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

The Unmet Diagnostic and Treatment Needs in Large Cell Neuroendocrine Carcinoma of the Lung

Large cell neuroendocrine carcinoma of the lung (LCNEC) is currently classified as a rare lung cancer subtype, but given the high incidence of lung cancer, the overall number of cases is considerable. The pathologic diagnosis of LCNEC is mainly based on the microscopic appearance of the tumor cells, the mitotic rate, the amount of intra-tumoral necrosis, and the presence of positive neuroendocrine markers identified by immunohistochemistry. Recently, a subdivision into two main categories was proposed based on mutation signatures involving the RB1, TP53, KRAS, and STK11/LKB1 genes, into SCLC-like (small cell lung cancer-like) and NSCLC-like (non-small cell lung cancer-like) LCNEC. In terms of treatment, surgery is still the best option for resectable, stage I-IIIA cases. Chemotherapy and radiotherapy have conflicting evidence. Etoposide/platinum remains the standard chemotherapy regimen. However, based on the newly proposed LCNEC subtypes, some retrospective series report better outcomes using a pathology-driven chemotherapy approach. Encouraging outcomes have also been reported for immunotherapy and targeted therapy, but the real impact of these strategies is still being determined in the absence of adequate prospective clinical trials. The current paper scrutinized the epidemiology, reviewed the reliability of pathologic diagnosis, discussed the need for molecular subtyping, and reviewed the heterogeneity of treatment algorithms in LCNEC.

Systemic treatment for neuroendocrine non-small cell lung carcinoma: A cases series and a systematic review of the literature

INTRODUCTION

Neuroendocrine lung cancer constitutes a continuum from carcinoid tumours (CT) to large cell neuroendocrine (LCNEC) and small-cell carcinomas (SCLC). Except for SCLC, there is no consensual agreement on systemic therapy. The aim of this study is to review our clinical experience among patients with CT and LCNEC in the light of a systematic review of the literature.

METHODS

A retrospective study of all patients with CT and LCNEC receiving a systemic therapy at Institut Jules Bordet and Erasme Hospital between 01/01/2000-31/12/2020. A systematic review of the literature was performed in Ovid Medline.

RESULTS

53 patients (21 CT and 32 LCNEC) were included. Despite limited response rates, patients with CT receiving a "carcinoid-like" 1st-line regimen (somatostatin analogues (SSA), everolimus, peptide receptor radionuclide therapy (PRRT)) had a numerically longer survival compared to those receiving other type of regimens (median 51.4 vs 18.6 months, respectively; p = 0.17). We observed a similar survival between 1st line "SCLC-like" vs "non-small cell lung cancer (NSCLC)-like" schemes in LCNEC (median 11.2 vs 12.6 months, respectively; p = 0.46). The systematic review identified 23 studies (12 prospective, 15 and 8 for CT and LCNEC respectively). For CT, everolimus and SSA led to prolonged disease control with an acceptable toxicity profile, while higher response rates but lower tolerance were associated with PRRT and chemotherapy regimens including oxaliplatine and dacarbazine. For LCNEC, no difference emerged when comparing "SCLC-like" and "NSCLC-like" regimens considering response rate, progression-free or overall survival.

CONCLUSIONS

SSA, everolimus and PRRT present a good therapeutic index for CT, while the role of chemotherapy remains limited to aggressive and rapidly evolving CT. The best type of chemotherapy regimen remains an open question in LCNEC.

Challenging Metastatic Melanoma to the Lung With p40 Expression: A Diagnostic Pitfall, Case Report

p40 immunohistochemistry is a cornerstone of histopathological examination for non-small cell lung carcinoma. p40 is an isoform of p63 and is reported to be highly specific for the diagnosis of squamous cell carcinoma. Very rare pitfalls are reported for this antibody, and p40 is typically negative in melanoma. A 66-year-old patient was admitted for multiple hemorrhagic brain tumors evocative of secondary tumors. On imaging, a 26 mm lung tumor was detected, and a biopsy of the lung tumor was performed. The tumor was stained by melanic markers and diffusely stained by p40 and p63. Molecular analysis found a somatic p.Asn581Ser (c.1742A>G) point mutation in exon 15 of BRAF and a p.Arg80Ter (c.238C>T) germline variant of CDKN2A , a predisposing mutation to melanoma. This case report highlights the importance of clinical, pathologic, and molecular correlation.

