Purpose: Immune-checkpoint inhibitors (ICI) have improved the survival of patients with non–small cell lung cancer (NSCLC). However, only a subset of patients benefit from ICIs, and the role of PD-L1 as predictive biomarker is still debated. A plasma immune-related miRNA-signature classifier (MSC) was established in lung cancer screening settings to identify the lethal form of the disease in early stages. In this exploratory study, we tested the efficacy of the MSC as prognostic marker in patients with advanced NSCLC treated with ICIs. Experimental Design: The MSC risk level was prospectively assessed in a consecutive series of 140 patients with NSCLC before starting treatment with ICIs. Overall response rate (ORR), progression-free survival (PFS), and overall survival (OS) in strata of PD-L1 and MSC alone or combined were considered as endpoints. Multiple plasma samples to monitor MSC risk level during treatment were also profiled. Results: Adequate tissue and plasma samples were available from 111 (79%) and 104 (75%) patients with NSCLC, respectively. MSC risk level was associated with ORR (P = 0.0009), PFS [multivariate HR = 0.31; 95% confidence interval (CI), 0.17–0.56; P = 0.0001], and OS (multivariate HR = 0.33; 95% CI, 0.18–0.59; P = 0.0002). The combination of MSC and PD-L1 stratified patients into three risk groups having 39%–18%–0% 1-year PFS (P < 0.0001) and 88%–44%–0% 1-year OS (P < 0.0001), according to the presence of 2–1–0 favorable markers. During treatment, MSC risk level decreased or remained low until tumor progression in patients with responsive or stable disease. Conclusions: The plasma MSC test could supplement PD-L1 tumor expression to identify a subgroup of patients with advanced lung cancer with worse ORR, PFS, and OS in immunotherapy regimens.

The prognostic value of Toll-like receptor 3 (TLR3) is debated in cancer, differing between tumor types, methods, and cell types. We recently showed for the first time that TLR3 expression on early stage non-small-cell lung cancer (NSCLC) results associated with a good prognosis. Here, we provide experimental evidences explaining the molecular reason behind TLR3’s favorable prognostic role. We demonstrated that TLR3 activation in vitro induces apoptosis in lung cancer cell lines and, accordingly, that TLR3 expression is associated with caspase-3 activation in adenocarcinoma NSCLC specimens, both evaluated by immunohistochemistry. Moreover, we showed that TLR3 expression on cancer cells contributes to activate the CD103+ lung dendritic cell subset, that is specifically associated with processing of antigens derived from apoptotic cells and their presentation to CD8+ T lymphocytes. These findings point to the relevant role of TLR3 expression on lung cancer cells and support the use of TLR3 agonists in NSCLC patients to re-activate local innate immune response.

Lung cancer is the most frequent cause of cancer-related death worldwide, with limited therapeutic options and rapid development of drug resistance. MicroRNAs, a class of small non-coding RNAs that control different physiological processes, have been associated with cancer development, as either oncomiRNAs or tumor-suppressor miRNAs. In the present study we investigated the interaction between mir-486-5p and mir-660-5p, two independent tumor-suppressor miRNAs, to assess their possible role and synergistic effect in lung cancer treatment. Our data show that mir-660-5p over-expression in A549 lung cancer cells induced a remarkable increase in mir-486-5p expression level and activity, detected as a reduction of its target gene, p85. mir-486-5p expression was confirmed by microRNA in situ hybridization. mir-660-5p modulated mir-486-5p through the silencing of Mouse Double Minute 2 (MDM2), one of its direct target, and then through p53 stimulation. This regulatory pathway was effective in A549, but not in H1299; therefore, only in the context of a functional p53 protein. Our findings support the conclusion that mir-486-5p is positively regulated by mir-660-5p in lung cancer cell lines, through the mir-660-MDM2-p53 pathway, making mir-660-5p even more interesting for its potential successful use in lung cancer therapy.

Neuroendocrine neoplasms (NENs) are rare neoplasms with heterogeneous clinical behavior. Alteration in human microbiota was reported in association with carcinogenesis in different solid tumors. However, few studies addressed the role of microbiota in NEN. We here aimed at evaluating the presence of bacterial infiltration in neuroendocrine tumoral tissue. To assess the presence of bacteria, 20 specimens from pancreatic NEN (pan-NEN) and 20 from intestinal NEN (I-NEN) were evaluated through Fluorescent In situ Hybridization and confocal microscopy. Demographic data, pre-operative investigations, operative findings, pathological diagnosis, follow-up, and survival data were evaluated. Among I-NEN, bacteria were detected in 15/20 (75%) specimens, with high variability in microbial distribution. In eight patients, a high infiltration of microorganisms was observed. Among pan-NEN, 18/20 (90%) showed microorganisms’ infiltration, with a homogeneous microbial distribution. Bacterial localization in pan-NEN was observed in the proximity of blood vessels. A higher bacterial infiltration in the tumoral specimen as compared with non-tumoral tissue was reported in 10/20 pan-NEN (50%). No significant differences were observed in mean bacterial count according to age, sex, ki67%, site, tumor stage. Mean bacterial count did not result to be a predictor of disease-specific survival. This preliminary study demonstrates the presence of a significant microbiota in the NEN microenvironment. Further research is needed to investigate the potential etiological or clinical role of microbiota in NEN.

Six thoracic pathologists reviewed 259 lung neuroendocrine tumours (LNETs) from the lungNENomics project, with 171 of them having associated survival data. This cohort presents a unique opportunity to assess the strengths and limitations of current World Health Organization (WHO) classification criteria and to evaluate the utility of emerging markers. Patients were diagnosed based on the 2021 WHO criteria, with atypical carcinoids (ACs) defined by the presence of focal necrosis and/or 2-10 mitoses per 2 mm². We investigated two markers of tumour proliferation: the Ki-67 index and phospho-histone H3 (PHH3) protein expression, quantified by pathologists and automatically via deep learning. Additionally, an unsupervised deep learning algorithm was trained to uncover previously unnoticed morphological features with diagnostic value. The accuracy in distinguishing typical from ACs is hampered by interobserver variability in mitotic counting and the limitations of morphological criteria in identifying aggressive cases. Our study reveals that different Ki-67 cut-offs can categorise LNETs similarly to current WHO criteria. Counting mitoses in PHH3+ areas does not improve diagnosis, while providing a similar prognostic value to the current criteria. With the advantage of being time efficient, automated assessment of these markers leads to similar conclusions. Lastly, state-of-the-art deep learning modelling does not uncover undisclosed morphological features with diagnostic value. This study suggests that the mitotic criteria can be complemented by manual or automated assessment of Ki-67 or PHH3 protein expression, but these markers do not significantly improve the prognostic value of the current classification, as the AC group remains highly unspecific for aggressive cases. Therefore, we may have exhausted the potential of morphological features in classifying and prognosticating LNETs. Our study suggests that it might be time to shift the research focus towards investigating molecular markers that could contribute to a more clinically relevant morpho-molecular classification.