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

MRI radiomics in head and neck cancer from reproducibility to combined approaches

The clinical applicability of radiomics in oncology depends on its transferability to real-world settings. However, the absence of standardized radiomics pipelines combined with methodological variability and insufficient reporting may hamper the reproducibility of radiomic analyses, impeding its translation to clinics. This study aimed to identify and replicate published, reproducible radiomic signatures based on magnetic resonance imaging (MRI), for prognosis of overall survival in head and neck squamous cell carcinoma (HNSCC) patients. Seven signatures were identified and reproduced on 58 HNSCC patients from the DB2Decide Project. The analysis focused on: assessing the signatures' reproducibility and replicating them by addressing the insufficient reporting; evaluating their relationship and performances; and proposing a cluster-based approach to combine radiomic signatures, enhancing the prognostic performance. The analysis revealed key insights: (1) despite the signatures were based on different features, high correlations among signatures and features suggested consistency in the description of lesion properties; (2) although the uncertainties in reproducing the signatures, they exhibited a moderate prognostic capability on an external dataset; (3) clustering approaches improved prognostic performance compared to individual signatures. Thus, transparent methodology not only facilitates replication on external datasets but also advances the field, refining prognostic models for potential personalized medicine applications.

Immune-related pan-cancer gene expression signatures of patient survival revealed by NanoString-based analyses

The immune system plays a central role in the onset and progression of cancer. A better understanding of transcriptional changes in immune cell-related genes associated with cancer progression, and their significance in disease prognosis, is therefore needed. NanoString-based targeted gene expression profiling has advantages for deployment in a clinical setting over RNA-seq technologies. We analysed NanoString PanCancer Immune Profiling panel gene expression data encompassing 770 genes, and overall survival data, from multiple previous studies covering 10 different cancer types, including solid and blood malignancies, across 515 patients. This analysis revealed an immune gene signature comprising 39 genes that were upregulated in those patients with shorter overall survival; of these 39 genes, three (MAGEC2, SSX1 and ULBP2) were common to both solid and blood malignancies. Most of the genes identified have previously been reported as relevant in one or more cancer types. Using Cibersort, we investigated immune cell levels within individual cancer types and across groups of cancers, as well as in shorter and longer overall survival groups. Patients with shorter survival had a higher proportion of M2 macrophages and γδ T cells. Patients with longer overall survival had a higher proportion of CD8+ T cells, CD4+ T memory cells, NK cells and, unexpectedly, T regulatory cells. Using a transcriptomics platform with certain advantages for deployment in a clinical setting, our multi-cancer meta-analysis of immune gene expression and overall survival data has identified a specific transcriptional profile associated with poor overall survival.

HPV-Related Prognostic Signature Predicts Survival in Head and Neck Squamous Cell Carcinoma

Background. Head and neck squamous cell carcinoma (HNSCC) is one of the most common cancers, worldwide. Considering the role of human papilloma virus (HPV) in tumor development and sensitivity to treatment of HNSCC, we aimed to explore the prognostic classification ability of HPV-related signatures in head and neck cancer. Methods. HPV-related signatures were screened out based on Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) databases. HPV-related signatures with prognostic value were identified through univariate Cox regression analysis and a risk signature was established by least absolute shrinkage and selection operator (LASSO). Further, we developed a nomogram by integrating independent prognostic factors. Results. A total of 55 HPV-associated signatures were differentially expressed and ten of them were associated with prognosis of HNSCC patients. The prognostic signature based on CDKN2A, CELSR3, DMRTA2, SERPINE1, TJP3, FADD, and IGF2BP2 expression was constructed. Univariate and multivariate regression analyses demonstrated that the novel prognostic signature was an independent prognostic factor of HNSCC. The nomogram integrating the prognostic signature and other independent prognostic factors was developed. Conclusion. In summary, the prognostic signature of the HPV-related signatures might serve as an important prognostic biomarker for patients with HNSCC.

Prostate Cancer Secretome and Membrane Proteome from Pten Conditional Knockout Mice Identify Potential Biomarkers for Disease Progression

Prostate cancer (PCa) is the second most common cause of mortality among men. Tumor secretome is a promising strategy for understanding the biology of tumor cells and providing markers for disease progression and patient outcomes. Here, transcriptomic-based secretome analysis was performed on the PCa tumor transcriptome of Genetically Engineered Mouse Model (GEMM) Pb-Cre4/Pten^f/f mice to identify potentially secreted and membrane proteins—PSPs and PMPs. We combined a selection of transcripts from the GSE 94574 dataset and a list of protein-coding genes of the secretome and membrane proteome datasets using the Human Protein Atlas Secretome. Notably, nine deregulated PMPs and PSPs were identified in PCa (DMPK, PLN, KCNQ5, KCNQ4, MYOC, WIF1, BMP7, F3, and MUC1). We verified the gene expression patterns of Differentially Expressed Genes (DEGs) in normal and tumoral human samples using the GEPIA tool. DMPK, KCNQ4, and WIF1 targets were downregulated in PCa samples and in the GSE dataset. A significant association between shorter survival and KCNQ4, PLN, WIF1, and F3 expression was detected in the MSKCC dataset. We further identified six validated miRNAs (mmu-miR-6962-3p, mmu-miR- 6989-3p, mmu-miR-6998-3p, mmu-miR-5627-5p, mmu-miR-15a-3p, and mmu-miR-6922-3p) interactions that target MYOC, KCNQ5, MUC1, and F3. We have characterized the PCa secretome and membrane proteome and have spotted new dysregulated target candidates in PCa.

