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1. Cell. 2024 Jan 4;187(1):184-203.e28. doi: 10.1016/j.cell.2023.12.004.

Proteogenomic characterization of small cell lung cancer identifies biological

insights and subtype-specific therapeutic strategies.

Liu Q(1), Zhang J(2), Guo C(3), Wang M(4), Wang C(5), Yan Y(2), Sun L(2), Wang

D(2), Zhang L(6), Yu H(2), Hou L(7), Wu C(7), Zhu Y(2), Jiang G(2), Zhu H(8),

Zhou Y(8), Fang S(8), Zhang T(4), Hu L(3), Li J(9), Liu Y(10), Zhang H(11),

Zhang B(12), Ding L(13), Robles AI(14), Rodriguez H(14), Gao D(15), Ji H(16),

Zhou H(17), Zhang P(18).

Author information:

(1)Department of Thoracic Surgery, Shanghai Pulmonary Hospital, School of

Medicine, Tongji University, Shanghai 200433, China; Department of Analytical

Chemistry, State Key Laboratory of Drug Research, Shanghai Institute of Materia

Medica, Chinese Academy of Sciences, Shanghai 201203, China.

(2)Department of Thoracic Surgery, Shanghai Pulmonary Hospital, School of

Medicine, Tongji University, Shanghai 200433, China.

(3)State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and

Cell Biology, CAS Center for Excellence in Molecular Cell Science, Chinese

Academy of Sciences, Shanghai 200031, China.

(4)State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and

Cell Biology, CAS Center for Excellence in Molecular Cell Science, Chinese

Academy of Sciences, Shanghai 200031, China; University of Chinese Academy of

Sciences, Beijing 100049, China.

(5)Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration of

Ministry of Education, Department of Orthopedics, Tongji Hospital, School of

Life Sciences and Technology, Tongji University, Shanghai 200092, China;

Frontier Science Center for Stem Cells, School of Life Sciences and Technology,

Tongji University, Shanghai 200092, China.

(6)Central Laboratory, Shanghai Pulmonary Hospital, School of Medicine, Tongji

University, Shanghai 200433, China.

(7)Department of Pathology, Shanghai Pulmonary Hospital, School of Medicine,

Tongji University, Shanghai 200433, China.

(8)Department of Analytical Chemistry, State Key Laboratory of Drug Research,

Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai

201203, China.

(9)D1 Medical Technology, Shanghai 201800, China.

(10)Cancer Biology Institute, Yale University School of Medicine, West Haven, CT

06516, USA.

(11)Department of Pathology, Johns Hopkins University School of Medicine,

Baltimore, MD 21287, USA.

(12)Lester and Sue Smith Breast Center, Baylor College of Medicine, Houston, TX

77030, USA.

(13)Department of Medicine, McDonnell Genome Institute, Washington University,

St. Louis, MO 63108, USA.

(14)Office of Cancer Clinical Proteomics Research, National Cancer Institute,

National Institutes of Health, Rockville, MD 20850, USA.

(15)State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and

Cell Biology, CAS Center for Excellence in Molecular Cell Science, Chinese

Academy of Sciences, Shanghai 200031, China; University of Chinese Academy of

Sciences, Beijing 100049, China; Key Laboratory of Systems Health Science of

Zhejiang Province, School of Life Science, Hangzhou Institute for Advanced

Study, University of Chinese Academy of Sciences, Hangzhou 310024, China.

Electronic address: dgao@sibcb.ac.cn.

(16)State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and

Cell Biology, CAS Center for Excellence in Molecular Cell Science, Chinese

Academy of Sciences, Shanghai 200031, China; University of Chinese Academy of

Sciences, Beijing 100049, China; Key Laboratory of Systems Health Science of

Zhejiang Province, School of Life Science, Hangzhou Institute for Advanced

Study, University of Chinese Academy of Sciences, Hangzhou 310024, China; School

of Life Science and Technology, Shanghai Tech University, Shanghai 200120,

China. Electronic address: hbji@sibcb.ac.cn.

(17)Department of Analytical Chemistry, State Key Laboratory of Drug Research,

Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai

201203, China; University of Chinese Academy of Sciences, Beijing 100049, China;

School of Pharmaceutical Science and Technology, Hangzhou Institute for Advanced

Study, University of Chinese Academy of Sciences, Hangzhou 310024, China.

Electronic address: zhouhu@simm.ac.cn.

(18)Department of Thoracic Surgery, Shanghai Pulmonary Hospital, School of

Medicine, Tongji University, Shanghai 200433, China. Electronic address:

zhangpeng1121@tongji.edu.cn.

Comment in

    Cell. 2024 Jan 4;187(1):14-16.

We performed comprehensive proteogenomic characterization of small cell lung

cancer (SCLC) using paired tumors and adjacent lung tissues from 112

treatment-naive patients who underwent surgical resection. Integrated

multi-omics analysis illustrated cancer biology downstream of genetic

aberrations and highlighted oncogenic roles of FAT1 mutation, RB1 deletion, and

chromosome 5q loss. Two prognostic biomarkers, HMGB3 and CASP10, were

identified. Overexpression of HMGB3 promoted SCLC cell migration via

transcriptional regulation of cell junction-related genes. Immune landscape

characterization revealed an association between ZFHX3 mutation and high immune

infiltration and underscored a potential immunosuppressive role of elevated DNA

damage response activity via inhibition of the cGAS-STING pathway. Multi-omics

clustering identified four subtypes with subtype-specific therapeutic

vulnerabilities. Cell line and patient-derived xenograft-based drug tests

validated the specific therapeutic responses predicted by multi-omics subtyping.

This study provides a valuable resource as well as insights to better understand

SCLC biology and improve clinical practice.

Copyright © 2023 Elsevier Inc. All rights reserved.

DOI: 10.1016/j.cell.2023.12.004

PMID: 38181741 [Indexed for MEDLINE]

Conflict of interest statement: Declaration of interests J.L. is an employee of

D1 Medical Technology.

2. J Thorac Oncol. 2024 Jan;19(1):80-93. doi: 10.1016/j.jtho.2023.09.004. Epub 2023

Sep 12.

Bidirectional Association Between Cardiovascular Disease and Lung Cancer in a

Prospective Cohort Study.

Zhang S(1), Liu L(2), Shi S(3), He H(4), Shen Q(1), Wang H(1), Qin S(1), Chang

J(1), Zhong R(5).

Author information:

(1)Department of Epidemiology and Biostatistics and Ministry of Education Key

Laboratory of Environment and Health, School of Public Health, Tongji Medical

College, Huazhong University of Science and Technology, Wuhan, People's Republic

of China.

(2)Division of Cardiology, Department of Internal Medicine, Tongji Hospital,

Tongji Medical College, Huazhong University of Science and Technology, Wuhan,

People's Republic of China.

(3)Department of Pathology, The First Affiliated Hospital of Nanjing Medical

University, Nanjing, Jiangsu, People's Republic of China.

(4)Department of Epidemiology and Health Statistics, School of Public Health,

Fujian Medical University, Fuzhou, People's Republic of China.

(5)Department of Epidemiology and Biostatistics and Ministry of Education Key

Laboratory of Environment and Health, School of Public Health, Tongji Medical

College, Huazhong University of Science and Technology, Wuhan, People's Republic

of China. Electronic address: zhongr@hust.edu.cn.

INTRODUCTION: The study aimed to prospectively investigate the bidirectional

association between cardiovascular disease (CVD) and lung cancer, and whether

this association differs across genetic risk levels.

METHODS: This study prospectively followed 455,804 participants from the United

Kingdom Biobank cohort who were free of lung cancer at baseline. Cox

proportional hazard models were used to estimate the hazard ratio (HR) for

incident lung cancer according to CVD status. In parallel, similar approaches

were used to assess the risk of incident CVD according to lung cancer status

among 478,756 participants free of CVD at baseline. The bidirectional causal

relations between these conditions were assessed using Mendelian randomization

analysis. Besides, polygenic risk scores were estimated by integrating

genome-wide association studies identified risk variants.

RESULTS: During 4,007,477 person-years of follow-up, 2006 incident lung cancer

cases were documented. Compared with participants without CVD, those with CVD

had HRs (95% confidence interval [CI]) of 1.49 (1.30-1.71) for NSCLC, 1.80

(1.39-2.34) for lung squamous cell carcinoma (LUSC), and 1.25 (1.01-1.56) for

lung adenocarcinoma (LUAD). After stratification by smoking status, significant

associations of CVD with lung cancer risk were observed in former smokers (HR =

1.44, 95% CI: 1.20-1.74) and current smokers (HR = 1.38, 95% CI: 1.13-1.69), but

not in never-smokers (HR = 0.98, 95% CI: 0.60-1.61). In addition, CVD was

associated with lung cancer risk across each genetic risk level

(pheterogeneity = 0.336). In the second analysis, 32,974 incident CVD cases were

recorded. Compared with those without lung cancer, the HRs (95% CI) for CVD were

2.33 (1.29-4.21) in NSCLC, 3.66 (1.65-8.14) in LUAD, and 1.98 (0.64-6.14) in

LUSC. In particular, participants with lung cancer had a high risk of incident

CVD at a high genetic risk level (HR = 3.79, 95% CI: 1.57-9.13). No causal

relations between these conditions were observed in Mendelian randomization

analysis.

CONCLUSIONS: CVD is associated with an increased risk of NSCLC including LUSC

and LUAD. NSCLC, particularly LUAD, is associated with a higher CVD risk.

Awareness of this bidirectional association may improve prevention and treatment

strategies for both diseases. Future clinical demands will require a greater

focus on cardiac oncology.

Copyright © 2023 International Association for the Study of Lung Cancer.

Published by Elsevier Inc. All rights reserved.

DOI: 10.1016/j.jtho.2023.09.004

PMID: 37703998 [Indexed for MEDLINE]

3. CA Cancer J Clin. 2024 Jan-Feb;74(1):50-81. doi: 10.3322/caac.21811. Epub 2023

Nov 1.

Screening for lung cancer: 2023 guideline update from the American Cancer Society.

Wolf AMD(1), Oeffinger KC(2), Shih TY(3), Walter LC(4), Church TR(5), Fontham

ETH(6), Elkin EB(7), Etzioni RD(8), Guerra CE(9), Perkins RB(10), Kondo KK(11),

Kratzer TB(12), Manassaram-Baptiste D(11), Dahut WL(13), Smith RA(11).

Author information:

(1)University of Virginia School of Medicine, Charlottesville, Virginia, USA.

