Distinct profile of driver mutations and clinical features in immunomarker-defined subsets of pulmonary large-cell carcinoma

Large cell carcinoma of the lung: LDCT features and survival in screen-detected cases

PURPOSE

To investigate the early radiological features and survival of Large Cell Carcinoma (LCC) cases diagnosed in low-dose computed tomography (LDCT) screening trials.

METHODS

Two radiologists jointly reviewed the radiological features of screen-detected LCCs observed in NLST, ITALUNG, and LUSI trials between 2002 and 2016, comprising a total of 29,744 subjects who underwent 3-5 annual screening LDCT examinations. Survival or causes of death were established according to the mortality registries extending more than 12 years since randomization.

RESULTS

LCC was diagnosed in 30 (4 %) of 750 subjects with screen-detected lung cancer (LC), including 15 prevalent and 15 incident cases. Three additional LCCs occurred as interval cancers during the screening period. LDCT images were available for 29 cases of screen-detected LCCs, and 28 showed a single, peripheral, and well-defined solid nodule or mass with regularly smooth (39 %), lobulated (43 %), or spiculated (18 %) margins. One case presented as hilar mass. In 9 incident LCCs, smaller solid nodules were identified in prior LDCT examinations, allowing us to calculate a mean Volume Doubling Time (VDT) of 98.7 ± 47.8 days. The overall five-year survival rate was 50 %, with a significant (p = 0.0001) difference between stages I-II (75 % alive) and stages III-IV (10 % alive).

CONCLUSIONS

LCC is a fast-growing neoplasm that can escape detection by annual LDCT screening. LCC typically presents as a single solid peripheral nodule or mass, often with lobulated margins, and exhibits a short VDT. The 5-year survival reflects the stage at diagnosis.

SMARCA4 deficiency and mutations are frequent in large cell lung carcinoma and are prognostically significant

SMARCA4 mutation has emerged as a marker of poor prognosis in lung cancer and has potential predictive value in cancer treatment, but recommendations for which patients require its investigation are lacking. We comprehensively studied SMARCA4 alterations and the clinicopathological significance in a large cohort of immunohistochemically-subtyped non-small cell lung cancer (NSCLC). A total of 1416 patients was studied for the presence of SMARCA4 deficiency by immunohistochemistry (IHC). Thereafter, comprehensive sequencing of tumours was performed for 397 of these patients to study the mutational spectrum of SWI/SNF and SMARCA4 aberrations. IHC evidence of SMARCA4 deficiency was found in 2.9% of NSCLC. Of the sequenced tumours, 38.3% showed aberration in SWI/SNF complex, and 9.3% had SMARCA4 mutations. Strikingly, SMARCA4 aberrations were much more prevalent in large cell carcinoma (LCC) than other histological tumour subtypes. SMARCA4-deficient and SMARCA4-mutated tumours accounted for 40.5% and 51.4% of all LCC, respectively. Multivariable analyses confirmed SMARCA4 mutation was an independent prognostic factor in lung cancer. The immunophenotype of a subset of these tumours frequently showed TTF1 negativity and HepPAR1 positivity. SMARCA4 mutation or its deficiency was associated with positive smoking history and poor prognosis. It also demonstrated mutual exclusion with EGFR mutation. Taken together, the high incidence of SMARCA4 aberrations in LCC may indicate its diagnostic and prognostic value. Our study established the necessity of SMARCA4 IHC in the identification of SMARCA4-aberrant tumours, and this may be of particular importance in LCC and tumours without known driver events.

Utility of Immunohistochemistry in the Diagnosis of Pleuropulmonary and Mediastinal Cancers: A Review and Update

CONTEXT.—

Immunohistochemistry has become a valuable ancillary tool for the accurate classification of pleuropulmonary and mediastinal neoplasms necessary for therapeutic decisions and predicting prognostic outcome. Diagnostic accuracy has significantly improved because of the continuous discoveries of tumor-associated biomarkers and the development of effective immunohistochemical panels.

OBJECTIVE.—

To increase the accuracy of diagnosis and classify pleuropulmonary neoplasms through immunohistochemistry.

DATA SOURCES.—

Literature review and the author's research data and personal practice experience.

CONCLUSIONS.—

This review article highlights that appropriately selecting immunohistochemical panels enables pathologists to effectively diagnose most primary pleuropulmonary neoplasms and differentiate primary lung tumors from a variety of metastatic tumors to the lung. Knowing the utilities and pitfalls of each tumor-associated biomarker is essential to avoid potential diagnostic errors.

LCMR1 Promotes Large-Cell Lung Cancer Proliferation and Metastasis by Downregulating HLA-Encoding Genes

Lung cancer is notorious for its high global morbidity and mortality. Here, we examined whether the LCMR1 gene, which we previously cloned from a human large-cell lung carcinoma cell line, contributes to the proliferation and metastasis of large-cell lung carcinoma. To this end, we performed pan-cancer and non-small cell lung cancer (NSCLC) cell line-based LCMR1 expression profiling. Results revealed that LCMR1 was expressed at high levels in most solid tumors, including NSCLC. LCMR1 expression was the highest in the 95D large cell lung cancer cell line. Functional studies using lentivirus-based knockdown revealed that LCMR1 was critical for the proliferation, migration, and invasion of cultured large cell lung cancer cells. Moreover, blocking this gene significantly reduced tumor growth in a 95D cell xenograft mouse model. A multiple sequence-based assay revealed a mechanism by which LCMR1 diminished the RNA Pol II occupancy at the promoter of human leukocyte antigen (HLA)-encoding genes to prevent their transcription. The HLA genes play vital roles in cancer-specific antigen presentation and anticancer immunity. A correlation assay using TCGA database identified a negative relationship between the expression levels of LCMR1 and HLA coding genes. Taken together, our findings demonstrate that LCMR1 is required for large cell lung cancer cell growth and invasion and suggest its potential as a valid target in clinical treatment.