Assessment of gene expressions from squamous cell carcinoma of the head and neck to predict radiochemotherapy-related xerostomia and dysphagia

PURPOSE

We tested the hypothesis that gene expressions from biopsies of locally advanced head and neck squamous cell carcinoma (HNSCC) patients can supplement dose-volume parameters to predict dysphagia and xerostomia following primary radiochemotherapy (RCTx).

MATERIAL AND METHODS

A panel of 178 genes previously related to radiochemosensitivity of HNSCC was considered for nanoString analysis based on tumour biopsies of 90 patients with locally advanced HNSCC treated by primary RCTx. Dose-volume parameters were extracted from the parotid, submandibular glands, oral cavity, larynx, buccal mucosa, and lips. Normal tissue complication probability (NTCP) models were developed for acute, late, and for the improvement of xerostomia grade ≥2 and dysphagia grade ≥3 using a cross-validation-based least absolute shrinkage and selection operator (LASSO) approach combined with stepwise logistic regression for feature selection. The final signatures were included in a logistic regression model with optimism correction. Performance was assessed by the area under the receiver operating characteristic curve (AUC).

RESULTS

NTCP models for acute and late xerostomia and the improvement of dysphagia resulted in optimism-corrected AUC values of 0.84, 0.76, and 0.70, respectively. The minimum dose to the contralateral parotid was selected for both acute and late xerostomia and the minimum dose to the larynx was selected for dysphagia improvement. For the xerostomia endpoints, the following gene expressions were selected: RPA2 (cellular response to DNA damage), TCF3 (salivary gland cells development), GBE1 (glycogen storage and regulation), and MAPK3 (regulation of cellular processes). No gene expression features were selected for the prediction of dysphagia.

CONCLUSION

This hypothesis-generating study showed the potential of improving NTCP models using gene expression data for HNSCC patients. The presented models require independent validation before potential application in clinical practice.

A robust and interpretable gene signature for predicting the lymph node status of primary T1/T2 oral cavity squamous cell carcinoma

Oral cavity squamous cell carcinoma (OSCC) affects more than 30 000 individuals in the United States annually, with smoking and alcohol consumption being the main risk factors. Management of early-stage tumors usually includes surgical resection followed by postoperative radiotherapy in certain cases. The cervical lymph nodes (LNs) are the most common site for local metastasis, and elective neck dissection is usually performed if the primary tumor thickness is greater than 3.5 mm. However, postoperative histological examination often reveals that many patients with early-stage disease are negative for neck nodal metastasis, posing a pressing need for improved risk stratification to either avoid overtreatment or prevent the disease progression. To this end, we aimed to identify a primary tumor gene signature that can accurately predict cervical LN metastasis in patients with early-stage OSCC. Using gene expression profiles from 189 samples, we trained K-top scoring pairs models and identified six gene pairs that can distinguish primary tumors with nodal metastasis from those without metastasis. The signature was further validated on an independent cohort of 35 patients using real-time polymerase chain reaction (PCR) in which it achieved an area under the receiver operating characteristic (ROC) curve and accuracy of 90% and 91%, respectively. These results indicate that such signature holds promise as a quick and cost effective method for detecting patients at high risk of developing cervical LN metastasis, and may be potentially used to guide the neck treatment regimen in early-stage OSCC.

SOD2- and NRF2-associated Gene Signature to Predict Radioresistance in Head and Neck Cancer

BACKGROUND

We propose a novel prognostic biomarker-based strategy for increasing the efficacy of radiotherapy (RT) in head and neck squamous cell carcinoma (HNSCC).

MATERIALS AND METHODS

We identified genes associated with superoxide dismutase 2 (SOD2) and nuclear factor erythroid-2-related factor 2 (NRF2) from gene-expression data of The Cancer Genome Atlas (TCGA) by calculating Pearson correlation. Patients were divided into two groups using hierarchical clustering. Colony-formation assay was performed to determine radioresistance in HNSCC cell line CAL27. Pathway analysis was conducted using The Database for Annotation, Visualization and Integrated Discovery (DAVID).

RESULTS

We developed a 49-gene signature with SOD2- and NRF2-associated genes. Using mRNA expression data for the 49-gene signature, we performed hierarchical clustering to stratify patients into two subtypes, subtype A and B. In the TCGA cohort, subgroup A demonstrated a better prognosis than subgroup B in patients who received RT. The signature robustness was evaluated in other independent cohorts. We showed through colony-formation assay that depletion of SOD2 or NRF2 leads to increased radiosensitivity.

CONCLUSION

We identified and validated a robust gene signature of SOD2- and NRF2-associated genes in HNSCC and confirmed their link to radioresistance using in vitro assay, providing a novel biomarker for the evaluation of HNSCC prognosis.

Oral Cancer: Genetics and the Role of Precision Medicine

Oral squamous cell carcinoma (OSCC) is one of the leading cancers in the world. OSCC patients are managed with surgery and/or chemoradiation. Prognoses and survival rates are dismal, however, and have not improved for more than 20 years. Recently, the concept of precision medicine was introduced, and the introduction of targeted therapeutics demonstrated promising outcomes. This article reviews the current understanding of initiation, progression, and metastasis of OSCC from both genetic and epigenetic perspectives. In addition, the applications and integration of omics technologies in biomarker discovery and drug development for treating OSCC are reviewed.

