Mutational and gene fusion analyses of primary large cell and large cell neuroendocrine lung cancer

Investigation into the Spatial Heterogeneity of Lung Composite Large-Cell Neuroendocrine Carcinoma Spatial Transcriptomic Analysis of Combined Large-Cell Neuroendocrine Carcinoma

Background: Lung combined large-cell neuroendocrine carcinoma (CoLCNEC) refers to lung regions exhibiting both the features of large-cell neuroendocrine carcinoma (LCNEC) and the defined components of nonsmall cell lung cancer (NSCLC), with a relatively high mitotic rate. Diagnosing and predicting the prognosis of CoLCNEC are challenging. This study aimed to explore spatial transcriptomic expression patterns and identify crucial genes. Methods: We utilized a sample from a CoLCNEC patient containing three distinct components, namely, LCNEC, adenocarcinoma, and squamous cell carcinoma, with the former being predominant. Spatial transcriptomics (ST) technology, which employs the 10× Genomics Visium formalin-fixed paraffin-embedded ST kit, was applied along with high-throughput sequencing to obtain gene expression information and spatial locations for each spot. Subsequent analysis included differentially gene expression and functional enrichment. Finally, immunohistochemistry was employed to validate the marker protein structural maintenance of chromosomes 1A (SMC1A). Then, SMC1A was overexpressed and silenced in NCI-H661 and LTEP-a-2 cells, and the migration and invasion ability of the cells were detected by scratch assay and Transwell, respectively. The role of SMC1A in cancer cell cycle was detected by Real-time Reverse Transcription-PCR(RT-qPCR), Western blot, and flow cytometry, the apoptosis was detected by flow cytometry. Results: The results revealed that tumor tissue regions had higher unique molecular identifiers and gene counts than nontumor regions did. Unsupervised clustering identified four clusters, revealing the uniform distribution of unique transcripts, which were mapped onto slices to display apparent spatial separation. Differentially gene expression analysis revealed genes highly expressed in cancer cells. Further analysis of different regions revealed distinct cellular subgroups enriched through differentially gene expression analysis in various pathways, such as the cell cycle and DNA replication. Finally, SMC1A was chosen as a candidate gene, and immunohistochemistry confirmed its elevated expression in tumor regions. In addition, compared with oe-NC, oe-SMC1A can significantly promote the migration, invasion and G1/S phase transition of lung cancer cells, and promote the inhibition of apoptosis of cancer cells, while sh-SMC1A is completely opposite. Conclusions: In the tumor region of CoLCNEC, SMC1A is significantly upregulated. Moreover, silencing SMC1A effectively inhibits lung cancer cell invasion, migration, and G1/S phase transition, while promoting apoptosis. These findings indicate that SMC1A has the potential to be a new therapeutic target for CoLCNEC treatment.

Clinical and pathological characteristics of gastric large cell neuroendocrine carcinoma: A report of 2 cases series and literature review

RATIONALE

Gastric large cell neuroendocrine carcinoma (LCNEC) is a rare, aggressive neuroendocrine carcinoma that arises from the stomach and with high malignancy. Patients with gastric LCNEC usually have a poor prognosis. The standard treatment plan has not been established and its curative effect is poor. The present study described 2 cases diagnosed with gastric LCNEC and reviewed in depth the literature to improve our understanding more about this uncommon tumor and further to provide more experience to diagnose and treat this disease.

PATIENT CONCERNS

The present study reported 2 cases of gastric LCNEC in male patients aged 51 and 73 years old, respectively. Both patients had epigastric discomfort, pain, acid reflux and heartburn. The medical history was unremarkable.

DIAGNOSES

The ulcerative lesion located at gastric was examined in the 2 patients by taking the esophagogastroduodenoscopy (EGO), computed tomography (CT) and digital gastrointestinal radiography (GI), that both were suspected gastric malignancy. Endoscopic biopsies of the tumor led to the initial diagnosis of gastric cancer. Postoperative pathological and immunohistochemical examinations of the surgical specimens confirmed that 1 case had mixed adeno-neuroendocrine carcinoma (MANEC) and the other had LCNEC.

INTERVENTIONS

Both patients underwent surgical resection and received etoposide-cisplatin combination chemotherapy following surgery.

OUTCOMES

The operation was successful. Both patients had uneventful recoveries following surgery, and had been followed-up regularly. The general condition was satisfactory, and no tumor metastasis was observed at present.

Characterization of two transcriptomic subtypes of marker-null large cell carcinoma of the lung suggests different origin and potential new therapeutic perspectives

Pulmonary large cell carcinoma (LCC) is an undifferentiated neoplasm lacking morphological, histochemical, and immunohistochemical features of small cell lung cancer, adenocarcinoma (ADC), or squamous cell carcinoma (SCC). The available molecular information on this rare disease is limited. This study aimed to provide an integrated molecular overview of 16 cases evaluating the mutational asset of 409 genes and the transcriptomic profiles of 20,815 genes. Our data showed that TP53 was the most frequently inactivated gene (15/16; 93.7%) followed by RB1 (5/16; 31.3%) and KEAP1 (4/16; 25%), while CRKL and MYB genes were each amplified in 4/16 (25%) cases and MYC in 3/16 (18.8%) cases; transcriptomic analysis identified two molecular subtypes including a Pure-LCC and an adenocarcinoma like-LCC (ADLike-LCC) characterized by different activated pathways and cell of origin. In the Pure-LCC group, POU2F3 and FOXI1 were distinctive overexpressed markers. A tuft cell-like profile and the enrichment of a replication stress signature, particularly involving ATR, was related to this profile. Differently, the ADLike-LCC were characterized by an alveolar-cell transcriptomic profile and association with AIM2 inflammasome complex signature. In conclusion, our study split the histological marker-null LCC into two different transcriptomic entities, with POU2F3, FOXI1, and AIM2 genes as differential expression markers that might be probed by immunohistochemistry for the differential diagnosis between Pure-LCC and ADLike-LCC. Finally, the identification of several signatures linked to replication stress in Pure-LCC and inflammasome complex in ADLike-LCC could be useful for designing new potential therapeutic approaches for these subtypes.

Whole-genome characterization of large-cell lung carcinoma: A comparative analysis based on the histological classification

Background: According to the 2015 World Health Organization classification, large cell neuroendocrine carcinoma (LCNEC) was isolated from Large-cell lung cancer (LCLC) tumors, which constitutes 2%-3% of non-small cell lung cancer (NSCLC). However, LCLC tumors are still fairly vaguely defined at the molecular level compared to other subgroups. Materials and Methods: In this study, whole-genome sequencing (WGS) was performed on 23 LCLC and 15 LCNEC tumor specimens. Meanwhile, data from the TCGA (586 LUADs and 511 LUSCs) and U Cologne (120 SCLCs) were analyzed and compared. Results: The most common driver mutations were found in TP53 (13/23, 57%), FAM135B (8/23, 35%) and FAT3 (7/23, 30%) in LCLC, while their counterparts in LCNEC were TP53 (13/15, 87%), LRP1B (6/15, 40%) and FAT1 (6/15, 40%). Notably, FAM135B mutations only occurred in LCLC (P = 0.013). Cosmic signature analysis revealed widespread defective DNA mismatch repair and tobacco-induced mutations in both LCLC and LCNEC. Additionally, LCNEC had a higher incidence of chromosomal copy number variations (CNVs) and structural variations (SVs) compared with LCLC, although the differences were not statistically significant. Particularly, chromothripsis SVs was significantly associated with CNVs. Furthermore, mutational landscape of different subtypes indicated differences between subtypes, and there seems to be more commonalty between our cohort and SCLC than with other subtypes. SMARCA4 mutations may be specific driver gene alteration in our cohort. Conclusion: Our results support that LCLC and LCNEC tumors follow distinct tumorigenic pathways. To our knowledge, this is the first genome-wide profiling comparison of LCLC and LCNEC.

