Resistance Mechanisms to Anti-Epidermal Growth Factor Receptor Therapy in RAS/RAF Wild-Type Colorectal Cancer Vary by Regimen and Line of Therapy.

PURPOSE: Acquired resistance to anti-epidermal growth factor receptor (EGFR) inhibitor (EGFRi) therapy in colorectal cancer (CRC) has previously been explained by the model of acquiring new mutations in KRAS/NRAS/EGFR, among other MAPK-pathway members. However, this was primarily on the basis of single-agent EGFRi trials and little is known about the resistance mechanisms of EGFRi combined with effective cytotoxic chemotherapy in previously untreated patients. METHODS: We analyzed paired plasma samples from patients with RAS/BRAF/EGFR wild-type metastatic CRC enrolled in three large randomized trials evaluating EGFRi in the first line in combination with chemotherapy and as a single agent in third line. The mutational signature of the alterations acquired with therapy was evaluated. CRC cell lines with resistance to cetuximab, infusional fluorouracil, leucovorin, and oxaliplatin, and SN38 were developed, and transcriptional changes profiled. RESULTS: Patients whose tumors were treated with and responded to EGFRi alone were more likely to develop acquired mutations (46%) compared with those treated in combination with cytotoxic chemotherapy (9%). Furthermore, contrary to the generally accepted hypothesis of the clonal evolution of acquired resistance, we demonstrate that baseline resistant subclonal mutations rarely expanded to become clonal at progression, and most remained subclonal or disappeared. Consistent with this clinical finding, preclinical models with acquired resistance to either cetuximab or chemotherapy were cross-resistant to the alternate agents, with transcriptomic profiles consistent with epithelial-to-mesenchymal transition. By contrast, commonly acquired resistance alterations in the MAPK pathway do not affect sensitivity to cytotoxic chemotherapy. CONCLUSION: These findings support a model of resistance whereby transcriptomic mechanisms of resistance predominate in the presence of active cytotoxic chemotherapy combined with EGFRi, with a greater predominance of acquired MAPK mutations after single-agent EGFRi. The proposed model has implications for prospective studies evaluating EGFRi rechallenge strategies guided by acquired MAPK mutations, and highlights the need to address transcriptional mechanisms of resistance.

Identification of Gene Co-Expression Networks Associated with Consensus Molecular Subtype-1 of Colorectal Cancer.

Colorectal cancer (CRC) is driven in part by dysregulated Wnt, Ras-Raf-MAPK, TGF-ß, and PI3K-Akt signaling. The progression of CRC is also promoted by molecular alterations and heterogeneous-yet interconnected-gene mutations, chromosomal instability, transcriptomic subtypes, and immune signatures. Genomic alterations of CRC progression lead to changes in RNA expression, which support CRC metastasis. An RNA-based classification system used for CRC, known as consensus molecular subtyping (CMS), has four classes. CMS1 has the lowest survival after relapse of the four CRC CMS phenotypes. Here, we identify gene signatures and associated coding mRNAs that are co-expressed during CMS1 CRC progression. Using RNA-seq data from CRC primary tumor samples, acquired from The Cancer Genome Atlas (TCGA), we identified co-expression gene networks significantly correlated with CMS1 CRC progression. CXCL13, CXCR5, IL10, PIK3R5, PIK3AP1, CCL19, and other co-expressed genes were identified to be positively correlated with CMS1. The co-expressed eigengene networks for CMS1 were significantly and positively correlated with the TNF, WNT, and ERK1 and ERK2 signaling pathways, which together promote cell proliferation and survival. This network was also aligned with biological characteristics of CMS1 CRC, being positively correlated to right-sided tumors, microsatellite instability, chemokine-mediated signaling pathways, and immune responses. CMS1 also differentially expressed genes involved in PI3K-Akt signaling. Our findings reveal CRC gene networks related to oncogenic signaling cascades, cell activation, and positive regulation of immune responses distinguishing CMS1 from other CRC subtypes.

Multivariate transcriptome analysis identifies networks and key drivers of chronic lymphocytic leukemia relapse risk and patient survival.

BACKGROUND: Chronic lymphocytic leukemia (CLL) is an indolent heme malignancy characterized by the accumulation of CD5+ CD19+ B cells and episodes of relapse. The biological signaling that influence episodes of relapse in CLL are not fully described. Here, we identify gene networks associated with CLL relapse and survival risk. METHODS: Networks were investigated by using a novel weighted gene network co-expression analysis method and examining overrepresentation of upstream regulators and signaling pathways within co-expressed transcriptome modules across clinically annotated transcriptomes from CLL patients (N = 203). Gene Ontology analysis was used to identify biological functions overrepresented in each module. Differential Expression of modules and individual genes was assessed using an ANOVA (Binet Stage A and B relapsed patients) or T-test (SF3B1 mutations). The clinical relevance of biomarker candidates was evaluated using log-rank Kaplan Meier (survival and relapse interval) and ROC tests. RESULTS: Eight distinct modules (M2, M3, M4, M7, M9, M10, M11, M13) were significantly correlated with relapse and differentially expressed between relapsed and non-relapsed Binet Stage A CLL patients. The biological functions of modules positively correlated with relapse were carbohydrate and mRNA metabolism, whereas negatively correlated modules to relapse were protein translation associated. Additionally, M1, M3, M7, and M13 modules negatively correlated with overall survival. CLL biomarkers BTK, BCL2, and TP53 were co-expressed, while unmutated IGHV biomarker ZAP70 and cell survival-associated NOTCH1 were co-expressed in modules positively correlated with relapse and negatively correlated with survival days. CONCLUSIONS: This study provides novel insights into CLL relapse biology and pathways associated with known and novel biomarkers for relapse and overall survival. The modules associated with relapse and overall survival represented both known and novel pathways associated with CLL pathogenesis and can be a resource for the CLL research community. The hub genes of these modules, e.g., ARHGAP27P2, C1S, CASC2, CLEC3B, CRY1, CXCR5, FUT5, MID1IP1, and URAHP, can be studied further as new therapeutic targets or clinical markers to predict CLL patient outcomes.