[Pulmonary neuroendocrine tumors in the new WHO 2015 classification: Start of breaking new grounds?]

Plasma Progastrin-Releasing Peptide and Chromogranin A Assays for Diagnosing and Monitoring Lung Well-Differentiated Neuroendocrine Tumors: A Brief Report

INTRODUCTION

The use of chromogranin A (CGA) as a circulating biomarker in lung carcinoids (LCs) is limited by low specificity and sensitivity. This study aimed to evaluate plasma progastrin-releasing peptide (ProGRPp) as an alternative to plasma CGA (CGAp), for the diagnosis and follow-up of LC.

METHODS

ProGRPp and CGAp concentrations were measured in 107 patients with LC and 105 patients with benign lung disease (BLD).

RESULTS

ProGRPp distinguished patients with LC with active disease in the pretreatment (n = 43) and post-treatment (n = 43) groups from those with BLD: area under the curve for both 0.864 (p < 0.0001); sensitivity 67.4% and 58.1%, respectively; specificity 96.2%; at 64 pg/mL cutoff. CGAp failed to differentiate both LC groups from those with BLD: area under the curve 0.579 and 0.526 (for both p > 0.1); sensitivity 34.9% and 25.6%, respectively; specificity 73.3%; at 104 ng/mL cutoff. Only ProGRPp correlated with the Ki67 proliferation index (r = 0.40, p < 0.001) and was associated with mitotic count (p = 0.025), stage (p = 0.018), grade (p = 0.019), and the expression of thyroid transcription factor-1 (p = 0.005). ProGRPp had a high sensitivity (92.3%) in LC with diffuse idiopathic pulmonary neuroendocrine cell hyperplasia. Abnormal postoperative ProGRPp level was associated with residual disease (p = 0.029). The changes in ProGRPp level during treatment, a decrease greater than 30% and an increase greater than 8%, were associated with image-based outcomes, partial response and disease progression, respectively (p < 0.0001). CGAp did not reflect the disease course.

CONCLUSIONS

ProGRPp was superior to CGAp in diagnosing LC with correlations concerning proliferation, grading, staging, diffuse idiopathic pulmonary neuroendocrine cell hyperplasia co-occurrence, and response to treatment. ProGRPp is an optimal emerging biomarker to be further evaluated.

Design, synthesis, and biological evaluation of novel HSP27 inhibitors to sensitize lung cancer cells to clinically available anticancer agents

Expression of heat shock protein (HSP) correlates with the oncogenic status of malignant cells and plays an important role in tumorigenesis. HSP27 is constitutively expressed at specific stages of cancer development, and several clinical trials have reported correlations between HSP27 expression and tumor progression, metastasis, and chemoresistance in various types of cancer cells. These findings indicate that HSP27 is a major drug target, particularly in chemo-resistant cancers. As part of our ongoing efforts to improve the previously identified J2, a HSP27 cross-linker, we, in this study, report the identification of NK16 as a novel inducer of abnormal HSP27 dimers that did not affect the expression of HSP90 in an NCI-H460 lung cancer cell model. When NCI-H460 cells were treated with NK16 in combination with the anticancer drug cisplatin or paclitaxel, cleavage of PARP and caspase-3 was increased compared to administration of cisplatin or paclitaxel alone. Similar results were obtained in an NCI-H460-xenografted mouse model, in which tumor growth was suppressed more by co-administration of NK16 and paclitaxel than by paclitaxel alone. We propose NK16 as a meaningful strategy to improve the anticancer efficacy of cisplatin and paclitaxel.

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.

Synergistic alterations in the multilevel chromatin structure anchor dysregulated genes in small cell lung cancer

Small cell lung cancer (SCLC) is an aggressive form of lung cancer that uniquely changes the chromosomal structure, although the basis of aberrant gene expression in SCLC remains largely unclear. Topologically associated domains (TADs) are structural and functional units of the human genome. Genetic and epigenetic alterations in the cancer genome can lead to the disruption of TAD boundaries and may cause gene dysregulation. To understand the potential regulatory role of this process in SCLC, we developed the TAD boundary alteration-related gene identification in tumors (TARGET) computational framework, which enables the systematic identification of candidate dysregulated genes associated with altered TAD boundaries. Using TARGET to compare gene expression profiles between SCLC and normal human lung fibroblast cell lines, we identified >100 genes in this category, of which 24 were further verified in samples from patients with SCLC using NanoString. The analysis revealed synergistic chromatin structure alteration at the A/B compartment and TAD boundary levels that underlies aberrant gene expression in SCLC. TARGET is a novel and powerful tool that can be used to explore the relationship of chromatin structure alteration to gene dysregulation related to SCLC tumorigenesis, progression, and prognosis.