Targeted therapy for rare lung cancers: Status, challenges, and prospects

Lung cancer causes the most cancer-related deaths worldwide. In recent years, molecular and immunohistochemical techniques have rapidly developed, further inaugurating an era of personalized medicine for lung cancer. The rare subset of lung cancers accounts for approximately 10%, each displaying distinct clinical characteristics. Treatments for rare lung cancers are mainly based on evidence from common counterparts, which may lead to unsolid clinical benefits considering intertumoral heterogeneity. The increasing knowledge of molecular profiling of rare lung cancers has made targeting genetic alterations and immune checkpoints a powerful strategy. Additionally, cellular therapy has emerged as a promising way to target tumor cells. In this review, we first discuss the current status of targeted therapy and preclinical models for rare lung cancers, as well as provide mutational profiles by integrating the results of existing cohorts. Finally, we point out the challenges and future directions for developing targeted agents for rare lung cancer.

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.

Expression Profiles of AQP3 and AQP4 in Lung Adenocarcinoma Samples Generated via Bronchoscopic Biopsies

Aquaporins (AQPs) are highly conserved channel proteins which are mainly responsible for the exchange of water and small molecules and have shown to play a pivotal role in the development and progression of cancer. Lung adenocarcinoma is the most common primary lung cancer seen in patients in Europe and the United States. However, in patients it is often not diagnosed until the advanced tumor stage is present. Previous studies provided strong evidence that some members of the AQP family could serve as clinical biomarkers for different diseases. Therefore, we aimed to investigate how AQP3 and AQP4 protein expression in lung adenocarcinoma (ADC) biopsy samples correlate with clinical and pathological parameters. The protein expression of AQP3 and AQP4 was analyzed based on immunohistochemical staining. AQP3 protein was observed in the cytoplasmic membrane of cancer tissue in 82% of lung samples. Significant differences in relative protein expression of AQP3 were noted between advanced age patients compared to younger counterparts (p = 0.017). A high expression of AQP3 was significant in cancer tissue when compared to the control group (p < 0.001), whereas a low AQP4 membrane expression was noted as significantly common in cancer tissue compared to non-neoplastic lung tissue (p < 0.001). Moreover, a low AQP4 membrane expression was positively correlated with a more advanced disease status, e.g., lymph node metastases (p = 0.046). Based on our findings, AQP3 and AQP4 could be used as biomarkers in ADC patients.

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.

Invasive Mucinous Adenocarcinomas With Spatially Separate Lung Lesions: Analysis of Clonal Relationship by Comparative Molecular Profiling

INTRODUCTION

Pulmonary invasive mucinous adenocarcinomas (IMAs) often present with spatially separate lung lesions. Clonal relationship between such lesions, particularly those involving contralateral lobes, is not well established. Here, we used comparative genomic profiling to address this question.

METHODS

Patients with genomic analysis performed on two IMAs located in different lung regions were identified. Molecular assays included DNA-based next-generation sequencing (NGS) for 410 to 468 genes (Memorial Sloan Kettering-Integrated Mutation Profiling of Actionable Cancer Targets), RNA-based NGS for 62 genes (Memorial Sloan Kettering-Fusion), or non-NGS assays.

RESULTS

Comparative genomic profiling was performed on two separate IMAs in 24 patients, of whom 19 had contralateral lesions. Tumors from all but one patient shared matching driver alterations, including KRAS (n = 19), NRG1 (n = 2), ERBB2 (n = 1) or BRAF (n = 1). In addition, in patients with paired tumors profiled by NGS (n = 12), shared driver alterations were accompanied by up to 4 (average 2.6) other identical mutations, further supporting the clonal relationship between the tumors. Only in a single patient separate IMAs harbored entirely nonoverlapping mutation profiles, supporting clonally unrelated, distinct primary tumors. Notably, in a subset of patients (n = 3), molecular testing confirmed a clonal relationship between the original resected IMAs and subsequent contralateral IMA presenting after an extremely long latency (8.1-11.7 y).

CONCLUSIONS

Comparative molecular profiling supports that nearly all separate pulmonary IMA lesions represent intrapulmonary spread arising from a single tumor and documents a subset with a remarkably protracted course of intrapulmonary progression. This study reinforces the unique biology and clinical behavior of IMAs while further highlighting the value of genomic testing for clarifying the clonal relationship between multiple lung carcinomas.

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.

Deep learning classification of lung cancer histology using CT images

Tumor histology is an important predictor of therapeutic response and outcomes in lung cancer. Tissue sampling for pathologist review is the most reliable method for histology classification, however, recent advances in deep learning for medical image analysis allude to the utility of radiologic data in further describing disease characteristics and for risk stratification. In this study, we propose a radiomics approach to predicting non-small cell lung cancer (NSCLC) tumor histology from non-invasive standard-of-care computed tomography (CT) data. We trained and validated convolutional neural networks (CNNs) on a dataset comprising 311 early-stage NSCLC patients receiving surgical treatment at Massachusetts General Hospital (MGH), with a focus on the two most common histological types: adenocarcinoma (ADC) and Squamous Cell Carcinoma (SCC). The CNNs were able to predict tumor histology with an AUC of 0.71(p = 0.018). We also found that using machine learning classifiers such as k-nearest neighbors (kNN) and support vector machine (SVM) on CNN-derived quantitative radiomics features yielded comparable discriminative performance, with AUC of up to 0.71 (p = 0.017). Our best performing CNN functioned as a robust probabilistic classifier in heterogeneous test sets, with qualitatively interpretable visual explanations to its predictions. Deep learning based radiomics can identify histological phenotypes in lung cancer. It has the potential to augment existing approaches and serve as a corrective aid for diagnosticians.

