Large Cell Neuroendocrine Carcinoma Patients Research Articles

Association of preexisting anti-thyroid antibodies and body mass index with prognosis of lung cancer patients treated with PD-1/PD-L1 inhibitors

Abstract Objectives Immune checkpoint inhibitors are a new beneficial medication in the treatment of cancer. Whether preexisting TPOAb was related to longer overall survival (OS) is controversial. This retrospective study analyzed the OS and progression-free survival (PFS) of patients with lung cancer, and explored predictive factors associated with the efficacy of PD-1/PD-L1 inhibitors treatment. Methods Patients with lung cancer who were hospitalized in the First Affiliated Hospital of Wenzhou Medical University between January 1, 2020 and December 30, 2020 were enrolled. Thyroid function, TPOAb, TGAb, and prognostic nutritional index levels and body mass index were analyzed. Supervising physicians independently assessed patient staging, OS, and PFS. Demographic data, pathological type, and previous treatment history were also collected. Results In total, this study enrolled 69 patients, with ages of 46–80 years old. Patients with lower weight showed reduced OS and PFS rates relative to those with normal weight and overweight (p<0.05). The single patient with large cell neuroendocrine carcinoma (LCNEC) exhibited a 1-, 1.5- and 2-year OS rate lower than that of the patients diagnosed with squamous cell carcinoma, small cell lung cancer, or adenocarcinoma (p<0.05). This LCNEC patient also had lower 1-, 1.5-, and 2-year PFS rates compared to adenocarcinoma patients (p<0.05). TPOAb and TGAb levels were unrelated to OS or PFS. Multivariate Cox regression analyses revealed a positive association between body mass index, OS, and PFS. Conclusions Patients with lower body weight were predictive of poorer survival outcomes when receiving PD-1/PD-L1 inhibitors treatment as compared to patients with normal weight and overweight. However, positive baseline TGAb and TPOAb levels were not associated with increased OS or PFS in patients with lung cancer.

A prognostic nomogram based on least absolute shrinkage and selection operator Cox regression in patients with pulmonary large-cell neuroendocrine carcinoma.

Pulmonary large-cell neuroendocrine carcinoma (LCNEC) is a rare subtype of breast cancer with a poor prognosis. Despite its rarity, it is important to gain a better understanding of the epidemiological, clinical, and prognostic features of pulmonary LCNEC. The purpose of this study was to design, construct, and validate a new nomogram for predicting overall survival (OS) in patients with pulmonary LCNEC. In total, the data of 1,864 LCNEC patients were extracted from the Surveillance, Epidemiology, and End Results (SEER) database, which is maintained by the National Cancer Institute in the United States and serves as a comprehensive source of cancer-related information. Of these patients, 556 served as the validation group and 1,308 served as the training cohort. We constructed a new nomogram with the training cohort that included the independent factors for OS as identified by least absolute shrinkage and selection operator Cox regression. Five independent factors were ultimately selected by the stepwise regression. Every factor of the Cox regression was included in the nomogram. Analyses of the calibration curve, decision curve, area under the curve, and concordance index (C-index) values were performed to assess the effectiveness and discriminative ability of the nomogram. Five optimal predictive factors for OS were selected and merged to construct a 3- and 5-year OS nomogram. The nomogram had C-index values of 0.716 and 0.708 in the training cohort and validation cohort, respectively. The actual OS rates and the calibration curves showing the predictions of the nomogram were in good agreement. The prognostic nomogram may be very helpful in estimating the OS of patients with pulmonary LCNEC.

The outcomes of different regimens depend on the molecular subtypes of pulmonary large-cell neuroendocrine carcinoma: A retrospective study in China.

The optimal systemic treatment for pulmonary large-cell neuroendocrine carcinoma (LCNEC) remains controversial, and recent advances in LCNEC molecular subtype classification have provided potential strategies for assisting in treatment decisions. Our study aimed to investigate the impact of treatment regimens, molecular subtypes and their concordance on clinical outcomes of patients diagnosed with LCNEC. All patients diagnosed with advanced pulmonary LCNEC in Peking Union Medical College Hospital (PUMCH) between January 2000 and October 2021 were enrolled in this retrospective study. The tumor samples were collected and sequenced using a tumor-specific gene panel, while clinical information was retrieved from the medical records system. The survival and therapeutic response were analyzed and compared between different subgroups classified by treatment regimen (SCLC or NSCLC-based), molecular subtype (type I or II) or the combination. In univariate subgroup analysis categorized only by treatment regimen or molecular subtype, there were no differences identified in DCR, ORR, PFS, or OS. Nevertheless, the group with consistent treatment regimen and molecular subtype exhibited significantly longer OS than that of the inconsistent group (median OS 37.7 vs. 8.3 months; p = 0.046). Particularly, the OS of patients with type II LCNEC treated with SCLC-based regimen was significantly prolonged than that of others (median 37.7 vs. 10.5 months; p = 0.039). Collectively, our study revealed the clinical outcomes of different treatment regimens for LCNEC patients highly depend on their molecular subtypes, highlighting the need for sequencing-guided therapy.

