Integrative miRNA-Gene Expression Analysis Enables Refinement of Associated Biology and Prediction of Response to Cetuximab in Head and Neck Squamous Cell Cancer

Application of laboratory models for sarcoidosis research

This manuscript will review the implications and applications of sarcoidosis models towards advancing our understanding of sarcoidosis disease mechanisms, identification of biomarkers, and preclinical testing of novel therapies. Emerging disease models and innovative research tools will also be considered.

Modeling Climate Change Effects on Genetic Diversity of an Endangered Horse Breed Using Canonical Correlations

The historical increase in the occurrence of extreme weather events in Spain during the last thirty years makes it a perfect location for the evaluation of climate change. Modeling the effects of climate change on domestic animals' genetic diversity may help to anticipate challenging situations. However, animal populations' short life cycle and patent lack of historical information during extended periods of time drastically compromise the evaluation of climate change effects. Locally adapted breeds' gene pool is the base for their improved resilience and plasticity in response to climate change's extreme climatic conditions. The preservation of these domestic resources offers selection alternatives to breeders who seek such improved adaptability. The Spanish endangered autochthonous Hispano-Arabian horse breed is perfectly adapted to the conditions of the territory where it was created, developed, and widespread worldwide. The possibility to trace genetic diversity in the Hispano-Arabian breed back around seven decades and its global ubiquity make this breed an idoneous reference subject to act as a model for other international populations. Climate change's shaping effects on the genetic diversity of the Hispano-Arabian horse breed's historical population were monitored from 1950 to 2019 and evaluated. Wind speed, gust speed, or barometric pressure have greater repercussions than extreme temperatures on genetic diversity. Extreme climate conditions, rather than average modifications of climate, may push breeders/owners to implement effective strategies in the short to medium term, but the effect will be plausible in the long term due to breed sustainability and enhanced capacity of response to extreme climate events. When extreme climatic conditions occur, breeders opt for mating highly diverse unrelated individuals, avoiding the production of a large number of offspring. People in charge of domestic population conservation act as catalyzers of the regulatory changes occurring during breeds' climate change adaptive process and may identify genes conferring their animals with greater adaptability but still maintaining enhanced performance. This model assists in determining how owners of endangered domestic populations should plan their breeding strategies, seeking the obtention of animals more resilient and adapted to climate-extreme conditions. This efficient alternative is focused on the obtention of increased profitability from this population and in turn ensuring their sustainability.

Multiomic Investigations into Lung Health and Disease

Diseases of the lung account for more than 5 million deaths worldwide and are a healthcare burden. Improving clinical outcomes, including mortality and quality of life, involves a holistic understanding of the disease, which can be provided by the integration of lung multi-omics data. An enhanced understanding of comprehensive multiomic datasets provides opportunities to leverage those datasets to inform the treatment and prevention of lung diseases by classifying severity, prognostication, and discovery of biomarkers. The main objective of this review is to summarize the use of multiomics investigations in lung disease, including multiomics integration and the use of machine learning computational methods. This review also discusses lung disease models, including animal models, organoids, and single-cell lines, to study multiomics in lung health and disease. We provide examples of lung diseases where multi-omics investigations have provided deeper insight into etiopathogenesis and have resulted in improved preventative and therapeutic interventions.

miRNAs as potential game-changers in head and neck cancer: Future clinical and medicinal uses

Head and neck cancers (HNCs) are a group of heterogeneous tumors formed most frequently from epithelial cells of the larynx, lips, oropharynx, nasopharynx, and mouth. Numerous epigenetic components, including miRNAs, have been demonstrated to have an impact on HNCs characteristics like progression, angiogenesis, initiation, and resistance to therapeutic interventions. The miRNAs may control the production of numerous genes linked to HNCs pathogenesis. The roles that miRNAs play in angiogenesis, invasion, metastasis, cell cycle, proliferation, and apoptosis are responsible for this impact. The miRNAs also have an impact on crucial HNCs-related mechanistic networks like the WNT/β-catenin signaling, PTEN/Akt/mTOR pathway, TGFβ, and KRAS mutations. miRNAs may affect how the HNCs respond to treatments like radiation and chemotherapy in addition to pathophysiology. This review aims to demonstrate the relationship between miRNAs and HNCs with a particular emphasis on how miRNAs impact HNCs signaling networks.

