a-3p) were suggested as novel candidate prognostic biomarkers for ovarian cancer. Further experimental and clinical validation of the proposed biomarkers could help future development of potential diagnostic and therapeutic innovations in ovarian cancer.

A Pair of Prognostic Biomarkers in Triple-Negative Breast Cancer: KLK10 and KLK11 mRNA Expression

Triple-negative breast cancer (TNBC) is an aggressive breast cancer subtype with poor patient prognosis and limited therapeutic options. A lack of prognostic biomarkers and therapeutic targets fuels the need for new approaches to tackle this severe disease. Extracellular matrix degradation, release, and modulation of the activity of growth factors/cytokines/chemokines, and the initiation of signaling pathways by extracellular proteolytic networks, have been identified as major processes in the carcinogenesis of breast cancer. Members of the kallikrein-related peptidase (KLK) family contribute to these tumor-relevant processes, and are associated with breast cancer progression and metastasis. In this study, the clinical relevance of mRNA expression of two members of this family, KLK10 and KLK11, has been evaluated in TNBC. For this, their expression levels were quantified in tumor tissue of a large, well-characterized patient cohort (n = 123) via qPCR. Although, in general, the overall expression of both factors are lower in tumor tissue of breast cancer patients (encompassing all subtypes) compared to normal tissue of healthy donors, in the TNBC subtype, expression is even increased. In our cohort, a significant, positive correlation between the expression levels of both KLKs was detected, indicating a coordinate expression mode of these proteases. Elevated KLK10 and KLK11 mRNA levels were associated with poor patient prognosis. Moreover, both factors were found to be independent of other established clinical factors such as age, lymph node status, or residual tumor mass, as determined by multivariable Cox regression analysis. Thus, both proteases, KLK10 and KLK11, may represent unfavorable prognostic factors for TNBC patients and, furthermore, appear as promising potential targets for therapy in TNBC.

The impact of neoadjuvant chemotherapy on the tumor microenvironment in advanced high-grade serous carcinoma

High-grade serous ovarian, fallopian tube or peritoneal carcinoma is an aggressive subtype of ovarian cancer that frequently develops resistance to chemotherapy. It remains contested whether the resistance is caused by the acquisition of novel molecular aberrations or alternatively through the selection of rare pre-existing tumor clones. To address this question, we applied single-cell RNA sequencing to depict the tumor landscape of 6 samples from a single case of advanced high-grade serous fallopian tube carcinoma during neoadjuvant chemotherapy (NACT). We analyzed a total of 32,079 single cells, with 17,249 cells derived from the pre-NACT multisite tumor tissue samples and 14,830 cells derived from the post-NACT multisite tumor tissue samples. We identified the diverse properties of the tumor, immune and stromal cell types between the pre-NACT and post-NACT tumors. The malignant epithelial cells displayed a high degree of intratumor heterogeneity in response to NACT. We showed that the primary resistant clone (clone 63) epithelial genotype was already present in the pre-NACT tumors, and was adaptively enriched after NACT. This clone 63 was correlated with a poor clinical prognosis. Furthermore, single-cell analysis of CD4⁺ T cells demonstrated that IL2RAhi-CCL22+-Tregs were selectively enriched in post-NACT tumors. Interestingly, this Treg subtype could recruit and enrich themselves through secreting the CCL22-CCR1 combination in pre-NACT and post-NACT tumors, and further express CD274 to suppress other CD4 and CD8 T cells through a CD274-PDCD1 axis in the post-NACT tumors, and this predicted an immunosuppressive state after NACT. Overall, our results provide important evidence for the adaptive resistance theory of HGSC, and for the potential development of therapeutic strategies to treat HGSC and improve the survival of patients with HGSC.

Variational Bayes for high-dimensional proportional hazards models with applications within gene expression

MOTIVATION

Few Bayesian methods for analyzing high-dimensional sparse survival data provide scalable variable selection, effect estimation and uncertainty quantification. Such methods often either sacrifice uncertainty quantification by computing maximum a posteriori estimates, or quantify the uncertainty at high (unscalable) computational expense.

RESULTS

We bridge this gap and develop an interpretable and scalable Bayesian proportional hazards model for prediction and variable selection, referred to as sparse variational Bayes. Our method, based on a mean-field variational approximation, overcomes the high computational cost of Markov chain Monte Carlo, whilst retaining useful features, providing a posterior distribution for the parameters and offering a natural mechanism for variable selection via posterior inclusion probabilities. The performance of our proposed method is assessed via extensive simulations and compared against other state-of-the-art Bayesian variable selection methods, demonstrating comparable or better performance. Finally, we demonstrate how the proposed method can be used for variable selection on two transcriptomic datasets with censored survival outcomes, and how the uncertainty quantification offered by our method can be used to provide an interpretable assessment of patient risk.

AVAILABILITY AND IMPLEMENTATION

our method has been implemented as a freely available R package survival.svb (https://github.com/mkomod/survival.svb).

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Can Schlafen 11 Help to Stratify Ovarian Cancer Patients Treated with DNA-Damaging Agents?

Platinum-based chemotherapy has been the cornerstone of systemic treatment in ovarian cancer. Since no validated molecular predictive markers have been identified yet, the response to platinum-based chemotherapy has been evaluated clinically, based on platinum-free interval. The new promising marker Schlafen 11 seems to correlate with sensitivity or resistance to DNA-damaging agents, including platinum compounds or PARP inhibitors in various types of cancer. We provide background information about the function of Schlafen 11, its evaluation in tumor tissue, and its prevalence in ovarian cancer. We discuss the current evidence of the correlation of Schlafen 11 expression in ovarian cancer with treatment outcomes and the potential use of Schlafen 11 as the key predictive and prognostic marker that could help to better stratify ovarian cancer patients treated with platinum-based chemotherapy or PARP inhibitors. We also provide perspectives on future directions in the research on this promising marker.

Novel MicroRNA-Regulated Transcript Networks Are Associated with Chemotherapy Response in Ovarian Cancer

High-grade serous ovarian cancer (HGSOC) is a highly lethal gynecologic cancer, in part due to resistance to platinum-based chemotherapy reported among 20% of patients. This study aims to generate novel hypotheses of the biological mechanisms underlying chemotherapy resistance, which remain poorly understood. Differential expression analyses of mRNA- and microRNA-sequencing data from HGSOC patients of The Cancer Genome Atlas identified 21 microRNAs associated with angiogenesis and 196 mRNAs enriched for adaptive immunity and translation. Coexpression network analysis identified three microRNA networks associated with chemotherapy response enriched for lipoprotein transport and oncogenic pathways, as well as two mRNA networks enriched for ubiquitination and lipid metabolism. These network modules were replicated in two independent ovarian cancer cohorts. Moreover, integrative analyses of the mRNA/microRNA sequencing and single-nucleotide polymorphisms (SNPs) revealed potential regulation of significant mRNA transcripts by microRNAs and SNPs (expression quantitative trait loci). Thus, we report novel transcriptional networks and biological pathways associated with resistance to platinum-based chemotherapy in HGSOC patients. These results expand our understanding of the effector networks and regulators of chemotherapy response, which will help to improve the management of ovarian cancer.