Outcomes of Patients with Pulmonary Large Cell Neuroendocrine Carcinoma in I-IV Stage

Background and Objectives: Large cell neuroendocrine cancer is characterised by poor prognosis. The standard of treatment is still not established. The aim of this study was to assess the predictive factors of overall survival (OS) and progression-free survival (PFS) of pulmonary large cell neuroendocrine carcinoma (LCNEC) and combined LCNEC. Materials and Methods: All patients had confirmed pathology stage I-IV disease recorded between period 2002–2018. Survival curves were estimated by Kaplan–Meier method. Uni- and multivariable analysis was conducted using Cox-regression analysis. Results: A total of 132 patients with LCNEC and combined LCNEC were included. Half of them had clinical stage IIIB/C-IV. Patients were treated with radical (n = 67, including surgery alone; resection with neo-adjuvant or adjuvant chemotherapy, radiochemotherapy, or adjuvant radiotherapy; patients treated with radiochemotherapy alone), palliative (n = 41) or symptomatic (n = 24) intention. Seventeen patients were treated with resection margin R1 or R2. Non-small cell carcinoma (NSCLC) chemotherapy (platinum-vinorelbine; PN schedule) and small-cell lung carcinoma (SCLC) chemotherapy approaches (platinum/carboplatinum-etoposide; PE/KE schedule) were administered in 20 and in 55 patients, respectively. The median (95% Confidence Interval (CI)) OS and PFS were 17 months (9.0–36.2 months) and 7 months (3.0–15.0 months), respectively. Patients treated with negative resection margin, with lower clinical stage, without lymph node metastasis, and with size of primary tumour ≤4 cm showed significantly better OS and PFS. The main risk factors with an adverse effect on survival were advanced CS and positive resection margin. Conclusions: Patients with LCNEC characterized poor prognosis. Independent prognostic factors influencing PFS were initial clinical stage and resection margin R0 vs. R1-2.

Statistical Assessment of Toxic and Essential Metals in the Serum of Female Patients with Lung Carcinoma from Pakistan

Lung cancer (LC) is the number one cancer killer of women both in the USA and around the world. Besides cigarette smoking, an important feature in the etiology of LC is its strong association with exposure of toxic metals. The primary objective of the present investigation was to assess the concentrations of toxic/essential elements (Ni, Ca, Se, Zn, Co, K, Cr, As, Cu, Na, Fe, Hg, Cd, Mg, Mn, and Pb) in the serum samples of LC female patients with female controls by atomic absorption spectrometry after wet-acid digestion procedure. Carcinoembryonic antigen (CEA) was also measured in the serum of the patients using immunoradiometric method. Comparative appraisal of the data revealed that concentrations of Cr, Mg, Cd, Pb, Hg, As, and Ni were noted to be high significantly in serum of LC female patients, while the average Fe, Co, Mn, Na, K, Zn, Ca, and Se were observed at higher levels in female controls (p < 0.05). The correlation study revealed significantly different mutual associations among the elements in the both donor groups. Markedly, variations in the elemental levels were also noted for different types (non-small cell lung cancer and small cell lung cancer) and stages (I, II, III, & IV) of LC patients. Multivariate analyses showed substantially diverse apportionment of the metals in the female patients and female controls. Hence, present findings suggest that the toxic and essential metals accumulated in the body may pose a high risk for LC progression in Pakistani females.

The blood cells in NSCLC and the changes after RFA

Lung cancer has attracted a lot of attention because of its high morbidity and mortality. The emergence of RFA provides a new treatment for unresectable NSCLC patients. In addition to killing in situ lung tumors, RFA also provides new immuno-activated antigens, for the treatment of lung cancer. It changes the tumor microenvironment and activates the entire immune system of patients. The peripheral blood cell count is easy to achieve and the blood cells are important in tumor immunity, which changes after RFA. On the one hand, the changes in blood cells identify the immune changes of NSCLC; on the other hand, it provides support and suspicion for the treatment of RFA.

CT texture analysis of liver metastases in PNETs versus NPNETs: Correlation with histopathological findings

PURPOSE

To compare CT and Texture features of liver metastases in Pancreatic Neuroendocrine Tumors (PNETs) and in Non-Pancreatic Neuroendocrine Tumors (NPNETs) according to tumor grading, overall survival (OS), time to progression (TTP) and Ki67 index.