A Transcriptomic Analysis of Head and Neck Squamous Cell Carcinomas for Prognostic Indications

Survival analysis of the Cancer Genome Atlas (TCGA) dataset is a well-known method for discovering gene expression-based prognostic biomarkers of head and neck squamous cell carcinoma (HNSCC). A cutoff point is usually used in survival analysis for patient dichotomization when using continuous gene expression values. There is some optimization software for cutoff determination. However, the software's predetermined cutoffs are usually set at the medians or quantiles of gene expression values. There are also few clinicopathological features available in pre-processed datasets. We applied an in-house workflow, including data retrieving and pre-processing, feature selection, sliding-window cutoff selection, Kaplan-Meier survival analysis, and Cox proportional hazard modeling for biomarker discovery. In our approach for the TCGA HNSCC cohort, we scanned human protein-coding genes to find optimal cutoff values. After adjustments with confounders, clinical tumor stage and surgical margin involvement were found to be independent risk factors for prognosis. According to the results tables that show hazard ratios with Bonferroni-adjusted p values under the optimal cutoff, three biomarker candidates, CAMK2N1, CALML5, and FCGBP, are significantly associated with overall survival. We validated this discovery by using the another independent HNSCC dataset (GSE65858). Thus, we suggest that transcriptomic analysis could help with biomarker discovery. Moreover, the robustness of the biomarkers we identified should be ensured through several additional tests with independent datasets.

Predicting the clinical outcome of oral potentially malignant disorders using transcriptomic-based molecular pathology

BACKGROUND

This study was undertaken to develop and validate a gene expression signature that characterises oral potentially malignant disorders (OPMD) with a high risk of undergoing malignant transformation.

METHODS

Patients with oral epithelial dysplasia at one hospital were selected as the 'training set' (n = 56) whilst those at another hospital were selected for the 'test set' (n = 66). RNA was extracted from formalin-fixed paraffin-embedded (FFPE) diagnostic biopsies and analysed using the NanoString nCounter platform. A targeted panel of 42 genes selected on their association with oral carcinogenesis was used to develop a prognostic gene signature. Following data normalisation, uni- and multivariable analysis, as well as prognostic modelling, were employed to develop and validate the gene signature.

RESULTS

A prognostic classifier composed of 11 genes was developed using the training set. The multivariable prognostic model was used to predict patient risk scores in the test set. The prognostic gene signature was an independent predictor of malignant transformation when assessed in the test set, with the high-risk group showing worse prognosis [Hazard ratio = 12.65, p = 0.0003].

CONCLUSIONS

This study demonstrates proof of principle that RNA extracted from FFPE diagnostic biopsies of OPMD, when analysed on the NanoString nCounter platform, can be used to generate a molecular classifier that stratifies the risk of malignant transformation with promising clinical utility.

Oropharyngeal Squamous Cell Carcinoma Treatment in the Era of Immune Checkpoint Inhibitors

While head and neck squamous cell carcinomas (HNSCC) are marginally decreasing due to the reduction in exposure to the major risk factors, tobacco and alcohol, the incidence of high-risk human papillomavirus (HPV)-positive oropharynx squamous cell carcinomas (OPSCC), especially those in the tonsil and base of tongue subsites, are increasing. Patients with the latter are younger, display a longer overall survival, and show a lower recurrence rate after standard-of-care treatment than those with HPV-negative OPSCC. This may reflect an important role for immune surveillance and control during the natural history of the virally driven tumour development. Immune deviation through acquisition of immune-suppressive factors in the tumour microenvironment (TME) is discussed in relation to treatment response. Understanding how the different immune factors are integrated in the TME battleground offers opportunities for identifying prognostic biomarkers as well as novel therapeutic strategies. OPSCC generally receive surgery or radiotherapy for early-stage tumour treatment, but many patients present with locoregionally advanced disease requiring multimodality therapies which can involve considerable complications. This review focuses on the utilization of newly emerged immune checkpoint inhibitors (PD-1/PD-L1 pathway) for treatment of HNSCC, in particular HPV-positive OPSCC, since they could be less toxic and more efficacious. PD-1/PD-L1 expression in the TME has been extensively investigated as a biomarker of patient response but is yet to provide a really effective means for stratification of treatment. Extensive testing of combinations of therapeutic approaches by types and sequencing will fuel the next evolution of treatment for OPSCC.

Identification and Complete Validation of Prognostic Gene Signatures for Human Papillomavirus-Associated Cancers: Integrated Approach Covering Different Anatomical Locations