Transcriptional epigenetic regulation of Fkbp1/Pax9 genes is associated with impaired sensitivity to platinum treatment in ovarian cancer

Background

In an effort to contribute to overcoming the platinum resistance exhibited by most solid tumors, we performed an array of epigenetic approaches, integrating next-generation methodologies and public clinical data to identify new potential epi-biomarkers in ovarian cancer, which is considered the most devastating of gynecological malignancies.

Methods

We cross-analyzed data from methylome assessments and restoration of gene expression through microarray expression in a panel of four paired cisplatin-sensitive/cisplatin-resistant ovarian cancer cell lines, along with publicly available clinical data from selected individuals representing the state of chemoresistance. We validated the methylation state and expression levels of candidate genes in each cellular phenotype through Sanger sequencing and reverse transcription polymerase chain reaction, respectively. We tested the biological role of selected targets using an ectopic expression plasmid assay in the sensitive/resistant tumor cell lines, assessing the cell viability in the transfected groups. Epigenetic features were also assessed in 189 primary samples obtained from ovarian tumors and controls.

Results

We identified PAX9 and FKBP1B as potential candidate genes, which exhibited epigenetic patterns of expression regulation in the experimental approach. Re-establishment of FKBP1B expression in the resistant OVCAR3 phenotype in which this gene is hypermethylated and inhibited allowed it to achieve a degree of platinum sensitivity similar to the sensitive phenotype. The evaluation of these genes at a translational level revealed that PAX9 hypermethylation leads to a poorer prognosis in terms of overall survival. We also set a precedent for establishing a common epigenetic signature in which the validation of a single candidate, MEST, proved the accuracy of our computational pipelines.

Conclusions

Epigenetic regulation of PAX9 and FKBP1B genes shows that methylation in non-promoter areas has the potential to control gene expression and thus biological consequences, such as the loss of platinum sensitivity. At the translational level, PAX9 behaves as a predictor of chemotherapy response to platinum in patients with ovarian cancer. This study revealed the importance of the transcript-specific study of each gene under potential epigenetic regulation, which would favor the identification of new markers capable of predicting each patient’s progression and therapeutic response.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13148-021-01149-8.

A novel homeostatic loop of sorcin drives paclitaxel-resistance and malignant progression via Smad4/ZEB1/miR-142-5p in human ovarian cancer

The primary chemotherapy of ovarian cancer (OC) often acquires chemoresistance. Sorcin (SRI), a soluble resistance-related calcium-binding protein, has been reported to be an oncogenic protein in cancer. However, the molecular mechanisms of SRI regulation and the role and aberrant expression of SRI in chemoresistant OC remain unclear. Here, we identified SRI as a key driver of paclitaxel (PTX)-resistance and explored its regulatory mechanism. Using transcriptome profiles, qRT-PCR, proteomics, Western blot, immunohistochemistry, and bioinformatics analyses, we found that SRI was overexpressed in PTX-resistant OC cells and the overexpression of SRI was related to the poor prognosis of patients. SRI was a key molecule required for growth, migration, and PTX-resistance in vitro and in vivo and was involved in epithelial-mesenchymal transition (EMT) and stemness. Mechanistic studies showed that miR-142-5p directly bound to the 3'-UTR of SRI to suppress its expression, whereas a transcription factor zinc-finger E-box binding homeobox 1 (ZEB1) inhibited the transcription of miR-142-5p by directly binding to the E-box fragment in the miR-142 promoter region. Furthermore, ZEB1 was negatively regulated by SRI which physically interacted with Smad4 to block its translocation from the cytosol to the nucleus. Taken together, our findings unveil a novel homeostatic loop of SRI that drives the PTX-resistance and malignant progression via Smad4/ZEB1/miR-142-5p in human OC. Targeting this SRI/Smad4/ZEB1/miR-142-5p loop may reverse the PTX-resistance.

Super-Enhancer Redistribution as a Mechanism of Broad Gene Dysregulation in Repeatedly Drug-Treated Cancer Cells

Cisplatin is an antineoplastic drug administered at suboptimal and intermittent doses to avoid life-threatening effects. Although this regimen shortly improves symptoms in the short term, it also leads to more malignant disease in the long term. We describe a multilayered analysis ranging from chromatin to translation-integrating chromatin immunoprecipitation sequencing (ChIP-seq), global run-on sequencing (GRO-seq), RNA sequencing (RNA-seq), and ribosome profiling-to understand how cisplatin confers (pre)malignant features by using a well-established ovarian cancer model of cisplatin exposure. This approach allows us to segregate the human transcriptome into gene modules representing distinct regulatory principles and to characterize that the most cisplatin-disrupted modules are associated with underlying events of super-enhancer plasticity. These events arise when cancer cells initiate without ultimately ending the program of drug-stimulated death. Using a PageRank-based algorithm, we predict super-enhancer regulator ISL1 as a driver of this plasticity and validate this prediction by using CRISPR/dCas9-KRAB inhibition (CRISPRi) and CRISPR/dCas9-VP64 activation (CRISPRa) tools. Together, we propose that cisplatin reprograms cancer cells when inducing them to undergo near-to-death experiences.

Targeting mTOR and eIF4E: a feasible scenario in ovarian cancer therapy

Ovarian carcinoma is one of the most common causes for cancer death in women; lack of early diagnosis and acquired resistance to platinum-based chemotherapy account for its poor prognosis and high mortality rate. As with other cancer types, ovarian cancer is characterized by dysregulated signaling pathways and protein synthesis, which together contribute to rapid cellular growth and invasiveness. The mechanistic/mammalian target of rapamycin (mTOR) pathway represents the core of different signaling pathways regulating a number of essential steps in the cell, among which protein synthesis and the eukaryotic initiation factor 4E (eIF4E), the mRNA cap binding protein, is one of its downstream effectors. eIF4E is a limiting factor in translation initiation and its overexpression is a hallmark in many cancers. Because its action is regulated by a number of factors that compete for the same binding site, eIF4E is an ideal target for developing novel antineoplastic drugs. Several inhibitors targeting the mTOR signaling pathway have been designed thus far, however most of these molecules show poor stability and high toxicity in vivo. This minireview explores the possibility of targeting mTOR and eIF4E proteins, thus impacting on translation initiation in ovarian cancer, describing the most promising experimental strategies and specific inhibitors that have been shown to have an effect on other kinds of cancers.

