Ranran Wu

Cumulative incidence curves of the PFAP signature stratified by risk categories (Q denotes risk quartiles), comparing lung cancer–specific mortality, mortality from other cancers, and non-cancer–related mortality.

Pairwise correlations among quantified forever-plastics and phthalates in entire PLCO cohort.

Supplementary Table 1. Detectable microplastics (MP), per- and polyfluoroalkyl substances (PFAS), and plasticizers (BPA and phthalates) in the internal mass spectrometry database. Supplemental Table S2. Patient characteristics for the Development and Validation Set. Supplementary Table S3. Association between detected PFAS and plasticizers with lung cancer incidence when adjusting for age and smoking as confounding variables. Supplementary Table S4. Association between detected PFAS and plasticizers with lung cancer incidence in the entire PLCO dataset when stratifying samples into quantiles. Supplementary Table S5. Association between detected PFAS and plasticizers with lung cancer incidence stratifying by sex in the entire PLCO dataset. Supplementary Table S6. Association between detected PFAS and plasticizers with lung cancer incidence stratifying by age in the entire PLCO dataset. Supplementary Table S7. Association between detected PFAS and plasticizers with lung cancer incidence stratifying by smoking intensity in the entire PLCO dataset. Supplementary Table S8. Association between detected PFAS and plasticizers with lung cancer incidence stratifying by ethnicity in the entire PLCO dataset. Supplementary Table S9. Association between detected PFAS and plasticizers with lung cancer incidence in the entire PLCO specimen set when stratifying by stage at diagnosis. Supplementary Table S10. Association between detected PFAS and plasticizers with lung cancer incidence in the entire PLCO specimen set when stratifying by lung cancer subtype at the time of clinical diagnosis. Supplementary Table S11: Causes of death for the participants in the PLCO cohort. Supplementary Table S12. Association between detected PFAS and plasticizers with lung cancer mortality in the entire PLCO dataset using cause-specific hazard ratios. Supplementary Table 13. Association between detected PFAS and plasticizers with lung cancer mortality using cause-specific hazard ratio in the entire PLCO dataset when adjusting for age and smoking intensity. Supplementary Table S14. Association between detected PFAS and plasticizers with lung cancer mortality in the entire PLCO dataset using cause-specific hazard ratios stratifying by sex. Supplementary Table S15. Association between detected PFAS and plasticizers with lung cancer mortality in the entire PLCO dataset using cause-specific hazard ratios stratifying by age. Supplementary Table S16. Association between detected PFAS and plasticizers with lung cancer mortality in the entire PLCO dataset using cause-specific hazard ratios stratifying by smoking intensity. Supplementary Table S17. Association between detected PFAS and plasticizers with lung cancer mortality in the entire PLCO dataset using cause-specific hazard ratios stratifying by ethnicity. Supplementary Table S18. Association between detected PFAS and plasticizers with lung cancer mortality in the entire PLCO dataset using cause-specific hazard ratios stratifying by stage at diagnosis. Supplementary Table S19. Association between detected PFAS and plasticizers with lung cancer mortality in the entire PLCO dataset using cause-specific hazard ratios stratifying by lung cancer subtype at the time of clinical diagnosis. Supplementary Table S20. Association between detected PFAS and plasticizers with lung cancer mortality in the entire PLCO dataset using sub-distributional hazard ratio. Supplementary Table 21. Association between detected PFAS and plasticizers with lung cancer mortality using sub-distributional hazard ratio in the entire PLCO dataset when adjusting for age and smoking intensity. Supplementary Table S22. Association between detected PFAS and plasticizers with lung cancer mortality in the entire PLCO dataset using sub-distributional hazard ratio stratifying by sex. Supplementary Table S23. Association between detected PFAS and plasticizers with lung cancer mortality in the entire PLCO dataset using sub-distributional hazard ratio stratifying by age. Supplementary Table S24. Association between detected PFAS and plasticizers with lung cancer mortality in the entire PLCO dataset using sub-distributional hazard ratio stratifying by smoking intensity. Supplementary Table S25. Association between detected and plasticizers with lung cancer mortality in the entire PLCO dataset using sub-distributional hazard ratio stratifying by ethnicity. Supplementary Table S26. Association between detected PFAS and plasticizers with lung cancer mortality in the entire PLCO dataset using sub-distributional hazard ratio stratifying by stage at diagnosis. Supplementary Table S27. Association between detected PFAS and plasticizers with lung cancer mortality in the entire PLCO dataset using sub-distributional hazard ratio stratifying by lung cancer subtype at the time of clinical diagnosis. Supplementary Table S28. Association between the PFAP model with lung cancer mortality using cause-specific and sub-distributional hazard ratio in the PLCO Development and Testing sets. Supplementary Table S29. Variance inflation factors for features included in the PFAP model. Supplementary Table S30. Likelihood ratio test P values comparing linear and cubic spline Cox models for associations with survival. Supplementary Table S31. Continuous hazard ratios for lung cancer–specific mortality using a cause-specific approach for PFAP under different sampling approach. Supplementary Table S32. Association between the PFAP model with lung-cancer mortality using cause-specific and sub-distributional hazard ratio in the entire PLCO dataset when adjusting for age, sex, BMI, smoking status, education, and emphysema. Supplementary Table S33. Association between the PFAP model with lung-cancer mortality using cause-specific and sub-distributional hazard ratio in the entire PLCO dataset when excluding deaths within 1-, 2-, and 5-years after sample collection. Supplementary Table S34. Performance estimates (AUC and C-index) of the PFAP model...

