Exploration of genetic characterization in hyperprogressive disease after immunotherapy retreatment in a patient with LCNEC: A case report

Immune checkpoint inhibitors (ICIs) have emerged as a promising therapeutic option for large cell neuroendocrine carcinoma (LCNEC). However, various studies have suggested a potential risk of hyperprogressive disease (HPD) in patients receiving ICI, which might be associated with gene alterations. Here, this is the first report on an unknown primary LCNEC patient who had achieved a long-term response from ICI treatment (atezolizumab), but developed HPD after tumor progression due to receiving another ICI agent (serplulimab). The mutation region of FAT4, SMARCA4, CYLD, CTNNB1, and KIT was altered prior to serplulimab treatment compared to before atezolizumab treatment. This case suggested a potential association between these mutated genes and HPD. Patients with the aforementioned genes should caution when selecting ICI treatment. These findings required further confirmation in a larger study cohort.

Metastasis pattern and prognosis of large cell neuroendocrine carcinoma: a population-based study

PURPOSE

As a rare type of tumor, the metastasis pattern of large cell neuroendocrine carcinoma (LCNEC) is still unclear. Our aim was to investigate metastatic patterns and develop a predictive model of prognosis in patients with advanced LCNEC.

METHODS

Patients of LCNEC diagnosed between 2010-2015 from the Surveillance, Epidemiology and End Results (SEER) database were retrospectively included. Chi-square test was used for baseline characteristics analysis. Survival differences were assessed using Kaplan-Meier curves. Independent prognostic factors identified by multivariate Cox proportional risk model were used for the construction of nomogram.

RESULTS

557 eligible patients with metastasis LCNEC (median (IQR), 64 (56 to 72) years; 323 males) were included in this research. Among patients with isolated metastases, brain metastases had the highest incidence (29.4%), and multisite metastases had worse OS (HR: 2.020: 95% CI 1.413-2.888; P < 0.001) and LCSS (HR: 2.144, 95% CI 1.480-3.104; P < 0.001) in all age groups. Independent prognostic indicators including age, race, T stage, N stage, chemotherapy, radiotherapy and metastatic site were used for the construction of nomogram. Concordance index (C-index) and decision-curve analyses (DCAs) showed higher accuracy and net clinical benefit of nomogram compared to the 7th TNM staging system (OS: 0.692 vs 0.555; P < 0.001; LCSS: 0.693 vs 0.555; P < 0.001).

CONCLUSIONS

We firstly established a novel comprehensive nomogram to predict the prognosis of metastasis LCNEC. The prognostic model demonstrated excellent accuracy and predictive performance. Chemotherapy and metastasis pattern were the two strongest predictive variables. Close follow-up of patients with LCNEC is necessary to make individualized treatment decisions according to different metastasis patterns.

Risk factors, survival analysis, and nomograms for distant metastasis in patients with primary pulmonary large cell neuroendocrine carcinoma: A population-based study

INTRODUCTION

Pulmonary large cell neuroendocrine carcinoma (LCNEC) is a rapidly progressive and easily metastatic high-grade lung cancer, with a poor prognosis when distant metastasis (DM) occurs. The aim of our study was to explore risk factors associated with DM in LCNEC patients and to perform survival analysis and to develop a novel nomogram-based predictive model for screening risk populations in clinical practice.

METHODS

The study cohort was derived from the Surveillance, Epidemiology, and End Results database, from which we selected patients with LCNEC between 2004 to 2015 and formed a diagnostic cohort (n = 959) and a prognostic cohort (n = 272). The risk and prognostic factors of DM were screened by univariate and multivariate analyses using logistic and Cox regressions, respectively. Then, we established diagnostic and prognostic nomograms using the data in the training group and validated the accuracy of the nomograms in the validation group. The diagnostic nomogram was evaluated using receiver operating characteristic curves, decision curve analysis curves, and the GiViTI calibration belt. The prognostic nomogram was evaluated using receiver operating characteristic curves, the concordance index, the calibration curve, and decision curve analysis curves. In addition, high- and low-risk groups were classified according to the prognostic monogram formula, and Kaplan-Meier survival analysis was performed.