Clinical characteristics, treatment, and outcome of patients with large cell neuroendocrine carcinoma of the lung and brain metastases – data from a tertiary care center

Large cell neuroendocrine carcinoma (LCNEC) of the lung is an aggressive malignancy, with brain metastases (BM) occurring in approximately 20% of cases. There are currently no therapy guidelines for this population as only few data on the management of LCNEC and BM have been published. For this retrospective single center study, patients with LCNEC and BM were identified from the Vienna Brain Metastasis Registry. Data on clinicopathological features, BM-specific characteristics, treatment, and outcome were extracted. In total, 52/6083 (0.09%) patients in the dataset had a diagnosis of LCNEC and radiologically verified BM. Median age at diagnosis of LCNEC and BM was 59.1 and 60.1 years, respectively. Twenty-seven (51.9%) presented with single BM, while 12 (23%) exhibited > 3 BM initially. Neurologic symptoms due to BM were present in n = 40 (76.9%), encompassing neurologic deficits (n = 24), increased intracranial pressure (n = 18), and seizures (n = 6). Initial treatment of BM was resection (n = 13), whole brain radiation therapy (n = 19), and/or stereotactic radiosurgery (n = 25). Median overall survival (mOS) from LCNEC diagnosis was 16 months, and mOS after BM diagnosis was 7 months. Patients with synchronous BM had reduced mOS from LCNEC diagnosis versus patients with metachronous BM (11 versus 27 months, p = 0.003). Median OS after BM diagnosis did not differ between LCNEC patients and a control group of small cell lung cancer patients with BM (7 versus 6 months, p = 0.17). Patients with LCNEC and BM have a poor prognosis, particularly when synchronous BM are present. Prospective trials are required to define optimal therapeutic algorithms.

Development and Validation of a Nomogram for Patients with Lung Large Cell Neuroendocrine Carcinoma

Pulmonary large cell neuroendocrine carcinoma (LCNEC) is a rarely high-grade neuroendocrine carcinoma of the lung with features of both small cell and non-small cell lung cancer. We aim to construct a prognostic nomogram combined with the clinical features and treatment options to predict disease-specific survival (DSS), meanwhile, evaluating the role of prophylactic cranial irradiation (PCI) in LCNEC by subgroup analysis. A total of 713 patients diagnosed with LCNEC from the US National Cancer Institute's Surveillance Epidemiology and End Results (SEER) registry between 2010 and 2016. Cox proportional hazards analysis was conducted to choose the significant predictors of DSS. External validation was performed using 77 patients with LCNEC in the West China Hospital Sichuan University between 2010 and 2018, subgroup analysis was carried out for the whole brain radiotherapy (WBRT) and PCI population. The predictive accuracy and discriminative capability were estimated by the concordance index (C-index), calibration curve and receiver operating characteristic (ROC) curve. The clinical applicability of the nomogram was verified through the decision curve analysis (DCA). Six independent risk factors for DSS were identified and integrated into the nomogram. The nomogram achieved good C- indexes of 0.803 and 0.767 in the training and validation group respectively. Moreover, the calibration curves of both cohorts for the probability of survival showed good agreement between prediction by nomogram and actual observation in 1-, 3- and 5-year DSS. The ROC curves demonstrated the prediction accuracy of the established nomogram (all AUC>0.8). DCA confirmed the better potential clinical practicality of the nomogram in the prediction of LCNEC survival than AJCC staging. A risk classification system was built which could perfectly classify LCNEC patients into high- and low-risk groups(p<0.001). Subgroup analysis showed that WBRT did not bring survival benefits, PCI appeared to have survival benefits in LCNEC patients without brain metastases (p>0.05). The prognostic nomogram developed in this study has certain prognostic value and clinical practicality for LCNEC patients. PCI might be investigated as a means of improving prognosis.

Lung Large Cell Neuroendocrine Carcinoma: A Population-Based Retrospective Cohort Study.

