The Use of Immunohistochemistry Improves the Diagnosis of Small Cell Lung Cancer and Its Differential Diagnosis. An International Reproducibility Study in a Demanding Set of Cases

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.

Management of patients with extensive small-cell lung cancer in the immunotherapy era: an Italian consensus through a Delphi approach

BACKGROUND

Immunotherapy represented a turning point for treating extensive small-cell lung cancer (ES-SCLC). Although, many issues remain debated.

METHODS

A group of Italian medical and radiation oncologists with expertise in managing patients with ES-SCLC developed a list of statements divided in six areas of interest. The Delphi method was used to assess the consensus on the defined list of statements.

RESULTS

32 statements were included in the final list to be voted by the Delphi panel, and 26 reached a consensus on the agreement. A prompt involvement of a multidisciplinary team is a priority to provide an integrated treatment strategy. First-line recommended treatment is immunotherapy in combination with platinum-based chemotherapy and etoposide for four cycles followed by maintenance immunotherapy.

CONCLUSIONS

While awaiting new data from clinical trials and real-world studies, these recommendations can represent a useful tool to guide the management of ES-SCLC patients in daily practice.

Spread Through Air Spaces in Stage I Pulmonary Large Cell Neuroendocrine Carcinoma

BACKGROUND

Pulmonary large cell neuroendocrine carcinoma (LCNEC) represents an exceptionally aggressive and infrequent variant within the realm of non-small cell lung cancer, necessitating surgical intervention as the primary therapeutic approach. However, the postoperative management strategy for early-stage patients continues to be a subject of intense debate and uncertainty.

METHODS

A retrospective analysis was conducted on a cohort of patients diagnosed with LCNEC who underwent surgical resection at Shanghai Pulmonary Hospital between July 2018 and June 2022. Comprehensive assessments, encompassing univariate and multivariate analyses, were performed to evaluate the prognostic significance of these indicators in patient clinical profiles, overall survival (OS), and disease-free survival (DFS).

RESULTS

A comprehensive screening effort identified 171 patients with LCNEC, with 70 stage I patients meeting the criteria for inclusion in the final cohort. Of these, 11 patients (15.7%) presented with combined LCNEC, and 59 (84.3%) exhibited pure LCNEC. Univariate and multivariate analyses both unveiled that spread through air spaces (STAS) status emerged as an independent prognostic determinant for both DFS (P = .003) and OS (P = .013), whereas histologic subtype independently predicted OS (P = .011). Subgroup survival analyses further underscored that the advantageous effects of postoperative chemotherapy were significantly pronounced exclusively among STAS-positive patients, showcasing a statistically significant enhancement in DFS (P = .047) and OS (P = .018).

CONCLUSIONS

STAS may serve as an adverse prognostic factor in stage I LCNEC patients, potentially offering guidance for postoperative chemotherapy decisions.

Unraveling the link: locomotor activity exerts a dual role in predicting Achilles tendon healing and boosting regeneration in mice

Introduction

Tendon disorders present significant challenges in the realm of musculoskeletal diseases, affecting locomotor activity and causing pain. Current treatments often fall short of achieving complete functional recovery of the tendon. It is crucial to explore, in preclinical research, the pathways governing the loss of tissue homeostasis and its regeneration. In this context, this study aimed to establish a correlation between the unbiased locomotor activity pattern of CRL:CD1 (ICR) mice exposed to uni- or bilateral Achilles tendon (AT) experimental injuries and the key histomorphometric parameters that influence tissue microarchitecture recovery.

Methods

The study involved the phenotyping of spontaneous and voluntary locomotor activity patterns in male mice using digital ventilated cages (DVC®) with access to running wheels either granted or blocked. The mice underwent non-intrusive 24/7 long-term activity monitoring for the entire study period. This period included 7 days of pre-injury habituation followed by 28 days post-injury.

Results and discussion

The results revealed significant variations in activity levels based on the type of tendon injury and access to running wheels. Notably, mice with bilateral lesions and unrestricted wheel access exhibited significantly higher activity after surgery. Extracellular matrix (ECM) remodeling, including COL1 deposition and organization, blood vessel remodeling, and metaplasia, as well as cytological tendon parameters, such as cell alignment and angle deviation were enhanced in surgical (bilateral lesion) and husbandry (free access to wheels) groups. Interestingly, correlation matrix analysis uncovered a strong relationship between locomotion and microarchitecture recovery (cell alignment and angle deviation) during tendon healing. Overall, this study highlights the potential of using mice activity metrics obtained from a home-cage monitoring system to predict tendon microarchitecture recovery at both cellular and ECM levels. This provides a scalable experimental setup to address the challenging topic of tendon regeneration using innovative and animal welfare-compliant strategies.

In-depth analysis of immunohistochemistry concordance in biopsy-resection pairs of bronchial carcinoids

Primary diagnosis of bronchial carcinoids (BC) is always made on biopsies and additional immunohistochemistry (IHC) is often necessary. In the present study we investigated the concordance of common diagnostic (synaptophysin, chromogranin, CD56 and INSM-1) and potential prognostic (OTP, CD44, Rb and p16) IHC markers between the preoperative biopsies and resections of in total 64 BCs, 26 typical (41 %) and 38 atypical (59 %) carcinoid tumors. Synaptophysin and chromogranin had 100 % concordance in all resected carcinoids and paired diagnostic biopsies. Synaptophysin was not affected by variable expression in biopsies compared to chromogranin, CD56 and INSM-1. Notably, INSM-1 IHC was false negative in 8 % of biopsies. Of the novel and potential prognostic markers, only CD44 showed 100 % concordance between biopsies and resections, while OTP showed two (4 %) false negative results in paired biopsies. While Rb IHC was false negative in 8 % of biopsies, no strong and diffuse pattern of p16 expression was observed. In this study, most false negative IHC results (85 %, 22/26) were observed in small flexible biopsies. Taken together, our data suggest excellent concordance of synaptophysin and CD44 on the preoperative biopsy samples, while other neuroendocrine markers, Rb and OTP should be interpreted with caution, especially in small biopsies.

Identification of naturally occurring compounds as alternatives to radiation therapy for treatment of small cell lung cancer

Radiation resistance is one of the major problems in the treatment of small cell lung cancer (SCLC). Most of these patients are given radiation as first-line treatment and it was observed that the initial response in these patients is very good. However, they show relapse in a few months which is also associated with resistance to treatment. Thus, targeting the mechanism by which these cells develop resistance could be an important strategy to improve the survival chances of these patients. From the RNA-Seq data analysis, it was identified that CHEK1 gene was overexpressed. Chk1 protein which is encoded by the CHEK1 gene is an important protein that is involved in radiation resistance in SCLC. It is known to favour the cells to deal with replicative stress. CHEK1 is the major cause for developing radiation resistance in SCLC. Thus, natural compounds that could also serve as potential inhibitors for Chk1 were explored. Accordingly; the compounds were screened based on ADME, docking and MM-GBSA scores. MD simulations were performed for the selected protein-ligand complexes and the results were compared to the co-crystallised ligand, 3-(indol-2-yl)indazole. The results showed that compound INC000033832986 could be a natural alternative to the commercial ligand for the prevention of SCLC.Communicated by Ramaswamy H. Sarma.

POU2F3: A Sensitive and Specific Diagnostic Marker for Neuroendocrine-low/negative Small Cell Lung Cancer

POU2F3 (POU class 2 homeobox 3) is a novel transcription factor used to define the special molecular subtype of small cell lung cancer (SCLC) known as SCLC-P. Nevertheless, the sensitivity and specificity of POU2F3 immunohistochemical (IHC) staining have not been fully investigated. In this study, we explored the expression of POU2F3 by IHC in a large cohort of SCLC clinical samples (n=246), other common lung cancer types (n=2207), and various other cancer types (n=194). The results showed that POU2F3 was strongly nuclear stained in 13.41% (33/246) of SCLC cases, with negative or minimal labeling for thyroid transcription factor-1 and neuroendocrine (NE) markers. Compared with POU2F3-negative SCLC, SCLC-P harbored fewer TP53 and RB1 mutations. POU2F3 was also expressed in 3.13% (8/256) of squamous cell carcinomas (SCCs) and 20% (2/10) of large cell NE carcinomas (LCNECs), whereas other lung cancer types were negative. In addition to lung cancer, POU2F3 was positive in 22.2% (4/18) of thymic tumors. All other tumors were POU2F3-negative except for thymic carcinoma, although sparsely distributed weak nuclear staining was observed in lung adenocarcinoma, cervical SCC, and colorectal carcinoma. The sensitivity and specificity of POU2F3 in NE-low/negative SCLC were 82.1% and 99.4%, respectively. Notably, some rare unique patterns of POU2F3 expression were observed. One case of thymic SCC was characterized by diffuse and uniform cytomembrane staining. One case of esophageal NE tumor was nuclear-positive, while the normal proliferating squamous epithelium was strongly membrane-stained. This is the largest cohort of clinical samples to confirm that POU2F3 is a highly sensitive and specific diagnostic marker for NE-low/negative SCLC.