(2)Department of Medicine, Duke University School of Medicine and Duke Cancer

Institute Center for Onco-Primary Care, Durham, North Carolina, USA.

(3)David Geffen School of Medicine and Jonsson Comprehensive Cancer Center,

University of California Los Angeles, Los Angeles, California, USA.

(4)Department of Medicine, University of California San Francisco and San

Francisco Veterans Affairs Medical Center, San Francisco, California, USA.

(5)Masonic Cancer Center, University of Minnesota, Minneapolis, Minnesota, USA.

(6)Health Sciences Center, School of Public Health, Louisiana State University,

New Orleans, Louisiana, USA.

(7)Department of Health Policy and Management, Columbia University Mailman

School of Public Health, New York, New York, USA.

(8)Fred Hutchinson Cancer Research Center, University of Washington, Seattle,

Washington, USA.

(9)Perelman School of Medicine, University of Pennsylvania, Philadelphia,

Pennsylvania, USA.

(10)Obstetrics and Gynecology, Boston University Chobanian and Avedisian School

of Medicine, Boston, Massachusetts, USA.

(11)Early Cancer Detection Science, American Cancer Society, Atlanta, Georgia,

USA.

(12)Cancer Surveillance and Health Equity Science, American Cancer Society,

Atlanta, Georgia, USA.

(13)American Cancer Society, Atlanta, Georgia, USA.

Lung cancer is the leading cause of mortality and person-years of life lost from

cancer among US men and women. Early detection has been shown to be associated

with reduced lung cancer mortality. Our objective was to update the American

Cancer Society (ACS) 2013 lung cancer screening (LCS) guideline for adults at

high risk for lung cancer. The guideline is intended to provide guidance for

screening to health care providers and their patients who are at high risk for

lung cancer due to a history of smoking. The ACS Guideline Development Group

(GDG) utilized a systematic review of the LCS literature commissioned for the US

Preventive Services Task Force 2021 LCS recommendation update; a second

systematic review of lung cancer risk associated with years since quitting

smoking (YSQ); literature published since 2021; two Cancer Intervention and

Surveillance Modeling Network-validated lung cancer models to assess the

benefits and harms of screening; an epidemiologic and modeling analysis

examining the effect of YSQ and aging on lung cancer risk; and an updated

analysis of benefit-to-radiation-risk ratios from LCS and follow-up

examinations. The GDG also examined disease burden data from the National Cancer

Institute's Surveillance, Epidemiology, and End Results program. Formulation of

recommendations was based on the quality of the evidence and judgment

(incorporating values and preferences) about the balance of benefits and harms.

The GDG judged that the overall evidence was moderate and sufficient to support

a strong recommendation for screening individuals who meet the eligibility

criteria. LCS in men and women aged 50-80 years is associated with a reduction

in lung cancer deaths across a range of study designs, and inferential evidence

supports LCS for men and women older than 80 years who are in good health. The

ACS recommends annual LCS with low-dose computed tomography for asymptomatic

individuals aged 50-80 years who currently smoke or formerly smoked and have a

≥20 pack-year smoking history (strong recommendation, moderate quality of

evidence). Before the decision is made to initiate LCS, individuals should

engage in a shared decision-making discussion with a qualified health

professional. For individuals who formerly smoked, the number of YSQ is not an

eligibility criterion to begin or to stop screening. Individuals who currently

smoke should receive counseling to quit and be connected to cessation resources.

Individuals with comorbid conditions that substantially limit life expectancy

should not be screened. These recommendations should be considered by health

care providers and adults at high risk for lung cancer in discussions about LCS.

If fully implemented, these recommendations have a high likelihood of

significantly reducing death and suffering from lung cancer in the United

States.

© 2023 The Authors. CA: A Cancer Journal for Clinicians published by Wiley

Periodicals LLC on behalf of American Cancer Society.

DOI: 10.3322/caac.21811

PMID: 37909877 [Indexed for MEDLINE]

4. Adv Mater. 2024 Jan;36(3): e2308977. doi: 10.1002/adma.202308977. Epub 2023 Nov

27.

Nanomedicine Combats Drug Resistance in Lung Cancer.

Zheng X(1), Song X(2), Zhu G(1), Pan D(1), Li H(1), Hu J(2), Xiao K(1), Gong

Q(1)(3)(4), Gu Z(1), Luo K(1)(3), Li W(1)(3).

Author information:

(1)Department of Radiology, Department of Respiratory, Huaxi MR Research Center

(HMRRC) and Critical Care Medicine, Institute of Respiratory Health, Precision

Medicine Center, Frontiers Science Center for Disease-Related Molecular Network,

State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, No.

37 Guoxue Alley, Chengdu, 610041, China.

(2)Department of General Surgery, Gastric Cancer Center and Laboratory of

Gastric Cancer, West China Hospital, Sichuan University, No. 37 Guoxue Alley,

Chengdu, 610041, China.

(3)Precision Medicine Key Laboratory of Sichuan Province, Functional and

Molecular Imaging Key Laboratory of Sichuan Province, and Research Unit of

Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, 610041, China.

(4)Department of Radiology, West China Xiamen Hospital of Sichuan University,

Xiamen, Fujian, 361000, China.

Lung cancer is the second most prevalent cancer and the leading cause of

cancer-related death worldwide. Surgery, chemotherapy, molecular targeted

therapy, immunotherapy, and radiotherapy are currently available as treatment

methods. However, drug resistance is a significant factor in the failure of lung

cancer treatments. Novel therapeutics have been exploited to address complicated

resistance mechanisms of lung cancer and the advancement of nanomedicine is

extremely promising in terms of overcoming drug resistance. Nanomedicine

equipped with multifunctional and tunable physiochemical properties in alignment

with tumor genetic profiles can achieve precise, safe, and effective treatment

while minimizing or eradicating drug resistance in cancer. Here, this work

reviews the discovered resistance mechanisms for lung cancer chemotherapy,

molecular targeted therapy, immunotherapy, and radiotherapy, and outlines novel

strategies for the development of nanomedicine against drug resistance. This

work focuses on engineering design, customized delivery, current challenges, and

clinical translation of nanomedicine in the application of resistant lung

cancer.

© 2023 Wiley-VCH GmbH.

DOI: 10.1002/adma.202308977

PMID: 37968865 [Indexed for MEDLINE]

5. JAMA Oncol. 2024 Jan 1;10(1):122-128. doi: 10.1001/jamaoncol.2023.4897.

Structural Racism and Lung Cancer Risk: A Scoping Review.

Bonner SN(1)(2), Curley R(3), Love K(4), Akande T(3), Akhtar A(3), Erhunmwunsee

L(3)(5).

Author information:

(1)Department of Surgery, University of Michigan, Ann Arbor.

(2)National Clinician Scholars Program, University of Michigan, Ann Arbor.

(3)Department of Surgery, City of Hope Comprehensive Cancer Center, Duarte,

California.

(4)Library Services, City of Hope, Duarte, California.

(5)Department of Populations Sciences, City of Hope National Medical Center,

Duarte, California.

IMPORTANCE: Structural racism is associated with persistent inequities in health

and health outcomes in the US for racial and ethnic minority groups. This review

summarizes how structural racism contributes to differential population-level

exposure to lung cancer risk factors and thus disparate lung cancer risk across

different racial and ethnic groups.

OBSERVATIONS: A scoping review was conducted focusing on structural racism and

lung cancer risk for racial and ethnic minority groups. The domains of

structural racism evaluated included housing and built environment, occupation

and employment, health care, economic and educational opportunity, private

industry, perceived stress and discrimination, and criminal justice involvement.

The PubMed, Embase, and MedNar databases were searched for English-language

studies in the US from January 1, 2010, through June 30, 2022. The review

demonstrated that racial and ethnic minority groups are more likely to have

environmental exposures to air pollution and known carcinogens due to

segregation of neighborhoods and poor housing quality. In addition, racial and

ethnic minority groups were more likely to have exposures to pesticides, silica,

and asbestos secondary to higher employment in manual labor occupations.

Furthermore, targeted marketing and advertisement of tobacco products by private

industry were more likely to occur in neighborhoods with more racial and ethnic

minority groups. In addition, poor access to primary care services and

inequities in insurance status were associated with elevated lung cancer risk

among racial and ethnic minority groups. Lastly, inequities in tobacco use and

cessation services among individuals with criminal justice involvement had

important implications for tobacco use among Black and Hispanic populations.

CONCLUSIONS AND RELEVANCE: The findings suggest that structural racism must 

be considered as a fundamental contributor to the unequal distribution of lung

cancer risk factors and thus disparate lung cancer risk across different racial

and ethnic groups. Additional research is needed to better identify mechanisms

contributing to inequitable lung cancer risk and tailor preventive

interventions.

DOI: 10.1001/jamaoncol.2023.4897

PMID: 38032677 [Indexed for MEDLINE]

6. J Thorac Oncol. 2024 Jan;19(1):36-51. doi: 10.1016/j.jtho.2023.07.019. Epub 2023

Jul 23.

Current and Future Perspectives on Computed Tomography Screening for Lung

Cancer: A Roadmap From 2023 to 2027 From the International Association for the

Study of Lung Cancer.

Lam S(1), Bai C(2), Baldwin DR(3), Chen Y(4), Connolly C(5), de Koning H(6),

Heuvelmans MA(7), Hu P(8), Kazerooni EA(9), Lancaster HL(7), Langs G(10),

McWilliams A(11), Osarogiagbon RU(12), Oudkerk M(13), Peters M(14), Robbins

HA(15), Sahar L(16), Smith RA(17), Triphuridet N(18), Field J(19).

Author information:

(1)Department of Integrative Oncology, British Columbia Cancer Research

Institute, Vancouver, British Columbia, Canada; Department of Medicine,

University of British Columbia, Vancouver, British Columbia, Canada. Electronic

address: slam2@bccancer.bc.ca.

(2)Shanghai Respiratory Research Institute and Chinese Alliance Against Cancer,

Shanghai, People's Republic of China.

(3)Nottingham University Hospitals National Health Services (NHS) Trust,

Nottingham, United Kingdom.

(4)Digital Screening, Faculty of Medicine & Health Sciences, University of

Nottingham Medical School, Nottingham, United Kingdom.

(5)International Association for the Study of Lung Cancer, Denver, Colorado.

(6)Department of Public Health, Erasmus MC University Medical Centre Rotterdam,

The Netherlands.

