Search

BACKGROUND:Programmed cell death ligand-1 (PD-L1) expression on tumor cells (TCs) is associated with improved survival in patients with head and neck squamous cell carcinoma (HNSCC) treated with immunotherapy, although its role as a prognostic factor is controversial. This study investigates whether tumoral expression of PD-L1 is a prognostic marker in patients with recurrent and/or metastatic (R/M) HNSCC treated with standard chemotherapy. METHODS:This retrospective, multicenter, noninterventional study assessed PD-L1 expression on archival R/M HNSCC tissue samples using the VENTANA PD-L1 (SP263) Assay. PD-L1 high was defined as PD-L1 staining of ≥ 25% TC, with exploratory scoring at TC ≥ 10% and TC ≥ 50%. The primary objective of this study was to estimate the prognostic value of PD-L1 status in terms of overall survival (OS) in patients with R/M HNSCC. RESULTS:412 patients (median age, 62.0 years; 79.9% male; 88.2% Caucasian) were included from 19 sites in seven countries. 132 patients (32.0%) had TC ≥ 25% PD-L1 expression; 199 patients (48.3%) and 85 patients (20.6%) had TC ≥ 10% and ≥ 50%, respectively. OS did not differ significantly across PD-L1 expression (at TC ≥ 25% cutoff median OS: 8.2 months vs TC

Introduction In advanced basal cell carcinoma (BCC), the issue of whether Hedgehog inhibitors (HHIs) should be stopped or not after clinical complete response (cCR) achievement remains an unmet clinical need. Materials and Methods We conducted a retrospective, multicenter study across 7 Italian dermato-oncology units including patients with BCC who continued vismodegib after cCR between 2012 and 2019. We assessed the relationship between the duration of vismodegib intake (days to cCR [DTCR], days to stop after cCR [DTS], total treatment days [TTD]), and disease-free survival (DFS). Reasons to stop vismodegib were (R1) toxicity and (R2) disease recurrence. The relationship between DTCR, DTS, TTD, and DFS in the whole population and in R1 subgroup was assessed by Pearson's correlation coefficient (P  < .05) and Bayesian statistics (BF10). Results Sixty-eight BCC patients with a median (m) age of 75.5 years (39-100) were included. Most patients were male (N  = 43, 63%), without Gorlin syndrome (N  = 56, 82%) and with head and neck area as primary site (N  = 51, 75%). After cCR, out of 68 patients, 90% (N = 61/68) discontinued vismodegib: 82% (N  = 50/61) due to toxicity (R1), and 18% (N  = 11/61) due to recurrence (R2). Conversely, 10% (N  = 7/68) continued vismodegib until last follow-up. In the whole population (N  = 68), cCR was achieved with a mDTCR of 180.50 days. DFS showed a significant correlation with DTS (P  < .01, BF10 = 39.2) and TTD (P  < .01, BF10 = 35566), while it was not correlated to DTCR (BF10 < 0.1). The analysis of R1 subgroup (N  = 50) confirmed these results. DFS correlated with DTS in all recurrent patients (N  = 38, r  = 0.44, P  < .01) and in the recurrent patients who stopped vismodegib for toxicity (N  = 26, r  = 0.665, P  < .01). DFS was longer when vismodegib was maintained for >2 months after cCR (mDFS > 2 months, N  = 54 vs. ≤ 2 months, N  = 14: 470 vs. 175 d, P  < .01). Conclusions Our retrospective results suggest that HHIs should be continued after cCR to improve DFS in BCC. [ABSTRACT FROM AUTHOR]