Value of immunohistochemistry in crushed areas of pulmonary neuroendocrine carcinoma

Immunohistochemical demonstration of neuroendocrine differentiation is often performed in routine diagnostic practice for lung neuroendocrine carcinoma. However, these carcinomas are often crushed, especially on small specimens. The value of immunohistochemistry on crushed areas is not known. We aimed to assess the value of immunohistochemical markers in crushed areas. We performed a retrospective study of 299 patients with a diagnosis of pulmonary neuroendocrine carcinoma. We showed that the markers TTF-1, synaptophysin, chromogranin A, CD56, and INSM1 were more often negative in crushed areas compared with well-preserved areas. The proliferation index with anti-Ki67 was decreased but remained on average around 90%. For all markers, the percentage of labeled cells was lower than in the preserved areas. Finally, we show that cases without labeling in the crushed areas and maintained labeling in the non-crushed areas have a lower percentage of labeling than cases without this labeling mismatch. Finally, there were no false positives of these stains. Neuroendocrine markers are valid in crushed areas when positive. However, the percentage of labeled cells may be lower than on preserved areas and lead to false negatives. Finally, the proliferation index, although decreased, remains close to that on preserved areas.

A novel quantitative prognostic model for initially diagnosed non-small cell lung cancer with brain metastases

Background

The prognosis of non-small cell lung cancer (NSCLC) with brain metastases (BMs) had been researched in some researches, but the combination of clinical characteristics and serum inflammatory indexes as a noninvasive and more accurate model has not been described.

Methods

We retrospectively screened patients with BMs at the initial diagnosis of NSCLC at Sun Yat-Sen University Cancer Center. LASSO-Cox regression analysis was used to establish a novel prognostic model for predicting OS based on blood biomarkers. The predictive accuracy and discriminative ability of the prognostic model was compared to Adjusted prognostic Analysis (APA), Recursive Partition Analysis (RPA), and Graded Prognostic Assessment (GPA) using concordance index (C-index), time-dependent receiver operating characteristic (td-ROC) curve, Decision Curve Analysis(DCA), net reclassification improvement index (NRI), and integrated discrimination improvement index (IDI).

Results

10-parameter signature's predictive model for the NSCLC patients with BMs was established according to the results of LASSO-Cox regression analysis. The C-index of the prognostic model to predict OS was 0.672 (95% CI = 0.609 ~ 0.736) which was significantly higher than APA,RPA and GPA. The td-ROC curve and DCA of the predictive model also demonstrated good predictive accuracy of OS compared to APA, RPA and GPA. Moreover, NRI and IDI analysis indicated that the prognostic model had improved prediction ability compared with APA, RPA and GPA.

Conclusion

The novel prognostic model demonstrated favorable performance than APA, RPA, and GPA for predicting OS in NSCLC patients with BMs.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-022-02671-2.

Large Cell Neuroendocrine Carcinoma in the Sinonasal Cavity with Large Intracranial Extension Treated with Endonasal Endoscopic and Transcranial Combined Surgery: A Case Report

Large cell neuroendocrine carcinoma (LCNEC) is a rare malignant tumor that typically arises in the lungs. It is especially rare in the sinonasal cavity, and treatment has not been established. In this study, we present the case of a 56-year-old woman with a large sinonasal LCNEC that extended into her brain. We performed endonasal endoscopic and transcranial combined surgery followed by chemoradiation therapy. The combined surgery enabled us to approach and remove the extensive tumor from two different directions at one time less invasively. We have achieved good tumor control for 18 months so far.

[Progress of Immune Checkpoint Inhibitors in the Treatment of Advanced Pulmonary Neuroendocrine Tumors]

Pulmonary neuroendocrine tumors (PNETs) are a kind of epithelial tumors originating from pulmonary neuroendocrine cells, accounting for about 20% of primary lung tumors, including typical carcinoid, atypical carcinoid, small cell carcinoma, and large cell neuroendocrine carcinoma. The morphologic and clinical characteristics of these four types of PNETs are relatively highly heterogeneous. Immune checkpoint inhibitors (ICIs) have been shown robust antitumor activity in a variety of solid tumors. Treatment regimens of advanced PNETs have developed greatly in the past decade, but ICIs are still in their infancy in the field of PNETs. This review focuses on the landscape of current clinical trials and research as well as the situation of ICIs-related biomarkers in PNETs.
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Management of Large Cell Neuroendocrine Carcinoma

BACKGROUND

Large cell neuroendocrine carcinoma (LCNEC) is a rare, aggressive cancer with a dismal prognosis. The majority of cases occur in the lung and the gastrointestinal tract; however, it can occur throughout the body. Recently advances in the understanding of the molecular underpinnings of this disease have paved the way for additional novel promising therapies. This review will discuss the current best evidence for management of LCNEC and new directions in the classification and treatment of this rare disease.