Bioinformatics analysis of mRNA and miRNA microarray to identify the key miRNA-mRNA pairs in cisplatin-resistant ovarian cancer

Background

Ovarian cancer (OC) is a gynecological malignancy with the highest mortality rate. Cisplatin (DDP) based chemotherapy is a standard strategy for ovarian cancer. Despite good response rates for initial chemotherapy, almost 80% of the patients treated with DDP based chemotherapy will experience recurrence due to drug-resistant, which will ultimately result in fatality. The aim of the present study was to examine the pathogenesis and potential molecular markers of cisplatin-resistant OC by studying the differential expression of mRNAs and miRNAs between cisplatin resistant OC cell lines and normal cell lines.

Methods

Two mRNA datasets (GSE58470 and GSE45553) and two miRNA sequence datasets (GSE58469 and GSE148251) were downloaded from the Gene expression omnibus (GEO) database. Differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs) were screened by the NetworkAnalyst. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were conducted to analyze the biological functions of DEGs. The protein-protein interaction network was constructed using STRING and Cytoscape software to identify the molecular mechanisms of key signaling pathways and cellular activities. FunRich and MiRNATip databases were used to identify the target genes of the DEMs.

Results

A total of 380 DEGs, and 5 DEMs were identified. Protein–protein interaction (PPI) network of DEGs containing 379 nodes and 1049 edges was constructed, and 4 key modules and 24 hub genes related to cisplatin-resistant OC were screened. Two hundred ninety-nine target genes of the 5 DEMs were found out. Subsequently, one of these 299 target genes (UBB) belonging to the hub genes of GSE58470 and GSE45553 was identified by MCODE and CytoHubba,which was regulated by one miRNA (mir-454).

Conclusions

One miRNA–mRNA regulatory pairs (mir-454-UBB) was established. Taken together, our study provided evidence concerning the alteration genes involved in cisplatin-resistant OC, which will help to unravel the mechanisms underlying drug resistant.

Dissecting the Business Case for Adoption and Implementation of Digital Pathology: A White Paper from the Digital Pathology Association

We believe the switch to a digital pathology (DP) workflow is imminent and it is essential to understand the economic implications of conversion. Many aspects of the adoption of DP will be disruptive and have a direct financial impact, both in short term costs, such as investment in equipment and personnel, and long term revenue potential, such as improved productivity and novel tests. The focus of this whitepaper is to educate pathologists, laboratorians and other stakeholders about the business and monetary considerations of converting to a digital pathology workflow. The components of a DP business plan will be thoroughly summarized, and guidance will be provided on how to build a case for adoption and implementation as well as a roadmap for transitioning from an analog to a digital pathology workflow in various laboratory settings. It is important to clarify that this publication is not intended to list prices although some financials will be mentioned as examples. The authors encourage readers who are evaluating conversion to a DP workflow to use this paper as a foundational guide for conducting a thorough and complete assessment while incorporating in current market pricing. Contributors to this paper analyzed peer-reviewed literature and data collected from various institutions, some of which are mentioned. Digital pathology will change the way we practice through facilitating patient access to expert pathology services and enabling image analysis tools and assays to aid in diagnosis, prognosis, risk stratification and therapeutic selection. Together, they will result in the delivery of valuable information from which to make better decisions and improve the health of patients.

Emerging Roles for Ion Channels in Ovarian Cancer: Pathomechanisms and Pharmacological Treatment

Ovarian cancer (OC) is the deadliest gynecologic cancer, due to late diagnosis, development of platinum resistance, and inadequate alternative therapy. It has been demonstrated that membrane ion channels play important roles in cancer processes, including cell proliferation, apoptosis, motility, and invasion. Here, we review the contribution of ion channels in the development and progression of OC, evaluating their potential in clinical management. Increased expression of voltage-gated and epithelial sodium channels has been detected in OC cells and tissues and shown to be involved in cancer proliferation and invasion. Potassium and calcium channels have been found to play a critical role in the control of cell cycle and in the resistance to apoptosis, promoting tumor growth and recurrence. Overexpression of chloride and transient receptor potential channels was found both in vitro and in vivo, supporting their contribution to OC. Furthermore, ion channels have been shown to influence the sensitivity of OC cells to neoplastic drugs, suggesting a critical role in chemotherapy resistance. The study of ion channels expression and function in OC can improve our understanding of pathophysiology and pave the way for identifying ion channels as potential targets for tumor diagnosis and treatment.

miR-21 Induces Chemoresistance in Ovarian Cancer Cells via Mediating the Expression and Interaction of CD44v6 and P-gp

Background

Ovarian cancer (OC), a representative female reproductive system tumor, is one of the most malignant tumors in female. The most important reason for its poor prognosis is because of its high rate of chemotherapy resistance.

Results

This study aims to explore the effects of miR-21 on the chemotherapy resistance of OC cells. The functions of miR-21 on proliferation, migration and invasion of OC cells were assessed by transwell, clonal formation and CCK8 assay. Expression levels of miR-21, P-gp and CD44v6 in SKOV3 (cisplatin sensitive) cells and SKOV3/DDP (cisplatin resistant) cells were detected by quantitative reverse transcription-polymerase chain reaction (qRT-PCR) and Western blotting. Si-CD44v6 was transfected into OC cells to detect the influence on P-glycoprotein (P-gp) expression. Immunofluorescence was used to detect the localization of CD44v6 and P-gp in cell. Co-immunoprecipitation was used to detect the relationship between CD44v6 and P-gp. Results showed that miR-21 expression in cisplatin-resistant SKOV3/DDP cells was significantly higher than that in SKOV3 cells, at the same time, cells proliferation, as well as invasion and migration ability were enhanced after the miR-21 mimics transfected into SKOV3 cisplatin-sensitive cells. Furthermore, miR-21 expression level affected the CD44v6 and P-gp expression. Immunofluorescence and co-immunoprecipitation showed that CD44v6 and P-gp protein could interact.

Conclusion

In conclusion, the high miR-21 expression level could increase the proliferation, invasion, and migration ability of OC cells. And the interaction of CD44v6 and P-gp may mediate miR-21 involvement in chemotherapy resistance of OC cells.

