Stephen B. Baylin

Early Detection of Ovarian Cancer Using Cell-Free DNA Fragmentomes and Protein Biomarkers

Abstract Ovarian cancer is a leading cause of death for women worldwide, in part due to ineffective screening methods. In this study, we used whole-genome cell-free DNA (cfDNA) fragmentome and protein biomarker [cancer antigen 125 (CA-125) and human epididymis protein 4 (HE4)] analyses to evaluate 591 women with ovarian cancer, with benign adnexal masses, or without ovarian lesions. Using a machine learning model with the combined features, we detected ovarian cancer with specificity >99% and sensitivities of 72%, 69%, 87%, and 100% for stages I to IV, respectively. At the same specificity, CA-125 alone detected 34%, 62%, 63%, and 100%, and HE4 alone detected 28%, 27%, 67%, and 100% of ovarian cancers for stages I to IV, respectively. Our approach differentiated benign masses from ovarian cancers with high accuracy (AUC = 0.88, 95% confidence interval, 0.83–0.92). These results were validated in an independent population. These findings show that integrated cfDNA fragmentome and protein analyses detect ovarian cancers with high performance, enabling a new accessible approach for noninvasive ovarian cancer screening and diagnostic evaluation. Significance: There is an unmet need for effective ovarian cancer screening and diagnostic approaches that enable earlier-stage cancer detection and increased overall survival. We have developed a high-performing accessible approach that evaluates cfDNA fragmentomes and protein biomarkers to detect ovarian cancer.

Genomic Landscapes of Endometrioid and Mucinous Ovarian Cancers and Morphologically Similar Tumor Types

Abstract Endometrioid and mucinous ovarian carcinomas represent nearly a fifth of ovarian cancers, but their molecular characteristics and pathologic origins are poorly understood. To identify the genomic and epigenomic alterations characteristic of these ovarian cancer subtypes and evaluate links to morphologically similar tumors from other sites, we performed a combination of sequence, copy number, mutation signature, and rearrangement analyses from tumor samples and matched normal tissues of 133 patients, as well as methylation analyses of these tumors and tissues of 150 patients from The Cancer Genome Atlas. Genomic analyses included samples from patients with ovarian endometrioid (n = 44), ovarian mucinous (n = 43), uterine endometrioid (n = 15), and gastrointestinal mucinous carcinomas (n = 31), including mucinous carcinomas of the stomach, colon, and pancreas. In addition to identifying genes previously known to be involved in these tumors, we identified alterations in RAD51C, NOTCH4, SMARCA1/4, and JAK1 in ovarian endometrioid, ESR1 in uterine endometrioid, and SMARCA4 in ovarian mucinous carcinomas. Whole-genome sequencing revealed rearrangements involving PTEN, NF1, and NF2 in ovarian endometrioid carcinomas and NF1 and MED1 in ovarian mucinous carcinomas. The number of alterations, affected genes, and genome-wide methylation profiles were not distinguishable between ovarian and uterine endometrioid carcinomas, supporting the hypothesis that these tumors share a tissue of origin. In contrast, mutation and methylation patterns in ovarian mucinous carcinomas were different from gastrointestinal mucinous carcinomas. These analyses provide insights into the genomic landscapes and origins of mucinous and endometrioid ovarian carcinomas, providing new avenues for early clinical intervention and management of patients with these cancers. Significance: Integrative multi-omic analyses support a common tissue of origin between ovarian endometrioid and uterine endometrioid carcinomas but not between ovarian mucinous and gastric or pancreatic mucinous carcinomas.

ZNFX1 Functions as a Master Regulator of Epigenetically Induced Pathogen Mimicry and Inflammasome Signaling in Cancer

Abstract DNA methyltransferase (DNMT) and PARP inhibitors induce a stimulator of IFN gene–dependent pathogen mimicry response (PMR) in ovarian and other cancers. In this study, we showed that combining DNMT and PARP inhibitors upregulates expression of the nucleic acid sensor NFX1-type zinc finger–containing 1 (ZNFX1) protein. ZNFX1 mediated the induction of PMR in mitochondria, serving as a gateway for stimulator of IFN gene–dependent IFN/inflammasome signaling. Loss of ZNFX1 in ovarian cancer cells promoted proliferation and spheroid formation in vitro and tumor growth in vivo. In patient ovarian cancer databases, expression of ZNFX1 was elevated in advanced stage disease, and ZNFX1 expression alone significantly correlated with an increase in overall survival in a phase III trial for patients with therapy-resistant ovarian cancer receiving bevacizumab in combination with chemotherapy. RNA sequencing revealed an association between inflammasome signaling through ZNFX1 and abnormal vasculogenesis. Together, this study identified that ZNFX1 is a tumor suppressor that controls PMR signaling through mitochondria and may serve as a biomarker to facilitate personalized therapy in patients with ovarian cancer. Significance: DNMT and PARP inhibitors induce a nucleic acid sensor, ZNFX1, that serves as a mitochondrial gateway to STING-dependent inflammasome signaling with tumor suppressor properties in ovarian cancer.