METHODS

We performed a PubMed search for "Large cell neuroendocrine carcinoma" and "High grade neuroendocrine carcinoma." All titles were screened for relevance to the management of LCNEC. Papers were included based on relevance to the management of LCNEC.

RESULTS

Papers were included reviewing both pulmonary and extra pulmonary LCNEC. We summarized the data driven best practices for the management of both early and advanced stage LCNEC. We describe emerging therapies with promising potential.

DISCUSSION

LCNEC are rare and aggressive neoplasms. In advanced disease, the historical regimen of platinum based therapy in combination with etoposide or irinotecan remains among the commonly used first line therapies, however for extra thoracic LCNEC regimens like FOLFOX, FOLFOIRI and CAPTEM can also be used. Further effective and safe treatment options are desperately needed. Recently, new advances including a new understanding of the genetic subcategories of LCNEC and immunotherapy agents may guide further treatments.

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

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

Large cell neuroendocrine carcinoma (LCNEC) together with small cell carcinoma (SCLC) and typical and atypical carcinoids form the group of pulmonary neuroendocrine tumors. LCNEC and SCLC are high-grade carcinomas. Although both can be found outside the thoracic cavity, they are most common in the lung. LCNEC differs from SCLC by morphologic pattern, and by cytological features such as nuclear size, nucleoli, chromatin pattern, but also by genetic differences. Originally thought to represent a single entity, it became evident, that three subgroups of LCNEC can be identified at the molecular level: a SCLC-like type with loss of retinoblastoma 1 gene (RB1) and TP53 mutations; a non-small cell lung carcinoma (NSCLC)-like type with wildtype RB1, TP53 mutation, and activating mutations of the phosphoinositol-3 kinase (PI3K-CA), or loss of PTEN; and a carcinoid-like type with MEN1 gene mutation. These subtypes can be identified by immunohistochemical staining for RB1, p53, and molecular analysis for PI3K and MEN1 mutations. These subtypes might also respond differently to chemotherapy. Immuno-oncologic treatment has also been applied to LCNEC, however, in addition to the evaluation of tumor cells the stroma evaluation seems to be important. Based on personal experiences with these tumors and available references this review will try to encompass our present knowledge in this rare entity and provoke new studies for better treatment of this carcinoma.

Immune-Checkpoint Inhibitors in Advanced Non-Small Cell Lung Cancer With Uncommon Histology

BACKGROUND

Immune-checkpoint inhibitors (ICIs) have significantly improved outcome of advanced non-small cell lung cancer (aNSCLC) patients. However, their efficacy remains uncertain in uncommon histologies (UH).

MATERIALS AND METHODS

Data from ICI treated aNSCLC patients (April,2013-January,2021) in one Institution were retrospectively collected. Univariate and multivariate survival analyses were estimated by Kaplan-Meier and Cox proportional hazards regression model, respectively. Objective response rate (ORR) and disease control rate (DCR) were assessed.

RESULTS

Of 375 patients, 79 (21.1%) had UH: 19 (24.1%) sarcomatoid carcinoma, 15 (19.0%) mucinous adenocarcinoma, 10 (12.6%) enteric adenocarcinoma, 8 (10.1%) adenocarcinoma not otherwise specified, 7 (8.9%) large-cell neuroendocrine carcinoma, 6 (7.6%) mixed histology non-adenosquamous, 5 (6.3%) adenosquamous carcinoma, 9 (11.4%) other UH. In UH group, programmed death-ligand 1 (PD-L1) <1%, 1-49%, ≥50% and unknown expression were reported in 27.8%, 22.8%, 31.7% and 17.7% patients respectively and ICI was the second/further-line in the majority of patients. After a median follow-up of 35.64 months (m), median progression-free survival (mPFS) was 2.5 m in UH [95% CI 2.2-2.9 m] versus (vs.) 2.7 m in CH [95% CI 2.3-3.2 m, P-value = .584]; median overall survival (mOS) was 8.8 m [95% CI 4.9-12.6 m] vs. 9.7 m [95% CI 8.0-11.3 m, P-value = .653]. At multivariate analyses only ECOG PS was a confirmed prognostic factor in UH. ORR and DCR were 25.3% and 40.5% in UH vs. 21.6% and 49.5% in CH [P-value = .493 and .155 respectively].

