Consalvo Petti

Stromal contribution to the colorectal cancer transcriptome

Recent studies identified a poor-prognosis stem/serrated/mesenchymal (SSM) transcriptional subtype of colorectal cancer (CRC). We noted that genes upregulated in this subtype are also prominently expressed by stromal cells, suggesting that SSM transcripts could derive from stromal rather than epithelial cancer cells. To test this hypothesis, we analyzed CRC expression data from patient-derived xenografts, where mouse stroma supports human cancer cells. Species-specific expression analysis showed that the mRNA levels of SSM genes were mostly due to stromal expression. Transcriptional signatures built to specifically report the abundance of cancer-associated fibroblasts (CAFs), leukocytes or endothelial cells all had significantly higher expression in human CRC samples of the SSM subtype. High expression of the CAF signature was associated with poor prognosis in untreated CRC, and joint high expression of the stromal signatures predicted resistance to radiotherapy in rectal cancer. These data show that the distinctive transcriptional and clinical features of the SSM subtype can be ascribed to its particularly abundant stromal component.

MACC1 mRNA levels predict cancer recurrence after resection of colorectal cancer liver metastases.

Objective:Upon colon cancer metastasis resection in liver, disease outcome is heterogeneous, ranging from indolent to very aggressive, with early recurrence. The aim of this study is to investigate the capability of metastasis associated in colon cancer 1 (MACC1) levels measured in liver metastasis specimens to predict further recurrence of the disease. Methods:Gene expression and gene dosage of MACC1, hepatocyte growth factor (HGF), and hepatocyte growth factor receptor (MET) were assessed using quantitative realtime polymerase chain reaction on a cohort of 64 liver metastasis samples from patients with complete follow-up of 36 months and detailed clinical annotation. The most relevant mutations associated to prognosis in colorectal cancer, KRAS, and PIK3CA were assessed on the same specimens with Sanger sequencing. Results:Receiver operating characteristic (ROC) analysis revealed that MACC1 mRNA abundance is a good indicator of metastatic recurrence (AUC = 0.65, P < 0.05), whereas no such results were obtained with MET and HGF, nor with gene dosage. Generation of MACC1-based risk classes was capable of successfully separating patients into poor and good prognosis subgroups [hazard ratio (HR) = 5.236, 95% confidence interval (CI) = 1.2068–22.715, P < 0.05]. Also KRAS mutation was significantly associated with higher risk of recurrence (HR = 2.07, 95% CI = 1.048–4.09, P < 0.05). Cox regression multivariate analysis supported the independence of MACC1, but not KRAS, from known prognostic clinical information (Node Size HR = 3.155, 95% CI = 1.4418–6.905, P < 0.001, Preoperative carcinoembryonic antigen HR = 2.359, 95% CI = 1.0203–5.452, P < 0.05, MACC1 HR = 7.2739, 95% CI = 1.6584–31.905, P < 0.01). Conclusions:MACC1, a new easily detectable biomarker in cancer, is an independent prognostic factor of recurrence after liver resection of colorectal cancer metastasis.

MicroRNA–mRNA interactions underlying colorectal cancer molecular subtypes

Colorectal cancer (CRC) transcriptional subtypes have been recently identified by gene expression profiling. Here we describe an analytical pipeline, microRNA master regulator analysis (MMRA), developed to search for microRNAs potentially driving CRC subtypes. Starting from a microRNA–mRNA tumour expression data set, MMRA identifies candidate regulator microRNAs by assessing their subtype-specific expression, target enrichment in subtype mRNA signatures and network analysis-based contribution to subtype gene expression. When applied to a CRC data set of 450 samples, assigned to subtypes by 3 different transcriptional classifiers, MMRA identifies 24 candidate microRNAs, in most cases downregulated in the stem/serrated/mesenchymal (SSM) poor prognosis subtype. Functional validation in CRC cell lines confirms downregulation of the SSM subtype by miR-194, miR-200b, miR-203 and miR-429, which share target genes and pathways mediating this effect. These results show that, by combining statistical tests, target prediction and network analysis, MMRA effectively identifies microRNAs functionally associated to cancer subtypes.

