Paul Roepman

The consensus molecular subtypes of colorectal cancer

Colorectal cancer (CRC) is a frequently lethal disease with heterogeneous outcomes and drug responses. To resolve inconsistencies among the reported gene expression–based CRC classifications and facilitate clinical translation, we formed an international consortium dedicated to large-scale data sharing and analytics across expert groups. We show marked interconnectivity between six independent classification systems coalescing into four consensus molecular subtypes (CMSs) with distinguishing features: CMS1 (microsatellite instability immune, 14%), hypermutated, microsatellite unstable and strong immune activation; CMS2 (canonical, 37%), epithelial, marked WNT and MYC signaling activation; CMS3 (metabolic, 13%), epithelial and evident metabolic dysregulation; and CMS4 (mesenchymal, 23%), prominent transforming growth factor–β activation, stromal invasion and angiogenesis. Samples with mixed features (13%) possibly represent a transition phenotype or intratumoral heterogeneity. We consider the CMS groups the most robust classification system currently available for CRC—with clear biological interpretability—and the basis for future clinical stratification and subtype-based targeted interventions.

An expression profile for diagnosis of lymph node metastases from primary head and neck squamous cell carcinomas

Metastasis is the process by which cancers spread to distinct sites in the body. It is the principal cause of death in individuals suffering from cancer. For some types of cancer, early detection of metastasis at lymph nodes close to the site of the primary tumor is pivotal for appropriate treatment. Because it can be difficult to detect lymph node metastases reliably, many individuals currently receive inappropriate treatment. We show here that DNA microarray gene-expression profiling can detect lymph node metastases for primary head and neck squamous cell carcinomas that arise in the oral cavity and oropharynx. The predictor, established with an 82-tumor training set, outperforms current clinical diagnosis when independently validated. The 102 predictor genes offer unique insights into the processes underlying metastasis. The results show that the metastatic state can be deciphered from the primary tumor gene-expression pattern and that treatment can be substantially improved.

Gene Expression Signature to Improve Prognosis Prediction of Stage II and III Colorectal Cancer

PURPOSE This study aims to develop a robust gene expression classifier that can predict disease relapse in patients with early-stage colorectal cancer (CRC). PATIENTS AND METHODS Fresh frozen tumor tissue from 188 patients with stage I to IV CRC undergoing surgery was analyzed using Agilent 44K oligonucleotide arrays. Median follow-up time was 65.1 months, and the majority of patients (83.6%) did not receive adjuvant chemotherapy. A nearest mean classifier was developed using a cross-validation procedure to score all genes for their association with 5-year distant metastasis-free survival. RESULTS An optimal set of 18 genes was identified and used to construct a prognostic classifier (ColoPrint). The signature was validated on an independent set of 206 samples from patients with stage I, II, and III CRC. The signature classified 60% of patients as low risk and 40% as high risk. Five-year relapse-free survival rates were 87.6% (95% CI, 81.5% to 93.7%) and 67.2% (95% CI, 55.4% to 79.0%) for low- and high-risk patients, respectively, with a hazard ratio (HR) of 2.5 (95% CI, 1.33 to 4.73; P = .005). In multivariate analysis, the signature remained one of the most significant prognostic factors, with an HR of 2.69 (95% CI, 1.41 to 5.14; P = .003). In patients with stage II CRC, the signature had an HR of 3.34 (P = .017) and was superior to American Society of Clinical Oncology criteria in assessing the risk of cancer recurrence without prescreening for microsatellite instability (MSI). CONCLUSION ColoPrint significantly improves the prognostic accuracy of pathologic factors and MSI in patients with stage II and III CRC and facilitates the identification of patients with stage II disease who may be safely managed without chemotherapy.

MED12 Controls the Response to Multiple Cancer Drugs through Regulation of TGF-β Receptor Signaling

Inhibitors of the ALK and EGF receptor tyrosine kinases provoke dramatic but short-lived responses in lung cancers harboring EML4-ALK translocations or activating mutations of EGFR, respectively. We used a large-scale RNAi screen to identify MED12, a component of the transcriptional MEDIATOR complex that is mutated in cancers, as a determinant of response to ALK and EGFR inhibitors. MED12 is in part cytoplasmic where it negatively regulates TGF-βR2 through physical interaction. MED12 suppression therefore results in activation of TGF-βR signaling, which is both necessary and sufficient for drug resistance. TGF-β signaling causes MEK/ERK activation, and consequently MED12 suppression also confers resistance to MEK and BRAF inhibitors in other cancers. MED12 loss induces an EMT-like phenotype, which is associated with chemotherapy resistance in colon cancer patients and to gefitinib in lung cancer. Inhibition of TGF-βR signaling restores drug responsiveness in MED12(KD) cells, suggesting a strategy to treat drug-resistant tumors that have lost MED12.