CONCLUSIONS

No significant differences were detected between UH and CH groups. Prospective trials are needed to understand ICIs role in UH population.

How can artificial intelligence models assist PD-L1 expression scoring in breast cancer: results of multi-institutional ring studies

Programmed death ligand-1 (PD-L1) expression is a key biomarker to screen patients for PD-1/PD-L1-targeted immunotherapy. However, a subjective assessment guide on PD-L1 expression of tumor-infiltrating immune cells (IC) scoring is currently adopted in clinical practice with low concordance. Therefore, a repeatable and quantifiable PD-L1 IC scoring method of breast cancer is desirable. In this study, we propose a deep learning-based artificial intelligence-assisted (AI-assisted) model for PD-L1 IC scoring. Three rounds of ring studies (RSs) involving 31 pathologists from 10 hospitals were carried out, using the current guideline in the first two rounds (RS1, RS2) and our AI scoring model in the last round (RS3). A total of 109 PD-L1 (Ventana SP142) immunohistochemistry (IHC) stained images were assessed and the role of the AI-assisted model was evaluated. With the assistance of AI, the scoring concordance across pathologists was boosted to excellent in RS3 (0.950, 95% confidence interval (CI): 0.936-0.962) from moderate in RS1 (0.674, 95% CI: 0.614-0.735) and RS2 (0.736, 95% CI: 0.683-0.789). The 2- and 4-category scoring accuracy were improved by 4.2% (0.959, 95% CI: 0.953-0.964) and 13% (0.815, 95% CI: 0.803-0.827) (p < 0.001). The AI results were generally accepted by pathologists with 61% "fully accepted" and 91% "almost accepted". The proposed AI-assisted method can help pathologists at all levels to improve the PD-L1 assay (SP-142) IC assessment in breast cancer in terms of both accuracy and concordance. The AI tool provides a scheme to standardize the PD-L1 IC scoring in clinical practice.

Prevalence and Heterogeneity of PD-L1 Expression by 22C3 Assay in Routine Population-Based and Reflexive Clinical Testing in Lung Cancer

INTRODUCTION

Programmed death-ligand 1 (PD-L1) is used as a biomarker for anti-programmed cell death protein-1 (PD-1) or anti-PD-L1 immunotherapies in NSCLC. We report here the results of population-based PD-L1 testing using the 22C3 IHC pharmDx Assay (Agilent Technologies) in a large Canadian regional reference pathology laboratory.

METHODS

Testing was conducted reflexively on biopsies and resections for NSCLC during an 8-month period. Tumor proportion score (TPS) cutoffs for low and high expression were 1% and 50%, respectively.

RESULTS

Altogether, 2031 PD-L1 tests were performed on specimens from 1795 patients, with 107 inconclusive results (5.3%). Excluding cases with inconclusive/missing data, proportions for the remaining 1713 patients were 41.6% for TPS less than 1%, 28.6% for TPS 1% to 49%, and 29.8% for TPS greater than or equal to 50%. Higher PD-L1 expression rates were noted in EGFR wild-type versus mutant tumors (p < 0.001), squamous versus adenocarcinoma (p < 0.001), and metastatic versus primary tumors (p < 0.001). PD-L1 among 103 patients with paired biopsy and resection specimens revealed moderate concordance (κ = 0.67). A total of 52% (25 of 48) of biopsies with TPS less than 1% had TPS greater than 1% in resection, whereas 84.6% (22 of 26) of biopsies with TPS greater than or equal to 50% were concordant in resected tumors. Discordance rates between biopsy and resection were 71.4% for biopsies with less than 8 mm² total area, compared with 33.3% for biopsies with greater than or equal to 8 mm² area (p < 0.026). Concordance among 27 patients with paired primary lung and metastatic tumor biopsies revealed only weak concordance (κ = 0.48).

CONCLUSIONS

Intratumoral heterogeneity of PD-L1 expression may result in misclassification of PD-L1 status in a substantial proportion of PD-L1-negative small biopsy samples. Biopsy of metastatic site may increase proportion of patients with high PD-L1 expression.

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

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