METHODS

23 patients with PNETs and 25 patients with NPNETs affected by liver metastases were compared. The lesions were G1 and G2 according to WHO classification of tumors. Texture parameters (Mean, Standard Deviation, Entropy, Kurtosis, Skewness, Mean of Positive Pixel) at different spatial scale image filtration (SSF) were evaluated in both arterial and portal phase using a dedicated software for volumetric analysis. All CT images were acquired before the beginning of any medical treatment.

RESULTS

The following significant results (P < 0.05) were found: in the arterial phase for value of Skewness between PNETs G2 and NPNETs G2; in the portal phase between PNETs versus NPNETs, PNETs G1 versus NPNETs G1, PNETs G2 versus NPNETs G2; value of Mean in portal phase in PNETs vs NPNETs. Regarding PNETs, a P < 0.05 was found in: inverse correlation between Entropy and TTP; direct correlation between Mean and OS; correlating Kurtosis and high risk of death; correlating Skewness and low risk of death. Regarding NPNETs, P < 0.05 was found in: inverse correlation between Entropy and OS; correlating Entropy and high risk of dying.

CONCLUSIONS

This study shows that CT texture features are significantly different in PNETs from NPNETs. Additionally, textural features such as Entropy, Kurtosis and Skewness, were found to have significant correlation with higher mortality risk.

An Assessment of Circulating Chromogranin A as a Biomarker of Bronchopulmonary Neuroendocrine Neoplasia: A Systematic Review and Meta-Analysis

BACKGROUND

Management of bronchopulmonary neuroendocrine neoplasia (NEN; pulmonary carcinoids [PCs], small-cell lung cancer [SCLC], and large cell neuroendocrine carcinoma) is hampered by the paucity of biomarkers. Chromogranin A (CgA), the default neuroendocrine tumor biomarker, has undergone wide assessment in gastroenteropancreatic neuroendocrine tumors.

OBJECTIVES

To evaluate CgA in lung NEN, define its clinical utility as a biomarker, assess its diagnostic, prognostic, and predictive efficacy, as well as its accuracy in the identification of disease recurrence.

METHODS

A systematic review of PubMed was undertaken using the preferred reporting items for systematic reviews and meta-analyses guidelines. No language restrictions were applied. Overall, 33 original scientific papers and 3 case reports, which met inclusion criteria, were included in qualitative analysis, and meta-analysis thereafter. All studies, except 2, were retrospective. Meta-analysis statistical assessment by generic inverse variance methodology.

RESULTS

Ten different CgA assay types were reported, without consistency in the upper limit of normal (ULN). For PCs (n = 16 studies; median patient inclusion 21 [range 1-200, total: 591 patients]), the CgA diagnostic sensitivity was 34.5 ± 2.7% with a specificity of 93.8 ± 4.7. CgA metrics were not available separately for typical or atypical carcinoids. CgA >100 ng/mL (2.7 × ULN) and >600 ng/mL (ULN unspecified) were anecdotally prognostic for overall survival (n = 2 retrospective studies). No evidence was presented for predicting treatment response or identifying post-surgery residual disease. For SCLC (n = 19 studies; median patient inclusion 23 [range 5-251, total: 1,241 patients]), the mean diagnostic sensitivity was 59.9 ± 6.8% and specificity 79.4 ± 3.1. Extensive disease typically exhibited higher CgA levels (diagnostic accuracy: 61 ± 2.5%). An elevated CgA was prognostic for overall survival (n = 4 retrospective studies). No prospective studies evaluating predictive benefit or prognostic utility were identified.

CONCLUSION

The available data are scarce. An assessment of all published data showed that CgA exhibits major limitations as an effective and accurate biomarker for either PC or SCLC. Its utility especially for localized PC/limited SCLC (when surgery is potentially curative), is limited. The clinical value of CgA remains to be determined. This requires validated, well-constructed, multicenter, prospective, randomized studies. An assessment of all published data indicates that CgA does not exhibit the minimum required metrics to function as a clinically useful biomarker for lung NENs.

Blood Chromogranin A Is Not Effective as a Biomarker for Diagnosis or Management of Bronchopulmonary Neuroendocrine Tumors/Neoplasms

BACKGROUND

Identification of circulating tumor markers for clinical management in bronchopulmonary (BP) neuroendocrine tumors/neoplasms (NET/NEN) is of considerable clinical interest. Chromogranin A (CgA), a "universal" NET biomarker, is considered controversial as a circulating biomarker of BPNEN.