Pulmonary large cell neuroendocrine carcinoma (LCNEC) is a rarely high-grade neuroendocrine carcinoma of the lung with features of both small cell and non-small cell lung cancer. In this study, we aim to construct a prognostic nomogram that integrates the clinical features and treatment options to predict disease-specific survival (DSS). A total of 713 patients diagnosed with LCNEC were from the US National Cancer Institute's Surveillance Epidemiology and End Results (SEER) registry between 2010-2016. Cox proportional hazards analysis was conducted to choose the significant predictors of DSS. External validation was performed using 77 patients with LCNEC in the West China Hospital Sichuan University between 2010-2018. The predictive accuracy and discriminative capability were estimated by the concordance index (C-index), calibration curve, and receiver operating characteristic (ROC) curve. The clinical applicability of the nomogram was verified through the decision curve analysis (DCA). Additionally, we conducted a subgroup analysis of data available in the external cohort that may impact prognosis but was not recorded in the SEER database. Six independent risk factors for DSS were identified and integrated into the nomogram. The nomogram achieved good C- indexes of 0.803 and 0.767 in the training and validation group, respectively. Moreover, the calibration curves for the probability of survival showed good agreement between prediction by nomogram and actual observation in 1-, 3- and 5-year DSS. The ROC curves demonstrated the prediction accuracy of the established nomogram (all Area Under Curve (AUC) > 0.8). DCA exhibited the favorable clinical applicability of the nomogram in the prediction of LCNEC survival. A risk classification system was built which could perfectly classify LCNEC patients into high-, medium- and low-risk groups (p < 0.001). The survival analysis conducted on the West China Hospital cohort indicated that whole brain radiation therapy (WBRT), prophylactic cranial irradiation (PCI), surgical procedures, tumor grade, Ki-67, and PD-L1 expression were not significantly associated with DSS. This study has effectively developed a prognostic nomogram and a corresponding risk stratification system, which demonstrate promising potential for predicting the DSS of patients with LCNEC.

Pulmonary large cell neuroendocrine carcinoma (LCNEC): a population-based study addressing recent molecular-genetic advances and emerging therapeutic approaches.

Large cell neuroendocrine carcinoma (LCNEC) of the lung is a rare, aggressive cancer most commonly found in the lungs but not exclusively, with a worse prognosis than non-small cell lung carcinomas. Currently, LCNEC patients are treated using small cell and non-small cell protocols. This study aims to use the SEER database to identify demographic, clinical, pathological, and therapeutic factors affecting the prognosis and survival of patients with LCNEC of the lung. Demographic, clinical, and management data of patients with lung LCNEC were extracted from the SEER database for the period 2000-2018. In the USA, LCNEC has a higher incidence in elderly white men: M:F ratio = 1.2:1, Caucasian: 83.3%, mean age: 67 ± 10.2years. The most common treatment modality was chemotherapy only: 29.2%, followed by surgery: 21.5% (but in this group the statuses of chemotherapy were unknown), and combination surgery/chemotherapy: 8.8%. The overall and cause-specific 5-year survival was 17.5% (95% CI 16.3-18.8) and 21.9% (95% CI 20.5-23.4), respectively. By treatment, the best 5-year survival was for surgery alone (48%), followed by multimodality therapy (chemo + surgery + radiation) at 35% (95% CI 27-43). Age > 60years, male gender, size > 7cm, and nodal and liver metastasis were independent risk factors associated with increased mortality. Lung LCNEC is an aggressive neoplasm most common in older white males that presents at an advanced stage despite small primary tumors. Most patients die within 2years. The best predictor of survival is surgery with chemotherapy. Given its dismal prognosis, new treatment guidelines are needed for this aggressive cancer.

Differences between Advanced Large Cell Neuroendocrine Carcinoma and Advanced Small Cell Lung Cancer: A Propensity Score Matching Analysis.

Background: Nowadays, the characteristics and treatment of advanced pulmonary large cell neuroendocrine carcinoma (LCNEC) remain controversial. This study aimed to analyze the similarity of clinical characteristics, survival outcomes and treatment modalities between advanced LCNEC and advanced small cell lung cancer (SCLC) to provide more evidence for the study of advanced LCNEC. Methods: All SCLC and LCNEC patient data were obtained from the SEER database (2010-2019). Pearson's χ2 test was used to compare the differences in clinical characteristics. Propensity score matching (PSM) was utilized to balance the bias of the variables between patients. Univariate and multivariate Cox proportional hazards regression analyses were performed to identify prognostic factors. KM analysis was used to calculate survival. Results: A total of 1094 patients with IV LCNEC and 20939 patients with IV SCLC were included in this study. The demographic characteristics and tumor characteristics of IV LCNEC and IV SCLC were different (p < 0.05). After PSM, the overall survival (OS) for IV LCNEC and IV SCLC was 6.0 months, the cancer-specific survival (CSS) was 7.0 months, and there was no significant difference in OS or CSS between the two groups. Risk/protective factors for OS and CSS were similar for IV LCNEC and IV SCLC patients. Survival outcomes were similar in patients with IV LCNEC and IV SCLC with different treatment modalities; chemoradiotherapy significantly improved OS and CSS in patients with IV LCNEC (9.0 months) and SCLC (10.0 months), however, radiotherapy alone did not improve survival in patients with IV LCNEC. Conclusions: These results confirmed that the prognosis and treatment modalities are similar and that advanced LCNEC could be treated as advanced SCLC, which provide new evidence for the treatment of advanced LCNEC patients.