Human papillomavirus (HPV) infects squamous epithelium and is a major cause of cervical cancer (CC) and a subset of head and neck cancers (HNC). Virus-induced tumorigenesis, molecular alterations, and related prognostic markers are expected to be similar between the two cancers, but they remain poorly understood. We present integrated molecular analysis of HPV-associated tumors from TCGA and GEO databases and identify prognostic biomarkers. Analysis of gene expression profiles identified common upregulated genes and pathways of DNA replication and repair in the HPV-associated tumors. We established 34 prognostic gene signatures with a universal cutoff value in TCGA-CC using Elastic Net Cox regression analysis. We were able to externally validate our results in the TCGA-HNC and several GEO data sets, and demonstrated prognostic power in HPV-associated HNC, but not in HPV-negative cancers. The HPV-related prognostic and predictive indicator did not discriminate other cancers, except bladder urothelial carcinoma. These results identify and completely validate a highly selective prognostic system and its cross-usefulness in HPV-associated cancers, regardless of the tumor's anatomical subsite.IMPORTANCE Persistent infection with high-risk HPV interferes with cell function regulation and causes cell mutations, which accumulate over the long term and eventually develop into cancer. Results of pathway enrichment analysis presumably showed this accumulation of intracellular damage during the chronic HPV-infected state. We used highly advanced statistical methods to identify the most appropriate genes and coefficients and developed the HPV-related prognostic and predictive indicator (HPPI) risk scoring system. We applied the same cutoff value to training and validation sets and demonstrated good prognostic performance in both data sets, and confirmed a consistent trend in external validation. Moreover, HPPI presented significant validation results for bladder cancer suspected to be related to HPV. This suggested that our risk scoring system based on the prognostic gene signature could play an important role in the development of treatment strategies for patients with HPV-related cancer.

[RNA in situ hybridization: technology, potential, and fields of application]

Significant improvements in the technology of RNA in situ hybridization (RNA-ISH) in the past five decades have opened up novel fields of its application as a valuable and an attractive adjunct to the portfolio of pathologist's daily routine diagnostic practice.In contrast to the former methodology, the current bDNA-based technology is not only easier to handle but also considerably more sensitive, enabling single-target molecule detection in formalin-fixed and paraffin-embedded tissue specimens without significant effort by both the lab and the evaluating pathologist, as assays can be run on standard automated staining devices and evaluated by light microscopy. Compared to molecular methods like RT-PCR and whole-genome analysis, RNA-ISH maintains tissue integrity thus offering the invaluable advantage of localization of target cells especially in relation to secreted proteins and expression of the target sequence in multiple cell types. The first clinical trials implementing RNA-ISH for patient stratification and selection are in progress and already led to the first drug approvals based on its use as a CDx test.In addition to its role as a complementary method for the establishment of novel IHC procedures or as an addition or replacement to IHC in the standard routine portfolio, RNA-ISH has gained special importance for its capacity to detect noncoding RNA species or mutation or splice variants, where no alternative procedures are available. This more complex application requires development of standardized procedures and involvement of the pathologist during assay establishment and for routine specimen evaluation.The present article reviews the development of RNA-ISH from its early uses to its current applications in research and diagnostics based on the authors' considerable experience of applying it as tool in a biopharmaceutical research organization.

A meta-learning approach for genomic survival analysis

RNA sequencing has emerged as a promising approach in cancer prognosis as sequencing data becomes more easily and affordably accessible. However, it remains challenging to build good predictive models especially when the sample size is limited and the number of features is high, which is a common situation in biomedical settings. To address these limitations, we propose a meta-learning framework based on neural networks for survival analysis and evaluate it in a genomic cancer research setting. We demonstrate that, compared to regular transfer-learning, meta-learning is a significantly more effective paradigm to leverage high-dimensional data that is relevant but not directly related to the problem of interest. Specifically, meta-learning explicitly constructs a model, from abundant data of relevant tasks, to learn a new task with few samples effectively. For the application of predicting cancer survival outcome, we also show that the meta-learning framework with a few samples is able to achieve competitive performance with learning from scratch with a significantly larger number of samples. Finally, we demonstrate that the meta-learning model implicitly prioritizes genes based on their contribution to survival prediction and allows us to identify important pathways in cancer.

Density of CD3+ and CD8+ cells in gingivo-buccal oral squamous cell carcinoma is associated with lymph node metastases and survival

The tumor immune microenvironment is emerging as a critical player in predicting cancer prognosis and response to therapies. However, the prognostic value of tumor-infiltrating immune cells in Gingivo-Buccal Oral Squamous Cell Carcinoma (GBOSCC) and their association with tumor size or lymph node metastases status require further elucidation. To study the relationship of tumor-infiltrating immune cells with tumor size (T stage) and lymph node metastases (N stages), we analyzed the density of tumor-infiltrating immune cells in archived, whole tumor resections from 94 patients. We characterized these sections by immune-histochemistry using 12 markers and enumerated tumor-infiltrating immune cells at the invasive margins (IM) and centers of tumors (CT). We observed that a higher density of CD3+ cells in the IM and CT was associated with smaller tumor size (T1-T2 stage). Fewer CD3+ cells was associated with larger tumor size (T3-T4 stage). High infiltration of CD3+and CD8+ cells in IM and CT as well as high CD4+ cell infiltrates in the IM was significantly associated with the absence of lymph node metastases. High infiltrates of CD3+ and CD8+ cells in CT was associated with significantly improved survival. Our results illustrate that the densities and spatial distribution of CD3+ and CD8+ cell infiltrates in primary GBOSCC tumors is predictive of disease progression and survival. Based on our findings, we recommend incorporating immune cell quantification in the TNM classification and routine histopathology reporting of GBOSCC. Immune cell quantification in CT and IM may help predict the efficacy of future therapies.

