Targeted composite value-based endpoints in platinum-sensitive recurrent ovarian cancer

Global publication productivity and research trends on recurrent ovarian cancer: a bibliometric study

Introduction

Recurrent ovarian cancer (ROC) presents a dismal prognosis, persistently devoid of efficacious therapeutic strategies. Over the past decade, significant shifts have transpired in ROC management, marked by the identification of novel therapeutic targets and advancements in biomarker research and innovation. Since bibliometrics is an effective method for revealing scientific literature, we conducted a bibliometric analysis of literature pertaining to ROC. Our exploration encompassed identifying emerging research trends and common patterns, analyzing collaborative networks, and anticipating future directions within this clinical context.

Methods

We conducted a search in the Web of Science Core Collection (WoSCC) to acquire relevant articles as our dataset, which were then exported using R-Studio-2023.12.0-369 software. The Bibliometrix R package was utilized to perform visual analyses on countries, institutions, journals, authors, landmark articles, and keywords within this research field.

Results

A total of 1538 articles and 173 reviews published between 2014 and 2023 were eventually retrieved. The annual growth rate of scientific production was 4.27%. The USA led the way in the number of published works, total citations, and collaboration. Gynecologic Oncology was the most favoured journal in this research field. Vergote I from the University Hospital Leuven, was the most influential author. At last, the most prominent keywords were "chemotherapy" (n = 124), "bevacizumab" (n = 87), and "survival" (n = 65). Clinical outcomes (prognosis, survival), chemotherapy, bevacizumab, and PARP inhibitors (olaparib, niraparib) represented the basic and transversal themes, while antibody-drug conjugate (ADC) and drug resistance were emerging themes. Cytoreduction surgical procedures and tamoxifen were niche themes, while immunotherapy and biomarkers were motor themes and had high centrality.

Conclusion

The trends in the ROC research field over the past decade were revealed through bibliometric analysis. Platinum resistance, ADC, and immunotherapy have emerged as the current prominent research topics.

Homologous Recombination Abnormalities Associated With BRCA1/2 Mutations as Predicted by Machine Learning of Targeted Next-Generation Sequencing Data

Background

Homologous recombination deficiency (HRD) is the hallmark of breast cancer gene 1/2 (BRCA1/2)-mutated tumors and the unique biomarker for predicting response to double-strand break (DSB)-inducing drugs. The demonstration of HRD in tumors with mutations in genes other than BRCA1/2 is considered the best biomarker of potential response to these DSB-inducer drugs.

Objectives

We explored the potential of developing a practical approach to predict in any tumor the presence of HRD that is similar to that seen in tumors with BRCA1/2 mutations using next-generation sequencing (NGS) along with machine learning (ML).

Design

We use copy number alteration (CNA) generated from routine-targeted NGS data along with a modified naïve Bayesian model for the prediction of the presence of HRD.

Methods

The CNA from NGS of 434 targeted genes was analyzed using CNVkit software to calculate the log2 of CNA changes. The log2 values of various sequencing reads (bins) were used in ML to train the system on predicting tumors with BRCA1/2 mutations and tumors with abnormalities similar to those detected in BRCA1/2 mutations.

Results

Using 31 breast or ovarian cancers with BRCA1/2 mutations and 84 tumors without mutations in any of 12 homologous recombination repair (HRR) genes, the ML demonstrated high sensitivity (90%, 95% confidence interval [CI] = 73%-97.5%) and specificity (98%, 95% CI = 90%-100%). Testing of 114 tumors with mutations in HRR genes other than BRCA1/2 showed 39% positivity for HRD similar to that seen in BRCA1/2. Testing 213 additional wild-type (WT) cancers showed HRD positivity similar to BRCA1/2 in 32% of cases. Correlation with proportional loss of heterozygosity (LOH) as determined using whole exome sequencing of 51 samples showed 90% (95% CI = 72%-97%) concordance. The approach was also validated in an independent set of 1312 consecutive tumor samples.

Conclusions

These data demonstrate that CNA when combined with ML can reliably predict the presence of BRCA1/2 level HRD with high specificity. Using BRCA1/2 mutant cases as gold standard, this ML can be used to predict HRD in cancers with mutations in other HRR genes as well as in WT tumors.

High-grade serous peritoneal cancer follows a high stromal response signature and shows worse outcome than ovarian cancer

In the era of personalized medicine, where transition from organ‐based to individualized genetic diagnosis takes place, the tailoring of treatment in cancer becomes increasingly important. This is particularly true for high‐grade, advanced FIGO stage serous adenocarcinomas of the ovary (OC), fallopian tube (TC), and peritoneum (PC), which are currently all treated identically. We analyzed three independent patient cohorts using histopathologically classified diagnosis and various molecular approaches (transcriptomics, immunohistochemistry, next‐generation sequencing, fluorescent and chromogenic in situ hybridization). Using multivariate Cox regression model, we found that PC is more aggressive compared with advanced‐stage OC independent of residual disease as shown by an earlier relapse‐free survival in two large cohorts (HR: 2.63, CI: 1.59–4.37, P < 0.001, and HR: 1.66, CI: 1.04–2.63, P < 0.033). In line with these findings, transcriptomic data revealed differentially expressed gene signatures identifying PC as high stromal response tumors. The third independent cohort (n = 4054) showed a distinction between these cancer types for markers suggested to be predictive for chemotherapy drug response. Our findings add additional evidence that ovarian and peritoneal cancers are epidemiologically and molecularly distinct diseases. Moreover, our data also suggest consideration of the tumor‐sampling site for future diagnosis and treatment decisions.