AIM

Assess utility of CgA in the diagnosis and management of BPNEN in a multicentric study.

MATERIAL AND METHODS

CgA diagnostic metrics were assessed in lung NET/NENs (n = 200) and controls (n = 140), randomly assigned to a Training and Test set (100 BPC and 70 controls in each). Assay specificity was evaluated in neoplastic lung disease (n = 137) and nonneoplastic lung disease (n = 77). CgA efficacy in predicting clinical status was evaluated in the combined set of 200 NET/NENs. CgA levels in bronchopulmonary neuroendocrine tumor (BPNET) subtypes (atypical [AC] vs. typical [TC]) and grade was examined. The clinical utility of an alteration of CgA levels (±25%) was evaluated in a subset of 49 BPNET over 12 months. CgA measurement was by NEOLISATM kit (EuroDiagnostica).

RESULTS

Sensitivity and specificity in the training set were 41/98%, respectively. Test set data were 42/87%. Training set area under receiver operator characteristic analysis differentiated BPC from control area under the curve (AUC) 0.61 ± 0.05 p = 0.015. Test set the data were AUC 0.58 ± 0.05, p = 0.076. In the combined set (n = 200), 67% BPNET/NEN (n = 134) had normal CgA levels. CgA levels did not distinguish histological subtypes (TC vs. AC, AUC 0.56 ± 0.04, p = 0.21), grade (p = 0.45-0.72), or progressive from stable disease (AUC 0.53 ± 0.05 p = 0.47). There was no correlation of CgA with Ki-67 index (Pearson r = 0.143, p = 0.14). For nonneoplastic diseases (chronic obstructive pulmonary disorder and idiopathic pulmonary fibrosis), CgA was elevated in 26-37%. For neoplastic disease (NSCLC, squamous cell carcinoma), CgA was elevated in 11-16%. The neuroendocrine SCLC also exhibited elevated CgA (50%). Elevated CgA was not useful for differentiating BPNET/NEN from these other pathologies. Monitoring BPNET/NEN over a 12-month period identified neither CgA levels per se nor changes in CgA were reflective of somatostatin analog treatment outcome/efficacy or the natural history of the disease (progression).

CONCLUSIONS

Blood CgA levels are not clinically useful as a biomarker for lung BPNET/NEN. The low specificity and elevations in both nonneoplastic as well as other common neoplastic lung diseases identified limited clinical utility for this biomarker.

Identification of lung cancer gene markers through kernel maximum mean discrepancy and information entropy

BACKGROUND

The early diagnosis of lung cancer has been a critical problem in clinical practice for a long time and identifying differentially expressed gene as disease marker is a promising solution. However, the most existing gene differential expression analysis (DEA) methods have two main drawbacks: First, these methods are based on fixed statistical hypotheses and not always effective; Second, these methods can not identify a certain expression level boundary when there is no obvious expression level gap between control and experiment groups.

METHODS

This paper proposed a novel approach to identify marker genes and gene expression level boundary for lung cancer. By calculating a kernel maximum mean discrepancy, our method can evaluate the expression differences between normal, normal adjacent to tumor (NAT) and tumor samples. For the potential marker genes, the expression level boundaries among different groups are defined with the information entropy method.

RESULTS

Compared with two conventional methods t-test and fold change, the top average ranked genes selected by our method can achieve better performance under all metrics in the 10-fold cross-validation. Then GO and KEGG enrichment analysis are conducted to explore the biological function of the top 100 ranked genes. At last, we choose the top 10 average ranked genes as lung cancer markers and their expression boundaries are calculated and reported.

CONCLUSION

The proposed approach is effective to identify gene markers for lung cancer diagnosis. It is not only more accurate than conventional DEA methods but also provides a reliable method to identify the gene expression level boundaries.

[Neuroendocrine tumors : Classification, clinical presentation and imaging]

CONTEXT

Neuroendocrine tumors (NET) are a heterogeneous group of neoplasms found in all organs. They often present with characteristic clinical syndromes due to hormone hypersecretion.

DIAGNOSTICS

In addition to hormone diagnostics molecular-genetic work-up can play an important role.

IMAGING

Morphological imaging comprises ultrasound, endoscopy, computed tomography (CT) and magnetic resonance imaging (MRI) scans. Functional imaging of NET relies on radioligands that bind to specific receptors or transporters (Ga-68-DOTATATE-PET-CT, Tc-99-tektrotyd-SPECT/CT, F‑18-DOPA-PET/CT).

