Gastric cancers have been historically classified based on histomorphologic features. The Cancer Genome Atlas network reported the comprehensive identification of genetic alterations associated with gastric cancer, identifying four distinct subtypes— Epstein-Barr virus (EBV)-positive, microsatellite-unstable/instability (MSI), genomically stable and chromosomal instability. In particular, EBV-positive and MSI gastric cancers seem responsive to novel immunotherapies drugs. The aim of this review is to describe MSI and EBV positive gastric cancer’s subgroups and their relationship with novel immunotherapy.
Systemic treatment of renal cancer (RCC) has undergone remarkable changes over the past 20 years with the introduction of immunotherapeutic agents targeting programmed cell death (PD-1)/programmed death-ligand 1 (PD-L1) axis, as a single-agent or combined with anti-CTLA-4 monoclonal antibodies (MoAbs) or a multi-target vascular endothelial growth factor-(VEGF) tyrosine kinase inhibitor (TKI). In this paper, we review the main evidence on the use of Immune Checkpoint Inhibitors (ICIs) for RCC treatment from the first demonstration of activity of a nivolumab single agent in a phase I trial to the novel combination strategies (anti-PD-1 plus anti-CTLA4 or anti-PD-1 plus TKI). In addition, we discuss the use of anti-PD-1/PD-L1 agents in patients with non-clear cells and rare histological subtype RCC. Then, we critically examine the current findings in biomarkers that have been proposed to be prognostic or predictive to the response of immunotherapy including immune gene expression signature, B7-H1 expression, PBRM1 loss of function, PD-L1 expression, frame shift indel count, mutations in bromodomain-containing genes in patients with MiT family translocation RCC (tRCC), high expression of the T-effector gene signature, and a high myeloid inflammation gene expression pattern. To date, a single biomarker as a predictor of response has not been established. Since the dynamic behavior of the immune response and the different impact of ICI treatment on patients with specific RCC subtypes, the integration of multiple biomarkers and further validation in clinical trials are needed.
Background: Immune-related adverse events (irAEs) are inflammatory side effects, which can occur during immune-checkpoint(s) inhibitors (ICIs) therapy. Steroids are the first-line agents to manage irAEs because of their immunosuppressive properties. However, it is still debated whether or when steroids can be administered without abrogating the therapeutic efforts of immunotherapy. Methods: We retrospectively evaluated 146 patients with metastatic non-small cell lung cancer (NSCLC), melanoma and renal cell carcinoma (RCC) treated with ICIs. We assessed the progression-free survival (PFS) of patients treated with steroids due to an irAE compared to a no-steroid group. Results: The early treatment with steroid (within the first 30 days from the beginning of immunotherapy) was not related to a shorter PFS (p = 0.077). Interestingly, patients who were treated with steroids after 30 days from the start of immunotherapy had significantly longer PFS (p = 0.017). In a multivariate analysis, treatment with steroids after 30 days was an independent prognostic factor for PFS (HR: 0.59 [95% CI 0.36–0.97], p = 0.037). Conclusions: This retrospective study points out that early systemic steroids administration to manage irAEs might not have a detrimental effect on patient clinical outcome in NSCLC, melanoma and RCC patients.
The application of machine learning (ML) techniques could facilitate the identification of predictive biomarkers of somatostatin analog (SSA) efficacy in patients with neuroendocrine tumors (NETs). We collected data from 74 patients with a pancreatic or gastrointestinal NET who received SSA as first-line therapy. We developed three classification models to predict whether the patient would experience a progressive disease (PD) after 12 or 18 months based on clinic-pathological factors at the baseline. The dataset included 70 samples and 15 features. We initially developed three classification models with accuracy ranging from 55% to 70%. We then compared ten different ML algorithms. In all but one case, the performance of the Multinomial Naïve Bayes algorithm (80%) was the highest. The support vector machine classifier (SVC) had a higher performance for the recall metric of the progression-free outcome (97% vs. 94%). Overall, for the first time, we documented that the factors that mainly influenced progression-free survival (PFS) included age, the number of metastatic sites and the primary site. In addition, the following factors were also isolated as important: adverse events G3–G4, sex, Ki67, metastatic site (liver), functioning NET, the primary site and the stage. In patients with advanced NETs, ML provides a predictive model that could potentially be used to differentiate prognostic groups and to identify patients for whom SSA therapy as a single agent may not be sufficient to achieve a long-lasting PFS.
HERG1 potassium channels are widely expressed in human cancers of different origins, where they affect several key aspects of cellular behaviour. The present study was designed to evaluate the expression and clinical relevance of hERG1 protein in cancer tissues from patients suffering from neuroendocrine tumours (NETs) of ileal (iNETs) and pancreatic (pNETs) origin, with available clinicopathological history and follow-up. The study was carried out by immunohistochemistry with an anti-hERG1 monoclonal antibody. In a subset of samples, a different antibody directed against the hERG1/β1 integrin complex was also used. The analysis showed for the first time that hERG1 is expressed in human NETs originating from either the ileum or the pancreas. hERG1 turned out to have a prognostic value in NETs, showing (i) a statistically significant positive impact on OS of patients affected by ileal NETs, regardless the TNM stage; (ii) a statistically significant positive impact on OS of patients affected by aggressive (TNM stage IV) disease, either ileal or pancreatic; (iii) a trend to a negative impact on OS of patients affected by less aggressive (TNM stage I-III) disease, either ileal or pancreatic. Moreover, in order to evaluate whether ERG1 was functionally expressed in a cellular model of pNET, the INS1E rat insulinoma cell line was used, and it emerged that blocking ERG1 with a specific inhibitor of the channel (E4031) turned out in a significant reduction in cell proliferation.