Molecular Pathology of Primary Non-small Cell Lung Cancer

Lung carcinoma is one of the most common human cancers and is estimated to have an incidence of approximately 2 million new cases per year worldwide with a 20% mortality rate. Lung cancer represents one of the leading causes of cancer related death in the world. Of all cancer types to affect the pulmonary system, non-small cell lung carcinoma comprises approximately 80-85% of all tumors. In the past few decades cytogenetic and advanced molecular techniques have helped define the genomic landscape of lung cancer, and in the process, revolutionized the clinical management and treatment of patients with advanced non-small cell lung cancer. The discovery of specific, recurrent genetic abnormalities has led to the development of targeted therapies that have extended the life expectancy of patients who develop carcinoma of the lungs. Patients are now routinely treated with targeted therapies based on identifiable molecular alterations or other predictive biomarkers which has led to a revolution in the field of pulmonary pathology and oncology. Numerous different testing modalities, with various strengths and limitations now exist which complicate diagnostic algorithms, however recently emerging consensus guidelines and recommendations have begun to standardize the way to approach diagnostic testing of lung carcinoma. Herein we provide an overview of the molecular genetic landscape of non-small cell lung carcinoma, with attention to those clinically relevant alterations which drive management, as well as review current recommendations for molecular testing.

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.

Clinical characteristics and prognosis of pulmonary large cell carcinoma: A population-based retrospective study using SEER data

BACKGROUND

Pulmonary large cell carcinoma (LCC) is an infrequent neoplasm with a poor prognosis. This study explored the clinical characteristics and survival prognostic factors of LCC patients.

METHODS

Patient data were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Chi-square tests or rank-sum tests were used to compare differences in clinical characteristics. Log-rank tests, univariate, and multivariate analyses were performed to investigate the independent factors of survival. Analyses of stage I-IV patients were performed to further explore the optimal treatment.

RESULTS

In total, 3197 LCC patients were included in this analysis. Compared with other non-small cell lung cancers (NSCLCs), there was a worse overall survival (OS) from LCC. LCC was more common in males, over age 60 and in the upper lobe. A total of 73.6% of patients were stage III/IV. The median OS of stage I-IV patients was 42 months, 22 months, 11 months, and three months, respectively. The elderly, males, later stage, and main bronchus location, or overlapping lesions were risk factors for survival prognosis. In stage I-III patients, treatment including surgery could significantly reduce the risk of death by 60% at least compared with no therapy. Surgery was still beneficial for stage IV patients, and the hazard ratio (HR) compared with no therapy was 0.462 (P = 0.001).

CONCLUSIONS

Our study concluded that LCC has unique clinical features, and that age, sex, primary site, stage, and treatment are significantly related to OS. Surgery based comprehensive treatments are effective for LCC.

KEY POINTS

Significant findings of the study In stage IV patients, chemotherapy or radiotherapy combined with surgery could further improve survival. When surgical resection involved more than one lobe, it may be beneficial for survival prognosis. What this study adds LCC patients were principally male and over age 60, with later stages and poor survival prognosis. Age, sex, stage, primary site and therapy are closely related to survival.

Lung Cancer Pathology: Current Concepts

Lung cancer can be diagnosed based on histologic biopsy or cytologic specimens. The 2015 World Health Organization Classification of Lung Tumors addressed the diagnosis of lung cancer in resection specimens and in small biopsies and cytology specimens. For these small specimens, diagnostic terms and criteria are recommended. Targetable mutations such as EGFR and ALK rearrangements emphasize the importance of managing these small specimens for molecular testing.

A qualitative transcriptional signature for the histological reclassification of lung squamous cell carcinomas and adenocarcinomas

Background

Targeted therapy for non-small cell lung cancer is histology dependent. However, histological classification by routine pathological assessment with hematoxylin-eosin staining and immunostaining for poorly differentiated tumors, particularly those from small biopsies, is still challenging. Additionally, the effectiveness of immunomarkers is limited by technical inconsistencies of immunostaining and lack of standardization for staining interpretation.

Results

Using gene expression profiles of pathologically-determined lung adenocarcinomas and squamous cell carcinomas, denoted as pADC and pSCC respectively, we developed a qualitative transcriptional signature, based on the within-sample relative gene expression orderings (REOs) of gene pairs, to distinguish ADC from SCC. The signature consists of two genes, KRT5 and AGR2, which has the stable REO pattern of KRT5 > AGR2 in pSCC and KRT5 < AGR2 in pADC. In the two test datasets with relative unambiguous NSCLC types, the apparent accuracy of the signature were 94.44 and 98.41%, respectively. In the other integrated dataset for frozen tissues, the signature reclassified 4.22% of the 805 pADC patients as SCC and 12% of the 125 pSCC patients as ADC. Similar results were observed in the clinical challenging cases, including FFPE specimens, mixed tumors, small biopsy specimens and poorly differentiated specimens. The survival analyses showed that the pADC patients reclassified as SCC had significantly shorter overall survival than the signature-confirmed pADC patients (log-rank p = 0.0123, HR = 1.89), consisting with the knowledge that SCC patients suffer poor prognoses than ADC patients. The proliferative activity, subtype-specific marker genes and consensus clustering analyses also supported the correctness of our signature.

Conclusions

The non-subjective qualitative REOs signature could effectively distinguish ADC from SCC, which would be an auxiliary test for the pathological assessment of the ambiguous cases.

