A microRNA prognostic signature in patients with diffuse intrinsic pontine gliomas through non-Invasive liquid biopsy

SIMPLE SUMMARY: Diffuse intrinsic pontine glioma (DIPG) is a neuro-radiologically defined tumor of the brainstem, primarily affecting children, with most diagnoses occurring between 5 and 7 years of age. Surgical removal in DIPGs is not feasible. Subsequent tumor progression is almost universal and no biomarker for predicting the course of the disease has entered into clinical practice so far. Under these premises, it is essential to develop reliable biomarkers that are able to improve outcomes and stratify patients using non-invasive methods to determine tumor profiles. We designed a study assessing circulating miRNA expression by a high-throughput platform and divided patients into training and validation phases in order to disclose a potential signature with clinical impact. Our results for the first time have proved the usefulness of blood-circulating nucleic acids as powerful, easy-to-assay molecular markers of disease status in DIPG. ABSTRACT: Diffuse midline gliomas (DMGs) originate in the thalamus, brainstem, cerebellum and spine. This entity includes tumors that infiltrate the pons, called diffuse intrinsic pontine gliomas (DIPGs), with a rapid onset and devastating neurological symptoms. Since surgical removal in DIPGs is not feasible, the purpose of this study was to profile circulating miRNA expression in DIPG patients in an effort to identify a non-invasive prognostic signature with clinical impact. Using a high-throughput platform, miRNA expression was profiled in serum samples collected at the time of MRI diagnosis and prior to radiation and/or systemic therapy from 47 patients enrolled in clinical studies, combining nimotuzumab and vinorelbine with concomitant radiation. With progression-free survival as the primary endpoint, a semi-supervised learning approach was used to identify a signature that was also tested taking overall survival as the clinical endpoint. A signature comprising 13 circulating miRNAs was identified in the training set (n = 23) as being able to stratify patients by risk of disease progression (log-rank p = 0.00014; HR = 7.99, 95% CI 2.38–26.87). When challenged in a separate validation set (n = 24), it confirmed its ability to predict progression (log-rank p = 0.00026; HR = 5.51, 95% CI 2.03–14.9). The value of our signature was also confirmed when overall survival was considered (log-rank p = 0.0021, HR = 4.12, 95% CI 1.57–10.8). We have identified and validated a prognostic marker based on the expression of 13 circulating miRNAs that can shed light on a patient’s risk of progression. This is the first demonstration of the usefulness of nucleic acids circulating in the blood as powerful, easy-to-assay molecular markers of disease status in DIPG. This study provides Class II evidence that a signature based on 13 circulating miRNAs is associated with the risk of disease progression

Gene Expression Clustering and Selected Head and Neck Cancer Gene Signatures Highlight Risk Probability Differences in Oral Premalignant Lesions

BACKGROUND: Oral premalignant lesions (OPLs) represent the most common oral precancerous conditions. One of the major challenges in this field is the identification of OPLs at higher risk for oral squamous cell cancer (OSCC) development, by discovering molecular pathways deregulated in the early steps of malignant transformation. Analysis of deregulated levels of single genes and pathways has been successfully applied to head and neck squamous cell cancers (HNSCC) and OSCC with prognostic/predictive implications. Exploiting the availability of gene expression profile and clinical follow-up information of a well-characterized cohort of OPL patients, we aim to dissect tissue OPL gene expression to identify molecular clusters/signatures associated with oral cancer free survival (OCFS). MATERIALS AND METHODS: The gene expression data of 86 OPL patients were challenged with: an HNSCC specific 6 molecular subtypes model (Immune related: HPV related, Defense Response and Immunoreactive; Mesenchymal, Hypoxia and Classical); one OSCC-specific signature (13 genes); two metabolism-related signatures (3 genes and signatures raised from 6 metabolic pathways associated with prognosis in HNSCC and OSCC, respectively); a hypoxia gene signature. The molecular stratification and high versus low expression of the signatures were correlated with OCFS by Kaplan-Meier analyses. The association of gene expression profiles among the tested biological models and clinical covariates was tested through variance partition analysis. RESULTS: Patients with Mesenchymal, Hypoxia and Classical clusters showed an higher risk of malignant transformation in comparison with immune-related ones (log-rank test, p = 0.0052) and they expressed four enriched hallmarks: "TGF beta signaling" "angiogenesis", "unfolded protein response", "apical junction". Overall, 54 cases entered in the immune related clusters, while the remaining 32 cases belonged to the other clusters. No other signatures showed association with OCFS. Our variance partition analysis proved that clinical and molecular features are able to explain only 21% of gene expression data variability, while the remaining 79% refers to residuals independent of known parameters. CONCLUSIONS: Applying the existing signatures derived from HNSCC to OPL, we identified only a protective effect for immune-related signatures. Other gene expression profiles derived from overt cancers were not able to identify the risk of malignant transformation, possibly because they are linked to later stages of cancer progression. The availability of a new well-characterized set of OPL patients and further research is needed to improve

