Ovarian cancer: markers of response

STAU1-mediated CNBP mRNA degradation by LINC00665 alters stem cell characteristics in ovarian cancer

BACKGROUND

To investigate the role of lncRNA LINC00665 in modulating ovarian cancer stemness and its influence on treatment resistance and cancer development.

METHODS

We isolated ovarian cancer stem cells (OCSCs) from the COC1 cell line using a combination of chemotherapeutic agents and growth factors, and verified their stemness through western blotting and immunofluorescence for stem cell markers. Employing bioinformatics, we identified lncRNAs associated with ovarian cancer, with a focus on LINC00665 and its interaction with the CNBP mRNA. In situ hybridization, immunohistochemistry, and qPCR were utilized to examine their expression and localization, alongside functional assays to determine the effects of LINC00665 on CNBP.

RESULTS

LINC00665 employs its Alu elements to interact with the 3'-UTR of CNBP mRNA, targeting it for degradation. This molecular crosstalk enhances stemness by promoting the STAU1-mediated decay of CNBP mRNA, thereby modulating the Wnt and Notch signaling cascades that are pivotal for maintaining CSC characteristics and driving tumor progression. These mechanistic insights were corroborated by a series of in vitro assays and validated in vivo using tumor xenograft models. Furthermore, we established a positive correlation between elevated CNBP levels and increased disease-free survival in patients with ovarian cancer, underscoring the prognostic value of CNBP in this context.

CONCLUSIONS

lncRNA LINC00665 enhances stemness in ovarian cancer by mediating the degradation of CNBP mRNA, thereby identifying LINC00665 as a potential therapeutic target to counteract drug resistance and tumor recurrence associated with CSCs.

Identification of modules and hub genes associated with platinum-based chemotherapy resistance and treatment response in ovarian cancer by weighted gene co-expression network analysis

High-grade serous ovarian carcinoma (HGSOC) is the most prevalent and malignant ovarian tumor.To identify co-expression modules and hub genes correlated with platinum-based chemotherapy resistant and sensitive HGSOC, we performed weighted gene co-expression network analysis (WGCNA) on microarray data of HGSOC with 12 resistant samples and 16 sensitive samples of GSE51373 dataset.A total of 5122 genes were included in WGCNA, and 16 modules were identified. Module-trait analysis identified that the module salmon (cor = 0.50), magenta (cor = 0.49), and black (cor = 0.45) were discovered associated with chemotherapy resistant, and the significance for these platinum-resistant modules were validated in the GSE63885 dataset. Given that the black module was validated to be the most related one, hub genes of this module, alcohol dehydrogenase 1B, cadherin 11, and vestigial like family member 3were revealed to be expressional related with platinum resistance, and could serve as prognostic markers for ovarian cancer.Our analysis might provide insight for molecular mechanisms of platinum-based chemotherapy resistance and treatment response in ovarian cancer.

The significance of the change pattern of serum CA125 level for judging prognosis and diagnosing recurrences of epithelial ovarian cancer

Background

Ovarian cancer has the highest mortality rate of the three main malignant tumors of the female reproductive system, with a 5-year overall survival (OS) of only 20–30 %. Approximately 70 % of patients relapse without being cured. To explore the significance of serum CA125 level pre-treatment and the change pattern of CA125 post-treatment for judging prognosis and diagnosing recurrences of epithelial ovarian cancer (EOC).

Methods

A radioimmunoassay was used to continuously monitor levels of serum CA125 in 152 patients with EOC. The first test was done before surgery, then once a month after surgery for more than two consecutive years. The data were analyzed by using Kaplan-Meier curves and the log-rank test, stratified chi-square test, Pearson correlation analysis, and multivariate Cox regression analysis.

Results

(1) There was a relationship between patient outcomes and the serum CA125 levels before treatment and the extent and speed of serum CA125 decrease after treatment. The outcomes of patients with pre-treatment serum CA125 ≤ 35 U/ml were better than those with serum CA125 > 35 U/ml; the outcomes of patients with serum CA125 who had a logarithmic decrease or a decrease to normal within a month after treatment were also better than those with a non-logarithmic decrease or a decrease to normal that took longer than a month. (2) The results of multivariate Cox regression analysis showed that serum CA125 levels before treatment and a decreased speed of decline after treatment were independent prognostic factors; (3) The mean level of serum CA125 at relapse was 116.28 U/ml. The average time from serum CA125 increase to detection of a recurrent lesion by physical or imaging examination was 122 days. The correlation coefficient of serum CA125 level increase and tumor recurrence time was −0.674. (4) The area under the Receiver Operating Characteristic (ROC) curve of serum CA125 for diagnosing EOC recurrence was 0.879, and the sensitivity and specificity were 67.39 and 86.79 %, respectively.