SMARCA4-Deficient Thoracic Sarcomatoid Tumors Represent Primarily Smoking-Related Undifferentiated Carcinomas Rather Than Primary Thoracic Sarcomas

Introduction:

Highly aggressive thoracic neoplasms characterized by SMARCA4 (BRG1) deficiency and undifferentiated round cell or rhabdoid morphology have been recently described and proposed to represent thoracic sarcomas. However, it remains unclear whether such tumors may instead represent sarcomatoid carcinomas, and how their clinicopathologic characteristics compare with those of nonsarcomatoid SMARCA4-deficient non–small cell lung carcinomas (SD-NSCC).

Methods:

We identified 22 SMARCA4-deficient thoracic sarcomatoid tumors (SD-TSTs) with round cell and/or rhabdoid morphology and 45 SD-NSCCs, and comprehensively analyzed their clinicopathologic, immunohistochemical, and genomic characteristics using 341–468 gene next-generation sequencing and other molecular platforms.

Results:

The relationship of SD-TSTs with NSCC was supported by (1) the presence of NSCC components juxtaposed with sarcomatoid areas in five cases, (2) focal expression of NSCC lineage markers TTF1 or p40 in four additional cases, (3) smoking history in all except one patient (mean = 51 pack-years), accompanied by genomic smoking signature, and (4) high tumor mutation burden (mean = 14.2 mutations per megabase) and mutations characteristic of NSCC in a subset. Compared with SD-NSCCs, SD-TSTs exhibited considerably larger primary tumor size (p < 0.0001), worse survival (p = 0.004), and more frequent presentation at younger age (30–50 years) despite heavier smoking history. Distinctive pathologic features of SD-TSTs included consistent lack of adhesion molecule claudin-4, SMARCA2 (BRM) codeficiency, and frequent expression of stem cell markers.

Conclusions:

SD-TSTs represent primarily smoking-associated undifferentiated/de-differentiated carcinomas rather than primary thoracic sarcomas. Despite their histogenetic relationship with NSCC, these tumors have unique clinicopathologic characteristics, supporting their recognition as a distinct entity. Further studies are warranted to determine therapeutic approaches to this novel class of exceptionally aggressive thoracic tumors.

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.

Best Practices Recommendations for Diagnostic Immunohistochemistry in Lung Cancer

Since the 2015 WHO classification was introduced into clinical practice, immunohistochemistry (IHC) has figured prominently in lung cancer diagnosis. In addition to distinction of small cell versus non-small cell carcinoma, patients' treatment of choice is directly linked to histologic subtypes of non-small cell carcinoma, which pertains to IHC results, particularly for poorly differentiated tumors. The use of IHC has improved diagnostic accuracy in the classification of lung carcinoma, but the interpretation of IHC results remains challenging in some instances. Also, pathologists must be aware of many interpretation pitfalls, and the use of IHC should be efficient to spare the tissue for molecular testing. The International Association for the Study of Lung Cancer Pathology Committee received questions on practical application and interpretation of IHC in lung cancer diagnosis. After discussions in several International Association for the Study of Lung Cancer Pathology Committee meetings, the issues and caveats were summarized in terms of 11 key questions covering common and important diagnostic situations in a daily clinical practice with some relevant challenging queries. The questions cover topics such as the best IHC markers for distinguishing NSCLC subtypes, differences in thyroid transcription factor 1 clones, and the utility of IHC in diagnosing uncommon subtypes of lung cancer and distinguishing primary from metastatic tumors. This article provides answers and explanations for the key questions about the use of IHC in diagnosis of lung carcinoma, representing viewpoints of experts in thoracic pathology that should assist the community in the appropriate use of IHC in diagnostic pathology.

Nanotechnology in the diagnosis and treatment of lung cancer

Lung cancer is an umbrella term for a subset of heterogeneous diseases that are collectively responsible for the most cancer-related deaths worldwide. Despite the tremendous progress made in understanding lung tumour biology, advances in early diagnosis, multimodal therapy and deciphering molecular mechanisms of drug resistance, overall curative outcomes remain low, especially in metastatic disease. Nanotechnology, in particular nanoparticles (NPs), continue to progressively impact the way by which tumours are diagnosed and treated. The unique physicochemical properties of materials at the nanoscale grant access to a diverse molecular toolkit that can be manipulated for use in respiratory oncology. This realisation has resulted in several clinically approved NP formulations and many more in clinical trials. However, NPs are not a panacea and have yet to be utilised to maximal effect in lung cancer, and medicine in a wider context. This review serves to: describe the complexity of lung cancer, the current diagnostic and therapeutic environment, and highlight the recent advancements of nanotechnology based approaches in diagnosis and treatment of respiratory malignancies. Finally, a brief outlook on the future directions of nanomedicine is provided; presently the full potential of the field is yet to be realised. By gleaning lessons and integrating advancements from neighbouring disciplines, nanomedicine can be elevated to a position where the current barriers that stymie full clinical impact are lifted.

Classification and Pathology of Lung Cancer

Advancement in the understanding of lung tumor biology enables continued refinement of lung cancer classification, reflected in the recently introduced 2015 World Health Organization classification of lung cancer. In small biopsy or cytology specimens, special emphasis is placed on separating adenocarcinomas from the other lung cancers to effectively select tumors for targeted molecular testing. In resection specimens, adenocarcinomas are further classified based on architectural pattern to delineate tissue types of prognostic significance. Neuroendocrine tumors are divided into typical carcinoid, atypical carcinoid, small cell carcinoma, and large cell neuroendocrine carcinoma based on a combination of features, especially tumor cell proliferation rate.

Clinicopathological analysis of Large Cell Lung Carcinomas definitely diagnosed according to the New World Health Organization Criteria

OBJECTIVE

The definition of large cell lung carcinoma (LCC) has undergone an extensive modification in the World Health Organization (WHO) Classification (2015). Present study aimed to investigate the clinicopathological characteristics of patients diagnosed as LCC according to current WHO criteria.

