Germline genetic regulation of the colorectal tumor immune microenvironment.

OBJECTIVE: To evaluate the contribution of germline genetics to regulating the briskness and diversity of T cell responses in CRC, we conducted a genome-wide association study to examine the associations between germline genetic variation and quantitative measures of T cell landscapes in 2,876 colorectal tumors from participants in the Molecular Epidemiology of Colorectal Cancer Study (MECC). METHODS: Germline DNA samples were genotyped and imputed using genome-wide arrays. Tumor DNA samples were extracted from paraffin blocks, and T cell receptor clonality and abundance were quantified by immunoSEQ (Adaptive Biotechnologies, Seattle, WA). Tumor infiltrating lymphocytes per high powered field (TILs/hpf) were scored by a gastrointestinal pathologist. Regression models were used to evaluate the associations between each variant and the three T-cell features, adjusting for sex, age, genotyping platform, and global ancestry. Three independent datasets were used for replication. RESULTS: We identified a SNP (rs4918567) near RBM20 associated with clonality at a genome-wide significant threshold of 5 × 10- 8, with a consistent direction of association in both discovery and replication datasets. Expression quantitative trait (eQTL) analyses and in silico functional annotation for these loci provided insights into potential functional roles, including a statistically significant eQTL between the T allele at rs4918567 and higher expression of ADRA2A (P = 0.012) in healthy colon mucosa. CONCLUSIONS: Our study suggests that germline genetic variation is associated with the quantity and diversity of adaptive immune responses in CRC. Further studies are warranted to replicate these findings in additional samples and to investigate functional genomic mechanisms.

MmCMS: mouse models' consensus molecular subtypes of colorectal cancer.

BACKGROUND: Colorectal cancer (CRC) primary tumours are molecularly classified into four consensus molecular subtypes (CMS1-4). Genetically engineered mouse models aim to faithfully mimic the complexity of human cancers and, when appropriately aligned, represent ideal pre-clinical systems to test new drug treatments. Despite its importance, dual-species classification has been limited by the lack of a reliable approach. Here we utilise, develop and test a set of options for human-to-mouse CMS classifications of CRC tissue. METHODS: Using transcriptional data from established collections of CRC tumours, including human (TCGA cohort; n = 577) and mouse (n = 57 across n = 8 genotypes) tumours with combinations of random forest and nearest template prediction algorithms, alongside gene ontology collections, we comprehensively assess the performance of a suite of new dual-species classifiers. RESULTS: We developed three approaches: MmCMS-A; a gene-level classifier, MmCMS-B; an ontology-level approach and MmCMS-C; a combined pathway system encompassing multiple biological and histological signalling cascades. Although all options could identify tumours associated with stromal-rich CMS4-like biology, MmCMS-A was unable to accurately classify the biology underpinning epithelial-like subtypes (CMS2/3) in mouse tumours. CONCLUSIONS: When applying human-based transcriptional classifiers to mouse tumour data, a pathway-level classifier, rather than an individual gene-level system, is optimal. Our R package enables researchers to select suitable mouse models of human CRC subtype for their experimental testing.

Extranodal natural killer/T-cell lymphoma nasal type in a western population: Molecular profiling identifies new therapeutic targets.

(A) Correlation matrix of unsupervised co-regulated genes, based on the 208 genes included in the NanoString platform. Some of the clusters of co-regulated genes corresponded to the following: Inflammatory cells; Epstein-Barr virus; B-cells; Cytotoxic T-cells; T-cells; and Proliferation. (B) Analysis of genomic alterations by targeted sequencing. Distribution of mutations in the 62 analyzed genes. Rows correspond to sequenced genes, columns represent individual patients. Color coding: green, missense; blue, synonymous; pink, frameshift; violet, Indel; red, stop gained; yellow, UTR.

Copy-number intratumor heterogeneity increases the risk of relapse in chemotherapy-naive stage II colon cancer.

Optimal selection of high-risk patients with stage II colon cancer is crucial to ensure clinical benefit of adjuvant chemotherapy. Here, we investigated the prognostic value of genomic intratumor heterogeneity and aneuploidy for disease recurrence. We combined targeted sequencing, SNP arrays, fluorescence in situ hybridization, and immunohistochemistry on a retrospective cohort of 84 untreated stage II colon cancer patients. We assessed the clonality of copy-number alterations (CNAs) and mutations, CD8+ lymphocyte infiltration, and their association with time to recurrence. Prognostic factors were included in machine learning analysis to evaluate their ability to predict individual relapse risk. Tumors from recurrent patients displayed a greater proportion of CNAs compared with non-recurrent (mean 31.3% versus 23%, respectively; p = 0.014). Furthermore, patients with elevated tumor CNA load exhibited a higher risk of recurrence compared with those with low levels [p = 0.038; hazard ratio (HR) 2.46], which was confirmed in an independent cohort (p = 0.004; HR 3.82). Candidate chromosome-specific aberrations frequently observed in recurrent cases included gain of the chromosome arm 13q (p = 0.02; HR 2.67) and loss of heterozygosity at 17q22-q24.3 (p = 0.05; HR 2.69). CNA load positively correlated with intratumor heterogeneity (R = 0.52; p < 0.0001). Consistently, incremental subclonal CNAs were associated with an elevated risk of relapse (p = 0.028; HR 2.20), which we did not observe for subclonal single-nucleotide variants and small insertions and deletions. The clinico-genomic model rated an area under the curve of 0.83, achieving a 10% incremental gain compared with clinicopathological markers (p = 0.047). In conclusion, tumor aneuploidy and copy-number intratumor heterogeneity were predictive of poor outcome and improved discriminative performance in early-stage colon cancer. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Post-polypectomy colonoscopy surveillance: Can we improve the diagnostic yield?