Topical Administration of an Apoptosis Inducer Mitigates Bleomycin-Induced Skin Fibrosis

Pathological fibrosis is distinguished from physiological wound healing by persistent myofibroblast activation, suggesting that therapies that induce myofibroblast apoptosis selectively could prevent progression and potentially reverse the established fibrosis, such as for scleroderma (a heterogeneous autoimmune disease characterized by multiorgan fibrosis). Navitoclax (NAVI) is a BCL-2/BCL-xL inhibitor with antifibrotic properties and has been investigated as a potential therapeutic for fibrosis. NAVI makes myofibroblasts particularly vulnerable to apoptosis. However, despite NAVI's significant potency, clinical translation of BCL-2 inhibitors, NAVI in this case, is hindered due to the risk of thrombocytopenia. Therefore, in this work, we utilized a newly developed ionic liquid formulation of NAVI for direct topical application to the skin, thereby avoiding systemic circulation and off-target-mediated side effects. The ionic liquid composed of choline and octanoic acid (COA) at a 1:2 molar ionic ratio increases skin diffusion and transportation of NAVI and maintains their retention within the dermis for a prolonged duration. Topical administration of NAVI-mediated BCL-xL and BCL-2 inhibition results in the transition of myofibroblast to fibroblast and ameliorates pre-existing fibrosis, as demonstrated in a scleroderma mouse model. We have observed a significant reduction of α-SMA and collagen, which are known as fibrosis marker proteins, as a result of the inhibition of anti-apoptotic proteins BCL-2/BCL-xL. Overall, our findings show that COA-assisted topical delivery of NAVI upregulates apoptosis specific to myofibroblasts, with minimal presence of the drug in the systemic circulation, resulting in an accelerated therapeutic effect with no discernible drug-associated toxicity.

Prevalence of Thyroid Transcription Factor-1 (TTF-1)-Negative Small Cell Carcinoma and Napsin A Positivity in Small Cell Carcinoma in a Cross-Sectional Study of Lung Core Biopsies

Background The prevalence of thyroid transcription factor-1 (TTF-1) and napsin A expression are poorly characterized in lung core biopsies of small cell carcinoma. Locally, the TTF-1 clone is 8G7G3/1 (Agilent/Dako), and the napsin A clone is IP64 (Leica Biosystems). Methods All in-house lung core biopsy reports for cases accessioned at a regional laboratory from January 2011 to December 2020 were retrieved and analyzed using a validated hierarchical free-text string matching algorithm (HFTSMA) to establish the diagnosis. TTF-1 and napsin A were manually coded with the assistance of a logical text parsing tool. All TTF-1-negative small cell lung carcinoma (SCLC) cases had a full report review by pathologists. Results The cohort had 5,867 lung core biopsies, and 232 cases were confirmed as small cell carcinoma on pathologist review. TTF-1 immunostain results were available in 173 SCLC cases, and 16 cases of TTF-1-negative SCLC were confirmed on full report review. These 16 cases had at least one positive neuroendocrine (NE) marker and positive keratin staining; cases with mixed histology or positive CK5/6 staining were excluded. Ki-67 was done in 10/16 cases; the average Ki-67 was 75%. Napsin A was negative in 50/51 small cell carcinomas, and 0/3 TTF-1-negative SCLC had napsin A positivity. Conclusions Standardized immunostain reporting would simplify such analyses. Based on the cohort, approximately 9% (16/173) of SCLC is TTF-1 negative. Napsin A positivity in suspected small cell carcinoma should prompt consideration of an alternate diagnosis or explanation.

Pulmonary neuroendocrine tumors: study of 266 cases focusing on clinicopathological characteristics, immunophenotype, and prognosis

OBJECTIVE

Pulmonary neuroendocrine tumors (PNETs) consist of small-cell lung cancer (SCLC), large-cell neuroendocrine carcinoma (LCNEC), typical carcinoid (TC), and atypical carcinoid (AC). We aimed to analyze the immunophenotypic, metastatic, and prognostic risk factors for PNETs.

MATERIALS AND METHODS

A total of 266 patients with PNETs were enrolled, including 219 patients with SCLC, 18 patients with LCNEC, 11 patients with TC, and 18 patients with AC. Clinicopathological characteristics and immunophenotypes were compared among the subtypes of PNETs. Risk factors for metastasis, progression-free survival (PFS), and overall survival (OS) were analyzed.

RESULTS

Thyroid transcription factor-1 (TTF-1) and the Ki-67 index were significantly different among subtypes of PNETs (all P < 0.05). Smoking (OR, 2.633; P = 0.031), high pretreatment carcinoembryonic antigen (CEA > 5 ng/ml: OR, 3.084; P = 0.014), and poorly differentiated pathotypes (P = 0.001) were independent risk factors for lymph-node metastasis. Smoking (OR, 2.071; P = 0.027) and high pretreatment CEA (OR, 2.260; P = 0.007) were independent risk factors for distant metastasis. Results of the multivariate Cox regression model showed pretreatment CEA (HR, 1.674; P = 0.008) and lymphocyte-monocyte ratio (LMR) (HR = 0.478, P = 0.007) were significantly associated with PFS; BMI (P = 0.031), lymph-node metastasis (HR = 4.534, P = 0.001), poorly differentiated pathotypes (P = 0.015), platelet-lymphocyte ratio (PLR) (HR = 2.305, P = 0.004), and LMR (HR = 0.524, P = 0.045) were significantly associated with OS.

CONCLUSIONS

PNETs are a group of highly heterogeneous tumors with different clinical manifestations, pathological features, and prognoses. Knowing clinicopathological characteristics and immunophenotypes of PNETs is significant for diagnosis. Pretreatment PLR, LMR, and CEA have certain value in the prognosis of PNETs.

Retinoblastoma Expression and Targeting by CDK4/6 Inhibitors in Small Cell Lung Cancer

The canonical model of "small cell lung cancer" (SCLC) depicts tumors arising from dual inactivation of TP53 and RB1. However, many genomic studies have persistently identified tumors with no RB1 mutations. Here, we examined RB1 protein expression and function in SCLC. RB1 expression was examined by IHC analysis of 62 human SCLC tumors. These studies showed that ∼14% of SCLC tumors expressed abundant RB1 protein, which is associated with neuroendocrine gene expression and is enriched in YAP1 expression, but no other lineage proteins that stratify SCLC. SCLC cells and xenograft tumors with RB1 protein expression were sensitive to growth inhibition by the CDK4/6 inhibitor palbociclib, and this inhibition was shown to be dependent on RB1 expression by CRISPR knockout. Furthermore, a patient with biopsy-validated wild-type RB1 SCLC who received the CDK4/6 inhibitor abemaciclib demonstrated a dramatic decrease in mutant TP53 ctDNA allelic fraction from 62.1% to 0.4% and decreased tumor mass on CT scans. Importantly, IHC of the diagnostic biopsy specimen showed RB1 positivity. Finally, we identified a transcriptomics-based RB1 loss-of-function signature that discriminates between SCLC cells with or without RB1 protein expression and validated it in the patient who was responsive to abemaciclib, suggesting its potential use to predict CDK4/6 inhibitor response in patients with SCLC. Our study demonstrates that RB1 protein is an actionable target in a subgroup of SCLC, a cancer that exhibits no currently targetable mutations.

The Complex Histopathological and Immunohistochemical Spectrum of Neuroendocrine Tumors-An Overview of the Latest Classifications

Neuroendocrine neoplasms (NENs) originate from the neuroendocrine cell system, which may either take the shape of organoid cell aggregations or be composed of dispersed cells across various organs. Therefore, these tumors are heterogenous regarding the site of origin, functional status, degree of aggressiveness, and prognosis. When treating patients with neuroendocrine tumors, one of the most significant challenges for physicians is determining the correct tumor grade and thus classifying patients into risk categories. Over the years, the classification of these tumors has changed significantly, often causing confusion due to clinical, molecular, and immunohistochemical variability. This review aims to outline the latest NENs classifications regardless of their site of origin. Thus, an overview of the key histopathological and immunohistochemical characteristics of NENs could pave the way to validate possible predictive and prognostic markers and also guide the therapeutic conduct.

