Project description:Samples were prospectively collected from patients with histologically normal surgical resection margins. 96 tissue samples (histologically normal margins, oral carcinoma and adjacent normal tissues) from 24 patients comprised the training set. Our study design was guided by the hypothesis that the expression of genes present in oral squamous cell carcinoma (OSCC) but not in healthy oral tissues would be indicative of recurrence in advance of histological alteration. We used meta-analysis of five published microarray data sets (GEO accession GDS2520, Kuriakose et al. 2004; GDS1584, Toruner et al. 2004; GSE6791, Pyeon et al. 2007; GSE9844, Ye et al. 2008; and GSE10121, Sticht et al. 2008), in conjunction with the current training set, to identify genes reliably over-expressed in OSCC. This reduced gene set was used to train a risk model to predict recurrence based on over-expression of a subset of these genes in histologically normal surgical resection margins. Validation of the risk signature was performed using quantitative real-time reverse-transcription PCR in an independent set of 136 samples from an independent cohort of 30 patients. This was a case-only design involving a training set of 23 tumors and 73 margins from 24 patients with squamous cell carcinoma of the tongue.
Project description:Samples were prospectively collected from patients with histologically normal surgical resection margins. 96 tissue samples (histologically normal margins, oral carcinoma and adjacent normal tissues) from 24 patients comprised the training set. Our study design was guided by the hypothesis that the expression of genes present in oral squamous cell carcinoma (OSCC) but not in healthy oral tissues would be indicative of recurrence in advance of histological alteration. We used meta-analysis of five published microarray data sets (GEO accession GDS2520, Kuriakose et al. 2004; GDS1584, Toruner et al. 2004; GSE6791, Pyeon et al. 2007; GSE9844, Ye et al. 2008; and GSE10121, Sticht et al. 2008), in conjunction with the current training set, to identify genes reliably over-expressed in OSCC. This reduced gene set was used to train a risk model to predict recurrence based on over-expression of a subset of these genes in histologically normal surgical resection margins. Validation of the risk signature was performed using quantitative real-time reverse-transcription PCR in an independent set of 136 samples from an independent cohort of 30 patients.
Project description:A "Cartes d'Identite des Tumeurs" (CIT) project from the french Ligue Nationale Contre le Cancer (http://cit.ligue-cancer.net). 81 samples on Affymetrix HG-U133 Plus 2.0 GeneChips arrays for 81 patients with primary Head and Neck Squamous Cell Carcinoma (HNSCC; oral cavity, tongue, oro- or hypopharynx); metastases as first recurrent event in a 36-month follow up; histologically tumor-free margins (?3 mm); patients had undergone surgical resection as the first treatment and had no clinically evident distant metastases.
Project description:The aim of this study is to provide an extended, retrospective validation of a previously described 4-gene signature (MMP1, COL4A1, P4HA2, and THBS2) predictive of oral carcinoma recurrence. We assessed an independent cohort including 245 histologically normal surgical margins from 62 patients with OSCC. Gene expression was determined using a color-coded probe assay for quantitative gene expression analysis. All margins and tumor blocks were cut (4-5µm tick) and stained with Hematoxylin-Eosin and tissues were subjected to needle microdissection using the stereo microscope Leica EZ4 (Leica Microsystems, Wetzlar, Germany) before RNA extraction, in order to isolate pure tumor or normal cell populations. RNA from FFPE samples was isolated using the RecoverAll Total Nucleic Acid Isolation kit (Ambion/Life Technologies, Carlsbad, CA, USA), following our previously reported protocol with modifications to improve RNA yield [PMID:23835716]. RNA was stored at -80ºC until RNA extraction and gene expression validation. In addition, tumor tissues from the same patients were collected for further analysis (not in scope of the presented study). Probes were designed for the 4-gene signature (MMP1, COL4A1, P4HA2 and THBS2) and contained one capture probe linked to biotin and one reporter probe attached to a color-coded molecular tag for each gene sequence, according to the nCounterTM code-set design. RNA samples were randomized using a numerical ID and were then subjected to NanoString nCounterTM analysis by the Princess Margaret Genomics Centre (https://www.pmgenomics.ca), Toronto, ON, Canada. Patient samples were analyzed in two batches consisting of 125 and 152 margins tissue samples. The detailed protocol for mRNA transcript quantification analysis, including sample preparation, hybridization, detection and scanning followed the manufacturer’s recommendations and was described in [PMID: 21549012]. We used 400 ng of total RNA isolated from FFPE tissues for detection of probe signals. Raw data were analyzed using the nCounterTM digital analyzer software (http://www.nanostring.com/support/ncounter/) and gene expression levels were subjected to further bioinformatic and statistical analyses.