Knowledge and expectations about miRNAs as biomarkers in head and neck squamous cell cancers

Head and neck squamous cell cancer patients suffer from a high postoperative recurrence rate and poor prognosis. Thus, it is essential to better understand the underlying molecular mechanisms and identify the role of new biomarkers. Recent research has shown that the dysregulation of microRNAs is a potential biomarker as a screening or prognostic tool. Moreover, the literature reveals its promising usefulness to select the best treatment strategy and monitor tumour response. The purpose of this review is to identify and synthesize the available literature on microRNAs as biomarkers that could help manage patients with head and neck squamous cell cancer. A search in scientific databases was completed, including all relevant articles related to circulating microRNAs in head and neck squamous cell cancer published in English or Spanish. We focused on articles whose main findings were related to their usefulness in diagnosis and prognosis. Conclusion: Knowledge of microRNAs opens the possibilities that these molecules offer in terms of monitoring cancer disease in a less-invasive, simple manner, allowing for serial sampling to assess the response to treatment and minimal residual disease. It is yet to be determined whether liquid biopsy will replace the traditional biopsy in the future but it represents a change in the paradigm of management of head and neck squamous cell cancer.

Macrophage Heterogeneity in the Intestinal Cells of Salmon: Hints From Transcriptomic and Imaging Data

The intestine has many types of cells that are present mostly in the epithelium and lamina propria. The importance of the intestinal cells for the mammalian mucosal immune system is well-established. However, there is no in-depth information about many of the intestinal cells in teleosts. In our previous study, we reported that adherent intestinal cells (AIC) predominantly express macrophage-related genes. To gather further evidence that AIC include macrophage-like cells, we compared their phagocytic activity and morphology with those of adherent head kidney cells (AKC), previously characterized as macrophage-like cells. We also compared equally abundant as well as differentially expressed mRNAs and miRNAs between AIC and AKC. AIC had lower phagocytic activity and were larger and more circular than macrophage-like AKC. RNA-Seq data revealed that there were 18309 mRNAs, with 59 miRNAs that were equally abundant between AIC and AKC. Integrative analysis of the mRNA and miRNA transcriptomes revealed macrophage heterogeneity in both AIC and AKC. In addition, analysis of AIC and AKC transcriptomes revealed functional characteristics of mucosal and systemic macrophages. Five pairs with significant negative correlations between miRNA and mRNAs were linked to macrophages and epithelial cells and their interaction could be pointing to macrophage activation and differentiation. The potential macrophage markers suggested in this study should be investigated under different immune conditions to understand the exact macrophage phenotypes.

Shooting at Moving and Hidden Targets-Tumour Cell Plasticity and the Notch Signalling Pathway in Head and Neck Squamous Cell Carcinomas

Head and Neck Squamous Cell Carcinoma (HNSCC) is often aggressive, with poor response to current therapies in approximately 40-50% of the patients. Current therapies are restricted to operation and irradiation, often combined with a small number of standard-of-care chemotherapeutic drugs, preferentially for advanced tumour patients. Only very recently, newer targeted therapies have entered the clinics, including Cetuximab, which targets the EGF receptor (EGFR), and several immune checkpoint inhibitors targeting the immune receptor PD-1 and its ligand PD-L1. HNSCC tumour tissues are characterized by a high degree of intra-tumour heterogeneity (ITH), and non-genetic alterations that may affect both non-transformed cells, such as cancer-associated fibroblasts (CAFs), and transformed carcinoma cells. This very high degree of heterogeneity likely contributes to acquired drug resistance, tumour dormancy, relapse, and distant or lymph node metastasis. ITH, in turn, is likely promoted by pronounced tumour cell plasticity, which manifests in highly dynamic and reversible phenomena such as of partial or hybrid forms of epithelial-to-mesenchymal transition (EMT), and enhanced tumour stemness. Stemness and tumour cell plasticity are strongly promoted by Notch signalling, which remains poorly understood especially in HNSCC. Here, we aim to elucidate how Notch signal may act both as a tumour suppressor and proto-oncogenic, probably during different stages of tumour cell initiation and progression. Notch signalling also interacts with numerous other signalling pathways, that may also have a decisive impact on tumour cell plasticity, acquired radio/chemoresistance, and metastatic progression of HNSCC. We outline the current stage of research related to Notch signalling, and how this pathway may be intricately interconnected with other, druggable targets and signalling mechanisms in HNSCC.