Defining Morphologic Features of Invasion in Pulmonary Nonmucinous Adenocarcinoma With Lepidic Growth: A Proposal by the International Association for the Study of Lung Cancer Pathology Committee

INTRODUCTION

Since the eight edition of the Union for International Cancer Control and American Joint Committee on Cancer TNM classification system, the primary tumor pT stage is determined on the basis of presence and size of the invasive components. The aim of this study was to identify histologic features in tumors with lepidic growth pattern which may be used to establish criteria for distinguishing invasive from noninvasive areas.

METHODS

A Delphi approach was used with two rounds of blinded anonymized analysis of resected nonmucinous lung adenocarcinoma cases with presumed invasive and noninvasive components, followed by one round of reviewer de-anonymized and unblinded review of cases with known outcomes. A digital pathology platform was used for measuring total tumor size and invasive tumor size.

RESULTS

The mean coefficient of variation for measuring total tumor size and tumor invasive size was 6.9% (range: 1.7%-22.3%) and 54% (range: 14.7%-155%), respectively, with substantial variations in interpretation of the size and location of invasion among pathologists. Following the presentation of the results and further discussion among members at large of the International Association for the Study of Lung Cancer Pathology Committee, extensive epithelial proliferation (EEP) in areas of collapsed lepidic growth pattern is recognized as a feature likely to be associated with invasive growth. The EEP is characterized by multilayered luminal epithelial cell growth, usually with high-grade cytologic features in several alveolar spaces.

CONCLUSIONS

Collapsed alveoli and transition zones with EEP were identified by the Delphi process as morphologic features that were a source of interobserver variability. Definition criteria for collapse and EEP are proposed to improve reproducibility of invasion measurement.

Proposing Specific Neuronal Epithelial-to-Mesenchymal Transition Genes as an Ancillary Tool for Differential Diagnosis among Pulmonary Neuroendocrine Neoplasms

Pulmonary neuroendocrine neoplasms (PNENs) are currently classified into four major histotypes, including typical carcinoid (TC), atypical carcinoid (AC), large cell neuroendocrine carcinoma (LCNEC), and small cell lung carcinoma (SCLC). This classification was designed to be applied to surgical specimens mostly anchored in morphological parameters, resulting in considerable overlapping among PNENs, which may result in important challenges for clinicians' decisions in the case of small biopsies. Since PNENs originate from the neuroectodermic cells, epithelial-to-mesenchymal transition (EMT) gene expression shows promise as biomarkers involved in the genotypic transformation of neuroectodermic cells, including mutation burden with the involvement of chromatin remodeling genes, apoptosis, and mitosis rate, leading to modification in final cellular phenotype. In this situation, additional markers also applicable to biopsy specimens, which correlate PNENs subtypes with systemic treatment response, are much needed, and current potential candidates are neurogenic EMT genes. This study investigated EMT genes expression and its association with PNENs histotypes in tumor tissues from 24 patients with PNENs. PCR Array System for 84 EMT-related genes selected 15 differentially expressed genes among the PNENs, allowing to discriminate TC from AC, LCNEC from AC, and SCLC from AC. Functional enrichment analysis of the EMT genes differentially expressed among PNENs subtypes showed that they are involved in cellular proliferation, extracellular matrix degradation, regulation of cell apoptosis, oncogenesis, and tumor cell invasion. Interestingly, four EMT genes (MAP1B, SNAI2, MMP2, WNT5A) are also involved in neurological diseases, in brain metastasis, and interact with platinum-based chemotherapy and tyrosine-kinase inhibitors. Collectively, these findings emerge as an important ancillary tool to improve the strategies of histologic diagnosis in PNENs and unveil the four EMT genes that can play an important role in driving chemical response in PNENs.

Small Biopsy and Cytology of Pulmonary Neuroendocrine Neoplasms: Brief Overview of Classification, Immunohistochemistry, Molecular Profiles, and World Health Organization Updates

Pulmonary neuroendocrine neoplasms comprise ~20% of all lung tumors. Typical carcinoid, atypical carcinoid, small cell carcinoma, and large cell neuroendocrine carcinoma represent the 4 major distinct subtypes recognized on resections. This review provides a brief overview of the cytomorphologic features and the 2021 World Health Organization classification of these tumor types on small biopsy and cytology specimens. Also discussed are the role of immunohistochemistry in the diagnosis and molecular signatures of pulmonary neuroendocrine tumors.

Rb Tumor Suppressor in Small Cell Lung Cancer: Combined Genomic and IHC Analysis with a Description of a Distinct Rb-Proficient Subset

PURPOSE

RB1 mutations and loss of retinoblastoma (Rb) expression represent consistent but not entirely invariable hallmarks of small cell lung cancer (SCLC). The prevalence and characteristics of SCLC retaining wild-type Rb are not well-established. Furthermore, the performance of targeted next-generation sequencing (NGS) versus immunohistochemistry for Rb assessment is not well-defined.

EXPERIMENTAL DESIGN

A total of 208 clinical SCLC samples were analyzed by comprehensive targeted NGS, covering all exons of RB1, and Rb IHC. On the basis of established coordination of Rb/p16/cyclinD1 expression, p16-high/cyclinD1-low profile was used as a marker of constitutive Rb deficiency.

RESULTS

Fourteen of 208 (6%) SCLC expressed wild-type Rb, accompanied by a unique p16-low/cyclinD1-high profile supporting Rb proficiency. Rb-proficient SCLC was associated with neuroendocrine-low phenotype, combined SCLC with non-SCLC (NSCLC) histology and aggressive behavior. These tumors exclusively harbored CCND1 amplification (29%), and were markedly enriched in CDKN2A mutations (50%) and NSCLC-type alterations (KEAP1, STK11, FGFR1). The remaining 194 of 208 SCLC were Rb-deficient (p16-high/cyclinD1-low), including 184 cases with Rb loss (of which 29% lacked detectable RB1 alterations by clinical NGS pipeline), and 10 cases with mutated but expressed Rb.

CONCLUSIONS

This is the largest study to date to concurrently analyze Rb by NGS and IHC in SCLC, identifying a 6% rate of Rb proficiency. Pathologic-genomic data implicate NSCLC-related progenitors as a putative source of Rb-proficient SCLC. Consistent upstream Rb inactivation via CDKN2A/p16↓ and CCND1/cyclinD1↑ suggests the potential utility of CDK4/6 inhibitors in this aggressive SCLC subset. The study also clarifies technical aspects of Rb status determination in clinical practice, highlighting the limitations of exon-only sequencing for RB1 interrogation. See related commentary by Mahadevan and Sholl, p. 4603.

POU2F3 in SCLC: Clinicopathologic and Genomic Analysis With a Focus on Its Diagnostic Utility in Neuroendocrine-Low SCLC

INTRODUCTION

POU2F3 is a recent marker of a small cell lung carcinoma (SCLC) subtype related to chemosensory tuft cells (SCLC-P). The characteristics of SCLC-P have not been fully defined, and the data on POU2F3 expression in other lung tumors are scarce.

METHODS

We screened 254 SCLC for POU2F3 expression and comprehensively analyzed histopathologic, genomic, and clinical characteristics of POU2F3-positive tumors. We also explored POU2F3 expression in other major lung cancer types (n = 433) and a targeted set of potential diagnostic mimics of SCLC (n = 123).

RESULTS

POU2F3 was expressed in 30 of 254 (12%) SCLC and was strongly associated with low expression of standard neuroendocrine markers (synaptophysin, chromogranin A, CD56, INSM1). Notably, POU2F3 was expressed in 75% of SCLC with entirely negative or minimal neuroendocrine marker expression (15/20) and was helpful in supporting the diagnosis of SCLC in such cases. Broad targeted next-generation sequencing revealed that SCLC-P (n = 12) exhibited enrichment in several alterations, including PTEN inactivation, MYC amplifications, and 20q13 amplifications, but similar rates of RB1 and TP53 alterations as other SCLC (n = 155). Beyond SCLC, POU2F3 expression was exclusively limited to large cell neuroendocrine carcinoma (12%) and basaloid squamous cell carcinoma (22%).

CONCLUSIONS

This is the largest cohort of SCLC-P clinical samples to date, where we describe the diagnostic utility of POU2F3 in a challenging subset of SCLC with low or absent expression of standard neuroendocrine markers. The distinct genomic alterations in SCLC-P may offer a novel avenue for therapeutic targeting. The role of POU2F3 in a narrow subset of other lung cancer types warrants further study.