Conclusions

It is important to monitor serum CA125 levels pre-treatment and the change pattern of CA125 post-treatment for judging prognosis and diagnosing recurrences of EOC.

Comparative meta-analysis of prognostic gene signatures for late-stage ovarian cancer

BACKGROUND

Ovarian cancer is the fifth most common cause of cancer deaths in women in the United States. Numerous gene signatures of patient prognosis have been proposed, but diverse data and methods make these difficult to compare or use in a clinically meaningful way. We sought to identify successful published prognostic gene signatures through systematic validation using public data.

METHODS

A systematic review identified 14 prognostic models for late-stage ovarian cancer. For each, we evaluated its 1) reimplementation as described by the original study, 2) performance for prognosis of overall survival in independent data, and 3) performance compared with random gene signatures. We compared and ranked models by validation in 10 published datasets comprising 1251 primarily high-grade, late-stage serous ovarian cancer patients. All tests of statistical significance were two-sided.

RESULTS

Twelve published models had 95% confidence intervals of the C-index that did not include the null value of 0.5; eight outperformed 97.5% of signatures including the same number of randomly selected genes and trained on the same data. The four top-ranked models achieved overall validation C-indices of 0.56 to 0.60 and shared anticorrelation with expression of immune response pathways. Most models demonstrated lower accuracy in new datasets than in validation sets presented in their publication.

CONCLUSIONS

This analysis provides definitive support for a handful of prognostic models but also confirms that these require improvement to be of clinical value. This work addresses outstanding controversies in the ovarian cancer literature and provides a reproducible framework for meta-analytic evaluation of gene signatures.

Comparative meta-analysis of prognostic gene signatures for late-stage ovarian cancer

BACKGROUND

Ovarian cancer is the fifth most common cause of cancer deaths in women in the United States. Numerous gene signatures of patient prognosis have been proposed, but diverse data and methods make these difficult to compare or use in a clinically meaningful way. We sought to identify successful published prognostic gene signatures through systematic validation using public data.

METHODS

A systematic review identified 14 prognostic models for late-stage ovarian cancer. For each, we evaluated its 1) reimplementation as described by the original study, 2) performance for prognosis of overall survival in independent data, and 3) performance compared with random gene signatures. We compared and ranked models by validation in 10 published datasets comprising 1251 primarily high-grade, late-stage serous ovarian cancer patients. All tests of statistical significance were two-sided.

RESULTS

Twelve published models had 95% confidence intervals of the C-index that did not include the null value of 0.5; eight outperformed 97.5% of signatures including the same number of randomly selected genes and trained on the same data. The four top-ranked models achieved overall validation C-indices of 0.56 to 0.60 and shared anticorrelation with expression of immune response pathways. Most models demonstrated lower accuracy in new datasets than in validation sets presented in their publication.

CONCLUSIONS

This analysis provides definitive support for a handful of prognostic models but also confirms that these require improvement to be of clinical value. This work addresses outstanding controversies in the ovarian cancer literature and provides a reproducible framework for meta-analytic evaluation of gene signatures.

Randomized reverse marker strategy design for prospective biomarker validation

We describe a novel study design for validating marker-based treatment strategies meant to select among possible therapeutic options using a biologic marker. Studying existing designs in realistic scenarios, we demonstrate that this design is more than four times more efficient for testing the interaction between a marker and its intended treatment. Our analysis employs a simple parametric framework that uncovers systematic biases in currently proposed designs and suggests how they may be accommodated or enumerated. In the context of markers for choosing a treatment for recurrent ovarian cancer, our proposal requires sample sizes on the order of recently completed phases II and III studies making validation studies for this clinical decision scenario viable.