Exploratory genomic analysis of high-grade neuroendocrine neoplasms across diverse primary sites

High-grade (grade 3) neuroendocrine neoplasms (G3 NENs) have poor survival outcomes. From a clinical standpoint, G3 NENs are usually grouped regardless of primary site and treated similarly. Little is known regarding the underlying genomics of these rare tumors, especially when compared across different primary sites. We performed whole transcriptome (n = 46), whole exome (n = 40), and gene copy number (n = 43) sequencing on G3 NEN formalin-fixed, paraffin-embedded samples from diverse organs (in total, 17 were lung, 16 were gastroenteropancreatic, and 13 other). G3 NENs despite arising from diverse primary sites did not have gene expression profiles that were easily segregated by organ of origin. Across all G3 NENs, TP53, APC, RB1, and CDKN2A were significantly mutated. The CDK4/6 cell cycling pathway was mutated in 95% of cases, with upregulation of oncogenes within this pathway. G3 NENs had high tumor mutation burden (mean 7.09 mutations/MB), with 20% having >10 mutations/MB. Two somatic copy number alterations were significantly associated with worse prognosis across tissue types: focal deletion 22q13.31 (HR, 7.82; P = 0.034) and arm amplification 19q (HR, 4.82; P = 0.032). This study is among the most diverse genomic study of high-grade neuroendocrine neoplasms. We uncovered genomic features previously unrecognized for this rapidly fatal and rare cancer type that could have potential prognostic and therapeutic implications.

Targeting ALK in Neuroendocrine Tumors of the Lung

Background

Anaplastic lymphoma kinase (ALK) rearrangements are known oncogenic drivers in non-small cell lung cancer (NSCLC). Few case reports described the occurrence of such rearrangements in large cell neuroendocrine carcinomas (LCNECs) of the lung without information on clinical responses to ALK tyrosine kinase inhibitors (TKIs) in these cases. Currently, neuroendocrine tumors of the lungs are not screened for ALK rearrangements.

Methods

To illustrate the clinical impact of molecular characterization in LCNECs, we report the disease course in three patients with ALK-rearranged metastatic LCNEC from our clinical routine, as well as their treatment response to ALK TKIs (index cases). To gain insight into the prevalence of ALK rearrangements in neuroendocrine tumors of the lung, we analyzed a retrospective cohort of 436 tumor biopsies including LCNEC (n = 61), small cell lung cancer (SCLC) (n = 206), typical (n = 91) and atypical (n = 69) carcinoids, and mixed histology (n = 9) for the presence of ALK rearrangements using a sequential diagnostic algorithm. ALK immunohistochemistry (IHC) was evaluable in 362 cases; fluorescence in situ hybridization (FISH) was evaluable in 28 out of the 35 IHC-positive cases, followed by next-generation sequencing (NGS) that was available in 12 cases.

Results

Within the retrospective cohort, ALK IHC was positive in 35 out of 362 (9.7%) evaluable samples. FISH was positive in 3 out of the 28 (10.7%) evaluable cases: 2 with atypical carcinoids and 1 with LCNEC. Additionally, the 3 index cases showed positive ALK IHC, which was confirmed by NGS. Within the retrospective cohort, NGS confirmed the presence of an ALK genomic rearrangement in one FISH-positive atypical carcinoid where material was sufficient for sequencing. Two out of three patients with metastatic ALK-rearranged LCNEC received up-front treatment with the ALK TKI alectinib and showed rapid tumor response at all metastatic sites, including multiple brain metastases.

Conclusions

ALK rearrangements represent rare but targetable oncogenic driver alterations in LCNEC. Contrarily to NSCLC, the detection of ALK rearrangements in neuroendocrine tumors of the lung is challenging, since ALK IHC can lead to false-positive results and therefore needs confirmation by FISH or NGS. Up-front comprehensive molecular profiling with NGS should be performed in metastatic LCNEC in order not to miss actionable genomic alterations.

Diagnostic criteria and evolving molecular characterization of pulmonary neuroendocrine carcinomas

Neuroendocrine carcinomas of the lung are currently classified into two categories: small cell lung carcinoma and large cell neuroendocrine carcinoma. Diagnostic criteria for small cell- and large cell neuroendocrine carcinoma are based solely on tumor morphology; however, overlap in histologic and immunophenotypic features between the two types of carcinoma can potentially make their classification challenging. Accurate diagnosis of pulmonary neuroendocrine carcinomas is paramount for patient management, as clinical course and treatment differ between small cell and large cell neuroendocrine carcinoma. Molecular-genetic, transcriptomic, and proteomic data published over the past decade suggest that small cell and large cell neuroendocrine carcinomas are not homogeneous categories but rather comprise multiple groups of distinctive malignancies. Nuances in the susceptibility of small cell lung carcinoma subtypes to different chemotherapeutic regimens and the discovery of targetable mutations in large cell neuroendocrine carcinoma suggest that classification and treatment of neuroendocrine carcinomas may be informed by ancillary molecular and protein expression testing going forward. This review summarizes current diagnostic criteria, prognostic and predictive correlates of classification, and evidence of previously unrecognized subtypes of small cell and large cell neuroendocrine carcinoma.

Are anaplastic lymphoma kinase (ALK) and O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation driver biomarkers of pulmonary neuroendocrine tumors (NETs) and carcinomas (NECs)?

Background: Novel targets in neuroendocrine tumors (NETs) and neuroendocrine carcinomas (NECs) are needed to improve outcome. The presence of O6-Methylguanine-DNA methyltransferase (MGMT) promoter methylation in NETs and NECs may act as a predictive marker for response on treatment with temozolomide. As anaplastic lymphoma kinase (ALK) plays an important role in the nervous system we hypothesized that ALK rearrangement can act as a biomarker in patients with NETs and NECs.

Materials and Methods: We performed a retrospective analysis to establish the frequency of MGMT promoter methylation and ALK expression in tissue samples of patients with NETs and NECs.

Results: 21% (14/67) of patients tested positive for MGMT promoter methylation. MGMT promoter methylation was present in 33% (3/9) patients with typical carcinoid, in 22% (2/9) patients with atypical carcinoid, in 22% (8/37) patients with small cell lung cancer and in 8% (1/12) patient with large cell neuroendocrine carcinoma. ALK- expression was present in 14% (10 of 70 patients). In all of these patients, no ALK-rearrangement nor ALK-mutation was revealed.

Conclusions: Routine testing of NET and NEC samples for an ALK rearrangement is not recommended as ALK-expression is not associated with an ALK-rearrangement. Routine testing of NET and NEC samples for MGMT will detect a promoter hypermethylation in a sizable minority of patients who are eligible for a targeted treatment with temozolomide.

Pan-cancer analysis of necroptosis-related gene signature for the identification of prognosis and immune significance

BACKGROUND

Necroptosis is a novel programmed cell death mode independent on caspase. A number of studies have revealed that the induction of necroptosis could act as an alternative therapeutic strategy for drug-resistant tumors as well as affect tumor immune microenvironment.

METHODS

Gene expression profiles and clinical data were downloaded from XENA-UCSC (including The Cancer Genome Atlas and Genotype-Tissue Expression), Gene Expression Omnibus, International Cancer Genome Consortium and Chinese Glioma Genome Atlas. We used non-negative matrix factorization method to conduct tumor classification. The least absolute shrinkage and selection operator regression was applied to establish risk models, whose prognostic effectiveness was examined in both training and testing sets with Kaplan-Meier analysis, time-dependent receiver operating characteristic curves as well as uni- and multi-variate survival analysis. Principal Component Analysis, t-distributed Stochastic Neighbor Embedding and Uniform Manifold Approximation and Projection were conducted to check the risk group distribution. Gene Set Enrichment Analyses, immune infiltration analysis based on CIBERSORT, EPIC, MCPcounter, ssGSEA and ESTIMATE, gene mutation and drug sensitivity between the risk groups were also taken into consideration.

RESULTS

There were eight types of cancer with at least ten differentially expressed necroptosis-related genes which could influence patients' prognosis, namely, adrenocortical carcinoma (ACC), cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC), acute myeloid leukemia (LAML), brain lower grade glioma (LGG), pancreatic adenocarcinoma (PAAD), liver hepatocellular carcinoma (LIHC), skin cutaneous melanoma (SKCM) and thymoma (THYM). Patients could be divided into different clusters with distinct overall survival in all cancers above except for LIHC. The risk models could efficiently predict prognosis of ACC, LAML, LGG, LIHC, SKCM and THYM patients. LGG patients from high-risk group had a higher infiltration level of M2 macrophages and cancer-associated fibroblasts. There were more CD8+ T cells, Th1 cells and M1 macrophages in low-risk SKCM patients' tumor microenvironment. Gene mutation status and drug sensitivity are also different between low- and high-risk groups in the six cancers.

CONCLUSIONS

Necroptosis-related genes can predict clinical outcomes of ACC, LAML, LGG, LIHC, SKCM and THYM patients and help to distinguish immune infiltration status for LGG and SKCM.