Hierarchical identification of a transcriptional panel for the histological diagnosis of lung neuroendocrine tumors

Background: Lung cancer is a complex disease composed of neuroendocrine (NE) and non-NE tumors. Accurate diagnosis of lung cancer is essential in guiding therapeutic management. Several transcriptional signatures have been reported to distinguish between adenocarcinoma (ADC) and squamous cell carcinoma (SCC) belonging to non-NE tumors. This study aims to identify a transcriptional panel that could distinguish the histological subtypes of NE tumors to complement the morphology-based classification of an individual.

Methods: A public dataset with NE subtypes, including 21 small-cell lung cancer (SCLC), 56 large-cell NE carcinomas (LCNECs), and 24 carcinoids (CARCIs), and non-NE subtypes, including 85 ADC and 61 SCC, was used as a training set. In the training set, consensus clustering was first used to filter out the samples whose expression patterns disagreed with their histological subtypes. Then, a rank-based method was proposed to develop a panel of transcriptional signatures for determining the NE subtype for an individual, based on the within-sample relative gene expression orderings of gene pairs. Twenty-three public datasets with a total of 3,454 samples, which were derived from fresh-frozen, formalin-fixed paraffin-embedded, biopsies, and single cells, were used for validation. Clinical feasibility was tested in 10 SCLC biopsy specimens collected from cancer hospitals via bronchoscopy.

Results: The NEsubtype-panel was composed of three signatures that could distinguish NE from non-NE, CARCI from non-CARCI, and SCLC from LCNEC step by step and ultimately determine the histological subtype for each NE sample. The three signatures achieved high average concordance rates with 97.31%, 98.11%, and 90.63%, respectively, in the 23 public validation datasets. It is worth noting that the 10 clinic-derived SCLC samples diagnosed via immunohistochemical staining were also accurately predicted by the NEsubtype-panel. Furthermore, the subtype-specific gene expression patterns and survival analyses provided evidence for the rationality of the reclassification by the NEsubtype-panel.

Conclusion: The rank-based NEsubtype-panel could accurately distinguish lung NE from non-NE tumors and determine NE subtypes even in clinically challenging samples (such as biopsy). The panel together with our previously reported signature (KRT5-AGR2) for SCC and ADC would be an auxiliary test for the histological diagnosis of lung cancer.

Insulinoma-Associated Protein 1 (INSM1): Diagnostic, Prognostic, and Therapeutic Use in Small Cell Lung Cancer

Small cell lung carcinoma (SCLC) is an aggressive and difficult to treat cancer. Although immunohistochemistry is not mandatory for a SCLC diagnosis, it might be required, especially in small samples. Insulinoma-associated protein 1 (INSM1) is expressed in endocrine and nervous tissues during embryogenesis, generally absent in adults and re-expressed in SCLC and other neuroendocrine neoplasms. Its high specificity propelled its use as diagnostic biomarker and an attractive therapeutic target. Herein, we aim to provide a systematic and critical review on the use of INSM1 for diagnosis, prognostication and the treatment of SCLC. An extensive bibliographic search was conducted in PubMed® focusing on articles published since 2015. According to the literature, INSM1 is a highly sensitive (75–100%) and specific (82–100%) neuroendocrine immunohistochemical marker for SCLC diagnosis. It can be used in histological and cytological samples. Although advantageous, its standalone use is currently not recommended. Studies correlating INSM1 expression and prognosis have disclosed contrasting results, although the expression seemed to entail a worse survival. Targeting INSM1 effectively suppressed SCLC growth either as a suicide gene therapy regulator or as an indirect target of molecular-targeted therapy. INSM1 represents a valuable biomarker for a SCLC diagnosis that additionally offers vast opportunities for the development of new prognostic and therapeutic strategies.

Reproducible, high-dimensional imaging in archival human tissue by multiplexed ion beam imaging by time-of-flight (MIBI-TOF)

Multiplexed ion beam imaging by time-of-flight (MIBI-TOF) is a form of mass spectrometry imaging that uses metal labeled antibodies and secondary ion mass spectrometry to image dozens of proteins simultaneously in the same tissue section. Working with the National Cancer Institute's (NCI) Cancer Immune Monitoring and Analysis Centers (CIMAC), we undertook a validation study, assessing concordance across a dozen serial sections of a tissue microarray of 21 samples that were independently processed and imaged by MIBI-TOF or single-plex immunohistochemistry (IHC) over 12 days. Pixel-level features were highly concordant across all 16 targets assessed in both staining intensity (R² = 0.94 ± 0.04) and frequency (R² = 0.95 ± 0.04). Comparison to digitized, single-plex IHC on adjacent serial sections revealed similar concordance (R² = 0.85 ± 0.08) as well. Lastly, automated segmentation and clustering of eight cell populations found that cell frequencies between serial sections yielded an average correlation of R² = 0.94 ± 0.05. Taken together, we demonstrate that MIBI-TOF, with well-vetted reagents and automated analysis, can generate consistent and quantitative annotations of clinically relevant cell states in archival human tissue, and more broadly, present a scalable framework for benchmarking multiplexed IHC approaches.

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.

Expression patterns and prognostic relevance of subtype-specific transcription factors in surgically resected small cell lung cancer: an international multicenter study

The tissue distribution and prognostic relevance of subtype‐specific proteins (ASCL1, NEUROD1, POU2F3, YAP1) present an evolving area of research in small‐cell lung cancer (SCLC). The expression of subtype‐specific transcription factors and P53 and RB1 proteins were measured by immunohistochemistry (IHC) in 386 surgically resected SCLC samples. Correlations between subtype‐specific proteins and in vitro efficacy of various therapeutic agents were investigated by proteomics and cell viability assays in 26 human SCLC cell lines. Besides SCLC‐A (ASCL1‐dominant), SCLC‐AN (combined ASCL1/NEUROD1), SCLC‐N (NEUROD1‐dominant), and SCLC‐P (POU2F3‐dominant), IHC and cluster analyses identified a quadruple‐negative SCLC subtype (SCLC‐QN). No unique YAP1‐subtype was found. The highest overall survival rates were associated with non‐neuroendocrine subtypes (SCLC‐P and SCLC‐QN) and the lowest with neuroendocrine subtypes (SCLC‐A, SCLC‐N, SCLC‐AN). In univariate analyses, high ASCL1 expression was associated with poor prognosis and high POU2F3 expression with good prognosis. Notably, high ASCL1 expression influenced survival outcomes independently of other variables in a multivariate model. High POU2F3 and YAP1 protein abundances correlated with sensitivity and resistance to standard‐of‐care chemotherapeutics, respectively. Specific correlation patterns were also found between the efficacy of targeted agents and subtype‐specific protein abundances. In conclusion, we investigated the clinicopathological relevance of SCLC molecular subtypes in a large cohort of surgically resected specimens. Differential IHC expression of ASCL1, NEUROD1, and POU2F3 defines SCLC subtypes. No YAP1‐subtype can be distinguished by IHC. High POU2F3 expression is associated with improved survival in a univariate analysis, whereas elevated ASCL1 expression is an independent negative prognosticator. Proteomic and cell viability assays of human SCLC cell lines revealed distinct vulnerability profiles defined by transcription regulators. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Dynamic expression of Schlafen 11 (SLFN11) in circulating tumour cells as a liquid biomarker in small cell lung cancer

INTRODUCTION

Small cell lung cancer (SCLC) is an aggressive malignancy with no established biomarkers. Schlafen 11(SLFN11), a DNA/RNA helicase that sensitises cancer cells to DNA-damaging agents, has emerged as a promising predictive biomarker for several drug classes including platinum and PARP inhibitors. Detection of SLFN11 in circulating tumour cells (CTCs) may provide a valuable alternative to tissue sampling.

METHODS

SLFN11 expression was evaluated in tumour samples and characterised in circulating tumour cells (CTC) longitudinally to determine its potential role as a biomarker of response.

RESULTS

Among 196 SCLC tumours, 51% expressed SLFN11 by IHC. In addition, 20/29 extra-thoracic high-grade neuroendocrine tumours expressed SLFN11 expression. In 64 blood samples from 42 SCLC patients, 83% (53/64) of samples had detectable CTCs, and SLFN11-positive CTCs were detected in 55% (29/53). Patients actively receiving platinum treatment had the lowest number of CTCs and a lower percentage of SLFN11-positive CTCs (p = 0.014). Analysis from patients with longitudinal samples suggest a decrease in CTC number and in SLFN11 expression that correlates with clinical response.

CONCLUSIONS

SLFN11 levels can be monitored in CTCs from SCLC patients using non-invasive liquid biopsies. The ability to detect SLFN11 in CTCs from SCLC patients adds a valuable tool for the detection and longitudinal monitoring of this promising biomarker.

