May 7, 2026
For many oncologists, developing an early detection system for ovarian cancer is considered a holy grail. Screening for ovarian cancer is extremely challenging, as current screening tools lack the sensitivity and specificity to accurately determine if a tumor is malignant. Ovarian cancer is the 8th most common type of cancer in women, affecting more than 300,000 women worldwide. Furthermore, one in five women will be diagnosed with an adnexal mass, a tumor on the ovary, in their lifetime, and approximately 80% of those tumors turn out to be benign.
Because reliable tools to accurately distinguish benign from malignant adnexal masses remain limited, many women with suspicious ovarian masses are referred for surgical evaluation to determine whether a tumor is cancerous. Current biomarkers and risk assessment tools often have limited specificity, leading to frequent overdiagnosis and unnecessary surgical referrals, while still missing some early-stage ovarian cancers—when treatment is most effective. Early diagnosis can dramatically improve outcomes, with survival exceeding 90% for early-stage ovarian cancer compared with roughly 30% for advanced-stage. “The risk of not operating can be significant in cases where a tumor ultimately proves to be cancerous,” says Bodour Salhia, PhD, a professor of cancer biology at the University of Southern California’s Keck School of Medicine. “However, most of the cases are not malignant and these women could have received a much less invasive procedure. Improving the high-risk triage and referral system for women who have an ovarian mass is one of the biggest unmet clinical needs in women’s health.”
Salhia and her team of researchers have been studying early detection of ovarian cancer for years. Their work focuses on cell-free DNA methylation liquid biopsy for the risk assessment of ovarian cancer. This approach uses bisulfite sequencing to identify differentially methylated regions between cancerous and non-cancerous tissue, and they constructed a classifier, called OvaPrint, to discriminate between malignant and benign masses. However, detecting cancer-specific methylation signals in plasma is inherently challenging because tumor-derived DNA only represents a small fraction of total circulating DNA. The researchers needed an approach that could reliably capture these subtle signals.
A new approach beyond bisulfite sequencing
Recognizing the importance of Salhia’s research, Illumina provided her team with early access to the Illumina multiomics portfolio, including Illumina’s 5-base solution, Illumina Protein Prep, and Illumina Spatial Technology. Salhia’s team applied the 5-base solution to their tissue samples and found that it enabled high-accuracy methylation and genomic variant detection, preserved DNA integrity, and retained library complexity with exceptional efficiency. The research team then applied the 5-base solution to plasma samples to determine if it could help identify the hard-to-detect histological classes of tumors that OvaPrint had misclassified. They found that the 5-base solution provided better class separation—recovering the false negative cases and separating malignant and benign adnexal masses much better than traditional methods.
Salhia and her team also explored whether a multiomic strategy could provide additional biological insight. By layering Illumina Protein Prep and Illumina Spatial Technology on top of the 5-base methylation approach, they were able to capture complementary signals, including protein expression and spatial tissue context. While still preliminary, this work highlights the potential of multiomic approaches to deepen understanding of tumor biology and inform future liquid biopsy strategies.
“Multiomics gave us deeper insight into the biology behind the plasma signals and how they relate to tumor architecture and activity,” says Salhia. “Having protein, methylation, and spatial data together in one place made it much easier to interpret those signals and understand what was driving classification or misclassification.”
“Multiomics gave us deeper insight... Having protein, methylation, and spatial data together in one place made it much easier to interpret signals and understand what was driving classification or misclassification.”
Salhia’s research using the Illumina Connected Multiomics portfolio helped clarify underlying ovarian tumor biology driving false positive and false negative results. It also enabled them to conduct gene enrichment and pathway analysis, which uncovered novel molecular pathways in ovarian cancer—insights that could help address critical unmet needs in oncology care. “It’s about identifying the right combination of biomarkers and testing different approaches to see which technologies deliver the best results,” says Salhia. “When we get the combination right, it’s phenomenal—and it deepens our understanding of ovarian cancer, guides diagnosis and treatment decisions, and advances drug development.” Salhia hopes that integrated technologies such as multiomics will deliver earlier, more accurate diagnostics for ovarian cancer in the near future. For patients, that progress could mean fewer invasive procedures, clearer treatment decisions, more timely care, and better outcomes when it matters most.
“It’s an exciting time to be a genomics scientist,” says Salhia. “I’m grateful for this journey and the people who made it possible, and I’m inspired by the innovators who have transformed biotechnology and enabled us to conduct complex research that could ultimately improve patient care.”
To learn more about multiomics, follow this link.
To read about the advocates behind the World Ovarian Cancer Coalition, follow this link.
To read about an ovarian cancer survivor in Brazil who founded a nonprofit to educate patients, follow this link.