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

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. 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. 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. 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.

Pulmonary Large Cell Neuroendocrine Carcinoma.

Pulmonary large cell neuroendocrine carcinoma (LCNEC) is a rare subtype of malignant pulmonary tumor. The incidence rate of LCNEC was reported to be 0.3%–3% in lung cancers. Although LCNEC is classified as non-small cell lung cancer (NSCLC), it is more aggressive and malignant than other NSCLC, and its biological behavior is similar to that of small cell lung cancer (SCLC). Most of the LCNEC patients are elderly smoking male and the clinical manifestations are not specific. The imaging manifestations of the tumors are often located in the periphery and the upper lobes, and the enlargement of mediastinal or hilar lymph nodes is common. The diagnosis is mainly based on pathology by the histological features and immunohistochemistry (IHC). Specific neuroendocrine markers such as chromogranin A (CgA), synaptophysin (Syn) and CD56 are usually diffusely positive in LCNEC, and found that insulinoma-associated protein (INSM1) and high rate of Ki-67 are helpful for diagnosis. More differential diagnoses also increase the difficulty of correctly diagnosing LCNEC. The rise of LCNEC molecular typing in recent years may be helpful for diagnosis and subsequent treatment. This review focuses on the epidemiological features, imaging studies, pathology, diagnosis, treatment, and prognosis of LCNEC.

Risk factors and prognostic factors for pulmonary large cell neuroendocrine carcinoma with brain metastasis.

As the studies regarding the brain metastasis (BM) of pulmonary large cell neuroendocrine carcinoma (LCNEC) are insufficient, the present research aims to describe the risk factors and prognostic factors that are related to cancer-specific survival (CSS) for LCNEC patients with BM. The data of LCNEC patients between January 2010 and October 2018 were obtained from the SEER database. Binary logistic regression analyses were utilized to screen the possible risk factors related to BM. Prognostic factors for LCNEC patients with BM were indentified by Cox regression analyses. Moreover, a nomogram was established to predict the 6-, 12-, and 18-month CSS rates. The concordance index (C-index), receiver operating characteristic (ROC) curves and calibration curves were utilized to assess the discrimination and reliability of the model. Clinical decision curves (DCAs) were used to evaluate the clinical benefits and utility of our model. Totally, 1875 patients were enrolled, with 294 (15.7%) of them having BM at diagnosis. Multivariate logistic regression analyses revealed that patients with age < 65 (odds ratio, OR=1.564) and N2 staging (OR=1.775) had a greater chance of developing BM. Age (≥ 65 vs. < 65: hazard ratio, HR=1.409), T staging (T1 vs. T0: HR=4.580; T2 vs. T0: HR=6.008; T3 vs. T0: HR=7.065; T4 vs. T0: HR=6.821), N staging (N2 vs. N0: HR=1.592; N3 vs. N0: HR=1.654), liver metastasis (HR=1.410), primary site surgery (HR=0.581) and chemotherapy (HR=0.452) were independent prognostic factors for LCNEC patients with BM. A nomogram prediction model was constructed by incorporating these factors. Using the C-index, calibration curves, ROC curves, and DCAs, we found that the clinical prediction model performed well. We described the risk factors and prognostic factors that were associated with CSS for LCNEC patients with BM. The related nomogram was established and validated to help clinicians formulate more rational and effective treatment strategies.