(7)University of Groningen, Groningen, The Netherlands; Department of

Epidemiology, University Medical Center Groningen, Groningen, The Netherlands;

The Institute for Diagnostic Accuracy, Groningen, The Netherlands.

(8)Division of Cancer Prevention, National Cancer Institute, National Institutes

of Health, Bethesda, Maryland.

(9)Division of Cardiothoracic Radiology, Department of Radiology, University of

Michigan Medical School, Ann Arbor, Michigan; Division of Pulmonary and Critical

Care Medicine, Department of Internal Medicine, University of Michigan Medical

School, Ann Arbor, Michigan.

(10)Computational Imaging Research Laboratory, Department of Biomedical Imaging

and Image-guided Therapy, Medical University of Vienna, Vienna, Austria.

(11)Department of Respiratory Medicine, Fiona Stanley Hospital, Murdoch, Western

Australia, Australia; Australia University of Western Australia, Nedlands,

Western Australia.

(12)Thoracic Oncology Research Group, Baptist Cancer Center, Memphis, Tennessee.

(13)Center for Medical Imaging and The Institute for Diagnostic Accuracy,

Faculty of Medical Sciences, University of Groningen, Groningen, The

Netherlands.

(14)Woolcock Institute of Respiratory Medicine, Macquarie University, Sydney,

New South Wales, Australia.

(15)Genomic Epidemiology Branch, International Agency for Research on Cancer,

Lyon, France.

(16)Data Science, American Cancer Society, Atlanta, Georgia.

(17)Early Cancer Detection Science, American Cancer Society, Atlanta, Georgia.

(18)Department of Medicine, Chulabhorn Hospital, Bangkok, Thailand.

(19)Department of Molecular and Clinical Cancer Medicine, The University of

Liverpool, Liverpool, United Kingdom.

Low-dose computed tomography (LDCT) screening for lung cancer substantially

reduces mortality from lung cancer, as revealed in randomized controlled trials

and meta-analyses. This review is based on the ninth CT screening symposium of

the International Association for the Study of Lung Cancer, which focuses on the

major themes pertinent to the successful global implementation of LDCT screening

and develops a strategy to further the implementation of lung cancer screening

globally. These recommendations provide a 5-year roadmap to advance the

implementation of LDCT screening globally, including the following: (1)

establish universal screening program quality indicators; (2) establish

evidence-based criteria to identify individuals who have never smoked but are at

high-risk of developing lung cancer; (3) develop recommendations for

incidentally detected lung nodule tracking and management protocols to

complement programmatic lung cancer screening; (4) Integrate artificial

intelligence and biomarkers to increase the prediction of malignancy in

suspicious CT screen-detected lesions; and (5) standardize high-quality

performance artificial intelligence protocols that lead to substantial

reductions in costs, resource utilization and radiologist reporting time; (6)

personalize CT screening intervals on the basis of an individual's lung cancer

risk; (7) develop evidence to support clinical management and cost-effectiveness

of other identified abnormalities on a lung cancer screening CT; (8) develop

publicly accessible, easy-to-use geospatial tools to plan and monitor equitable

access to screening services; and (9) establish a global shared education

resource for lung cancer screening CT to ensure high-quality reading and

reporting.

Copyright © 2023 International Association for the Study of Lung Cancer.

Published by Elsevier Inc. All rights reserved.

DOI: 10.1016/j.jtho.2023.07.019

PMID: 37487906 [Indexed for MEDLINE]

7. Am J Respir Crit Care Med. 2024 Jan 15;209(2):185-196. doi:

10.1164/rccm.202306-0942OC.

Occupational Benzene Exposure and Lung Cancer Risk: A Pooled Analysis of 14

Case-Control Studies.

Wan W(1), Peters S(1), Portengen L(1), Olsson A(2), Schüz J(2), Ahrens W(3)(4),

Schejbalova M(5), Boffetta P(6)(7), Behrens T(8), Brüning T(8), Kendzia B(8),

Consonni D(9), Demers PA(10), Fabiánová E(11)(12), Fernández-Tardón G(13)(14),

Field JK(15), Forastiere F(16), Foretova L(17), Guénel P(18), Gustavsson P(19),

Jöckel KH(20), Karrasch S(21)(22)(23), Landi MT(24), Lissowska J(25), Barul

C(26), Mates D(27), McLaughlin JR(28), Merletti F(29), Migliore E(29), Richiardi

L(29), Pándics T(30), Pohlabeln H(3), Siemiatycki J(31), Świątkowska B(32),

Wichmann HE(33)(22), Zaridze D(34), Ge C(35), Straif K(36)(37), Kromhout H(1),

Vermeulen R(1).

Author information:

(1)Institute for Risk Assessment Sciences, Utrecht University, Utrecht, the

Netherlands.

(2)International Agency for Research on Cancer/World Health Organization, Lyon,

France.

(3)Leibniz Institute for Prevention Research and Epidemiology, Bremen, Germany.

(4)Faculty of Mathematics and Computer Science, Institute of Statistics,

University of Bremen, Bremen, Germany.

(5)Institute of Hygiene and Epidemiology, First Faculty of Medicine, Charles

University, Prague, Czechia.

(6)Stony Brook Cancer Center, Stony Brook University, Stony Brook, New York.

(7)Department of Medical and Surgical Sciences, University of Bologna, Bologna,

Italy.

(8)Institute for Prevention and Occupational Medicine of the German Social

Accident Insurance, Institute of the Ruhr University, Bochum, Germany.

(9)Epidemiology Unit, Fondazione Istituto di Ricovero e Cura a Carattere

Scientifico Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy.

(10)Occupational Cancer Research Centre, Ontario Health, Toronto, Ontario,

Canada.

(11)Regional Authority of Public Health, Banská Bystrica, Slovakia.

(12)Faculty of Health, Catholic University, Ružomberok, Slovakia.

(13)Consortium for Biomedical Research in Epidemiology and Public Health,

Madrid, Spain.

(14)Health Research Institute of Asturias, University Institute of Oncology of

Asturias - Cajastur Social Program, University of Oviedo, Oviedo, Spain.

(15)Roy Castle Lung Cancer Research Programme, Department of Molecular and

Clinical Cancer Medicine, University of Liverpool, Liverpool, United Kingdom.

(16)Department of Epidemiology, Azienda Sanitaria Locale Roma E, Rome, Italy.

(17)Masaryk Memorial Cancer Institute, Brno, Czechia.

(18)Center for Research in Epidemiology and Population Health, Team Exposome and

Heredity, U1018 Institut national de la santé et de la recherche médicale,

University of Paris-Saclay, Villejuif, France.

(19)Institute of Environmental Medicine, Karolinska Institutet, Stockholm,

Sweden.

(20)Institute for Medical Informatics, Biometry and Epidemiology, University

Hospital Essen, Essen, Germany.

(21)Institute and Clinic for Occupational, Social and Environmental Medicine,

University Hospital, and.

(22)Comprehensive Pneumology Center Munich, Member of the German Center for Lung

Research, Munich, Germany.

(23)Institute of Epidemiology, Helmholtz Zentrum München - German Research

Center for Environmental Health, Neuherberg, Germany.

(24)Division of Cancer Epidemiology and Genetics, National Cancer Institute,

Bethesda, Maryland.

(25)Epidemiology Unit, Department of Cancer Epidemiology and Prevention, M.

Sklodowska-Curie National Research Institute of Oncology, Warsaw, Poland.

(26)Université Rennes, Institut national de la santé et de la recherche

médicale, École des hautes études en santé publique, Institut de recherche en

santé, environnement et travail, UMR_S 1085, Pointe-à-Pitre, France.

(27)National Institute of Public Health, Bucharest, Romania.

(28)Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario,

Canada.

(29)Cancer Epidemiology Unit, Department of Medical Sciences, University of

Turin, Turin, Italy.

(30)National Public Health Center, Budapest, Hungary.

(31)Department of Social and Preventive Medicine, University of Montreal,

Montreal, Quebec, Canada.

(32)Department of Environmental Epidemiology, The Nofer Institute of

Occupational Medicine, Lodz, Poland.

(33)Institut für Medizinische Informatik Biometrie Epidemiologie,

Ludwig-Maximilians-Universität München, Munich, Germany.

(34)Department of Cancer Epidemiology and Prevention, N.N. Blokhin National

Research Center of Oncology, Moscow, Russia.

(35)Nederlandse Organisatie voor Toegepast Natuurwetenschappelijk Onderzoek,

Utrecht, the Netherlands.

(36)ISGlobal, Barcelona, Spain; and.

(37)Boston College, Boston, Massachusetts.

Comment in

    Am J Respir Crit Care Med. 2024 Jan 15;209(2):128-130.

Rationale: Benzene has been classified as carcinogenic to humans, but there is

limited evidence linking benzene exposure to lung cancer. Objectives: We aimed

to examine the relationship between occupational benzene exposure and lung

cancer. Methods: Subjects from 14 case-control studies across Europe and Canada

were pooled. We used a quantitative job-exposure matrix to estimate benzene

exposure. Logistic regression models assessed lung cancer risk across different

exposure indices. We adjusted for smoking and five main occupational lung

carcinogens and stratified analyses by smoking status and lung cancer subtypes.

Measurements and Main Results: Analyses included 28,048 subjects (12,329 cases,

15,719 control subjects). Lung cancer odds ratios ranged from 1.12 (95%

confidence interval, 1.03-1.22) to 1.32 (95% confidence interval, 1.18-1.48)

(Ptrend = 0.002) for groups with the lowest and highest cumulative occupational

exposures, respectively, compared with unexposed subjects. We observed an

increasing trend of lung cancer with longer duration of exposure

(Ptrend < 0.001) and a decreasing trend with longer time since last exposure

(Ptrend = 0.02). These effects were seen for all lung cancer subtypes,

regardless of smoking status, and were not influenced by specific occupational

groups, exposures, or studies. Conclusions: We found consistent and robust

associations between different dimensions of occupational benzene exposure and

lung cancer after adjusting for smoking and main occupational lung carcinogens.

These associations were observed across different subgroups, including

nonsmokers. Our findings support the hypothesis that occupational benzene

exposure increases the risk of developing lung cancer. Consequently, there is a

need to revisit published epidemiological and molecular data on the pulmonary

carcinogenicity of benzene.

DOI: 10.1164/rccm.202306-0942OC

PMCID: PMC10806413

PMID: 37812782 [Indexed for MEDLINE]

8. CA Cancer J Clin. 2024 Jan-Feb;74(1):84-114. doi: 10.3322/caac.21808. Epub 2023

Nov 1.