Liquid lncRNA Biopsy for the Evaluation of Locally Advanced and Metastatic Squamous Cell Carcinomas of the Head and Neck

Background: Long non-coding RNA (lncRNA) are RNA molecules that are more than 200 nucleotides long and have the ability to modify the activity of genes. They can be found in both healthy and cancer tissues, as well as in plasma, saliva and other bodily fluids. They can also be used as biomarkers of early detection, prognosis and chemotherapy resistance in several cancer types. Treatment of head and neck squamous cell carcinoma (HNSCC) patients with locally advanced disease is still difficult, and choice of treatment should be based on more precise and available biomarkers, such as those obtained from a liquid biopsy. For improvement of treatment efficacy, identification and clinical implementation of new biomarkers are of the utmost importance. Methods: Plasma samples drawn before (p1) and three cycles post (p2) (TPF: docetaxel, cisplatin, 5-fluorouracil/PF: cisplatin, 5-fluorouracil) chemotherapy from 53 HNSCC patients (17 with locally advanced and 36 with metastatic disease) and 14 healthy volunteers were studied. Expression levels of 90 lncRNA expression were analyzed using the qRT-PCR method, and the obtained results were compared between proper groups. Statistical analyses were carried out using Jupyter Notebooks (5.7.2), Python (ver. 3.6) and GraphPad Prism 8. Results: The study demonstrated the differences between the expressions of several lncRNA in cancer patients' and healthy volunteers' plasma, as well as between locally advanced and metastatic patients' groups. A correlation between the response to systemic therapy and lncRNA expression levels was observed. Patients with a (high/low) expression of Alpha 250 and Emx2os showed statistically significant differences in progression free survival (PFS), as well as for overall survival (OS) depending on the level of Alpha 250, snaR, SNHG1. The univariate and multivariate Cox regression model showed Alpha 250 as the best prognostic factor for HNSCC patients. Conclusions: Liquid biopsies based on lncRNAs are promising diagnostic tools that can be used to differentiate between those with cancer and healthy individuals. Additionally, they can also serve as biomarkers for chemotherapy resistance. An identified, circulating lncRNA Alpha 250 seems to prove the best prognostic biomarker, associated with extended PFS and OS, and should be validated in a larger cohort in the future.

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 the identification of adequate prognosticators in OPLs.

Elevated KLF7 levels may serve as a prognostic signature and might contribute to progression of squamous carcinoma

Global efforts have been undertaken to define the genome-wide distribution of epigenetic markers in cancerous tissues, which provide an invaluable opportunity to understand cancer biology and identify predictive signatures. Several studies have focused on the gene expression patterns of squamous carcinoma to identify tumor subtypes and find prognostic and therapeutic targets because squamous carcinoma genomes showed high instability. However, the number of reliable reports referring prognostic significance of genes and their role in squamous carcinoma is still quite limited. Krüppel-like factor 7 (KLF7) is a transcription factor that is widely expressed in numerous human tissues at low levels. Members of the KLF family have established roles in tumor cell fate, stress response, cell survival and the tumor-initiating properties of cancer stem-like cells. Hence to investigate whether KFL7 expression from cancer tissue holds promise as a prognostic and/or therapeutic target, we analyzed gene expression profiles from squamous carcinoma and surgical margin tissues in The Cancer Genome Atlas. We identified significant up-regulation of KLF7 in squamous carcinoma, which was confirmed by immunohistochemical staining. Elevated KLF7 expression was associated with poor squamous carcinoma prognosis before and after correcting for confounding factors by multivariate Cox regression analysis. Several pathways, such as Neurotrophin and GnRH pathways, were activated in KLF7-up-regulated squamous carcinoma samples through Gene Set Enrichment Analysis. In conclusion, we consolidate the potential role(s) of KLF7 in squamous carcinoma carcinogenesis from The Cancer Genome Atlas surgical margin tissue, offering insights into expression signatures that are potentially useful for prognosis modalities.

Genomics and precision surgery for head and neck squamous cell carcinoma

The identification of the biological determinants that shape the response of tumors to medical therapies offers perspectives for better patient stratification and therapeutic targeting. Here, we discuss how genomics could help to improve the surgical treatment of head and neck squamous cell carcinoma (HNSCC). We examine the potential use of genomic analyses for: i) refining and standardizing the indications for surgery, ii) the choice of surgical procedure, and iii) the follow-up of patients with resected tumors. We highlight the studies that used genomics to explore the contribution of tumor biology to the outcome of surgery. We discuss the important developments that are challenging current surgical practice in HNSCC, such as neoadjuvant immunotherapy and the analysis of circulating DNA. Genomic analyses provide practical tools that could help improve the pathological diagnosis and staging of HNSCC, and increase the appreciation of the importance of tumor biology in the outcome of surgery. Identification of biomarkers will likely contribute to a move toward precision surgery of HNSCC, i.e. the personalization of surgical practice based on tumor biology.

The prognostic value of a seven-lncRNA signature in patients with esophageal squamous cell carcinoma: a lncRNA expression analysis

Background

Long non-coding RNAs (lncRNAs) have been reported to be prognostic biomarkers in many types of cancer. We aimed to identify a lncRNA signature that can predict the prognosis in patients with esophageal squamous cell carcinoma (ESCC).

Methods

Using a custom microarray, we retrospectively analyzed lncRNA expression profiles in 141 samples of ESCC and 81 paired non-cancer specimens from Sun Yat-Sen University Cancer Center (Guangzhou, China), which were used as a training cohort to identify a signature associated with clinical outcomes. Then we conducted quantitative RT-PCR in another 103 samples of ESCC from the same cancer center as an independent cohort to verify the signature.