THERAPY

Somatostatin analogs either native or coupled to radionuclides are potent drugs for treating various neuroendocrine tumors.

CONCLUSION

The requirements of imaging are determined by clinical presentation, laboratory findings, tumor stage, the presence of a tumor syndrome and the need of a personalized systemic treatment modality.

[Pulmonary carcinoids and carcinoids of the small intestine]

CLINICAL/METHODICAL ISSUE

Pulmonary carcinoids and carcinoids of the small intestine (jejunum and ileum) are often asymptomatic and can affect various parts of the body, which makes diagnosis difficult.

STANDARD RADIOLOGICAL METHODS

Contrast-enhanced computed tomography (CE-CT) is commonly used for primary diagnostics. In case of concomitant pulmonary consolidation (e.g., atelectasis or pneumonia), tumor lesions can be obscured. In addition, differentiation between atypical (AC) and typical carcinoids (TC) is not possible using CT. Small tumors of the small intestine are easily overlooked (sensitivity: 50-85%, specificity: 25-97%, based on the literature). Additional functional imaging evaluation using hybrid imaging techniques can be applied, e.g., positron emission tomography/computed tomography (PET/CT).

METHODICAL INNOVATIONS/PERFORMANCE

Depending on the histological characteristics of the tumor, PET/CT scans can be performed with different tracers. Since most carcinoids (e.g., TC) express somatostatin receptors (SSR), ⁶⁸ gallium-radiolabeled PET tracers (e.g. ⁶⁸ Ga-DOTA-TOC) are commonly used (sensitivity: 88-93%, specificity: 88-95%, based on the literature). Poorly differentiated carcinoids (e.g., AC) demonstrate lower SSR expression; thus, use of ¹⁸F‑FDG (sensitivity: 37-72%, based on the literature) is indicated. In principle, these methods enable a noninvasive prognostic differentiation based on SSR expression and ¹⁸F‑FDG uptake. However, the diagnosis must always be histologically confirmed.

ACHIEVEMENTS/PRACTICAL RECOMMENDATIONS

Hybrid imaging with CE-CT and PET is useful to detect pulmonary carcinoids and carcinoids of the small intestine, respectively, and can be utilized for primary diagnostics and restaging.

Peptide Receptor Radionuclide Therapy for Pancreatic Neuroendocrine Tumours

Background:

The incidence of pancreatic Neuroendocrine Tumours (pNETs) has increased considerably in the last few decades. The characteristic features of this tumour and the development of new investigative and therapeutic methods had a great impact on its management.

Objective:

The aim of this review is to investigate the outcome of Peptide Receptor Radionuclide Therapy (PRRT) in the treatment of pancreatic neuroendocrine tumours.

Methods:

A comprehensive literature search strategy was used based on two databases (SCOPUS, and PubMed). We considered all studies published in English, evaluating the use of PRRT (177Luteciuim- DOTA-conjugated peptides and 90Yetrium- DOTA- conjugated peptides) in the treatment of pancreatic neuroendocrine tumours as a standalone entity or as a subgroup within the wider category of Gastroenteropancreatic Neuroendocrine Tumours (GEP NETs).

Results:

PRRT was found to be an effective treatment modality as a monotherapy or in combination with other therapies in the treatment of non-operable and metastatic pNETs where other options are limited. Complete response was reported to be between 2-6% while partial response was achieved in up to 60% of cases. Survival analysis was also impressive. Progression Free Survival (PFS) reached a mean of 34 months and Overall Survival (OS) of 53 months. PRRT also proved to improve patients’ Quality of Life (QoL). Acute and sub-acute side effects like nephrotoxicity and haematotoxicity are usually mild and reversible.

Conclusion:

PRRT is well tolerated and effective treatment option for non-operable and/or metastatic pNETs. Side effects are usually mild and reversible. Larger randomized controlled trails need to be done to compare PRRT with other treatment modalities and to provide more detailed guidelines regarding patient selections, the choice of PRRT, follow up and response assessment to maximum potential benefit.

Automated quantification of Ki-67 index associates with pathologic grade of pulmonary neuroendocrine tumors

Background:

Classification of the pulmonary neuroendocrine tumor (pNET) categories is a step-wise process identified by the presence of necrosis and number of mitoses per 2 mm². In neuroendocrine tumor pathology, Ki-67 was first described as a prognostic factor in the pancreas and incorporated into the grading system of digestive tract neuroendocrine neoplasms in the 2010 WHO classification. However, the significance of Ki-67 in pNETs was still a controversial issue. This study was to investigate the potentially diagnostic value of Ki-67 in pNETs.