RESULTS

In the diagnostic cohort, LCNEC close to bronchus, with higher tumor size, and with higher N stage indicated higher likelihood of DM. In the prognostic cohort (patients with LCNEC and DM), men with higher N stage, no surgery, and no chemotherapy had poorer overall survival. Patients in the high-risk group had significantly lower median overall survival than the low-risk group.

CONCLUSION

Two novel established nomograms performed well in predicting DM in patients with LCNEC and in evaluating their prognosis. These nomograms could be used in clinical practice for screening of risk populations and treatment planning.

Large cell neuroendocrine carcinoma of the lungs: case report and literature review

Pulmonary large cell neuroendocrine carcinoma (LCNEC) is a rare but destructive tumor type, accounting for approximately 1% of all lung cancers, associated with poor prognosis. LCNEC is challenging diagnosing using biopsy specimens. While current LCNEC therapies include surgery, radiotherapy, and chemotherapy, it has not yet proved its greatest treatment strategies. Immunotherapy is rapidly emerging as a possibility for lung cancer treatment. However, there are scant reports in the literature regarding LCNEC immunotherapy. Therefore, the author here reports a case of LCNEC by immunotherapy, and retrospective reviews the present research status and progress of LENCE and corresponding clinical treatment progress. This case will supply valuable information for the treatment options for LCNEC. A 64-year-old male smoker was treated for one month for blood in his sputum. Chest radiography and computed tomography revealed a 3-cm solitary tumor in the left upper lung. We treated the patient with thoracoscopic radical surgery for upper left lung cancer. Postoperative pathology shows pulmonary LCNEC. We performed postoperative chemotherapy with a double-drug regimen holding platinum. Then, bevacizumab, paclitaxel, and the PD-L1 checkpoint inhibitor nivolumab were applied, but the patient progressed rapidly. Immunotherapy is an ineffective treatment possibility for these patients, even if PD-L1 expression is positive. A possible contributing factor is the timing of immunotherapy too late.

Activity and Immune Correlates of Programmed Death-1 Blockade Therapy in Patients With Advanced Large Cell Neuroendocrine Carcinoma

BACKGROUND

The efficacy of anti-programmed death receptor 1 (PD-1) therapy in patients with large cell neuroendocrine carcinoma (LCNEC) remains unclear. We investigated the outcome of anti-PD-1 therapy and its predictive markers by evaluating the immune-related tumor microenvironment.

PATIENTS

We retrospectively reviewed patients with advanced LCNEC treated with systemic chemotherapy. We also evaluated PD ligand 1 (PD-L1) expression (clone: 22C3), CD8-positive tumor-infiltrating lymphocytes (TILs), and the mutational profiles.

RESULTS

Seventy patients were enrolled, and 13 of 70 patients received anti-PD-1 therapy. The progression-free survival (PFS) and objective response rate (ORR) of the anti-PD-1 therapy were 4.2 months and 39%, respectively. The overall survival of patients treated with anti-PD-1 therapy (n = 13) was significantly better than those treated without anti-PD-1 therapy (n = 57) (25.2 months vs 10.9 months; P = .02). Among the 13 patients treated with anti-PD-1 therapy, 10 patients (90%) had PD-L1-negative tumors. Patients with a high density of tumoral CD8-positive TILs (≥38/mm²) had a significantly better ORR and PFS than those with a low density of tumoral CD8-positive TILs (ORR: P = .02; PFS: P = .003). Additionally, all 3 patients with TP53 mutation co-occurring with PIK3CA mutation (2 of 8 patients) or RB1 mutation (1 of 8 patients) responded to anti-PD-1 therapy.

CONCLUSIONS

Anti-PD-1 therapy was effective regardless of PD-L1 positivity in patients with advanced LCNEC. Our investigation might suggest that the density of tumoral CD8-positive TILs and the presence of co-occurring mutations are predictors of the efficacy of anti-PD-1 therapy in patients with advanced LCNEC.