Prevalence of HPV in Mexican Patients with Head and Neck Squamous Carcinoma and Identification of Potential Prognostic Biomarkers

Simple Summary

Head and neck squamous cell carcinomas (HNSCC) are a heterogeneous group of neoplasms that show diverse clinical and biological characteristics associated with human papillomavirus (HPV). Biological and clinical characterization is essential to stratify patients based on prognostic and predictive factors. The biological features of HNSCC may change according to geography and population characteristics. Studies on the molecular biology of HNSCC in Mexico are scarce. In the present study, we analyzed 414 Mexican patients with HNSCC and determined the presence and genotype of HPV, p16 expression, and global gene expression profiles. Twenty-two percent of total cases were HPV+, and 32% were p16+. We identified genes associated with survival, such as SLIRP, KLF10, AREG, ACT1, and LIMA. In addition, CSF1R, MYC, and SRC genes were identified as potential therapeutic targets. This study offers information that may be relevant for our understanding of the biology of HNSCC and the development of therapeutic strategies.

Abstract

Head and neck squamous cell carcinomas (HNSCC) show a variety of biological and clinical characteristics that could depend on the association with the human papillomavirus (HPV). Biological and clinical characterization is essential to stratify patients based on prognostic and predictive factors. Reports on HNSCC are scarce in Mexico. Herein, we analyzed 414 Mexican patients with HNSCC, including oropharynx (OPSCC), larynx (LASCC), and oral cavity (OCSCC), and identified HPV DNA and p16 expression. Global gene expression profiles were analyzed in 25 HPV+/p16+ vs. HPV−/p16− cases. We found 32.3% p16+ and 22.3% HPV+ samples, HPV 16, 18, 39, 52, and 31 being the most frequent genotypes. For OPSCC, LASCC and OCSCC, 39.2, 14.7, and 9.6% were HPV+/p16+, respectively. High expression of SLIRP, KLF10, AREG, and LIMA was associated with poor survival; in contrast, high expression of MYB and SYCP2 correlated with better survival. In HPV+ cases, high expression of SLC25A39 and GJB2 was associated with poor survival. Likewise, EGFR, IL-1, IL-6, JAK-STAT, WNT, NOTCH, and ESR1 signaling pathways were downregulated in HPV+ cases. CSF1R, MYC, and SRC genes were identified as key hubs and therapeutic targets. Our study offers information regarding the molecular and clinical characteristics of HNSCC in Mexican patients.

Gene Correlation Guided Gene Selection for Microarray Data Classification

The microarray cancer data obtained by DNA microarray technology play an important role for cancer prevention, diagnosis, and treatment. However, predicting the different types of tumors is a challenging task since the sample size in microarray data is often small but the dimensionality is very high. Gene selection, which is an effective means, is aimed at mitigating the curse of dimensionality problem and can boost the classification accuracy of microarray data. However, many of previous gene selection methods focus on model design, but neglect the correlation between different genes. In this paper, we introduce a novel unsupervised gene selection method by taking the gene correlation into consideration, named gene correlation guided gene selection (G³CS). Specifically, we calculate the covariance of different gene dimension pairs and embed it into our unsupervised gene selection model to regularize the gene selection coefficient matrix. In such a manner, redundant genes can be effectively excluded. In addition, we utilize a matrix factorization term to exploit the cluster structure of original microarray data to assist the learning process. We design an iterative updating algorithm with convergence guarantee to solve the resultant optimization problem. Experimental results on six publicly available microarray datasets are conducted to validate the efficacy of our proposed method.

Identification of latent biomarkers in connection with progression and prognosis in oral cancer by comprehensive bioinformatics analysis

BACKGROUND

Oral cancer (OC) is a common and dangerous malignant tumor with a low survival rate. However, the micro level mechanism has not been explained in detail.

METHODS

Gene and miRNA expression micro array data were extracted from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) and miRNAs (DE miRNAs) were identified by R software. Gene Ontology (GO) enrichment and Kyoto Encyclopedia of genes and genomes (KEGG) pathway analysis were used to assess the potential molecular mechanisms of DEGs. Cytoscape software was utilized to construct protein-protein interaction (PPI) network and miRNA-gene network. Central genes were screened out with the participation of gene degree, molecular complex detection (MCODE) plugin, and miRNA-gene network. Then, the identified genes were checked by The Cancer Genome Atlas (TCGA) gene expression profile, Kaplan-Meier data, Oncomine, and the Human Protein Atlas database. Receiver operating characteristic (ROC) curve was drawn to predict the diagnostic efficiency of crucial gene level in normal and tumor tissues. Univariate and multivariate Cox regression were used to analyze the effect of dominant genes and clinical characteristics on the overall survival rate of OC patients.