Results

Microarray analysis showed that there were 338 lncRNAs significantly differentially expressed between ESCC and non-cancer esophagus tissues in the training cohort. From these differentially expressed lncRNAs, we found 16 lncRNAs associated with overall survival (OS) of ESCC patients using Cox regression analysis. Then a 7-lncRNA signature for predicting survival was identified from the 16 lncRNAs, which classified ESCC patients into high-risk and low-risk groups. Patients with high-risk have shorter OS (HR: 3.555, 95% CI 2.195–5.757, p < 0.001) and disease-free survival (DFS) (HR: 2.537, 95% CI 1.646–3.909, p < 0.001) when compared with patients with low-risk in the training cohort. In the independent cohort, the 7 lncRNAs were detected by qRT-PCR and used to compute risk score for the patients. The result indicates that patients with high risk also have significantly worse OS (HR = 2.662, 95% CI 1.588–4.464, p < 0.001) and DFS (HR 2.389, 95% CI 1.447–3.946, p < 0.001). The univariate and multivariate Cox regression analyses indicate that the signature is an independent factor for predicting survival of patients with ESCC. Combination of the signature and TNM staging was more powerful in predicting OS than TNM staging alone in both the training (AUC: 0.772 vs 0.681, p = 0.002) and independent cohorts (AUC: 0.772 vs 0.660, p = 0.003).

Conclusions

The 7-lncRNA signature is a potential prognostic biomarker in patients with ESCC and may help in treatment decision when combined with the TNM staging system.

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.

Immunohistochemical Analysis Revealed a Correlation between Musashi-2 and Cyclin-D1 Expression in Patients with Oral Squamous Cells Carcinoma

Aim: Musashi 2 (MSI2), which is an RNA-binding protein, plays a fundamental role in the oncogenesis of several cancers. The aim of this study is to investigate the expression of MSI2 in Oral Squamous Cell Carcinoma (OSCC) and evaluate its correlation to clinic-pathological variables and prognosis. Materials and Methods: A bioinformatic analysis was performed on data downloaded from The Cancer Genome Atlas (TCGA) database. The MSI2 expression data were analysed for their correlation with clinic-pathological and prognostic features. In addition, an immmunohistochemical evaluation of MSI2 expression on 108 OSCC samples included in a tissue microarray and 13 healthy mucosae samples was performed. Results: 241 patients’ data from TCGA were included in the final analysis. No DNA mutations were detected for the MSI2 gene, but a hyper methylated condition of the gene emerged. MSI2 mRNA expression correlated with Grading (p = 0.009) and overall survival (p = 0.045), but not with disease free survival (p = 0.549). Males presented a higher MSI2 mRNA expression than females. The immunohistochemical evaluation revealed a weak expression of MSI2 in both OSCC samples and in healthy oral mucosae. In addition, MSI2 expression directly correlated with Cyclin-D1 expression (p = 0.022). However, no correlation has been detected with prognostic outcomes (overall and disease free survival). Conclusions: The role of MSI2 expression in OSCC seems to be not so closely correlated with prognosis, as in other human neoplasms. The correlation with Cyclin-D1 expression suggests an indirect role that MSI2 might have in the proliferation of OSCC cells, but further studies are needed to confirm such results.

Clinical update on head and neck cancer: molecular biology and ongoing challenges

Head and neck squamous cell carcinomas (HNSCCs) are an aggressive, genetically complex and difficult to treat group of cancers. In lieu of truly effective targeted therapies, surgery and radiotherapy represent the primary treatment options for most patients. But these treatments are associated with significant morbidity and a reduction in quality of life. Resistance to both radiotherapy and the only available targeted therapy, and subsequent relapse are common. Research has therefore focussed on identifying biomarkers to stratify patients into clinically meaningful groups and to develop more effective targeted therapies. However, as we are now discovering, the poor response to therapy and aggressive nature of HNSCCs is not only affected by the complex alterations in intracellular signalling pathways but is also heavily influenced by the behaviour of the extracellular microenvironment. The HNSCC tumour landscape is an environment permissive of these tumours' aggressive nature, fostered by the actions of the immune system, the response to tumour hypoxia and the influence of the microbiome. Solving these challenges now rests on expanding our knowledge of these areas, in parallel with a greater understanding of the molecular biology of HNSCC subtypes. This update aims to build on our earlier 2014 review by bringing up to date our understanding of the molecular biology of HNSCCs and provide insights into areas of ongoing research and perspectives for the future.

Preferential Response of Basal-Like Head and Neck Squamous Cell Carcinoma Cell Lines to EGFR-Targeted Therapy Depending on EREG-Driven Oncogenic Addiction

The management of locally advanced head and neck squamous cell carcinoma (HNSCC) with Cetuximab, a monoclonal antibody targeting the epidermal growth factor receptor (EGFR), achieves only moderate response rates, and clinical trials that evaluated EGFR-blockade with tyrosine kinase inhibitors (TKI) yielded disappointing results. Inter-tumor heterogeneity may hinder the therapeutic efficiency of anti-EGFR treatments. HNSCC heterogeneity was addressed in several studies, which all converged towards the definition of molecular subgroups. They include the basal subgroup, defined by the deregulated expression of factors involved in the EGFR signaling pathway, including the epiregulin EGFR ligand encoded by the EREG gene. These observations indicate that basal tumors could be more sensitive to anti-EGFR treatments. To test this hypothesis, we performed a screen of a representative collection of basal versus non-basal HNSCC cell lines for their sensitivity to several anti-EGFR drugs (Cetuximab, Afatinib, and Gefitinib), tested as monotherapy or in combination with drugs that target closely-linked pathways [Mitogen-activated protein kinase kinase/extracellular signal–regulated kinases (MEK), mammalian Target of Rapamycine (mTOR) or Human Epidermal growth factor Receptor 2 (HER2)]. Basal-like cell lines were found to be more sensitive to EGFR blockade alone or in combination with treatments that target MEK, mTOR, or HER2. Strikingly, the basal-like status was found to be a better predictor of cell response to EGFR blockade than clinically relevant mutations [e.g., cyclin-dependent kinase Inhibitor 2A (CDKN2A)]. Interestingly, we show that EGFR blockade inhibits EREG expression, and that EREG knock-down decreases basal cell clonogenic survival, suggesting that EREG expression could be a predictive functional marker of sensitivity to EGFR blockade in basal-like HNSCC.

