Reannotation and Analysis of Clinical and Chemotherapy Outcomes in the Ovarian Data Set From The Cancer Genome Atlas

Systematic identification of anticancer drug targets reveals a nucleus-to-mitochondria ROS-sensing pathway

Multiple anticancer drugs have been proposed to cause cell death, in part, by increasing the steady-state levels of cellular reactive oxygen species (ROS). However, for most of these drugs, exactly how the resultant ROS function and are sensed is poorly understood. It remains unclear which proteins the ROS modify and their roles in drug sensitivity/resistance. To answer these questions, we examined 11 anticancer drugs with an integrated proteogenomic approach identifying not only many unique targets but also shared ones-including ribosomal components, suggesting common mechanisms by which drugs regulate translation. We focus on CHK1 that we find is a nuclear H2O2 sensor that launches a cellular program to dampen ROS. CHK1 phosphorylates the mitochondrial DNA-binding protein SSBP1 to prevent its mitochondrial localization, which in turn decreases nuclear H2O2. Our results reveal a druggable nucleus-to-mitochondria ROS-sensing pathway-required to resolve nuclear H2O2 accumulation and mediate resistance to platinum-based agents in ovarian cancers.

Aberrant Transcript Usage Is Associated with Homologous Recombination Deficiency and Predicts Therapeutic Response

BRCA1/2 mutations account for only a small fraction of homologous recombination (HR) deficiency (HRD) cases. Recently developed genomic HRD (gHRD) tests suffer confounding factors that cause low precision in predicting samples that will respond to PARP inhibitors and DNA damaging agents. Here we present molecular and clinical evidence of transcriptional HRD (tHRD) that is based on aberrant transcript usage (aTU) of minor isoforms. Specifically, increased TU of nonfunctional isoforms of DNA repair genes was prevalent in breast and ovarian cancer with gHRD. Functional assays validated the association of aTU with impaired HR activity. Machine learning-based tHRD detection by the transcript usage (TU) pattern of key genes was superior to directly screening for gHRD or BRCA1/2 mutations in accurately predicting responses of cell lines and patients with cancer to PARP inhibitors and genotoxic drugs. This approach demonstrated the capability of tHRD status to reflect functional HR status, including in a cohort of olaparib-treated ovarian cancer with acquired platinum resistance. Diagnostic tests based on tHRD are expected to broaden the clinical utility of PARP inhibitors. SIGNIFICANCE: A novel but widespread transcriptional mechanism by which homologous recombination deficiency arises independently of BRCA1/2 mutations can be utilized as a companion diagnostic for PARP inhibitors.

Distinct fibroblast functional states drive clinical outcomes in ovarian cancer and are regulated by TCF21

Recent studies indicate that cancer-associated fibroblasts (CAFs) are phenotypically and functionally heterogeneous. However, little is known about CAF subtypes, the roles they play in cancer progression, and molecular mediators of the CAF “state.” Here, we identify a novel cell surface pan-CAF marker, CD49e, and demonstrate that two distinct CAF states, distinguished by expression of fibroblast activation protein (FAP), coexist within the CD49e⁺ CAF compartment in high-grade serous ovarian cancers. We show for the first time that CAF state influences patient outcomes and that this is mediated by the ability of FAP-high, but not FAP-low, CAFs to aggressively promote proliferation, invasion and therapy resistance of cancer cells. Overexpression of the FAP-low–specific transcription factor TCF21 in FAP-high CAFs decreases their ability to promote invasion, chemoresistance, and in vivo tumor growth, indicating that it acts as a master regulator of the CAF state. Understanding CAF states in more detail could lead to better patient stratification and novel therapeutic strategies.

iMOKA: k-mer based software to analyze large collections of sequencing data

iMOKA (interactive multi-objective k-mer analysis) is a software that enables comprehensive analysis of sequencing data from large cohorts to generate robust classification models or explore specific genetic elements associated with disease etiology. iMOKA uses a fast and accurate feature reduction step that combines a Naïve Bayes classifier augmented by an adaptive entropy filter and a graph-based filter to rapidly reduce the search space. By using a flexible file format and distributed indexing, iMOKA can easily integrate data from multiple experiments and also reduces disk space requirements and identifies changes in transcript levels and single nucleotide variants. iMOKA is available at https://github.com/RitchieLabIGH/iMOKA and Zenodo https://doi.org/10.5281/zenodo.4008947 .

