Clinical Informatics Approaches to Understand and Address Cancer Disparities.

OBJECTIVES: Disparities in cancer incidence and outcomes across race, ethnicity, gender, socioeconomic status, and geography are well-documented, but their etiologies are often poorly understood and multifactorial. Clinical informatics can provide tools to better understand and address these disparities by enabling high-throughput analysis of multiple types of data. Here, we review recent efforts in clinical informatics to study and measure disparities in cancer. METHODS: We carried out a narrative review of clinical informatics studies related to cancer disparities and bias published from 2018-2021, with a focus on domains such as real-world data (RWD) analysis, natural language processing (NLP), radiomics, genomics, proteomics, metabolomics, and metagenomics. RESULTS: Clinical informatics studies that investigated cancer disparities across race, ethnicity, gender, and age were identified. Most cancer disparities work within clinical informatics used RWD analysis, NLP, radiomics, and genomics. Emerging applications of clinical informatics to understand cancer disparities, including proteomics, metabolomics, and metagenomics, were less well represented in the literature but are promising future research avenues. Algorithmic bias was identified as an important consideration when developing and implementing cancer clinical informatics techniques, and efforts to address this bias were reviewed. CONCLUSIONS: In recent years, clinical informatics has been used to probe a range of data sources to understand cancer disparities across different populations. As informatics tools become integrated into clinical decision-making, attention will need to be paid to ensure that algorithmic bias does not amplify existing disparities. In our increasingly interconnected medical systems, clinical informatics is poised to untap the full potential of multi-platform health data to address cancer disparities.

NCOA4-Mediated Ferritinophagy Is a Pancreatic Cancer Dependency via Maintenance of Iron Bioavailability for Iron-Sulfur Cluster Proteins.

Pancreatic ductal adenocarcinomas (PDAC) depend on autophagy for survival; however, the metabolic substrates that autophagy provides to drive PDAC progression are unclear. Ferritin, the cellular iron storage complex, is targeted for lysosomal degradation (ferritinophagy) by the selective autophagy adaptor NCOA4, resulting in release of iron for cellular utilization. Using patient-derived and murine models of PDAC, we demonstrate that ferritinophagy is upregulated in PDAC to sustain iron availability, thereby promoting tumor progression. Quantitative proteomics reveals that ferritinophagy fuels iron-sulfur cluster protein synthesis to support mitochondrial homeostasis. Targeting NCOA4 leads to tumor growth delay and prolonged survival but with the development of compensatory iron acquisition pathways. Finally, enhanced ferritinophagy accelerates PDAC tumorigenesis, and an elevated ferritinophagy expression signature predicts for poor prognosis in patients with PDAC. Together, our data reveal that the maintenance of iron homeostasis is a critical function of PDAC autophagy, and we define NCOA4-mediated ferritinophagy as a therapeutic target in PDAC. SIGNIFICANCE: Autophagy and iron metabolism are metabolic dependencies in PDAC. However, targeted therapies for these pathways are lacking. We identify NCOA4-mediated selective autophagy of ferritin ("ferritinophagy") as upregulated in PDAC. Ferritinophagy supports PDAC iron metabolism and thereby tumor progression and represents a new therapeutic target in PDAC. See related commentary by Jain and Amaravadi, p. 2023. See related article by Ravichandran et al., p. 2198. This article is highlighted in the In This Issue feature, p. 2007.