Deep Learning Facilitates Distinguishing Histologic Subtypes of Pulmonary Neuroendocrine Tumors on Digital Whole-Slide Images

Simple Summary

Challenges persist in diagnosing pulmonary neuroendocrine tumors. Our case study shows that deep learning combined with convolutional neural networks has the potential to assist in the diagnosis of pulmonary neuroendocrine tumors from digital whole-slide images.

Abstract

The histological distinction of lung neuroendocrine carcinoma, including small cell lung carcinoma (SCLC), large cell neuroendocrine carcinoma (LCNEC) and atypical carcinoid (AC), can be challenging in some cases, while bearing prognostic and therapeutic significance. To assist pathologists with the differentiation of histologic subtyping, we applied a deep learning classifier equipped with a convolutional neural network (CNN) to recognize lung neuroendocrine neoplasms. Slides of primary lung SCLC, LCNEC and AC were obtained from the Laboratory of Clinical and Experimental Pathology (University Hospital Nice, France). Three thoracic pathologists blindly established gold standard diagnoses. The HALO-AI module (Indica Labs, UK) trained with 18,752 image tiles extracted from 60 slides (SCLC = 20, LCNEC = 20, AC = 20 cases) was then tested on 90 slides (SCLC = 26, LCNEC = 22, AC = 13 and combined SCLC with LCNEC = 4 cases; NSCLC = 25 cases) by F1-score and accuracy. A HALO-AI correct area distribution (AD) cutoff of 50% or more was required to credit the CNN with the correct diagnosis. The tumor maps were false colored and displayed side by side to original hematoxylin and eosin slides with superimposed pathologist annotations. The trained HALO-AI yielded a mean F1-score of 0.99 (95% CI, 0.939–0.999) on the testing set. Our CNN model, providing further larger validation, has the potential to work side by side with the pathologist to accurately differentiate between the different lung neuroendocrine carcinoma in challenging cases.

Large Cell Neuroendocrine Carcinoma of the Lung: Current Understanding and Challenges

Large cell neuroendocrine carcinoma of the lung (LCNEC) is a rare and highly aggressive type of lung cancer, with a complex biology that shares similarities with both small-cell lung cancer (SCLC) and non-small-cell lung cancer (NSCLC). The prognosis of LCNEC is poor, with a median overall survival of 8-12 months. The diagnosis of LCNEC requires the identification of neuroendocrine morphology and the expression of at least one of the neuroendocrine markers (chromogranin A, synaptophysin or CD56). In the last few years, the introduction of next-generation sequencing allowed the identification of molecular subtypes of LCNEC, with prognostic and potential therapeutic implications: one subtype is similar to SCLC (SCLC-like), while the other is similar to NSCLC (NSCLC-like). Because of LCNEC rarity, most evidence comes from small retrospective studies and treatment strategies that are extrapolated from those adopted in patients with SCLC and NSCLC. Nevertheless, limited but promising data about targeted therapies and immune checkpoint inhibitors in patients with LCNEC are emerging. LCNEC clinical management is still controversial and standardized treatment strategies are currently lacking. The aim of this manuscript is to review clinical and molecular data about LCNEC to better understand the optimal management and the potential prognostic and therapeutic implications of molecular subtypes.

Lung neuroendocrine neoplasms: recent progress and persistent challenges

This review summarizes key recent developments relevant to the pathologic diagnosis of lung neuroendocrine neoplasms, including carcinoids, small cell lung carcinoma (SCLC), and large cell neuroendocrine carcinoma (LCNEC). Covered are recent insights into the biological subtypes within each main tumor type, progress in pathological diagnosis and immunohistochemical markers, and persistent challenging areas. Highlighted topics include highly proliferative carcinoids and their distinction from small cell and large cell neuroendocrine carcinomas (NECs), the evolving role of Ki67, the update on the differential diagnosis of NEC to include thoracic SMARCA4-deficient undifferentiated tumors, the recent data on SCLC transcriptional subtypes with the emergence of POU2F3 as a novel marker for the diagnosis of SCLC with low/negative expression of standard neuroendocrine markers, and the update on the diagnosis of LCNEC, particularly in biopsies. There has been remarkable recent progress in the understanding of the genetic and expression-based profiles within each type of lung neuroendocrine neoplasm, and it is hoped that these insights will enable the development of novel diagnostic, prognostic, and predictive biomarkers to aid in the pathologic assessment of these tumors in the future.

Small Cell Lung Cancer, Version 2.2022, NCCN Clinical Practice Guidelines in Oncology

The NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines) for Small Cell Lung Cancer (SCLC) provide recommended management for patients with SCLC, including diagnosis, primary treatment, surveillance for relapse, and subsequent treatment. This selection for the journal focuses on metastatic (known as extensive-stage) SCLC, which is more common than limited-stage SCLC. Systemic therapy alone can palliate symptoms and prolong survival in most patients with extensive-stage disease. Smoking cessation counseling and intervention should be strongly promoted in patients with SCLC and other high-grade neuroendocrine carcinomas. The "Summary of the Guidelines Updates" section in the SCLC algorithm outlines the most recent revisions for the 2022 update, which are described in greater detail in this revised Discussion text.

Real-World Diagnostic Accuracy and Use of Immunohistochemical Markers in Lung Cancer Diagnostics

Objectives: Accurate and reliable diagnostics are crucial as histopathological type influences selection of treatment in lung cancer. The aim of this study was to evaluate real-world accuracy and use of immunohistochemical (IHC) staining in lung cancer diagnostics. Materials and Methods: The diagnosis and used IHC stains for small specimens with lung cancer on follow-up resection were retrospectively investigated for a 15-month period at two major sites in Sweden. Additionally, 10 pathologists individually suggested diagnostic IHC staining for 15 scanned bronchial and lung biopsies and cytological specimens. Results: In 16 (4.7%) of 338 lung cancer cases, a discordant diagnosis of potential clinical relevance was seen between a small specimen and the follow-up resection. In half of the cases, there was a different small specimen from the same investigational work-up with a concordant diagnosis. Diagnostic inaccuracy was often related to a squamous marker not included in the IHC panel (also seen for the scanned cases), the case being a neuroendocrine tumor, thyroid transcription factor-1 (TTF-1) expression in squamous cell carcinomas (with clone SPT24), or poor differentiation. IHC was used in about 95% of cases, with a higher number of stains in biopsies and in squamous cell carcinomas and especially neuroendocrine tumors. Pre-surgical transthoracic samples were more often diagnostic than bronchoscopic ones (72–85% vs. 9–53% for prevalent types). Conclusions: Although a high overall diagnostic accuracy of small specimens was seen, small changes in routine practice (such as consequent inclusion of p40 and TTF-1 clone 8G7G3/1 in the IHC panel for non-small cell cancer with unclear morphology) may lead to improvement, while reducing the number of IHC stains would be preferable from a time and cost perspective.

Small-Cell Carcinoma of the Lung: What We Learned about It?

Small-cell lung carcinoma (SCLC) is a high-grade aggressive disease that belongs to the neuroendocrine (NE) group of lung tumors that also includes typical carcinoid, atypical carcinoid, and large-cell NE carcinoma. SCLC has specific histological diagnostic criteria that are sometimes troublesome to be assessed in cytological samples that indeed represent the most frequent source of diagnostic material due to the typical advanced presentation at the onset of SCLC. However, cytological preparations could be in some instances more reliable than histology due to the better preservation of nuclear details. Cytological criteria for diagnosis of SCLC include high cellularity, small cell size, scant cytoplasm, coarsely granulated chromatin with "salt-and-pepper" appearance, inconspicuous or absent nucleoli, Azzopardi crush effect, and necrotic debris in the background. Despite being distinctive, these features could be incomplete to differentiate SCLC with other small-cell neoplasia. Therefore, immunocytochemical determination of diagnostic biomarkers is crucial to achieve a confident diagnosis. Furthermore, recent findings on molecular and transcriptomic studies of SCLC revealed the potential rise of new predictive and prognostic biomarkers that, whenever validated by immunocytochemistry, may potentially assist to tailor the best therapy, including immune checkpoint inhibition.