Colorectal cancer intrinsic subtypes predict chemotherapy benefit, deficient mismatch repair and epithelial-to-mesenchymal transition.

In most colorectal cancer (CRC) patients, outcome cannot be predicted because tumors with similar clinicopathological features can have differences in disease progression and treatment response. Therefore, a better understanding of the CRC biology is required to identify those patients who will benefit from chemotherapy and to find a more tailored therapy plan for other patients. Based on unsupervised classification of whole genome data from 188 stages I–IV CRC patients, a molecular classification was developed that consist of at least three major intrinsic subtypes (A‐, B‐ and C‐type). The subtypes were validated in 543 stages II and III patients and were associated with prognosis and benefit from chemotherapy. The heterogeneity of the intrinsic subtypes is largely based on three biological hallmarks of the tumor: epithelial‐to‐mesenchymal transition, deficiency in mismatch repair genes that result in high mutation frequency associated with microsatellite instability and cellular proliferation. A‐type tumors, observed in 22% of the patients, have the best prognosis, have frequent BRAF mutations and a deficient DNA mismatch repair system. C‐type patients (16%) have the worst outcome, a mesenchymal gene expression phenotype and show no benefit from adjuvant chemotherapy treatment. Both A‐type and B‐type tumors have a more proliferative and epithelial phenotype and B‐types benefit from adjuvant chemotherapy. B‐type tumors (62%) show a low overall mutation frequency consistent with the absence of DNA mismatch repair deficiency. Classification based on molecular subtypes made it possible to expand and improve CRC classification beyond standard molecular and immunohistochemical assessment and might help in the future to guide treatment in CRC patients.

An Immune Response Enriched 72-Gene Prognostic Profile for Early-Stage Non–Small-Cell Lung Cancer

Purpose: Current staging methods are imprecise for predicting prognosis of early-stage non–small-cell lung cancer (NSCLC). We aimed to develop a gene expression profile for stage I and stage II NSCLC, allowing identification of patients with a high risk of disease recurrence within 2 to 3 years after initial diagnosis. Experimental Design: We used whole-genome gene expression microarrays to analyze frozen tumor samples from 172 NSCLC patients (pT1-2, N0-1, M0) from five European institutions, who had undergone complete surgical resection. Median follow-up was 89 months (range, 1.2-389) and 64 patients developed a recurrence. A random two thirds of the samples were assigned as the training cohort with the remaining samples set aside for independent validation. Cox proportional hazards models were used to evaluate the association between expression levels of individual genes and patient recurrence-free survival. A nearest mean analysis was used to develop a gene-expression classifier for disease recurrence. Results: We have developed a 72-gene expression prognostic NSCLC classifier. Based on the classifier score, patients were classified as either high or low risk of disease recurrence. Patients classified as low risk showed a significantly better recurrence-free survival both in the training set (P < 0.001; n = 103) and in the independent validation set (P < 0.01; n = 69). Genes in our prognostic signature were strongly enriched for genes associated with immune response. Conclusions: Our 72-gene signature is closely associated with recurrence-free and overall survival in early-stage NSCLC patients and may become a tool for patient selection for adjuvant therapy.

Integration of Gene Dosage and Gene Expression in Non-Small Cell Lung Cancer, Identification of HSP90 as Potential Target

Background Lung cancer causes approximately 1.2 million deaths per year worldwide, and non-small cell lung cancer (NSCLC) represents 85% of all lung cancers. Understanding the molecular events in non-small cell lung cancer (NSCLC) is essential to improve early diagnosis and treatment for this disease. Methodology and Principal Findings In an attempt to identify novel NSCLC related genes, we performed a genome-wide screening of chromosomal copy number changes affecting gene expression using microarray based comparative genomic hybridization and gene expression arrays on 32 radically resected tumor samples from stage I and II NSCLC patients. An integrative analysis tool was applied to determine whether chromosomal copy number affects gene expression. We identified a deletion on 14q32.2-33 as a common alteration in NSCLC (44%), which significantly influenced gene expression for HSP90, residing on 14q32. This deletion was correlated with better overall survival (P = 0.008), survival was also longer in patients whose tumors had low expression levels of HSP90. We extended the analysis to three independent validation sets of NSCLC patients, and confirmed low HSP90 expression to be related with longer overall survival (P = 0.003, P = 0.07 and P = 0.04). Furthermore, in vitro treatment with an HSP90 inhibitor had potent antiproliferative activity in NSCLC cell lines. Conclusions We suggest that targeting HSP90 will have clinical impact for NSCLC patients.