Pulmonary large cell carcinoma with neuroendocrine morphology shows genetic similarity to large cell neuroendocrine carcinoma

Background

Large cell neuroendocrine carcinoma (LCNEC) is a high-grade malignant pulmonary neuroendocrine tumour. The distinction of pulmonary large cell carcinoma (LCC) and LCNEC is based on the presence of neuroendocrine morphology and the expression of at least one neuroendocrine marker in at least 10% of tumour cells in the latter. According to the current classification, LCC with neuroendocrine morphology and without neuroendocrine marker expression is classified as LCC. This subgroup we have named LCNEC-null and aimed to analyze its characteristics.

Methods

31 surgical samples resected in West China Hospital of Sichuan University between 2017 to 2021 were collected, including 7 traditional LCCs, 11 LCNEC-nulls and 13 LCNECs. Each case was conducted to immunohistochemistry and 425-panel-NGS.

Results

Compared to other LCCs, detailed analysis of LCNEC-nulls revealed biological features similar to those of LCNECs, especially for immunohistochemistry and molecular analysis: 1. diffusive, coarse granular and high expression of Pan-CK; 2. rare PD-L1 expression; 3. High rate of p53 expression and Rb deficiency 4. abundant genetic alterations are similar to LCNEC. All characteristics above deviated from traditional LCC, indicating they have the same origin as LCNEC. Furthermore, LCNEC could be genetically divided into two subtypes when we reclassified LCNEC-null as LCNEC, and the mutational type and prognosis differed significantly.

Conclusions

We consider that LCNEC-null should be reclassified as LCNEC based on analysis above. In addition, two genetic types of LCNEC with different prognosis also indicate two mechanism of tumour formation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13000-022-01204-9.

Biomarker Landscape in Neuroendocrine Tumors With High-Grade Features: Current Knowledge and Future Perspective

Neuroendocrine tumors (NETs) are classified based on morphology and are graded based on their proliferation rate as either well-differentiated low-grade (G1) to intermediate (G2–G3) or poorly differentiated high-grade neuroendocrine carcinomas (NEC G3). Recently, in gastroenteropancreatic (GEP) NETs, a new subgroup of well-differentiated high-grade tumors (NET G3) has been divided from NEC by WHO due to its different clinical–pathologic features. Although several mutational analyses have been performed, a molecular classification of NET is an unmet need in particular for G3, which tends to be more aggressive and have less benefit to the available therapies. Specifically, new possible prognostic and, above all, predictive factors are highly awaited, giving the basis for new treatments. Alteration of KRAS, TP53, and RB1 is mainly reported, but also druggable alterations, including BRAF and high microsatellite instability (MSI-H), have been documented in subsets of patients. In addition, PD-L1 demonstrated to be highly expressed in G3 NETs, probably becoming a new biomarker for G3 neuroendocrine neoplasm (NEN) discrimination and a predictive one for immunotherapy response. In this review, we describe the current knowledge available on a high-grade NET molecular landscape with a specific focus on those harboring potentially therapeutic targets in the advanced setting.

Role of Immune Checkpoint Inhibitor Therapy in Advanced EGFR-Mutant Non-Small Cell Lung Cancer

Over the last decade, the treatment of advanced non-small cell lung cancer (NSCLC) has undergone rapid changes with innovations in oncogene-directed therapy and immune checkpoint inhibitors. In patients with epidermal growth factor receptor (EGFR) gene mutant (EGFRm) NSCLC, newer-generation tyrosine kinase inhibitors (TKIs) are providing unparalleled survival benefit and tolerability. Unfortunately, most patients will experience disease progression and thus an urgent need exists for improved subsequent lines of therapies. The concurrent revolution in immune checkpoint inhibitor (ICI) therapy is providing novel treatment options with improved clinical outcomes in wild-type EGFR (EGFRwt) NSCLC; however, the application of ICI therapy to advanced EGFRm NSCLC patients is controversial. Early studies demonstrated the inferiority of ICI monotherapy to EGFR TKI therapy in the first line setting and inferiority to chemotherapy in the second line setting. Additionally, combination ICI and EGFR TKI therapies have demonstrated increased toxicities, and EGFR TKI therapy given after first-line ICI therapy has been correlated with severe adverse events. Nonetheless, combination therapies including dual-ICI blockade and ICI, chemotherapy, and angiogenesis inhibitor combinations are areas of active study with some intriguing signals in preliminary studies. Here, we review previous and ongoing clinical studies of ICI therapy in advanced EGFRm NSCLC. We discuss advances in understanding the differences in the tumor biology and tumor microenvironment (TME) of EGFRm NSCLC tumors that may lead to novel approaches to enhance ICI efficacy. It is our goal to equip the reader with a knowledge of current therapies, past and current clinical trials, and active avenues of research that provide the promise of novel approaches and improved outcomes for patients with advanced EGFRm NSCLC.

[Advances in Molecular Biomarker for Pulmonary Large Cell Neuroendocrine Carcinoma]

Pulmonary large cell neuroendocrine carcinoma (LCNEC) is a pathological subtype of lung neuroendocrine cancer, which accounts for 2.4%-3.1% in surgical specimens of lung cancer. It is characterized by high invasiveness and poor prognosis, and highly correlated with smoking. There are few relevant studies due to the low incidence and small sample size. Therefore, it is relatively difficult to diagnosis and treatment in clinical practice. In this review, we described molecular subtype, diagnostic and prognostic-related markers about large cell neuroendocrine carcinoma of lung based on the recent progress in genomic sequencing and molecular markers, to find the direction for the next research.
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Prevalence of TP-53/Rb-1 Co-Mutation in Large Cell Neuroendocrine Carcinoma

Introduction

Large cell neuroendocrine carcinoma (LCNEC) is a rare and highly aggressive high-grade neuroendocrine neoplasm, which can arise from anywhere in the body. Due to its rarity there is a lacuna in our understanding of LCNEC's molecular biology. In 2016, Rekhtman and colleagues presented one of the largest molecular sequencing series of pulmonary LCNEC. They differentiated genomic profiles of LCNEC into two major subsets: small cell lung cancer (SCLC)-like, characterized by TP53 + RB1 co-mutation/loss, and non-small cell lung cancer (NSCLC)-like, characterized by the lack of co-altered TP53 + RB1. This finding is of significance because at present LCNEC patients are often treated like SCLC. However, the universal genomic SCLC biomarker of TP53 and RB1 co-mutation was only found in 40% of their cohort. Since then various other scientists have looked into molecular profiling of LCNEC with markedly discordant results. The objective of this study was to conduct a systematic review of publicly available next generation sequencing (NGS) data to evaluate the prevalence of TP53 + RB1 co-mutation in LCNEC.

Method

We conducted a literature search using PubMed. Seven studies including 302 patients with pulmonary LCNEC and four studies including 20 patients with extra-pulmonary LCNEC underwent final analysis.

Results

The prevalence of TP53 + RB1 co-mutation was 36% (109/302) among pulmonary LCNEC patients and 35% (7/20) among the extra-thoracic LCNEC cohort. This finding is in stark contrast to >90% TP53 + RB1 co-mutation in SCLC.

Conclusion

It is now well established that LCNEC is molecularly distinct from SCLC. LCNEC seems to have two molecularly defined sub-cohort based on TP53 + RB1 co-mutation status. Future studies should look into prognostic and predictive implication of TP53 + RB1 co-mutation status in LCNEC. Prospective studies should be designed to characterize molecular subtypes and direct treatment accordingly. We are currently conducting a prospective pilot clinical trial wherein LCNEC patients are treated based on TP53 + RB1 co-mutation status. The study is currently enrolling. "Next Generation Sequencing-Based Stratification of Front Line Treatment of Neuroendocrine Carcinoma (PRECISION-NEC).

Systematic Review

ClinicalTrials.gov, identifier NCT04452292.

