Proposal for a Combined Histomolecular Algorithm to Distinguish Multiple Primary Adenocarcinomas from Intrapulmonary Metastasis in Patients with Multiple Lung Tumors.

Introduction: Multiple nodules in the lung are being diagnosed with an increasing frequency thanks to high-quality computed tomography imaging. In patients with lung cancer, this situation represents up to 10% of patients who have an operation. For clinical management, it is important to classify th...

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Publicado en:Journal of Thoracic Oncology Vol. 14; no. 5; pp. 844 - 857
Autores principales: Mansuet-Lupo, Audrey, Barritault, Marc, Alifano, Marco, Janet-Vendroux, Aurélie, Zarmaev, Makmoud, Biton, Jérôme, Velut, Yoan, Le Hay, Christine, Cremer, Isabelle, Régnard, Jean-François, Fournel, Ludovic, Rance, Bastien, Wislez, Marie, Laurent-Puig, Pierre, Herbst, Ronald, Damotte, Diane, Blons, Hélène
Formato: research tables/charts Journal Article
Publicado: Elsevier B.V. May2019
Acceso en línea:Ver este registro en EBSCOhost
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      dt: May2019
      vid: 14
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      pub: Elsevier B.V.
      place: New York, New York
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        10.1016/j.jtho.2019.01.017
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        atl: Proposal for a Combined Histomolecular Algorithm to Distinguish Multiple Primary Adenocarcinomas from Intrapulmonary Metastasis in Patients with Multiple Lung Tumors.
      aug:
        au:
          Mansuet-Lupo, Audrey
          Barritault, Marc
          Alifano, Marco
          Janet-Vendroux, Aurélie
          Zarmaev, Makmoud
          Biton, Jérôme
          Velut, Yoan
          Le Hay, Christine
          Cremer, Isabelle
          Régnard, Jean-François
          Fournel, Ludovic
          Rance, Bastien
          Wislez, Marie
          Laurent-Puig, Pierre
          Herbst, Ronald
          Damotte, Diane
          Blons, Hélène
        affil: Department of Pathology, Hôpitaux Universitaire Paris Centre, Cochin Hospital, Assistance Publique–Hôpitaux de Paris, Paris, France
      sug:
        subj:
          Sequence Analysis Methods
          Adenocarcinoma Complications
          Neoplasms, Multiple Primary Complications
          Lung Neoplasms
          Neoplasm Metastasis
          Algorithms
          Aged, 80 and Over
          Adult
          Male
          Adenocarcinoma Pathology
          Human
          Female
          Middle Age
          Lung Neoplasms Pathology
          Aged
          Validation Studies
          Comparative Studies
          Evaluation Research
          Multicenter Studies
          Aged, 80 & over
          Adult: 19-44 years
          Middle Aged: 45-64 years
          Aged: 65+ years
          Male
          Female
      ab: Introduction: Multiple nodules in the lung are being diagnosed with an increasing frequency thanks to high-quality computed tomography imaging. In patients with lung cancer, this situation represents up to 10% of patients who have an operation. For clinical management, it is important to classify the disease as intrapulmonary metastasis or multiple primary lung carcinoma to define TNM classification and optimize therapeutic options. In the present study, we evaluated the respective and combined input of histological and molecular classification to propose a classification algorithm for multiple nodules.Methods: We studied consecutive patients undergoing an operation with curative intent for lung adenocarcinoma (N = 120) and harboring two tumors (N = 240). Histological diagnosis according to the WHO 2015 classification and molecular profiling using next-generation sequencing targeting 22 hotspot genes allowed classification of samples as multiple primary lung adenocarcinomas or as intrapulmonary metastasis.Results: Next-generation sequencing identified molecular mutations in 91% of tumor pairs (109 of 120). Genomic and histological classification showed a fair agreement when the κ test was used (κ = 0.43). Discordant cases (30 of 109 [27%]) were reclassified by using a combined histomolecular algorithm. EGFR mutations (p = 0.03) and node involvement (p = 0.03) were significantly associated with intrapulmonary metastasis, whereas KRAS mutations (p = 0.00005) were significantly associated with multiple primary lung adenocarcinomas. EGFR mutations (p = 0.02) and node involvement (p = 0.004) were the only independent prognostic factors.Conclusion: We showed that combined histomolecular algorithm represents a relevant tool to classify multifocal lung cancers, which could guide adjuvant treatment decisions. Survival analysis underlined the good prognosis of EGFR-mutated adenocarcinoma in patients with intrapulmonary metastasis.
      pubtype: Academic Journal
      doctype:
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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