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Unraveling Tumor Grading and Genomic Landscape in Lung Neuroendocrine Tumors

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Abstract

Currently, grading in lung neuroendocrine tumors (NETs) is inherently defined by the histological classification based on cell features, mitosis count, and necrosis, for which typical carcinoids (TC) are low-grade malignant tumors with long life expectation, atypical carcinoids (AC) intermediate-grade malignant tumors with more aggressive clinical behavior, and large cell NE carcinomas (LCNEC) and small cell lung carcinomas (SCLC) high-grade malignant tumors with dismal prognosis. While Ki-67 antigen labeling index, highlighting the proportion of proliferating tumor cells, has largely been used in digestive NETs for assessing prognosis and assisting therapy decisions, the same marker does not play an established role in the diagnosis, grading, and prognosis of lung NETs. Next generation sequencing techniques (NGS), thanks to their astonishing ability to process in a shorter timeframe up to billions of DNA strands, are radically revolutionizing our approach to diagnosis and therapy of tumors, including lung cancer. When applied to single genes, panels of genes, exome, or the whole genome by using either frozen or paraffin tissues, NGS techniques increase our understanding of cancer, thus realizing the bases of precision medicine. Data are emerging that TC and AC are mainly altered in chromatin remodeling genes, whereas LCNEC and SCLC are also mutated in cell cycle checkpoint and cell differentiation regulators. A common denominator to all lung NETs is a deregulation of cell proliferation, which represents a biological rationale for morphologic (mitoses and necrosis) and molecular (Ki-67 antigen) parameters to successfully serve as predictors of tumor behavior (i.e., identification of pathological entities with clinical correlation). It is envisaged that a novel grading system in lung NETs based on the combined assessment of mitoses, necrosis, and Ki-67 LI may offer a better stratification of prognostic classes, realizing a bridge between molecular alterations, morphological features, and clinical behavior.

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Acknowledgments

This work was presented in part at the meeting in honor of Carlo Capella “The Birth and Growth of the Varese School of Pathology: The Bright and Fascinating World of Neuroendocrine Cells” under the title “Neuroendocrine Tumors of the Lung.” This work was supported by LILT (Lega Italiana per la Lotta contro i Tumori, Sezione di Milano) and is dedicated to the memory of Carlotta, an extraordinarily lively girl who untimely died of cancer in the prime of life.

Conflict of Interest Disclosures

None of the authors have anything to declare.

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Authors and Affiliations

  1. Department of Pathology and Laboratory Medicine, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy

    Giuseppe Pelosi

  2. Department of Biomedical and Clinical Sciences Luigi Sacco, Università degli Studi, Milan, Italy

    Giuseppe Pelosi

  3. Department of Oncology, Università degli Studi of Turin at San Luigi Hospital, Orbassano, Torino, Italy

    Mauro Papotti

  4. Institute of Anatomic Pathology, Gemelli Hospital and Università Cattolica del Sacro Cuore, Rome, Italy

    Guido Rindi

  5. Department of Pathology and Diagnostics, Università degli Studi, Verona, Italy

    Aldo Scarpa

  6. ARC-NET Research Centre, Università degli Studi, Verona, Italy

    Aldo Scarpa

  7. Dipartimento di Patologia Diagnostica e Laboratorio, Fondazione IRCCS Istituto Nazionale dei Tumori, Via G. Venezian, 1, 20133, Milan, Italy

    Giuseppe Pelosi

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  1. Giuseppe Pelosi
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  2. Mauro Papotti
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  3. Guido Rindi
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  4. Aldo Scarpa
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Correspondence to Giuseppe Pelosi.

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Pelosi, G., Papotti, M., Rindi, G. et al. Unraveling Tumor Grading and Genomic Landscape in Lung Neuroendocrine Tumors. Endocr Pathol 25, 151–164 (2014). https://doi.org/10.1007/s12022-014-9320-0

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  • DOI: https://doi.org/10.1007/s12022-014-9320-0

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