Detectable Lipidomes and Metabolomes by Different Plasma Exosome Isolation Methods in Healthy Controls and Patients with Advanced Prostate and Lung Cancer.

Circulating exosomes in the blood are promising tools for biomarker discovery in cancer. Due to their heterogeneity, different isolation methods may enrich distinct exosome cargos generating different omic profiles. In this study, we evaluated the effects of plasma exosome isolation methods on detectable multi-omic profiles in patients with non-small cell lung cancer (NSCLC), castration-resistant prostate cancer (CRPC), and healthy controls, and developed an algorithm to quantify exosome enrichment. Plasma exosomes were isolated from CRPC (n = 10), NSCLC (n = 14), and healthy controls (n = 10) using three different methods: size exclusion chromatography (SEC), lectin binding, and T-cell immunoglobulin domain and mucin domain-containing protein 4 (TIM4) binding. Molecular profiles were determined by mass spectrometry of extracted exosome fractions. Enrichment analysis of uniquely detected molecules was performed for each method with MetaboAnalyst. The exosome enrichment index (EEI) scores methods based on top differential molecules between patient groups. The lipidomic analysis detected 949 lipids using exosomes from SEC, followed by 246 from lectin binding and 226 from TIM4 binding. The detectable metabolites showed SEC identifying 191 while lectin binding and TIM4 binding identified 100 and 107, respectively. When comparing uniquely detected molecules, different methods showed preferential enrichment of different sets of molecules with SEC enriching the greatest diversity. Compared to controls, SEC identified 28 lipids showing significant difference in NSCLC, while only 1 metabolite in NSCLC and 5 metabolites in CRPC were considered statistically significant (FDR < 0.1). Neither lectin-binding- nor TIM4-binding-derived exosome lipids or metabolites demonstrated significant differences between patient groups. We observed the highest EEI from SEC in lipids (NSCLC: 871.33) which was also noted in metabolites. These results support that the size exclusion method of exosome extraction implemented by SBI captures more heterogeneous exosome populations. In contrast, lectin-binding and TIM4-binding methods bind surface glycans or phosphatidylserine moieties of the exosomes. Overall, these findings suggest that specific isolation methods select subpopulations which may significantly impact cancer biomarker discovery.

Factors associated with self-reported social isolation among patients with cancer during the COVID-19 pandemic.

OBJECTIVE: We aimed to identify patient-level demographic and behavioral characteristics associated with higher social isolation among patients with cancer throughout the coronavirus disease 2019 (COVID-19) pandemic. METHOD: Moffitt Cancer Center patients seen on or after January 1, 2015, had a last known alive vital status, a valid e-mail address, and were 18-89 years old, were emailed a survey regarding social isolation. We collected information on age, sex, race, ethnicity, marital status, smoking, self-reported cancer diagnosis, cancer treatment, and perceived life changes due to the COVID-19 pandemic. We calculated a COVID-19 risk mitigation score by summing the frequency of risk mitigation behaviors (e.g., mask wearing). Social isolation was assessed with the self-reported Patient-Reported Outcomes Measurement Information System (PROMIS) Social Isolation Short Form. Logistic regression models compared characteristics of participants reporting higher versus lower social isolation (T-scores >60 vs. ≤60). RESULTS: Most participants (N = 9,579) were female (59.2%), White (93.0%), and non-Hispanic (92.5%). Participants at greater odds of higher social isolation were younger (per 10 years decrease odds ratio [OR] = 1.36, 95% confidence interval, CI [1.30, 1.43]), female (vs. male OR = 1.54, 95% CI [1.36, 1.74]), unmarried (vs. married OR = 1.83, 95% CI [1.62, 2.08]), current smokers (vs. never OR = 2.38, 95% CI [1.88, 3.00]), reporting more risk mitigation behaviors (per 1 SD; OR = 1.33, 95% CI [1.24, 1.42]), and more perceived life changes (vs. little/no change; OR = 2.64, 95% CI [2.08, 3.35]). CONCLUSIONS: We identified younger age, females, unmarried, current smokers, more risk mitigation behaviors, and more perceived life changes increased odds of social isolation for patients with cancer during the COVID-19 pandemic. This can inform identification of patients with cancer at higher risk of social isolation for targeted mitigation strategies. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Quantitative Assessment of Visceral Obesity and Postoperative Colon Cancer Outcomes.

BACKGROUND: Quantitative computed tomography (CT) assessment of visceral adiposity may be superior to body mass index (BMI) as a predictor of surgical morbidity. We sought to examine the association of CT measures of obesity and BMI with short-term postoperative outcomes in colon cancer patients. METHODS: In this retrospective study, 110 patients treated with colectomy for stage I-III colon cancer were classified as obese or non-obese by preoperative CT-based measures of adiposity or BMI [obese: BMI ≥ 30 kg/m2, visceral fat area (VFA) to subcutaneous fat area ratio (V/S) ≥0.4, and VFA > 100 cm2]. Postoperative morbidity and mortality rates were compared. RESULTS: Obese patients, by V/S and VFA but not BMI, were more likely to be male and have preexisting hypertension and diabetes. The overall complication rate was 25.5%, and there were no mortalities. Obese patients by VFA (with a trend for V/S but not BMI) were more likely to develop postoperative complications as compared to patients classified as non-obese: VFA (30.5 vs.10.7%, p = 0.03), V/S (29.2 vs. 9.5%, p = 0.05), and BMI (32.4 vs. 21.9%, p = 0.23). CONCLUSIONS: Elevated visceral obesity quantified by CT is associated with the presence of key metabolic comorbidities and increased postoperative morbidity and may be superior to BMI for risk stratification.