Prognostic significance of YAP1 expression and its association with neuroendocrine markers in resected pulmonary large cell neuroendocrine carcinoma (LCNEC)

BackgroundYAP1 (Yes-associated protein 1), an important effector of the Hippo pathway, acts as an oncogene and is overexpressed in various malignant tumors. However, the function and expression pattern of YAP1 in pulmonary large cell neuroendocrine carcinoma (LCNEC) have not been systematically established. This study aimed to explore the relationship between YAP1 expression and neuroendocrine differentiation markers and their prognostic significance in LCNEC. Materials and methodsYAP1 protein and neuroendocrine markers (INSM1, NeuroD1 and DLL3) expression were examined by immunohistochemical (IHC) staining in 80 resected pulmonary LCNEC cases. The possible association between these markers and clinicopathological features was evaluated and survival analyses were performed. ResultsYAP1 was highly expressed in 25% LCNECs (20/80) , especially at a relatively higher T stage (p = 0.015). YAP1 expression was negatively correlated with INSM1 (χ2=11.53, p = 0.001) and DLL3(χ2=8.55, p = 0.004), but not with NeuroD1 (p = 0.482). For survival analyses, YAP1 expression was associated with worse disease-free survival (DFS) and overall survival (OS) (median DFS: 13 months vs. not reached (NR), p = 0.0096; median OS: not reached, NR vs. NR, p = 0.038), and was an unfavorable prognostic factor for DFS (HR:3.285; 95%CI: 1.526-7.071, p = 0.002) and OS (HR: 2.864, 95% CI: 0.932-8.796, p = 0.066). ConclusionsYAP1 was found to be conversely correlated with neuroendocrine markers and a prognostic factor for worse survival in resected LCNEC patients, and mechanisms need to be further investigated.

Different Characteristics and Survival between Surgically Resected Pure and Combined Pulmonary Large Cell Neuroendocrine Carcinoma.

Large cell neuroendocrine carcinoma (LCNEC) is a rare high-grade neuroendocrine carcinoma of the lung. Little is known about the differences between the pure and combined LCNEC subtypes, and thus we conducted this study to provide more comprehensive insight into LCNEC. We reviewed 221 patients with pure LCNEC (P-LCNEC) and 120 patients with combined LCNEC (C-LCNEC) who underwent pulmonary surgery in our hospital to compare their clinical features, driven genes' status (EGFR/ALK/ROS1/KRAS/BRAF), and adjuvant chemotherapy regimens. Propensity score matching (PSM) was applied to reduce selection bias. The P-LCNEC group included a higher proportion of males and smokers than the C-LCNEC group. Furthermore, the C-LCNEC group had higher incidences of visceral pleural invasion (VPI), EGFR mutation and ALK rearrangement compared with the P-LCNEC group. Expression of neuroendocrine markers (CD56, CGA, and SYN) and recurrence patterns were not significantly different between the two groups. The P-LCNEC group had better disease-free survival (DFS) and overall survival (OS) compared with the C-LCNEC group (median DFS: 67.0 vs. 28.1 months, p=0.021; median OS: 72.0 vs. 45.0 months, p=0.001), which was further confirmed by the PSM method (p=0.004 and p<0.001, respectively). Adjuvant chemotherapy was also an independent factor for DFS and OS. Subgroup analysis found that regardless of whether it was for the entire LCNEC group or the P- and C-LCNEC subtypes, the small cell lung cancer (SCLC) regimens presented with superior survival compared with the non-small cell lung cancer (NSCLC) regimens. P-LCNEC was associated with more favorable prognosis compared with C-LCNEC. SCLC-based adjuvant chemotherapy was more appropriate for LCNEC patients than NSCLC-based regimens, regardless of whether they were the pure or combined LCNEC subtypes. C-LCNEC patients may be the potential beneficiary of targeted therapy.

Clinical and molecular pathological features of bronchopulmonary large cell neuroendocrine carcinoma

