Pan-Cancer Mycobiome Analysis Platform to Predict Survival and Treatment Response

Background & Unmet Need

• The tumor microenvironment (TME) is a complex ecosystem of immune cells, extracellular matrix, blood vessels, and other cell types
• While the microbiome (bacteria) has been shown to participate in the TME and influence response to cancer treatments, the role of the mycobiome (fungi) is poorly understood
• For instance, the gut microbiome plays a significant role in whether patients respond to anti-PDL1 treatment
• An improved understanding of the TME and the role of bacteria and fungi may lead to the development of improved diagnostics and treatments
• Unmet Need: Improved platform for analyzing the tumor microbiome and mycobiome

Technology Overview

• The Technology: A computational platform to extract fungal sequences from sequencing data of human tumor samples
• The Discovery: Candida-to-S.Cerevisae ratio were predictive of metastatic colon cancer
• Fungal species, specifically C. albicans and S. Cerevisae species, are prognostic markers of disease progression and worse clinical outcomes of GI cancers
• PoC Data: Fungal species associate with primary tumor samples and with different stages of disease, specifically in GI tumors
• The technology provides a novel method of screening and stratifying cancer patients who may be candidates for antifungal therapy

Technology Applications

• Computational platform to identify tumor-associated fungal species
• Development of a prognostic resource specifically for GI cancers where the technology has identified Candida ssp. as markers for disease progression and outcome
• Identification of potentially druggable fungal species to improve patient outcome

Technology Advantages

• The technology offers a unique framework to detect tumor associated fungal species
• The insights gained through the application of the technology could identify new prognostic markers and inform new treatment strategies such as anti-fungal therapies
• Future advances in detection of fungal DNA in blood samples could allow non-invasive diagnostics