Discrete mixture modeling to address genetic heterogeneity in time-to-event regression

MOTIVATION

Time-to-event regression models are a critical tool for associating survival time outcomes with molecular data. Despite mounting evidence that genetic subgroups of the same clinical disease exist, little attention has been given to exploring how this heterogeneity affects time-to-event model building and how to accommodate it. Methods able to diagnose and model heterogeneity should be valuable additions to the biomarker discovery toolset.

RESULTS

We propose a mixture of survival functions that classifies subjects with similar relationships to a time-to-event response. This model incorporates multivariate regression and model selection and can be fit with an expectation maximization algorithm, we call Cox-assisted clustering. We illustrate a likely manifestation of genetic heterogeneity and demonstrate how it may affect survival models with little warning. An application to gene expression in ovarian cancer DNA repair pathways illustrates how the model may be used to learn new genetic subsets for risk stratification. We explore the implications of this model for censored observations and the effect on genomic predictors and diagnostic analysis.

AVAILABILITY AND IMPLEMENTATION

R implementation of CAC using standard packages is available at https://gist.github.com/programeng/8620b85146b14b6edf8f Data used in the analysis are publicly available.

Ovarian cancer: targeting the untargetable

The premise that all tumors are targetable has been met with some controversy in the approach to epithelial ovarian cancer (EOC). Genomic analysis shows that these tumors (specifically, high-grade serous carcinomas) are genomically unstable and lack actionable driver mutations, much like HER2 in breast and gastric cancers. In this paper, Michael Birrer, MD, PhD, Massachusetts General Hospital, argues that the interpretation of genomic data in ovarian cancer requires a more thoughtful approach that necessitates a closer inspection of the data beyond the mere presence or absence of mutations. We must look at the extensive genomic alterations in DNA and, to understand more about the role of those genes affected by these changes, look beyond the tumor to the role of the stroma. As such, Dr. Birrer is arguing for the importance of translational research. This will be the key to precision medicine in ovarian cancer, as we approach drug discovery and improvements in treatment. Dr. Birrer is a world-renowned scientist who has devoted his career to the study of gynecologic cancers. He has published over 200 papers and written over 27 book chapters and reviews, served on numerous leadership positions in gynecologic oncology (including as co-chair of the National Cancer Institute's Gynecologic Cancer Steering Committee), and remains a clinician-scientist with an active lab and an active clinic. His career trajectory has shown me it is possible to be engaged as a researcher and a clinician and the work he has done has already impacted the care of patients with ovarian cancer. Don S. Dizon, MD, ASCO Educational Book Editor.

Ascites analysis by a microfluidic chip allows tumor-cell profiling

Ascites tumor cells (ATCs) represent a potentially valuable source of cells for monitoring treatment of ovarian cancer as it would obviate the need for more invasive surgical biopsies. The ability to perform longitudinal testing of ascites in a point-of-care setting could significantly impact clinical trials, drug development, and clinical care. Here, we developed a microfluidic chip platform to enrich ATCs from highly heterogeneous peritoneal fluid and then perform molecular analyses on these cells. We evaluated 85 putative ovarian cancer protein markers and found that nearly two-thirds were either nonspecific for malignant disease or had low abundance. Using four of the most promising markers, we prospectively studied 47 patients (33 ovarian cancer and 14 control). We show that a marker set (ATCdx) can sensitively and specifically map ATC numbers and, through its reliable enrichment, facilitate additional treatment-response measurements related to proliferation, protein translation, or pathway inhibition.

The significance of the pattern of serum CA125 level ascent to above the normal range in epithelial ovarian, primary peritoneal and tubal carcinoma patients

OBJECTIVE

A rise of the CA125 marker above the normal range during follow-up of ovarian, primary peritoneal and tubal carcinoma patients with a complete clinical response after initial treatment signifies recurrence. We assessed whether the pattern of CA125 ascent to above the normal range at recurrence is associated with outcome.

METHODS

The records of all recurrent ovarian primary peritoneal and tubal carcinoma patients diagnosed during 1998-2007 were abstracted. Included were patients who fulfilled the following criteria: CA125 levels were ≥35 U/mL at diagnosis and at recurrence, they had full primary treatment with a complete clinical and radiographic response, were followed-up according to schedule, and had at least two CA125 results within the normal range during follow-up. Two patterns of CA125 ascent to above the normal range were compared: a gradual rise and an abrupt rise.