Clinical-Pathologic Challenges in the Classification of Pulmonary Neuroendocrine Neoplasms and Targets on the Horizon for Future Clinical Practice

Diagnosing a pulmonary neuroendocrine neoplasm (NEN) may be difficult, challenging clinical decision making. In this review, the following key clinical and pathologic issues and informative molecular markers are being discussed: (1) What is the preferred outcome parameter for curatively resected low-grade NENs (carcinoid), for example, overall survival or recurrence-free interval? (2) Does the WHO classification combined with a Ki-67 proliferation index and molecular markers, such as OTP and CD44, offer improved prognostication in low-grade NENs? (3) What is the value of a typical versus atypical carcinoid diagnosis on a biopsy specimen in local and metastatic disease? Diagnosis is difficult in biopsy specimens and recent observations of an increased mitotic rate in metastatic carcinoid from typical to atypical and high-grade NEN can further complicate diagnosis. (4) What is the (ir)relevance of morphologically separating large cell neuroendocrine carcinoma (LCNEC) SCLC and the value of molecular markers (RB1 gene and pRb protein or transcription factors NEUROD1, ASCL1, POU2F3, or YAP1 [NAPY]) to predict systemic treatment outcome? (5) Are additional diagnostic criteria required to accurately separate LCNEC from NSCLC in biopsy specimens? Neuroendocrine morphology can be absent owing to limited sample size leading to missed LCNEC diagnoses. Evaluation of genomic studies on LCNEC and marker studies have identified that a combination of napsin A and neuroendocrine markers could be helpful. Hence, to improve clinical practice, we should consider to adjust our NEN classification incorporating prognostic and predictive markers applicable on biopsy specimens to inform a treatment outcome-driven classification.

Non-Small Cell Lung Cancer Harboring Concurrent EGFR Genomic Alterations: A Systematic Review and Critical Appraisal of the Double Dilemma

The molecular pathways which promote lung cancer cell features have been broadly explored, leading to significant improvement in prognostic and diagnostic strategies. Epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) have dramatically altered the treatment approach for patients with metastatic non-small cell lung cancer (NSCLC). Latest investigations by using next-generation sequencing (NGS) have shown that other oncogenic driver mutations, believed mutually exclusive for decades, could coexist in EGFR-mutated NSCLC patients. However, the exact clinical and pathological role of concomitant genomic aberrations needs to be investigated. In this systematic review, we aimed to summarize the recent data on the oncogenic role of concurrent genomic alterations, by specifically evaluating the characteristics, the pathological significance, and their potential impact on the treatment approach.

Insulinoma-associated Protein 1 (INSM1) in Thoracic Tumors is Less Sensitive but More Specific Compared With Synaptophysin, Chromogranin A, and CD56

OBJECTIVE

Recognition of neuroendocrine differentiation is important for tumor classification and treatment stratification. To detect and confirm neuroendocrine differentiation, a combination of morphology and immunohistochemistry is often required. In this regard, synaptophysin, chromogranin A, and CD56 are established immunohistochemical markers. Insulinoma-associated protein 1 (INSM1) has been suggested as a novel stand-alone marker with the potential to replace the current standard panel. In this study, we compared the sensitivity and specificity of INSM1 and established markers.

MATERIALS AND METHODS

A cohort of 493 lung tumors including 112 typical, 39 atypical carcinoids, 77 large cell neuroendocrine carcinomas, 144 small cell lung cancers, 30 thoracic paragangliomas, 47 adenocarcinomas, and 44 squamous cell carcinomas were selected and tissue microarrays were constructed. Synaptophysin, chromogranin A, CD56, and INSM1 were stained on all cases and evaluated manually as well as with an analysis software. Positivity was defined as ≥1% stained tumor cells in at least 1 of 2 cores per patient.

RESULTS

INSM1 was positive in 305 of 402 tumors with expected neuroendocrine differentiation (typical and atypical carcinoids, large cell neuroendocrine carcinomas, small cell lung cancers, and paraganglioma; sensitivity: 76%). INSM1 was negative in all but 1 of 91 analyzed non-neuroendocrine tumors (adenocarcinomas, squamous cell carcinomas; specificity: 99%). All conventional markers, as well as their combination, had a higher sensitivity (97%) and a lower specificity (78%) for neuroendocrine differentiation compared with INSM1.

CONCLUSIONS

Although INSM1 might be a meaningful adjunct in the differential diagnosis of neuroendocrine neoplasias, a general uncritical vote for replacing the traditional markers by INSM1 may not be justified.

Recent advances and current controversies in lung neuroendocrine neoplasms✰

In the lung, neuroendocrine tumors (NETs), namely typical and atypical carcinoids, and neuroendocrine carcinomas (NECs), grouping small cell carcinoma (SCLC) and large cell neuroendocrine carcinoma (LCNEC), make up for distinct tumor entities according to epidemiological, genetic, pathologic and clinical data. The proper classification is essential in clinical practice for diagnosis, prognosis and therapy purposes. Through an extensive literature survey, three perspectives on lung NENs have been revised: i) criteria and terminology on biopsy or cytology samples of primaries or metastases; ii) carcinoids with elevated mitotic counts and/or Ki-67 proliferation rates; iii) relevance of molecular landscape to identify new tumor entities and therapeutic targets. Furthermore, a dispute about lung NEN development has been raised according to emerging molecular models. We herein provide a pathology update on practical topics in the setting of lung NENs according to the current classification (recent advances). We have also reappraised the development of these tumors by modeling risk factors and natural history of disease (recent controversies). Combining recent advances and controversies may help clarify our biological understanding of lung NENs and give practical information for the clinical decision-making process.

Pathology and Classification of SCLC

Simple Summary

Small cell lung carcinoma (SCLC), is a high-grade neuroendocrine carcinoma defined by its aggressiveness, poor differentiation, and somber prognosis. This review highlights current pathological concepts including classification, immunohistochemistry features, and differential diagnosis. Additionally, we summarize the current knowledge of the immune tumor microenvironment, tumor heterogeneity, and genetic variations of SCLC. Recent comprehensive genomic research has improved our understanding of the diverse biological processes that occur in this tumor type, suggesting that a new era of molecular-driven treatment decisions is finally foreseeable for SCLC patients.

Abstract

Lung cancer is consistently the leading cause of cancer-related death worldwide, and it ranks as the second most frequent type of new cancer cases diagnosed in the United States, both in males and females. One subtype of lung cancer, small cell lung carcinoma (SCLC), is an aggressive, poorly differentiated, and high-grade neuroendocrine carcinoma that accounts for 13% of all lung carcinomas. SCLC is the most frequent neuroendocrine lung tumor, and it is commonly presented as an advanced stage disease in heavy smokers. Due to its clinical presentation, it is typically diagnosed in small biopsies or cytology specimens, with routine immunostaining only. However, immunohistochemistry markers are extremely valuable in demonstrating neuroendocrine features of SCLC and supporting its differential diagnosis. The 2015 WHO classification grouped all pulmonary neuroendocrine carcinomas in one category and maintained the SCLC combined variant that was previously recognized. In this review, we explore multiple aspects of the pathologic features of this entity, as well as clinically relevant immunohistochemistry markers expression and its molecular characteristics. In addition, we will focus on characteristics of the tumor microenvironment, and the latest pathogenesis findings to better understand the new therapeutic options in the current era of personalized therapy.

Morphologic and molecular classification of lung neuroendocrine neoplasms

Neuroendocrine neoplasms (NENs) of the lung encompass neuroendocrine tumors (NETs) composed of typical (TC) and atypical (AC) carcinoids and full-fledged carcinomas (NECs) inclusive of large cell neuroendocrine carcinoma (LCNEC) and small cell carcinoma (SCLC). NETs and NECs are thought to represent distinct and separate lesions with neither molecular overlap nor common developmental continuum. Two perspectives were addressed regarding the morphologic and molecular classification of lung NENs: (i) a supervised approach by browsing the traditional classification, the relevant gene alterations, and their clinical implications; and (ii) an unsupervised approach, by reappraising neoplasms according to risk factors and natural history of disease to construct an interpretation model relied on biological data. We herein emphasize lights and shadows of the current classification of lung NENs and provide an alternative outlook on these tumors focused on what we currently know about the biological determinants and the natural history of disease.

Clinical implications of lung neuroendocrine neoplasm classification

INTRODUCTION

Neuroendocrine neoplasms of the lung (Lung NENs) encompass NE tumors (NETs), which are in turn split into typical and atypical carcinoids, and NE carcinomas (NECs), which group together small-cell carcinoma and large-cell NE carcinoma. This classification is the current basis for orienting the daily practice of these patients, with diagnostic, prognostic, and predictive inferences.

AREAS COVERED

The clinical implications of lung NEN classification are addressed according to three converging perspectives, which were dissected through an extensive literature overview: (1) how to put intratumor heterogeneity into the context of the current classification; (2) how to contextualize immunohistochemistry markers to improve diagnosis, prognosis, and therapy prediction; and (3) how to use immuno-oncology strategies for life-threatening NECs, which still account for 90% or more of lung NENs.