Selective analysis of cancer-cell intrinsic transcriptional traits defines novel clinically relevant subtypes of colorectal cancer

Stromal content heavily impacts the transcriptional classification of colorectal cancer (CRC), with clinical and biological implications. Lineage-dependent stromal transcriptional components could therefore dominate over more subtle expression traits inherent to cancer cells. Since in patient-derived xenografts (PDXs) stromal cells of the human tumour are substituted by murine counterparts, here we deploy human-specific expression profiling of CRC PDXs to assess cancer-cell intrinsic transcriptional features. Through this approach, we identify five CRC intrinsic subtypes (CRIS) endowed with distinctive molecular, functional and phenotypic peculiarities: (i) CRIS-A: mucinous, glycolytic, enriched for microsatellite instability or KRAS mutations; (ii) CRIS-B: TGF-β pathway activity, epithelial–mesenchymal transition, poor prognosis; (iii) CRIS-C: elevated EGFR signalling, sensitivity to EGFR inhibitors; (iv) CRIS-D: WNT activation, IGF2 gene overexpression and amplification; and (v) CRIS-E: Paneth cell-like phenotype, TP53 mutations. CRIS subtypes successfully categorize independent sets of primary and metastatic CRCs, with limited overlap on existing transcriptional classes and unprecedented predictive and prognostic performances.

Efficacy of NEDD8 Pathway Inhibition in Preclinical Models of Poorly Differentiated, Clinically Aggressive Colorectal Cancer

Background: The NEDD8 conjugation pathway modulates the ubiquitination and activity of a wide range of intracellular proteins, and its blockade by pevonedistat is emerging as a promising therapeutic approach in various cancer settings. However, systematic characterization of pevonedistat efficacy in specific tumor types and definition of response predictors are still missing. Methods: We investigated in vitro sensitivity to pevonedistat in 122 colorectal cancer (CRC) cell lines by an ATP‐based proliferation assay and evaluated apoptosis and DNA content by flow cytometry. Associations between pevonedistat sensitivity and CRC molecular features were assessed by Students t test. A 184‐gene transcriptional predictor was generated in cell lines and applied to 87 metastatic CRC samples for which patient‐derived xenografts (PDXs) were available. In vivo reponse to pevonedistat was assessed in PDX models (≥5 mice per group). All statistical tests were two‐sided. Results: Sixteen (13.1%) cell lines displayed a marked response to pevonedistat, featuring DNA re‐replication, proliferative block, and increased apoptosis. Pevonedistat sensitivity did not statistically significantly correlate with microsatellite instability or mutations in KRAS or BRAF and was functionally associated with low EGFR pathway activity. While ineffective on predicted resistant PDXs, in vivo administration of pevonedistat statistically significantly impaired growth of five out of six predicted sensitive models (P < .01). In samples from CRC patients, transcriptional prediction of pevonedistat sensitivity was associated with poor prognosis after surgery (hazard ratio [HR] = 2.49, 95% confidence interval [CI] = 1.34 to 4.62, P = .003) and early progression under cetuximab treatment (HR = 3.59, 95% CI = 1.60 to 8.04, P < .001). Histological and immunohistochemical analyses revealed that the pevonedistat sensitivity signature captures transcriptional traits of poor differentiation and high‐grade mucinous adenocarcinoma. Conclusions: These results highlight NEDD8‐pathway inhibition by pevonedistat as a potentially effective treatment for poorly differentiated, clinically aggressive CRC.

Loss of AXIN1 drives acquired resistance to WNT pathway blockade in colorectal cancer cells carrying RSPO3 fusions

In colorectal cancer (CRC), WNT pathway activation by genetic rearrangements of RSPO3 is emerging as a promising target. However, its low prevalence severely limits availability of preclinical models for in‐depth characterization. Using a pipeline designed to suppress stroma‐derived signal, we find that RSPO3 “outlier” expression in CRC samples highlights translocation and fusion transcript expression. Outlier search in 151 CRC cell lines identified VACO6 and SNU1411 cells as carriers of, respectively, a canonical PTPRK(e1)‐RSPO3(e2) fusion and a novel PTPRK(e13)‐RSPO3(e2) fusion. Both lines displayed marked in vitro and in vivo sensitivity to WNT blockade by the porcupine inhibitor LGK974, associated with transcriptional and morphological evidence of WNT pathway suppression. Long‐term treatment of VACO6 cells with LGK974 led to the emergence of a resistant population carrying two frameshift deletions of the WNT pathway inhibitor AXIN1, with consequent protein loss. Suppression of AXIN1 in parental VACO6 cells by RNA interference conferred marked resistance to LGK974. These results provide the first mechanism of secondary resistance to WNT pathway inhibition.

