Transcriptomic characterization of differential gene expression in oral squamous cell carcinoma: a meta-analysis of publicly available microarray data sets

A comprehensive transcriptome based meta-analysis to unveil the aggression nexus of oral squamous cell carcinoma

Lymph node metastasis in oral cancer (OC) complicates management due to its aggressive nature and high risk of recurrence, underscoring the need for biomarkers for early detection and targeted therapies. However, the drivers of this aggressive phenotype remain unclear due to the variability in gene expression patterns. To address this, an integrative meta-analysis of six publicly available transcriptomic profiles, categorized by lymph nodal status, is conducted. Key determinants of disease progression are identified through functional characterization and the TopConfects ranking approach of nodal associated differentially expressed genes (DEGs). To explore the critical nexus between lymph node metastasis and OC recurrence, significant metastatic genes were cross-analysed with literature-derived genes exhibiting aberrant methylation patterns in OC recurrence. Their clinical relevance and expression patterns were then validated in an external dataset from the TCGA head and neck cancer cohort. The analysis identified elevated expression of genes involved in extracellular matrix remodelling and immune response, while the expression of genes related to cellular differentiation and barrier functions was reduced, driving the transition to nodal positivity. The highest-ranked gene, MMP1, showed a log-fold change (LFC) of 4.946 (95 % CI: 3.71, 6.18) in nodal-negative samples, which increased to 5.899 (95 % CI: 4.80, 6.99) in nodal-positive samples, indicating consistent elevation across disease stages. In contrast, TMPRSS11B was significantly downregulated, with an LFC of -5.512 (95 % CI: -6.63, -4.38) in nodal-negative samples and -5.898 (95 % CI: -7.15, -4.64) in nodal-positive samples. Furthermore, MEIS1, down-regulated in nodal-positive status, was found to exhibit hypermethylation at CpG sites associated with OC recurrence. This study represents the first transcriptomic meta-analysis to explore the intersection of lymph node metastasis and OC recurrence, identifying MEIS1 as a potential key contributor. These comprehensive insights into disease trajectories offer potential biomarkers and therapeutic targets for future treatment strategies.

Genomic landscape and gene expression profiles of feline oral squamous cell carcinoma

Feline oral squamous cell carcinoma (FOSCC) is a cancer of the squamous cell lining in the oral cavity and represents up to 80% of all oral cancers in cats, with a poor prognosis. We have used whole exome sequencing (WES) and RNA sequencing of the tumor to discover somatic mutations and gene expression changes that may be associated with FOSCC occurrence. FOSCC offers a potential comparative model to study human head and neck squamous cell carcinoma (HNSCC) due to its similar spontaneous formation, and morphological and histological features. In this first study using WES to identify somatic mutations in feline cancer, we have identified tumor-associated gene mutations in six cats with FOSCC and found some overlap with identified recurrently mutated genes observed in HNSCC. Four samples each had mutations in TP53, a common mutation in all cancers, but each was unique. Mutations in other cellular growth control genes were also found such as KAT2B and ARID1A. Enrichment analysis of FOSCC gene expression profiles suggests a molecular similarity to human OSCC as well, including alterations in epithelial to mesenchymal transition and IL6/JAK/STAT pathways. In this preliminary study, we present exome and transcriptome results that further our understanding of FOSCC.

Digesting the Role of JAK-STAT and Cytokine Signaling in Oral and Gastric Cancers

When small proteins such as cytokines bind to their associated receptors on the plasma membrane, they can activate multiple internal signaling cascades allowing information from one cell to affect another. Frequently the signaling cascade leads to a change in gene expression that can affect cell functions such as proliferation, differentiation and homeostasis. The Janus kinase-signal transducer and activator of transcription (JAK-STAT) and the tumor necrosis factor receptor (TNFR) are the pivotal mechanisms employed for such communication. When deregulated, the JAK-STAT and the TNF receptor signaling pathways can induce chronic inflammatory phenotypes by promoting more cytokine production. Furthermore, these signaling pathways can promote replication, survival and metastasis of cancer cells. This review will summarize the essentials of the JAK/STAT and TNF signaling pathways and their regulation and the molecular mechanisms that lead to the dysregulation of the JAK-STAT pathway. The consequences of dysregulation, as ascertained from founding work in haematopoietic malignancies to more recent research in solid oral-gastrointestinal cancers, will also be discussed. Finally, this review will highlight the development and future of therapeutic applications which modulate the JAK-STAT or the TNF signaling pathways in cancers.

