Objectives: Oropharyngeal squamous cell carcinoma (OPSCC) incidence is rapidly increasing in the United States and around the world, driven in large part by infection with the human papillomavirus (HPV). HPV associated OPSCC (HPV+OPSCC) has been shown to have improved response to treatment relative to tobacco-associated OPSCC. However, improvement in patient survival has not been uniform. Subsets of OPSCC patients in the US and around the world continue to have poor oncologic outcomes. Although the drivers of this phenomenon remain unclear, there is increasing evidence that tobacco exposure plays an important role in modulating HPV+OPSCC clinical outcomes.
Methods: We conducted a review of the literature.
Results: We discuss the potential biological and epidemiological interplay between tobacco and HPV exposure in the context of OPSCC. Multiple retrospective and prospective cohorts show that HPV+OPSCC patients with a history of tobacco exposure have response to treatment and clinical outcomes distinct from HPV+OPSCC non-smokers which poses clinical and scientific challenges to be addressed over the next decade.
Conclusions: The interaction between tobacco exposure and HPV infection in the context of OPSCC has significant implications for both standard of care treatment regimens and development of novel therapeutic approaches, in particular those which incorporate immunomodulatory agents.
Level Of Evidence: 5.
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http://dx.doi.org/10.1002/lio2.316 | DOI Listing |
Ann Am Thorac Soc
January 2025
University of California San Francisco, Department of Epidemiology and Biostatistics, San Francisco, California, United States.
Rationale: Globally, in 2019, chronic obstructive pulmonary disease (COPD) was the third leading cause of death. While tobacco smoking is the predominant risk factor, the role of long-term air pollution exposure in increasing risk of COPD remains unclear. Moreover, there are few studies that have been conducted in racial and ethnic minoritized and socioeconomically diverse populations, while accounting for smoking history and other known risk factors.
View Article and Find Full Text PDFBiomol Biomed
January 2025
China Tobacco Sichuan Industrial Co., Ltd., Chengdu, China; Harmful Components and Tar Reduction in Cigarette Key Laboratory of Sichuan Province, Chengdu, China; Department of Biotherapy, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, China.
In recent years, the health challenges linked to frailty in the elderly, particularly those worsened by cigarette smoke, have become more pronounced. However, quantitative studies examining the impact of smoking dosage on frailty in this population remain limited. To address this gap, we developed a model using smoke-exposed elderly mice.
View Article and Find Full Text PDFJAMA Netw Open
January 2025
Herbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego.
Importance: The degree that in-home cannabis smoking can be detected in the urine of resident children is unclear.
Objective: Test association of in-home cannabis smoking with urinary cannabinoids in children living at home.
Design, Setting, And Participants: This cross-sectional study used baseline data from Project Fresh Air, a 2012-2016 randomized clinical trial to reduce fine particulate matter levels.
Mediators Inflamm
January 2025
Department of Blood Transfusion, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.
Tobacco smoke is known to contain numerous harmful chemicals, and epidemiological evidence has firmly established smoking as a potent risk factor for hypertension and myocardial infarction (MI). However, the precise mechanisms by which smoking contributes to cardiovascular disease are not fully understood. The aim of this study is to identify common molecular signatures in blood that link smoking to acute MI (AMI).
View Article and Find Full Text PDFToxicol Rep
June 2025
Division of Molecular Medicine, Bose Institute, Kolkata 700054, India.
Machine learning (ML) has the potential to transform tobacco research and address the urgent public health crisis posed by tobacco use. Despite the well-documented health risks, cessation rates remain low. ML techniques offer innovative solutions by analyzing vast datasets to uncover patterns in smoking behavior, genetic predispositions, and effective cessation strategies.
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