Epstein-Barr virus (EBV)-related nasopharyngeal carcinoma (NPC) is an epithelial malignancy arising from the nasopharyngeal mucosal lining. A high incidence was recorded in EBV-endemic areas (EA) such as East and Southeast Asia [1] while in Europe, a non-endemic area (NEA), is low (1/105/year); however, the estimated survival rate is much lower than that recorded in Asian EA (5-year age-standardized relative survival = 54–57% vs. 74%) [2]. Risk factors of NPC include genetic, ethnic and environmental factors [3]. Differences in incidence and survival rates between EA and NEA NPCs could involve several factors, including EBV-related factors, genetic susceptibility of the population to EBV infections, and environmental factors such as diet and pollution [4-7]. Nevertheless, all proposed models of NPC pathogenesis are based on data derived from EA in Asia. Furthermore, clinical, pathogenic, and microenvironmental characteristics may play additional roles. EBV-related NPC in EA has already been characterized using genomic and transcriptomic data analysis [8-9]. However, gene expression analysis data [10] of NEA NPC is limited. Comparing gene expression data from EA and NEA diseases allows the recognition of similarities and differences in incidence and outcome among diseases arising in different geographical areas. We investigated the transcriptomic patterns of genes involved in EA NPC to interpret these differences and verifying them to an Italian cohort with available tumor tissue and clinical data. The immune and biological/functional characterization of EA and NEA NPC could improve the identification of new therapeutic strategies. Currently, the treatment for localized NPC includes radiotherapy, which is often combined with platinum-based chemotherapy, especially for locally advanced cancer. Neoadjuvant chemotherapy with cisplatin and gemcitabine was administered in the case of high-risk disease [11 -12]. Immunotherapy with checkpoint inhibitors has shown clinical efficacy in recurrent/metastatic advanced NPC and is currently under evaluation to define its mechanism of action [13]. Our study aimed to dissect the gene expression (GE) and microenvironment of NPC, leading to the identification of the molecular subtypes of EA and NEA NPC. We also aimed to elucidate the biological and functional differences within EA NPC and between EA NPC and NEA NPC to eventually provide new insights into novel treatment strategies. Six GE datasets of NPC-EA transcriptomic repositories, including tumor and normal samples (GSE12452, GSE34573, GSE132112, GSE53819, GSE68799, GSE102349) and one validation dataset including both EA and NEA (https://doi.org/10.5281/zenodo.5347891) were retrieved. Four GE signatures associated to EBV related NPC prognosis (PMID: 24297049, 35262435, 32596151, 33096113), genes/pathways and gene sets (PMID: 35846746, 35394843, 35105963) were applied on EA and NEA NPC cohorts (Liu_NPC, Wood EBV EBNA1 Targets Down, Sengupta NPC_with LMP1 UP, REACTOME DNA Repair; Hallmarks). A bioinformatic meta-analysis approach was used to integrate the six EA datasets, and the classifier method was applied to the validation dataset in order to identify the subtype with worst prognosis. Moreover, RNA sequencing was performed on 50 Italian NEA NPC samples (study number: INT188/19; GSE208281). Biological and functional profiling of EA and NEA were performed using xCell, Gene set enrichment analyses, and treatment prediction methods (radiosensitivity index PMID: 16103067, pRRophetic R package, Immunophenoscore PMID: 28052254). Through the meta-analysis of EA-NPC datasets, four clusters (Cl) were identified. Prognostic analyses revealed that Cl3 had the worst prognosis (P=0.0476), confirmed by three of the four prognostic signatures and in the validation dataset (P=0.0368). The biological and functional characterization of these clusters disclosed the relative GE subtypes: Cl1, Immune-active; Cl2, Defense-response; Cl3, Proliferation;Cl4, Perineural-interaction/EBV-exhaustion. According to the treatment prediction methods, the sensitivity of each cluster was radiotherapy and immunotherapy for immune-active, radiochemotherapy and immunotherapy for defense-response, chemotherapy for proliferation, and cisplatin treatment for perineural-interaction/EBV-exhaustion. Only three clusters, excluding perineural-interaction/EBV-exhaustion, were expressed in our NEA cohort. Immune/biological characterization and treatment prediction analyses of NEA partially replicated the EA results. Our study provides a relevant biological overview of EBV-related NPC in both EA and NEA. The immune microenvironment plays a critical role in NPC owing to the viral etiology of this malignancy. The presence of a perineural-interaction/EBV-exhaustion cluster in EA suggests an inactive EBV infection according to the viral related "hit and run theory". Evaluation of miRNAs is ongoing along with miRNA/gene expression integration. Well characterized EA- and NEA-NPC retrospective and prospective cohorts are needed to validate the obtained results and can help designing future clinical studies. [ABSTRACT FROM AUTHOR]