Lung cancer diagnosis and mortality beyond 15 years since quit in individuals

with a 20+ pack-year history: A systematic review.

Kondo KK(1)(2), Rahman B(1), Ayers CK(3), Relevo R(1), Griffin JC(1), Halpern

MT(4).

Author information:

(1)Early Cancer Detection Science, American Cancer Society, Kennesaw, Georgia,

USA.

(2)Research Integrity, Oregon Health & Science University, Portland, Oregon,

USA.

(3)Center to Improve Veteran Involvement in Care, Portland Veterans Affairs

Health Care System, Portland, Oregon, USA.

(4)Division of Cancer Control & Population Sciences, National Cancer Institute,

Bethesda, Maryland, USA.

Current US lung cancer screening recommendations limit eligibility to adults

with a pack-year (PY) history of ≥20 years and the first 15 years since quit

(YSQ). The authors conducted a systematic review to better understand lung

cancer incidence, risk and mortality among otherwise eligible individuals in

this population beyond 15 YSQ. The PubMed and Scopus databases were searched

through February 14, 2023, and relevant articles were searched by hand. Included

studies examined the relationship between adults with both a ≥20-PY history and

≥15 YSQ and lung cancer diagnosis, mortality, and screening ineligibility. One

investigator abstracted data and a second confirmed. Two investigators

independently assessed study quality and certainty of evidence (COE) and

resolved discordance through consensus. From 2636 titles, 22 studies in 26

articles were included. Three studies provided low COE of elevated lung cancer

incidence beyond 15 YSQ, as compared with people who never smoked, and six

studies provided moderate COE that the risk of a lung cancer diagnosis after 15

YSQ declines gradually, but with no clinically significant difference just

before and after 15 YSQ. Studies examining lung cancer-related disparities

suggest that outcomes after 15 YSQ were similar between African American/Black

and White participants; increasing YSQ would expand eligibility for African

American/Black individuals, but for a significantly larger proportion of White

individuals. The authors observed that the risk of lung cancer not only persists

beyond 15 YSQ but that, compared with individuals who never smoked, the risk may

remain significantly elevated for 2 or 3 decades. Future research of nationally

representative samples with consistent reporting across studies is needed, as

are better data from which to examine the effects on health disparities across

different populations.

© 2023 The Authors. CA: A Cancer Journal for Clinicians published by Wiley

Periodicals LLC on behalf of American Cancer Society.

DOI: 10.3322/caac.21808

PMID: 37909870 [Indexed for MEDLINE]

9. Lancet Infect Dis. 2024 Jan;24(1):46-56. doi: 10.1016/S1473-3099(23)00371-7.

Epub 2023 Aug 14.

Incidence and risk factors of tuberculosis among 420 854 household contacts of

patients with tuberculosis in the 100 Million Brazilian Cohort (2004-18): a

cohort study.

Pinto PFPS(1), Teixeira CSS(2), Ichihara MY(2), Rasella D(3), Nery JS(4), Sena

SOL(2), Brickley EB(5), Barreto ML(4), Sanchez MN(6), Pescarini JM(7).

Author information:

(1)Centro de Integração de Dados e Conhecimentos para Saúde (Cidacs), Fundação

Oswaldo Cruz, Salvador, Brazil. Electronic address: priferscaff@hotmail.com.

(2)Centro de Integração de Dados e Conhecimentos para Saúde (Cidacs), Fundação

Oswaldo Cruz, Salvador, Brazil.

(3)Centro de Integração de Dados e Conhecimentos para Saúde (Cidacs), Fundação

Oswaldo Cruz, Salvador, Brazil; Institute of Global Health (ISGlobal), Hospital

Clínic-Universitat de Barcelona, Barcelona, Spain.

(4)Centro de Integração de Dados e Conhecimentos para Saúde (Cidacs), Fundação

Oswaldo Cruz, Salvador, Brazil; Instituto de Saúde Coletiva, Universidade

Federal da Bahia, Salvador, Brazil.

(5)Department of Infectious Disease Epidemiology, London School of Hygiene &

Tropical Medicine, London, UK.

(6)Centro de Integração de Dados e Conhecimentos para Saúde (Cidacs), Fundação

Oswaldo Cruz, Salvador, Brazil; Núcleo de Medicina Tropical, Universidade de

Brasília (UnB), Brasília, Brazil.

(7)Centro de Integração de Dados e Conhecimentos para Saúde (Cidacs), Fundação

Oswaldo Cruz, Salvador, Brazil; Department of Infectious Disease Epidemiology,

London School of Hygiene & Tropical Medicine, London, UK.

BACKGROUND: Although household contacts of patients with tuberculosis are known

to be particularly vulnerable to tuberculosis, the published evidence focused on

this group at high risk within the low-income and middle-income country context

remains sparse. Using nationwide data from Brazil, we aimed to estimate the

incidence and investigate the socioeconomic and clinical determinants of

tuberculosis in a cohort of contacts of tuberculosis patients.

METHODS: In this cohort study, we linked individual socioeconomic and

demographic data from the 100 Million Brazilian Cohort to mortality data and

tuberculosis registries, identified contacts of tuberculosis index patients

diagnosed from Jan 1, 2004 to Dec 31, 2018, and followed up the contacts until

the contact's subsequent tuberculosis diagnosis, the contact's death, or Dec 31,

2018. We investigated factors associated with active tuberculosis using

multilevel Poisson regressions, allowing for municipality-level and

household-level random effects.

FINDINGS: We studied 420 854 household contacts of 137 131 tuberculosis index

patients. During the 15 years of follow-up (median 4·4 years [IQR 1·9-7·6]), we

detected 8953 contacts with tuberculosis. The tuberculosis incidence among

contacts was 427·8 per 100 000 person-years at risk (95% CI 419·1-436·8),

16-times higher than the incidence in the general population (26·2 [26·1-26·3])

and the risk was prolonged. Tuberculosis incidence was associated with the index

patient being preschool aged (<5 years; adjusted risk ratio 4·15 [95% CI

3·26-5·28]) or having pulmonary tuberculosis (2·84 [2·55-3·17]).

INTERPRETATION: The high and sustained risk of tuberculosis among contacts

reinforces the need to systematically expand and strengthen contact tracing and

preventive treatment policies in Brazil in order to achieve national and

international targets for tuberculosis elimination.

FUNDING: Wellcome Trust and Brazilian Ministry of Health.

Copyright © 2024 The Author(s). Published by Elsevier Ltd. This is an Open

Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All

rights reserved.

DOI: 10.1016/S1473-3099(23)00371-7

PMCID: PMC10733584

PMID: 37591301 [Indexed for MEDLINE]

Conflict of interest statement: Declaration of interests We declare no competing

interests.

10. Lancet Public Health. 2024 Jan;9(1): e47-e56. doi: 10.1016/S2468-2667(23)00276-1.

Racial and ethnic disparities in diagnosis and treatment outcomes among US-born

people diagnosed with tuberculosis, 2003-19: an analysis of national

surveillance data.

Regan M(1), Li Y(2), Swartwood NA(2), Barham T(3), Asay GRB(4), Cohen T(5), Hill

AN(4), Horsburgh CR(6), Khan A(4), Marks SM(4), Myles RL(3), Salomon JA(7), Self

JL(4), Menzies NA(2).

Author information:

(1)Department of Global Health and Population, Harvard TH Chan School of Public

Health, Boston, MA, USA. Electronic address: mathildaregan@hsph.harvard.edu.

(2)Department of Global Health and Population, Harvard TH Chan School of Public

Health, Boston, MA, USA.

(3)Office of Health Equity, National Center for HIV, Viral Hepatitis, STD, and

TB prevention, US Centers for Disease Control and Prevention, Atlanta, GE, USA.

(4)Division of Tuberculosis Elimination, National Center for HIV, Viral

Hepatitis, STD, and TB prevention, US Centers for Disease Control and

Prevention, Atlanta, GE, USA.

(5)Yale School of Public Health, New Haven, CT, USA.

(6)Departments of Epidemiology, Biostatistics, Global Health, and Medicine,

Boston University Schools of Public Health and Medicine, Boston, MA, USA.

(7)Department of Health Policy, Stanford University, Stanford, CA, USA.

BACKGROUND: Persistent racial and ethnic disparities in tuberculosis incidence

exist in the USA, however, less is known about disparities along the

tuberculosis continuum of care. This study aimed to describe how race and

ethnicity are associated with tuberculosis diagnosis and treatment outcomes.

METHODS: In this analysis of national surveillance data, we extracted data from

the US National Tuberculosis Surveillance System on US-born patients with

tuberculosis during 2003-19. To estimate the association between race and

ethnicity and tuberculosis diagnosis (diagnosis after death, cavitation, and

sputum smear positivity) and treatment outcomes (treatment for more than 12

months, treatment discontinuation, and death during treatment), we fitted

log-binomial regression models adjusting for calendar year, sex, age category,

and regional division. Race and ethnicity were defined based on US Census Bureau

classification as White, Black, Hispanic, Asian, American Indian or Alaska

Native, Native Hawaiian or Pacific Islander, and people of other ethnicities. We

quantified racial and ethnic disparities as adjusted relative risks (aRRs) using

non-Hispanic White people as the reference group. We also calculated the Index

of Disparity as a summary measure that quantifies the dispersion in a given

outcome across all racial and ethnic groups, relative to the population mean. We

estimated time trends in each outcome to evaluate whether disparities were

closing or widening.

FINDINGS: From 2003 to 2019, there were 72 809 US-born individuals diagnosed

with tuberculosis disease of whom 72 369 (35·7% women and 64·3% men) could be

included in analyses. We observed an overall higher risk of any adverse outcome

(defined as diagnosis after death, treatment discontinuation, or death during

treatment) for non-Hispanic Black people (aRR 1·27, 95% CI 1·22-1·32), Hispanic

people (1·20, 1·14-1·27), and American Indian or Alaska Native people (1·24,

1·12-1·37), relative to non-Hispanic White people. The Index of Disparity for

this summary outcome remained unchanged over the study period.

INTERPRETATION: This study, based on national surveillance data, indicates

racial and ethnic disparaties among US-born tuberculosis patients along the

tuberculosis continuum of care. Initiatives are needed to reduce diagnostic

delays and improve treatment outcomes for US-born racially marginalised people

in the USA.

FUNDING: US Centers for Disease Control and Prevention.