Project description:Interactions between cancer and immune cells determine the formation and progression of a tumor. Variability of immune contextures in tumor and margins among patients with oral squamous cell carcinoma of the gingivobuccal region (OSCC-GB) – the most prevalent subtype of oral cancer in India and southeast Asia – and the relationship of these contextures with prognosis are largely unknown. Treatment naïve, HPV negative, OSCC-GB patients (n=46) were recruited, treated, followed-up for two years and recurrence/death noted. Immune contextures of tumor and negative margins were studied using RNA-sequencing and immunohistochemistry (n=43; margin tissues were unavailable from three patients). Expressions of 544 immune related genes (IRGs) revealed a subgroup of patients (28%) with poor prognosis (high recurrence and death). The compositions of immune cell-types of normal and negative margin tissues were similar among patients irrespective of prognoses; differences were observed only in tumor.
Project description:We obtained fibroblast cultures from fresh surgical specimen ressected from patients with primary colorectal carcinoma: normal colonic fibroblasts (NCF=9) from the normal colonic mucosa at least 5-10cm from the surgical margin, carcinoma-associated fibroblasts from the primary tumor (CAF-PT=14) and carcinoma-associated fibroblasts (CAF-LM=11) from fresh surgical specimens of liver metastases. We identified 277 probes, in common between the three types of fibroblasts, whose expression level is sequentially deregulated according to cancer progression (NCF→CAF-PT→CAF-LM; fold change Log2 normalized expression>1.5 in each step). Prediction Analysis of Microarrays was applied to obtain a 25-gene signature that better characterizes each fibroblast class. The signature is able to classify patients carrying primary tumors according to prognosis. This fact was exploited to obtain a 19-gene signature (from the 277 deregulated probes) predicting recurrence with high accuracy in stage II/III colorectal cancer patients. Signature validation has been carried out in two independent datasets and in a meta-cohort of 336 stage II/III patients. Since the 25-gene signature was obtained regardless of gene expression data of tumor specimens or patient’s clinical data, the prognostic power of this signature provides strong evidence of the link between the tumor stroma and cancer progression. Furthermore, the 19-gene signature was able to identify low-risk patients with very high accuracy, especially relevant for those high-risk stage-II patients. We hybridised fibroblast RNA in Affymetrix GeneChip 1.0 st arrays
Project description:We obtained fibroblast cultures from fresh surgical specimen ressected from patients with primary colorectal carcinoma: normal colonic fibroblasts (NCF=9) from the normal colonic mucosa at least 5-10cm from the surgical margin, carcinoma-associated fibroblasts from the primary tumor (CAF-PT=14) and carcinoma-associated fibroblasts (CAF-LM=11) from fresh surgical specimens of liver metastases. We identified 277 probes, in common between the three types of fibroblasts, whose expression level is sequentially deregulated according to cancer progression (NCF→CAF-PT→CAF-LM; fold change Log2 normalized expression>1.5 in each step). Prediction Analysis of Microarrays was applied to obtain a 25-gene signature that better characterizes each fibroblast class. The signature is able to classify patients carrying primary tumors according to prognosis. This fact was exploited to obtain a 19-gene signature (from the 277 deregulated probes) predicting recurrence with high accuracy in stage II/III colorectal cancer patients. Signature validation has been carried out in two independent datasets and in a meta-cohort of 336 stage II/III patients. Since the 25-gene signature was obtained regardless of gene expression data of tumor specimens or patient’s clinical data, the prognostic power of this signature provides strong evidence of the link between the tumor stroma and cancer progression. Furthermore, the 19-gene signature was able to identify low-risk patients with very high accuracy, especially relevant for those high-risk stage-II patients.
Project description:Microarray was used to find out the differentially expressed in tumor sites of early-stage oral squamous cell carcinoma compared with Normal parts. Furthermore, we compared cases of early-stage oral squamous cell carcinoma with lymph node metastasis with cases without lymph node metastasis. The miRNAs obtained may not only serve as predictive biomarkers for lymph node metastasis, but may also be used further to understand disease.