Genomic profiling of large-cell neuroendocrine carcinoma of the lung.

Miyoshi, Tomohiro; Umemura, Shigeki; Matsumura, Yuki; Mimaki, Sachiyo; Tada, Satoshi; Ishii, Genichiro; Matsumoto, Shingo; Yoh, Kiyotaka; Niho, Seiji; Ohmatsu, Hironobu; Aokage, Keiju; Hishida, Tomoyuki; Nagai, Kanji; Goto, Kōichi; Tsuboi, Masahiro; Tsuchihara, Katsuya

doi:10.1200/jco.2015.33.15_suppl.7519

Cited by 47 publications

(101 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For example, the high frequency of inactivating mutations in RB1 was observed in all three tumor types. The mutation frequency of RB1 identified in our study was consistent with the findings of previous studies, which reported a mutation frequency of 39–69.5% in SCLC and 38% in LCNEC . We revealed 50% and 36% prevalence in SCLC and LCNEC patients, respectively.…”

Section: Discussionsupporting

confidence: 92%

“…It is becoming evident that a subset of LCNEC tumors shares mutational patterns with SCLC and LCC, whereas others carry mutations typically altered in non‐neuroendocrine tumors . Currently, the standard of care for advanced or refractory LCNEC patients is combination chemotherapy.…”

Section: Discussionmentioning

confidence: 99%

“…It is becoming evident that a subset of LCNEC tumors shares mutational patterns with SCLC and LCC, whereas others carry mutations typically altered in nonneuroendocrine tumors. 14,21,27,28 Currently, the standard of care for advanced or refractory LCNEC patients is combination chemotherapy. It is interesting to note that a large percentage (64.29%) of LCNEC patients harbor mutations in genes either with Food and Drug Administration approved drugs or with drugs in advanced trials, such as BRCA1 and ERBB4 mutations, and EGFR, KIT, and PDGFRA amplifications, respectively.…”

Section: Discussionmentioning

confidence: 99%

See 2 more Smart Citations

Comparison of genomic landscapes of large cell neuroendocrine carcinoma, small cell lung carcinoma, and large cell carcinoma

et al. 2019

View full text Add to dashboard Cite

Background The classification of large cell neuroendocrine carcinoma (LCNEC) has generated considerable debate and has been revised since its recognition as a separate entity. Although it shares clinical features with small cell lung carcinoma (SCLC) and was classified with SCLC in the 2015 World Health Organization classification system, numerous studies have revealed inferior treatment outcomes of LCNEC when it was treated as SCLC. Because the incidence of LCNEC is rare, its mutational landscape has not been comprehensively interrogated. Methods We performed capture‐based ultra‐deep targeted sequencing on tumor samples of LCNEC, large cell carcinoma (LCC), and SCLC to elucidate its biological relationship with these subtypes and to identify potentially targetable molecular alterations. Results Our data revealed a molecular signature, consisting of RUNX1 , ERBB4 , BRCA1 , and EPHA3 , that is distinctively mutated in LCNEC. A majority (60%) of LCNEC patients harbored copy number variations (CNVs). Interestingly, there were no common CNVs shared among the three subtypes: NFкBIA amplification was shared between LCNEC and LCC, while AKT2 amplification was shared between LCNEC and SCLC. Furthermore, genetic alterations in the PI3K/AKT/mTOR pathway were enriched in all three subtypes. Conclusion Despite the histological and/or morphological similarities among LCNEC, LCC, and SCLC, our data revealed a molecular signature, consisting of RUNX1 , ERBB4 , BRCA1 , and EPHA3 , that is distinctively mutated in LCNEC, which has the potential to be used as a panel of biomarkers to distinguish LCNEC from a molecular perspective. Furthermore, the molecular distinction among the three subtypes can also be reflected from CNV events.

show abstract

Section: Discussionsupporting

confidence: 92%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Comparison of genomic landscapes of large cell neuroendocrine carcinoma, small cell lung carcinoma, and large cell carcinoma

et al. 2019

View full text Add to dashboard Cite

show abstract

“…SCLC metastasizes lymph nodes and distant organs even in the early stage . The two types resemble each other both in clinical behavior, poor prognosis and genetic background …”

Section: Introductionmentioning

confidence: 99%

Neuroendocrine marker staining pattern categorization of small‐sized pulmonary large cell neuroendocrine carcinoma

