Expression patterns of novel immunotherapy targets in intermediate- and high-grade lung neuroendocrine neoplasms.

Background: Advancements in immunotherapeutic approaches only had a modest impact on the therapy of lung neuroendocrine neoplasms (LNENs). Our multicenter study aimed to investigate the expression patterns of novel immunotherapy targets in intermediate- and high-grade LNENs.

Methods: The expressions of V-domain Ig suppressor of T cell activation (VISTA), OX40L, Glucocorticoid-induced TNF receptor (GITR), and T cell immunoglobulin and mucin domain 3 (TIM3) proteins were measured by immunohistochemistry in surgically resected tumor samples of 26 atypical carcinoid (AC), 49 large cell neuroendocrine lung cancer (LCNEC), and 66 small cell lung cancer (SCLC) patients.

Computed Tomography-Based Quantitative Texture Analysis and Gut Microbial Community Signatures Predict Survival in Non-Small Cell Lung Cancer.

This study aims to combine computed tomography (CT)-based texture analysis (QTA) and a microbiome-based biomarker signature to predict the overall survival (OS) of immune checkpoint inhibitor (ICI)-treated non-small cell lung cancer (NSCLC) patients by analyzing their CT scans ( = 129) and fecal microbiome ( = 58). One hundred and five continuous CT parameters were obtained, where principal component analysis (PCA) identified seven major components that explained 80% of the data variation. Shotgun metagenomics (MG) and ITS analysis were performed to reveal the abundance of bacterial and fungal species.

[Small cell lung cancer heterogeneity and molecular subtypes: biological and clinical relevance].

Small-cell lung cancer (SCLC) is a highly aggressive malignancy characterised by genomic instability and early metastatic spread. Patients are typically diagnosed at advanced disease stage, when platinum-based chemotherapy with immunotherapy represents the standard therapeutic approach. The role of radiotherapy with concomitant systemic therapy is also well established in the management of SCLC patients.

Comparative expression analysis of immune-related markers in surgically resected lung neuroendocrine neoplasms.

Background: Although immunotherapy has led to a paradigm shift in the treatment of lung cancer, the therapeutic approaches for lung neuroendocrine neoplasms (LNENs) are still limited. Our aim was to explore the immunological landscape and the expression of immune checkpoint markers in LNENs.

Methods: Surgically removed tumor samples of 26 atypical carcinoid (AC), 30 large cell neuroendocrine carcinoma (LCNEC) and 29 small cell lung cancer (SCLC) patients were included.

Candida expansion in the gut of lung cancer patients associates with an ecological signature that supports growth under dysbiotic conditions.

Candida species overgrowth in the human gut is considered a prerequisite for invasive candidiasis, but our understanding of gut bacteria promoting or restricting this overgrowth is still limited. By integrating cross-sectional mycobiome and shotgun metagenomics data from the stool of 75 male and female cancer patients at risk but without systemic candidiasis, bacterial communities in high Candida samples display higher metabolic flexibility yet lower contributional diversity than those in low Candida samples. We develop machine learning models that use only bacterial taxa or functional relative abundances to predict the levels of Candida genus and species in an external validation cohort with an AUC of 78.