117 research outputs found

    A genome-wide association study of radiotherapy induced toxicity in head and neck cancer patients identifies a susceptibility locus associated with mucositis

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    PURPOSE: A two-stage genome-wide association study was carried out in head and neck cancer (HNC) patients aiming to identify genetic variants associated with either specific radiotherapy-induced (RT) toxicity endpoints or a general proneness to develop toxicity after RT.MATERIALS AND METHODS: The analysis included 1780 HNC patients treated with primary RT for laryngeal or oro/hypopharyngeal cancers. In a non-hypothesis-driven explorative discovery study, associations were tested in 1183 patients treated within The Danish Head and Neck Cancer Group. Significant associations were later tested in an independent Dutch cohort of 597 HNC patients and if replicated, summary data obtained from discovery and replication studies were meta-analysed. Further validation of significantly replicated findings was pursued in an Asian cohort of 235 HNC patients with nasopharynx as the primary tumour site.RESULTS: We found and replicated a significant association between a locus on chromosome 5 and mucositis with a pooled OR for rs1131769*C in meta-analysis = 1.95 (95% CI 1.48-2.41; ppooled = 4.34 × 10-16).CONCLUSION: This first exploratory GWAS in European cohorts of HNC patients identified and replicated a risk locus for mucositis. A larger Meta-GWAS to identify further risk variants for RT-induced toxicity in HNC patients is warranted.</p

    Tumor volume and cancer stem cell expression as prognostic markers for high-dose loco-regional failure in head and neck squamous cell carcinoma - A DAHANCA 19 study

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    BACKGROUND AND PURPOSE: Reliable and accessible biomarkers for patients with Head and Neck Squamous Cell Carcinoma (HNSCC) are warranted for biologically driven radiotherapy (RT). This study aimed to investigate the prognostic value of putative cancer stem cell (CSC) markers, hypoxia, and tumor volume using loco-regional high-dose failure (HDF) as endpoint.MATERIALS AND METHODS: Tumor tissue was retrieved from patients treated with primary chemo-(C-)RT and nimorazole for HNSCC in the Danish Head and Neck Cancer Study Group (DAHANCA) 19 study. Tumor volume, hypoxic classification, and expression of CSC markers CD44, SLC3A2, and MET were analyzed. For patients with eligible data on all parameters (n = 340), the risk of HDF following primary chemo-(C-)RT were analyzed by these biomarkers as a whole and stratified for p16-positive oropharynx (p16 + OPSCC) vs p16-negative (p16-) tumors (oral cavity, p16- oropharynx, hypopharynx and larynx).RESULTS: Higher risk of HDF was seen for patients with larger primary and nodal volume (&gt;25 cm3, Hazard Ratio (HR): 3.00 [95 % CI: 1.73-5.18]), high SLC3A2 (HR: 2.99 [1.28-6.99]), CD44 (&gt;30 % positive, HR: 2.29 [1.05-5.00]), and p16- tumors (HR: 2.53 [1.05-6.11]). p16- tumors had a higher CSC marker expression than p16 + OPSCC. The factors associated with the highest risk of HDF were larger volume (HR: 3.29 [1.79-6.04]) for p16- tumors (n = 178) and high SLC3A2 (HR: 6.19 [1.58-24.23]) for p16 + OPSCC (n = 162).CONCLUSION: Tumor volume, p16, and CSC markers are potential biomarkers for HDF for patients with HNSCC treated with (C-)RT. Lower expression of CSC in p16 + OPSCC may contribute to better tumor control.</p

    Integrative clustering reveals a novel split in the luminal A subtype of breast cancer with impact on outcome