Medullary Thyroid Carcinoma Mutational Spectrum Update and Signaling-Type Inference by Transcriptional Profiles: Literature Meta-Analysis and Study of Tumor Samples

Medullary thyroid carcinoma (MTC) is a rare but aggressive tumor. Although RET and RAS genes are recognized drivers in MTC, associated downstream signaling pathways are largely unknown. In this study, we report 17 sporadic MTCs, collected at our institution, comprising patient-matched primary and lymph node metastatic tumors investigated for mutational and transcriptional profiles. As we identified two uncommon RET deletions (D898_E901del and E632_L633del), we also performed a literature review and meta-analysis to assess the occurrence of unconventional alterations in MTC, focusing on next-generation sequencing studies. We found that new gene alterations are emerging, along with the known RET/RAS drivers, involving not only RET by multiple concurrent mutations or deletions but also other previously underestimated cancer-related genes, especially in sporadic MTCs. In our MTC gene profiles, we found transcriptome similarity between patient-matched tissues and expression of immune genes only by a few samples. Furthermore, we defined a gene signature able to stratify samples into two distinct signaling types, termed MEN2B-like and MEN2A-like. We provide an updated overview of the MTC mutational spectrum and describe how transcriptional profiles can be used to define distinct MTC signaling subtypes that appear to be shared by various gene drivers, including the unconventional ones

Medullary Thyroid Carcinoma Mutational Spectrum Update and Signaling-Type Inference by Transcriptional Profiles: Literature Meta-Analysis and Study of Tumor Samples

Medullary thyroid carcinoma (MTC) is a rare but aggressive tumor. Although RET and RAS genes are recognized drivers in MTC, associated downstream signaling pathways are largely unknown. In this study, we report 17 sporadic MTCs, collected at our institution, comprising patient-matched primary and lymph node metastatic tumors investigated for mutational and transcriptional profiles. As we identified two uncommon RET deletions (D898_E901del and E632_L633del), we also performed a literature review and meta-analysis to assess the occurrence of unconventional alterations in MTC, focusing on next-generation sequencing studies. We found that new gene alterations are emerging, along with the known RET/RAS drivers, involving not only RET by multiple concurrent mutations or deletions but also other previously underestimated cancer-related genes, especially in sporadic MTCs. In our MTC gene profiles, we found transcriptome similarity between patient-matched tissues and expression of immune genes only by a few samples. Furthermore, we defined a gene signature able to stratify samples into two distinct signaling types, termed MEN2B-like and MEN2A-like. We provide an updated overview of the MTC mutational spectrum and describe how transcriptional profiles can be used to define distinct MTC signaling subtypes that appear to be shared by various gene drivers, including the unconventional ones

Biological properties of hypoxia-related gene expression models/signatures on clinical benefit of anti-EGFR treatment in two head and neck cancer window-of-opportunity trials

Not applicable (letter

An Inflammatory Signature to Predict the Clinical Benefit of First-Line Cetuximab Plus Platinum-Based Chemotherapy in Recurrent/Metastatic Head and Neck Cancer