Clinicopathological and molecular characteristics of endometrial neuroendocrine carcinomas reveal preexisting endometrial carcinoma origin

Endometrial neuroendocrine carcinoma is a rare disease with unknown clinicopathological and molecular characteristics. Therefore, we conducted the present study to elucidate the clinicopathological and molecular characteristics of endometrial neuroendocrine carcinoma, as compared to conventional endometrial carcinoma, and to determine the origin of the former. We analyzed 22 endometrial neuroendocrine carcinomas and 22 conventional endometrial neoplasia cases with respect to clinical, histological and genetic features. Of these, 21/22 neuroendocrine carcinoma cases were admixed carcinomas, with 15 admixed with endometrioid adenocarcinoma. Genetic analysis of hotspot mutations in 50 cancer-related genes revealed that the neuroendocrine carcinoma group carried mutations in PIK3CA (12/22 cases; 54%) and PTEN (8/22 cases; 36%), commonly encountered in endometrioid adenocarcinoma. Comparative statistical analysis of neuroendocrine carcinoma and conventional endometrial neoplasia cases showed a significant trend only in PIK3CA mutation. Moreover, in six mixed-type neuroendocrine carcinoma cases, macrodissection was used to separate the neuroendocrine carcinoma and endometrioid adenocarcinoma components for next-generation sequencing, which revealed several mutations common among the two. These findings suggest that endometrial neuroendocrine carcinoma could originate from conventional endometrial neoplasia, especially endometrioid adenocarcinoma.

Molecular Pathology of Pulmonary Large Cell Neuroendocrine Carcinoma: Novel Concepts and Treatments

Pulmonary large cell neuroendocrine carcinoma (LCNEC) is an aggressive neoplasm with poor prognosis. Histologic diagnosis of LCNEC is not always straightforward. In particular, it is challenging to distinguish small cell lung carcinoma (SCLC) or poorly differentiated carcinoma from LCNEC. However, histological classification for LCNEC as well as their therapeutic management has not changed much for decades. Recently, genomic and transcriptomic analyses have revealed different molecular subtypes raising hopes for more personalized treatment. Two main molecular subtypes of LCNEC have been identified by studies using next generation sequencing, namely type I with TP53 and STK11/KEAP1 alterations, alternatively called as non-SCLC type, and type II with TP53 and RB1 alterations, alternatively called as SCLC type. However, there is still no easy way to classify LCNEC subtypes at the actual clinical level. In this review, we have discussed histological diagnosis along with the genomic studies and molecular-based treatment for LCNEC.

Large Cell Neuro-Endocrine Carcinoma of the Lung: Current Treatment Options and Potential Future Opportunities

Large-cell neuroendocrine carcinomas of the lung (LCNECs) are rare tumors representing 1-3% of all primary lung cancers. Patients with LCNEC are predominantly male, older, and heavy smokers. Histologically, these tumors are characterized by large cells with abundant cytoplasm, high mitotic rate, and neuroendocrine immunohistochemistry-detected markers (chromogranin-A, synaptophysin, and CD56). In 2015 the World Health Organization classified LCNEC as a distinct subtype of pulmonary large-cell carcinoma and, therefore, as a subtype of non-small cell lung carcinoma (NSCLC). Because of the small-sized tissue samples and the likeness to other neuroendocrine tumors, the histological diagnosis of LCNEC remains difficult. Clinically, the prognosis of metastatic LCNECs is poor, with high rates of recurrence after surgery alone and overall survival of approximately 35% at 5 years, even for patients with early stage disease that is dramatically shorter compared with other NSCLC subtypes. First-line treatment options have been largely discussed but with limited data based on phase II studies with small sample sizes, and there are no second-line well defined treatments. To date, no standard treatment regimen has been developed, and how to treat LCNEC is still on debate. In the immunotherapy and targeted therapy era, in which NSCLC treatment strategies have been radically reshaped, a few data are available regarding these opportunities in LCNEC. Due to lack of knowledge in this field, many efforts have been done for a deeper understanding of the biological and molecular characteristics of LCNEC. Next generation sequencing analyses have identified subtypes of LCNEC that may be relevant for prognosis and response to therapy, but further studies are needed to better define the clinical impact of these results. Moreover, scarce data exist about PD-L1 expression in LCNEC and its predictive value in this histotype with regard to immunotherapy efficacy. In the literature some cases are reported concerning LCNEC metastatic patients carrying driver mutations, especially EGFR alterations, showing targeted therapy efficacy in this setting of disease. Due to the rarity and the challenging understanding of LCNEC, in this review we aim to summarize the management options currently available for treatment of LCNEC.

Genomics of High-Grade Neuroendocrine Neoplasms: Well-Differentiated Neuroendocrine Tumor with High-Grade Features (G3 NET) and Neuroendocrine Carcinomas (NEC) of Various Anatomic Sites

High-grade neuroendocrine neoplasms (HG-NENs) are clinically aggressive diseases, the classification of which has recently been redefined. They now include both poorly differentiated NENs (neuroendocrine carcinoma, NECs) and high proliferating well-differentiated NENs (called grade 3 neuroendocrine tumors, G3 NETs, in the digestive system). In the last decade, the "molecular revolution" that has affected all fields of medical oncology has also shed light in the understanding of HG NENs heterogeneity and has provided new diagnostic and therapeutic tools, useful in the management of these malignancies. Considering the kaleidoscopic aspects of HG NENs in various anatomical sites, this review systematically addresses the genomic landscape of such neoplasm throughout the more common thoracic and digestive locations, as well as it will consider other rare but not exceptional primary sites, including the skin, the head and neck, and the urogenital system. The revision of the available literature will then be oriented to understand the translational relevance of molecular data, by analyzing conceptual issues, clinicopathological correlations, and unmet needs in this field.

Detection of Non-Small Lung Cell Carcinoma-Associated Genetic Alterations Using a NanoString Gene Expression Platform Approach

In non-small cell lung cancer (NSCLC), mutation detection and fusion gene status are treatment predictive and, hence, key factors in clinical management. Lately, alternate splicing variants of MET have gained focus as NSCLC tumors harboring a MET exon 14 skipping event have proven sensitive toward targeted therapy. Reliable methods for detection of genetic alterations in NSCLC have proven to be of increased importance. This chapter provides with hands-on experience of the NanoString gene expression platform for detection of genetic alterations in NSCLC.

A Population-Based Systematic Clinical Analysis With a Single-Center Case Series of Patients With Pulmonary Large Cell Neuroendocrine Carcinoma

BACKGROUND AND OBJECTIVES

This study aims to conduct an updated systematic analysis of patients with pulmonary large cell neuroendocrine carcinoma (PLCNC) in recent decades, concerning incidence and mortality trends, demographics, treatments, survival and death causes.

METHODS

Patients who were diagnosed with PLCNC at the Peking Union Medical College Hospital (PUMCH) between 2000 to 2020 were retrospectively analyzed. The population-based Surveillance, Epidemiology, and End Results (SEER) database were also retrieved. Frequencies and average annual age-adjusted rates (AAR) of PLCNC patients were calculated and analyzed by Joint-point regression. Univariate and multivariate Cox regression were used for identifying prognostic factors. Predictive nomograms for overall survival (OS) and cancer-specific survival (CSS) were developed and then validated by calculating C-index values and drawing calibration curves. Survival curves were plotted using the Kaplan-Meier method and compared by log-rank test. Causes of death were also analyzed by time latency.

RESULTS

A total of 56 PLCNC patients of the PUMCH cohort were included. Additionally, the PLCNC patients in the SEER database were also identified from different subsets. The AAR from 2001 to 2017 were 3.21 (95%CI: 3.12-3.30) per million. Its incidence and mortality rates in PLCNC patients increased at first but seemed to decline in recent years. Besides TNM stage and treatments, older age and male gender were independently associated with poorer survival, while marital status only affected CSS other than OS. The nomograms for OS and CSS presented great predictive ability and calibration performance. Surgery gave significantly more survival benefits to PLCNC patients, and chemotherapy might add survival benefits to stage II-IV. However, radiation therapy seemed to only improve stage III patients' survival.

CONCLUSIONS

This study supported some previous studies in terms of incidence, survival, and treatment options. The mortality rates seemed to decline recently, after an earlier increase. Among PLCNC patients, most of the deaths occurred within the first five years, while other non-PLCNC diseases increased after that. Thus, careful management and follow-up of other comorbidities are of equal importance. Our study may partly solve the dilemma caused by PLCNC's rarity and inspire more insights in future researches.

Challenges in Ki-67 assessments in pulmonary large-cell neuroendocrine carcinomas

AIMS

To gather the best available evidence regarding Ki-67% values in large-cell neuroendocrine carcinoma (LCNEC) and determine whether certain cut-off values could serve as a prognostic feature in LCNEC.