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    Background: Breast cancer is a heterogeneous disease at the clinical and molecular level. In this study we integrate classifications extracted from five different molecular levels in order to identify integrated subtypes. Methods: Tumor tissue from 425 patients with primary breast cancer from the Oslo2 study was cut and blended, and divided into fractions for DNA, RNA and protein isolation and metabolomics, allowing the acquisition of representative and comparable molecular data. Patients were stratified into groups based on their tumor characteristics from five different molecular levels, using various clustering methods. Finally, all previously identified and newly determined subgroups were combined in a multilevel classification using a "cluster-of-clusters" approach with consensus clustering. Results: Based on DNA copy number data, tumors were categorized into three groups according to the complex arm aberration index. mRNA expression profiles divided tumors into five molecular subgroups according to PAM50 subtyping, and clustering based on microRNA expression revealed four subgroups. Reverse-phase protein array data divided tumors into five subgroups. Hierarchical clustering of tumor metabolic profiles revealed three clusters. Combining DNA copy number and mRNA expression classified tumors into seven clusters based on pathway activity levels, and tumors were classified into ten subtypes using integrative clustering. The final consensus clustering that incorporated all aforementioned subtypes revealed six major groups. Five corresponded well with the mRNA subtypes, while a sixth group resulted from a split of the luminal A subtype; these tumors belonged to distinct microRNA clusters. Gain-of-function studies using MCF-7 cells showed that microRNAs differentially expressed between the luminal A clusters were important for cancer cell survival. These microRNAs were used to validate the split in luminal A tumors in four independent breast cancer cohorts. In two cohorts the microRNAs divided tumors into subgroups with significantly different outcomes, and in another a trend was observed. Conclusions: The six integrated subtypes identified confirm the heterogeneity of breast cancer and show that finer subdivisions of subtypes are evident. Increasing knowledge of the heterogeneity of the luminal A subtype may add pivotal information to guide therapeutic choices, evidently bringing us closer to improved treatment for this largest subgroup of breast cancer.Peer reviewe

    Meta-GWAS identifies the heritability of acute radiation-induced toxicities in head and neck cancer

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    Background and purpose: We aimed to the genetic components and susceptibility variants associated with acute radiation-induced toxicities (RITs) in patients with head and neck cancer (HNC). Materials and methods: We performed the largest meta-GWAS of seven European cohorts (n = 4,042). Patients were scored weekly during radiotherapy for acute RITs including dysphagia, mucositis, and xerostomia. We analyzed the effect of variants on the average burden (measured as area under curve, AUC) per each RIT, and standardized total average acute toxicity (STATacute) score using a multivariate linear regression. We tested suggestive variants (p < 1.0x10-5) in discovery set (three cohorts; n = 2,640) in a replication set (four cohorts; n = 1,402). We meta-analysed all cohorts to calculate RITs specific SNP-based heritability, and effect of polygenic risk scores (PRSs), and genetic correlations among RITS. Results: From 393 suggestive SNPs identified in discovery set; 37 were nominally significant (preplication < 0.05) in replication set, but none reached genome-wide significance (pcombined < 5 × 10-8). In-silico functional analyses identified “3′-5'-exoribonuclease activity” (FDR = 1.6e-10) for dysphagia, “inositol phosphate-mediated signalling” for mucositis (FDR = 2.20e-09), and “drug catabolic process” for STATacute (FDR = 3.57e-12) as the most enriched pathways by the RIT specific suggestive genes. The SNP-based heritability (±standard error) was 29 ± 0.08 % for dysphagia, 9 ± 0.12 % (mucositis) and 27 ± 0.09 % (STATacute). Positive genetic correlation was rg = 0.65 (p = 0.048) between dysphagia and STATacute. PRSs explained limited variation of dysphagia (3 %), mucositis (2.5 %), and STATacute (0.4 %). Conclusion: In HNC patients, acute RITs are modestly heritable, sharing 10 % genetic susceptibility, when PRS explains < 3 % of their variance. We identified numerus suggestive SNPs, which remain to be replicated in larger studies

    In Silico Ascription of Gene Expression Differences to Tumor and Stromal Cells in a Model to Study Impact on Breast Cancer Outcome