METHODS

LCCs diagnosed based on the previous WHO classification were reevaluated, and 17 cases of LCC were finally identified at Peking Union Medical College Hospital and Beijing Chest Hospital between 2009 and 2015. The clinicopathologic features were examined and EGFR and KRAS mutations were tested. Survival of the patients was analyzed by Kaplan-Meier method.

RESULTS

The median age of the patients was 64 years (range: 40-78). Most patients were male (64.7%) and about half of the patients were at TNM stage III (47.1%). Morphologically, most cases (70.6%) were classic LCC. All patients were treated by lobectomy plus lymph node dissection, 2 with bi-lobectomy and 1 with complex lobectomy, and the other 2 patients were further treated by partial pericardiotomy. Ten patients received postoperative chemotherapy, while only 3 patients were treated with radiotherapy after surgery. Molecular analysis showed two cases of EGFR mutation (L858R) but without non-overlapping KRAS mutation. The 3-year overall survival rate was 48.4 ± 15.1%. Chemotherapy was the only predictive factor that is associated with the prognosis of the patients (P = 0.003).

CONCLUSION

The clinicopathological characteristics of 17 cases of stringently diagnosed LCC were retrospectively analyzed. LCC in our study showed aggressive behavior with high recurrence and metastasis and poor prognosis. Chemotherapy was only predictive factor that is significantly associated with the prognosis of the patients. Future studies based on a larger series and long term follow-up are still needed to characterize it further.

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.

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.

Correlation between molecular analysis, diagnosis according to the 2015 WHO classification of unresected lung tumours and TTF1 expression in small biopsies and cytology specimens from 344 non-small cell lung carcinoma patients

We investigated correlations between diagnosis according to the 2015 World Health Organization (WHO) classification of unresected lung tumours, molecular analysis and TTF1 expression in small biopsy and cytology specimens from 344 non-small cell lung carcinoma (NSCLC) patients. One case failed testing for EGFR, KRAS and ALK abnormalities and six had insufficient tumour for ALK testing. Overall mutation rate in 343 cases was 48% for the genes tested, with 19% EGFR, 33% KRAS and 4% BRAF mutations, and 5% ALK rearrangements detected. More EGFR-mutant (78%) and ALK-rearranged (75%) tumours had morphologic adenocarcinoma than KRAS-mutant (56%) tumours. Despite no significant difference in the overall rate of any molecular abnormality between morphologic adenocarcinoma (52%) and NSCLC, favour adenocarcinoma (47%) (p = 0.18), KRAS mutations were detected more frequently in the latter group. No significant difference in the overall rate of any molecular abnormality between TTF1 positive (49%) and TTF1 negative tumours (44%) (p = 0.92) was detected, but more EGFR-mutant (97%) and ALK-rearranged tumours (92%) were TTF1 positive than KRAS-mutant tumours (68%). Rates of EGFR, KRAS and BRAF mutations and ALK rearrangements in this Australian NSCLC patient population are consistent with the published international literature. Our findings suggest that 2015 WHO classification of unresected tumours may assist in identifying molecular subsets of advanced NSCLC.

The Molecular Pathology of Lung Cancer

Advances in lung cancer genomics have revolutionized the diagnosis and treatment of this heterogeneous and clinically significant group of tumors. This article provides a broad overview of the most clinically relevant oncogenic alterations in common and rare lung tumors, with an emphasis on the pathologic correlates of the major oncogenic drivers, including EGFR, KRAS, ALK, and MET. Illustrations emphasize the morphologic diversity of lung adenocarcinoma, including genotype-phenotype correlations of genomic evolution in tumorigenesis. Molecular diagnostic approaches, including PCR-based testing, massively parallel sequencing, fluorescence in situ hybridization, and immunohistochemistry are reviewed.

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.

Genome-wide copy number variation pattern analysis and a classification signature for non-small cell lung cancer

The accurate classification of non-small cell lung carcinoma (NSCLC) into lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) is essential for both clinical practice and lung cancer research. Although the standard WHO diagnosis of NSCLC on biopsy material is rapid and economic, more than 13% of NSCLC tumors in the USA are not further classified. The purpose of this study was to analyze the genome-wide pattern differences in copy number variations (CNVs) and to develop a CNV signature as an adjunct test for the routine histopathologic classification of NSCLCs. We investigated the genome-wide CNV differences between these two tumor types using three independent patient datasets. Approximately half of the genes examined exhibited significant differences between LUAD and LUSC tumors and the corresponding non-malignant tissues. A new classifier was developed to identify signature genes out of 20 000 genes. Thirty-three genes were identified as a CNV signature of NSCLC. Using only their CNV values, the classification model separated the LUADs from the LUSCs with an accuracy of 0.88 and 0.84, respectively, in the training and validation datasets. The same signature also classified NSCLC tumors from their corresponding non-malignant samples with an accuracy of 0.96 and 0.98, respectively. We also compared the CNV patterns of NSCLC tumors with those of histologically similar tumors arising at other sites, such as the breast, head, and neck, and four additional tumors. Of greater importance, the significant differences between these tumors may offer the possibility of identifying the origin of tumors whose origin is unknown.

An Expression Signature as an Aid to the Histologic Classification of Non-Small Cell Lung Cancer

PURPOSE

Most non-small cell lung cancers (NSCLC) are now diagnosed from small specimens, and classification using standard pathology methods can be difficult. This is of clinical relevance as many therapy regimens and clinical trials are histology dependent. The purpose of this study was to develop an mRNA expression signature as an adjunct test for routine histopathologic classification of NSCLCs.