RESULTS

52 patients with recurrent disease who met the inclusion criteria were identified. The median progression free and overall survival were significantly longer in patients with a gradual than in those with an abrupt rise (22.96 vs 14.07; P=0.0014; and 44.37 vs. median not yet reach, respectively). Multivariate analysis showed that the pattern of CA125 ascent is an independent predictor of progression free and overall survival.

CONCLUSIONS

Our data seem to indicate that at recurrence the pattern of ascent of serum CA125 levels to above the normal range in patients in complete clinical remission is of prognostic value.

The role of tandem duplicator phenotype in tumour evolution in high-grade serous ovarian cancer

High-grade serous ovarian carcinoma (HGSOC) is characterized by genomic instability, ubiquitous TP53 loss, and frequent development of platinum resistance. Loss of homologous recombination (HR) is a mutator phenotype present in 50% of HGSOCs and confers hypersensitivity to platinum treatment. We asked which other mutator phenotypes are present in HGSOC and how they drive the emergence of platinum resistance. We performed whole-genome paired-end sequencing on a model of two HGSOC cases, each consisting of a pair of cell lines established before and after clinical resistance emerged, to describe their structural variants (SVs) and to infer their ancestral genomes as the SVs present within each pair. The first case (PEO1/PEO4), with HR deficiency, acquired translocations and small deletions through its early evolution, but a revertant BRCA2 mutation restoring HR function in the resistant lineage re-stabilized its genome and reduced platinum sensitivity. The second case (PEO14/PEO23) had 216 tandem duplications and did not show evidence of HR or mismatch repair deficiency. By comparing the cell lines to the tissues from which they originated, we showed that the tandem duplicator mutator phenotype arose early in progression in vivo and persisted throughout evolution in vivo and in vitro, which may have enabled continual evolution. From the analysis of SNP array data from 454 HGSOC cases in The Cancer Genome Atlas series, we estimate that 12.8% of cases show patterns of aberrations similar to the tandem duplicator, and this phenotype is mutually exclusive with BRCA1/2 carrier mutations.

Evolution of platinum resistance in high-grade serous ovarian cancer

High-grade serous ovarian cancers account for most ovarian-cancer mortality. Although this disease initially responds well to platinum-based chemotherapy, relapse and progression to chemotherapy resistance are frequently seen. Time to relapse after first-line therapy is a predictor of response to secondary platinum treatment: more than 12 months is associated with high chance of a secondary response, whereas relapses within 6 months generally indicate platinum resistance. In this Personal View we discuss whether patterns of response, relapse, and the development of drug resistance in high-grade serous ovarian cancers are related to distinct underlying molecular and cellular biological characteristics. In particular, we propose that rapid relapse with platinum-resistant disease is due to minor subpopulations of intrinsically resistant cancer cells at presentation.

miRNA control of apoptotic programs: focus on ovarian cancer

miRNAs are a class of small non-coding RNAs that regulate the stability or translational efficiency of targeted mRNAs. miRNAs are involved in many cellular processes, such as differentiation, proliferation and apoptosis, which are altered in cancer through miRNA expression dysregulation. In this article we will discuss recent findings implicating miRNAs in apoptotic program regulation using ovarian carcinoma as an example. Ovarian cancer is the most lethal gynecological malignancy. Most patients are diagnosed with advanced disease that is conventionally managed with surgical resection followed by platinum-based chemotherapy. Killing of cancer cells by chemotherapeutic agents or by triggering cell-surface death receptors relies on activation of apoptotic programs executed through receptor-mediated extrinsic pathways and mitochondrial-dependent intrinsic pathways. Despite an initial good response to chemotherapy, ovarian cancer patients typically experience disease relapse within 2 years of the initial treatment developing resistance even to structurally different drugs. Thus, also in this pathology, tumor cells are able to evade apoptosis using multiple mechanisms, several of which are dependent on miRNA gene regulation.

Progression-free survival in ovarian cancer is reflected in epigenetic DNA methylation profiles

OBJECTIVE

Many patients with ovarian cancer disease relapse within 6 months after adjuvant chemotherapy, with a limited prognosis. Epigenetic modifications have been shown to play an important role in tumor development and formation. Therefore, global analysis of DNA methylation patterns might reveal specific CpG sites that correlate with progression-free interval (PFI) after therapy.