Tumor-intrinsic and -extrinsic (immune) gene signatures robustly predict overall survival and treatment response in high grade serous ovarian cancer patients

In the present study, we developed a transcriptomic signature capable of predicting prognosis and response to primary therapy in high grade serous ovarian cancer (HGSOC). Proportional hazard analysis was performed on individual genes in the TCGA RNAseq data set containing 229 HGSOC patients. Ridge regression analysis was performed to select genes and develop multigenic models. Survival analysis identified 120 genes whose expression levels were associated with overall survival (OS) (HR = 1.49-2.46 or HR = 0.48-0.63). Ridge regression modeling selected 38 of the 120 genes for development of the final Ridge regression models. The consensus model based on plurality voting by 68 individual Ridge regression models classified 102 (45%) as low, 23 (10%) as moderate and 104 patients (45%) as high risk. The median OS was 31 months (HR = 7.63, 95% CI = 4.85-12.0, P < 1.0-10) and 77 months (HR = ref) in the high and low risk groups, respectively. The gene signature had two components: intrinsic (proliferation, metastasis, autophagy) and extrinsic (immune evasion). Moderate/high risk patients had more partial and non-responses to primary therapy than low risk patients (odds ratio = 4.54, P < 0.001). We concluded that the overall survival and response to primary therapy in ovarian cancer is best assessed using a combination of gene signatures. A combination of genes which combines both tumor intrinsic and extrinsic functions has the best prediction. Validation studies are warranted in the future.

Chemotherapy sensitivity testing on ovarian cancer cells isolated from malignant ascites

BACKGROUND

In epithelial ovarian cancer (EOC), 15-20% of the tumors do not respond to first-line chemotherapy (paclitaxel with platinum-based therapy), and in recurrences this number increases. Our aim is to determine the feasibility of cell proliferation assays of tumor cells isolated from malignant ascites to predict in vitro chemotherapy sensitivity, and to correlate these results with clinical outcome.

MATERIALS AND METHODS

Ascites was collected from twenty women with advanced EOC. Cell samples were enriched for tumor cells and EOC origin was confirmed by intracellular staining of CK7, surface staining of CA125 and EpCAM, and HE4 gene expression. In vitro sensitivity to chemotherapy was determined in cell proliferation assays using intracellular ATP content as an indirect measure of cell number. In vitro drug response was quantified by calculation of the drug concentration at which cell growth was inhibited with 50%. Clinical outcome was determined using post-treatment CA125 level.

RESULTS

Cell samples of twenty patients were collected, of which three samples that failed to proliferate were excluded in the analysis (15%). Three other samples were excluded, because clinical outcome could not be determined correctly. In twelve of the fourteen remaining cases (86%) in vitro drug sensitivity and clinical outcome corresponded, while in two samples (14%) there was no correspondence.

CONCLUSIONS

Our study demonstrates the feasibility of drug sensitivity tests using tumor cells isolated from ascites of advanced EOC patients. Larger observational studies are required to confirm the correlation between the in vitro sensitivity and clinical outcome.

Prediction of the treatment response in ovarian cancer: a ctDNA approach

Ovarian cancer is the eighth most commonly occurring cancer in women. Clinically, the limitation of conventional screening and monitoring approaches inhibits high throughput analysis of the tumor molecular markers toward prediction of treatment response. Recently, analysis of liquid biopsies including circulating tumor DNA (ctDNA) open new way toward cancer diagnosis and treatment in a personalized manner in various types of solid tumors. In the case of ovarian carcinoma, growing pre-clinical and clinical studies underscored promising application of ctDNA in diagnosis, prognosis, and prediction of treatment response. In this review, we accumulate and highlight recent molecular findings of ctDNA analysis and its associations with treatment response and patient outcome. Additionally, we discussed the potential application of ctDNA in the personalized treatment of ovarian carcinoma. ctDNA-monitoring usage during the ovarian cancer treatments procedures.

Interleukin-34 expression in ovarian cancer: a possible correlation with disease progression

Ovarian cancer is the second-most lethal gynecological malignancy and the seventh-commonest cause of cancer-related death in women around the world. Most of the ovarian cancer patients are diagnosed at advanced stages and suffer from recurrence after primary cytoreductive surgery and standard first-line chemotherapy. Thus, the successful management of ovarian cancer patients requires the identification of factors that contribute to progression and relapse. Interleukin-34 (IL-34) is a novel cytokine that acts as a tissue-specific ligand of colony-stimulating factor-1 receptor (CSF-1R). In cancer, IL-34 exerts pro-tumorigenic functions that promote tumor growth, metastasis, angiogenesis, immune suppression and therapeutic resistance. In this study, we evaluate the impact of IL-34 on progression and survival of ovarian cancer patients. First, IL-34 was found to be expressed in several human ovarian cancer cell lines and cancer tissues from patients. The expression of IL-34 was enhanced by cytotoxic chemotherapy in ovarian cancer cell lines and cancer tissues from chemotherapy-treated ovarian cancer patients. Importantly, high IL-34 expression correlated with worse progression-free survival (PFS) and overall survival in different cohorts. The assessment of PFS based on a combination between IL34 expression and other related genes such as CSF1R and CD163 helped further to reach more statistical significance compared with IL34 alone. Furthermore, in the murine ovarian cancer cell HM-1 in vivo model, it was suggested that IL-34-derived tumor cells was correlated with tumor progression and survival by modulating the immune environment. Collectively, these findings indicate a possible correlation between IL-34 expression and disease progression in ovarian cancer patients and the mouse model.

Analytical Challenges in Development of Chemoresistance Predictors for Precision Oncology

Chemoresistance, i.e., tumor insensitivity to chemotherapy, shortens life expectancy of cancer patients. Despite the availability of new treatment options, initial systemic regimens for solid tumors are dominated by a set of standard chemotherapy drugs, and alternative therapies are used only when a patient has demonstrated chemoresistance clinically. Chemoresistance predictors use laboratory parameters measured on tissue samples to predict the patient's response to chemotherapy and help to avoid application of chemotherapy to chemoresistant patients. Despite thousands of publications on putative chemoresistance predictors, there are only about a dozen predictors that are sufficiently accurate for precision oncology. One of the major reasons for inaccuracy of predictors is inaccuracy of analytical methods utilized to measure their laboratory parameters: an inaccurate method leads to an inaccurate predictor. The goal of this study was to identify analytical challenges in chemoresistance-predictor development and suggest ways to overcome them. Here we describe principles of chemoresistance predictor development via correlating a clinical parameter, which manifests disease state, with a laboratory parameter. We further classify predictors based on the nature of laboratory parameters and analyze advantages and limitations of different predictors using the reliability of analytical methods utilized for measuring laboratory parameters as a criterion. Our eventual focus is on predictors with known mechanisms of reactions involved in drug resistance (drug extrusion, drug degradation, and DNA damage repair) and using rate constants of these reactions to establish accurate and robust laboratory parameters. Many aspects and conclusions of our analysis are applicable to all types of disease biomarkers built upon the correlation of clinical and laboratory parameters.