EXPERIMENTAL DESIGN

A microarray dataset of resected adenocarcinomas (ADC) and squamous cell carcinomas (SCC) was used as the learning set for an ADC-SCC signature. The Cancer Genome Atlas (TCGA) lung RNAseq dataset was used for validation. Another microarray dataset of ADCs and matched nonmalignant lung was used as the learning set for a tumor versus nonmalignant signature. The classifiers were selected as the most differentially expressed genes and sample classification was determined by a nearest distance approach.

RESULTS

We developed a 62-gene expression signature that contained many genes used in immunostains for NSCLC typing. It includes 42 genes that distinguish ADC from SCC and 20 genes differentiating nonmalignant lung from lung cancer. Testing of the TCGA and other public datasets resulted in high prediction accuracies (93%-95%). In addition, a prediction score was derived that correlates both with histologic grading and prognosis. We developed a practical version of the Classifier using the HTG EdgeSeq nuclease protection-based technology in combination with next-generation sequencing that can be applied to formalin-fixed paraffin-embedded (FFPE) tissues and small biopsies.

CONCLUSIONS

Our RNA classifier provides an objective, quantitative method to aid in the pathologic diagnosis of lung cancer. Clin Cancer Res; 22(19); 4880-9. ©2016 AACR.

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

Large cell carcinoma with or without neuroendocrine features (LCNEC and LC, respectively) constitutes 3-9% of non-small cell lung cancer but is poorly characterized at the molecular level. Herein we analyzed 41 LC and 32 LCNEC (including 15 previously reported cases) tumors using massive parallel sequencing for mutations in 26 cancer-related genes and gene fusions in ALK, RET, and ROS1. LC patients were additionally subdivided into three immunohistochemistry groups based on positive expression of TTF-1/Napsin A (adenocarcinoma-like, n = 24; 59%), CK5/P40 (squamous-like, n = 5; 12%), or no marker expression (marker-negative, n = 12; 29%). Most common alterations were TP53 (83%), KRAS (22%), MET (12%) mutations in LCs, and TP53 (88%), STK11 (16%), and PTEN (13%) mutations in LCNECs. In general, LCs showed more oncogene mutations compared to LCNECs. Immunomarker stratification of LC revealed oncogene mutations in 63% of adenocarcinoma-like cases, but only in 17% of marker-negative cases. Moreover, marker-negative LCs were associated with inferior overall survival compared with adenocarcinoma-like tumors (p = 0.007). No ALK, RET or ROS1 fusions were detected in LCs or LCNECs. Together, our molecular analyses support that LC and LCNEC tumors follow different tumorigenic paths and that LC may be stratified into molecular subgroups with potential implications for diagnosis, prognostics, and therapy decisions.

The 2015 World Health Organization Classification of Lung Tumors: Impact of Genetic, Clinical and Radiologic Advances Since the 2004 Classification

The 2015 World Health Organization (WHO) Classification of Tumors of the Lung, Pleura, Thymus and Heart has just been published with numerous important changes from the 2004 WHO classification. The most significant changes in this edition involve (1) use of immunohistochemistry throughout the classification, (2) a new emphasis on genetic studies, in particular, integration of molecular testing to help personalize treatment strategies for advanced lung cancer patients, (3) a new classification for small biopsies and cytology similar to that proposed in the 2011 Association for the Study of Lung Cancer/American Thoracic Society/European Respiratory Society classification, (4) a completely different approach to lung adenocarcinoma as proposed by the 2011 Association for the Study of Lung Cancer/American Thoracic Society/European Respiratory Society classification, (5) restricting the diagnosis of large cell carcinoma only to resected tumors that lack any clear morphologic or immunohistochemical differentiation with reclassification of the remaining former large cell carcinoma subtypes into different categories, (6) reclassifying squamous cell carcinomas into keratinizing, nonkeratinizing, and basaloid subtypes with the nonkeratinizing tumors requiring immunohistochemistry proof of squamous differentiation, (7) grouping of neuroendocrine tumors together in one category, (8) adding NUT carcinoma, (9) changing the term sclerosing hemangioma to sclerosing pneumocytoma, (10) changing the name hamartoma to "pulmonary hamartoma," (11) creating a group of PEComatous tumors that include (a) lymphangioleiomyomatosis, (b) PEComa, benign (with clear cell tumor as a variant) and

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.

[Squamous cell carcinoma, basaloid squamous cell carcinoma and adenosquamous carcinoma in the lung]

The precise distinction between adenocarcinoma and squamous cell carcinoma (SqCC) has become very important for determining the appropriate therapy for patients and more specifically to drive the use of tyrosine kinase inhibitors, pemetrexed, anti-VEGF monoclonal antibody and crizotinib. Squamous pearls and distinct intercellular bridges identify keratinizing SqCC. In non-keratinizing SqCC, immuno-histochemistry is required. Recent studies have shown p40 and TTF1 to be the two best markers of SqCC and adenocarcinoma respectively. Many morphological variants of SqCC have been described. Basaloid SqCC is a poorly differentiated epithelial tumor lacking squamous morphology but showing immuno-histochemical expression of squamous makers. The pronostic of basaloid carcinoma is considered poorer than that of other non-small cell lung cancers. Adenosquamous carcinoma shows components of both SqCC and adenocarcinoma. Both components must be clearly identified either on H&E or by immuno-histochemistry. The adenocarcinoma components justified a screening for gene rearrangements. Finally, the recent WHO classification of lung tumors did not change the criteria applying for the grading of preinvasive bronchial lesion.

