A colorectal tumor is not an isolated entity growing in a restricted location of the body. The patient’s gut environment constitutes the framework where the tumor evolves and this relationship promotes and includes a complex and tight correlation of the tumor with inflammation, blood vessels formation, nutrition, and gut microbiome composition. The tumor influence in the environment could both promote an anti-tumor or a pro-tumor response. A set of 98 paired adjacent mucosa and tumor tissues from colorectal cancer (CRC) patients and 50 colon mucosa from healthy donors (246 samples in total) were included in this work. RNA extracted from each sample was hybridized in Affymetrix chips Human Genome U219. Functional relationships between genes were inferred by means of systems biology using both transcriptional regulation networks (ARACNe algorithm) and protein-protein interaction networks (BIANA software). Here we report a transcriptomic analysis revealing a number of genes activated in adjacent mucosa from CRC patients, not activated in mucosa from healthy donors. A functional analysis of these genes suggested that this active reaction of the adjacent mucosa was related to the presence of the tumor. Transcriptional and protein-interaction networks were used to further elucidate this response of normal gut in front of the tumor, revealing a crosstalk between proteins secreted by the tumor and receptors activated in the adjacent colon tissue; and vice versa. Remarkably, Slit family of proteins activated ROBO receptors in tumor whereas tumor-secreted proteins transduced a cellular signal finally activating AP-1 in adjacent tissue. The systems-level approach provides new insights into the micro-ecology of colorectal tumorogenesis. Disrupting this intricate molecular network of cell-cell communication and pro-inflammatory microenvironment could be a therapeutic target in CRC patients.

Somatic copy number aberrations (CNAs) are common acquired changes in cancer cells having an important role in the progression of colon cancer (colorectal cancer, CRC). This study aimed to perform a characterisation of CNA and their impact in gene expression. Copy number aberrations were inferred from SNP array data in a series of 99 CRC. Copy number aberration events were calculated and used to assess the association between copy number dosage, clinical and molecular characteristics of the tumours, and gene expression changes. All analyses were adjusted for the quantity of stroma in each sample, which was inferred from gene expression data. High heterogeneity among samples was observed; the proportion of altered genome ranged between 0.04 and 26.6%. Recurrent CNA regions with gains were frequent in chromosomes 7p, 8q, 13q, and 20, whereas 8p, 17p, and 18 cumulated losses. A significant positive correlation was observed between the number of somatic mutations and total CNA (Spearman’s r=0.42, P=0.006). Approximately 37% of genes located in CNA regions changed their level of expression and the average partial correlation (adjusted for stromal content) with copy number was 0.54 (interquartile range 0.20 to 0.81). Altered genes showed enrichment in pathways relevant for CRC. Tumours classified as CMS2 and CMS4 by the consensus molecular subtyping showed higher frequency of CNA. Losses of one small region in 1p36.33, with gene CDK11B, were associated with poor prognosis. More than 66% of the recurrent CNA were validated in the The Cancer Genome Atlas (TCGA) data when analysed with the same procedure. Furthermore, 79% of the genes with altered expression in our data were validated in the TCGA. Although CNA are frequent events in microsatellite stable CRC, few focal recurrent regions were found. These aberrations have strong effects on gene expression and contribute to deregulate relevant cancer pathways. Owing to the diploid nature of stromal cells, it is important to consider the purity of tumour samples to accurately calculate CNA events in CRC.