Objective: To investigate the clinical manifestations, imaging, pathological and molecular features of bronchopulmonary large-cell neuroendocrine carcinoma (LCNEC). Methods: The clinical data of 216 LCNEC patients in the First Affiliated Hospital of Zhengzhou University from 2011 to 2021 were analyzed retrospectively. The clinical manifestations, tumor location and size, characteristics of CT images, immunohistochemical and molecular pathological features were analyzed and compared with 115 cases of mixed small cell carcinoma (M-SCLC) diagnosed in the same period. Results: Among the 216 LCNEC patients, there were 190 males and 26 females, with a median age of 65 years. The first symptoms of the patients were mainly cough (106 cases, 49.1%) and bloody sputum (48 cases, 22.2%). The median tumor length were 4.7cm, including 55 cases of nodular type (25.5%) and 161 cases of mass-forming type (74.5%). CT imaging results showed that LCNEC lesions had soft tissue density, and the proportion of slight enhancement lesions was significantly lower than that in M-SCLC group (52.3% vs 74.8%, P<0.001). In contrast, the proportion of necrosis (87.0% vs 58.3%, P<0.001) and calcification (26.9% vs 2.6%, P<0.001) in LCNEC patients was significantly higher than that in M-SCLC group. Immunohistochemical results showed that the positive rate of CK in LCNEC was significantly higher than that in M-SCLC (99.0 % vs 90.5%, P<0.05), while the positive rate of TTF-1 was significantly lower than that in M-SCLC (51.6% vs 67.0%, P<0.05). In LCNEC group, the proportion of patients with Ki-67 positive index between 50% and 80% was significantly higher than that of M-SCLC (41.2% vs 25.2%), while the proportion between 80% and 100% was lower than that of M-SCLC (51.9% vs 72.2%). There was no significant difference in the positive rates of CD56 (91.7% vs 94.6%, P=0.336), Syn (83.8% vs 84.7%, P=0.838) and CgA (54.8% vs 50.0%, P=0.632) in both tumor types. Molecular pathology results showed that frequent mutatios were TP53 (54.5%), RB1 (36.4%), KEAP1 (18.2%), MYC(18.2%), and PTEN (14.3%), and the rate of tumor mutation burden which is more than 25 mutation/Mb was 27.3%. Conclusions: LCNEC lacks specific clinical manifestations. CT imaging is powerful in distinguishing LCNEC from M-SCLC. LCNEC contains a specific mutation spectrum. Pathology combined with immunohistochemical staining is still the gold standard for LCNEC diagnosis, and the differentiation from M-SCLC mainly depends on cell size and nuclear chromatin pattern with light microscopy.

Clinical significance of ALDH1A1 expression and its association with E-cadherin and N-cadherin in resected large cell neuroendocrine carcinoma

BackgroundThe roles of cancer stem cells (CSCs) and epithelial-mesenchymal transition (EMT) in solid tumors are well established. However, the interaction between CSCs and EMT in pulmonary large cell neuroendocrine carcinoma (LCNEC) remains unknown. The aim of this study was to investigate the expression and clinical significance of a CSC marker (ALDH1A1) and its correlation with Epithelial-like phenotype marker (E-cadherin) and Mesenchymal-like phenotype marker (N-cadherin) in LCNEC patients. MethodsImmunohistochemistry (IHC) for ALDH1A1, E-cadherin and N-cadherin expression was conducted on tissue microarrays made from 79 resected LCNEC patient samples. ALDH1A1 protein expression was evaluated by the IHC score, and its correlations with the expression of E-cadherin, N-cadherin and clinicopathological features were determined based on IHC data. Survival analyses were also performed. ResultsALDH1A1 was positively expressed in 75.9% (60/79 cases) of LCNEC patients. No significant difference in clinicopathological variables was observed between the ALDH1A1-negative and ALDH1A1-positive groups. However, ALDH1A1 expression was positively correlated with E-cadherin (Spearman's rho = 0.229, p-value = 0.007), which represents the epithelial-like phenotype, but not with N-cadherin. Patients with expression of ALDH1A1 had significantly longer disease-free survival (DFS) and overall survival (OS) than those who were ALDH1A1 negative (median DFS: 52 vs 12 months, p = 0.028; median OS: not reached; p = 0.027). Multivariate analysis showed that ALDH1A1 was an independent favorable prognostic factor for DFS (p = 0.032, HR: 0.438, 95% CI: 0.206–0.932) and OS (p = 0.025, HR: 0.279, 95% CI: 0.091–0.852) in LCNEC patients. ConclusionThis study suggests that ALDH1A1 can act as a favorable independent prognostic factor for LCNEC, which related to the epithelioid phenotype in EMT, and its internal mechanism needs further study.

Comprehensive Characterization of the Genomic Landscape in Chinese Pulmonary Neuroendocrine Tumors Reveals Prognostic and Therapeutic Markers (CSWOG-1901).