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    Breast tumors consist of several different tissue components. Despite the heterogeneity, most gene expression analyses have traditionally been performed without prior microdissection of the tissue sample. Thus, the gene expression profiles obtained reflect the mRNA contribution from the various tissue components. We utilized histopathological estimations of area fractions of tumor and stromal tissue components in 198 fresh-frozen breast tumor tissue samples for a cell type-associated gene expression analysis associated with distant metastasis. Sets of differentially expressed gene-probes were identified in tumors from patients who developed distant metastasis compared with those who did not, by weighing the contribution from each tumor with the relative content of stromal and tumor epithelial cells in their individual tumor specimen. The analyses were performed under various assumptions of mRNA transcription level from tumor epithelial cells compared with stromal cells. A set of 30 differentially expressed gene-probes was ascribed solely to carcinoma cells. Furthermore, two sets of 38 and five differentially expressed gene-probes were mostly associated to tumor epithelial and stromal cells, respectively. Finally, a set of 26 differentially expressed gene-probes was identified independently of cell type focus. The differentially expressed genes were validated in independent gene expression data from a set of laser capture microdissected invasive ductal carcinomas. We present a method for identifying and ascribing differentially expressed genes to tumor epithelial and/or stromal cells, by utilizing pathologic information and weighted t-statistics. Although a transcriptional contribution from the stromal cell fraction is detectable in microarray experiments performed on bulk tumor, the gene expression differences between the distant metastasis and no distant metastasis group were mostly ascribed to the tumor epithelial cells of the primary breast tumors. However, the gene PIP5K2A was found significantly elevated in stroma cells in distant metastasis group, compared to stroma in no distant metastasis group. These findings were confirmed in gene expression data from the representative compartments from microdissected breast tissue. The method described was also found to be robust to different histopathological procedures

    In vivo Identification and Specificity assessment of mRNA markers of hypoxia in human and mouse tumors

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    <p>Abstract</p> <p>Background</p> <p>Tumor hypoxia is linked to poor prognosis, but identification and quantification of tissue hypoxia remains a challenge. The hypoxia-specificity of HIF-1Îą target genes in vivo has been questioned due to the confounding influence of other microenvironmental abnormalities known to affect gene expression (e.g., low pH). Here we describe a new technique that by exploiting intratumoral oxygenation heterogeneity allows us to identify and objectively rank the most robust mRNA hypoxia biomarkers.</p> <p>Methods</p> <p>Mice carrying human (FaDu<sub>dd</sub>) or murine (SCCVII) tumors were injected with the PET hypoxia tracer FAZA. Four hours post-injection tumors were removed, frozen, and crushed into milligram-sized fragments, which were transferred individually to pre-weighed tubes containing RNAlater and then weighed. For each fragment radioactivity per tissue mass and expression patterns of selected mRNA biomarkers were analyzed and compared.</p> <p>Results</p> <p>In both tumour models, fragmentation into pieces weighing 10 to 60 mg resulted in tissue fragments with highly variable relative content of hypoxic cells as evidenced by an up to 13-fold variation in FAZA radioactivity per mass of tissue. Linear regression analysis comparing FAZA retention with patterns of gene expression in individual tissue fragments revealed that CA9, GLUT1 and LOX mRNA levels were equally and strongly correlated to hypoxic extent in FaDu<sub>dd</sub>. The same link between hypoxia and gene expression profile was observed for CA9 and GLUT1, but not LOX, in SCCVII tumors. Apparent in vivo hypoxia-specificity for other putative molecular markers of tissue hypoxia was considerably weaker.</p> <p>Conclusions</p> <p>The portrayed technique allows multiple pairwise measurements of mRNA transcript levels and extent of hypoxia in individual tumors at a smallest possible volumetric scale which (by limiting averaging effects inherent to whole-tumor analysis) strengthen the conclusiveness on true hypoxia-specificity of candidate genes while limiting the required number of tumors. Among tested genes, our study identified CA9, GLUT1 and possibly LOX as highly specific biomarkers of tumor hypoxia in vivo.</p
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