Tej Pandya

MB.ChB

Francis Crick Institute

Visiting Scientist

PLCO (Learn more about this study)

PLCO-1401

Dec 4, 2023

Mapping the progression of COPD to Lung Cancer

Air pollution, especially particulate matter with aerodynamic diameter of less than 2.5 micrometres (PM2.5) is known to be a cause of lung cancer (Huang, et al., 2017) and has also been linked to other cancers such as colorectal cancer (Jenwitheesuk, et al., 2020) (Wong, et al., 2016). Particulate matter with diameter < 10 micrometres can penetrate the lungs and enter the blood stream (Manisalidis, et al., 2020). Much of the body is likely exposed to air pollutants and hence vulnerable to any carcinogenic effect. We have previously shown that PM promotes lung cancer development via an inflammatory axis involving the influx of macrophages into the lung and the release of IL1β (Hill, Lim, Weeden, et al., 2023). By determining any relationship between these pollutants, host factors, and cancer types, we can examine the mechanism underlying this relationship, particularly whether the proposed inflammatory basis is evidenced.

We propose analysis of the PLCO study cohort. We will stratify the cohort by diagnosis of individual cancers with important and relevant co-variates, such as age, sex, BMI, and smoking status amongst others. Regression analyses will be utilised to analyse the relationship between air pollution measures and cancer outcomes as well as differences between males and females, whilst controlling for relevant covariates. We will explore the possibility of using deep learning to understand the progression to cancer from illnesses (e.g creating a neural network to map the progression of COPD). For those cancer types which are associated with air pollution, we will investigate the mechanistic basis for this relationship. This will be achieved through interrogating the data on participant medical histories, blood biomarkers, environmental exposures, and genomic data to determine whether specific factors mitigate or enhance the air pollution-induced risk of developing a certain cancer.

Aims:

• Elucidate the relationships between environmental exposures and cancer outcomes.
• Assess whether there are any differences between males and females, and by smoking status.
• Investigate interactions between environmental and host factors (for example genotypes) and how they affect cancer outcomes.
• Link insights from survey, health outcomes, and genetic data with blood biomarker data to yield mechanistic insights into how air pollution and sex dimorphisms might predispose to cancer risk.

Methods

Study Design
The study employs a cross-sectional and longitudinal design to elucidate the relationships between environmental exposures and cancer outcomes, assess differences by sex and smoking status, and investigate interactions between environmental exposures, host factors (genotypes), and cancer outcomes. The study integrates survey data, health outcomes, genetic data, and blood biomarker data to provide a comprehensive analysis. Where possible, we will try and harmonise our findings with other biobanks (e.g UK Biobank).

Participants

The study includes participants from the [Name of Biobank], a comprehensive biobank with diverse demographic representation. Participants will be stratified by gender and smoking status to facilitate subgroup analyses.

Data Sources (where applicable)
1. Survey Data:
- A structured survey capturing environmental exposures, lifestyle factors, and demographic information.
2. Health Outcomes Data:
- Comprehensive health records, including cancer diagnoses and relevant clinical information.
3. Genetic Data:
- Genotyping data providing information on host factors (genotypes).
4. Blood Biomarker Data:
- Comprehensive blood biomarker data, linking molecular information with health outcomes.