Methods:

We retrieved 159 surgical specimens of pNETs, including 35 typical carcinoids (TCs), 2 atypical carcinoid (ACs), 28 large-cell neuroendocrine carcinomas (LCNECs), 94 small-cell lung cancers (SCLCs). Manual conventional method (MCM) and computer-assisted image analysis method (CIAM) were used to calculate the Ki-67 proliferative index. In CIAM, 6 equivalent fields (500 × 500 μm) at 10× magnification were manually annotated for digital image analysis.

Results:

The Ki-67 index among the 4 groups with ranges of 0.38% to 12.66% for TC, 4.34% to 29.48% for AC, 30.67% to 93.74% for LCNEC, and 40.71% to 96.87% for SCLC. The cutoff value of Ki-67 index to distinguish low grade with high grade was 30.07%. For the univariate survival analyses in pNETs, both the overall survival and progression-free survival correlated with Ki-67 index. In addition, the Ki-67 index performed by CIAM was proved to be of great positive correlation with MCM.

Conclusions:

Ki-67 index counted by CIAM is a reliable method and can be a useful adjunct to classify the low- and high-grade NETs.

Cross-talk between lung cancer and bones results in neutrophils that promote tumor progression

Lung cancer is the leading cause of cancer mortality around the world. The lack of detailed understanding of the cellular and molecular mechanisms participating in the lung tumor progression restrains the development of efficient treatments. Recently, by using state-of-the-art technologies, including in vivo sophisticated Cre/loxP technologies in combination with lung tumor models, it was revealed that osteoblasts activate neutrophils that promote tumor growth in the lung. Strikingly, genetic ablation of osteoblasts abolished lung tumor progression via interruption of SiglecF^high-expressing neutrophils supply to the tumor microenvironment. Interestingly, SiglecF^high neutrophil signature was associated with worse lung adenocarcinoma patients outcome. This study identifies novel cellular targets for lung cancer treatment. Here, we summarize and evaluate recent advances in our understanding of lung tumor microenvironment.

Characteristics of 252 patients with bronchopulmonary neuroendocrine tumours treated at the Copenhagen NET Centre of Excellence

BACKGROUND

Bronchopulmonary neuroendocrine tumours are divided into typical carcinoid (TC), atypical carcinoid (AC), large cell neuroendocrine carcinoma (LCNEC), and small cell lung cancer (SCLC).

AIM

To thoroughly describe a cohort of 252 patients with TC, AC and LCNEC (SCLC excluded).

MATERIAL AND METHODS

Collection of data from 252 patients referred to and treated at Rigshospitalet 2008-2016. Data was collected from electronic patient files and our prospective NET database. Statistics were performed in SPSS.

RESULTS

162 (64%) had TC, 29 (12%) had AC and 61 (24%) had LCNEC. Median age at diagnosis was 69 years (range: 19-89) with no difference between genders. Thoraco-abdominal CT was performed in all patients at diagnosis. FDG-PET/CT was performed in 207 (82%) at diagnosis and was positive in 95% of the entire cohort, with no difference between tumour types. Synaptophysin was positive in 98%, chromogranin A in 92% and CD56 in 97%. Mean Ki67 index was 5% in TC, 16% in AC and 69% in LCNEC (p < 0.001). Metastatic disease was found in 4% of TC, 27% of AC and 58% of LCNEC at time of initial diagnosis (p < 0.001). In total 179 patients (71%) underwent surgical resection; TC: 87%, AC: 72% and LCNEC: 28% (p < 0.001). Of the resected patients, 11 (6%) had recurrence. Five-year survival rate was 88% for TC, 63% for AC and 20% for LCNEC.

CONCLUSION

In this comprehensive study of a cohort of 252 patients, one of the largest until date, with TC, AC and LCNEC, the gender distribution showed female predominance with 68%. FDG-PET/CT was positive in 95% of the patients independent of tumour type, which confirms that FDG-PET/CT should be a part of the preoperative work-up for TC, AC and LCNEC. Tumour type was the single most potent independent prognostic factor.

