Insights into Novel Prognostic and Possible Predictive Biomarkers of Lung Neuroendocrine Tumors

Mechanism Research of PZD Inhibiting Lung Cancer Cell Proliferation, Invasion, and Migration based on Network Pharmacology

BACKGROUND

A classic Chinese medicine decoction, Pinellia ternata (Thunb.) Breit.-Zingiber officinale Roscoe (Ban-Xia and Sheng-Jiang in Chinese) decoction (PZD), has shown significant therapeutic effects on lung cancer.

OBJECTIVE

This study aimed to explore and elucidate the mechanism of action of PZD on lung cancer using network pharmacology methods.

METHODS

Active compounds were selected according to the ADME parameters recorded in the TCMSP database. Potential pathways related to genes were identified through GO and KEGG analysis. The compoundtarget network was constructed by using Cytoscape 3.7.1 software, and the core common targets were obtained by protein-protein interaction (PPI) network analysis. Batch molecular docking of small molecule compounds and target proteins was carried out by using the AutoDock Vina program. Different concentrations of PZD water extracts (10, 20, 40, 80, and 160 μg/mL) were used on lung cancer cells. Moreover, MTT and Transwell experiments were conducted to validate the prominent therapeutic effects of PZD on lung cancer cell H1299.

RESULTS

A total of 381 components in PZD were screened, of which 16 were selected as bioactive compounds. The compound-target network consisting of 16 compounds and 79 common core targets was constructed. MTT experiment showed that the PZD extract could inhibit the cell proliferation of NCI-H1299 cells, and the IC50 was calculated as 97.34 ± 6.14 μg/mL. Transwell and wound-healing experiments showed that the PZD could significantly decrease cell migration and invasion at concentrations of 80 and 160 μg/mL, respectively. The in vitro experiments confirmed that PZD had significant therapeutic effects on lung cancer cells, mainly through the PI3K/AKT signaling pathway.

CONCLUSION

PZD could inhibit the cell proliferation, migration, and invasion of NCI-H1299 cells partially through the PI3K/AKT signaling pathway. These findings suggested that PZD might be a potential treatment strategy for lung cancer patients.

Prognostic significance of laterality in lung neuroendocrine tumors

PURPOSE

Well-differentiated lung neuroendocrine tumors (Lu-NET) are classified as typical (TC) and atypical (AC) carcinoids, based on mitotic counts and necrosis. However, prognostic factors, other than tumor node metastasis (TNM) stage and the histopathological diagnosis, are still lacking. The current study is aimed to identify potential prognostic factors to better stratify lung NET, thus, improving patients' treatment strategy and follow-up.

METHODS

A multicentric retrospective study, including 300 Lung NET, all surgically removed, from Italian and Spanish Institutions.

RESULTS

Median age 61 years (13-86), 37.7% were males, 25.0% were AC, 42.0% were located in the lung left parenchyma, 80.3% presented a TNM stage I-II. Mitotic count was ≥2 per 10 high-power field (HPF) in 24.7%, necrosis in 13.0%. Median overall survival (OS) was 46.1 months (0.6-323), median progression-free survival (PFS) was 36.0 months (0.3-323). Female sex correlated with a more indolent disease (T1; N0; lower Ki67; lower mitotic count and the absence of necrosis). Left-sided primary tumors were associated with higher mitotic count and necrosis. At Cox-multivariate regression model, age, left-sided tumors, nodal (N) positive status and the diagnosis of AC resulted independent negative prognostic factors for PFS and OS.

CONCLUSIONS

This study highlights that laterality is an independent prognostic factors in Lu-NETs, with left tumors being less frequent but showing a worse prognosis than right ones. A wider spectrum of clinical and pathological prognostic factors, including TNM stage, age and laterality is suggested. These parameters could help clinicians to personalize the management of Lu-NET.

Prognostic nomogram for predicting long-term survival in bronchopulmonary carcinoid tumor patients receiving resection

Background

We analyzed bronchopulmonary carcinoid tumor (BPC) patients receiving resection from the Surveillance, Epidemiology, and End Results (SEER) database to identify the predictive factors of their survival. Then, we developed and validated nomograms to predict overall survival (OS) and cancer-specific survival (CSS) in BPC patients.

Methods

BPC patients registered in the SEER database were included. They were divided into a training set and an internal validation set (7:3). BPC patients from our center were included as an external validation set. Independent prognostic factors identified by a Cox regression model in the training set were used to construct nomograms to predict survival. Discrimination and calibration plots were used to evaluate the predictive accuracy of the nomograms. The nomograms were evaluated in both the internal and the external validation datasets.