Identification of novel transcription factor-microRNA-mRNA co-regulatory networks in pulmonary large-cell neuroendocrine carcinoma

Background

Large cell neuroendocrine carcinoma (LCNEC) of the lung is a rare neuroendocrine neoplasm. Previous studies have shown that microRNAs (miRNAs) are widely involved in tumor regulation through targeting critical genes. However, it is unclear which miRNAs play vital roles in the pathogenesis of LCNEC, and how they interact with transcription factors (TFs) to regulate cancer-related genes.

Methods

To determine the novel TF-miRNA-target gene feed-forward loop (FFL) model of LCNEC, we integrated multi-omics data from Gene Expression Omnibus (GEO), Transcriptional Regulatory Relationships Unraveled by Sentence-Based Text Mining (TRRUST), Transcriptional Regulatory Element Database (TRED), and The experimentally validated microRNA-target interactions database (miRTarBase database). First, expression profile datasets for mRNAs (GSE1037) and miRNAs (GSE19945) were downloaded from the GEO database. Overlapping differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs) were identified through integrative analysis. The target genes of the FFL were obtained from the miRTarBase database, and the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses were performed on the target genes. Then, we screened for key miRNAs in the FFL and performed gene regulatory network analysis based on key miRNAs. Finally, the TF-miRNA-target gene FFLs were constructed by the hypergeometric test.

Results

A total of 343 DEGs and 60 DEMs were identified in LCNEC tissues compared to normal tissues, including 210 down-regulated and 133 up-regulated genes, and 29 down-regulated and 31 up-regulated miRNAs. Finally, the regulatory network of TF-miRNA-target gene was established. The key regulatory network modules included ETS1-miR195-CD36, TAOK1-miR7-1-3P-GRIA1, E2F3-miR195-CD36, and TEAD1-miR30A-CTHRC1.

Conclusions

We constructed the TF-miRNA-target gene regulatory network, which is helpful for understanding the complex LCNEC regulatory mechanisms.

DLL3 expression in large cell neuroendocrine carcinoma (LCNEC) and association with molecular subtypes and neuroendocrine profile

OBJECTIVES

For stage IV pulmonary large cell neuroendocrine carcinoma (LCNEC), the only therapeutic option is palliative chemotherapy. DLL3 is a new therapeutic target, which seems to be often expressed in SCLC and LCNEC. It has recently been reported that DLL3 mRNA expression is particularly upregulated in the LCNEC subgroup with STK11/KEAP1 and TP53 co-mutations, in contrast to lower expression levels in RB1 and TP53 co-mutated LCNEC. Our aim was to investigate DLL3 protein expression in stage IV LCNEC and correlate data with mutational profiles (i.e.STK11/KEAP1/RB1), immunostaining results (pRb, NE markers) and clinical characteristics.

MATERIALS AND METHODS

Immunohistochemical analysis for DLL3 (SC16.65) and ASCL1 (SC72.201) was performed on 94 and 51 FFPE tissue sections, respectively, of pathologically reviewed stage IV LCNEC. DLL3 and ASCL1 were scored positive if ≥1% of the tumor cells showed cytoplasmic/membranous or dotlike (DLL3) or nuclear (ASCL1) immunostaining. Data were correlated with available sequencing (TP53, RB1, STK11, KEAP1), immunostaining (pRb, NE markers) and clinical data.

RESULTS

DLL3 was expressed in 70/94 (74%) LCNEC, 56 (80%) of which showed cytoplasmic/membranous staining. Median H-score was 55 (interquartile range 0-160). DLL3 staining was not different in pRb immunohistochemistry negative and positive patients (DLL3+ in 53/70 (76%) vs. 14/21 (67%), p = 0.409) or RB1 mutated and wildtype patients (DLL3+ in 27/34 (79%) vs. 23/33 (70%), p = 0.361). Nevertheless, 6/6 (100%) STK11 mutated, 10/11 (91%) KEAP1 mutated and 9/9 (100%) TP53 wildtype tumors were DLL3+ . Furthermore, DLL3 expression was associated with expression of ASCL1 and at least 2 out of 3 neuroendocrine markers.