[Large cell carcinoma, lymphoepithelioma-like carcinoma, NUT carcinoma]

The diagnosis of large cell carcinoma can only be made on a sampled resected tumor and should not be applied to biopsies or cytology. In the 2015 WHO classification, the definition of large cell carcinoma is restricted to carcinomas both lacking morphological signs of glandular, squamous or neuroendocrine differentiation and exhibiting a null or unclear phenotype (TTF1-/p40 ou p63 ou CK5/6+ focally). These carcinomas have an adenocarcinoma molecular profile because they harbor a significant number of KRAS and BRAF mutations, a profile that is more similar to adenocarcinoma than squamous cell carcinoma. They also have a worse prognosis than the other types of non-small cell lung carcinoma. Many large cell carcinomas previously classified on morphological data alone are now reclassified in the adenocarcinoma and squamous cell carcinoma types, including immunohistochemical features. The other large cell carcinoma subtypes from the 2004 WHO classification, i.e. large cell neuroendocrine carcinoma and basaloid carcinoma, are grouped respectively with the other neuroendocrine tumors and squamous cell carcinomas. Clear cell and rhabdoid features are now considered as cytological variants that can occur in any histopathological subtype and not as distinct subtypes. Lymphoepithelioma-like carcinoma is moved to the group of other and unclassified carcinomas as NUT carcinoma.

Clinical features of large cell neuroendocrine carcinoma: a population-based overview

Pulmonary large cell neuroendocrine carcinoma (LCNEC) is an orphan disease and few data are available on its clinical characteristics. Therefore, we analysed LCNEC registered in the Netherlands Cancer Registry, and compared data with small cell lung carcinoma (SCLC), squamous cell carcinoma (SqCC) and adenocarcinoma (AdC).

Histologically confirmed LCNEC (n=952), SCLC (n=11 844), SqCC (n=19 633) and AdC (n=24 253) cases were selected from the Netherlands Cancer Registry (2003–2012). Patient characteristics, metastasis at diagnosis (2006 or later), overall survival (OS) including multivariate Cox models and first-line treatment were compared for stage I–II, III and IV disease.

The number of LCNEC cases increased from 56 patients in 2003 to 143 in 2012, accounting for 0.9% of all lung cancers. Stage IV LCNEC patients (n=383) commonly had metastasis in the liver (47%), bone (32%) and brain (23%), resembling SCLC. Median OS (95% CI) of stage I–II, III and IV LCNEC patients was 32.4 (22.0–42.9), 12.6 (10.3–15.0) and 4.0 (3.5–4.6) months, respectively. Multivariate-adjusted OS of LCNEC patients resembled that of SCLC patients, and was poorer than those of SqCC and AdC patients. However, frequency of surgical resection and adjuvant chemotherapy resembled SqCC and AdC more than SCLC.

Diagnosis of LCNEC has increased in recent years. The metastatic pattern of LCNEC resembles SCLC as does the OS. However, early-stage treatment strategies seem more comparable to those of SqCC and AdC.

Validation of the Lung Subtyping Panel in Multiple Fresh-Frozen and Formalin-Fixed, Paraffin-Embedded Lung Tumor Gene Expression Data Sets

Context .- A histologic classification of lung cancer subtypes is essential in guiding therapeutic management. Objective .- To complement morphology-based classification of lung tumors, a previously developed lung subtyping panel (LSP) of 57 genes was tested using multiple public fresh-frozen gene-expression data sets and a prospectively collected set of formalin-fixed, paraffin-embedded lung tumor samples. Design .- The LSP gene-expression signature was evaluated in multiple lung cancer gene-expression data sets totaling 2177 patients collected from 4 platforms: Illumina RNAseq (San Diego, California), Agilent (Santa Clara, California) and Affymetrix (Santa Clara) microarrays, and quantitative reverse transcription-polymerase chain reaction. Gene centroids were calculated for each of 3 genomic-defined subtypes: adenocarcinoma, squamous cell carcinoma, and neuroendocrine, the latter of which encompassed both small cell carcinoma and carcinoid. Classification by LSP into 3 subtypes was evaluated in both fresh-frozen and formalin-fixed, paraffin-embedded tumor samples, and agreement with the original morphology-based diagnosis was determined. Results .- The LSP-based classifications demonstrated overall agreement with the original clinical diagnosis ranging from 78% (251 of 322) to 91% (492 of 538 and 869 of 951) in the fresh-frozen public data sets and 84% (65 of 77) in the formalin-fixed, paraffin-embedded data set. The LSP performance was independent of tissue-preservation method and gene-expression platform. Secondary, blinded pathology review of formalin-fixed, paraffin-embedded samples demonstrated concordance of 82% (63 of 77) with the original morphology diagnosis. Conclusions .- The LSP gene-expression signature is a reproducible and objective method for classifying lung tumors and demonstrates good concordance with morphology-based classification across multiple data sets. The LSP panel can supplement morphologic assessment of lung cancers, particularly when classification by standard methods is challenging.

Next-Generation Sequencing of a Cohort of Pulmonary Large Cell Carcinomas Reclassified by World Health Organization 2015 Criteria

CONTEXT

The classification of pulmonary large cell carcinoma has undergone a major revision with the recent World Health Organization (WHO) 2015 Classification. Many large cell carcinomas are now reassigned to either adenocarcinoma with solid pattern or nonkeratinizing squamous cell carcinoma based on immunopositivity for adenocarcinoma markers or squamous cell carcinoma markers, respectively. Large cell carcinomas that are negative for adenocarcinoma and squamous cell carcinoma immunomarkers are now classified as large cell carcinoma with null immunohistochemical features (LCC-N). Although a few studies investigated the mutation profile of large cell carcinomas grouped by immunostain profile before the publication of the new WHO classification, investigation of tumors previously diagnosed as large cell carcinoma and reclassified according to the 2015 WHO classification has not, to our knowledge, been reported.