RESULTS

Gene expression data of gene expression profiling chip(GSE9844, GSE30784, and GSE74530) were obtained from GEO database, including 199 tumor and 63 non-tumor samples. We identified 298 gene mutations, including 200 upregulated and 98 downregulated genes. GO functional annotation analysis showed that DEGs were enriched in extracellular structure and extracellular matrix containing collagen. In addition, KEGG pathway enrichment analysis demonstrated that the DEGs were significantly enriched in IL-17 signaling pathway and PI3K-Akt signaling pathway. Then, we detected three most relevant modules in PPI network. Central genes (CXCL8, DDX60, EIF2AK2, GBP1, IFI44, IFI44L, IFIT1, IL6, MMP9,CXCL1, CCL20, RSAD2, and RTP4) were screened out with the participation of MCODE plugin, gene degree, and miRNA-gene network. TCGA gene expression profile and Kaplan-Meier analysis showed that high expression of CXCL8, DDX60, IL6, and RTP4 was associated with poor prognosis in OC patients, while patients with high expression of IFI44L and RSAD2 had a better prognosis. The elevated expression of CXCL8, DDX60, IFI44L, RSAD2, and RTP44 in OC was verified by using Oncomine database. ROC curve showed that the mRNA levels of these five genes had a helpful diagnostic effect on tumor tissue. The Human Protein Atlas database showed that the protein expressions of DDX60, IFI44L, RSAD2, and RTP44 in tumor tissues were higher than those in normal tissues. Finally, univariate and multivariate Cox regression showed that DDX60, IFI44L, RSAD2, and RTP44 were independent prognostic indicators of OC.

CONCLUSION

This study revealed the potential biomarkers and relevant pathways of OC from publicly available GEO database, and provided a theoretical basis for elucidating the diagnosis, treatment, and prognosis of OC.

Cetuximab in locally advanced head and neck squamous cell carcinoma: Biological mechanisms involved in efficacy, toxicity and resistance

Since its introduction, the use of cetuximab in the treatment of head and neck squamous cell carcinoma (HNSCC) has experienced an evolution. Currently, cetuximab associated with radiotherapy is limited to the treatment of patients affected by a locally advanced malignancy and unfit for cisplatin. However, reliable biomarkers of cetuximab efficacy in this cancer setting are still lacking. This review focuses on the mechanisms of action of cetuximab, highlighting, in particular, the consequences of the binding to EGFR, and the pathways involved in the development of adverse events or acquired resistance. Indeed, adverse events, such as skin rash, have been associated with cetuximab efficacy in HNSCC several times. Acquired resistance is associated with microenvironment plasticity, which is, in turn, characterized by an increased immune infiltrate. The better definition of patients eligible for this kind of therapy could improve HNSCC management, possibly proposing a combined treatment with radiotherapy, cetuximab and immune checkpoint inhibitors as recently investigated.

MicroRNAs in head and neck squamous cell carcinoma: a possible challenge as biomarkers, determinants for the choice of therapy and targets for personalized molecular therapies

Head and neck squamous cell carcinoma (HNSCC) are referred to a group of heterogeneous cancers that include structures of aerodigestive tract such as oral and nasal cavity, salivary glands, oropharynx, pharynx, larynx, paranasal sinuses, and local lymph nodes. HNSCC is characterized by frequent alterations of several genes such as TP53, PIK3CA, CDKN2A, NOTCH1, and MET as well as copy number increase in EGFR, CCND1, and PIK3CA. These genomic alterations play a role in terms of resistance to chemotherapy, molecular targeted therapy, and prediction of patient outcome. MicroRNAs (miRNAs) are small single-stranded noncoding RNAs which are about 19-25 nucleotides. They are involved in the tumorigenesis of HNSCC including dysregulation of cell survival, proliferation, cellular differentiation, adhesion, and invasion. The discovery of the stable presence of the miRNAs in all human body made them attractive biomarkers for diagnosis and prognosis or as targets for novel therapeutic ways, enabling personalized treatment for HNSCC. In recent times the number of papers concerning the characterization of miRNAs in the HNSCC tumorigenesis has grown a lot. In this review, we discuss the very recent studies on different aspects of miRNA dysregulation with their clinical significance and we apologize for the many past and most recent works that have not been mentioned. We also discuss miRNA-based therapy that are being tested on patients by clinical trials.