A diphtheria toxin resistance marker for in vitro and in vivo selection of stably transduced human cells.

We developed a selectable marker rendering human cells resistant to Diphtheria Toxin (DT). The marker (DTR) consists of a primary microRNA sequence engineered to downregulate the ubiquitous DPH2 gene, a key enzyme for the biosynthesis of the DT target diphthamide. DTR expression in human cells invariably rendered them resistant to DT in vitro, without altering basal cell growth. DTR-based selection efficiency and stability were comparable to those of established drug-resistance markers. As mice are insensitive to DT, DTR-based selection can be also applied in vivo. Direct injection of a GFP-DTR lentiviral vector into human cancer cell-line xenografts and patient-derived tumorgrafts implanted in mice, followed by systemic DT administration, yielded tumors entirely composed of permanently transduced cells and detectable by imaging systems. This approach enabled high-efficiency in vivo selection of xenografted human tumor tissues expressing ectopic transgenes, a hitherto unmet need for functional and morphological studies in laboratory animals.

Corrigendum: Stromal contribution to the colorectal cancer transcriptome

Nat. Genet. 47, 312–319 (2015); published online 23 February 2015; corrected after print 29 August 2016 In the version of this article initially published, an affiliation for author Zsolt Fekete was incorrectly omitted. The missing affiliation was to the Department of Oncology, University of Medicine and Pharmacy Iuliu Hatieganu, Cluj-Napoca, Romania.

Abstract 4760: Stromal contribution to the colorectal cancer transcriptome

Proceedings: AACR 106th Annual Meeting 2015; April 18-22, 2015; Philadelphia, PA Recent studies have identified a stem/serrated/mesenchymal (SSM) molecular subtype of colorectal cancer (CRC) that is associated with poor prognosis. We noted that genes upregulated in this subtype are also prominently expressed by stromal cells. This led us to hypothesize that the SSM transcripts could derive from the tumor microenvironment, rather than being intrinsic to cancer cells. To test this hypothesis, we analyzed microarray and RNAseq expression data from patient-derived xenografts (PDXs) of CRC, where human cancer cells are supported by murine stroma. Species-specific expression analysis revealed that mRNA levels of SSM genes are mostly due to stromal expression. Considering only genes exclusively expressed by stromal cells in PDXs, We then built three expression signatures specifically reporting the abundance of cancer-associated fibroblasts (CAFs), leucocytes or endothelial cells. In human CRC samples, all stromal signatures were strongly associated with the SSM subtype. A high CAF signature was associated with poor prognosis in untreated CRC patients, while in rectal cancer high stromal signatures jointly predicted radioresistance. These data show that the distinctive transcriptional and clinical features of the SSM subtype can be ascribed to its particularly abundant stroma. Citation Format: Claudio Isella, Andrea Terrasi, Sara E. Bellomo, Consalvo Petti, Andrea Muratore, Alfredo Mellano, Mark De Ridder, Paola Cassoni, Guy Storme, Andrea Bertotti, Enzo Medico. Stromal contribution to the colorectal cancer transcriptome. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4760. doi:10.1158/1538-7445.AM2015-4760

A Novel Pipeline for Identification and Prioritization of Gene Fusions in Patient-derived Xenografts of Metastatic Colorectal Cancer

Metastatic spread to the liver is a frequent complication of colorectal cancer (CRC), occurring in almost half of the cases, for which personalized treatment strategies are highly desirable. To this aim, it has been proven that patient-derived mouse xenografts (PDX) of liver-metastatic CRC can be used to discover new therapeutic targets and determinants of drug resistance. To identify gene fusions in RNA-Seq data obtained from such PDX samples, we propose a novel pipeline that tackles the following issues: (i) discriminating human from murine RNA, to filter out transcripts contributed by the mouse stroma that supports the PDX; (ii) increasing sensitivity in case of suboptimal RNA-Seq coverage; (iii) prioritizing the detected chimeric transcripts by molecular features of the fusion and by functional relevance of the involved genes; (iv) providing appropriate sequence information for subsequent validation of the identified fusions. The pipeline, built on top of Chimerascan(R.Iyer, 2011) and deFuse(McPherson, 2011) aligner tools, was successfully applied to RNASeq data from 11 PDX samples. Among the 299 fusion genes identified by the aforementioned softwares, five were selected since passed all the filtering stages implemented into the proposed pipeline resulting as biologically relevant fusions. Three of them were experimentally confirmed.