Precision medicine in head and neck cancer

Kaidar‐Person, Orit; Gil, Ziv; Billan, Salem

doi:10.1016/j.drup.2018.09.001

Cited by 142 publications

(106 citation statements)

References 32 publications

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“…[34][35][36][37][38] The current treatment strategies of patients with HNSCC including surgery, radiation therapy (RT), chemotherapy with small molecule inhibitors or antibodies, immunotherapy, targeted therapy or combined modality treatments. 39,40 Head and Neck cancers continue to pose a major treatment challenge for identification of biomarkers for the early detection and prognosis of HNSCC.…”

Section: Discussionmentioning

confidence: 99%

MAGE-A11 Expression Predicts Patient Prognosis in Head and Neck Squamous Cell Carcinoma

Jia

Zhang

et al. 2020

CMAR

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Background: Head and neck squamous cell carcinomas (HNSCCs) are the sixth most common cancer worldwide. Growing evidence showed that Melanoma-associated antigen-A11 (MAGE-A11) was abnormally expressed in various malignancies, but MAGE-A11 expression and its biological roles in HNSCC had not been reported in detail. The aim of the study was to investigate the association between MAGE-A11 signatures and clinicopathological features of HNSCC patients and uncover its potential mechanisms in HNSCC patients. Methods: In the present study, we analyzed the expression of MAGE-A11 gene and evaluated the impact of MAGE-A11 genes expression on clinical outcome from the Cancer Genome Atlas (TCGA) database. MAGE-A11 expression was assessed in a wellcharacterized series of HNSCC (N = 75) with long-term follow-up and 10 cases of adjacent non-cancerous tissues, which were diagnosed between 2013 and 2014, by using immunohistochemistry. The correlation between MAGE-A11 expression and clinicopathological factors was analyzed. Kaplan-Meier and Cox regression analyses were used to assess the prognostic significance of MAGE-A11 expression among HNSCC patients. Results: The results showed that MAGE-A11 mRNA expression was increased in HNSCC tissues compared to "normal" tissues (P < 10 −12). MAGE-A11 protein expression was not correlated with lymph node status, relapse, age, gender, histological grade, differentiation, clinical stage, tumor size, radiotherapy or chemotherapy. The patients with high MAGE-A11 expression had lower 5-year overall survival (OS) rates than those with low MAGE-A11 expression as determined using the Kaplan-Meier method. The univariate and multivariate analyses confirmed that elevated MAGE-A11 was an independent prognostic factor for the OS of HNSCC patients. Conclusion: These findings indicate that MAGE-A11 may be a valuable diagnostic or prognostic marker as well as a potential molecular therapy target for HNSCC patients.

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Section: Discussionmentioning

confidence: 99%

MAGE-A11 Expression Predicts Patient Prognosis in Head and Neck Squamous Cell Carcinoma

Jia

Zhang

et al. 2020

CMAR

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“…HNSCC has a high morbidity and mortality, with a 5-year survival rate of only 40−50%, and more than 60% of patients are in advanced stages at their first clinical visit. 23,24 Therefore, it is vital to explore the diagnosis and prognosis biomarkers. In recent years, lncRNA has attracted widespread attention from researchers.…”

Section: Discussionmentioning

confidence: 99%

Identification and Clinical Validation of 4-lncRNA Signature for Predicting Survival in Head and Neck Squamous Cell Carcinoma

