Colon cancer subtypes: Concordance, effect on survival and selection of the most representative preclinical models

Multiple gene-expression-based subtypes have been proposed for the molecular subdivision of colon cancer in the last decade. We aimed to cross-validate these classifiers to explore their concordance and their power to predict survival. A gene-chip-based database comprising 2,166 samples from 12 independent datasets was set up. A total of 22 different molecular subtypes were re-trained including the CCHS, CIN25, CMS, ColoGuideEx, ColoGuidePro, CRCassigner, MDA114, Meta163, ODXcolon, Oncodefender, TCA19, and V7RHS classifiers as well as subtypes established by Budinska, Chang, DeSousa, Marisa, Merlos, Popovici, Schetter, Yuen, and Watanabe (first authors). Correlation with survival was assessed by Cox proportional hazards regression for each classifier using relapse-free survival data. The highest efficacy at predicting survival in stage 2-3 patients was achieved by Yuen (p = 3.9e-05, HR = 2.9), Marisa (p = 2.6e-05, HR = 2.6) and Chang (p = 9e-09, HR = 2.35). Finally, 61 colon cancer cell lines from four independent studies were assigned to the closest molecular subtype. © 2016 The Author(s)

Nanostring-based multigene assay to predict recurrence for gastric cancer patients after surgery

10.1371/journal.pone.0090133PLoS ONE93-POLN

Validation study of a quantitative multigene reverse transcriptase-polymerase chain reaction assay for assessment of recurrence risk in patients with stage II colon cancer.

PURPOSE: We developed quantitative gene expression assays to assess recurrence risk and benefits from chemotherapy in patients with stage II colon cancer. PATIENTS AND METHODS: We sought validation by using RNA extracted from fixed paraffin-embedded primary colon tumor blocks from 1,436 patients with stage II colon cancer in the QUASAR (Quick and Simple and Reliable) study of adjuvant fluoropyrimidine chemotherapy versus surgery alone. A recurrence score (RS) and a treatment score (TS) were calculated from gene expression levels of 13 cancer-related genes (n = 7 recurrence genes and n = 6 treatment benefit genes) and from five reference genes with prespecified algorithms. Cox proportional hazards regression models and log-rank methods were used to analyze the relationship between the RS and risk of recurrence in patients treated with surgery alone and between TS and benefits of chemotherapy. RESULTS: Risk of recurrence was significantly associated with RS (hazard ratio [HR] per interquartile range, 1.38; 95% CI, 1.11 to 1.74; P = .004). Recurrence risks at 3 years were 12%, 18%, and 22% for predefined low, intermediate, and high recurrence risk groups, respectively. T stage (HR, 1.94; P < .001) and mismatch repair (MMR) status (HR, 0.31; P < .001) were the strongest histopathologic prognostic factors. The continuous RS was associated with risk of recurrence (P = .006) beyond these and other covariates. There was no trend for increased benefit from chemotherapy at higher TS (P = .95). CONCLUSION: The continuous 12-gene RS has been validated in a prospective study for assessment of recurrence risk in patients with stage II colon cancer after surgery and provides prognostic value that complements T stage and MMR. The TS was not predictive of chemotherapy benefit

Methylation of WNT target genes AXIN2 and DKK1 as robust biomarkers for recurrence prediction in stage II colon cancer

Stage II colon cancer (CC) still remains a clinical challenge with patient stratification for adjuvant therapy (AT) largely relying on clinical parameters. Prognostic biomarkers are urgently needed for better stratification. Previously, we have shown that WNT target genes AXIN2, DKK1, APCDD1, ASCL2 and LGR5 are silenced by DNA methylation and could serve as prognostic markers in stage II CC patients using methylation-specific PCR. Here, we have extended our discovery cohort AMC90-AJCC-II (N=65) and methylation was analyzed by quantitative pyrosequencing. Subsequently, we validated the results in an independent EPICOLON1 CC cohort (N=79). Methylation of WNT target genes is negatively correlated to mRNA expression. A combination of AXIN2 and DKK1 methylation significantly predicted recurrences in univariate (area under the curve (AUC)=0.83, confidence interval (CI): 0.72-0.94, P<0.0001) analysis in stage II microsatellite stable (MSS) CC patients. This two marker combination showed an AUC of 0.80 (CI: 0.68-0.91, P<0.0001) in the EPICOLON1 validation cohort. Multivariate analysis in the Academic Medical Center (AMC) cohort revealed that both WNT target gene methylation and consensus molecular subtype 4 (CMS4) are significantly associated with poor recurrence-free survival (hazard ratio (HR)methylation: 3.84, 95% CI: 1.14-12.43; HRCMS4: 3.73, 95% CI: 1.22-11.48). CMS4 subtype tumors with WNT target methylation showed worse prognosis. Combining WNT target gene methylation and CMS4 subtype lead to an AUC of 0.89 (0.791-0.982, P<0.0001) for recurrence prediction. Notably, we observed that methylation of DKK1 is high in BRAF mutant and CIMP (CpG island methylator phenotype)-positive cancers, whereas AXIN2 methylation appears to be associated with CMS4. Methylation of AXIN2 and DKK1 were found to be robust markers for recurrence prediction in stage II MSS CC patients. Further validation of these findings in a randomized and prospective manner could pave a way to identify poor prognosis patients of stage II CC for AT

Transcriptional profiling of formalin fixed paraffin embedded tissue : pitfalls and recommendations for identifying biologically relevant changes

Expression profiling techniques have been used to study the biology of many types of cancer but have been limited to some extent by the requirement for collection of fresh tissue. In contrast, formalin fixed paraffin embedded (FFPE) samples are widely available and represent a vast resource of potential material. The techniques used to handle the degraded and modified RNA from these samples are relatively new and all the pitfalls and limitations of this material for whole genome expression profiling are not yet clarified. Here, we analyzed 70 FFPE tongue carcinoma samples and 17 controls using the whole genome DASL array covering nearly 21000 genes. We identified that sample age is related to quality of extracted RNA and that sample quality influences apparent expression levels in a non-random manner related to gene probe sequence, leading to spurious results. However, by removing sub-standard samples and analysing only those 28 cancers and 15 controls that had similar quality we were able to generate a list of 934 genes significantly altered in tongue cancer compared to control samples of tongue. This list contained previously identified changes and was enriched for genes involved in many cancer-related processes such as tissue remodelling, inflammation, differentiation and apoptosis. Four novel genes of potential importance in tongue cancer development and maintenance, SH3BGL2, SLC2A6, SLC16A3 and CXCL10, were independently confirmed, validating our data. Hence, gene expression profiling can be performed usefully on archival material if appropriate quality assurance steps are taken to ensure sample consistency and we present some recommendations for the use of FFPE material based on our findings