Integrating NGS-derived mutational profiling in the diagnosis of multiple lung adenocarcinomas

Nicole Ezer; Hangjun Wang; Andrea Gomez Corredor; Pierre Olivier Fiset; Ayesha Baig; Léon C van Kempen; George Chong; Marianne S M Issac; Richard Fraser; Alan Spatz; Jean-Baptiste Riviere; Philippe Broët; Jonathan Spicer; Sophie Camilleri-Broët

doi:10.1016/j.ctarc.2021.100484

Integrating NGS-derived mutational profiling in the diagnosis of multiple lung adenocarcinomas

Cancer Treat Res Commun. 2021:29:100484. doi: 10.1016/j.ctarc.2021.100484. Epub 2021 Oct 29.

Affiliations

¹ Department of Medicine, Division of Respirology, McGill University Health Center, 1001 Decarie Blvd., Montreal, QC, Canada; Centre for Outcomes Research and Evaluation - Research Institute of the McGill University Health Center, Montreal, 1001 Decarie Blvd., QC, Canada.
² Division of Pathology, McGill University Health Center, 1001 Decarie Blvd., Montreal, QC, Canada; OPTILAB-MUHC & Department of Laboratory Medicine, 1001 Decarie Blvd., Montreal, QC, Canada; Research Molecular Pathology Center, Lady Davis Institute, 3755 Côte Ste-Catherine Road, Montreal, QC, Canada.
³ OPTILAB-MUHC & Department of Laboratory Medicine, 1001 Decarie Blvd., Montreal, QC, Canada; Division of Molecular Genetics, McGill University Health Center, 1001 Decarie Blvd., Montreal, QC, Canada.
⁴ Division of Pathology, McGill University Health Center, 1001 Decarie Blvd., Montreal, QC, Canada; OPTILAB-MUHC & Department of Laboratory Medicine, 1001 Decarie Blvd., Montreal, QC, Canada.
⁵ OPTILAB-MUHC & Department of Laboratory Medicine, 1001 Decarie Blvd., Montreal, QC, Canada; Division of Molecular Genetics, McGill University Health Center, 1001 Decarie Blvd., Montreal, QC, Canada; University Medical Center of Groningen, PO box 30.001, 9700 RB, Groningen, Netherlands.
⁶ Research Institute of the McGill University Health Centre, 1001 Decarie Blvd, Montreal, QC, Canada; Department of Clinical and Chemical Pathology, Faculty of Medicine, Cairo University, El Saray St., El Manial, Postal Code 11956, Cairo, Egypt.
⁷ UMR 1018, INSERM, CESP, Paris-Saclay University, Faculty of Medicine, Paul-Brousse Hospital AP-AP, Villejuif, France; Research Center, CHU Ste-Justine, University of Montreal, 3175 Côte-Sainte-Catherine Road, H3T 1C5, Montreal, QC, Canada.
⁸ Division of Thoracic and Upper GI Surgery, McGill University Health Center, 1650 Cedar Avenue Montreal, H3G 1A4, Montreal, QC, Canada.
⁹ Division of Pathology, McGill University Health Center, 1001 Decarie Blvd., Montreal, QC, Canada; OPTILAB-MUHC & Department of Laboratory Medicine, 1001 Decarie Blvd., Montreal, QC, Canada. Electronic address: sophie.camilleri-broet@mcgill.ca.

PMID: 34773797
DOI: 10.1016/j.ctarc.2021.100484

Abstract

Microabstract: Integration of Next Generation Sequencing (NGS) information for use in distinguishing between Multiple Primary Lung Cancer and intrapulmonary metastasis was evaluated. We used a probabilistic model, comprehensive histologic assessment and NGS to classify patients. Integrating NGS data confirmed initial diagnosis (n = 41), revised the diagnosis (n = 12), while resulted in non-informative data (n = 8). Accuracy of diagnosis can be significantly improved with integration of NGS data.

Background: Distinguishing between multiple primary lung cancers (MPLC) and intrapulmonary metastases (IPM) is challenging. The goal of this study was to evaluate how Next Generation Sequencing (NGS) information may be integrated in the diagnostic strategy.

Patients and methods: Patients with multiple lung adenocarcinomas were classified using both the comprehensive histologic assessment and NGS. We computed the joint probability of each pair having independent mutations by chance (thus being classified as MPLC). These probabilities were computed using the marginal mutation rates of each mutation, and the known negative dependencies between driver genes and different gene loci. With these NGS-driven data, cases were re-classified as MPLC or IPM.

Results: We analyzed 61 patients with a total of 131 tumors. The most frequent mutation was KRAS (57.3%) which occured at a rate higher than expected (p < 0.001) in lung cancer. No mutation was detected in 25/131 tumors (19.1%). Discordant molecular findings between tumor sites were found in 46 patients (75.4%); 11 patients (18.0%) had concordant molecular findings, and 4 patients (6.6%) had concordant molecular findings at 2 of the 3 sites. After integration of the NGS data, the initial diagnosis was confirmed for 41 patients (67.2%), the diagnosis was revised for 12 patients (19.7%) or was considered as non-informative for 8 patients (13.1%).

Conclusion: Integrating the information of NGS data may significantly improve accuracy of diagnosis and staging.

Keywords: Comprehensive histologic assessment; Intrapulmonary metastases; Multiple primary lung cancers; NGS; Probabilistic model.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Adenocarcinoma of Lung / diagnosis*
Adenocarcinoma of Lung / pathology
Aged
Aged, 80 and over
Female
High-Throughput Nucleotide Sequencing / methods*
Humans
Lung Neoplasms / diagnosis*
Lung Neoplasms / pathology
Male
Middle Aged
Mutation