A gene signature for immune subtyping of desert, excluded, and inflamed ovarian tumors

PROBLEM

The current tumor immunology paradigm emphasizes the role of the immune tumor microenvironment and distinguishes several histologically and transcriptionally different immune tumor subtypes. However, the experimental validation of such classification is so far limited to selected cancer types. Here, we aimed to explore the existence of inflamed, excluded, and desert immune subtypes in ovarian cancer, as well as investigate their association with the disease outcome.

METHOD OF STUDY

We used the publicly available ovarian cancer dataset from The Cancer Genome Atlas for developing subtype assignment algorithm, which was next verified in a cohort of 32 real-world patients of a known tumor subtype.

RESULTS

Using clinical and gene expression data of 489 ovarian cancer patients in the publicly available dataset, we identified three transcriptionally distinct clusters, representing inflamed, excluded, and desert subtypes. We developed a two-step subtyping algorithm with COL5A2 serving as a marker for separating excluded tumors, and CD2, TAP1, and ICOS for distinguishing between inflamed and desert tumors. The accuracy of gene expression-based subtyping algorithm in a real-world cohort was 75%. Additionally, we confirmed that patients bearing inflamed tumors are more likely to survive longer.

CONCLUSION

Our results highlight the presence of transcriptionally and histologically distinct immune subtypes among ovarian tumors and emphasize the potential benefit of immune subtyping as a clinical tool for treatment tailoring.

miRNa signature in small extracellular vesicles and their association with platinum resistance and cancer recurrence in ovarian cancer

Carboplatin, administered as a single drug or in combination with paclitaxel, is the standard chemotherapy treatment for patients with ovarian cancer (OVCA). Recent evidence suggests that miRNAs associated with small extracellular vesicles (sEVs) participate in the development of chemoresistance. We studied the effect of carboplatin in a heterogeneity population of OVCA cells and their derived sEVs to identify mechanisms associated with chemoresistance. sEVs were quantified using an engineered superparamagnetic material, gold-loaded ferric oxide nanotubes and a screen-printed electrode. miR-21-3p, miR-21-5p, and miR-891-5p are enriched in sEVs, and they contribute to carboplatin resistance in OVCA. Using a quantitative MS/MS, miR-21-5p activates glycolysis and increases the expression of ATP-binding cassette family and a detoxification enzyme. miR-21-3p and miR-891-5p increase the expression of proteins involved in DNA repair mechanisms. Interestingly, the levels of miR-891-5p within sEVs are significantly higher in patients at risk of ovarian cancer relapse. Identification of miRNAs in sEVs also provides the opportunity to track them in biological fluids to potentially determine patient response to chemotherapy.

Copy Number Amplification of DNA Damage Repair Pathways Potentiates Therapeutic Resistance in Cancer

Rationale: Loss of DNA damage repair (DDR) in the tumor is an established hallmark of sensitivity to DNA damaging agents such as chemotherapy. However, there has been scant investigation into gain-of-function alterations of DDR genes in cancer. This study aims to investigate to what extent copy number amplification of DDR genes occurs in cancer, and what are their impacts on tumor genome instability, patient prognosis and therapy outcome.

Methods: Retrospective analysis was performed on the clinical, genomics, and pharmacogenomics data from 10,489 tumors, matched peripheral blood samples, and 1,005 cancer cell lines. The key discoveries were verified by an independent patient cohort and experimental validations.

Results: This study revealed that 13 of the 80 core DDR genes were significantly amplified and overexpressed across the pan-cancer scale. Tumors harboring DDR gene amplification exhibited decreased global mutation load and mechanism-specific mutation signature scores, suggesting an increased DDR proficiency in the DDR amplified tumors. Clinically, patients with DDR gene amplification showed poor prognosis in multiple cancer types. The most frequent Nibrin (NBN) gene amplification in ovarian cancer tumors was observed in 15 out of 31 independent ovarian cancer patients. NBN overexpression in breast and ovarian cancer cells leads to BRCA1-dependent olaparib resistance by promoting the phosphorylation of ATM-S1981 and homology-dependent recombination efficiency. Finally, integration of the cancer pharmacogenomics database of 37 genome-instability targeting drugs across 505 cancer cell lines revealed significant correlations between DDR gene copy number amplification and DDR drug resistance, suggesting candidate targets for increasing patient treatment response.

Principal Conclusions: DDR gene amplification can lead to chemotherapy resistance and poor overall survival by augmenting DDR. These amplified DDR genes may serve as actionable clinical biomarkers for cancer management.

Large-scale integrated analysis of ovarian cancer tumors and cell lines identifies an individualized gene expression signature for predicting response to platinum-based chemotherapy

Heterogeneity in chemotherapeutic response is directly associated with prognosis and disease recurrence in patients with ovarian cancer (OvCa). Despite the significant clinical need, a credible gene signature for predicting response to platinum-based chemotherapy and for guiding the selection of personalized chemotherapy regimens has not yet been identified. The present study used an integrated approach involving both OvCa tumors and cell lines to identify an individualized gene expression signature, denoted as IndividCRS, consisting of 16 robust chemotherapy-responsive genes for predicting intrinsic or acquired chemotherapy response in the meta-discovery dataset. The robust performance of this signature was subsequently validated in 25 independent tumor datasets comprising 2215 patients and one independent cell line dataset, across different technical platforms. The IndividCRS was significantly correlated with the response to platinum therapy and predicted the improved outcome. Moreover, the IndividCRS correlated with homologous recombination deficiency (HRD) and was also capable of discriminating HR-deficient tumors with or without platinum-sensitivity for guiding HRD-targeted clinical trials. Our results reveal the universality and simplicity of the IndividCRS as a promising individualized genomic tool to rapidly monitor response to chemotherapy and predict the outcome of patients with OvCa.

Multigene signatures of responses to chemotherapy derived by biochemically-inspired machine learning

Pharmacogenomic responses to chemotherapy drugs can be modeled by supervised machine learning of expression and copy number of relevant gene combinations. Such biochemical evidence can form the basis of derived gene signatures using cell line data, which can subsequently be examined in patients that have been treated with the same drugs. These gene signatures typically contain elements of multiple biochemical pathways which together comprise multiple origins of drug resistance or sensitivity. The signatures can capture variation in these responses to the same drug among different patients.

