Environmental Mixtures and Breast Cancer: Identifying Co-Exposure Patterns between Understudied vs Breast Cancer-Associated Chemicals using Chemical Inventory Informatics

Background: Although evidence linking environmental chemicals to breast cancer is growing, mixtures-based exposure evaluations are lacking. Objective: This study aimed to identify environmental chemicals in use inventories that co-occur and share properties with chemicals that have association with breast cancer, highlighting exposure combinations that may alter disease risk. Methods: The occurrence of chemicals within chemical use categories was characterized using the Chemical and Products Database. Co-exposure patterns were evaluated for chemicals that have an association with breast cancer (BC), no known association (NBC), and understudied chemicals (UC) identified through query of the Silent Spring Institute’s Mammary Carcinogens Review Database and the U.S. Environmental Protection Agency’s Toxicity Reference Database. UCs were ranked based on structure and physicochemical similarities and co-occurrence patterns with BCs within environmentally relevant exposure sources. Results: A total of 6,793 chemicals had data available for exposure source occurrence analyses. 50 top-ranking UCs spanning five clusters of co-occurring chemicals were prioritized, based on shared properties with co-occuring BCs, including chemicals used in food production and consumer/personal care products, as well as potential endocrine system modulators. Significance: Results highlight important co-exposure conditions that are likely prevalent within our everyday environments that warrant further evaluation for possible breast cancer risk.

The scalable nature of this framework allows for the introduction of new keywords and keyword kinds as the dataset grows. In CPDat version 3, the Chemical List Presence dataset includes 136 keywords grouped into 11 keyword kinds. Keywords were manually assigned to each chemical record in the Chemical List Presence dataset after evaluating the contents of the primary source to determine the use of the chemical being described. A level of caution was exercised to not make assumptions or propagate unsubstantiated claims regarding the chemical's use, focusing the assignment of keywords strictly on information presented in the primary data source. Additionally, care was taken to avoid the assignment of conflicting keywords and to limit the room for subjective user interpretation of a cassette. Resulting keyword cassettes provide a concise overview of an individual chemical's use, according to the primary source.
A listing of keyword kinds included in the CPDat version 3 release can be found in Table  SM1. Keywords, along with their definition and assigned keyword kind, can be found in Table  SM2. As an illustrative example of the keyword assignment process, consider a report from the California Department of Pesticide Regulation that chronicles the use trends of pesticides on California's Proposition 65 list that are known to be reprotoxic. Individual chemicals in this report received a cassette {Pesticides}, as this is what could be confidently inferred about the chemicals' use according to the original document. Another primary source from the Danish Environmental Protection Agency details hundreds of chemicals associated with children's personal care products such as shampoo, bodywash, soap, and lotion. These chemicals were assigned keywords resulting in the cassette {children; Europe; Personal Care}. This cassette should be interpreted as there is a relation between the chemical and a personal care product labeled for use by children in Europe. It is important to note that this cassette does not imply a detectable presence of the chemical, as the results of this report were largely based on the declaration of contents for many of the listed products.
It was common for keywords belonging to certain kinds to be used as part of the same cassette, for example, keywords belong to the PUC and Modifier kinds. Combining a keyword belonging to the Modifier kind ("detected") and a keyword belonging to the PUC kind ("Personal Care -dental care -toothpaste") creates the keyword cassette {"detected"; "Personal Caredental care -toothpaste"}. A chemical record would be assigned this cassette if the chemical was tested for and found in toothpaste. Modifiers were also commonly used alongside keywords belonging to the Media kind and the Foods & Agriculture kind, to describe a chemical's presence in specific media or food related substances. The keyword cassette {nondetect; Pesticides; surface_water}, for instance, should be interpreted as a chemical identified as a pesticide, was tested for, but not found, in surface water. Table SM1. Keyword Kinds with definitions included in CPDat version 3. PUC kinds (PUCarticle, PUC-formulation, and PUC-industrial) were built upon the previously defined PUC system, a hierarchical system for categorizing consumer products to aid in exposure assessments (Isaacs et al. 2020). PUC kind keywords always refer to a product, and the assimilation of the PUC system into this dataset allows for the integration of Chemical List Presence data with other data in CPDat.

Keyword Kind Definition
Foods & Agriculture related to food and agriculture   Figure S1A. Total sum of squares and silhouette profile for determining the optimal number of chemical clusters (k) where 1 k  100. Figure S1B. Total sum of squares and silhouette profile for determining the optimal number of exposure source category clusters (k) where 1 k  31. Figure S2. Distribution of enriched structural features across all UCs evaluated within CPDat (N=6,306 total). Here, 'enriched structural features' were identified as ToxPrint chemotypes that were significantly more commonly present in BCs in comparison to NBCs. Note the y-axis starts at 1.

Figure S3. Distribution of physicochemical correlations between UCs and BCs.
Correlations were calculated on a per-cluster basis and combined for visualization.