ECM-CSD: An Efficient Classification Model for Cancer Stage Diagnosis in CT Lung Images Using FCM and SVM Techniques

As is eminent, lung cancer is one of the death frightening syndromes among people in present cases. The earlier diagnosis and treatment of lung cancer can increase the endurance rate of the affected people. But, the structure of the cancer cell makes the diagnosis process more challenging, in which the most of the cells are superimposed. By adopting the efficient image processing techniques, the diagnosis process can be made effective, earlier and accurate, where the time aspect is extremely decisive. With those considerations, the main objective of this work is to propose a region based Fuzzy C-Means Clustering (FCM) technique for segmenting the lung cancer region and the Support Vector Machine (SVM) based classification for diagnosing the cancer stage, which helps in clinical practice in significant way to increase the morality rate. Moreover, the proposed ECM-CSD (Efficient Classification Model for Cancer Stage Diagnosis) uses Computed Tomography (CT) lung images for processing, since it poses higher imaging sensitivity, resolution with good isotopic acquisition in lung nodule identification. With those images, the pre-processing has been made with Gaussian Filter for smoothing and Gabor Filter for enhancement. Following, based on the extracted image features, the effective segmentation of lung nodules is performed using the FCM based clustering. And, the stages of cancer are identified based on the SVM classification technique. Further, the model is analyzed with MATLAB tool by incorporating the LIDC-IDRI lung CT images clinical dataset. The comparative experiments show the efficiency of the proposed model in terms of the performance evaluation factors like increased accuracy and reduced error rate.

Comparative evaluation of three proliferation markers, Ki-67, TOP2A, and RacGAP1, in bronchopulmonary neuroendocrine neoplasms: Issues and prospects

The classification of bronchopulmonary neuroendocrine neoplasms (BP-NEN) into four tumor entities (typical carcinoids (TC), atypical carcinoids (AC), small cell lung cancers (SCLC), large cell neuroendocrine lung carcinomas (LCNEC)) is difficult to perform accurately, but important for prognostic statements and therapeutic management decisions. In this regard, we compared the expression of three proliferation markers, Ki-67, Topoisomerase II alpha (TOP2A), and RacGAP1, in a series of tumor samples from 104 BP-NEN patients (24 TC, 21 AC, 52 SCLC, 7 LCNEC) using different evaluation methods (immunohistochemistry (IHC): Average evaluation, Hotspot evaluation, digital image analysis; RT-qPCR).

The results indicated that all three markers had increased protein and mRNA expression with poorer differentiation and correlated well with each other, as well as with grading, staging, and poor survival. Compared with Ki-67 and TOP2A, RacGAP1 allowed for a clearer prognostic statement. The cut-off limits obtained for Ki-67-Average (IHC) were TC-AC 1.5, AC-SCLC 19, and AC-LCNEC 23.5. The Hotspot evaluation generated equal to higher, the digital image analysis generally lower between-entity cut-off limits.

All three markers enabled a clear-cut differentiation between the BP-NEN entities, and all methods evaluated were suitable for marker assessment. However, to define optimal cut-off limits, the Ki-67 evaluation methods should be standardized. RacGAP1 appeared to be a new marker with great potential.

A liquid biopsy for bronchopulmonary/lung carcinoid diagnosis

No effective blood biomarker exists to detect and clinically manage bronchopulmonary (BP) neuroendocrine tumors (NET). We developed a blood-based 51 NET-specific transcript set for diagnosis and monitoring and evaluated clinical performance metrics. It accurately diagnosed the tumor and differentiated stable from progressive disease as determined by RECIST criteria. Gene expression was evaluated in: a) publicly available BPNET transcriptomes (GSE35679); b) two BPNET cell-lines; and c) BPNET tissue with paired blood (n = 7). Blood gene expression was assessed in 194 samples including controls, benign lung diseases, malignant lung diseases and small bowel NETs. A separate validation study in 25 age- and gender-matched BPNETs/controls was performed. Gene expression measured by real-time PCR was scored (0–100%; normal: < 14%). Regression analyses, Principal Component Analysis (PCA), hierarchical clustering, Fisher's and non-parametric evaluations were undertaken. All 51 genes were identified in BPNET transcriptomes, tumor samples and cell-lines. Significant correlations were evident between paired tumor and blood (R2:0.63–0.91, p < 0.001). PCA and hierarchical clustering identified blood gene expression was significantly different between lung cancers and benign diseases, including BPNETs. Gene expression was highly correlated (R²: 0.91, p = 1.7 × 10-¹⁵) between small bowel and BPNET. For validation, all 25 BPNETs were positive compared to 20% controls (p < 0.0001). Scores were significantly elevated (p < 0.0001) in BPNETs (57 ± 28%) compared to controls (4 ± 5%). BPNETs with progressive disease (85 ± 11%) exhibited higher scores than stable disease (32 ± 7%, p < 0.0001). Blood measurements accurately diagnosed bronchopulmonary carcinoids, distinguishing stable from progressive disease. This marker panel will have clinical utility as a diagnostic liquid biopsy able to define disease activity and progression in real-time.