Transcriptional Biomarkers in Oral Cancer: An Integrative Analysis and the Cancer Genome Atlas Validation

OBJECTIVE

An impervious mortality rate in oral cancer (OC) to a certain extent explains the exigencies of precise biomarkers. Therefore, the study was intended to identify OC candidate biomarkers using samples of healthy normal tissues (N=335), adjacent normal tissues (N=93) and OC tissues (N=533) from online microarray data.

METHODS

Differentially expressed genes (DEGs) were recognised through GeneSpring software (Fold change >4.0 and 'p' value.

Transcriptome profiling and pathway analysis in squamous cell carcinoma of buccal mucosa

BACKGROUND

High recurrence and poor overall survival in buccal mucosa squamous cell carcinoma (BMSCC) are not well addressed due to lack of efficient prognostic biomarkers and targeted therapies. To uncover gene candidates for the same, transcriptome profiling has been examined in BMSCC, which is not explored yet.

METHODS

We compared 9 BMSCC and 2 normal oral FFPE tissues using Agilent SurePrint G3 Human gene expression v3 microarray chips. The obtained RNA signatures were interrogated in the cancer genome atlas (TCGA) dataset for alteration values and survival data.

RESULTS

We found total 237 protein coding RNAs and 85 long non-coding RNAs (lncRNAs) which displayed significant differential expression with criteria of at-least 2 fold change and Benjamini Hochberg FDR < .05. In protein coding RNAs, RUNX3 and EMX2 showed utmost degree of up-regulation and down-regulation, respectively. Likewise, among lncRNAs, ARGFXP2 and lnc-SYCP3-2 displayed highest degree of up-regulation and down-regulation, respectively. Besides, an analysis of the RNA list in TCGA dataset spotted deregulation of 21 genes in both, our cohort and TCGA cohort. Among which, MRTO4 and EIF3J genes, and LINC00310, a lncRNA showed greatest expression alterations. Strikingly, at RNA expression level, up-regulation of two genes, EIF3J and SDCBP, was significantly associated with disease free survival and poor overall survival, respectively.

CONCLUSION

Our data documented significant findings to enhance understanding of the disease biology. The proposed RNA candidates (RUNX3, EMX2, MRTO4, EIF3J, SDCBP and LINC00310) may serve as putative therapeutic targets and potential biomarkers for BMSCC diagnosis and prognosis.

Distinct gene expression characteristics in epithelial cell-Porphyromonas gingivalis interactions by integrating transcriptome analyses

Porphyromonas gingivalis is a pivotal periodontal pathogen, and the epithelial cells serve as the first physical barrier to defend the host from bacterial attack. Within this host-bacteria interaction, P. gingivalis can modify the host immune reaction and adjust the gene expression, which is associated with periodontitis pathogenesis and developing strategies. Herein, a meta-analysis was made to get the differential gene expression profiles in epithelial cells with or without P. gingivalis infection. The network-based meta-analysis program for gene expression profiling was used. Both the gene ontology analysis and the pathway enrichment analysis of the differentially expressed genes were conducted. Our results determined that 290 genes were consistently up-regulated in P. gingivalis infected epithelial cells. 229 gene ontology biological process terms of up-regulated genes were discovered, including "negative regulation of apoptotic process" and "positive regulation of cell proliferation/migration/angiogenesis". In addition to the well-known inflammatory signaling pathways, the pathway associated with a transcriptional misregulation in cancer has also been increased. Our findings indicated that P. gingivalis benefited from the survival of epithelial cells, and got its success as a colonizer in oral epithelium. The results also suggested that infection of P. gingivalis might contribute to oral cancer through chronic inflammation. Negative regulation of the apoptotic process and transcriptional misregulation in cancer pathway are important contributors to the cellular physiology changes during infection development, which have particular relevance to the pathogenesis and progressions of periodontitis, even to the occurrence of oral cancer.

