hacksig: a unified and tidy R framework to easily compute gene expression signature scores.

SUMMARY: Hundreds of gene expression signatures have been developed during the last two decades. However, due to the multitude of development procedures and sometimes a lack of explanation for their implementation, it can become challenging to apply the original method on custom data. Moreover, at present, there is no unified and tidy interface to compute signature scores with different single sample enrichment methods. For these reasons, we developed hacksig, an R package intended as a unified framework to obtain single sample scores with a tidy output as well as a collection of manually curated gene signatures and methods from cancer transcriptomics literature. AVAILABILITY AND IMPLEMENTATION: The hacksig R package is freely available on CRAN (https://CRAN.R-project.org/package=hacksig) under the MIT license. The source code can be found on GitHub at https://github.com/Acare/hacksig. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Tumor molecular landscape of Epstein-Barr virus (EBV) related nasopharyngeal carcinoma in EBV-endemic and non-endemic areas: Implications for improving treatment modalities.

Epstein-Barr virus (EBV) related- nasopharyngeal carcinoma (NPC) is a squamous carcinoma of the nasopharyngeal mucosal lining. Endemic areas (EA) are east and Southeast Asia, were NPC was recorded with higher incidence and longer estimated survival than in non-endemic area (NEA) such as Europe, We analyzed the gene expression and microenvironment properties of NPC in both areas to identify molecular subtypes and assess biological and clinical correlates that might explain the differences in incidence and outcome between EA- and NEA-NPCs. Six EA-NPC transcriptomic datasets, including tumor and normal samples, were integrated in a meta-analysis to identify molecular subtypes using a ConsensusClusterPlus bioinformatic approach. Based on the biological/functional characterization of four identified clusters were identified: Cl1, Immune-active; Cl2, defense-response; Cl3, proliferation; Cl4, perineural-interaction/EBV-exhaustion. Kaplan-Meier survival analysis, applied to the single dataset with available disease-free survival indicated Cl3 as the cluster with the worst prognosis (P = 0.0476), confirmed when applying four previously published prognostic signatures. A Cl3 classifier signature was generated and its prognostic performance was confirmed (P = 0.0368) on a validation dataset. Prediction of treatment response suggested better responses to: radiotherapy and immune checkpoint inhibitors immune-active and defense-response clusters; chemotherapy proliferation cluster; cisplatin perineural-interaction/EBV-exhaustion cluster. RNA sequencing for gene expression profiling was performed on 50 NEA-NPC Italian samples. In the NEA cohort, Cl1, Cl2 and Cl3 were represented, while perineural-interaction/EBV-exhaustion was almost absent. The immune/biological characterization and treatment-response prediction analyses of NEA-NPC partially replicated the EA-NPC results. Well characterized EA- and NEA-NPC retrospective and prospective cohorts are needed to validate the obtained results and can help designing future clinical studies.

Association of a gene-expression subtype to outcome and treatment response in patients with recurrent/metastatic head and neck squamous cell carcinoma treated with nivolumab.

BACKGROUND: Immune checkpoint inhibitors have been approved and currently used in the clinical management of recurrent and metastatic head and neck squamous cell carcinoma (R/M HNSCC) patients. The reported benefit in clinical trials is variable and heterogeneous. Our study aims at exploring and comparing the predictive role of gene-expression signatures with classical biomarkers for immunotherapy-treated R/M HNSCC patients in a multicentric phase IIIb trial. METHODS: Clinical data were prospectively collected in Nivactor tiral (single-arm, open-label, multicenter, phase IIIb clinical trial in platinum-refractory HNSCC treated with nivolumab). Findings were validated in an external independent cohort of immune-treated HNSCC patients, divided in long-term and short-term survivors (overall survival >18 and <6 months since the start of immunotherapy, respectively). Pretreatment tumor tissue specimen from immunotherapy-treated R/M HNSCC patients was used for PD-L1 (Tumor Proportion Score; Combined Positive Score (CPS)) and Tumor Mutational Burden (Oncopanel TSO500) evaluation and gene expression profiling; classical biomarkers and immune signatures (retrieved from literature) were challenged in the NIVACTOR dataset. RESULTS: Cluster-6 (Cl6) stratification of NIVACTOR cases in high score (n=16, 20%) and low score (n=64, 80%) demonstrated a statistically significant and clinically meaningful improvement in overall survival in the high-score cases (p=0.00028; HR=4.34, 95% CI 1.84 to 10.22) and discriminative ability reached area under the curve (AUC)=0.785 (95% CI 0.603 to 0.967). The association of high-score Cl6 with better outcome was also confirmed in: (1) NIVACTOR progression-free survival (p=4.93E-05; HR=3.71, 95% CI 1.92 to 7.18) and objective-response-rate (AUC=0.785; 95% CI 0.603 to 0.967); (2) long survivors versus short survivors (p=0.00544). In multivariate Cox regression analysis, Cl6 was independent from Eastern Cooperative Oncology Group performance status, PDL1-CPS, and primary tumor site. CONCLUSIONS: These data highlight the presence of underlying biological differences able to predict survival and response following treatment with immunotherapy in platinum-refractory R/M HNSCC that could have translational implications improving treatment selection. TRIAL REGISTRATION NUMBER: EudraCT Number: 2017-000562-30.