Inhibitory effect on ovarian cancer ALDH+ stem-like cells by Disulfiram and Copper treatment through ALDH and ROS modulation

BACKGROUND

Disulfiram (DSF) is a drug used for treatment of alcoholism that has also displayed promising anti-cancer activity. It unfolds its effects by inhibiting the enzyme activity of aldehyde dehydrogenase (ALDH) isoforms.

METHODS

MTT assay, spheroid formation, clonogenicity assay, qRT-PCR, and ALDH enzyme activity analysis were performed using ovarian cancer cell lines IGROV1, SKOV3 and SKOV3IP1. Cell cycle analyses and measurement of intracellular reactive oxygen species (ROS) were carried out by flow cytometry. ALDH+ and ALDH- cells were isolated by FACS sorting.

RESULTS

ALDH activity was inhibited in ovarian cancer stem cells (the proportion of ALDH+ cells was reduced from 21.7% to 0.391%, 8.4% to 0%, 6.88% to 0.05% in cell lines IGROV1, SKOV3, and SKOV3IP1, respectively). DSF with or without the cofactor copper (Cu²⁺) exhibited cytotoxicity dose- and time-dependent and enhanced cisplatin-induced apoptosis. DSF + Cu²⁺ increased intracellular ROS levels triggering apoptosis of ovarian cancer stem cells (CSC). Significantly more colony and spheroid formation was observed in ALDH+ compared with ALDH- cells (P < 0.01). Moreover, ALDH+ cells were more resistant to cisplatin treatment compared with ALDH-cells (P < 0.05) and also exhibited a lower basal level of ROS. However, no significant difference in ROS accumulation nor in cellular viability was observed in ALDH + cells in comparison to ALDH- cells after pre-treatment with DSF (0.08 μM).

CONCLUSION

Our findings provide evidence that DSF might be employed as a novel adjuvant chemotherapeutic agent in combination with cisplatin for treatment of ovarian cancer.

The expression tractability of biological traits shaped by natural selection

Understanding how gene expression is translated to phenotype is central to modern molecular biology, and the success is contingent on the intrinsic tractability of the specific traits under examination. However, an a priori estimate of trait tractability from the perspective of gene expression is unavailable. Motivated by the concept of entropy in a thermodynamic system, we here propose such an estimate (S_T) by gauging the number (N) of expression states that underlie the same trait abnormality, with large S_T corresponding to large N. By analyzing over 200 yeast morphological traits, we show that S_T predicts the tractability of an expression-trait relationship. We further show that S_T is ultimately determined by natural selection, which builds co-regulated gene modules to minimize possible expression states.

MicroRNA-128/homeobox B8 axis regulates ovarian cancer cell progression

MicroRNA-128 (miR-128) has been found to be dysregulated and might function as a tumour suppressor in various cancers, including ovarian cancer. However, the underlying mechanism of miR-128 in ovarian cancer has not been fully understood. The miR-128 and homeobox B8 (HOXB8) levels in clinical samples and cultured cell lines were measured using qRT-PCR and/or Western blot analysis. Cell proliferation was assessed using Cell Counting Kit-8 assay. Cell apoptosis was determined using flow cytometry. The association between miR-128 and HOXB8 was confirmed using dual-luciferase reporter assay. Results showed that decreased miR-128 expression and increased HOXB8 expression were observed in ovarian cancer tissues and cell lines. Transfection with miR-128 mimics suppressed the cell proliferation and enhanced paclitaxel sensitivity in ovarian cancer cell lines. miR-128 directly targeted HOXB8 in ovarian cancer cell lines. Knockdown of HOXB8 abolished the effects of miR-128 inhibitor on ovarian cancer cell proliferation and paclitaxel sensitivity. Summarily, miR-128 displayed a tumour suppressor role in ovarian cancer via targeting HOXB8. It is supposed that miR-128 might be effective for targeting therapy for ovarian cancer.

Gene Expression Indicates Altered Immune Modulation and Signaling Pathway Activation in Ovarian Cancer Patients Resistant to Topotecan

Epithelial ovarian cancer (EOC) is one of the deadliest gynecological malignancies. Topotecan remains an essential tool in second-line therapy; even so, most patients develop resistance within a short period of time. We aimed to identify biomarkers of topotecan resistance by using gene expression signatures derived from patient specimens at surgery and available subsequent responses to therapy. Gene expression was collected for 1436 patients and 10,103 genes. Based on disease progression, patients were categorized as responders/nonresponders depending on their progression free survival (PFS) state at 9, 12, 15 and 18 months after surgery. For each gene, the median expression was compared between responders and nonresponders for two treatment regimens (chemotherapy including/excluding topotecan) with Mann-Whitney U test at each of the four different PFS cutoffs. Statistical significance was accepted in the case of p < 0.05 with a fold change (FC) ≥ 1.44. Four genes (EPB41L2, HLA-DQB1, LTF and SFRP1) were consistently overexpressed across multiple PFS cutoff times in initial tumor samples of patients with disease progression following topotecan treatment. A common theme linked to topotecan resistance was altered immune modulation. Genes associated with disease progression after systemic chemotherapy emphasize the role of the initial organization of the tumor microenvironment in therapy resistance. Our results uncover biomarkers with potential utility for patient stratification.

An Integrated Microfluidics Approach for Personalized Cancer Drug Sensitivity and Resistance Assay

Cancer is the second leading cause of death globally. Matching proper treatment and dosage is crucial for a positive outcome. Any given drug may affect patients with similar tumors differently. Personalized medicine aims to address this issue. Unfortunately, most cancer samples cannot be expanded in culture, limiting conventional cell-based testing. Herein, presented is a microfluidic device that combines a drug microarray with cell microscopy. The device can perform 512 experiments to test chemosensitivity and resistance to a drug array. MCF7 and 293T cells are cultured inside the device and their chemosensitivity and resistance to docetaxel, applied at various concentrations, are determined. Cell mortality is determined as a function of drug concentration and exposure time. It is found that both cell types form cluster morphology within the device, not evident in conventional tissue culture under similar conditions. Cells inside the clusters are less sensitive to drugs than dispersed cells. These findings support a heterogenous response of cancer cells to drugs. Then demonstrated is the principle of drug microarrays by testing cell response to four different drugs at four different concentrations. This approach may enable the personalization of treatment to the particular tumor and patient and may eventually improve final patient outcome.