Heterogeneity of the Head and Neck Squamous Cell Carcinoma Immune Landscape and Its Impact on Immunotherapy

Head and neck squamous cell carcinomas (HNSCCs) are highly aggressive, multi-factorial tumors in the upper aerodigestive tract affecting more than half a million patients worldwide each year. Alcohol, tobacco, and human papillomavirus (HPV) infection are well known causative factors for HNSCCs. Current treatment options for HNSCCs are surgery, radiotherapy, chemotherapy, or combinatorial remedies. Over the past decade, despite the marked improvement in clinical outcome of many tumor types, the overall 5-year survival rate of HNSCCs remained ∼40–50% largely due to poor availability of effective therapeutic options for HNSCC patients with recurrent disease. Therefore, there is an urgent and unmet need for the identification of specific molecular signatures that better predict the clinical outcomes and markers that serve as better therapeutic targets. With recent technological advances in genomic and epigenetic analyses, our knowledge of HNSCC molecular characteristics and classification has been greatly enriched. Clinical and genomic meta-analysis of multicohort HNSCC gene expression profile has clearly demonstrated that HPV⁺ and HPV^- HNSCCs are not only derived from tissues of different anatomical regions, but also present with different mutation profiles, molecular characteristics, immune landscapes, and clinical prognosis. Here, we briefly review our current understanding of the biology, molecular profile, and immunological landscape of the HPV⁺ and HPV^- HNSCCs with an emphasis on the diversity and heterogeneity of HNSCC clinicopathology and therapeutic responses. After a review of recent advances and specific challenges for effective immunotherapy of HNSCCs, we then conclude with a discussion on the need to further enhance our understanding of the unique characteristics of HNSCC heterogeneity and the plasticity of immune landscape. Increased knowledge regarding the immunological characteristics of HPV⁺ and HPV^- HNSCCs would improve therapeutic targeting and immunotherapy strategies for different subtypes of HNSCCs.

Molecular Classification of Lymph Node Metastases Subtypes Predict for Survival in Head and Neck Cancer

PURPOSE

In advanced stage head and neck squamous cell cancers (HNSCC), approximately half of the patients with lymph node metastases (LNM) are not cured. Given the heterogeneous outcomes in these patients, we profiled the expression patterns of LNMs to identify the biological factors associated with patient outcomes.Experimental Design: We performed mRNAseq and miRNAseq on 72 LNMs and 29 matched primary tumors from 34 patients with HNSCC. Clustering identified molecular subtypes in LNMs and in primary tumors. Prediction Analysis of Microarrays algorithm identified a 73-gene classifier that distinguished LNM subtypes. Gene-set enrichment analysis identified pathways upregulated in LNM subtypes.

RESULTS

Integrative clustering identified three distinct LNM subtypes: (i) an immune subtype (Group 1), (ii) an invasive subtype (Group 2), and (iii) a metabolic/proliferative subtype (Group 3). Group 2 subtype was associated with significantly worse locoregional control and survival. LNM-specific subtypes were not observed in matched primary tumor specimens. In HNSCCs, breast cancers, and melanomas, a 73-gene classifier identified similar Group 2 LNM subtypes that were associated with worse disease control and survival only when applied to lymph node sites, but not when applied to other primary tumors or metastatic sites. Similarly, previously proposed prognostic classifiers better distinguished patients with worse outcomes when applied to the transcriptional profiles of LNMs, but not the profiles of primary tumors.

CONCLUSIONS

The transcriptional profiles of LNMs better predict outcomes than transcriptional profiles of primary tumors. The LNMs display site-specific subtypes associated with worse disease control and survival across multiple cancer types.

A Five-MicroRNA Signature Predicts Survival and Disease Control of Patients with Head and Neck Cancer Negative for HPV Infection

PURPOSE

Human papillomavirus (HPV)-negative head and neck squamous cell carcinoma (HNSCC) is associated with unfavorable prognosis, while independent prognostic markers remain to be defined.

EXPERIMENTAL DESIGN

We retrospectively performed miRNA expression profiling. Patients were operated for locally advanced HPV-negative HNSCC and had received radiochemotherapy in eight different hospitals (DKTK-ROG; n = 85). Selection fulfilled comparable demographic, treatment, and follow-up characteristics. Findings were validated in an independent single-center patient sample (LMU-KKG; n = 77). A prognostic miRNA signature was developed for freedom from recurrence and tested for other endpoints. Recursive-partitioning analysis was performed on the miRNA signature, tumor and nodal stage, and extracapsular nodal spread. Technical validation used qRT-PCR. An miRNA-mRNA target network was generated and analyzed.

