Large-cell carcinoma (LCC) of the lung is an undifferentiated tumor, which lacks of the immunohistochemical and cytological characteristics of adenocarcinoma, squamous cell carcinoma or small-cell carcinoma (1). It is a relatively uncommon lung cancer that is characterized by poor prognosis and limited treatment options. Large cell neuroendocrine carcinoma (LCNEC) was initially classified as a histological variant of LCC. However, LCNEC and LCC differ in their cytological and histological features, as well as in clinical behavior to treatment. It has been reported that LCNEC was associated with worse survival outcome compared to LCC (2). As a consequence, the 2015 World Health Organization (WHO) classification significantly revised the classification of LCC and removed large cell neuroendocrine carcinoma (LCNEC) from the LCC category, establishing LCNEC as a distinct entity (3).

With the advances in next-generation sequencing (NGS), numerous actionable driver genes have emerged from the genetic landscape of different lung cancer subtypes. At the same time, many efforts have been undertaken to clarify the biological relationship between LCNEC, classic LCC and other types of lung cancer (1, 4–6). LCNEC has been segregated into small-cell lung carcinoma (SCLC)-like, characterized by the co-occurrence of TP53 and RB1 mutations, and non-small-cell lung carcinoma (NSCLC)-like, characterized by the lack of TP53/RB1 co-mutations and STK11/KEAP1/KRAS mutations (4, 6). On the other hand, classic LCCs are also genetically heterogeneous, displaying profiles characteristics of either adenocarcinoma or squamous cell carcinoma (7). In this study, we aimed to further investigate these two subtypes of lung cancer and identify potential biomarkers for treatment and prognostication of these patients.

In this study, we examined the mutational profiles of LCC and LCNEC patients and conducted association analysis of survival for the identification of potential biomarkers of diagnostic and prognostic value. LCC and LCNEC are two subtypes of lung cancer of heterogenous nature and limited treatment options. Due to relatively difficult diagnosis, detailed pathological diagnosis was finally confirmed by experienced pathologists in this study. The number of cases included in the study was relatively small but ensured the authenticity of subsequent genetic testing results. In this study, we identified several targetable mutations in both LCC and LCNEC, including KRAS G12 mutations and a RET fusion gene. This finding suggests that genetic profiling might be necessary in such patients as it might provide more therapeutic options which is available using, tumor DNA or cell-free DNA (cfDNA) to monitor these mutations (14).

While the number of patients in our study was not large, all patients received platinum-based first-line therapy in both LCNEC and LCC. In additional, our results are similar to the observations in reported study (15), 52.9% of patients received second-line chemotherapy, which was also platinum-based. In contrast to another previous report (2), we found that LCNEC patients had better survival compared to patients with classic LCC, which might be associated with the enrichment of RB1 and BRAF mutations in the LCNEC group and the enrichment of SMARCA4 and KEAP1 mutations in the LCC group. Previous studies have shown that KEAP1 mutations were known to be a typical characteristic of NSCLC-like LCNEC, and more likely to be resistant to chemotherapy and EGFR-TKI drugs (6, 16). LCNEC samples suggest that LCNEC can be subdivided into different subtypes, partly clustering with SCLC. By comparative analysis of 69 LCNECs and 110 SCLCs, George et al. have found that despite their mutational patterns, LCNECs with KEAP1 mutations exhibit a neuroendocrine profile with closest similarity to SCLC tumors (17). Rekhtman et al. also showed that significantly higher rate of KEAP1 alterations (33%) was found in SCLC-like LCNEC, differed from SCLC with 5% of KEAP1 alterations (4). The incidence of KEAP1 mutation is not high, especially in the Chinese lung cancer patients, with the reported incidence of about 20%. KEAP1 mutation was only found in LCC patients, but not in LCNEC in this study. Possible reasons are the small sample, and the neuroendocrine profile with closest similarity to SCLC in the LCNEC subtype. This is consistent with the poor survival of LCC patients with KEAP1 mutations shown in our data.

Within the LCC subgroup, the presence of SMARCA4 mutations remained associated with poor survival outcome. SMARCA4, encoding the BRG1 protein, participates in the chromatin remodeling process and DNA repair and is frequently mutated in lung cancer (18, 19). Low expression of SMARCA4 has been associated with worse prognosis in patients with non-small-cell lung cancer (18). Co-mutations occurred more frequently with SMARCA4 mutations than with SMARCA4 wild-type tumors. In our data, four cases were co-mutated with TP53 and two cases were co-mutated with KEAP1, and also the co-mutated patients showed shorter survival time. Recent studies have found that treatment with immune checkpoint inhibitors is associated with improved outcomes in patients with SMARCA4 mutated, suggesting that SMARCA4 mutated lung cancer may be more sensitive to immunotherapy. SMARCA4 mutation detection may be required in our future studies to further explore its correlation with immunotherapy (20). Within the LCNEC group, BRAF mutations showed a trend of increased survival. In addition, TET2 mutations might serve as a negative prognostic marker in the LCNEC subgroup.

In summary, we reported potentially targetable mutations in both LCC and LCNEC, and identified several novel genetic alterations that might serve for diagnostic and prognostic purposes. Given the relative uncommon nature of LCC and LCNEC and therefore the limited sample size in our cohort, the diagnostic and prognostic role of the reported genes would require further investigations in larger-sample cohorts.

The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: Genome Variation Map, National Genomics Data Center, GVM000288.

Written informed consent was obtained from the individual(s) for the publication of any potentially identifiable images or data included in this article.

XD contributed to study design and implementation. YC was the principal investigator and wrote the report. Sample collection was done by XC, DW, and YC. GX advised on the trial. Analysis and interpretation of data were done by YC, LC, MX, and LS. Writing, review, and/or revision of the manuscript were done by YC. All authors contributed to the interpretation of data. All authors contributed to the article and approved the submitted version.

Author DW was employed by Nanjing Geneseeq Technology Inc.

The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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