Exposure to Occupational Carcinogens and Non-Oncogene Addicted Phenotype in Lung Cancer: Results from a Real-Life Observational Study

<b>Background/Objectives</b>: Lung cancer (LC) remains one of the most lethal malignancies worldwide, with both environmental and occupational exposures contributing to its incidence. While oncogene-addicted tumors-defined by single driver mutations-have garnered attention due to their therapeutic implications, less is known about the mutational landscape of tumors potentially arising from occupational exposure to carcinogens. This real-life observational study aimed to assess whether previous occupational exposure to lung carcinogens correlates with distinct LC phenotypes, particularly non-oncogene-addicted (nOA) profiles. <b>Methods</b>: A total of 199 LC patients were enrolled across two specialized oncology centers in Northern Italy between 2021 and 2023. Each participant underwent detailed occupational history taking and molecular characterization using next-generation sequencing. Patients were stratified into nonexposed (NE), low exposed (LE), and high exposed (HE) to carcinogens for lung based on standardized questionnaires and sector-specific assessments. <b>Results</b>: No significant differences were found in histological subtypes across exposure groups. However, people with adenocarcinoma and high occupational exposure to lung carcinogens were more frequently characterized by a nOA phenotype compared to those with low occupational exposure. Logistic regression models-adjusted for age, sex, and smoking habits-confirmed that HE patients had a significantly higher likelihood of developing nOA tumors (OR = 3.07; 95% CI: 1.16-8.11; <i>p</i> = 0.023). This association persisted after adjusting for smoking habits Exposures occurring 5-10 years before diagnosis seemed to be associated with an increased nOA profile. <b>Conclusions</b>: These findings suggest that high levels of exposure to occupational carcinogens impact LC phenotypes. Indeed, these phenotypes are more complex to treat and show the worst prognosis. Assessing the occupational exposure to lung carcinogens during work may offer prognostic insights and support the request for more adequate compensation for the patients. Further studies are warranted to validate these results and to explain the mechanisms that produce the differences observed in LC phenotypes in people with high exposure to occupational carcinogens.

Authors

Institutions

Publication Details

Journal
Cancers
Published
2025-09-13
DOI
https://doi.org/10.3390/cancers17182997
Primary Topic
Lung Cancer Treatments and Mutations
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Exposure to Occupational Carcinogens and Non-Oncogene Addicted Phenotype in Lung Cancer: Results from a Real-Life Observational Study

Luca Toschi, Laura D. Locati, Roberta Pernetti, Enrico Oddone et al.
Cancers
Lung Cancer Treatments and Mutations
article

Exposure to Occupational Carcinogens and Non-Oncogene Addicted Phenotype in Lung Cancer: Results from a Real-Life Observational Study

Luca Toschi, Laura D. Locati, Roberta Pernetti, Enrico Oddone, Franca Barbic, Luca D’Amato, Luisa Spina, Giulia Riva, C. Iglesias Conde, Domenico Madeo, Federico Sottotetti, L. Ferrante, Sara Farinatti
article en

Abstract

<b>Background/Objectives</b>: Lung cancer (LC) remains one of the most lethal malignancies worldwide, with both environmental and occupational exposures contributing to its incidence. While oncogene-addicted tumors-defined by single driver mutations-have garnered attention due to their therapeutic implications, less is known about the mutational landscape of tumors potentially arising from occupational exposure to carcinogens. This real-life observational study aimed to assess whether previous occupational exposure to lung carcinogens correlates with distinct LC phenotypes, particularly non-oncogene-addicted (nOA) profiles. <b>Methods</b>: A total of 199 LC patients were enrolled across two specialized oncology centers in Northern Italy between 2021 and 2023. Each participant underwent detailed occupational history taking and molecular characterization using next-generation sequencing. Patients were stratified into nonexposed (NE), low exposed (LE), and high exposed (HE) to carcinogens for lung based on standardized questionnaires and sector-specific assessments. <b>Results</b>: No significant differences were found in histological subtypes across exposure groups. However, people with adenocarcinoma and high occupational exposure to lung carcinogens were more frequently characterized by a nOA phenotype compared to those with low occupational exposure. Logistic regression models-adjusted for age, sex, and smoking habits-confirmed that HE patients had a significantly higher likelihood of developing nOA tumors (OR = 3.07; 95% CI: 1.16-8.11; <i>p</i> = 0.023). This association persisted after adjusting for smoking habits Exposures occurring 5-10 years before diagnosis seemed to be associated with an increased nOA profile. <b>Conclusions</b>: These findings suggest that high levels of exposure to occupational carcinogens impact LC phenotypes. Indeed, these phenotypes are more complex to treat and show the worst prognosis. Assessing the occupational exposure to lung carcinogens during work may offer prognostic insights and support the request for more adequate compensation for the patients. Further studies are warranted to validate these results and to explain the mechanisms that produce the differences observed in LC phenotypes in people with high exposure to occupational carcinogens.

CancersVol. 17(18)
Humanitas University (IT), University of Pavia (IT), Istituti Clinici Scientifici Maugeri (IT), IRCCS Humanitas Research Hospital (IT)
Openalex Percentile: Top 64%
Lung Cancer Treatments and Mutations
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.