Copyright © 2024 The Author(s). Published by Elsevier Ltd. This is an Open

Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All

rights reserved.

DOI: 10.1016/S2468-2667(23)00276-1

PMID: 38176842 [Indexed for MEDLINE]

Conflict of interest statement: Declaration of interests We declare no competing

interests.

11. J Thorac Oncol. 2024 Jan;19(1):25-35. doi: 10.1016/j.jtho.2023.09.1443. Epub

2023 Sep 23.

A Shift in Paradigm: Selective Lymph Node Dissection for Minimizing Oversurgery

in Early Stage Lung Cancer.

Jiang C(1), Zhang Y(1), Fu F(1), Deng P(1), Chen H(2).

Author information:

(1)Department of Thoracic Surgery and State Key Laboratory of Genetic

Engineering, Fudan University Shanghai Cancer Center, Shanghai, People's

Republic of China; Institute of Thoracic Oncology, Fudan University, Shanghai,

People's Republic of China; Department of Oncology, Shanghai Medical College,

Fudan University, Shanghai, People's Republic of China.

(2)Department of Thoracic Surgery and State Key Laboratory of Genetic

Engineering, Fudan University Shanghai Cancer Center, Shanghai, People's

Republic of China; Institute of Thoracic Oncology, Fudan University, Shanghai,

People's Republic of China; Department of Oncology, Shanghai Medical College,

Fudan University, Shanghai, People's Republic of China. Electronic address:

hqchen1@yahoo.com.

Systematic lymph node dissection has been widely accepted and turned into a

standard procedure for lung cancer surgery. In recent years, the concept of

"minimal invasive surgery (MIS)" has greatly changed the surgical paradigm of

lung cancer. Previous studies revealed that excessive dissection of lymph nodes

without metastases had uncertain clinical benefit. Meanwhile, it leads to the

elevated risk of postoperative complications including chylothorax and laryngeal

nerve injury. In addition, dissection of nonmetastatic lymph nodes may disturb

systematic immunity, resulting in the secondary effect on primary tumor or

latent metastases. The past decades have witnessed the innovative strategies

such as lobe-specific lymph node dissection and selective lymph node dissection.

On the basis of evolution of lymph node dissection strategy, we discuss the

negative effects of excessive nonmetastatic lymph node dissection and summarize

the recent advances in the optimized dissection strategies, hoping to provide

unique perspectives on the future directions.

Copyright © 2023 International Association for the Study of Lung Cancer.

Published by Elsevier Inc. All rights reserved.

DOI: 10.1016/j.jtho.2023.09.1443

PMID: 37748691 [Indexed for MEDLINE]

12. Lancet Glob Health. 2024 Jan;12(1):e45-e54. doi: 10.1016/S2214-109X(23)00469-2.

Oral swabs with a rapid molecular diagnostic test for pulmonary tuberculosis in

adults and children: a systematic review.

Church EC(1), Steingart KR(2), Cangelosi GA(3), Ruhwald M(4), Kohli M(4),

Shapiro AE(5).

Author information:

(1)HIV Vaccine Trials Network, Fred Hutchinson Cancer Center, Seattle, WA, USA;

Division of Allergy and Infectious Diseases, University of Washington, Seattle,

WA, USA. Electronic address: cchurch2@fredhutch.org.

(2)Honorary Research Fellow, Department of Clinical Sciences, Liverpool School

of Tropical Medicine, Liverpool, UK.

(3)Department of Environmental and Occupational Health Sciences, School of

Public Health, University of Washington, Seattle, WA, USA.

(4)FIND, Geneva, Switzerland.

(5)Division of Allergy and Infectious Diseases, University of Washington,

Seattle, WA, USA; Department of Global Health, University of Washington,

Seattle, WA, USA.

BACKGROUND: Tuberculosis is a leading cause of infectious disease mortality

worldwide, but diagnosis of pulmonary tuberculosis remains challenging. Oral

swabs are a promising non-sputum alternative sample type for the diagnosis of

pulmonary tuberculosis. We aimed to assess the diagnostic accuracy of oral swabs

to detect pulmonary tuberculosis in adults and children and suggest research

implications.

METHODS: In this systematic review, we searched published and preprint studies

from Jan 1, 2000, to July 5, 2022, from eight databases (MEDLINE, Embase,

Scopus, Science Citation Index, medRxiv, bioRxiv, Global Index Medicus, and

Google Scholar). We included diagnostic accuracy studies including

cross-sectional, cohort, and case-control studies in adults and children from

which we could extract or derive sensitivity and specificity of oral swabs as a

sample type for the diagnosis of pulmonary tuberculosis against a sputum

microbiological (nucleic acid amplification test [NAAT] on sputum or culture) or

composite reference standard.

FINDINGS: Of 550 reports identified by the search, we included 16 eligible

reports (including 20 studies and 3083 participants) that reported diagnostic

accuracy estimates on oral swabs for pulmonary tuberculosis. Sensitivity on oral

swabs ranged from 36% (95% CI 26-48) to 91% (80-98) in adults and 5% (1-14) to

42% (23-63) in children. Across all studies, specificity ranged from 66% (95% CI

52-78) to 100% (97-100), with most studies reporting specificity of more than

90%. Meta-analysis was not performed because of sampling and testing

heterogeneity.

INTERPRETATION: Sensitivity varies in both adults and children when diverse

methods are used. Variability in sampling location, swab type, and type of NAAT

used in accuracy studies limits comparison. Although data are suggestive that

high accuracy is achievable using oral swabs with molecular testing, more

research is needed to define optimal methods for using oral swabs as a specimen

for tuberculosis detection. The current data suggest that tongue swabs and swab

types that collect increased biomass might have increased sensitivity. We would

recommend that future studies use these established methods to continue to

refine sample processing to maximise sensitivity.

FUNDING: Bill and Melinda Gates foundation (INV-045721) and FIND (Netherlands

Enterprise Agency on behalf of the Minister for Foreign Trade and Development

Cooperation [NL-GRNT05] and KfW Development Bank, German Federal Ministry of

Education and Research [KFW-TBBU01/02]).

Copyright © 2024 The Author(s). Published by Elsevier Ltd. This is an Open

Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All

rights reserved.

DOI: 10.1016/S2214-109X(23)00469-2

PMCID: PMC10733129

PMID: 38097297 [Indexed for MEDLINE]

Conflict of interest statement: Declaration of interests This study received

funding from FIND. ECC reports institution payments from FIND. MK and MR are

employed by FIND. AES is supported in part by a National Institutes of Health

(NIH) K23 AI40918 award. GAC is funded by the NIH and Bill and Melinda Gates

foundation and reports receiving donations of research supplies (FLOQswabs) from

Copan Italia. KS has received financial support from Cochrane Infectious

Diseases, McGill University, Baylor College of Medicine, Maastricht University,

TB Proof, and WHO Global Tuberculosis Programme; consultancy fees from FIND, the

global alliance for diagnostics; consulting fees from Stellenbosch University,

and travel support to attend WHO guideline development group meetings.

13. Am J Respir Crit Care Med. 2024 Jan 15;209(2):197-205. doi:

10.1164/rccm.202301-0155OC.

What Goes into Patient Selection for Lung Cancer Screening? Factors Associated

with Clinician Judgments of Suitability for Screening.

Núñez ER(1)(2)(3)(4), Zhang S(1)(2)(5), Glickman ME(1)(2)(5), Qian SX(1)(2),

Boudreau JH(1)(2), Lindenauer PK(4), Slatore CG(6)(7)(8), Miller DR(1)(2)(9),

Caverly TJ(7)(10)(11), Wiener RS(1)(2)(3)(7).

Author information:

(1)Center for Healthcare Organization and Implementation Research, VA Boston and

Bedford Healthcare Systems, Boston, Massachusetts.

(2)VA Bedford Healthcare System, Bedford, Massachusetts.

(3)The Pulmonary Center, School of Medicine, Boston University, Boston,

Massachusetts.

(4)Department of Healthcare Delivery and Population Sciences, Chan Medical

School-Baystate, University of Massachusetts, Springfield, Massachusetts.

(5)Department of Statistics, Harvard University, Cambridge, Massachusetts.

(6)Center to Improve Veteran Involvement in Care, VA Portland Health Care

System, Portland Oregon.

(7)National Center for Lung Cancer Screening, Veterans Health Administration,

Washington, DC.

(8)Division of Pulmonary and Critical Care Medicine, Oregon Health and Science

University, Portland, Oregon.

(9)Zuckerberg College of Health Sciences, University of Massachusetts, Lowell,

Massachusetts.

(10)VA Ann Arbor Healthcare System, Ann Arbor, Michigan; and.

(11)School of Medicine, University of Michigan, Ann Arbor, Michigan.

Comment in

    Am J Respir Crit Care Med. 2024 Jan 15;209(2):130-131.

Rationale: Achieving the net benefit of lung cancer screening (LCS) depends on

optimizing patient selection. Objective: To identify factors associated with

clinician assessments that a patient was unlikely to benefit from LCS

("LCS-inappropriate") because of comorbidities or limited life expectancy.

Methods: Retrospective analysis of patients assessed for LCS at 30 Veterans

Health Administration facilities from January 1, 2015 to February 1, 2021. We

conducted hierarchical mixed-effects logistic regression analyses to determine

factors associated with clinicians' designations of LCS inappropriateness

(primary outcome), accounting for 3-year predicted probability (i.e., competing

risk) of non-lung cancer death. Measurements and Main Results: Among 38,487

LCS-eligible patients, 1,671 (4.3%) were deemed LCS-inappropriate by clinicians,

whereas 4,383 (11.4%) had an estimated 3-year competing risk of non-lung cancer

death greater than 20%. Patients with higher competing risks of non-lung cancer

death were more likely to be deemed LCS-inappropriate (odds ratio [OR], 2.66;

95% confidence interval [CI], 2.32-3.05). Older patients (ages 75-80; OR, 1.45;

95% CI, 1.18-1.78) and those with interstitial lung disease (OR, 1.98; 95% CI,

1.51-2.59) were more likely to be deemed LCS-inappropriate than would be

explained by competing risk of non-lung cancer death, whereas patients currently

smoking (OR, 0.65; 95% CI, 0.58-0.73) were less likely to be deemed

LCS-inappropriate, suggesting that clinicians over- or underweighted these

factors. The probability of being deemed LCS-inappropriate varied from 0.4% to

74%, depending on the clinician making the assessment (median OR, 3.07; 95% CI,

2.89-3.25). Conclusion: Concerningly, the likelihood that a patient is deemed

LCS-inappropriate is more strongly associated with the clinician making the

assessment than with patient characteristics. Patient selection may be optimized

by providing decision support to help clinicians assess net LCS benefit.