Predictive Value of EGFR-PI3K-AKT-mTOR-Pathway Inhibitor Biomarkers for Head and Neck Squamous Cell Carcinoma: A Systematic Review

BACKGROUND

Understanding molecular pathogenesis of head and neck squamous cell carcinomas (HNSCC) has considerably improved in the last decades. As a result, novel therapeutic strategies have evolved, amongst which are epidermal growth factor receptor (EGFR)-targeted therapies. With the exception of cetuximab, targeted therapies for HNSCC have not yet been introduced into clinical practice. One important aspect of new treatment regimes in clinical practice is presence of robust biomarkers predictive for therapy response.

METHODS

We performed a systematic search in PubMed, Embase and the Cochrane library. Articles were included if they investigated a biomarker for targeted therapy in the EGFR-PI3K-AKT-mTOR-pathway.

RESULTS

Of 83 included articles, 52 were preclinical and 33 were clinical studies (two studies contained both a preclinical and a clinical part). We classified EGFR pathway inhibitor types and investigated the type of biomarker (biomarker on epigenetic, DNA, mRNA or protein level).

CONCLUSION

Several EGFR-PI3K-AKT-mTOR-pathway inhibitor biomarkers have been researched for HNSCC but few of the investigated biomarkers have been adequately confirmed in clinical trials. A more systematic approach is needed to discover proper biomarkers as stratifying patients is essential to prevent unnecessary costs and side effects.

Network Diffusion Promotes the Integrative Analysis of Multiple Omics

The development of integrative methods is one of the main challenges in bioinformatics. Network-based methods for the analysis of multiple gene-centered datasets take into account known and/or inferred relations between genes. In the last decades, the mathematical machinery of network diffusion—also referred to as network propagation—has been exploited in several network-based pipelines, thanks to its ability of amplifying association between genes that lie in network proximity. Indeed, network diffusion provides a quantitative estimation of network proximity between genes associated with one or more different data types, from simple binary vectors to real vectors. Therefore, this powerful data transformation method has also been increasingly used in integrative analyses of multiple collections of biological scores and/or one or more interaction networks. We present an overview of the state of the art of bioinformatics pipelines that use network diffusion processes for the integrative analysis of omics data. We discuss the fundamental ways in which network diffusion is exploited, open issues and potential developments in the field. Current trends suggest that network diffusion is a tool of broad utility in omics data analysis. It is reasonable to think that it will continue to be used and further refined as new data types arise (e.g. single cell datasets) and the identification of system-level patterns will be considered more and more important in omics data analysis.

Transcriptomics and Epigenomics in head and neck cancer: available repositories and molecular signatures

For many years, head and neck squamous cell carcinoma (HNSCC) has been considered as a single entity. However, in the last decades HNSCC complexity and heterogeneity have been recognized. In parallel, high-throughput omics techniques had allowed picturing a larger spectrum of the behavior and characteristics of molecules in cancer and a large set of omics web-based tools and informative repository databases have been developed. The objective of the present review is to provide an overview on biological, prognostic and predictive molecular signatures in HNSCC. To contextualize the selected data, our literature survey includes a short summary of the main characteristics of omics data repositories and web-tools for data analyses. The timeframe of our analysis was fixed, encompassing papers published between January 2015 and January 2019. From more than 1000 papers evaluated, 61 omics studies were selected: 33 investigating mRNA signatures, 11 and 13 related to miRNA and other non-coding-RNA signatures and 4 analyzing DNA methylation signatures. More than half of identified signatures (36) had a prognostic value but only in 10 studies selection of a specific anatomical sub-site (8 oral cavity, 1 oropharynx and 1 both oral cavity and oropharynx) was performed. Noteworthy, although the sample size included in many studies was limited, about one-half of the retrieved studies reported an external validation on independent dataset(s), strengthening the relevance of the obtained data. Finally, we highlighted the development and exploitation of three gene-expression signatures, whose clinical impact on prognosis/prediction of treatment response could be high. Based on this overview on omics-related literature in HNSCC, we identified some limits and strengths. The major limits are represented by the low number of signatures associated to DNA methylation and to non-coding RNA (miRNA, lncRNA and piRNAs) and the availability of a single dataset with multiple omics on more than 500 HNSCC (i.e. TCGA). The major strengths rely on the integration of multiple datasets through meta-analysis approaches and on the growing integration among omics data obtained on the same cohort of patients. Moreover, new approaches based on artificial intelligence and informatic analyses are expected to be available in the next future.