Biological Insights into Chemotherapy Resistance in Ovarian Cancer

The majority of patients with high-grade serous ovarian cancer (HGSOC) initially respond to chemotherapy; however, most will develop chemotherapy resistance. Gene signatures may change with the development of chemotherapy resistance in this population, which is important as it may lead to tailored therapies. The objective of this study was to compare tumor gene expression profiles in patients before and after treatment with neoadjuvant chemotherapy (NACT). Tumor samples were collected from six patients diagnosed with HGSOC before and after administration of NACT. RNA extraction and whole transcriptome sequencing was performed. Differential gene expression, hierarchical clustering, gene set enrichment analysis, and pathway analysis were examined in all of the samples. Tumor samples clustered based on exposure to chemotherapy as opposed to patient source. Pre-NACT samples were enriched for multiple pathways involving cell cycle growth. Post-NACT samples were enriched for drug transport and peroxisome pathways. Molecular subtypes based on the pre-NACT sample (differentiated, mesenchymal, proliferative and immunoreactive) changed in four patients after administration of NACT. Multiple changes in tumor gene expression profiles after exposure to NACT were identified from this pilot study and warrant further attention as they may indicate early changes in the development of chemotherapy resistance.

MiR-34c/SOX9 axis regulates the chemoresistance of ovarian cancer cell to cisplatin-based chemotherapy

Cisplatin (DDP)-based chemotherapy is a standard strategy for ovarian cancer (OC), while chemoresistance remains a major therapeutic challenge. Transcription factor SOX9 has been reported to be associated with tumor cell proliferation, metastasis, and chemoresistance. In the current study, we observed a higher SOX9 expression in OC cell lines; SOX9 overexpression might aggravate the chemoresistance of the OC cell to DDP, whereas its knockdown enhanced the chemoresistance. We screened for candidate microRNAs (miRNAs) which might target SOX9 using online tools and further verified the effect of miR-34c, one of the candidate miRNA that significantly inhibited SOX9 expression, in the regulation of OC cell proliferation and chemoresistance to DDP. Further, we verified the interaction between SOX9 and miR-34c, as well as the involvement of β-catenin signaling in this process. Through the analysis of the correlation between miR-34c expression and the clinical features of patients with OC, we revealed that miR-34c might inhibit OC cell proliferation and chemoresistance to improve the prognosis of patients with OC. Further, the expression of SOX9, β-catenin, and c-Myc in OC tissues was upregulated and inversely correlated with miR-34c expression, indicating that rescuing miR-34c expression, thus to inhibit SOX9, β-catenin, and c-Myc expression presents a promising strategy of reducing the chemoresistance of the OC cell to DDP.

AS1411 aptamer-decorated cisplatin-loaded poly(lactic-co-glycolic acid) nanoparticles for targeted therapy of miR-21-inhibited ovarian cancer cells

AIM

The overexpression of miRNA-21 correlates with the cisplatin (CIS) resistance in the ovarian cancers.

METHODS

AS1411 antinucleolin aptamer-decorated PEGylated poly(lactic-co-glycolic acid) nanoparticles containing CIS (Ap-CIS-NPs) and anti-miR-21 (Ap-anti-miR-21-NPs) were prepared, physicochemically investigated and their cancer-targeting ability was confirmed. CIS-resistant A2780 cells (A2780 R) were infected with anti-miR-21 using Ap-anti-miR-21-NPs to decrease the drug resistance and sensitize the cells to CIS. Afterward, miR-21-inhibited cells were exposed to the Ap-CIS-NPs.

RESULTS

Ap-anti-miR-21-NPs could infect the A2780 R cells mainly through nucleolin-mediated endocytosis and inhibit the endogenous miR-21. Targeted delivery of CIS using Ap-CIS-NPs into the miR-21-inhibited cells caused an enhanced mortality.

CONCLUSION

The targeted delivery of chemotherapeutics to the oncomiR-inhibited cells may find a robust application in cancer chemo/gene therapy.

Therapeutic enhancement of a cytotoxic agent using photochemical internalisation in 3D compressed collagen constructs of ovarian cancer

Photochemical internalisation (PCI) is a method for enhancing delivery of drugs to their intracellular target sites of action. In this study we investigated the efficacy of PCI using a porphyrin photosensitiser and a cytotoxic agent on spheroid and non-spheroid compressed collagen 3D constructs of ovarian cancer versus conventional 2D culture. The therapeutic responses of two human carcinoma cell lines (SKOV3 and HEY) were compared using a range of assays including optical imaging. The treatment was shown to be effective in non-spheroid constructs of both cell lines causing a significant and synergistic reduction in cell viability measured at 48 or 96 h post-illumination. In the larger spheroid constructs, PCI was still effective but required higher saporin and photosensitiser doses. Moreover, in contrast to the 2D and non-spheroid experiments, where comparable efficacy was found for the two cell lines, HEY spheroid constructs were found to be more susceptible to PCI and a lower dose of saporin could be used. PCI treatment was observed to induce death principally by apoptosis in the 3D constructs compared to the mostly necrotic cell death caused by PDT. At low oxygen levels (1%) both PDT and PCI were significantly less effective in the constructs. STATEMENT OF SIGNIFICANCE: Assessment of new drugs or delivery systems for cancer therapy prior to conducting in vivo studies often relies on the use of conventional 2D cell culture, however 3D cancer constructs can provide more physiologically relevant information owing to their 3D architecture and the presence of an extracellular matrix. This study investigates the efficacy of Photochemical Internalisation mediated drug delivery in 3D constructs. In 3D cultures, both oxygen and drug delivery to the cells are limited by diffusion through the extracellular matrix unlike 2D models, and in our model we have used compressed collagen constructs where the density of collagen mimics physiological values. These 3D constructs are therefore well suited to studying drug delivery using PCI. Our study highlights the potential of these constructs for identifying differences in therapeutic response to PCI of two ovarian carcinoma lines.

Identification of clinical tumor stages related mRNAs and miRNAs in cervical squamous cell carcinoma

OBJECTIVES

The aim of this study is to identify the clinical tumor stage related mRNAs and miRNAs, shedding light on the potential molecular mechanisms of cervical squamous cell carcinoma (CSCC).

METHODS

Firstly, the mRNA and miRNA next-generation sequencing data were downloaded. Secondly, clinical tumor stage correlation analysis of mRNAs and miRNA was performed, followed by the functional enrichment analysis of all clinical tumor stage related mRNAs. Thirdly, differentially expression analysis of mRNAs and miRNA between different clinical tumor stages was performed, followed by target gene prediction of these differentially expressed miRNAs.