Purpose:Recent evidence suggests a significant association between microplastic (MP), forever chemicals, and plasticizers and various diseases, including cancer. In this study, we evaluated circulating levels of plastic-associated chemicals in relation to lung cancer incidence and mortality among smokers in the Prostate, Lung, Colorectal, and Ovarian (PLCO) study.Experimental Design:Using mass spectrometry, we screened for 29 known MP, forever plastics [per- and polyfluoroalkyl substances (PFAS)], and plasticizer chemicals in 245 sera collected preceding a lung cancer diagnosis and 1,200 noncase sera from participants in the PLCO study who had a history of smoking. Five PFAS and three plasticizers were detected and quantified in sera. A PFAP model, consisting of perfluorooctane sulfonate (PFOS) + perfluorohexanesulfonic acid (PFHA) + mono-iso-nonyl phthalate, was developed for predicting lung cancer mortality and risk strata based on quantiles established.Results:Higher circulating levels of PFOS, PFHA, and mono-iso-nonyl phthalate were associated with increased risk of lung cancer death (P < 0.05) but not incidence. Compared with the lowest quantile (reference), individuals with PFAP scores in the highest quantile were at markedly higher risk of death from lung cancer (P < 0.0001), with respective cause-specific and subdistributional HR of 1.86 [95% confidence interval (CI), 1.18–2.93] and 1.82 (95% CI, 1.15–2.88). Substratified analyses confirmed that the PFAP model remained an independent predictor of lung cancer–specific mortality (P < 0.05) across strata defined by age, sex, smoking history, histologic subtype, and stage at diagnosis.Conclusions:In the PLCO cohort, elevated levels of PFOS, PFHA, and mono-iso-nonyl phthalate were associated with increased lung cancer mortality among ever smokers across disease subgroups.

Calibration plot of the PFAP model comparing predicted and observed lung cancer–specific mortality risk at 5-, 10-, and 15-years following blood collection.

Purpose: Recent evidence suggests a significant association between microplastic (MP), forever chemicals, and plasticizers and various diseases, including cancer. In this study, we evaluated circulating levels of plastic-associated chemicals in relation to lung cancer incidence and mortality among smokers in the Prostate, Lung, Colorectal, and Ovarian (PLCO) study. Experimental Design: Using mass spectrometry, we screened for 29 known MP, forever plastics [per- and polyfluoroalkyl substances (PFAS)], and plasticizer chemicals in 245 sera collected preceding a lung cancer diagnosis and 1,200 noncase sera from participants in the PLCO study who had a history of smoking. Five PFAS and three plasticizers were detected and quantified in sera. A PFAP model, consisting of perfluorooctane sulfonate (PFOS) + perfluorohexanesulfonic acid (PFHA) + mono-iso-nonyl phthalate, was developed for predicting lung cancer mortality and risk strata based on quantiles established. Results: Higher circulating levels of PFOS, PFHA, and mono-iso-nonyl phthalate were associated with increased risk of lung cancer death (P < 0.05) but not incidence. Compared with the lowest quantile (reference), individuals with PFAP scores in the highest quantile were at markedly higher risk of death from lung cancer (P < 0.0001), with respective cause-specific and subdistributional HR of 1.86 [95% confidence interval (CI), 1.18–2.93] and 1.82 (95% CI, 1.15–2.88). Substratified analyses confirmed that the PFAP model remained an independent predictor of lung cancer–specific mortality (P < 0.05) across strata defined by age, sex, smoking history, histologic subtype, and stage at diagnosis. Conclusions: In the PLCO cohort, elevated levels of PFOS, PFHA, and mono-iso-nonyl phthalate were associated with increased lung cancer mortality among ever smokers across disease subgroups.

Figure S3. (A) Average time that study participants wore the Fitbit throughout the study; (B) Resting heart rate in study participants at baseline; (C) Average total minutes of exercise at heart rate 70-85% of PHR; (D) Average total minutes of exercise at heart rate >85% of PHR. (***, P ≤0.001; ****, P≤0.0001).

Table S3. Number of patients experiencing adverse events. Only those toxicities experienced while on the trial are presented in the table. Toxicities during the pre-study stage of the trial, for example, that were present before participants begin intervention were not included. Should a patient experience an adverse event more than once, the patient is only counted once at the highest grade for that adverse event.

Figure S2. CYCLE-P trial study visits and follow-up.

Figure S8. (A) Volcano plot of statistically significant genes and fold-changes between the usual care and exercise groups in DSP assay. Top significantly differentially expressed genes are labeled; (B) The dot plot presents enriched GSEA HALLMARK pathways. The sizes of the dots represent the count of core enrichment (leading-edge) genes. The colors of the dots represent the BH-adjusted P-values. The order of HALLMARK gene sets is based on the gene ratio (number of significant genes associated with the HALLMARK gene sets / total number of significant genes; (C) Total CD8+ T cell density per mm2 (left) and epithelial (right) in colonic mucosa preand post- intervention from usual care (n=4) and exercise (n=4) participants; (D) Total CD57+ NK cell density per mm2 (left) and epithelial (right) in colonic mucosa pre- and post- intervention from usual care (n=4) and exercise (n=4) participants.