EXPERT OPINION

We provide practical insights to account for intratumor heterogeneity, practice the choice of immunohistochemistry markers, and emphasize once again the added value of immuno-oncology in the setting of personalized medicine of lung NENs.

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.

Protein Kinase C Isozymes Associated With Relapse Free Survival in Non-Small Cell Lung Cancer Patients

INTRODUCTION

Protein expression is deregulated in cancer, and the proteomic changes observed in lung cancer may be a consequence of mutations in essential genes. The purpose of this study was to identify protein expression associated with prognosis in lung cancers stratified by smoking status, molecular subtypes, and EGFR-, TP53-, and KRAS-mutations.

METHODS

We performed profiling of 295 cancer-relevant phosphorylated and non-phosphorylated proteins, using reverse phase protein arrays. Biopsies from 80 patients with operable lung adenocarcinomas were analyzed for protein expression and association with relapse free survival (RFS) were studied.

RESULTS

Spearman's rank correlation analysis identified 46 proteins with significant association to RFS (p<0.05). High expression of protein kinase C (PKC)-α and the phosporylated state of PKC-α, PKC-β, and PKC-δ, showed the strongest positive correlation to RFS, especially in the wild type samples. This was confirmed in gene expression data from 172 samples. Based on protein expression, unsupervised hierarchical clustering separated the samples into four subclusters enriched with the molecular subtypes terminal respiratory unit (TRU), proximal proliferative (PP), and proximal inflammatory (PI) (p=0.0001). Subcluster 2 contained a smaller cluster (2a) enriched with samples of the subtype PP, low expression of the PKC isozymes, and associated with poor RFS (p=0.003) compared to the other samples. Low expression of the PKC isozymes in the subtype PP and a reduced relapse free survival was confirmed with The Cancer Genome Atlas (TCGA) lung adenocarcinoma (LUAD) samples.

CONCLUSION

This study identified different proteins associated with RFS depending on molecular subtype, smoking- and mutational-status, with PKC-α, PKC-β, and PKC-δ showing the strongest correlation.

Integrated Immunohistochemical Study on Small-Cell Carcinoma of the Lung Focusing on Transcription and Co-Transcription Factors

Small-cell lung cancer (SCLC) is an aggressive malignant cancer that is classified into four subtypes based on the expression of the following key transcription and co-transcription factors: ASCL1, NEUROD1, YAP1, and POU2F3. The protein expression levels of these key molecules may be important for the formation of SCLC characteristics in a molecular subtype-specific manner. We expect that immunohistochemistry (IHC) of these molecules may facilitate the diagnosis of the specific SCLC molecular subtype and aid in the appropriate selection of individualized treatments. We attempted IHC of the four key factors and 26 candidate SCLC target molecules selected from the gene expression omnibus datasets of 47 SCLC samples, which were grouped based on positive or negative results for the four key molecules. We examined differences in the expression levels of the candidate targets and key molecules. ASCL1 showed the highest positive rate in SCLC samples, and significant differences were observed in the expression levels of some target molecules between the ASCL1-positive and ASCL1-negative groups. Furthermore, the four key molecules were coordinately and simultaneously expressed in SCLC cells. An IHC study of ASCL1-positive samples showed many candidate SCLC target molecules, and IHC could become an essential method for determining SCLC molecular subtypes.

Insulinoma-associated Protein 1 (INSM1) Is a Better Marker for the Diagnosis and Prognosis Estimation of Small Cell Lung Carcinoma Than Neuroendocrine Phenotype Markers Such as Chromogranin A, Synaptophysin, and CD56

To diagnose small cell lung carcinoma (SCLC), neuroendocrine (NE) phenotype markers such as chromogranin A, synaptophysin, and CD56 are helpful. However, because they are dispensable, SCLCs occur without apparent NE phenotypes. Insulinoma-associated protein 1 (INSM1) is a transcription factor for NE differentiation and has emerged as a single practical marker for SCLC. Using the surgical samples of 141 pulmonary NE tumors (78 SCLCs, 44 large cell NE carcinomas, and 19 carcinoids), and 246 non-NE carcinomas, we examined the immunohistochemical expression and prognostic relevance of INSM1 in association with NE phenotype markers. We evaluated its sensitivity and specificity for SCLC diagnosis, as well as its usefulness to diagnose SCLC without NE marker expression and to estimate the prognosis. INSM1 was expressed in SCLCs (92%, 72/78), large cell NE carcinomas (68%, 30/44), and carcinoids (95%, 18/19). In addition, among SCLCs with no expression of NE phenotype markers (n=12), 9 (75%) were positive for INSM1. These data suggest the superiority of INSM1 to the phenotype markers. Only 7% of adenocarcinomas (9/134) and 4% of squamous cell carcinomas (4/112) were positive for INSM1. SCLC with low-INSM1 expression (n=28) had a significantly better prognosis (P=0.040) than the high-INSM1 group (n=50). Our study revealed that INSM1 is highly sensitive and specific to detect SCLC and can estimate prognosis. INSM1 will be a promising marker for SCLC.

Diagnostic Value of Insulinoma-Associated Protein 1 (INSM1) and Comparison With Established Neuroendocrine Markers in Pulmonary Cancers

CONTEXT.—

The diagnostic distinction of pulmonary neuroendocrine (NE) tumors from non-small cell lung carcinomas (NSCLCs) is clinically relevant for prognostication and treatment. Diagnosis is based on morphology and immunohistochemical staining.

OBJECTIVE.—

To determine the diagnostic value of insulinoma-associated protein 1 (INSM1), in comparison with established NE markers, in pulmonary tumors.

DESIGN.—

Fifty-four pulmonary NE tumors and 632 NSCLCs were stained for INSM1, CD56, chromogranin A, and synaptophysin. In a subset, gene expression data were available for analysis. Also, 419 metastases to the lungs were stained for INSM1. A literature search identified 39 additional studies with data on NE markers in lung cancers from the last 15 years. Seven of these included data on INSM1.

RESULTS.—

A positive INSM1 staining was seen in 39 of 54 NE tumors (72%) and 6 of 623 NSCLCs (1%). The corresponding numbers were 47 of 54 (87%) and 14 of 626 (2%) for CD56, 30 of 54 (56%) and 6 of 629 (1%) for chromogranin A, and 46 of 54 (85%) and 49 of 630 (8%) for synaptophysin, respectively. Analysis of literature data revealed that CD56 and INSM1 were the best markers for identification of high-grade NE pulmonary tumors when considering both sensitivity and specificity, while synaptophysin also showed good sensitivity. INSM1 gene expression was clearly associated with NE histology.

CONCLUSIONS.—

The solid data of both our and previous studies confirm the diagnostic value of INSM1 as a NE marker in pulmonary pathology. The combination of CD56 with INSM1 and/or synaptophysin should be the first-hand choice to confirm pulmonary high-grade NE tumors. INSM1 gene expression could be used to predict NE tumor histology.

In Search of the Long-Desired 'Copernican Therapeutic Revolution' in Small-Cell Lung Cancer

Small-cell lung cancer has defied our scientific community for decades. Chemotherapy has been the mainstay treatment for small-cell lung cancer (SCLC) and unlike its counterpart, non-small cell lung cancer, no significant therapeutic breakthroughs have been made since the 1970s. Among the reasons for this slow-paced therapeutic development, one that stands out is the distinctive and almost universal loss of function of the tumour suppressor genes TP53 and RB1 in this disease, for which pharmacological activation has yet to be achieved, despite having been highly sought after. Although no molecularly targeted approach has been approved for clinical practice thus far, several strategies are currently exploring the potential to drug the tumour's "Achilles heel" that stems from essential pathways regulating DNA-damage response. Most recently, we have witnessed newfound reasons to hope, as the combination of immunotherapy and systemic chemotherapy has improved survival outcomes, representing the first landmark achievement in decades and a new standard of care for patients with extensive disease SCLC. However, continuous efforts are still needed towards a better understanding of the molecular pathways that singularise this tumour to eventually identify the predictive biomarkers that might result in the development of a more rational therapeutic approach, including the use of immunotherapy combinations. In this review we aim to uncover critical aspects of the immune microenvironment and biology of SCLC and provide an overview of the current and future landscape of promising therapeutic opportunities. The challenge still stands, but regardless, we are living in exciting times to finally check SCLC off the "bucket list" of our scientific community.

