Objective: Although the incidence of lung cancer has decreased over the past decades, disparities in survival and treatment modalities have been observed for black and white patients with early-stage non-small cell lung cancer, despite the fact that surgical resection has been established as the standard of care. Possible contributors to these disparities are stage at diagnosis, comorbidities, socioeconomic factors, and patient preference. This study examines racial disparities in treatment, adjusting for clinicodemographic factors.Methods: The Surveillance, Epidemiology, and End Results-Medicare dataset was queried to identify patients diagnosed with primary stage I non-small cell lung cancer between 1992 and 2009. Multivariable logistic regressions were performed to assess the association between race and treatment modalities within 1 year of diagnosis, adjusted for clinical and demographic factors. Adjusted Cox proportional hazards models were performed to evaluate disparities in survival, accounting for mode of treatment.Results: We identified 22,724 patients; 21,230 (93.4%) white and 1494 (6.6%) black. Black patients were less likely to receive treatment (odds ratio [OR] adj , 0.62; 95% confidence interval [CI], 0.53-0.73) and less likely to receive surgery only when treated (OR adj , 0.70, 95% CI, 0.61-0.79). Although univariate survival for black patients was worse, when accounting for treatment mode, there was no difference in survival (hazard ratio adj , 0.97; 95% CI, 0.90-1.04 for all patients, hazard ratio adj , 0.98; 95% CI: 0.90-1.06 for treated patients).Conclusions: Treatment disparities persist, even when adjusting for clinical and demographic factors. However, when black patients receive similar treatment, survival is comparable with white patients.

Hepatocellular carcinoma (HCC) is the most common primary liver malignancy and one of the leading causes of cancer-related death worldwide. Despite the improvements in surveillance and treatment, the prognosis of HCC remains poor. Extracellular vesicles (EVs) are a heterogeneous group of phospholipid bilayer-enclosed particles circulating in the bloodstream and mediating intercellular communication. Emerging studies have shown that EVs play a crucial role in regulating the proliferation, immune escape, and metastasis of HCC. In addition, because EVs are present in the circulation at relatively early stages of disease, they are getting attention as an attractive biomarker for HCC detection. Over the past decade, dedicated efforts have been made to isolate EVs more efficiently and make them useful tools in different clinical settings. In this review article, we provide an overview of the EVs isolation methods and highlight the role of EVs as mediators in the pathogenesis and progression of HCC. Lastly, we summarize the potential applications of EVs in early-stage HCC detection.

Acute nicotine administration has been shown to activate the hypothalamic-pituitary-adrenal (HPA) axis and stimulate secretion of adrenocorticotrophic hormone (ACTH), corticosterone/cortisol and b-endorphin (beta-END) in both rodents and humans, raising the possibility that activation of the HPA axis by nicotine may mediate some of the effects of nicotine. Since stress can increase the risk of drug use and abuse, we hypothesized that repeated stress would increase the ability of nicotine to stimulate the secretion of HPA hormones. To test our hypothesis, mice were exposed to repeated stress (swimming in 15°C water for 3 min/day for 5 days) and killed 15 min after injection of saline or nicotine (0.1 mg/kg, s.c.). Repeated exposure to stress increased the ability of nicotine to stimulate plasma ACTH (p < 0.05) and beta-END (p < 0.05), but not corticosterone secretion. In contrast, repeated exposure to stress increased the post-saline injection levels of corticosterone (p < 0.05), but not ACTH and beta-END. The present results suggest that chronic stress leads to an enhanced sensitivity of some components of the HPA axis to a subsequent nicotine challenge.

Early cancer detection by cell-free DNA faces multiple challenges: low fraction of tumor cell-free DNA, molecular heterogeneity of cancer, and sample sizes that are not sufficient to reflect diverse patient populations. Here, we develop a cancer detection approach to address these challenges. It consists of an assay, cfMethyl-Seq, for cost-effective sequencing of the cell-free DNA methylome (with > 12-fold enrichment over whole genome bisulfite sequencing in CpG islands), and a computational method to extract methylation information and diagnose patients. Applying our approach to 408 colon, liver, lung, and stomach cancer patients and controls, at 97.9% specificity we achieve 80.7% and 74.5% sensitivity in detecting all-stage and early-stage cancer, and 89.1% and 85.0% accuracy for locating tissue-of-origin of all-stage and early-stage cancer, respectively. Our approach cost-effectively retains methylome profiles of cancer abnormalities, allowing us to learn new features and expand to other cancer types as training cohorts grow.

Well-preserved molecular cargo in circulating extracellular vesicles (EVs) offers an ideal material for detecting oncogenic gene alterations in cancer patients, providing a noninvasive diagnostic solution for detection of disease status and monitoring treatment response. Therefore, technologies that conveniently isolate EVs with sufficient efficiency are desperately needed. Here, a lipid labeling and click chemistry-based EV capture platform ("Click Beads"), which is ideal for EV message ribonucleic acid (mRNA) assays due to its efficient, convenient, and rapid purification of EVs, enabling downstream molecular quantification using reverse transcription digital polymerase chain reaction (RT-dPCR) is described and demonstrated. Ewing sarcoma protein (EWS) gene rearrangements and kirsten rat sarcoma viral oncogene homolog (KRAS) gene mutation status are detected and quantified using EVs isolated by Click Beads and matched with those identified in biopsy specimens from Ewing sarcoma or pancreatic cancer patients. Moreover, the quantification of gene alterations can be used for monitoring treatment responses and disease progression.