Biomarkers: paving stones on the road towards the personalized precision medicine for oral squamous cell carcinoma

Traditional therapeutics have encountered a bottleneck caused by diagnosis delay and subjective and unreliable assessment. Biomarkers can overcome this bottleneck and guide us toward personalized precision medicine for oral squamous cell carcinoma. To achieve this, it is important to efficiently and accurately screen out specific biomarkers from among the huge number of molecules. Progress in omics-based high-throughput technology has laid a solid foundation for biomarker discovery. With credible and systemic biomarker models, more precise and personalized diagnosis and assessment would be achieved and patients would be more likely to be cured and have a higher quality of life. However, this is not straightforward owing to the complexity of molecules involved in tumorigenesis. In this context, there is a need to focus on tumor heterogeneity and homogeneity, which are discussed in detail. In this review, we aim to provide an understanding of biomarker discovery and application for precision medicine of oral squamous cell carcinoma, and have a strong belief that biomarker will pave the road toward future precision medicine.

Gene Expression Signatures for Head and Neck Cancer Patient Stratification: Are Results Ready for Clinical Application?

OPINION STATEMENT

Head and neck squamous cell carcinoma (HNSCC) is the sixth leading cancer by incidence worldwide and considering the recent EUROCARE-5 population-based study the 5-year survival rate of HNSCC patients in Europe ranges between 69% in localized cases and 34% in patients with regional involvement. The development of high-throughput gene expression assays in the last two decades has provided the invaluable opportunity to improve our knowledge on cancer biology and to identify predictive signatures in the most deeply analyzed malignancies, such as hematological and breast cancers. At variance, till 2010, the number of reliable reports referring gene expression data related to HSNCC biology and prediction was quite limited. A critical revision of the literature reporting gene expression data in HNSCC indicated that in the last 6 years, there were new important studies with a relevant increase in the sample size and a more accurate selection of cases, the publication of a growing number of studies applying a computational integration (meta-analysis) of different microarray datasets addressing similar clinical/biological questions, the increased use of molecular sub-classification of tumors according to their gene expression, and the release of the publicly available largest dataset in HNSCC by The Cancer Genome Atlas (TCGA) consortium. Overall, also for this disease, it become evident that the expression analysis of the entire transcriptome has been enabling to achieve the identification of promising molecular signatures for (i) disclosure of the biology behind carcinogenesis with special focus on the HPV-related one, (ii) prediction of tumor recurrence or metastasis development, (iii) identification of subgroups of tumors with different biology and associated prognosis, and (iv) prediction of outcome and/or response to therapy. The increasing awareness of the relevance of strict collaboration among clinicians and translational researchers would in a near future enable the application of a personalized HNSCCs patients' treatment in the clinical practice based also on gene expression signatures.

In silico analysis of pathways activation landscape in oral squamous cell carcinoma and oral leukoplakia

A subset of patients with oral squamous cell carcinoma (OSCC), the most common subtype of head and neck squamous cell carcinoma (HNSCC), harbor dysplastic lesions (often visually identified as leukoplakia) prior to cancer diagnosis. Although evidence suggest that leukoplakia represents an initial step in the progression to cancer, signaling networks driving this progression are poorly understood. Here, we applied in silico Pathway Activation Network Decomposition Analysis (iPANDA), a new bioinformatics software suite for qualitative analysis of intracellular signaling pathway activation using transcriptomic data, to assess a network of molecular signaling in OSCC and pre-neoplastic oral lesions. In tumor samples, our analysis detected major conserved mitogenic and survival signaling pathways strongly associated with HNSCC, suggesting that some of the pathways identified by our algorithm, but not yet validated as HNSCC related, may be attractive targets for future research. While pathways activation landscape in the majority of leukoplakias was different from that seen in OSCC, a subset of pre-neoplastic lesions has demonstrated some degree of similarity to the signaling profile seen in tumors, including dysregulation of the cancer-driving pathways related to survival and apoptosis. These results suggest that dysregulation of these signaling networks may be the driving force behind the early stages of OSCC tumorigenesis. While future studies with larger leukoplakia data sets are warranted to further estimate the values of this approach for capturing signaling features that characterize relevant lesions that actually progress to cancers, our platform proposes a promising new approach for detecting cancer-promoting pathways and tailoring the right therapy to prevent tumorigenesis.