MRI-based radiomic prognostic signature for locally advanced oral cavity squamous cell carcinoma: development, testing and comparison with genomic prognostic signatures.

BACKGROUND: . At present, the prognostic prediction in advanced oral cavity squamous cell carcinoma (OCSCC) is based on the tumor-node-metastasis (TNM) staging system, and the most used imaging modality in these patients is magnetic resonance image (MRI). With the aim to improve the prediction, we developed an MRI-based radiomic signature as a prognostic marker for overall survival (OS) in OCSCC patients and compared it with published gene expression signatures for prognosis of OS in head and neck cancer patients, replicated herein on our OCSCC dataset. METHODS: For each patient, 1072 radiomic features were extracted from T1 and T2-weighted MRI (T1w and T2w). Features selection was performed, and an optimal set of five of them was used to fit a Cox proportional hazard regression model for OS. The radiomic signature was developed on a multi-centric locally advanced OCSCC retrospective dataset (n = 123) and validated on a prospective cohort (n = 108). RESULTS: The performance of the signature was evaluated in terms of C-index (0.68 (IQR 0.66-0.70)), hazard ratio (HR 2.64 (95% CI 1.62-4.31)), and high/low risk group stratification (log-rank p < 0.001, Kaplan-Meier curves). When tested on a multi-centric prospective cohort (n = 108), the signature had a C-index of 0.62 (IQR 0.58-0.64) and outperformed the clinical and pathologic TNM stage and six out of seven gene expression prognostic signatures. In addition, the significant difference of the radiomic signature between stages III and IVa/b in patients receiving surgery suggests a potential association of MRI features with the pathologic stage. CONCLUSIONS: Overall, the present study suggests that MRI signatures, containing non-invasive and cost-effective remarkable information, could be exploited as prognostic tools.

Genomic and transcriptomic analyses of thyroid cancers identify DICER1 somatic mutations in adult follicular-patterned RAS-like tumors.

Background: Papillary thyroid carcinoma (PTC) is the most common type of thyroid cancer (TC). Several genomic and transcriptomic studies explored the molecular landscape of follicular cell-derived TCs, and BRAFV600E, RAS mutations, and gene fusions are well-established drivers. DICER1 mutations were described in specific sets of TC patients but represent a rare event in adult TC patients. Methods: Here, we report the molecular characterization of 30 retrospective follicular cell-derived thyroid tumors, comprising PTCs (90%) and poorly differentiated TCs (10%), collected at our Institute. We performed DNA whole-exome sequencing using patient-matched control for somatic mutation calling, and targeted RNA-seq for gene fusion detection. Transcriptional profiles established in the same cohort by microarray were investigated using three signaling-related gene signatures derived from The Cancer Genome Atlas (TCGA). Results: The occurrence of BRAFV600E (44%), RAS mutations (13%), and gene fusions (13%) was confirmed in our cohort. In addition, in two patients lacking known drivers, mutations of the DICER1 gene (p.D1709N and p.D1810V) were identified. DICER1 mutations occur in two adult patients with follicular-pattern lesions, and in one of them a second concurrent DICER1 mutation (p.R459*) is also observed. Additional putative drivers include ROS1 gene (p.P2130A mutation), identified in a patient with a rare solid-trabecular subtype of PTC. Transcriptomics indicates that DICER1 tumors are RAS-like, whereas the ROS1-mutated tumor displays a borderline RAS-/BRAF-like subtype. We also provide an overview of DICER1 and ROS1 mutations in thyroid lesions by investigating the COSMIC database. Conclusion: Even though small, our series recapitulates the genetic background of PTC. Furthermore, we identified DICER1 mutations, one of which is previously unreported in thyroid lesions. For these less common alterations and for patients with unknown drivers, we provide signaling information applying TCGA-derived classification.

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.

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.