Epidermal growth factor receptor (EGFR) pathway has been shown to play a crucial role in several inflammatory conditions and host immune-inflammation status is related to tumor prognosis. This study aims to evaluate the prognostic significance of a four-gene inflammatory signature in recurrent/metastatic (R/M) head and neck squamous cell carcinoma (HNSCC) patients treated with the EGFR inhibitor cetuximab plus chemotherapy. The inflammatory signature was assessed on 123 R/M HNSCC patients, enrolled in the multicenter trial B490 receiving first-line cetuximab plus platinum-based chemotherapy. The primary endpoint of the study was progression free survival (PFS), while secondary endpoints were overall survival (OS) and objective response rate (ORR). The patient population was subdivided into 3 groups according to the signature score groups. The four-genes-signature proved a significant prognostic value, resulting in a median PFS of 9.2 months in patients with high vs. 6.2 months for intermediate vs. 3.9 months for low values (p = 0.0016). The same findings were confirmed for OS, with median time of 18.4, 13.4, and 7.5 months for high, intermediate, and low values of the score, respectively (p = 0.0001). When ORR was considered, the signature was significantly higher in responders than in non-responders (p = 0.0092), reaching an area under the curve (AUC) of 0.65 (95% CI: 0.55-0.75). Our findings highlight the role of inflammation in the response to cetuximab and chemotherapy in R/M-HNSCC and may have translational implications for improving treatment selection

Efficacy of ventilator waveform observation for detection of patient-ventilator asynchrony during NIV: a multicentre study

The objective of this study was to assess ability to identify asynchronies during noninvasive ventilation (NIV) through ventilator waveforms according to experience and interface, and to ascertain the influence of breathing pattern and respiratory drive on sensitivity and prevalence of asynchronies. 35 expert and 35 nonexpert physicians evaluated 40 5-min NIV reports displaying flow–time and airway pressure–time tracings; identified asynchronies were compared with those ascertained by three examiners who evaluated the same reports displaying, additionally, tracings of diaphragm electrical activity. We determined: 1) sensitivity, specificity, and positive and negative predictive values; 2) the correlation between the double true index (DTI) of each report (i.e., the ratio between the sum of true positives and true negatives, and the overall breath count) and the corresponding asynchrony index (AI); and 3) the influence of breathing pattern and respiratory drive on both AI and sensitivity. Sensitivities to detect asynchronies were low either according to experience (0.20 (95% CI 0.14–0.29) for expert versus 0.21 (95% CI 0.12–0.30) for nonexpert, p=0.837) or interface (0.28 (95% CI 0.17–0.37) for mask versus 0.10 (95% CI 0.05–0.16) for helmet, p<0.0001). DTI inversely correlated with the AI (r2=0.67, p<0.0001). Breathing pattern and respiratory drive did not affect prevalence of asynchronies and sensitivity. Patient–ventilator asynchrony during NIV is difficult to recognise solely by visual inspection of ventilator waveforms

Clinical Validity of a Prognostic Gene Expression Cluster-Based Model in Human Papillomavirus-Positive Oropharyngeal Carcinoma

Under common therapeutic regimens, the prognosis of human papillomavirus (HPV)-positive squamous oropharyngeal carcinomas (OPCs) is more favorable than HPV-negative OPCs. However, the prognosis of some tumors is dismal, and validated prognostic factors are missing in clinical practice. The present work aimed to validate the prognostic significance of our published three-cluster model and to compare its prognostic value with those of the 8th edition of the tumor-node-metastasis staging system (TNM8) and published signatures and clustering models. METHODS: Patients with HPV DNA-positive OPCs with locoregionally advanced nonmetastatic disease treated with curative intent (BD2Decide observational study, NCT02832102) were considered as validation cohort. Patients were treated in seven European centers, with expertise in the multidisciplinary management of patients with head and neck cancer. The median follow-up was 46.2 months (95% CI, 41.2 to 50), and data collection was concluded in September 2019. The primary end point of this study was overall survival (OS). Three-clustering models and seven prognostic signatures were compared with our three-cluster model. RESULTS: The study population consisted of 235 patients. The three-cluster model confirmed its prognostic value. Two-year OS in each cluster was 100% in the low-risk cluster, 96.6% in the intermediate-risk cluster, and 86.3% in the high-risk cluster (P = .00074). For the high-risk cluster, we observed an area under the curve = 0.832 for 2-year OS, significantly outperforming TNM 8th edition (area under the curve = 0.596), and functional and biological differences were identified for each cluster. CONCLUSION: The rigorous clinical selection of the cases included in this study confirmed the robustness of our three-cluster model in HPV-positive OPCs. The prognostic value was found to be independent and superior compared with TNM8. The next step includes the translation of the three-cluster model in clinical practice. This could open the way to future exploration of already available therapies in HPV-positive OPCs tailoring de-escalation or intensification according to the three-cluster model