BackgroundPulmonary neuroendocrine tumors (pNETs) include typical carcinoid (TC), atypical carcinoid (AC), large cell neuroendocrine carcinoma (LCNEC), and small cell lung carcinoma (SCLC). The optimal treatment strategy for each subtype remains elusive, partly due to the lack of comprehensive understanding of their molecular features. We aimed to explore differential genomic signatures in pNET subtypes and identify potential prognostic and therapeutic biomarkers.MethodsWe investigated genomic profiles of 57 LCNECs, 49 SCLCs, 18 TCs, and 24 ACs by sequencing tumor tissues with a 520-gene panel and explored the associations between genomic features and prognosis.ResultsBoth LCNEC and SCLC displayed higher mutation rates for TP53, PRKDC, SPTA1, NOTCH1, NOTCH2, and PTPRD than TC and AC. Small cell lung carcinoma harbored more frequent co-alterations in TP53-RB1, alterations in PIK3CA and SOX2, and mutations in HIF-1, VEGF and Notch pathways. Large cell neuroendocrine carcinoma (12.7 mutations/Mb) and SCLC (11.9 mutations/Mb) showed higher tumor mutational burdens than TC (2.4 mutations/Mb) and AC (7.1 mutations/Mb). 26.3% of LCNECs and 20.8% of ACs harbored alterations in classical non-small cell lung cancer driver genes. The presence of alterations in the homologous recombination pathway predicted longer progression-free survival in advanced LCNEC patients with systemic therapy (P = .005) and longer overall survival (OS) in SCLC patients with resection (P = .011). The presence of alterations in VEGF (P = .048) and estrogen (P = .018) signaling pathways both correlated with better OS in patients with resected SCLC.ConclusionWe performed a comprehensive genomic investigation on 4 pNET subtypes in the Chinese population. Our data revealed distinctive genomic signatures in subtypes and provided new insights into the prognostic and therapeutic stratification of pNETs.

Effect of Adjuvant and Palliative Chemotherapy in Large Cell Neuroendocrine Carcinoma of the Lung: A Systematic Review and Meta-Analysis.

Simple SummaryAdjuvant chemotherapy revealed a better outcome than surgery only, but there was no statistical difference in patients with stage IA. The small cell lung cancer regimen (SCLC) was frequently selected in adjuvant chemotherapy. The SCLC regimen showed better survival than the non-SCLC regimen as palliative chemotherapy at the endpoint of the odds ratio of mortality after two years. Background: Pulmonary large cell neuroendocrine carcinoma (LCNEC) is a rare subset of lung carcinoma with poor overall survival. Methods: A systematic review following a meta-analysis of studies was performed to identify the effect of different selections of chemotherapy in LCNEC. Articles providing overall survival data for adjuvant chemotherapy or palliative chemotherapy for LCNEC were eligible. The odds ratio (OR) of mortality at one or two years after chemotherapy was evaluated. Results: A total of 16 reports were finally included in the quantitative synthesis, involving a total of 5916 LCNEC patients. Adjuvant chemotherapy was administered to 1303 patients, and palliative chemotherapy was administered to 313 patients using either a small cell lung cancer (SCLC) or a non-small cell lung cancer (NSCLC) regimen. The OR for adjuvant chemotherapy was 0.73 (95% confidence interval (CI): 0.59 to 0.89, p = 0.002). The SCLC regimen showed an OR of 0.52 (95% CI: 0.11 to 2.38, p = 0.40) after one year, and 0.32 (95% CI: 0.11 to 0.89, p = 0.03) after two years, compared with the NSCLC regimen. Conclusions: Adjuvant chemotherapy for pulmonary large cell neuroendocrine carcinoma improved the outcome after surgery. The SCLC regimen showed better survival than the NSCLC regimen as palliative chemotherapy.

A Clinical Nomogram for Predicting Cancer-Specific Survival in Pulmonary Large-Cell Neuroendocrine Carcinoma Patients: A Population-Based Study.

PurposeThis study was designed to construct and validate a nomogram that was available for predicting cancer-specific survival (CSS) in patients with pulmonary large-cell neuroendocrine carcinoma (LCNEC).Patients and MethodsUsing the US Surveillance, Epidemiology, and End Results (SEER) database, we identified patients pathologically diagnosed as LCNEC from 1975 to 2016. Univariate and multivariate Cox regression was conducted to assess prognostic factors of CSS. A novel nomogram model was constructed and validated by the concordance index (C-index), calibration curves and decision curve analysis (DCA).ResultsA total of 624 LCNEC patients were enrolled. Five prognostic factors for CSS were identified and merged to establish nomograms. In the training and validation cohorts, calibration curves displayed the nomogram predictions are in a good agreement with the actual survival. The C-Index of the training and validation cohorts were both higher than 0.8, and the DCA results showed that the nomogram has clinical validity and utility.ConclusionThe proposed nomogram resulted in accurate CSS prognostic prediction for patients with LCNEC.

Prevalence of Delta-Like Protein 3 in a Consecutive Series of Surgically Resected Lung Neuroendocrine Neoplasms.