Accurate detection of characteristic proteins secreted by colon cancer tumor cells in biological fluids could serve as a biomarker for the disease. The aim of the present study was to identify and validate new serum biomarkers and demonstrate their potential usefulness for early diagnosis of colon cancer. The study was organized in three sequential phases: 1) biomarker discovery, 2) technical and biological validation, and 3) proof of concept to test the potential clinical use of selected biomarkers. A prioritized subset of the differentially-expressed genes between tissue types (50 colon mucosa from cancer-free individuals and 100 normal-tumor pairs from colon cancer patients) was validated and further tested in a series of serum samples from 80 colon cancer cases, 23 patients with adenoma and 77 cancer-free controls. In the discovery phase, 505 unique candidate biomarkers were identified, with highly significant results and high capacity to discriminate between the different tissue types. After a subsequent prioritization, all tested genes (N = 23) were successfully validated in tissue, and one of them, COL10A1, showed relevant differences in serum protein levels between controls, patients with adenoma (p = 0.0083) and colon cancer cases (p = 3.2e-6). We present a sequential process for the identification and further validation of biomarkers for early detection of colon cancer that identifies COL10A1 protein levels in serum as a potential diagnostic candidate to detect both adenoma lesions and tumor. The use of a cheap serum test for colon cancer screening should improve its participation rates and contribute to decrease the burden of this disease.

Background Only certain disseminated cells are able to grow in secondary organs to create a metastatic tumor. Under the hypothesis that the immune microenvironment of the host tissue may play an important role in this process, we have categorized metastatic samples based on their immune features. Methods Gene expression data of metastatic samples (n=374) from four secondary sites (brain, bone, liver and lung) were used to characterize samples based on their immune and stromal infiltration using gene signatures and cell quantification tools. A clustering analysis was done that separated metastatic samples into three different immune categories: high, medium and low. Results Significant differences were found between the immune profiles of samples metastasizing in distinct organs. Metastases in lung showed a higher immunogenic score than metastases in brain, liver or bone, regardless of their primary site of origin. Also, they preferentially clustered in the high immune group. Samples in this cluster exhibited a clear inflammatory phenotype, higher levels of immune infiltrate, overexpression of programmed death-ligand 1 (PD-L1) and cytotoxic T-lymphocyte-associated protein 4 (CTLA4) pathways and upregulation of genes predicting clinical response to programmed cell death protein 1 (PD-1) blockade (T-cell inflammatory signature). A decision tree algorithm was used to select CD74 as a biomarker that identify samples belonging to this high-immune subtype of metastases, having specificity of 0.96 and sensitivity of 1. Conclusions We have found a group of lung-enriched metastases showing an inflammatory phenotype susceptible to be treated with immunotherapy.

Little is known about the difference in gene expression between carcinoma‐associated fibroblasts (CAFs) and paired normal colonic fibroblasts (NCFs) in colorectal cancer. Paired CAFs and NCFs were isolated from eight primary human colorectal carcinoma specimens. In culture conditions, soluble factors secreted by CAFs in the conditioned media increased clonogenicity and migration of epithelial cancer cells lines to a greater extent than did NCF. In vivo, CAFs were more competent as tumour growth enhancers than paired NCFs when co‐inoculated with colorectal cell lines. Gene expression analysis of microarrays of CAF and paired NCF populations enabled us to identify 108 deregulated genes (38 upregulated and 70 downregulated genes). Most of those genes are fibroblast‐specific. This has been validated in silico in dataset GSE39396 and by qPCR in selected genes. GSEA analysis revealed a differential transcriptomic profile of CAFs, mainly involving the Wnt signallingsignalling pathway, focal adhesion and cell cycle. Both deregulated genes and biological processes involved depicted a considerable degree of overlap with deregulated genes reported in breast, lung, oesophagus and prostate CAFs. These observations suggest that similar transcriptomic programs may be active in the transition from normal fibroblast in adjacent tissues to CAFs, independently of their anatomic demarcation. Additionally NCF already depicted an activated pattern associated with inflammation.The deregulated genes signature score seemed to correlate with CAF tumour promoter abilities in vitro, suggesting a high degree of heterogeneity between CAFs, and it has also prognostic value in two independent datasets.Further characterization of the roles these biomarkers play in cancer will reveal how CAFs provide cancer cells with a suitable microenvironment and may help in the development of new therapeutic targets for cancer treatment.