Xue

2020

OTT

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Background: The prognosis of patients with head and neck squamous cell carcinoma (HNSCC) is still poor due to the lack of effective prognostic biomarkers. lncRNA is an important survival prognostic indicator and has important biological functions in tumorigenesis. Methods: RNA-seq was re-annotated, and comprehensive clinical information was obtained from the GEO database. Univariate and multivariate Cox regression analyses were used to construct the lncRNA prognosis signature. Gene set enrichment analysis (GSEA) enrichment analysis method is used to explore the possible mechanism of the selected lncRNA influencing HNSCC development. The rms package was used to calculate the C-index to evaluate the overall prediction performance between different signature. PCR is used to detect the expression of selected lncRNA in cancer and adjacent tissues. Results: In the GSE65858 training cohort, 124 probes significantly related to prognosis were identified, 11 significant lncRNAs were further selected by rbsurv dimensionality reduction analysis. Finally, 4-lncRNA signature was constructed by multivariate Cox analysis. This signature was associated with tumor-associated pathway and is an independent factor of the patient's prognosis. 4-lncRNA signature has strong robustness and can exert stable prediction performance in different cohorts. A nomogram comprising the prognostic model to predict the overall survival was established. The 4-lncRNA signature was significantly upregulated in HNSCC samples. Conclusion: The predictive model and nomogram will enable patients to be more accurately managed in trials and clinical practices and could be applied as a new prognostic model for predicting survival of HNSCC patients.

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“…The fact that the immune system is apparently important to the prognosis of HNSCC patients adds to immune modulation as a potential new dimension of treatment, which has already been approved regarding cytotoxic T-lymphocyte-associated protein (CTLA)-4 and programmed cell death protein (PD)-1 inhibition as an option for head and neck cancer patients [ 103 ]. The present results also suggest targeting the inflammatory dimension of HNSCC in treatment with agents, such as, e.g., specific antibodies.…”

Section: Discussionmentioning

confidence: 99%

The Acute Phase Reaction and Its Prognostic Impact in Patients with Head and Neck Squamous Cell Carcinoma: Single Biomarkers Including C-Reactive Protein Versus Biomarker Profiles

et al. 2020

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C-reactive protein (CRP) has a prognostic impact in head and neck squamous cell carcinoma (HNSCC). However, the acute phase reaction involves many other proteins depending on its inducing events, including various cytokines that can function as reaction inducers. In the present study, we compared the pretreatment acute phase cytokine profile for 144 patients with potentially curative HNSCC. We investigated the systemic levels of interleukin (IL)6 family mediators (glycoprotein (gp130), IL6 receptor (R)α, IL6, IL27, IL31, oncostatin M (OSM), ciliary neurotrophic factor (CNTF)), IL1 subfamily members (IL1R antagonist (A), IL33Rα), and tumor necrosis factor (TNF)α. Patient subsets identified from this 10-mediator profile did not differ with regard to disease stage, human papilloma virus (HPV) status, CRP levels, or death cause. Increased CRP, IL6, and IL1RA levels were independent markers for HNSCC-related death in the whole patient population. Furthermore, gp130, IL6Rα, and IL31 were suggested to predict prognosis among tumor HPV-negative patients. Only IL6 predicted survival in HPV-positive patients. Finally, we did a clustering analysis of HPV-negative patients based on six acute phase mediators that showed significant or borderline association with prognosis in Kaplan–Meier analyses; three subsets could then be identified, and they differed in survival (p < 0.001). To conclude, (i) HPV-negative and HPV-positive HNSCC patients show similar variations of their systemic acute phase profiles; (ii) the prognostic impact of single mediators differs between these two patient subsets; and (iii) for HPV-negative patients, acute phase profiling identifies three patient subsets that differ significantly in survival.

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Precision medicine in head and neck cancer

Cited by 142 publications

References 32 publications

<p>MAGE-A11 Expression Predicts Patient Prognosis in Head and Neck Squamous Cell Carcinoma</p>

<p>MAGE-A11 Expression Predicts Patient Prognosis in Head and Neck Squamous Cell Carcinoma</p>

<p>Identification and Clinical Validation of 4-lncRNA Signature for Predicting Survival in Head and Neck Squamous Cell Carcinoma</p>

The Acute Phase Reaction and Its Prognostic Impact in Patients with Head and Neck Squamous Cell Carcinoma: Single Biomarkers Including C-Reactive Protein Versus Biomarker Profiles

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