Delta-like protein 3 (DLL3) is a protein of the Notch pathway, and it is a potential therapeutic target for high-grade lung neuroendocrine tumors (NETs), i.e., small cell lung carcinoma (SCLC) and large cell neuroendocrine carcinoma (LCNEC). However, DLL3 prevalence in lung NETs and its association with clinicopathological characteristics and prognosis remained unclear. We analyzed the immunohistochemical expression of DLL3 and its prognostic role in a consecutive series of 155 surgically resected lung NETs, including typical carcinoid (TC), atypical carcinoid (AC), LCNEC, and SCLC patients. The DLL3 expression was categorized as high (>50% positive tumor cells) or low (<50%). In addition, tumors were categorized by H-score (i.e., percentage of positive cells by staining intensity, ≥150 vs. <150). DLL3 staining was positive in 99/155 (64%) samples, and high DLL3 expression was frequently observed in high-grade tumors. In detail, 46.9% and 75% of SCLC and 48.8% and 53.7% of LCNEC specimens showed a high DLL3 expression by using H-score and percentage of positive tumor cells, respectively. Regarding low-grade NETs, only 4.9% and 12.2% TCs and 19.5% and 24.4% ACs had high DLL3 expression considering H-score and percentage of positive tumor cells, respectively. High DLL3 expression was associated with advanced American Joint Committee on Cancer (AJCC) stage, peripheral location, and chromogranin A expression in high-grade tumors (p < 0.05). In low-grade NETs, high DLL3 expression was associated with female sex, peripheral location, a higher number of mitoses, higher Ki-67 index, presence of necrosis, and pleural infiltration (p < 0.05). No association was observed between high DLL3 expression and overall survival (OS) and disease-free survival (DFS) in high-grade NETs, whereas high DLL3 expression was associated with lower DFS in ACs (p = 0.01). In conclusion, our study demonstrated a high prevalence of DLL3 expression in high-grade lung NET patients and its association with aggressive clinicopathological features. These findings confirm that DLL3 could represent a useful biomarker for target therapy in high-grade tumors. Our results also suggest that the DLL3 expression could identify a subset of AC tumors with more aggressive behavior, thus providing the basis for new therapeutic options in this group of patients.

Incidence and Survival Outcomes in Patients with Lung Neuroendocrine Neoplasms in the United States.

Simple SummaryNeuroendocrine tumors are a rare group of neoplasms characterized by strikingly heterogeneous pathological features and clinical behavior. The incidence and prevalence of these tumors are rising. Studies have reported the incidence and prevalence of neuroendocrine tumors; however, specific data targeting lung neuroendocrine tumors are lacking. We conducted a retrospective analysis using a national database to report the incidence and survival trends of lung neuroendocrine neoplasms. We found that the overall survival and disease-specific survival trends varied significantly not only by stage and histological type but also by age, race, marital status, and insurance type. A small difference was also noted between the rural and urban populations. The rarity of these tumors poses several diagnostic and therapeutic challenges. Our findings generate the following hypothesis that increased awareness of these tumors, as well as better diagnostic modalities, may contribute to a higher incidence. Furthermore, newer therapeutic advances may have caused an improvement in the survival trends in recent years. Such population-based analysis is important to allot resources and guide future research in the field.Background: The incidence and prevalence of neuroendocrine neoplasms (NENs) are rapidly rising. Epidemiologic trends have been reported for common NENs, but specific data for lung NENs are lacking. Methods: We conducted a retrospective analysis utilizing the Surveillance, Epidemiology, and End Results (SEER) database. Associated population data were utilized to report the annual age-adjusted incidence and overall survival (OS) trends. Trends for large-cell neuroendocrine carcinoma (LCNEC) and atypical carcinoid (AC) were reported from 2000–2015, while those for typical carcinoid (TC) and small cell lung cancer (SCLC) were reported from 1988–2015. Results: We examined a total of 124,969 lung NENs [103,890—SCLC; 3303—LCNEC; 8146—TC; 656—AC; 8974—Other]. The age-adjusted incidence rate revealed a decline in SCLC from 8.6 in 1988 to 5.3 in 2015 per 100,000; while other NENs showed an increase: TC increased from 0.57 in 1988 to 0.77 in 2015, AC increased from 0.17 in 2001 to 0.22 in 2015, and LCNEC increased from 0.16 in 2000 to 0.41 in 2015. The 5-year OS rate among SCLC, LCNEC, AC, and TC patients was 5%, 17%, 64%, and 84%, respectively. On multivariable analyses, OS and disease-specific survival (DSS) varied significantly by stage, sex, histological type, insurance type, marital status, and race, with a better survival noted in earlier stages, females, married, insured, Hispanic and other races, and urban population. Similarly, TC and AC had better survival compared to SCLC and LCNEC. Conclusion: The incidence of lung NENs is rising, possibly in part because of advanced radiological techniques. However, the incidence of SCLCs is waning, likely because of declining smoking habits. Such population-based studies are essential for resource allocation and to prioritize future research directions.