METHODS AND RESULTS

Aperio ScanScope AT Turbo, eSlide Manager and ImageScope software (Leica Biosystems) were used to measure Ki-67% in 77 resected LCNEC diagnosed by World Health Organisation (WHO) criteria. Cases were stratified into six classes by 10% Ki-67 increments. Using the Kaplan-Meier method, overall (OS) and disease-free survivals (DFS) were compared by AJCC stage, by six Ki-67% classes and with Ki-67% cut-points ≥20% and ≥40%. Tumours were from 0.9 to 11.5 cm and pathological stages 1-3. The system measured Ki-67% positivity using 4072-44 533 tumour nuclei per case (mean 16610 ± 8039). Ki-67% ranged from 1 to 64% (mean = 26%; median = 26%). Only 16 (21%) tumours had Ki-67% ≥40%. OS ranged from 1 to 298 months (median follow-up = 25 months). DFS ranged from 1 to 276 months (median follow-up = 9 months). OS and DFS differed across AJCC stage (overall log-rank P = 0.038 and P = 0.037). However, neither OS nor DFS significantly correlated with Ki-67% when six or two classes were used with either ≥20% Ki-67 or ≥40% Ki-67 as cut-point. A literature review identified 14 reports meeting our inclusion criteria with ≥10 LCNEC. Reported Ki-67% ranged from 2% to 100%. Problems contributing to variability in Ki-67% measurements are discussed.

CONCLUSION

Our findings caution against a blanket use of 20%, 40% or other Ki-67% cut-points for LCNEC diagnosis or prognostication.

Beyond Traditional Morphological Characterization of Lung Neuroendocrine Neoplasms: In Silico Study of Next-Generation Sequencing Mutations Analysis across the Four World Health Organization Defined Groups

Simple Summary

Lung neuroendocrine neoplasms (LNENs) classes, as proposed by the World Health Organization 2015, do not provide properly prognostic and therapeutic indications. In fact, high-throughput molecular analysis, based on next-generation sequencing, identified novel molecular subgroups, associated with different genomic signatures, that could pave the way for alternative therapeutic approaches. The present review, coupled with in silico molecular analysis, could show the current genomic alterations state in actual LNENS groups. Interestingly our manuscript suggests that the molecular novelties could improve the LNENs therapeutics efficacy. In more detail, we reported the differences of gene alterations and mutational rate between LNENS, confirming the central pathogenetic role given by a different mutational rate in chromatin remodeling genes and tumor suppressors TP53-RB1. In conclusion, our results underlined that a further molecular layer is needed to improve the efficacy of LNENs medical treatment.

Abstract

Lung neuroendocrine neoplasms (LNENs) represent a rare and heterogeneous population of lung tumors. LNENs incidence rate has increased dramatically over the past 30 years. The current World Health Organization LNENs classification (WHO 2015), distinguished four LNENs prognostic categories, according to their morphology, necrosis amount and mitotic count: typical carcinoid (TC), atypical-carcinoid (AC), large cell neuroendocrine carcinoma (LCNEC) and small cell lung cancer (SCLC). At present, due to their rarity and biological heterogeneity there is still no consensus on the best therapeutic approach. Next-generation-sequencing analysis showed that WHO 2015 LNENs classes, could be characterized also by specific molecular alterations: frequently mutated genes involving chromatin remodeling and generally characterized by low mutational burden (MB) are frequently detected in both TC and AC; otherwise, TP53 and RB1 tumor suppressor genes alterations and high MB are usually detected in LCNEC and SCLC. We provide an overview concerning gene mutations in each WHO 2015 LNENs class in order to report the current LNENs mutational status as potential tool to better understand their clinical outcome and to drive medical treatment.

Pulmonary Large-Cell Neuroendocrine Carcinoma: Therapeutic Challenges and Opportunities

Pulmonary large cell neuroendocrine carcinoma (P-LCNEC) is a rare, poorly differentiated, non-small cell malignancy within the spectrum of neuroendocrine tumors (NETs) of the lung. Despite sharing several similarities with small cell lung cancer (SCLC) in their clinical, immunohistopathological, genomic, and prognostic features, it is a distinct and biologically heterogeneous entity with challenging diagnostic and therapeutic requirements. Given the lack of prospective, randomized data to guide management, it is common practice to pursue thoracic surgery for resectable tumors according to the guidelines for non-small cell lung cancer (NSCLC) and implement systemic chemotherapy as early as at stage I, similar to the treatment of SCLC. However, important issues, such as the optimal timing and combination of therapeutic modalities, the most effective type of chemotherapy for advanced-stage disease, and the benefit from prophylactic cranial irradiation, remain debated. Accumulating evidence from retrospective, molecular profiling studies supports the existence of at least two P-LCNEC subtypes, most notably a SCLC-like and a NSCLC-like phenotype, which presumably underlie the observed differential sensitivity to platinum-based regimens and warrant further validation as predictive biomarkers of efficacy. Furthermore, several potentially actionable, driver molecular alterations have been identified, offering implications for personalized treatment approaches, including targeted therapies and immunotherapy. The current review discusses open questions on the diagnosis and management of P-LCNEC, as well as recent advances in its genomic and transcriptomic characterization that create promising therapeutic opportunities.

Multiple faces of pulmonary large cell neuroendocrine carcinoma: update with a focus on practical approach to diagnosis

Pulmonary large cell neuroendocrine carcinoma (LCNEC) is a rare and aggressive malignancy that is strongly linked to smoking and notoriously difficult to diagnose and treat. Recent molecular data reveal that it represents a biologically heterogeneous group of tumors, characterized by morphologic and genomic diversity that straddles small cell and non-small cell lung carcinomas (NSCLCs), and in a minority of cases atypical carcinoids. This review provides an update on recent molecular and clinical developments in LCNEC with the main focus on practical approach to pathologic diagnosis using illustrative examples of the main differential diagnostic considerations.

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

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

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.

Clinical Application of Fusion Gene Detection Using Next-Generation Sequencing and the NanoString Technology

Fusion gene detection is of great diagnostic value since the presence of fusion genes may dictate treatment and patient outcome. When detecting fusion genes in clinical samples there are multiple aspects to consider regarding sample origin, choice of fusion gene detection technique, and data analysis.

Clinical genetic features and related survival implications in patients with surgically resected large-cell lung cancer

Background: Large-cell lung carcinomas (LCLCs) were reclassified by the World Health Organization 2015 criteria. and remain fairly unknown at the molecular level and targeted-therapeutic options.

Methods: Data of 184 lung cancer patients were retrieved from clinical records, of which 54 were found to be pathologically diagnosed as LCLC. The genetic alterations EGFR/KRAS/BRAF mutations, MET copy number, and exon 14 mutation, ALK and ROS1 rearrangements, and PDL1 expression were investigated using clinical technologies. The relationship between clinicopathologic and genetic features was analyzed, and the Kaplan–Meier method with log-rank test was used for analyzing patient survival.

Results: Major events, including EGFR, KRAS, and BRAF mutations and MET copy-number gain, were found in 5.6%, 16.7%, 1.9%, and 18.5% in LCLC, respectively. No ALK or ROS1 translocation was detected. PDL1 expression in tumor cells and in tumor-infiltrating lymphocytes was observed in 24 (44.4%) and 16 (29.6%) patients. Kaplan–Meier analysis showed that patients with a KRAS mutation had ower 5-year overall survival than those with wild-type KRAS (25.4% vs 47.8%, P=0.028) and that patients with negative PDL1 stained in tumor cells but positive for tumor-infiltrating lymphocytes had significantly favorable overall survival compared to those with solitary and positive PDL1 stained in tumor cells (62.5% vs 20.6%, P=0.044).

Conclusion:KRAS mutations and PDL1 expression can predict patient survival and be potential target options in LCLC.

Recent advances in the molecular landscape of lung neuroendocrine tumors

INTRODUCTION

Neuroendocrine tumors of the lung (Lung-NETs) make up a heterogenous family of neoplasms showing neuroendocrine differentiation and encompass carcinoids and neuroendocrine carcinomas. On molecular grounds, they considered two completely distinct and separate tumor groups with no overlap of molecular alterations nor common developmental mechanisms. Areas covered: Two perspectives were evaluated based on an extensive review and rethinking of literature: (1) the current classification as an instrument to obtaining clinical and molecular insights into the context of Lung-NETs; and (2) an alternative and innovative interpretation of these tumors, proposing a tripartite separation into early aggressive primary high-grade neuroendocrine tumors (HGNET), differentiating or secondary HGNET, and indolent NET. Expert opinion: We herein provide an alternative outlook on Lung-NETs, which is a paradigm shift to current pathogenesis models and expands the understanding of these tumors.