et al. 2019

View full text Add to dashboard Cite

Background The aim of this study was to identify subgroups with good or bad prognosis in patients with pulmonary large cell neuroendocrine carcinoma (LCNEC) based on immunostaining patterns with neuroendocrine markers and compare them with small cell lung carcinoma (SCLC). Methods From January 2001 to December 2017, of all patients with resected LCNEC and SCLC, we selected patients whose pathological tumor sizes were ≤30 mm in diameter (defined as small‐sized tumors) and who underwent complete resection with lymphadenectomy. We classified patients with small‐sized LCNEC (sLCNEC) into two subgroups based on immunostaining patterns with three neuroendocrine markers (chromogranin A, synaptophysin, and NCAM) and compared them to small‐sized SCLC (sSCLC). Results A total of 48 patients with sLCNEC and 39 patients with sSCLC were enrolled. Of 48 patients with sLCNEC, 21 were categorized as the small‐sized triple‐positive group (sTP), whose patients were positive for the three neuroendocrine markers, and 27 patients were categorized as the small‐sized nontriple‐positive group (sNTP), whose patients were not positive for all three neuroendocrine markers. The percentage of lymph node metastasis was significantly lower in sNTP than in sTP and sSCLC. There was no significant difference in overall survival, but recurrence‐free survival (RFS) and tumor‐specific survival (TSS) were significantly poorer in sTP and sSCLC than in sNTP. Multivariate analysis revealed sTP and sSCLC were independent prognostic factors for poorer RFS and TSS than those of sNTP. Conclusions The sNTP subgroup had a good prognosis and the sTP subgroup a poor prognosis. There were some similarities in clinicopathological features between sTP and sSCLC.

show abstract

“…Since the revised 2015 World Health Organization classification of lung tumors classified LCNEC as a NEN (Travis, Brambilla, Burke, Marx, & Nicholson, ), debates and investigations of the new classification were ceaseless. LCNEC was grouped with NENs due to its similarities with SCLC in terms of morphology, DNA methylation, protein levels, mutational aspects, and transcriptional levels (Aly et al, ; Karlsson et al, , ; Miyoshi et al, ; Rossi et al, ; Simbolo et al, ), in spite of a certain extent of heterogeneity (Clinical Lung Cancer Genome Project (CLCGP); Network Genomic Medicine (NGM), ; Rossi et al, ; Simbolo et al, ). In addition, despite the differences in histopathological characteristics between SCLC and LCNEC, their clinical characteristics are similar, including a generally poor outcome, greater incidence in men than in women, and advanced stage diagnosis (Asamura et al, ; Cerilli, Ritter, Mills, & Wick, ; Xu et al, ).…”

Section: Introductionmentioning

confidence: 99%

Common and distinct features of potentially predictive biomarkers in small cell lung carcinoma and large cell neuroendocrine carcinoma of the lung by systematic and integrated analysis

Dong

Liang

Zhai

et al. 2020

Molec Gen & Gen Med

View full text Add to dashboard Cite

Background Large‐cell neuroendocrine carcinoma of the lung (LCNEC) and small‐cell lung carcinoma (SCLC) are neuroendocrine neoplasms. However, the underlying mechanisms of common and distinct genetic characteristics between LCNEC and SCLC are currently unclear. Herein, protein expression profiles and possible interactions with miRNAs were provided by integrated bioinformatics analysis, in order to explore core genes associated with tumorigenesis and prognosis in SCLC and LCNEC. Methods http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE1037 gene expression profiles were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) in LCNEC and SCLC, as compared with normal lung tissues, were selected using the GEO2R online analyzer and Venn diagram software. Gene ontology (GO) analysis was performed using Database for Annotation, Visualization and Integrated Discovery. The biological pathway analysis was performed using the FunRich database. Subsequently, a protein–protein interaction (PPI) network of DEGs was generated using Search Tool for the Retrieval of Interacting Genes and displayed via Cytoscape software. The PPI network was analyzed by the Molecular Complex Detection app from Cytoscape, and 16 upregulated hub genes were selected. The Oncomine database was used to detect expression patterns of hub genes for validation. Furthermore, the biological pathways of these 16 hub genes were re‐analyzed, and potential interactions between these genes and miRNAs were explored via FunRich. Results A total of 384 DEGs were identified. A Venn diagram determined 88 common DEGs. The PPI network was constructed with 48 nodes and 221 protein pairs. Among them, 16 hub genes were extracted, 14 of which were upregulated in SCLC samples, as compared with normal lung specimens, and 10 were correlated with the cell cycle pathway. Furthermore, 57 target miRNAs for 8 hub genes were identified, among which 31 miRNAs were correlated with the progression of carcinoma, drug‐resistance, radio‐sensitivity, or autophagy in lung cancer. Conclusion This study provided effective biomarkers and novel therapeutic targets for diagnosis and prognosis of SCLC and LCNEC.

show abstract

Genomic profiling of large-cell neuroendocrine carcinoma of the lung.

Cited by 47 publications

References 0 publications

Comparison of genomic landscapes of large cell neuroendocrine carcinoma, small cell lung carcinoma, and large cell carcinoma

Comparison of genomic landscapes of large cell neuroendocrine carcinoma, small cell lung carcinoma, and large cell carcinoma

Neuroendocrine marker staining pattern categorization of small‐sized pulmonary large cell neuroendocrine carcinoma

Common and distinct features of potentially predictive biomarkers in small cell lung carcinoma and large cell neuroendocrine carcinoma of the lung by systematic and integrated analysis

Contact Info

Product

Resources

About