Olaparib Versus Nonplatinum Chemotherapy in Patients With Platinum-Sensitive Relapsed Ovarian Cancer and a Germline BRCA1/2 Mutation (SOLO3): A Randomized Phase III Trial

PURPOSE

A phase II study (ClinicalTrials.gov identifier: NCT00628251) showed activity of olaparib capsules versus pegylated liposomal doxorubicin in patients with germline BRCA-mutated platinum-resistant or partially platinum-sensitive relapsed ovarian cancer. We conducted a phase III trial (SOLO3) of olaparib tablets versus nonplatinum chemotherapy in patients with germline BRCA-mutated platinum-sensitive relapsed ovarian cancer who had received at least 2 prior lines of platinum-based chemotherapy.

PATIENTS AND METHODS

In this randomized, open-label trial, patients were randomly assigned 2:1 to olaparib 300 mg twice a day or physician's choice single-agent nonplatinum chemotherapy (pegylated liposomal doxorubicin, paclitaxel, gemcitabine, or topotecan). The primary end point was objective response rate (ORR) in the measurable disease analysis set assessed by blinded independent central review (BICR). The key secondary end point was progression-free survival (PFS) assessed by BICR in the intent-to-treat population.

RESULTS

Of 266 randomly assigned patients, 178 were assigned to olaparib and 88 to chemotherapy. In patients with measurable disease (olaparib, n = 151; chemotherapy, n = 72), the BICR-assessed ORR was significantly higher with olaparib than with chemotherapy (72.2% v 51.4%; odds ratio [OR], 2.53 [95% CI, 1.40 to 4.58]; P = .002). In the subgroup who had received 2 prior lines of treatment, the ORR was 84.6% with olaparib and 61.5% with chemotherapy (OR, 3.44 [95% CI, 1.42 to 8.54]). BICR-assessed PFS also significantly favored olaparib versus chemotherapy (hazard ratio, 0.62 [95% CI, 0.43 to 0.91]; P = .013; median, 13.4 v 9.2 months). Adverse events were consistent with the established safety profiles of olaparib and chemotherapy.

CONCLUSION

Olaparib resulted in statistically significant and clinically relevant improvements in ORR and PFS compared with nonplatinum chemotherapy in patients with germline BRCA-mutated platinum-sensitive relapsed ovarian cancer who had received at least 2 prior lines of platinum-based chemotherapy.

Insights into Impact of DNA Copy Number Alteration and Methylation on the Proteogenomic Landscape of Human Ovarian Cancer via a Multi-omics Integrative Analysis

In this work, we propose iProFun, an integrative analysis tool to screen for proteogenomic functional traits perturbed by DNA copy number alterations (CNAs) and DNA methylations. The goal is to characterize functional consequences of DNA copy number and methylation alterations in tumors and to facilitate screening for cancer drivers contributing to tumor initiation and progression. Specifically, we consider three functional molecular quantitative traits: mRNA expression levels, global protein abundances, and phosphoprotein abundances. We aim to identify those genes whose CNAs and/or DNA methylations have cis-associations with either some or all three types of molecular traits. Compared with analyzing each molecular trait separately, the joint modeling of multi-omics data enjoys several benefits: iProFun experienced enhanced power for detecting significant cis-associations shared across different omics data types, and it also achieved better accuracy in inferring cis-associations unique to certain type(s) of molecular trait(s). For example, unique associations of CNAs/methylations to global/phospho protein abundances may imply posttranslational regulations.We applied iProFun to ovarian high-grade serous carcinoma tumor data from The Cancer Genome Atlas and Clinical Proteomic Tumor Analysis Consortium and identified CNAs and methylations of 500 and 121 genes, respectively, affecting the cis-functional molecular quantitative traits of the corresponding genes. We observed substantial power gain via the joint analysis of iProFun. For example, iProFun identified 117 genes whose CNAs were associated with phosphoprotein abundances by leveraging mRNA expression levels and global protein abundances. By comparison, analyses based on phosphoprotein data alone identified none. A network analysis of these 117 genes revealed the known oncogene AKT1 as a key hub node interacting with many of the rest. In addition, iProFun identified one gene, BIN2, whose DNA methylation has cis-associations with its mRNA expression, global protein, and phosphoprotein abundances. These and other genes identified by iProFun could serve as potential drug targets for ovarian cancer.