DOI: 10.1164/rccm.202301-0155OC

PMCID: PMC10806423

PMID: 37819144 [Indexed for MEDLINE]

14. MMWR Morb Mortal Wkly Rep. 2024 Jan 5;72(5253):1385-1389. doi:

10.15585/mmwr.mm725253a1.

Second Nationwide Tuberculosis Outbreak Caused by Bone Allografts Containing

Live Cells - United States, 2023.

Wortham JM, Haddad MB, Stewart RJ, Annambhotla P, Basavaraju SV, Nabity SA,

Griffin IS, McDonald E, Beshearse EM, Grossman MK, Schildknecht KR, Calvet HM,

Keh CE, Percak JM, Coloma M, Shaw T, Davidson PJ, Smith SR, Dickson RP, Kaul DR,

Gonzalez AR, Rai S, Rodriguez G, Morris S, Armitige LY, Stapleton J, Lacassagne

M, Young LR, Ariail K, Behm H, Jordan HT, Spencer M, Nilsen DM, Denison BM,

Burgos M, Leonard JM, Cortes E, Thacker TC, Lehman KA, Langer AJ, Cowan LS,

Starks AM, LoBue PA.

During July 7-11, 2023, CDC received reports of two patients in different states

with a tuberculosis (TB) diagnosis following spinal surgical procedures that

used bone allografts containing live cells from the same deceased donor. An

outbreak associated with a similar product manufactured by the same tissue

establishment (i.e., manufacturer) occurred in 2021. Because of concern that

these cases represented a second outbreak, CDC and the Food and Drug

Administration worked with the tissue establishment to determine that this

product was obtained from a donor different from the one implicated in the 2021

outbreak and learned that the bone allograft product was distributed to 13

health care facilities in seven states. Notifications to all seven states

occurred on July 12. As of December 20, 2023, five of 36 surgical bone allograft

recipients received laboratory-confirmed TB disease diagnoses; two patients died

of TB. Whole-genome sequencing demonstrated close genetic relatedness between

positive Mycobacterium tuberculosis cultures from surgical recipients and unused

product. Although the bone product had tested negative by nucleic acid

amplification testing before distribution, M. tuberculosis culture of unused

product was not performed until after the outbreak was recognized. The public

health response prevented up to 53 additional surgical procedures using

allografts from that donor; additional measures to protect patients from

tissue-transmitted M. tuberculosis are urgently needed.

DOI: 10.15585/mmwr.mm725253a1

PMID: 38175804 [Indexed for MEDLINE]

Conflict of interest statement: All authors have completed and submitted the

International Committee of Medical Journal Editors form for disclosure of

potential conflicts of interest. Saroj Rai reports uncompensated service as the

Association of Immunization Managers’ (AIM) liaison to CDC’s Advisory Committee

on Immunization Practices – Chikungunya Workgroup and on the Legacy Council for

AIM; and retirement stocks at Novartis Pharmaceuticals. Jeffrey M. Percak

reports travel support from the County of San Diego and from the California

Tuberculosis Controller’s Association for attendance at the California

Tuberculosis Controller’s Association fall meeting. Lisa Y. Armitige reports

support from the Texas Department of State Health Services, consulting fees

(paid to institution) from the Kansas Health Department, and honoraria

(forwarded to institution) from the American Academy of HIV Medicine. No other

potential conflicts of interest were disclosed.

15. Lancet. 2024 Jan 31:S0140-6736(23)02270-5. doi: 10.1016/S0140-6736(23)02270-5.

Online ahead of print.

Effectiveness of a comprehensive package based on electronic medication monitors

at improving treatment outcomes among tuberculosis patients in Tibet: a

multicentre randomised controlled trial.

Wei X(1), Hicks JP(2), Zhang Z(3), Haldane V(4), Pasang P(5), Li L(5), Yin T(6),

Zhang B(6), Li Y(7), Pan Q(8), Liu X(9), Walley J(2), Hu J(10).

Author information:

(1)Dalla Lana School of Public Health, University of Toronto, Toronto, ON,

Canada; Institute of Health Policy, Management and Evaluation, University of

Toronto, Toronto, ON, Canada. Electronic address: xiaolin.wei@utoronto.ca.

(2)Nuffield Centre for International Health and Development, University of

Leeds, Leeds, UK.

(3)Dalla Lana School of Public Health, University of Toronto, Toronto, ON,

Canada.

(4)Institute of Health Policy, Management and Evaluation, University of Toronto,

Toronto, ON, Canada.

(5)Shigatse Centre for Disease Control and Prevention, Shigatse, China.

(6)Weifang Medical College, Weifang, China.

(7)Jining Medical University, Jining, China.

(8)North Sichuan Medical College, Nanchong, China.

(9)National Center for tuberculosis control and Prevention, Chinese Center for

Disease Control and Prevention, Beijing, China.

(10)Shigatse Centre for Disease Control and Prevention, Shigatse, China;

Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China.

Electronic address: sunnyhj@163.com.

BACKGROUND: WHO recommends that electronic medication monitors, a form of

digital adherence technology, be used as a complement to directly observed

treatment (DOT) for tuberculosis, as DOT is inconvenient and costly. However,

existing evidence about the effectiveness of these monitors is inconclusive.

Therefore, we evaluated the effectiveness of a comprehensive package based on

electronic medication monitors among patients with tuberculosis in Tibet

Autonomous Region (hereafter Tibet), China.

METHODS: This multicentre, randomised controlled trial recruited patients from

six counties in Shigatse, Tibet. Eligible participants had drug-susceptible

tuberculosis and were aged 15 years or older when starting standard tuberculosis

treatment. Tuberculosis doctors recruited patients from the public tuberculosis

dispensary in each county and the study statistician randomly assigned them to

the intervention or control group based on the predetermined randomised

allocation sequence. Intervention patients received an electronic medication

monitor box. The box included audio medication-adherence reminders and recorded

box-opening data, which were transmitted to a cloud-based server and were

accessible to health-care providers to allow remote adherence monitoring. A

linked smartphone app enabled text, audio, and video communication between

patients and health-care providers. Patients were also provided with a free data

plan. Patients selected a treatment supporter (often a family member) who was

trained to support patients with using the electronic medication monitor and

app. Patients in the control group received usual care plus a deactivated

electronic medication monitor, which only recorded and transmitted box-opening

data that was not made available to health-care providers. The control group

also had no access to the app or trained treatment supporters. The primary

outcome was a binary indicator of poor monthly adherence, defined as missing 20%

or more of planned doses in the treatment month, measured using electronic

medication monitor opening data, and verified by counting used medication

blister packages during consultations. We recorded other secondary treatment

outcomes based on national tuberculosis reporting data. We analysed the primary

outcome based on the intention-to-treat population. This trial is registered at

ISRCTN, 52132803.

FINDINGS: Between Nov 17, 2018, and April 5, 2021, 278 patients were enrolled

into the study. 143 patients were randomly assigned to the intervention group

and 135 patients to the control group. Follow-up ended when the final patient

completed treatment on Oct 4, 2021. In the intervention group, 87 (10%) of the

854 treatment months showed poor adherence compared with 290 (37%) of the 795

months in the control group. The corresponding adjusted risk difference for the

intervention versus control was -29·2 percentage points (95% CI -35·3 to -22·2;

p<0·0001). Five of the six secondary treatment outcomes also showed clear

improvements, including treatment success, which was found for 133 (94%) of the

142 individuals in the intervention arm and 98 (73%) of the 134 individuals in

the control arm, with an adjusted risk difference of 21 percentage points (95%

CI 12·4-29·4); p<0·0001.

INTERPRETATION: The interventions were effective at improving tuberculosis

treatment adherence and outcomes, and the trial suggests that a comprehensive

package involving electronic medication monitors might positively affect

tuberculosis programmes in high-burden and low-resource settings.

FUNDING: TB REACH.

Copyright © 2024 Elsevier Ltd. All rights reserved.

DOI: 10.1016/S0140-6736(23)02270-5

PMID: 38309280

Conflict of interest statement: Declaration of interests We declare no competing

interests.

16. Cancer Cell. 2024 Jan 8:S1535-6108(23)00449-X. doi: 10.1016/j.ccell.2023.12.021.

Online ahead of print.

Cancer-associated fibroblast phenotypes are associated with patient outcome in

non-small cell lung cancer.

Cords L(1), Engler S(2), Haberecker M(3), Rüschoff JH(3), Moch H(3), de Souza

N(2), Bodenmiller B(4).

Author information:

(1)Department of Quantitative Biomedicine, University of Zurich, 8057 Zurich,

Switzerland; Institute of Molecular Health Sciences, ETH Zurich, 8049 Zurich,

Switzerland; Life Science Zurich Graduate School, ETH Zurich and University of

Zurich, 8057 Zurich, Switzerland.

(2)Department of Quantitative Biomedicine, University of Zurich, 8057 Zurich,

Switzerland; Institute of Molecular Health Sciences, ETH Zurich, 8049 Zurich,

Switzerland.

(3)Department of Pathology and Molecular Pathology, University Hospital Zurich,

8091 Zurich, Switzerland.

(4)Department of Quantitative Biomedicine, University of Zurich, 8057 Zurich,

Switzerland; Institute of Molecular Health Sciences, ETH Zurich, 8049 Zurich,

Switzerland. Electronic address: bernd.bodenmiller@uzh.ch.

Despite advances in treatment, lung cancer survival rates remain low. A better

understanding of the cellular heterogeneity and interplay of cancer-associated

fibroblasts (CAFs) within the tumor microenvironment will support the

development of personalized therapies. We report a spatially resolved

single-cell imaging mass cytometry (IMC) analysis of CAFs in a non-small cell

lung cancer cohort of 1,070 patients. We identify four prognostic patient groups

based on 11 CAF phenotypes with distinct spatial distributions and show that

CAFs are independent prognostic factors for patient survival. The presence of

tumor-like CAFs is strongly correlated with poor prognosis. In contrast,

inflammatory CAFs and interferon-response CAFs are associated with inflamed

tumor microenvironments and higher patient survival. High density of matrix CAFs

is correlated with low immune infiltration and is negatively correlated with

patient survival. In summary, our data identify phenotypic and spatial features

of CAFs that are associated with patient outcome in NSCLC.

Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.

DOI: 10.1016/j.ccell.2023.12.021

PMID: 38242124

Conflict of interest statement: Declaration of interests B.B. has co-founded

Navignostics, a spin-off company of the University of Zurich, and is one of its

shareholders and a board member.

17. Cancer Cell. 2024 Feb 12;42(2):225-237.e5. doi: 10.1016/j.ccell.2024.01.001.

Epub 2024 Jan 25.

Tumor- and circulating-free DNA methylation identifies clinically relevant small

cell lung cancer subtypes.

Heeke S(1), Gay CM(1), Estecio MR(2), Tran H(1), Morris BB(1), Zhang B(1), Tang

X(3), Raso MG(3), Rocha P(4), Lai S(5), Arriola E(4), Hofman P(6), Hofman V(6),

Kopparapu P(7), Lovly CM(7), Concannon K(1), De Sousa LG(1), Lewis WE(1), Kondo

K(2), Hu X(8), Tanimoto A(1), Vokes NI(1), Nilsson MB(1), Stewart A(1), Jansen

M(9), Horváth I(10), Gaga M(11), Panagoulias V(12), Raviv Y(13), Frumkin D(14),

Wasserstrom A(14), Shuali A(14), Schnabel CA(15), Xi Y(16), Diao L(16), Wang

Q(16), Zhang J(17), Van Loo P(18), Wang J(16), Wistuba II(3), Byers LA(19),

Heymach JV(20).

Author information:

(1)Department of Thoracic/Head & Neck Medical Oncology, The University of Texas

MD Anderson Cancer Center, Houston, TX, USA.

(2)Epigenetic and Molecular Carcinogenesis, The University of Texas MD Anderson

Cancer Center, Houston, TX, USA.

(3)Department of Translational Molecular Pathology, the University of Texas MD

Anderson Cancer Center, Houston, TX, USA.

(4)Medical Oncology Department, Hospital del Mar, Barcelona, Spain.

(5)Department of Genetics, The University of Texas MD Anderson Cancer Center,

Houston, TX, USA; Graduate School of Biomedical Sciences, The University of

Texas MD Anderson Cancer Center UTHealth Houston, Houston, TX, USA.

(6)Laboratory of Clinical and Experimental Pathology, IHU RespirERA, Nice

Hospital, University Côte d'Azur, Nice, France.

(7)Department of Medicine, Division of Hematology and Oncology, Vanderbilt

University Medical Center, Nashville, TN, USA.

(8)Department of Genomic Medicine, The University of Texas MD Anderson Cancer

Center, Houston, TX, USA.

(9)Pulmonary Department, Ziekenhuisgroep Twente, Hengelo, the Netherlands.

(10)National Korányi Institute of Pulmonology, Budapest, Hungary.

(11)7th Respiratory Medicine Department, Athens Chest Hospital, Athens, Greece.

(12)2nd Respiratory Medicine Department, Athens Chest Hospital, Athens, Greece.

(13)Department of Medicine, Pulmonology, Institute, Soroka Medical Center,

Ben-Gurion University, Beer-Sheva, Israel.

(14)Nucleix Ltd. Rehovot, Israel.

(15)Nucleix Inc, San Diego, CA, USA.

(16)Department of Bioinformatics and Computational Biology, the University of

Texas MD Anderson Cancer Center, Houston, TX, USA.

(17)Department of Thoracic/Head & Neck Medical Oncology, The University of Texas

MD Anderson Cancer Center, Houston, TX, USA; Department of Genomic Medicine, The

University of Texas MD Anderson Cancer Center, Houston, TX, USA.

(18)Department of Genetics, The University of Texas MD Anderson Cancer Center,

Houston, TX, USA; Department of Genomic Medicine, The University of Texas MD

Anderson Cancer Center, Houston, TX, USA; The Francis Crick Institute, London,

UK.

(19)Department of Thoracic/Head & Neck Medical Oncology, The University of Texas

MD Anderson Cancer Center, Houston, TX, USA. Electronic address:

lbyers@mdanderson.org.

(20)Department of Thoracic/Head & Neck Medical Oncology, The University of Texas

MD Anderson Cancer Center, Houston, TX, USA. Electronic address:

jheymach@mdanderson.org.

Small cell lung cancer (SCLC) is an aggressive malignancy composed of distinct

transcriptional subtypes, but implementing subtyping in the clinic has remained

challenging, particularly due to limited tissue availability. Given the known

epigenetic regulation of critical SCLC transcriptional programs, we hypothesized

that subtype-specific patterns of DNA methylation could be detected in tumor or

blood from SCLC patients. Using genomic-wide reduced-representation bisulfite

sequencing (RRBS) in two cohorts totaling 179 SCLC patients and using machine

learning approaches, we report a highly accurate DNA methylation-based

classifier (SCLC-DMC) that can distinguish SCLC subtypes. We further adjust the

classifier for circulating-free DNA (cfDNA) to subtype SCLC from plasma. Using

the cfDNA classifier (cfDMC), we demonstrate that SCLC phenotypes can evolve

during disease progression, highlighting the need for longitudinal tracking of

SCLC during clinical treatment. These data establish that tumor and cfDNA

methylation can be used to identify SCLC subtypes and might guide precision SCLC

therapy.

Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.

DOI: 10.1016/j.ccell.2024.01.001

PMID: 38278149 [Indexed for MEDLINE]

Conflict of interest statement: Declaration of interests S.H., C.M.G., L.A.B.,

and J.V.H. own intellectual property on the classification of SCLC from DNA

methylation and gene expression. D.F., A.W., A.S., and C.A.S. are full time

employees of Nucleix and own stocks and stock options of Nucleix. Furthermore,

S.H. reports consulting fees from Guardant Health, AstraZeneca, Boehringer

Ingelheim, and Qiagen. C.M.G. is a member of the advisory board at Jazz

Pharmaceuticals, AstraZeneca, and Bristol Myers Squibb and served as speaker for

AstraZeneca and BeiGene. P.R. received travel support from AstraZeneca, BMS, and

MSD. E.A. reports consulting fees from Eli Lilly, AstraZeneca, BMS, Boehringer

Ingelheim, Takeda, Roche, and MSD, speaker’s fees from AstraZeneca, BMS,

Boehringer Ingelheim, Roche, and MSD, research funding from Roche and

AstraZeneca and travel support from AstraZeneca and Takeda. P.H. reports

research grants from Thermo Fisher Scientific and Biocartis, and speakers’ fees

from AstraZeneca, Roche, Novartis, Bristol-Myers Squibb, Pfizer, Bayer,

Illumina, Biocartis, Thermo Fisher Scientific, AbbVie, Amgen, Janssen, Eli

Lilly, Daiichi Sankyo, Pierre Fabre, and Guardant. V.H. reports speakers’ fees

from BMS. C.M.L. reports personal fees from Amgen, Arrivent, AstraZeneca,

Blueprints Medicine, Cepheid, D2G Oncology, Daiichi Sankyo, Eli Lilly, EMD

Serono, Foundation Medicine, Genentech, Janssen, Medscape, Novartis, Pfizer,

Puma, Syros, and Takeda. N.V. receives consulting fees from Sanofi, Regeneron,

Oncocyte, and Eli Lilly, and research funding from Mirati. M.B.N. receives

royalties and licensing fees from Spectrum Pharmaceuticals. I.H. received

personal as well as institutional funding from Nucleix. J.Z. served on advisory

board for AstraZeneca and Geneplus and received speaker’s fees from BMS,

Geneplus, OrigMed, Innovent and grants from Merck, Johnson and Johnson. L.A.B

received consulting fees and research funding from AstraZeneca, GenMab, Sierra

Oncology, research funding from ToleroPharmaceuticals and served as advisor or

consultant for PharmaMar, AbbVie, Bristol-Myers Squibb, Alethia, Merck, Pfizer,

Jazz Pharmaceuticals, Genentech, and Debiopharm Group. J.V.H. served as advisor

for AstraZeneca, EMD Serono, Boehringer-Ingelheim, Catalyst, Genentech,

GlaxoSmithKline, Guardant Health, Foundation medicine, Hengrui Therapeutics, Eli

Lilly, Novartis, Spectrum, Sanofi, Takeda, Mirati Therapeutics, BMS, BrightPath

Biotherapeutics, Janssen Global Services, Nexus Health Systems, Pneuma

Respiratory, Kairos Venture Investments, Roche, Leads Biolabs, RefleXion, Chugai

Pharmaceuticals, received research support from AstraZeneca, GlaxoSmithKline,

Spectrum as well as royalties and licensing fees from Spectrum.

18. Nat Rev Clin Oncol. 2024 Feb;21(2):121-146. doi: 10.1038/s41571-023-00844-0.

Epub 2024 Jan 9.

Lung cancer in patients who have never smoked - an emerging disease.

LoPiccolo J(1)(2), Gusev A(3)(4), Christiani DC(5)(6), Jänne PA(3)(7).

Author information:

(1)Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA,

USA. jaclyn_lopiccolo@dfci.harvard.edu.

(2)The Lowe Center for Thoracic Oncology, Dana-Farber Cancer Institute, Boston,

MA, USA. jaclyn_lopiccolo@dfci.harvard.edu.

(3)Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA,

USA.

(4)The Eli and Edythe L. Broad Institute, Cambridge, MA, USA.

(5)Department of Environmental Health, Harvard T. H. Chan School of Public

Health, Boston, MA, USA.

(6)Massachusetts General Hospital, Boston, MA, USA.

(7)The Lowe Center for Thoracic Oncology, Dana-Farber Cancer Institute, Boston,

MA, USA.

Lung cancer is the most common cause of cancer-related deaths globally. Although

smoking-related lung cancers continue to account for the majority of diagnoses,

smoking rates have been decreasing for several decades. Lung cancer in

individuals who have never smoked (LCINS) is estimated to be the fifth most

common cause of cancer-related deaths worldwide in 2023, preferentially

occurring in women and Asian populations. As smoking rates continue to decline,

understanding the aetiology and features of this disease, which necessitate

unique diagnostic and treatment paradigms, will be imperative. New data have

provided important insights into the molecular and genomic characteristics of

LCINS, which are distinct from those of smoking-associated lung cancers and

directly affect treatment decisions and outcomes. Herein, we review the emerging

data regarding the aetiology and features of LCINS, particularly the genetic and

environmental underpinnings of this disease as well as their implications for

treatment. In addition, we outline the unique diagnostic and therapeutic

paradigms of LCINS and discuss future directions in identifying individuals at

high risk of this disease for potential screening efforts.