Identification of recurrent FGFR3 fusion genes in lung cancer through kinome‐centred RNA sequencing

Oncogenic fusion genes that involve kinases have proven to be effective targets for therapy in a wide range of cancers. Unfortunately, the diagnostic approaches required to identify these events are struggling to keep pace with the diverse array of genetic alterations that occur in cancer. Diagnostic screening in solid tumours is particularly challenging, as many fusion genes occur with a low frequency. To overcome these limitations, we developed a capture enrichment strategy to enable high‐throughput transcript sequencing of the human kinome. This approach provides a global overview of kinase fusion events, irrespective of the identity of the fusion partner. To demonstrate the utility of this system, we profiled 100 non‐small cell lung cancers and identified numerous genetic alterations impacting fibroblast growth factor receptor 3 (FGFR3) in lung squamous cell carcinoma and a novel ALK fusion partner in lung adenocarcinoma.

A combined oncogenic pathway signature of BRAF, KRAS and PI3KCA mutation improves colorectal cancer classification and cetuximab treatment prediction

Objective To develop gene expression profiles that characterise KRAS-, BRAF- or PIK3CA-activated- tumours, and to explore whether these profiles might be helpful in predicting the response to the epidermal growth factor receptor (EGFR) pathway inhibitors better than mutation status alone. Design Fresh frozen tumour samples from 381 colorectal cancer (CRC) patients were collected and mutations in KRAS, BRAF and PIK3CA were assessed. Using microarray data, three individual oncogenic and a combined model were developed and validated in an independent set of 80 CRC patients, and in a dataset from metastatic CRC patients treated with cetuximab. Results 175 tumours (45.9%) harboured oncogenic mutations in KRAS (30.2%), BRAF (11.0%) and PIK3CA (11.5%). Activating mutation signatures for KRAS (75 genes), for BRAF (58 genes,) and for PIK3CA (49 genes) were developed. The development of a combined oncogenic pathway signature-classified tumours as ‘activated oncogenic’, or as ‘wildtype-like’ with a sensitivity of 90.3% and a specificity of 61.7%. The identified signature revealed other mechanisms that can activate ERK/MAPK pathway in KRAS, BRAF and PIK3CA wildtype patients. The combined signature is associated with response to cetuximab treatment in patients with metastatic CRC (HR 2.51, p<0.0009). Conclusion A combined oncogenic pathway signature allows the identification of patients with an active EGFR-signalling pathway that could benefit from downstream pathway inhibition.

Microarray-Based Determination of Estrogen Receptor, Progesterone Receptor, and HER2 Receptor Status in Breast Cancer

Purpose: The level of estrogen receptor (ER), progesterone receptor (PR), and HER2 aids in the determination of prognosis and treatment of breast cancer. Immunohistochemistry is currently the predominant method for assessment, but differences in methods and interpretation can substantially affect the accuracy, resulting in misclassification. Here, we investigated the association of microarray-based mRNA expression levels compared with immunohistochemistry. Experimental Design: Microarray mRNA quantification of ER, PR, and HER2 was done by the developed TargetPrint test and compared with immunohistochemical assessment for breast tumors from 636 patients. Immunohistochemistry was done in a central laboratory and in an independent reference laboratory according to American Society of Clinical Oncology/College of American Pathologists guidelines for 100 cases. For HER2 immunohistochemistry 2+ cases, additional chromogenic in situ hybridization (CISH) was used to determine the final status. Results: ER concordance between microarray and central immunohistochemistry was 93 [95 confidence interval (95 CI), 91-95]. Only 4 of immunohistochemistry-positive samples were classified negative using microarray, whereas 18 of immunohistochemistry-negative samples showed a positive microarray ER status. Concordance for PR was 83 (95 CI, 80-86) and 96 of all samples showed an identical classification of HER2 status by microarray and immunohistochemistry/CISH (95 CI, 94-98). Nine percent of immunohistochemistry HER2-positive samples showed a negative microarray classification. Detailed review of 11 cases with discordant classifications by American Society of Clinical Oncology/College of American Pathologists and central immunohistochemistry indicated that microarray assessment was likely to add additional information in 5 cases. Conclusion: Microarray-based readout of ER, PR, and HER2 shows a high concordance with immunohistochemistry/CISH and provides an additional, objective, and quantitative assessment of tumor receptor status in breast cancer. (Clin Cancer Res 2009;15(22):700311)