METHODS

Twenty samples of advanced ovarian cancer with a predominantly serous papillary histological subtype were subjected to DNA methylation profiling. Illumina HumanMethylation27 BeadChip technology was used for simultaneous analysis of 27,578 CpG sites in >14,000 genes.

RESULTS

Differential DNA methylation of various cytosines correlated with PFI. However, this becomes only significant by classification according to PFI with a cutoff of >28 months. Longer survival was associated with hypomethylation at specific CpG sites (e.g. GREB1, TGIF and TOB1) and hypermethylation in other genes (e.g. TMCO5, PTPRN and GUCY2C). Gene ontology analysis revealed that differentially methylated genes were significantly overrepresented in the categories telomere organization, mesoderm development and immune regulation.

CONCLUSION

Epigenetic modifications at specific CpG sites correlate with PFI in ovarian cancer. Therefore, such analysis might be of prognostic value.

Breast cancer 1 (BRCA1) protein expression as a prognostic marker in sporadic epithelial ovarian carcinoma: an NCIC CTG OV.16 correlative study

BACKGROUND

Breast cancer 1 (BRCA1) protein inactivation in sporadic ovarian carcinoma (OC) is common and low BRCA1 expression is linked with platinum sensitivity. The clinical validation of BRCA1 as a prognostic marker in OC remains unresolved.

PATIENTS AND METHODS

In 251 patient samples from the NCIC CTG clinical trial, OV.16, BRCA1 protein expression was determined by immunohistochemistry.

RESULTS

For all patients, when BRCA1 score was analyzed as a continuous variable, there was no significant correlation between BRCA1 protein expression and progression-free survival (PFS) [adjusted hazard ratio (HR) = 1.15 (0.96-1.37), P = 0.12] or response rate [HR = 0.89 (0.70-1.12), P = 0.32]. In the 116 patients with minimal residual disease (RD), higher BRCA1 expression correlated significantly with worse PFS [HR = 1.40 (1.04-1.89), P = 0.03]. Subgroup analysis divided patients with minimal RD into low (BRCA1 ≤2.5) and high (BRCA1 >2.5) expression groups. Patients with low BRCA1 expression had a more favorable outcome [median PFS was 24.7 and 16.6 months in patients with low and high BRCA1, respectively; HR = 0.56 (0.35-0.89), P = 0.01].

CONCLUSIONS

This study suggests that BRCA1 protein is a prognostic marker in sporadic OC patients with minimal RD. Further research is needed to evaluate BRCA1 as a predictive biomarker and to target BRCA1 expression to enhance chemotherapeutic sensitivity.

Progranulin is a potential prognostic biomarker in advanced epithelial ovarian cancers

OBJECTIVE

There are few validated relapse prediction biomarkers for epithelial ovarian cancer (EOC). We have shown progranulin (PGRN) and secretory leukocyte protease inhibitor (SLPI) are up regulated, overexpressed survival factors in EOC. We hypothesized they would predict presence of occult EOC.

METHOD

PGRN, SLPI, and the known biomarker HE4 were measured in EOC patient plasma samples, prospectively collected every 3 months from initial remission until relapse. Clinical data and CA125 results were incorporated into statistical analyses. Exploratory Kaplan-Meier estimates, dividing markers at median values, evaluated association with progression-free survival (PFS) and overall survival (OS). Area-under-the-curve (AUC) statistics were computed from receiver operating characteristic (ROC) curves to evaluate discrimination ability. A Cox proportional hazards model assessed the association between PFS, OS, and biomarkers, adjusting for clinical prognostic factors.

RESULTS

Samples from 23 advanced stage EOC patients were evaluated. PGRN at 3 months was the only biomarker independently associated with PFS (P<0.0001) and OS (P<0.003). When used to predict progression by 18 months, sensitivity and specificity were 93% and 100%, respectively, with AUC=0.944. The Cox model hazard ratio for PFS, divided at 59 ng/ml by ROC analysis and adjusted for clinical factors, was 23.5 (95% CI: 2.49-220). Combinations with SLPI, HE4, and/or CA125 did not improve the model.

CONCLUSIONS

We report pilot data indicating a potential independent association of PGRN on EOC patient PFS and OS. A validation study will be required to confirm this finding and to inform whether PGRN warrants evaluation as a potential screening biomarker.