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Oncogenic function and clinical implications of SLC3A2-NRG1 fusion in invasive mucinous adenocarcinoma of the lung.

ABSTRACT: The neuregulin 1 (NRG1) fusion is a recently identified novel driver oncogene in invasive mucinous adenocarcinoma of the lung (IMA). After identification of a case of SLC3A2-NRG1 in a patient with IMA, we verified this fusion gene in a cohort of 59 patients with IMA. Targeted cancer panel sequencing and RT-PCR identified the possible coexistence of other driver oncogenes. Among 59 IMAs, we found 16 NRG1 fusions (13 SLC3A2-NRG1 and 3 CD74-NRG1). Of 16 patients with NRG1 fusions, concurrent KRAS codon 12 mutations were found in 10 cases. We also found concurrent NRAS Q61L mutation and EML4-ALK fusion in additional two cases with NRG1 fusions. When comparing overall survival (OS) according to the presence of NRG1 fusions showed that patients harboring NRG1 fusions had significantly inferior OS than those without NRG1 fusions (hazard ratio = 0.286; 95% confidence interval, .094 to .865). Ectopic expression of the SLC3A2-NRG1 fusion in lung cancer cells increased cell migration, proliferation and tumor growth in vitro and in xenograft models, suggesting oncogenic function for the fusion protein. We found that the SLC3A2-NRG1 fusion promoted ERBB2-ERBB3 phosphorylation and heteroduplex formation and activated the downstream PI3K/AKT/mTOR pathway through paracrine signaling. These findings suggested that the SLC3A2-NRG1 fusion was a driver in IMA with an important prognostic impact. SLC3A2-NRG1 should be considered a therapeutic target for patients with IMA.

SUBMITTER: Shin DH

PROVIDER: S-EPMC5342490 | biostudies-literature | 2016 Oct

REPOSITORIES: biostudies-literature

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Oncogenic function and clinical implications of SLC3A2-NRG1 fusion in invasive mucinous adenocarcinoma of the lung.

Shin Dong Hoon DH Lee Donghoon D Hong Dong Wan DW Hong Seung Hyun SH Hwang Jung-Ah JA Lee Byung Il BI You Hye Jin HJ Lee Geon Kook GK Kim In-Hoo IH Lee Yeon-Su YS Han Ji-Youn JY

Oncotarget 20161001 43

The neuregulin 1 (NRG1) fusion is a recently identified novel driver oncogene in invasive mucinous adenocarcinoma of the lung (IMA). After identification of a case of SLC3A2-NRG1 in a patient with IMA, we verified this fusion gene in a cohort of 59 patients with IMA. Targeted cancer panel sequencing and RT-PCR identified the possible coexistence of other driver oncogenes. Among 59 IMAs, we found 16 NRG1 fusions (13 SLC3A2-NRG1 and 3 CD74-NRG1). Of 16 patients with NRG1 fusions, concurrent KRAS c ...[more]

PMID: 27626312

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Project description:Objective: This study aimed to develop and validate predictive models using clinical parameters, radiomic features, and a combination of both for invasive mucinous adenocarcinoma (IMA) of the lung in patients with lung adenocarcinoma. Method: A total of 173 and 391 patients with IMA and non-IMA, respectively, were retrospectively analyzed from January 2017 to September 2022 in our hospital. Propensity Score Matching was used to match the 2 groups of patients. A total of 1037 radiomic features were extracted from contrast-enhanced computed tomography (CT). The patients were randomly divided into training and test groups at a ratio of 7:3. The least absolute shrinkage and selection operator algorithm was used for radiomic feature selection. Three radiomics prediction models were applied: logistic regression (logistic), support vector machine (SVM), and decision tree. The best-performing model was adopted, and the radiomics score (Radscore) was then computed. A clinical model was developed using logistic regression. Finally, a combined model was established based on a clinical model and a radiomics model. The area under the receiver operating characteristic (ROC) curve (AUC) and decision curve analysis were used to evaluate the predictive value of the developed models. Results: Both clinical and radiomics models established using the logistic method showed the best performance. The Delong test revealed that the combined model was superior to the clinical and radiomics models (P = .018 and .020, respectively). The ROC-AUC (also decision curve analysis) of the combined model was 0.840 and 0.850 in the training and testing groups, respectively, which showed good predictive performance for IMA. The Brier scores for the combined model were 0.161 and 0.154 in the training and testing groups, respectively. Conclusion: The combined model incorporating radiomic CT features and clinical predictors may have the potential to predict IMA in patients with lung cancer.

Dataset Information

Oncogenic function and clinical implications of SLC3A2-NRG1 fusion in invasive mucinous adenocarcinoma of the lung.

Publications

Oncogenic function and clinical implications of SLC3A2-NRG1 fusion in invasive mucinous adenocarcinoma of the lung.

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