A combined gene expression tool for parallel histological prediction and gene fusion detection in non-small cell lung cancer

Accurate histological classification and identification of fusion genes represent two cornerstones of clinical diagnostics in non-small cell lung cancer (NSCLC). Here, we present a NanoString gene expression platform and a novel platform-independent, single sample predictor (SSP) of NSCLC histology for combined, simultaneous, histological classification and fusion gene detection in minimal formalin fixed paraffin embedded (FFPE) tissue. The SSP was developed in 68 NSCLC tumors of adenocarcinoma (AC), squamous cell carcinoma (SqCC) and large-cell neuroendocrine carcinoma (LCNEC) histology, based on NanoString expression of 11 (CHGA, SYP, CD56, SFTPG, NAPSA, TTF-1, TP73L, KRT6A, KRT5, KRT40, KRT16) relevant genes for IHC-based NSCLC histology classification. The SSP was combined with a gene fusion detection module (analyzing ALK, RET, ROS1, MET, NRG1, and NTRK1) into a multicomponent NanoString assay. The histological SSP was validated in six cohorts varying in size (n = 11–199), tissue origin (early or advanced disease), histological composition (including undifferentiated cancer), and gene expression platform. Fusion gene detection revealed five EML4-ALK fusions, four KIF5B-RET fusions, two CD74-NRG1 fusion and three MET exon 14 skipping events among 131 tested cases. The histological SSP was successfully trained and tested in the development cohort (mean AUC = 0.96 in iterated test sets). The SSP proved successful in predicting histology of NSCLC tumors of well-defined subgroups and difficult undifferentiated morphology irrespective of gene expression data platform. Discrepancies between gene expression prediction and histologic diagnosis included cases with mixed histologies, true large cell carcinomas, or poorly differentiated adenocarcinomas with mucin expression. In summary, we present a proof-of-concept multicomponent assay for parallel histological classification and multiplexed fusion gene detection in archival tissue, including a novel platform-independent histological SSP classifier. The assay and SSP could serve as a promising complement in the routine evaluation of diagnostic lung cancer biopsies.

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

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.

New Insights into the Molecular Characteristics of Pulmonary Carcinoids and Large Cell Neuroendocrine Carcinomas, and the Impact on Their Clinical Management

Carcinoids and large cell neuroendocrine carcinomas (LCNECs) are rare neuroendocrine lung tumors. Here we provide an overview of the most updated data on the molecular characteristics of these diseases. Recent genomic studies showed that carcinoids generally contain a low mutational burden and few recurrently mutated genes. Most of the reported mutations occur in chromatin-remodeling genes (e.g., menin 1 gene [MEN1]), and few affect genes of the phosphoinositide 3-kinase (PI3K)-AKT-mechanistic target of rapamycin gene pathway. Aggressive disease has been related to chromothripsis, DNA-repair gene mutations, loss of orthopedia homeobox/CD44, and upregulation of ret proto-oncogene gene (RET) gene expression. In the case of LCNECs, which present with a high mutation burden, two major molecular subtypes have been identified: one with biallelic inactivation of tumor protein p53 gene (TP53) and retinoblastoma gene (RB1), a hallmark of SCLC; and the other one with biallelic inactivation of TP53 and serine/threonine kinase 11 gene (STK11)/kelch like ECH associated protein 1 gene (KEAP1), genes that are frequently mutated in NSCLC. These data, together with the identification of common mutations in the different components of combined LCNEC tumors, provide further evidence of the close molecular relation of LCNEC with other lung tumor types. In terms of therapeutic options, future studies should explore the association between mechanistic target of rapamycin pathway mutations and response to mechanistic target of rapamycin inhibitors in carcinoids. For LCNEC, preliminary data suggest that the two molecular subtypes might have a predictive value for chemotherapy response, but this observation needs to be validated in randomized prospective clinical trials. Finally, delta like Notch canonical ligand 3 inhibitors and immunotherapy may provide alternative options for patient-tailored therapy in LCNEC.

Integrative genomic profiling of large-cell neuroendocrine carcinomas reveals distinct subtypes of high-grade neuroendocrine lung tumors

Pulmonary large-cell neuroendocrine carcinomas (LCNECs) have similarities with other lung cancers, but their precise relationship has remained unclear. Here we perform a comprehensive genomic (n = 60) and transcriptomic (n = 69) analysis of 75 LCNECs and identify two molecular subgroups: "type I LCNECs" with bi-allelic TP53 and STK11/KEAP1 alterations (37%), and "type II LCNECs" enriched for bi-allelic inactivation of TP53 and RB1 (42%). Despite sharing genomic alterations with adenocarcinomas and squamous cell carcinomas, no transcriptional relationship was found; instead LCNECs form distinct transcriptional subgroups with closest similarity to SCLC. While type I LCNECs and SCLCs exhibit a neuroendocrine profile with ASCL1high/DLL3high/NOTCHlow, type II LCNECs bear TP53 and RB1 alterations and differ from most SCLC tumors with reduced neuroendocrine markers, a pattern of ASCL1low/DLL3low/NOTCHhigh, and an upregulation of immune-related pathways. In conclusion, LCNECs comprise two molecularly defined subgroups, and distinguishing them from SCLC may allow stratified targeted treatment of high-grade neuroendocrine lung tumors.

Pulmonary large cell neuroendocrine carcinoma with adenocarcinoma-like features: napsin A expression and genomic alterations

Pulmonary large cell neuroendocrine carcinoma (LCNEC) is a highly aggressive malignancy, which was recently found to comprise three major genomic subsets: small cell carcinoma-like, non-small cell carcinoma (predominantly adenocarcinoma)-like, and carcinoid-like. To further characterize adenocarcinoma-like subset, here we analyzed the expression of exocrine marker napsin A, along with TTF-1, in a large series of LCNECs (n=112), and performed detailed clinicopathologic and genomic analysis of napsin A-positive cases. For comparison, we analyzed napsin A expression in other lung neuroendocrine neoplasms (177 carcinoids, 37 small cell carcinomas) and 60 lung adenocarcinomas. We found that napsin A was expressed in 15% of LCNEC (17/112), whereas all carcinoids and small cell carcinomas were consistently negative. Napsin A reactivity in LCNEC was focal in 12/17 cases, and weak or moderate in intensity in all cases, which was significantly lower in the extent and intensity than seen in adenocarcinomas (P<0.0001). The combination of TTF-1-diffuse/napsin A-negative or focal was typical of LCNEC but was rare in adenocarcinoma, and could thus serve as a helpful diagnostic clue. The diagnosis of napsin A-positive LCNECs was confirmed by classic morphology, diffuse labeling for at least one neuroendocrine marker, most consistently synaptophysin, and the lack of distinct adenocarcinoma component. Genomic analysis of 14 napsin A-positive LCNECs revealed the presence of mutations typical of lung adenocarcinoma (KRAS and/or STK11) in 11 cases. In conclusion, LCNECs are unique among lung neuroendocrine neoplasms in that some of these tumors exhibit low-level expression of exocrine marker napsin A, and harbor genomic alterations typical of adenocarcinoma. Despite the apparent close biological relationship, designation of adeno-like LCNEC as a separate entity from adenocarcinoma is supported by their distinctive morphology, typically diffuse expression of neuroendocrine marker(s) and aggressive behavior. Further studies are warranted to assess the clinical utility and optimal method of identifying adenocarcinoma-like and other subsets of LCNEC in routine practice.