miR-149-3p reverses CD8+ T-cell exhaustion by reducing inhibitory receptors and promoting cytokine secretion in breast cancer cells

Blockade of inhibitory receptors (IRs) is one of the most effective immunotherapeutic approaches to treat cancer. Dysfunction of miRNAs is a major cause of aberrant expression of IRs and contributes to the immune escape of cancer cells. How miRNAs regulate immune checkpoint proteins in breast cancer remains largely unknown. In this study, downregulation of miRNAs was observed in PD-1-overexpressing CD8⁺ T cells using miRNA array analysis of mouse breast cancer homografts. The data reveal that miR-149-3p was predicted to bind the 3'UTRs of mRNAs encoding T-cell inhibitor receptors PD-1, TIM-3, BTLA and Foxp1. Treatment of CD8⁺ T cells with an miR-149-3p mimic reduced apoptosis, attenuated changes in mRNA markers of T-cell exhaustion and downregulated mRNAs encoding PD-1, TIM-3, BTLA and Foxp1. On the other hand, T-cell proliferation and secretion of effector cytokines indicative of increased T-cell activation (IL-2, TNF-α, IFN-γ) were upregulated after miR-149-3p mimic treatment. Moreover, the treatment with a miR-149-3p mimic promoted the capacity of CD8⁺ T cells to kill targeted 4T1 mouse breast tumour cells. Collectively, these data show that miR-149-3p can reverse CD8⁺ T-cell exhaustion and reveal it to be a potential antitumour immunotherapeutic agent in breast cancer.

Age-Related Alterations in Immune Contexture Are Associated with Aggressiveness in Rhabdomyosarcoma

Adolescents and young adults (AYA) with rhabdomyosarcoma (RMS) form a subgroup of patients whose optimal clinical management and access to care remain a challenge and whose survival lacks behind that of children diagnosed with histologically similar tumors. Understanding the tumor biology that differentiates children from AYA-RMS could provide critical information and drive new initiatives to improve the final outcome. MicroRNA (miRNA) and gene expression profiling (GEP) was evaluated in a RMS cohort of 49 tumor and 15 non-neoplastic tissues. miRNAs analysis identified miR-223 over-expression and miR-431 down-regulation in AYA, validated by Real-Time PCR and miRNA in situ hybridization (ISH). GEP analysis detected 793 age-correlated genes in tumors, of which 194 were anti-correlated. NOTCH2, FGFR1/2 were significantly down-modulated in AYA-RMS. miR-223 was associated with up-regulation of epithelial mesenchymal translation (EMT) and inflammatory pathways, whereas miR-431 was correlated to myogenic differentiation and muscle metabolism. GEP showed an increase in genes associated with CD4 memory resting cells and a decrease in genes associated with γδ T-cells in AYA-RMS. Immunohistochemistry (IHC) analysis demonstrated an increase of infiltrated CD4, CD8, and neutrophils in AYA-RMS tumors. Our results show that aggressiveness of AYA-RMS could be explained by differences in microenvironmental signal modulation mediated by tumor cells, suggesting a fundamental role of immune contexture in AYA-RMS development.

A functional gene expression analysis in epithelial sinonasal cancer: Biology and clinical relevance behind three histological subtypes

Epithelial sinonasal cancers (SNCs) are rare diseases with overlapping morphological features and a dismal prognosis. We aimed to investigate the expression differences among the histological subtypes for discerning their molecular characteristics. We selected 47 SNCs: (i) 21 nonkeratinizing squamous cell carcinomas (NKSCCs), (ii) 13 sinonasal neuroendocrine cancers (SNECs), and (iii) 13 sinonasal undifferentiated cancers (SNUCs). Gene expression profiling was performed by DASL (cDNA-mediated annealing, selection, extension, and ligation) microarray analysis with internal validation by quantitative RT-PCR (RT-qPCR). Relevant molecular patterns were uncovered by sparse partial-least squares discriminant analysis (sPLS-DA), microenvironment cell type (xCell), CIBERSORT, and gene set enrichment (GSEA) analyses. The first two sPLS-DA components stratified samples by histological subtypes. xCell highlighted increased expression of immune components (CD8⁺ effector memory cells, in SNUC) and "other cells": keratinocytes and neurons in NKSCC and SNEC, respectively. Pathway enrichment was observed in NKSCC (six gene sets, proliferation related), SNEC (one gene set, pancreatic β-cells), and SNUC (twenty gene sets, some of them immune-system related). Major neuroendocrine involvement was observed in all the SNEC samples. Our high-throughput analysis revealed a good diagnostic ability to differentiate NKSCC, SNEC, and SNUC, but indicated that the neuroendocrine pathway, typical and pathognomonic of SNEC is also present at lower expression levels in the other two histological subtypes. The different and specific profiles may be exploited for elucidating their biology and could help to identify prognostic and therapeutic opportunities.