New molecular classification of large cell neuroendocrine carcinoma and small cell lung carcinoma with potential therapeutic impacts

Large cell neuroendocrine carcinoma (LCNECs) and small cell lung carcinomas (SCLCs) are high-grade neuroendocrine carcinomas of the lung with very aggressive behavior and poor prognosis. Their histological classification as well as their therapeutic management has not changed much in recent years, but genomic and transcriptomic analyses have revealed different molecular subtypes raising hopes for more personalized treatment. Indeed, four subtypes of SCLCs have been recently described, SCLC-A driven by the master gene ASCL1, SCLC-N driven by NEUROD1, SCLC-Y by YAP1 and SCLC-P by POU2F3. Whereas SCLC standard of care is based on concurrent chemoradiation for limited stages and on chemotherapy alone or chemotherapy combined with anti-PD-L1 checkpoint inhibitors for extensive stage SCLC, SCLC-A variants could benefit from DLL3 or BCL2 inhibitors, and SCLC-N variants from Aurora kinase inhibitors combined with chemotherapy, or PI3K/mTOR or HSP90 inhibitors. In addition, a new SCLC variant (SCLC-IM) with high-expression of immune checkpoints has been also reported, which could benefit from immunotherapies. PARP inhibitors also gave promising results in combination with chemotherapy in a subset of SCLCs. Regarding LCNECs, they represent a heterogeneous group of tumors, some of them exhibiting mutations also found in SCLC but with a pattern of expression of NSCLC, while others harbor mutations also found in NSCLC but with a pattern of expression of SCLC, questioning their clinical management as NSCLCs or SCLCs. Overall, we are probably entering a new area, which, if personalized treatments are effective, will also lead to the implementation in practice of molecular testing or biomarkers detection for the selection of patients who can benefit from them.

INSM1 expression in a subset of thoracic malignancies and small round cell tumors: rare potential pitfalls for small cell carcinoma

INSM1 is a diagnostic marker for neuroendocrine tumors originating in multiple anatomic sites. In the lung, INSM1 shows 76-97% sensitivity for neuroendocrine tumors overall. Our aim was to characterize INSM1 as a diagnostic marker for small cell carcinoma in the context of its epithelial, lymphoid, and mesenchymal morphologic mimics. Immunohistochemistry was performed on 231 tumors, including lung neuroendocrine tumors, nonneuroendocrine carcinomas of the thoracic cavity, diffuse large B-cell lymphomas, and small round cell sarcomas, using an anti-INSM1 mouse monoclonal antibody. Extent (0-100%) and intensity (1-3+) of nuclear INSM1 staining was multiplied in each case to calculate an H-score. Demographic and clinical information was obtained from the medical record. INSM1 had an overall sensitivity and specificity of 81.5% and 82.7% for small cell carcinoma, respectively, using a threshold established with a receiver operating characteristic curve. 40/48 (82.7%) small cell carcinomas were positive for INSM1, including 19/24 (79%) small cell carcinomas that were negative for chromogranin and synaptophysin. 5/5 carcinoids and 21/28 (75%) large cell neuroendocrine carcinomas showed INSM1 expression. Among nonneuroendocrine tumors, 7/38 (18%) lung adenocarcinomas, 2/17 (12%) lung squamous cell carcinomas, 4/10 (40%) thymic carcinomas, 4/12 (33%) adenoid cystic carcinomas, 1/19 (5%) diffuse large B-cell lymphomas, 4/11 (36%) alveolar rhabdomyosarcomas, and 4/23 (17%) Ewing sarcomas were positive for INSM1. No synovial sarcomas or desmoplastic small round cell tumors were positive. Weak, focal INSM1 expression alone is insufficient as a diagnostic marker for small cell carcinoma, but is sensitive and specific, easy to interpret in small biopsies, and makes a valuable addition to a diagnostic panel.

PD-L1-expression patterns in large-cell neuroendocrine carcinoma of the lung: potential implications for use of immunotherapy in these patients: the GFPC 03-2017 "EPNEC" study

Background

Few data are available on programmed cell-death-protein-1-ligand-1 (PD-L1) expression on large-cell neuroendocrine carcinomas of the lung (LCNECs). We analyzed PD-L1 expression on tumor (TCs) and inflammatory cells (ICs) from LCNEC patients to assess relationships between this expression, clinical characteristics, and disease outcomes.

Methods

PD-L1 expression was determined by immunohistochemistry with monoclonal antibody 22C3 in consecutive LCNEC patients managed in 17 French centers between January 2014 and December 2016.

Results

After centralized review, only 68 out of 105 (64%) patients had confirmed LCNEC diagnoses. Median overall survival (OS) (95% CI) was 11 (7-16) months for all patients, 7 (5-10), 21 (10-not reached) and not reached months for metastatic, stage III and localized forms (p = 0.0001). Respectively, 11% and 75% of the tumor samples were TC+ and IC+, and 66% had a TC-/IC+ profile. Comparing IC+ versus IC- metastatic LCNEC, the former had significantly longer progression-free survival [9 (4-13) versus 4 (1-8) months; p = 0.03], with a trend towards better median OS [12 (7-18) versus 9.5 (4-14) months; p = 0.21]. Compared to patients with TC- tumors, those with TC+ LCNECs tended to have non-significantly shorter median OS [4 (1-6.2) versus 11 (8-18) months, respectively]. Median OS was significantly shorter for patients with TC+/IC- metastatic LCNECs than those with TC-IC+ lesions (2 versus 8 months, respectively; p = 0.04).

Conclusion

TC-/IC+ was the most frequent PD-L1-expression profile for LCNECs, a pattern quite specific compared with non-small-cell lung cancer and small-cell lung cancer. IC PD-L1 expression seems to have a prognostic role.

Pathologists should probably forget about kappa. Percent agreement, diagnostic specificity and related metrics provide more clinically applicable measures of interobserver variability

Kappa statistics have been widely used in the pathology literature to compare interobserver diagnostic variability (IOV) among different pathologists but there has been limited discussion about the clinical significance of kappa scores. Five representative and recent pathology papers were queried using clinically relevant specific questions to learn how IOV was evaluated and how the clinical applicability of results was interpreted. The papers supported our anecdotal impression that pathologists usually assess IOV using Cohen's or Fleiss' kappa statistics and interpret the results using some variation of the scale proposed by Landis and Koch. The papers did not cite or propose specific guidelines to comment on the clinical applicability of results. The solutions proposed to decrease IOV included the development of better diagnostic criteria and additional educational efforts, but the possibility that the entities themselves represented a continuum of morphologic findings rather than distinct diagnostic categories was not considered in any of the studies. A dataset from a previous study of IOV reported by Thunnissen et al. was recalculated to estimate percent agreement among 19 international lung pathologists for the diagnosis of 74 challenging lung neuroendocrine neoplasms. Kappa scores and diagnostic sensitivity, specificity, positive and negative predictive values were calculated using the majority consensus diagnosis for each case as the gold reference diagnosis for that case. Diagnostic specificity estimates among multiple pathologists were > 90%, although kappa scores were considerably more variable. We explain why kappa scores are of limited clinical applicability in pathology and propose the use of positive and negative percent agreement and diagnostic specificity against a gold reference diagnosis to evaluate IOV among two and multiple raters, respectively.

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.

Lung cancer cytology and small biopsy specimens: diagnosis, predictive biomarker testing, acquisition, triage, and management

In the 21st century, there has been a dramatic shift in the management of advanced-stage lung carcinoma, and this has coincided with an increasing use of minimally invasive tissue acquisition methods. Both have had significant downstream effects on cytology and small biopsy specimens. Current treatments require morphologic, immunohistochemical, and/or genotypical subtyping of non-small cell lung carcinoma. To meet these objectives, standardized classification of cytology and small specimen diagnoses, immunohistochemical algorithms, and predictive biomarker testing guidelines have been developed. This review provides an overview of current classification, biomarker testing, methods of small specimen acquisition and triage, clinical management strategies, and emerging technologies.

Pulmonary small cell carcinoma: Review, common and uncommon differentials, genomics and management

Lung cancer is the leading cause of cancer-related death worldwide. It is divided into sub-categories based upon morphology, immunostaining pattern, biology, molecular profile, and/or treatment options. Up until the early 2000s when driver mutations with targeted therapies were identified in a subset of adenocarcinomas, the most critical distinction of lung carcinomas was driven by differences in treatment between small cell carcinoma (SCC) and nonsmall cell lung carcinoma (NSCLC). The distinction between SCC and NSCLC remains critical in the 21st century for management, especially for advanced stage cancer. In the vast majority of cases, morphological features are sufficient to separate SCC from other types of lung cancers. In some instances, however, cytomorphological features and immunohistochemical overlap with other tumors, limited sample availability, and/or crush artifact pose diagnostic challenges. The aim of this review is to highlight salient features of SCC and ancillary studies to distinguish it from common and uncommon potential mimickers, as well as provide updates in genomics and management.