Molecular Subtypes of Pulmonary Large-cell Neuroendocrine Carcinoma Predict Chemotherapy Treatment Outcome

Purpose: Previous genomic studies have identified two mutually exclusive molecular subtypes of large-cell neuroendocrine carcinoma (LCNEC): the RB1 mutated (mostly comutated with TP53) and the RB1 wild-type groups. We assessed whether these subtypes have a predictive value on chemotherapy outcome.Experimental Design: Clinical data and tumor specimens were retrospectively obtained from the Netherlands Cancer Registry and Pathology Registry. Panel-consensus pathology revision confirmed the diagnosis of LCNEC in 148 of 232 cases. Next-generation sequencing (NGS) for TP53, RB1, STK11, and KEAP1 genes, as well as IHC for RB1 and P16 was performed on 79 and 109 cases, respectively, and correlated with overall survival (OS) and progression-free survival (PFS), stratifying for non-small cell lung cancer type chemotherapy including platinum + gemcitabine or taxanes (NSCLC-GEM/TAX) and platinum-etoposide (SCLC-PE).Results:RB1 mutation and protein loss were detected in 47% (n = 37) and 72% (n = 78) of the cases, respectively. Patients with RB1 wild-type LCNEC treated with NSCLC-GEM/TAX had a significantly longer OS [9.6; 95% confidence interval (CI), 7.7-11.6 months] than those treated with SCLC-PE [5.8 (5.5-6.1); P = 0.026]. Similar results were obtained for patients expressing RB1 in their tumors (P = 0.001). RB1 staining or P16 loss showed similar results. The same outcome for chemotherapy treatment was observed in LCNEC tumors harboring an RB1 mutation or lost RB1 protein.Conclusions: Patients with LCNEC tumors that carry a wild-type RB1 gene or express the RB1 protein do better with NSCLC-GEM/TAX treatment than with SCLC-PE chemotherapy. However, no difference was observed for RB1 mutated or with lost protein expression. Clin Cancer Res; 24(1); 33-42. ©2017 AACR.

Clinicopathological and genetic characteristics of pulmonary large cell carcinoma under 2015 WHO classification: a pilot study

Pulmonary large cell carcinoma (LCC) was re-defined under the 2015 WHO classification criteria. However, the clinicopathological features and genetic mutation statuses of Chinese LCC patients based on the new classification have rarely been investigated. Twenty-four Chinese surgically resected LCC patients previously diagnosed under the 2004 WHO criteria were re-classified under the 2015 WHO criteria. Genetic analysis was performed using next-generation sequencing of 46 cancer-related genes. The correlation of clinicopathological and genetic data was further analyzed. Eight patients were re-defined as LCCs, and 16 patients were defined as non-LCCs under the refined criteria. All LCC patients were male, and 7 patients were smokers. No significant differences in age, gender, smoking status, primary site, TNM staging and overall survival were observed between the LCC and non-LCC patients under the refined criteria. Four of the 8 LCC patients presented TP53 mutations, and no somatic mutations were detected in the other 4 LCCs under the refined criteria. For the 16 non-LCCs, not only TP53 and KRAS but also EGFR, KIT, PIK3CA, PTEN, IDH1, APC, ATM and BRAF mutations were also observed. In addition, LCCs without TP53 mutations did not present any gene mutations under the 2004 or 2015 WHO criteria. Importantly, the patients with TP53 mutation exhibited a trend with a worse survival outcome at the time of follow-up. The new WHO diagnosis criteria have superior performance in precise molecular classification for LCC patients.

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.

Neuroendocrine carcinoma of the lung expressing anaplastic lymphoma kinase on high-sensitivity immunohistochemistry: A case report

It has been reported that anaplastic lymphoma kinase (ALK) protein is expressed in a proportion of non-small-cell carcinomas (mainly adenocarcinomas). By contrast, high-sensitivity immunohistochemistry (IHC) rarely detects ALK protein expression in neuroendocrine carcinomas (NECs) of the lung, which include small-cell carcinomas and large-cell neuroendocrine carcinomas (LCNECs). We herein present a case of NEC that was identified as ALK-positive via high-sensitivity IHC. A 51-year-old man was diagnosed with small-cell carcinoma in the upper lobe of the right lung. Although high-sensitivity IHC revealed that the tumor weakly expressed the ALK protein, no fusion gene with ALK was found using fluorescence in situ hybridization (FISH). Standard chemotherapy was administered to the patient. Six months after the first visit to the hospital for the tumor, another tumor was identified in the upper lobe of the left lung. The tumor was resected and diagnosed as NEC displaying LCNEC-like characteristics. This NEC also moderately expressed ALK protein by high-sensitivity IHC, without exhibiting fusion genes with ALK on FISH. These data suggest that the presence of ALK fusion genes should be confirmed by FISH or reverse transcription polymerase chain reaction, even if high-sensitivity IHC for ALK protein is positive in lung cancer.

Clinical framework for next generation sequencing based analysis of treatment predictive mutations and multiplexed gene fusion detection in non-small cell lung cancer

Precision medicine requires accurate multi-gene clinical diagnostics. We describe the implementation of an Illumina TruSight Tumor (TST) clinical NGS diagnostic framework and parallel validation of a NanoString RNA-based ALK, RET, and ROS1 gene fusion assay for combined analysis of treatment predictive alterations in non-small cell lung cancer (NSCLC) in a regional healthcare region of Sweden (Scandinavia). The TST panel was clinically validated in 81 tumors (99% hotspot mutation concordance), after which 533 consecutive NSCLCs were collected during one-year of routine clinical analysis in the healthcare region (~90% advanced stage patients). The NanoString assay was evaluated in 169 of 533 cases. In the 533-sample cohort 79% had 1-2 variants, 12% >2 variants and 9% no detected variants. Ten gene fusions (five ALK, three RET, two ROS1) were detected in 135 successfully analyzed cases (80% analysis success rate). No ALK or ROS1 FISH fusion positive case was missed by the NanoString assay. Stratification of the 533-sample cohort based on actionable alterations in 11 oncogenes revealed that 66% of adenocarcinomas, 13% of squamous carcinoma (SqCC) and 56% of NSCLC not otherwise specified harbored ≥1 alteration. In adenocarcinoma, 10.6% of patients (50.3% if including KRAS) could potentially be eligible for emerging therapeutics, in addition to the 15.3% of patients eligible for standard EGFR or ALK inhibitors. For squamous carcinoma corresponding proportions were 4.4% (11.1% with KRAS) vs 2.2%. In conclusion, multiplexed NGS and gene fusion analyses are feasible in NSCLC for clinical diagnostics, identifying notable proportions of patients potentially eligible for emerging molecular therapeutics.

Gene Expression Profiling of Large Cell Lung Cancer Links Transcriptional Phenotypes to the New Histological WHO 2015 Classification

INTRODUCTION

Large cell lung cancer (LCLC) and large cell neuroendocrine carcinoma (LCNEC) constitute a small proportion of NSCLC. The WHO 2015 classification guidelines changed the definition of the debated histological subtype LCLC to be based on immunomarkers for adenocarcinoma and squamous cancer. We sought to determine whether these new guidelines also translate into the transcriptional landscape of lung cancer, and LCLC specifically.

METHODS

Gene expression profiling was performed by using Illumina V4 HT12 microarrays (Illumina, San Diego, CA) on samples from 159 cases (comprising all histological subtypes, including 10 classified as LCLC WHO 2015 and 14 classified as LCNEC according to the WHO 2015 guidelines), with complimentary mutational and immunohistochemical data. Derived transcriptional phenotypes were validated in 199 independent tumors, including six WHO 2015 LCLCs and five LCNECs.

RESULTS

Unsupervised analysis of gene expression data identified a phenotype comprising 90% of WHO 2015 LCLC tumors, with characteristics of poorly differentiated proliferative cancer, a 90% tumor protein p53 gene (TP53) mutation rate, and lack of well-known NSCLC oncogene driver alterations. Validation in independent data confirmed aggregation of WHO 2015 LCLCs in the specific phenotype. For LCNEC tumors, the unsupervised gene expression analysis suggested two different transcriptional patterns corresponding to a proposed genetic division of LCNEC tumors into SCLC-like and NSCLC-like cancer on the basis of TP53 and retinoblastoma 1 gene (RB1) alteration patterns.

CONCLUSIONS

Refined classification of LCLC has implications for diagnosis, prognostics, and therapy decisions. Our molecular analyses support the WHO 2015 classification of LCLC and LCNEC tumors, which herein follow different tumorigenic paths and can accordingly be stratified into different transcriptional subgroups, thus linking diagnostic immunohistochemical staining-driven classification with the transcriptional landscape of lung cancer.

Endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA)-from morphology to molecular testing

In recent years, endobronchial ultrasound-guided TBNA (EBUS-TBNA) has emerged as an innovative technique for diagnosis and staging of lung cancer and has been successfully introduced into daily clinical practice with several advantages including minimally invasive approach, safe, cost-effective, real time image guidance, broad sampling capability, and rapid on-site evaluation (ROSE). Both cytological and histological approach could be useful to have material for diagnosis, immunohistochemical and molecular analyses which may be very important for targeted therapy with successful rate ranging from 89% to 98%. The utility of ROSE during EBUS-TBNA has been matter of debate. Indeed, although some evidence concluded that ROSE does not increase the diagnostic efficacy of EBUS-TBNA, other demonstrated that it improves the diagnostic yield of the procedure up to 30%, allows to avoid repetition of additional diagnostic procedures and reduces risk of complications. Furthermore the sample preparation by cytopathologist is optimized with the aid of direct macroscopic inspection, optimal smearing techniques, and triage of the sample permitting to obtain adequate tissue for diagnosis, ancillary techniques and molecular testing, when needed. Some pathological issues on EBUS-TBNA are reviewed and discussed with particular focus on ROSE and molecular testing.