RESULTS

3 mRNAs (PER1, PRKAB1 and PMM2) and 5 miRNAs (hsa-mir-486, hsa-mir-451, hsa-mir-424, hsa-mir-144 and hsa-mir-450a-2) were overlapped from stage 1, stage 2, stage 3 and stage 4.

CONCLUSIONS

Alterations of differentially expressed mRNAs and miRNAs may offer important insights into the molecular mechanisms in the pathology of CSCC.

Low expression of KCNN3 may affect drug resistance in ovarian cancer

Drug resistance is a principal contributor to the poor prognosis of ovarian cancer (OC). Therefore, identifying factors that affect drug resistance in OC is critical. In the present study, 51 OC specimens from lab collections were immunohistochemically tested, public data for 489 samples from The Cancer Genome Atlas cohort and 1,656 samples from the Kaplan‑Meier Plotter were downloaded, and data were retrieved from Oncomine. It was identified that the mRNA and protein expression of the potassium calcium‑activated channel subfamily N member 3 (KCNN3) was markedly lower in OC tissues compared with normal tissues, and in drug‑resistant OC tissues compared with sensitive OC tissues. Low KCNN3 expression consistently predicted shorter disease‑free and overall survival (OS). Specifically, low KCNN3 expression predicted shorter OS in 395 patients with low expression levels of mucin‑16. There was additional evidence that KCNN3 expression is mediated by microRNA‑892b. Furthermore, text mining and analyses of protein and gene interactions indicated that KCNN3 affects drug resistance. To the best of the authors' knowledge, this is the first report to associate KCNN3 with poor prognosis and drug resistance in OC. The present findings indicated that KCNN3 is a potential prognostic marker and therapeutic target for OC.

Developing a genetic signature to predict drug response in ovarian cancer

There is a lack of personalized treatment options for women with recurrent platinum-resistant ovarian cancer. Outside of bevacizumab and a group of poly ADP-ribose polymerase inhibitors, few options are available to women that relapse. We propose that efficacious drug combinations can be determined via molecular characterization of ovarian tumors along with pre-established pharmacogenomic profiles of repurposed compounds. To that end, we selectively performed multiple two-drug combination treatments in ovarian cancer cell lines that included reactive oxygen species inducers and HSP90 inhibitors. This allowed us to select cell lines that exhibit disparate phenotypes of proliferative inhibition to a specific drug combination of auranofin and AUY922. We profiled altered mechanistic responses from these agents in both reactive oxygen species and HSP90 pathways, as well as investigated PRKCI and lncRNA expression in ovarian cancer cell line models. Generation of dual multi-gene panels implicated in resistance or sensitivity to this drug combination was produced using RNA sequencing data and the validity of the resistant signature was examined using high-density RT-qPCR. Finally, data mining for the prevalence of these signatures in a large-scale clinical study alluded to the prevalence of resistant genes in ovarian tumor biology. Our results demonstrate that high-throughput viability screens paired with reliable in silico data can promote the discovery of effective, personalized therapeutic options for a currently untreatable disease.

Noncanonical agonist PPARγ ligands modulate the response to DNA damage and sensitize cancer cells to cytotoxic chemotherapy

The peroxisome-proliferator receptor-γ (PPARγ) is expressed in multiple cancer types. Recently, our group has shown that PPARγ is phosphorylated on serine 273 (S273), which selectively modulates the transcriptional program controlled by this protein. PPARγ ligands, including thiazolidinediones (TZDs), block S273 phosphorylation. This activity is chemically separable from the canonical activation of the receptor by agonist ligands and, importantly, these noncanonical agonist ligands do not cause some of the known side effects of TZDs. Here, we show that phosphorylation of S273 of PPARγ occurs in cancer cells on exposure to DNA damaging agents. Blocking this phosphorylation genetically or pharmacologically increases accumulation of DNA damage, resulting in apoptotic cell death. A genetic signature of PPARγ phosphorylation is associated with worse outcomes in response to chemotherapy in human patients. Noncanonical agonist ligands sensitize lung cancer xenografts and genetically induced lung tumors to carboplatin therapy. Moreover, inhibition of this phosphorylation results in deregulation of p53 signaling, and biochemical studies show that PPARγ physically interacts with p53 in a manner dependent on S273 phosphorylation. These data implicate a role for PPARγ in modifying the p53 response to cytotoxic therapy, which can be modulated for therapeutic gain using these compounds.

Report on the first SLFN11 monothematic workshop: from function to role as a biomarker in cancer

SLFN11 is a recently discovered protein with a putative DNA/RNA helicase function. First identified in association with the maturation of thymocytes, SLFN11 was later causally associated, by two independent groups, with the resistance to DNA damaging agents such as topoisomerase I and II inhibitors, platinum compounds, and other alkylators, making it an attractive molecule for biomarker development. Later, SLFN11 was linked to antiviral response in human cells and interferon production, establishing a potential bond between immunity and chemotherapy. Recently, we demonstrated the potential role of SLN11 as a biomarker to predict sensitivity to the carboplatin/taxol combination in ovarian cancer. The present manuscript reports on the first international monothematic workshop on SLFN11. Several researchers from around the world, directly and actively involved in the discovery, functional characterization, and study of SLFN11 for its biomarker and medicinal properties gathered to share their views on the current knowledge advances concerning SLFN11. The aim of the manuscript is to summarize the authors’ interventions and the main take-home messages resulting from the workshop.

The Prognostic 97 Chemoresponse Gene Signature in Ovarian Cancer

Patient diagnosis and care would be significantly improved by understanding the mechanisms underlying platinum and taxane resistance in ovarian cancer. Here, we aim to establish a gene signature that can identify molecular pathways/transcription factors involved in ovarian cancer progression, poor clinical outcome, and chemotherapy resistance. To validate the robustness of the gene signature, a meta-analysis approach was applied to 1,020 patients from 7 datasets. A 97-gene signature was identified as an independent predictor of patient survival in association with other clinicopathological factors in univariate [hazard ratio (HR): 3.0, 95% Confidence Interval (CI) 1.66–5.44, p = 2.7E-4] and multivariate [HR: 2.88, 95% CI 1.57–5.2, p = 0.001] analyses. Subset analyses demonstrated that the signature could predict patients who would attain complete or partial remission or no-response to first-line chemotherapy. Pathway analyses revealed that the signature was regulated by HIF1α and TP53 and included nine HIF1α-regulated genes, which were highly expressed in non-responders and partial remission patients than in complete remission patients. We present the 97-gene signature as an accurate prognostic predictor of overall survival and chemoresponse. Our signature also provides information on potential candidate target genes for future treatment efforts in ovarian cancer.