RESULTS

For DKTK-ROG and LMU-KKG patients, the median follow-up was 5.1 and 5.3 years, and the 5-year freedom from recurrence rate was 63.5% and 75.3%, respectively. A five-miRNA signature (hsa-let-7g-3p, hsa-miR-6508-5p, hsa-miR-210-5p, hsa-miR-4306, and hsa-miR-7161-3p) predicted freedom from recurrence in DKTK-ROG [hazard ratio (HR) 4.42; 95% confidence interval (CI), 1.98-9.88, P < 0.001], which was confirmed in LMU-KKG (HR 4.24; 95% CI, 1.40-12.81, P = 0.005). The signature also predicted overall survival (HR 3.03; 95% CI, 1.50-6.12, P = 0.001), recurrence-free survival (HR 3.16; 95% CI, 1.65-6.04, P < 0.001), and disease-specific survival (HR 5.12; 95% CI, 1.88-13.92, P < 0.001), all confirmed in LMU-KKG data. Adjustment for relevant covariates maintained the miRNA signature predicting all endpoints. Recursive-partitioning analysis of both samples combined classified patients into low (n = 17), low-intermediate (n = 80), high-intermediate (n = 48), or high risk (n = 17) for recurrence (P < 0.001).

CONCLUSIONS

The five-miRNA signature is a strong and independent prognostic factor for disease recurrence and survival of patients with HPV-negative HNSCC.See related commentary by Clump et al., p. 1441.

Oral Cancer: Genetics and the Role of Precision Medicine

Oral squamous cell carcinoma (OSCC) is one of the leading cancers in the world. OSCC patients are managed with surgery and/or chemoradiation. Prognoses and survival rates are dismal, however, and have not improved for more than 20 years. Recently, the concept of precision medicine was introduced, and the introduction of targeted therapeutics demonstrated promising outcomes. This article reviews the current understanding of initiation, progression, and metastasis of OSCC from both genetic and epigenetic perspectives. In addition, the applications and integration of omics technologies in biomarker discovery and drug development for treating OSCC are reviewed.

DDX3 Activates CBC-eIF3-Mediated Translation of uORF-Containing Oncogenic mRNAs to Promote Metastasis in HNSCC

Mutated or dysregulated DDX3 participates in the progression and metastasis of cancer via its multiple roles in regulating gene expression and cellular signaling. Here, we show that the high expression levels of DDX3 in head and neck squamous cell carcinoma (HNSCC) correlate with lymph node metastasis and poor prognosis and demonstrate that DDX3 is essential for the proliferation, invasion, and metastasis of oral squamous cell carcinoma (OSCC) cells. Microarray analyses revealed that DDX3 is required for the expression of a set of pro-metastatic genes, including ATF4-modulated genes in an aggressive OSCC cell line. DDX3 activated translation of ATF4 and a set of its downstream targets, all of which contain upstream open reading frames (uORF). DDX3 promoted translation of these targets, likely by skipping the inhibitory uORF. DDX3 specifically enhanced the association of the cap-binding complex (CBC) with uORF-containing mRNAs and facilitated recruitment of the eukaryotic initiation factor 3 (eIF3). CBC and certain eIF3 subunits contributed to the expression of metastatic-related gene expression. Taken together, our results indicate a role for the novel DDX3-CBC-eIF3 translational complex in promoting metastasis.Significance: The discovery of DDX3-mediated expression of oncogenic uORF-containing genes expands knowledge on translational control mechanisms and provides potential targets for cancer therapy.Graphical Abstract: http://cancerres.aacrjournals.org/content/canres/78/16/4512/F1.large.jpg Cancer Res; 78(16); 4512-23. ©2018 AACR.

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.

Expanding primary cells from mucoepidermoid and other salivary gland neoplasms for genetic and chemosensitivity testing

Restricted availability of cell and animal models is a rate-limiting step for investigation of salivary gland neoplasm pathophysiology and therapeutic response. Conditionally reprogrammed cell (CRC) technology enables establishment of primary epithelial cell cultures from patient material. This study tested a translational workflow for acquisition, expansion and testing of CRC-derived primary cultures of salivary gland neoplasms from patients presenting to an academic surgical practice. Results showed that cultured cells were sufficient for epithelial cell-specific transcriptome characterization to detect candidate therapeutic pathways and fusion genes, and for screening for cancer risk-associated single nucleotide polymorphisms (SNPs) and driver gene mutations through exome sequencing. Focused study of primary cultures of a low-grade mucoepidermoid carcinoma demonstrated amphiregulin-mechanistic target of rapamycin-protein kinase B (AKT; AKT1) pathway activation, identified through bioinformatics and subsequently confirmed as present in primary tissue and preserved through different secondary 2D and 3D culture media and xenografts. Candidate therapeutic testing showed that the allosteric AKT inhibitor MK2206 reproducibly inhibited cell survival across different culture formats. By contrast, the cells appeared resistant to the adenosine triphosphate competitive AKT inhibitor GSK690693. Procedures employed here illustrate an approach for reproducibly obtaining material for pathophysiological studies of salivary gland neoplasms, and other less common epithelial cancer types, that can be executed without compromising pathological examination of patient specimens. The approach permits combined genetic and cell-based physiological and therapeutic investigations in addition to more traditional pathologic studies, and can be used to build sustainable bio-banks for future inquiries.This article has an associated First Person interview with the first author of the paper.

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.