Machine Learning and Integrative Analysis of Biomedical Big Data

Recent developments in high-throughput technologies have accelerated the accumulation of massive amounts of omics data from multiple sources: genome, epigenome, transcriptome, proteome, metabolome, etc. Traditionally, data from each source (e.g., genome) is analyzed in isolation using statistical and machine learning (ML) methods. Integrative analysis of multi-omics and clinical data is key to new biomedical discoveries and advancements in precision medicine. However, data integration poses new computational challenges as well as exacerbates the ones associated with single-omics studies. Specialized computational approaches are required to effectively and efficiently perform integrative analysis of biomedical data acquired from diverse modalities. In this review, we discuss state-of-the-art ML-based approaches for tackling five specific computational challenges associated with integrative analysis: curse of dimensionality, data heterogeneity, missing data, class imbalance and scalability issues.

Identification of hub genes and potential molecular mechanisms in gastric cancer by integrated bioinformatics analysis

Objective

Gastric cancer (GC) is the fourth most common cause of cancer-related deaths in the world. In the current study, we aim to identify the hub genes and uncover the molecular mechanisms of GC.

Methods

The expression profiles of the genes and the miRNAs were extracted from the Gene Expression Omnibus database. The identification of the differentially expressed genes (DEGs), including miRNAs, was performed by the GEO2R. Database for Annotation, Visualization and Integrated Discovery was used to perform GO and KEGG pathway enrichment analysis. The protein–protein interaction (PPI) network and miRNA-gene network were constructed using Cytoscape software. The hub genes were identified by the Molecular Complex Detection (MCODE) plugin, the CytoHubba plugin and miRNA-gene network. Then, the identified genes were verified by Kaplan–Meier plotter database and quantitative real-time PCR (qRT-PCR) in GC tissue samples.

Results

A total of three mRNA expression profiles (GSE13911, GSE79973 and GSE19826) were downloaded from the Gene Expression Omnibus (GEO) database, including 69, 20 and 27cases separately. A total of 120 overlapped upregulated genes and 246 downregulated genes were identified. The majority of the DEGs were enriched in extracellular matrix organization, collagen catabolic process, collagen fibril organization and cell adhesion. In addition, three KEGG pathways were significantly enriched, including ECM-receptor interaction, protein digestion and absorption, and the focal adhesion pathways. In the PPI network, five significant modules were detected, while the genes in the modules were mainly involved in the ECM-receptor interaction and focal adhesion pathways. By combining the results of MCODE, CytoHubba and miRNA-gene network, a total of six hub genes including COL1A2, COL1A1, COL4A1, COL5A2, THBS2 and ITGA5 were chosen. The Kaplan–Meier plotter database confirmed that higher expression levels of these genes were related to lower overall survival, except for COL5A2. Experimental validation showed that the rest of the five genes had the same expression trend as predicted.

Conclusion

In conclusion, COL1A2, COL1A1, COL4A1, THBS2 and ITGA5 may be potential biomarkers and therapeutic targets for GC. Moreover, ECM-receptor interaction and focal adhesion pathways play significant roles in the progression of GC.

Gene signatures and expression of miRNAs associated with efficacy of panitumumab in a head and neck cancer phase II trial

OBJECTIVE

Platinum-based chemotherapy plus the anti-EGFR monoclonal antibody (mAb) cetuximab is used to treat recurrent/metastatic (RM) head-neck squamous cell carcinoma (HNSCC). Recently, we defined Cluster3 gene-expression signature as a potential predictor of favorable progression-free survival (PFS) in cetuximab-treated RM-HNSCC patients and predictor of partial metabolic FDG-PET response in an afatinib window-of-opportunity trial. Another anti-EGFR-mAb (panitumumab) was used as the treatment agent in RM-HNSCC patients in the phase II PANI01trial. PANI01 tumor samples were analyzed using functional genomics to explore response predictors to anti-EGFR therapy.