OBJECTIVE

To determine the mutation profiles of pulmonary large cell carcinomas reclassified by WHO 2015 criteria.

DESIGN

Archival cases of non-small cell lung carcinoma with large cell carcinoma morphology (n = 17) were reclassified according to 2015 WHO criteria. To determine mutation profile, we employed Ion Torrent (Life Technologies, Carlsbad, California)-based next-generation sequencing (50 genes; more than 2800 mutations) in addition to real-time quantitative reverse transcription polymerase chain reaction for ALK translocation detection.

RESULTS

Two of 17 cases (12%) were reclassified as LCC-N, and both had mutations-BRAF D594N in one case and KRAS G12C in the other case. Seven of 17 cases (41%) were reclassified in the adenocarcinoma with solid pattern group, which showed one KRAS G12C and one EGFR E709K + G719C double mutation in addition to mutations in TP53. Eight of 17 cases (47%) were reclassified in the nonkeratinizing squamous cell carcinoma group, which showed mutations in PIK3CA, CDKN2A, and TP53. No ALK translocations or amplifications were detected.

CONCLUSIONS

The adenocarcinoma with solid pattern group showed mutations typical of adenocarcinoma, whereas the nonkeratinizing squamous cell carcinoma group showed mutations typical of squamous cell carcinoma. Both LCC-N cases had mutations associated with adenocarcinoma, supporting the hypothesis that LCC-N is related to adenocarcinoma.

Reevaluation and reclassification of resected lung carcinomas originally diagnosed as squamous cell carcinoma using immunohistochemical analysis

Currently, non-small cell lung carcinomas are primarily classified by light microscopy. However, recent studies have shown that poorly differentiated tumors are more accurately classified by immunohistochemistry. In this study, we investigated the use of immunohistochemical analysis in reclassifying lung carcinomas that were originally diagnosed as squamous cell carcinoma. Tumor slides and blocks were available for histologic evaluation, and tissue microarrays were constructed from 480 patients with resected lung carcinomas originally diagnosed as squamous cell carcinoma between 1999 and 2009. Immunohistochemical analyses for p40, p63, thyroid transcription factor-1 (TTF-1; clones SPT24 and 8G7G3/1), napsin A, chromogranin A, synaptophysin, and CD56 were performed. Staining intensity (weak, moderate, or strong) and distribution (focal or diffuse) were also recorded. Of all, 449 (93.5%) patients were confirmed as having squamous cell carcinomas; the cases were mostly diffusely positive for p40 and negative for TTF-1 (8G7G3/1). Twenty cases (4.2%) were reclassified as adenocarcinoma, as they were positive for TTF-1 (8G7G3/1 or SPT24) with either no or focal p40 expression, and all of them were poorly differentiated with squamoid morphology. In addition, 1 case was reclassified as adenosquamous carcinoma, 4 cases as large cell carcinoma, 4 cases as large cell neuroendocrine carcinoma, and 2 cases as small cell carcinoma. In poorly differentiated non-small cell lung carcinomas, an accurate distinction between squamous cell carcinoma and adenocarcinoma cannot be reliably determined by morphology alone and requires immunohistochemical analysis, even in resected specimens. Our findings suggest that TTF-1 8G7G3/1 may be better suited as the primary antibody in differentiating adenocarcinoma from squamous cell carcinoma.

[Molecular pathology of lung cancer. State of the art 2014]

Lung cancer is the most frequent cause of cancer-related death in Germany in men and women alike. While in the last decades a classification of epithelial lung tumors into non-small cell and small cell lung cancer was clearly sufficient from the therapeutic viewpoint, the dawn of the era of personalized medicine together with tremendous developments in the field of high throughput technologies have led to a molecular individualization of these tumors and, even more important, to a molecularly defined individualization of tumor therapy. This development resulted in the definition of a wide array of molecularly divergent tumor families. In this article we will give an overview on relevant molecular alterations in non-small cell lung cancers, comprising adenocarcinomas, squamous cell carcinomas and large cell carcinomas and also small cell carcinomas and carcinoids. Besides some similarities data gathered in the last few years specifically highlighted the immense diversity of molecular alterations that might underlie tumorigenesis of lung neoplasms. The knowledge on how to detect these alterations is of utmost importance in pathology, as treatment decisions are increasingly based on their presence or absence, putting molecular pathology in the central focus of the novel era of personalized medicine in oncology.

Evaluation of azacitidine and entinostat as sensitization agents to cytotoxic chemotherapy in preclinical models of non-small cell lung cancer

Recent clinical data in lung cancer suggests that epigenetically targeted therapy may selectively enhance chemotherapeutic sensitivity. There have been few if any studies rigorously evaluating this hypothesized priming effect. Here we describe a series of investigations testing whether epigenetic priming with azacitidine and entinostat increases sensitivity of NSCLC to cytotoxic agents.

We noted no differences in chemosensitivity following treatment with epigenetic therapy in in vitro assays of viability and colony growth. Using cell line and patient-derived xenograft (PDX) models, we also observed no change in responsiveness to cisplatin in vivo. In select models, we noted differential responses to irinotecan treatment in vivo. In vitro epigenetic therapy prior to tumor implantation abrogated response of H460 xenografts to irinotecan. Conversely, in vitro epigenetic therapy appeared to sensitize A549 xenografts (tumor growth inhibition 51%, vs. 22% in mock-pretreated control). In vivo epigenetic therapy enhanced the response of adenocarcinoma PDX to irinotecan.

Taken together, these data do not support broadly applicable epigenetic priming in NSCLC. Priming effects may be context-specific, dependent on both tumor and host factors. Further preclinical study is necessary to determine whether, and in which contexts, priming with epigenetic therapy has potential to enhance chemotherapeutic efficacy in NSCLC patients.