© 2024. Springer Nature Limited.

DOI: 10.1038/s41571-023-00844-0

PMID: 38195910 [Indexed for MEDLINE]

19. Nat Med. 2024 Jan;30(1):218-228. doi: 10.1038/s41591-023-02660-6. Epub 2023 Oct 30.

Association between pathologic response and survival after neoadjuvant therapy

in lung cancer.

Deutsch JS(1), Cimino-Mathews A(1), Thompson E(1), Provencio M(2), Forde PM(1),

Spicer J(3), Girard N(4), Wang D(1), Anders RA(1), Gabrielson E(1), Illei P(1),

Jedrych J(1), Danilova L(1), Sunshine J(1), Kerr KM(5), Tran M(6), Bushong J(6),

Cai J(6), Devas V(6), Neely J(6), Balli D(6), Cottrell TR(7), Baras AS(1), Taube

JM(8)(9).

Author information:

(1)Bloomberg-Kimmel Institute for Cancer Immunotherapy, Johns Hopkins University

School of Medicine, Baltimore, MD, USA.

(2)Hospital Universitario Puerta de Hierro, Madrid, Spain.

(3)McGill University Health Center, Montreal, Québec, Canada.

(4)Institut du Thorax Curie-Montsouris, Institut Curie, Paris, France.

(5)Aberdeen Royal Infirmary, Aberdeen, UK.

(6)Bristol Myers Squibb, Princeton, NJ, USA.

(7)Queen's University, Kingston, Ontario, Canada.

(8)Bloomberg-Kimmel Institute for Cancer Immunotherapy, Johns Hopkins University

School of Medicine, Baltimore, MD, USA. jtaube1@jhmi.edu.

(9)The Mark Foundation Center for Advanced Genomics and Imaging, Johns Hopkins

University School of Medicine, Baltimore, MD, USA. jtaube1@jhmi.edu.

Neoadjuvant immunotherapy plus chemotherapy improves event-free survival (EFS)

and pathologic complete response (0% residual viable tumor (RVT) in primary

tumor (PT) and lymph nodes (LNs)), and is approved for treatment of resectable

lung cancer. Pathologic response assessment after neoadjuvant therapy is the

potential analog to radiographic response for advanced disease. However, %RVT

thresholds beyond pathologic complete response and major pathologic response

(≤10% RVT) have not been explored. Pathologic response was prospectively

assessed in the randomized, phase 3 CheckMate 816 trial (NCT02998528), which

evaluated neoadjuvant nivolumab (anti-programmed death protein 1) plus

chemotherapy in patients with resectable lung cancer. RVT, regression and

necrosis were quantified (0-100%) in PT and LNs using a pan-tumor scoring system

and tested for association with EFS in a prespecified exploratory analysis.

Regardless of LN involvement, EFS improved with 0% versus >0% RVT-PT (hazard

ratio = 0.18). RVT-PT predicted EFS for nivolumab plus chemotherapy (area under

the curve = 0.74); 2-year EFS rates were 90%, 60%, 57% and 39% for patients with

0-5%, >5-30%, >30-80% and >80% RVT, respectively. Each 1% RVT associated with a

0.017 hazard ratio increase for EFS. Combining pathologic response from PT and

LNs helped differentiate outcomes. When compared with radiographic response and

circulating tumor DNA clearance, %RVT best approximated EFS. These findings

support pathologic response as an emerging survival surrogate. Further

assessment of the full spectrum of %RVT in lung cancer and other tumor types is

warranted. ClinicalTrials.gov registration: NCT02998528 .

© 2023. The Author(s).

DOI: 10.1038/s41591-023-02660-6

PMCID: PMC10803255

PMID: 37903504 [Indexed for MEDLINE]

Conflict of interest statement: J.S.D. reports being named on a patent for

system and method for annotating pathology images to predict patient outcome (US

Provisional Patent Application: 63/313,548; filed 2/24/2022). A.C.-M. reports

receiving grants or contracts from Bristol Myers Squibb. M.P. reports receiving

grants or contracts from AstraZeneca, Bristol Myers Squibb, Janssen, Pfizer,

Roche and Takeda; and honoraria from AstraZeneca, Bristol Myers Squibb, MSD,

Pfizer, Roche and Takeda. P.M.F. reports research funding received by his

institution from AstraZeneca, BioNTech, Bristol Myers Squibb, Corvus, Kyowa,

Novartis and Regeneron; trial steering committee membership for AstraZeneca,

BioNTech, Bristol Myers Squibb and Corvus; participation in advisory boards and

reimbursement from Amgen, AstraZeneca, Bristol Myers Squibb, Daiichi, F-Star

Therapeutics, G1 Therapeutics, Genentech, ITeos Therapeutics, Janssen, Merck,

Novartis, Sanofi and Surface; and leadership positions at Mesothelioma Applied

Research Foundation and LUNGevity Foundation. J. Spicer reports research funding

received by his institution from AstraZeneca, Bristol Myers Squibb, CLS

Therapeutics, Protalix Biotherapeutics, Merck and Roche; receiving support for

the present manuscript from Bristol Myers Squibb; consulting fees from Amgen,

AstraZeneca, Bristol Myers Squibb, Merck, Novartis, Protalix Biotherapeutics,

Regeneron, Roche and Xenetic Biosciences; honoraria from AstraZeneca, Bristol

Myers Squibb and PeerView; participation on data safety monitoring/advisory

boards for the PUCC trial; and leadership positions at the Canadian Association

of Thoracic Surgeons (unpaid). N.G. reports receiving consulting fees from

Amgen, AstraZeneca, Bristol Myers Squibb, Eli Lilly, Janssen, MSD, Novartis,

Pfizer, Roche, Sanofi and Takeda; and meeting/travel support from Roche. R.A.A.

reports receiving support for the present manuscript from Bristol Myers Squibb;

grants or contracts from RAPT Therapeutics; consulting fees from AstraZeneca and

MSD; and meeting/travel support from Bristol Myers Squibb. E.G. reports research

funding received by his institution from the National Cancer Institute and

Congressionally Directed Medical Research Programs—Department of Defense;

honoraria from the LUNGevity Foundation; expert testimony provided to Covington

and Burling; and holding mutual funds and exchange traded funds. P.I. reports

receiving support for the present manuscript from Bristol Myers Squibb; grants

or contracts from Bristol Myers Squibb; consulting fees from AbbVie,

AstraZeneca, Merus, Roche and Sanofi; honoraria from Bristol Myers Squibb, Eli

Lilly and Genentech; and being a shareholder of Bristol Myers Squibb. J.

Sunshine reports grants or contracts from Palleon Pharmaceuticals. K.M.K.

reports consulting fees from AbbVie, Amgen, AstraZeneca, Bayer, Boehringer

Ingelheim, Bristol Myers Squibb, Janssen, Merck Serono, Merck Sharp & Dohme,

Novartis, Pfizer, Regeneron, Roche, Takeda and Ventana; and honoraria from

AstraZeneca, Amgen, Boehringer Ingelheim, Bristol Myers Squibb, Janssen,

Medscape, Merck Serono, Merck Sharp & Dohme, Novartis, Pfizer, Prime Oncology,

Roche and Ventana. M.T. is an employee and shareholder of Bristol Myers Squibb.

J.B. is an employee and shareholder of Bristol Myers Squibb. J.C. is an employee

and shareholder of Bristol Myers Squibb. V.D. is an employee and shareholder of

Bristol Myers Squibb. J.N. is an employee and shareholder of Bristol Myers

Squibb. D.B. is an employee and shareholder of Bristol Myers Squibb; and reports

being named on a patent of Bristol Myers Squibb. T.R.C. reports research funding

received by her institution from Janssen; and honoraria from AstraZeneca,

Society for Immunotherapy of Cancer and TotalCME. J.M.T. reports receiving

support for the present manuscript from Bristol Myers Squibb; consulting fees

from AstraZeneca, Bristol Myers Squibb, Merck and Roche; participation on

advisory boards from AstraZeneca; and being named on a patent for a machine

learning algorithm for irPRC. The other authors declare no competing interests.

20. Nat Immunol. 2024 Jan 15. doi: 10.1038/s41590-023-01739-z. Online ahead of

print.

BCG immunization induces CX3CR1(hi) effector memory T cells to provide

cross-protection via IFN-γ-mediated trained immunity.

Tran KA(1), Pernet E(1)(2), Sadeghi M(1), Downey J(1), Chronopoulos J(1),

Lapshina E(1), Tsai O(1), Kaufmann E(1)(3), Ding J(1), Divangahi M(4).

Author information:

(1)Department of Medicine, Department of Pathology, Department of Microbiology &

Immunology, Research Institute of the McGill University Health Centre, McGill

International TB Centre, Meakins-Christie Laboratories, McGill University,

Montreal, Quebec, Canada.

(2)Department of Medical Biology, Université du Québec à Trois-Rivières, Quebec,

Quebec, Canada.

(3)Department of Biomedical and Molecular Sciences, Queen's University,

Kingston, Ontario, Canada.

(4)Department of Medicine, Department of Pathology, Department of Microbiology &

Immunology, Research Institute of the McGill University Health Centre, McGill

International TB Centre, Meakins-Christie Laboratories, McGill University,

Montreal, Quebec, Canada. maziar.divangahi@mcgill.ca.

Erratum in

    Nat Immunol. 2024 Feb 1;:

After a century of using the Bacillus Calmette-Guérin (BCG) vaccine, our

understanding of its ability to provide protection against homologous

(Mycobacterium tuberculosis) or heterologous (for example, influenza virus)

infections remains limited. Here we show that systemic (intravenous) BCG

vaccination provides significant protection against subsequent influenza A virus

infection in mice. We further demonstrate that the BCG-mediated cross-protection

against influenza A virus is largely due to the enrichment of conventional CD4+

effector CX3CR1hi memory αβ T cells in the circulation and lung parenchyma.

Importantly, pulmonary CX3CR1hi T cells limit early viral infection in an

antigen-independent manner via potent interferon-γ production, which

subsequently enhances long-term antimicrobial activity of alveolar macrophages.

These results offer insight into the unknown mechanism by which BCG has

persistently displayed broad protection against non-tuberculosis infections via

cross-talk between adaptive and innate memory responses.

© 2024. The Author(s), under exclusive licence to Springer Nature America, Inc.

DOI: 10.1038/s41590-023-01739-z

PMID: 38225437