MATERIALS AND METHODS

Whole-gene expression and real-time PCR analyses were applied to pre-treatment samples from 25 PANI01 patients. Three gene signatures (Cluster3 score, RAS onco-signature, microenvironment score) and seven selected miRNAs were separately analyzed for association with panitumumab efficacy.

RESULTS

Cluster3 expression levels had a profile with a significant bimodal separation of samples (P =  3.08 E-13). Higher RAS activation, microenvironment score, and miRNA expression were associated with low-Cluster3 patients. The same biomarkers were separately associated with PFS. Patients with high-Cluster3 had significantly longer PFS than patients with low-Cluster3 (median PFS: 174 versus 51 days; log-rank P = 0.0021). ROC analysis demonstrated accuracy in predicting PFS (AUC = 0.877).

CONCLUSIONS

Despite differences in clinical settings and anti-EGFR inhibitors used for treatment, response prediction by the Cluster3 signature and selected miRNAs was essentially the same. Translation into a useful clinical assay requires validation in a broader setting.

Circulating miR-375 as a novel prognostic marker for metastatic medullary thyroid cancer patients

This study aimed to identify circulating miRNAs as novel non-invasive biomarkers for prognosis and vandetanib response in advanced medullary thyroid cancer (MTC) patients. We prospectively recruited two independent cohorts of locally advanced/metastatic MTC patients including a subgroup of vandetanib-treated subjects: a discovery cohort (n = 20), including matched plasma/tissue samples (n = 17/20), and a validation cohort, yielding only plasma samples (n = 17). Plasma samples from healthy subjects (n = 36) and MTC patients in remission (n = 9) were used as controls. MTC (n = 17 from 8 patients included in discovery cohort) and non-neoplastic thyroid specimens (n = 3) were assessed by microarray profiling to identify candidate circulating miRNAs. qRT-PCR and in situ hybridization were carried out to validate the expression and localization of a selected miRNA within tissues, and qRT-PCR was also performed to measure miRNA levels in plasma samples. By microarray analysis, we identified 51 miRNAs differentially expressed in MTC. The most overexpressed miR, miR-375, was highly expressed by C cells compared to other thyroid cells, and more expressed in MTC than in reactive C-cell hyperplasia. MTC patients had significantly higher miR-375 plasma levels than healthy controls (P < 0.0001) and subjects in remission (P = 0.0004) as demonstrated by qRT-PCR analysis. miR-375 plasma levels were not predictive of vandetanib response, but, notably, high levels were associated with significantly reduced overall survival (HR 10.61, P < 0.0001) and were a strong prognostic factor of poor prognosis (HR 6.24, P = 0.00025) in MTC patients. Overall, our results unveil plasma miR-375 as a promising prognostic marker for advanced MTC patients, to be validated in larger cohorts.

Are Fusion Transcripts in Relapsed/Metastatic Head and Neck Cancer Patients Predictive of Response to Anti-EGFR Therapies?

Prediction of benefit from combined chemotherapy and the antiepidermal growth factor receptor cetuximab is a not yet solved question in head and neck squamous cell carcinoma (HNSCC). In a selected series of 14 long progression-free survival (PFS) and 26 short PFS patients by whole gene and microRNA expression analysis, we developed a model potentially predictive of cetuximab sensitivity. To better decipher the “omics” profile of our patients, we detected transcript fusions by RNA-seq through a Pan-Cancer panel targeting 1385 cancer genes. Twenty-seven different fusion transcripts, involving mRNA and long noncoding RNA (lncRNA), were identified. The majority of fusions (81%) were intrachromosomal, and 24 patients (60%) harbor at least one of them. The presence/absence of fusions and the presence of more than one fusion were not related to outcome, while the lncRNA-containing fusions resulted enriched in long PFS patients (P = 0.0027). The CD274-PDCD1LG2 fusion was present in 7/14 short PFS patients harboring fusions and was absent in long PFS patients (P = 0.0188). Among the short PFS patients, those harboring this fusion had the worst outcome (P = 0.0172) and increased K-RAS activation (P = 0.00147). The associations between HNSCC patient's outcome following cetuximab treatment and lncRNA-containing fusions or the CD274-PDCD1LG2 fusion deserve validation in prospective clinical trials.