CONCLUSION

The high percentage (74%) of DLL3 expression in stage IV LCNEC denotes the potential of DLL3 targeted therapy in this patient group.

Prognostic significance of PD-L1 expression and tumor infiltrating lymphocytes in large cell neuroendocrine carcinoma of lung

OBJECTIVES

Since large cell neuroendocrine carcinoma (LCNEC) is a relatively rare histologic type of primary lung cancer, little is known about the immunological status of patients with LCNEC. We aimed to clarify the expression and prognostic impact of programmed cell death ligand 1 (PD-L1), CD8, CD4, and Forkhead box protein P3 (Foxp3) in LCNEC.

METHODS

We retrospectively analyzed PD-L1, CD8, CD4, and Foxp3 expressions in 95 surgically resected LCNEC. PD-L1 positive staining was determined in tumors with more than 1% of tumor cells stained to any intensity, and CD8, CD4, and Foxp3 positivity was determined in tumors with more than 5% of lymphocytes stained.

RESULTS

Positive expression of PD-L1, CD8, CD4, and Foxp3 was observed in 70 (74%), 52 (55%), 76 (80%), and 43 (45%) tumors, respectively. The expression of PD-L1 was significantly correlated with positive lymphatic permeation. Positive correlations were mutually observed among tumor infiltrating immune cells. Univariate and multivariate analyses showed that positive pleural invasion and Foxp3 negative expression were independent unfavorable prognostic factors for overall survival (OS). Advanced pathological stage, positive pleural invasion, CD4 negative expression in cancer stroma, and Foxp3 negative expression were identified as independent unfavorable prognostic factors for recurrence free survival (RFS).

CONCLUSIONS

Foxp3 positive tumor infiltrating lymphocytes (TILs) were an independent favorable prognostic factor for both OS and RFS, whereas CD4 positive TILs were an independent significant unfavorable prognostic factor for RFS. The high frequency of PD-L1 expression could support the use of anti-programmed cell death 1 antibody in the treatment of LCNEC.

Update on large cell neuroendocrine carcinoma

High-grade neuroendocrine carcinomas of the lung are classified into two categories: large cell neuroendocrine carcinoma (LCNEC) and small cell lung carcinoma (SCLC). While typical cases of LCNEC are morphologically distinct from SCLC, the differentiation between LCNEC and SCLC can be challenging in some cases. In fact, there are borderline high-grade neuroendocrine carcinomas that morphologically fall between LCNEC and SCLC. Growing evidence suggests that LCNEC is a histologically and biologically heterogeneous group of tumors. Molecular profiling with next-generation sequencing (NGS) has revealed a few biologically distinct subsets of LCNEC. Of those, the SCLC-like subset is characterized by concurrent inactivating mutations in TP53 and loss of RB1 that are typically seen in SCLC, whereas the non-small cell lung cancer (NSCLC)-like subset frequently harbors molecular alterations that are usually seen in NSCLC. Furthermore, the SCLC-like subset exhibits morphologic features of SCLC, and NSCLC-like morphology predominates in the NSCLC-like subset, although there was a substantial overlap in morphologic features between these subsets. As for the treatment of LCNEC, surgery is advocated for early stage tumors, but surgery alone does not appear to be sufficient and adjuvant chemotherapy, consisting of platinum/etoposide, likely prevents recurrence in patients with completely resected LCNEC. For advanced disease, there have been conflicting reports as to whether LCNEC responds to chemotherapeutic regimens in the similar manner to SCLC rather than NSCLC, and the heterogeneous biology of LCNEC may contribute in part to the discrepant results. A further understanding of the biology of LCNEC will lead to novel approaches to clinical managements of patients with LCNEC.