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Head and neck cancer subtypes with biological and clinical relevance: Meta-analysis of gene-expression data.

De Cecco L, Nicolau M, Giannoccaro M, Daidone MG, Bossi P, Locati L, Licitra L, Canevari S - Oncotarget (2015)

Bottom Line: Based on their main biological characteristics and de-regulated signaling pathways, the subtypes were designed as immunoreactive, inflammatory, human papilloma virus (HPV)-like, classical, hypoxia associated, and mesenchymal.Our findings highlighted a more aggressive behavior for mesenchymal and hypoxia-associated subtypes.The Genomics Drug Sensitivity Project was used to identify potential associations with drug sensitivity and significant differences were observed among the six subtypes.

View Article: PubMed Central - PubMed

Affiliation: Functional Genomics and Bioinformatics, Department of Experimental Oncology and Molecular Medicine, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy.

ABSTRACT
Head and neck squamous cell carcinoma (HNSCC) is a disease with heterogeneous clinical behavior and response to therapies. Despite the introduction of multimodality treatment, 40-50% of patients with advanced disease recur. Therefore, there is an urgent need to improve the classification beyond the current parameters in clinical use to better stratify patients and the therapeutic approaches. Following a meta-analysis approach we built a large training set to whom we applied a Disease-Specific Genomic Analysis (DSGA) to identify the disease component embedded into the tumor data. Eleven independent microarray datasets were used as validation sets. Six different HNSCC subtypes that summarize the aberrant alterations occurring during tumor progression were identified. Based on their main biological characteristics and de-regulated signaling pathways, the subtypes were designed as immunoreactive, inflammatory, human papilloma virus (HPV)-like, classical, hypoxia associated, and mesenchymal. Our findings highlighted a more aggressive behavior for mesenchymal and hypoxia-associated subtypes. The Genomics Drug Sensitivity Project was used to identify potential associations with drug sensitivity and significant differences were observed among the six subtypes. To conclude, we report a robust molecularly defined subtype classification in HNSCC that can improve patient selection and pave the way to the development of appropriate therapeutic strategies.

No MeSH data available.


Related in: MedlinePlus

Progression analysis of diseaseThe average distance of each tumor from the normal state has been assessed. A. 603 genes were identified associated to PAD. The upper bar illustrates to which subtype belongs each tumor sample. B. The box plots show the distance from normal state of each tumor was in relation to the six subtypes. Y-axis represents the distance from normal state computed as average bin-membership by PAD and depicted in Figure S4.
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Figure 5: Progression analysis of diseaseThe average distance of each tumor from the normal state has been assessed. A. 603 genes were identified associated to PAD. The upper bar illustrates to which subtype belongs each tumor sample. B. The box plots show the distance from normal state of each tumor was in relation to the six subtypes. Y-axis represents the distance from normal state computed as average bin-membership by PAD and depicted in Figure S4.

Mentions: We applied Mapper [18] a tool able to capture topological and geometric shapes in complex multidimensional data and included in PAD software, to the DSGA-transformed data matrix computed on the 527 cases in our meta-analysis. Figure S4 shows the output of PAD analysis. HNSCC tumors can be associated through a linear progression starting from tumors displaying features close to the normal state (blue bins) and ending with tumors with large deviation from the normal state (red bins), suggesting an increase in alterations accumulated during different stages of tumor progression. Through PAD analysis, 603 genes were found to significantly correlate to tumor progression (Figure 5A). The genes negatively correlated to PAD (i.e. up-regulated in tumors close to the normal state) were enriched in chemokines and cytokine indicating a huge communication among tumor cells and stroma. As the disease progresses, tumors present genes positively correlated to PAD and encode proteins related to tumor plasticity, invasion, and metastasis. Functional analysis of signaling pathways and network connections were performed by IPA. The top molecular functions (imposing a score >30) are illustrated in Figure S5.


Head and neck cancer subtypes with biological and clinical relevance: Meta-analysis of gene-expression data.

De Cecco L, Nicolau M, Giannoccaro M, Daidone MG, Bossi P, Locati L, Licitra L, Canevari S - Oncotarget (2015)

Progression analysis of diseaseThe average distance of each tumor from the normal state has been assessed. A. 603 genes were identified associated to PAD. The upper bar illustrates to which subtype belongs each tumor sample. B. The box plots show the distance from normal state of each tumor was in relation to the six subtypes. Y-axis represents the distance from normal state computed as average bin-membership by PAD and depicted in Figure S4.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4496244&req=5

Figure 5: Progression analysis of diseaseThe average distance of each tumor from the normal state has been assessed. A. 603 genes were identified associated to PAD. The upper bar illustrates to which subtype belongs each tumor sample. B. The box plots show the distance from normal state of each tumor was in relation to the six subtypes. Y-axis represents the distance from normal state computed as average bin-membership by PAD and depicted in Figure S4.
Mentions: We applied Mapper [18] a tool able to capture topological and geometric shapes in complex multidimensional data and included in PAD software, to the DSGA-transformed data matrix computed on the 527 cases in our meta-analysis. Figure S4 shows the output of PAD analysis. HNSCC tumors can be associated through a linear progression starting from tumors displaying features close to the normal state (blue bins) and ending with tumors with large deviation from the normal state (red bins), suggesting an increase in alterations accumulated during different stages of tumor progression. Through PAD analysis, 603 genes were found to significantly correlate to tumor progression (Figure 5A). The genes negatively correlated to PAD (i.e. up-regulated in tumors close to the normal state) were enriched in chemokines and cytokine indicating a huge communication among tumor cells and stroma. As the disease progresses, tumors present genes positively correlated to PAD and encode proteins related to tumor plasticity, invasion, and metastasis. Functional analysis of signaling pathways and network connections were performed by IPA. The top molecular functions (imposing a score >30) are illustrated in Figure S5.

Bottom Line: Based on their main biological characteristics and de-regulated signaling pathways, the subtypes were designed as immunoreactive, inflammatory, human papilloma virus (HPV)-like, classical, hypoxia associated, and mesenchymal.Our findings highlighted a more aggressive behavior for mesenchymal and hypoxia-associated subtypes.The Genomics Drug Sensitivity Project was used to identify potential associations with drug sensitivity and significant differences were observed among the six subtypes.

View Article: PubMed Central - PubMed

Affiliation: Functional Genomics and Bioinformatics, Department of Experimental Oncology and Molecular Medicine, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy.

ABSTRACT
Head and neck squamous cell carcinoma (HNSCC) is a disease with heterogeneous clinical behavior and response to therapies. Despite the introduction of multimodality treatment, 40-50% of patients with advanced disease recur. Therefore, there is an urgent need to improve the classification beyond the current parameters in clinical use to better stratify patients and the therapeutic approaches. Following a meta-analysis approach we built a large training set to whom we applied a Disease-Specific Genomic Analysis (DSGA) to identify the disease component embedded into the tumor data. Eleven independent microarray datasets were used as validation sets. Six different HNSCC subtypes that summarize the aberrant alterations occurring during tumor progression were identified. Based on their main biological characteristics and de-regulated signaling pathways, the subtypes were designed as immunoreactive, inflammatory, human papilloma virus (HPV)-like, classical, hypoxia associated, and mesenchymal. Our findings highlighted a more aggressive behavior for mesenchymal and hypoxia-associated subtypes. The Genomics Drug Sensitivity Project was used to identify potential associations with drug sensitivity and significant differences were observed among the six subtypes. To conclude, we report a robust molecularly defined subtype classification in HNSCC that can improve patient selection and pave the way to the development of appropriate therapeutic strategies.

No MeSH data available.


Related in: MedlinePlus