Ki-67 labeling index of neuroendocrine tumors of the lung has a high level of correspondence between biopsy samples and surgical specimens when strict counting guidelines are applied

Optimal histopathological analysis of biopsies from metastases of neuroendocrine tumor (NET) of the lung requires more than morphology only. Additional parameters such as Ki-67 labeling index are required for adequate diagnosis, but few studies have compared reproducibility of different counting protocols and modalities of reporting on biopsies of lung NET. We compared the results of four different manual counting techniques to establish Ki-67 LI. On 47 paired biopsies and surgical specimens from 22 typical carcinoids (TCs), 14 atypical carcinoids (ACs), six large cell neuroendocrine carcinomas (LCNECs), and five small cell carcinomas (SCCs) immunohistochemical staining of Ki-67 antigen was performed. We counted, in regions of highest nuclear staining (HSR), a full ×40-high-power field (diameter = 0.55 mm), 500 or 2000 cells, or 2 mm² surface area, including the HSR or the entire biopsy fragment(s). Mitoses and necrosis were evaluated in an area of 2 mm² or the entire biopsy fragment(s). Between the four counting methods, no differences in Ki-67 LI were observed. However, a Ki-67 LI higher than 5% was found in only four cases when in an HSR, 500 cells were counted (18%), five (23%) when in an HSR 2000 cells were counted, four (18%) when 2 mm² were counted, and one (5%) TC case when the entire biopsy was counted. A 20% cutoff distinguished TC and AC from LCNEC and SCC with 100% specificity and sensitivity, while mitoses and necrosis failed to a large extent. Ki-67 LI in biopsy samples was concordant with that in resection specimens when 2000 cells, 2 mm², or the entire biopsy fragment(s) were counted. Our results are important for clinical management of patients with metastases of a lung NET.

Testing for ROS1 in non-small cell lung cancer: a review with recommendations

Rearrangements of the ROS1 gene occur in 1-2 % of non-small cell lung cancers (NSCLCs). Crizotinib, a highly effective inhibitor of ROS1 kinase activity, is now FDA-approved for the treatment of patients with advanced ROS1-positive NSCLC. Consequently, focus on ROS1 testing is growing. Most laboratories currently rely on fluorescence in situ hybridisation (FISH) assays using a dual-colour break-apart probe to detect ROS1 rearrangements. Given the rarity of these rearrangements in NSCLC, detection of elevated ROS1 protein levels by immunohistochemistry may provide cost-effective screening prior to confirmatory FISH testing. Non-in situ testing approaches also hold potential as stand-alone methods or complementary tests, including multiplex real-time PCR assays and next-generation sequencing (NGS) platforms which include commercial test kits covering a range of fusion genes. In order to ensure high-quality biomarker testing, appropriate tissue handling, adequate control materials and participation in external quality assessment programmes are essential, irrespective of the testing technique employed. ROS1 testing is often only considered after negative tests for EGFR mutation and ALK gene rearrangement, based on the assumption that these oncogenic driver events tend to be exclusive. However, as the use of ROS1 inhibitors becomes routine, accurate and timely detection of ROS1 gene rearrangements will be critical for the optimal treatment of patients with NSCLC. As NGS techniques are introduced into routine diagnostic practice, ROS1 fusion gene testing will be provided as part of the initial testing package.

USP7 inhibitors, downregulating CCDC6, sensitize lung neuroendocrine cancer cells to PARP-inhibitor drugs

OBJECTIVES

CCDC6 gene product is a tumor-suppressor pro-apoptotic protein, substrate of ATM, involved in DNA damage response and repair. Altered levels of CCDC6 expression are dependent on post-translational modifications, being the de-ubiquitinating enzyme USP7 responsible of the fine tuning of the CCDC6 stability. Thus, our aim was to investigate CCDC6 and USP7 expression levels in Lung-Neuroendocrine Tumors (L-NETs) to verify if they correlate and may be exploited as novel predictive therapeutic markers.

MATERIALS AND METHODS

Tumor tissues from 29 L-NET patients were investigated on tissue microarrays. CCDC6 levels were scored and correlated with immunoreactivity for USP7. Next generation sequencing (NGS) of a homogenous group of Large Cell Neuroendocrine Carcinoma (LCNEC) (N=8) was performed by Ion AmpliSeq NGS platform and the Ion AmpliSeq Cancer Hotspot Panel v2. The inhibition of USP7, using P5091, was assayed in vitro to accelerate CCDC6 turnover in order to sensitize the neuroendocrine cancer cells to PARP-inhibitors, alone or in association with cisplatinum.

RESULTS

The immunostaining of 29 primary L-NETs showed that the intensity of CCDC6 staining correlated with the levels of USP7 expression (p≤0.05). The NGS analysis of 8 LCNEC revealed mutations in the hot spot regions of the p53 gene (in 6 out of 8). Moreover, gene polymorphisms were identified in the druggable STK11, MET and ALK genes. High intensity of p53 immunostaining was reported in the 6 tissues carrying the TP53 mutations. The inhibition of USP7 by P5091 accelerated the degradation of CCDC6 versus control in cycloheximide treated L-NET cells in vitro and sensitized the cells to PARP-inhibitors alone and in combination with cisplatinum.

CONCLUSION

Our data suggest that CCDC6 and USP7 have a predictive value for the clinical usage of USP7 inhibitors in combination with the PARP-inhibitors in L-NET in addition to standard therapy.

Next-Generation Sequencing of Pulmonary Large Cell Neuroendocrine Carcinoma Reveals Small Cell Carcinoma-like and Non-Small Cell Carcinoma-like Subsets

PURPOSE

Pulmonary large cell neuroendocrine carcinoma (LCNEC) is a highly aggressive neoplasm, whose biologic relationship to small cell lung carcinoma (SCLC) versus non-SCLC (NSCLC) remains unclear, contributing to uncertainty regarding optimal clinical management. To clarify these relationships, we analyzed genomic alterations in LCNEC compared with other major lung carcinoma types.

EXPERIMENTAL DESIGN

LCNEC (n = 45) tumor/normal pairs underwent targeted next-generation sequencing of 241 cancer genes by Memorial Sloan Kettering-Integrated Mutation Profiling of Actionable Cancer Targets (MSK-IMPACT) platform and comprehensive histologic, immunohistochemical, and clinical analysis. Genomic data were compared with MSK-IMPACT analysis of other lung carcinoma histologies (n = 242).

RESULTS

Commonly altered genes in LCNEC included TP53 (78%), RB1 (38%), STK11 (33%), KEAP1 (31%), and KRAS (22%). Genomic profiles segregated LCNEC into 2 major and 1 minor subsets: SCLC-like (n = 18), characterized by TP53+RB1 co-mutation/loss and other SCLC-type alterations, including MYCL amplification; NSCLC-like (n = 25), characterized by the lack of coaltered TP53+RB1 and nearly universal occurrence of NSCLC-type mutations (STK11, KRAS, and KEAP1); and carcinoid-like (n = 2), characterized by MEN1 mutations and low mutation burden. SCLC-like and NSCLC-like subsets revealed several clinicopathologic differences, including higher proliferative activity in SCLC-like tumors (P < 0.0001) and exclusive adenocarcinoma-type differentiation marker expression in NSCLC-like tumors (P = 0.005). While exhibiting predominant similarity with lung adenocarcinoma, NSCLC-like LCNEC harbored several distinctive genomic alterations, including more frequent mutations in NOTCH family genes (28%), implicated as key regulators of neuroendocrine differentiation.

CONCLUSIONS

LCNEC is a biologically heterogeneous group of tumors, comprising distinct subsets with genomic signatures of SCLC, NSCLC (predominantly adenocarcinoma), and rarely, highly proliferative carcinoids. Recognition of these subsets may inform the classification and management of LCNEC patients. Clin Cancer Res; 22(14); 3618-29. ©2016 AACR.