Background: The head and neck cancers (HNCs) incidence differs between Europe and East Asia. Our objective was to determine whether survival of HNC also differs between European and Asian countries. Methods: We used population-based cancer registry data to calculate 5-year relative survival (RS) for the oral cavity, hypopharynx, larynx, nasal cavity, and major salivary gland in Europe, Taiwan, and Japan. We modeled RS with a generalized linear model adjusting for time since diagnosis, sex, age, subsite, and histological grouping. Analyses were performed using federated learning, which enables analyses without sharing sensitive data. Findings: Five-year RS for HNC varied between geographical areas. For each HNC site, Europe had a lower RS than both Japan and Taiwan. HNC subsites and histologies distribution and survival differed between the three areas. Differences between Europe and both Asian countries persisted even after adjustments for all HNC sites but nasal cavity and paranasal sinuses, when comparing Europe and Taiwan. Interpretation: Survival differences can be attributed to different factors including different period of diagnosis, more advanced stage at diagnosis, or different availability/access of treatment. Cancer registries did not have stage and treatment information to further explore the reasons of the observed survival differences. Our analyses have confirmed federated learning as a feasible approach for data analyses that addresses the challenges of data sharing and urge for further collaborative studies including relevant prognostic factors. [ABSTRACT FROM AUTHOR]

Basal cell carcinoma (BCC) and cutaneous squamous cell carcinoma (cSCC) are the most frequent cancers in humans, with cumulative ultraviolet radiation exposure, aging, and immunodepression as the main risk factors. In most cases, these malignancies arise in the head and neck area, and they can be treated with locoregional therapies. A minority of cases require systemic therapy. Currently, Sonic Hedgehog inhibitors (i.e., vismodegib and sonidegib) have been approved for advanced BCC, while the PD-1 checkpoint inhibitor cemiplimab has been approved as a first-line treatment for cSCC and as a second-line treatment for BCC. Nevertheless, there is a clinical need for an effective and safe systemic therapies for advanced synchronous (syn) BCC/cSCC not amenable to local treatments. International guidelines do not provide specific recommendations for patients affected by this condition, and no case reports on the full-dose association of these medications have been previously reported. Here, we present the cases of two elderly patients affected by synBCC/cSCC of the head and neck, who received combined therapy with cemiplimab and sonidegib at full dose and standard schedule, achieving remarkable clinical benefit and long-term responses, without major adverse events. The instance of a feasible treatment for patients with advanced synBCC/cSCC will become increasingly frequent with the advancement of life expectancy in the global population, and the synergistic activity of targeted therapies and immunotherapy —administered either in association or sequentially—deserves to be further explored. [ABSTRACT FROM AUTHOR]

Patients surviving head and neck cancer (HNC) suffer from high physical, psychological, and socioeconomic burdens. Achieving cancer-free survival with an optimal quality of life (QoL) is the primary goal for HNC patient management. So, maintaining lifelong surveillance is critical. An ambitious goal would be to carry this out through the advanced analysis of environmental, emotional, and behavioral data unobtrusively collected from mobile devices. The aim of this clinical trial is to reduce, with non-invasive tools (i.e., patients' mobile devices), the proportion of HNC survivors (i.e., having completed their curative treatment from 3 months to 10 years) experiencing a clinically relevant reduction in QoL during follow-up. The Big Data for Quality of Life (BD4QoL) study is an international, multicenter, randomized (2:1), open-label trial. The primary endpoint is a clinically relevant global health-related EORTC QLQ-C30 QoL deterioration (decrease =10 points) at any point during 24 months post-treatment follow-up. The target sample size is 420 patients. Patients will be randomized to be followed up using the BD4QoL platform or per standard clinical practice. The BD4QoL platform includes a set of services to allow patients monitoring and empowerment through two main tools: a mobile application installed on participants' smartphones, that includes a chatbot for ecoaching, and the Point of Care dashboard, to let the investigators manage patients data. In both arms, participants will be asked to complete QoL questionnaires at study entry and once every 6 months, and will undergo posttreatment follow up as per clinical practice. Patients randomized to the intervention arm (n=280) will receive access to the BD4QoL platform, those in the control arm (n=140) will not. Eligibility criteria include completing curative treatments for non-metastatic HNC and the use of an Android-based smartphone. Patients undergoing active treatments or with synchronous cancers are excluded. [ABSTRACT FROM AUTHOR]