Results

Age, pathological type, and N stage were identified as independent prognostic factors of OS and CSS by Cox analyses (all P<0.05). Tumor size ≥2.5 cm (P=0.045) was an independent factor for unfavorable CSS. Based on these variables, nomograms were constructed. All concordance indexes of the training set, internal validation set, and external validation set indicated that the nomograms had the preferable discriminatory ability. The calibration plots for predictions of the 1-, 3-, and 5-year OS and CSS were in excellent agreement.

Conclusions

Age, pathological type, N stage, and tumor size were independent predictive factors of prognosis in BPC patients receiving resection. These nomograms could serve as effective and accurate tools for the prognostic evaluation of patients with BPCs.

MiRNA Expression in Neuroendocrine Neoplasms of Frequent Localizations

Neuroendocrine neoplasms (NEN) are infrequent malignant tumors of a neuroendocrine nature that arise in various organs. They occur most frequently in the lungs, intestines, stomach and pancreas. Molecular diagnostics and prognosis of NEN development are highly relevant. The role of clinical biomarkers can be played by microRNAs (miRNAs). This work is devoted to the analysis of data on miRNA expression in NENs. For the first time, a search for specificity or a community of their functional characteristics in different types of NEN was carried out. Their properties as biomarkers were also analyzed. To date, more than 100 miRNAs have been characterized as differentially expressed and significant for the development of NEN tumors. Only about 10% of the studied miRNAs are expressed in several types of NEN; differential expression of the remaining 90% was found only in tumors of specific localizations. A significant number of miRNAs have been identified as potential biomarkers. However, only a few miRNAs have values that characterized their quality as markers. The analysis demonstrates the predominant specific expression of miRNA in each studied type of NEN. This indicates that miRNA’s functional features are predominantly influenced by the tissue in which they are formed.

Molecular Pathology of Well-Differentiated Pulmonary and Thymic Neuroendocrine Tumors: What Do Pathologists Need to Know?

Thoracic (pulmonary and thymic) neuroendocrine tumors are well-differentiated epithelial neuroendocrine neoplasms that are classified into typical and atypical carcinoid tumors based on mitotic index cut offs and presence or absence of necrosis. This classification scheme is of great prognostic value but designed for surgical specimens, only. Deep molecular characterization of thoracic neuroendocrine tumors highlighted their difference with neuroendocrine carcinomas. Neuroendocrine tumors of the lung are characterized by a low mutational burden, and a high prevalence of mutations in chromatin remodeling and histone modification-related genes, whereas mutations in genes frequently altered in neuroendocrine carcinomas are rare. Molecular profiling divided thymic neuroendocrine tumors into three clusters with distinct clinical outcomes and characterized by a different average of copy number instability. Moreover, integrated histopathological, molecular and clinical evidence supports the existence of a grey zone category between neuroendocrine tumors (carcinoid tumors) and neuroendocrine carcinomas. Indeed, cases with well differentiated morphology but mitotic/Ki-67 indexes close to neuroendocrine carcinomas have been increasingly recognized. These are characterized by specific molecular profiles and have an aggressive clinical behavior. Finally, thoracic neuroendocrine tumors may arise in the background of genetic susceptibility, being MEN1 syndrome the well-defined familial form. However, pathologists should be aware of rarer germline variants that are associated with the concurrence of neuroendocrine tumors of the lung or their precursors (such as DIPNECH) with other neoplasms, including but not limited to breast carcinomas. Therefore, genetic counseling for all young patients with thoracic neuroendocrine neoplasia and/or any patient with pathological evidence of neuroendocrine cell hyperplasia-to-neoplasia progression sequence or multifocal disease should be considered.

Pulmonary Large-Cell Neuroendocrine Carcinoma: Therapeutic Challenges and Opportunities

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

The challenges of evaluating predictive biomarkers using small biopsy tissue samples and liquid biopsies from non-small cell lung cancer patients

The list of theranostic biomarkers for the care of patients with advanced stage or metastatic non-small cell lung cancer has lengthened considerably these last few years. Moreover, the advances in therapeutics will certainly increase the number and complexity of these tests performed in laboratories in the near future. In addition, the methods for investigation of biomarkers that require access to biological tissue are less and less invasive with the consequential increase in the use of small-sized tissue biopsies and cytological and blood samples. Thus, each laboratory must master the management of the biological samples according to the number and type of tests to be performed. This review will provide an update of the difference challenges facing pathologists and biologist in responding to the issues related to new treatments. These challenges concern: (I) the management of the pre-analytical phase; (II) the appropriate choice of the technological approach; (III) the performance of quality control; (IV) the mastering of the delay in obtaining the results; and (V) the economic model of the laboratory.