Current and Prospective Protein Biomarkers of Lung Cancer

Lung cancer is a malignant lung tumor with various histological variants that arise from different cell types, such as bronchial epithelium, bronchioles, alveoli, or bronchial mucous glands. The clinical course and treatment efficacy of lung cancer depends on the histological variant of the tumor. Therefore, accurate identification of the histological type of cancer and respective protein biomarkers is crucial for adequate therapy. Due to the great diversity in the molecular-biological features of lung cancer histological types, detection is impossible without knowledge of the nature and origin of malignant cells, which release certain protein biomarkers into the bloodstream. To date, different panels of biomarkers are used for screening. Unfortunately, a uniform serum biomarker composition capable of distinguishing lung cancer types is yet to be discovered. As such, histological analyses of tumor biopsies and immunohistochemistry are the most frequently used methods for establishing correct diagnoses. Here, we discuss the recent advances in conventional and prospective aptamer based strategies for biomarker discovery. Aptamers like artificial antibodies can serve as molecular recognition elements for isolation detection and search of novel tumor-associated markers. Here we will describe how these small synthetic single stranded oligonucleotides can be used for lung cancer biomarker discovery and utilized for accurate diagnosis and targeted therapy. Furthermore, we describe the most frequently used in-clinic and novel lung cancer biomarkers, which suggest to have the ability of differentiating between histological types of lung cancer and defining metastasis rate.

Everolimus in the treatment of neuroendocrine tumors of the respiratory and gastroenteropancreatic systems

Neuroendocrine tumors (NETs) are a rare diverse group of malignancies occurring most commonly in the gastroenteropancreatic system and the lungs. The incidence of NETs is increasing worldwide; median survival for patients with metastatic NETs is 5–65 months. A growing body of evidence shows survival benefit in patients with advanced NETs (gastroenteropancreatic and lung) treated with mTOR inhibitor everolimus, with improvement in survival being demonstrated in the clinical trial and real-world setting. Everolimus has been shown to have a manageable safety profile, with the most common adverse events being stomatitis, rash, diarrhea, fatigue and infections. Due to the rarity of the condition, there are challenges in conducting clinical trials in these patients. Further research is required to clarify the role of adjuvant therapy, treatment sequencing and the use of multimodality treatments.

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

OBJECTIVES

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

MATERIALS AND METHODS

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

RESULTS

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

CONCLUSION

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

Prognostic value of PD-L1 and PD-1 expression in pulmonary neuroendocrine tumors

PURPOSE

Programmed death 1 (PD-1) receptor and its ligand, programmed death ligand-1 (PD-L1), play critical roles in the immune invasion of various tumors. This study aimed to explore the clinical significance of PD-L1/PD-1 expression in the progression of pulmonary neuroendocrine tumors (PNETs).

METHODS

The expression of PD-L1 and PD-1 in 80 patients diagnosed with PNETs were investigated. Immunohistochemical analysis was performed on 80 formalin-fixed paraffin-embedded tissue specimens from PNETs and 20 corresponding cancer-adjacent tissue specimens.

RESULTS

Tissues from PNETs had higher levels of PD-L1 (58.8%) and PD-1 (51.3%) compared to the cancer-adjacent tissues (25% and 20%, respectively). Meanwhile, PD-L1 expression was associated with PD-1 expression (P=0.007). PD-L1 expression was significantly associated with histological type (P=0.014) and tumor stage (P=0.014). Univariate analyses showed that the overall survival time of PNETs patients was significantly associated with PD-L1 expression in cancer cells (P=0.003), PD-1 expression in tumor-infiltrating lymphocytes (P=0.001), tumor node metastasis stage (P<0.05), and distant metastasis (P<0.001). Additionally, multivariate analysis revealed that PD-L1 expression, PD1 expression, and distant metastasis of PNETs were independently associated with survival time. Moreover, Kaplan-Meier survival curves analysis revealed that patients with negative PD-L1 and PD-1 expression had better prognoses.

CONCLUSION

Data suggested that PD-L1 and PD-1 can be useful prognostic biomarkers for survival and can pave the way toward new immunotherapy regimens against PNETs through targeting the PD-L1/PD-1 pathway.