Background: Overexpression of human epidermal growth factor receptor type 2 (HER2) occurs in almost 25-30% of androgen receptor (AR)-positive salivary gland carcinomas (SGCs), notably salivary duct carcinoma (SDC) and adenocarcinoma not otherwise specified (NOS). In the last years, several studies have reported the clinical benefit of HER2 directed therapies in this setting. This work aims at describing the natural history of AR-positive recurrent/metastatic (R/M) SGC patients, based on HER2 amplification status. Methods: Consecutive R/M AR-positive SGC patients accessing our Institution from 2010 to 2021 were analyzed. Descriptive statistics and survival analyses were performed to present the clinical characteristics of the selected patients and the outcomes, based on HER2 status. A specific focus was dedicated to patients developing metastases to the central nervous system (CNS). Results: Seventy-four R/M AR-positive SGC patients (72 men) were analyzed. Median follow-up was 36.18 months (95% CI 30.19-42.66). HER2 status was available in 62 cases (84%) and in 42% the protein was overexpressed (HER2+). Compared with patients with HER2- SGCs, in patients with HER2+ disease, HR for disease recurrence was 2.97 (95% CI 1.44-6.1, p=0.003), and HR for death from R/ M disease was 3.22 (95% CI 1.39-7.49, p=0.007). Moreover, the HER2+ group showed a non-significant trend towards a higher prevalence of CNS metastases (40% vs. 24%, p=0.263). Patients developing CNS metastases had shorter survival than those who did not; at bivariate analysis (covariates: CNS disease and HER2 status), HER2 status demonstrated its independent prognostic significance. Discussion: In our patient population, HER2 amplification was a negative prognostic factor, and it was associated with a non-statistically significant higher risk of developing CNS metastasis. Further studies are needed to explore the potential clinical benefit of tackling the two biological pathways (AR and HER2) in patients affected by this rare and aggressive malignancy [ABSTRACT FROM AUTHOR]

In this paper, several radiomics‐based predictive models of response to induction chemotherapy (IC) in sinonasal cancers (SNCs) are built and tested. Models were built as a combination of radiomic features extracted from three types of MRI images: T1‐weighted images, T2‐weighted images and apparent diffusion coefficient (ADC) maps. Fifty patients (aged 54 ± 12 years, 41 men) were included in this study. Patients were classified according to their response to IC (25 responders and 25 nonresponders). Not all types of images were acquired for all of the patients: 49 had T1‐weighted images, 50 had T2‐weighted images and 34 had ADC maps. Only in a subset of 33 patients were all three types of image acquired. Eighty‐nine radiomic features were extracted from the MRI images. Dimensionality reduction was performed by using principal component analysis (PCA) and by selecting only the three main components. Different algorithms (trees ensemble, K‐nearest neighbors, support vector machine, naïve Bayes) were used to classify the patients as either responders or nonresponders. Several radiomic models (either monomodality or multimodality obtained by a combination of T1‐weighted, T2‐weighted and ADC images) were developed and the performance was assessed through 100 iterations of train and test split. The area under the curve (AUC) of the models ranged from 0.56 to 0.78. Trees ensemble, support vector machine and naïve Bayes performed similarly, but in all cases ADC‐based models performed better. Trees ensemble gave the highest AUC (0.78 for the T1‐weighted+T2‐weighted+ADC model) and was used for further analyses. For trees ensemble, the models based on ADC features performed better than those models that did not use those features (P < 0.02 for one‐tail Hanley test, AUC range 0.68–0.78 vs 0.56–0.69) except the T1‐weighted+ADC model (AUC 0.71 vs 0.69, nonsignificant differences). The results suggest the relevance of ADC‐based radiomics for prediction of response to IC in SNCs. [ABSTRACT FROM AUTHOR]