Although adenomas and serrated polyps are the preneoplastic lesions of colorectal cancer, only few of them will eventually progress to cancer. This review provides a comprehensive overview of the present and future of post-polypectomy colonoscopy surveillance. Post-polypectomy surveillance guidelines have recently been updated and all share the aim towards more selective and less frequent surveillance. We have examined these current guidelines and compared the recommendations of each of them. To improve the diagnostic yield of post-polypectomy surveillance it is important to find predictors of metachronous polyps that better identify high-risk individuals of developing advanced neoplasia. For this reason, we have also conducted a literature review of the molecular biomarkers of metachronous advanced colorectal polyps. Finally, we have discussed future directions of post-polypectomy surveillance and identified possible strategies to improve the use of endoscopic resources with the COVID-19 pandemic.

Additive Role of Immune System Infiltration and Angiogenesis in Uveal Melanoma Progression.

Uveal melanoma (UM) is a malignant tumor that arises in the melanocytes of the uveal tract. It is the most frequent eye cancer, and despite new therapeutic approaches, prognosis is still poor, with up to 50% of patients developing metastasis with no efficient treatment options available. In contrast to cutaneous melanoma, UM is considered an "immune-cold" tumor due to the low mutational burden and the unique immunosuppressive microenvironment. To gain insight into the role of the UM microenvironment in regard to prognosis and metastatic progression, we have performed a pool analysis characterizing the UM microenvironment by using a bioinformatic approach. A variety of scores based on gene expression measuring stromal infiltration were calculated and used to assess association with prognosis. As a result, the highest immune and stromal scores were associated with poor prognosis. Specifically, stromal cells (fibroblasts and endothelial cells), T cells CD8+, natural killer (NK) cells, and macrophages M1 and M2 infiltration were associated with poor prognosis. Contrary to other tumors, lymphocytic infiltration is related to poor prognosis. Only B cells were associated with more favorable prognosis. UM samples scoring high in both angiogenesis (Angio) and antigen presentation (AP) pathways showed a poor prognosis suggesting an additive role of both functions. Almost all these tumors exhibited a chromosome 3 monosomy. Finally, an enrichment analysis showed that tumors classified as high Angio-high AP also activated metabolic pathways such as glycolysis or PI3K-AKT-MTOR. In summary, our pool analysis identified a cluster of samples with angiogenic and inflammatory phenotypes exhibiting poor prognosis and metabolic activation. Our analysis showed robust results replicated in a pool analysis merging different datasets from different analytic platforms.

Lymphocytic infiltration in stage II microsatellite stable colorectal tumors: A retrospective prognosis biomarker analysis.

BACKGROUND: Identifying stage II patients with colorectal cancer (CRC) at higher risk of progression is a clinical priority in order to optimize the advantages of adjuvant chemotherapy while avoiding unnecessary toxicity. Recently, the intensity and the quality of the host immune response in the tumor microenvironment have been reported to have an important role in tumorigenesis and an inverse association with tumor progression. This association is well established in microsatellite instable CRC. In this work, we aim to assess the usefulness of measures of T-cell infiltration as prognostic biomarkers in 640 stage II, CRC tumors, 582 of them confirmed microsatellite stable. METHODS AND FINDINGS: We measured both the quantity and clonality index of T cells by means of T-cell receptor (TCR) immunosequencing in a discovery dataset (95 patients with colon cancer diagnosed at stage II and microsatellite stable, median age 67, 30% women) and replicated the results in 3 additional series of stage II patients from 2 countries. Series 1 and 2 were recruited in Barcelona, Spain and included 112 fresh frozen (FF, median age 69, 44% women) and 163 formalin-fixed paraffin-embedded (FFPE, median age 67, 39% women) samples, respectively. Series 3 included 270 FFPE samples from patients recruited in Haifa, Northern Israel, as part of a large case-control study of CRC (median age 73, 46% women). Median follow-up time was 81.1 months. Cox regression models were fitted to evaluate the prognostic value of T-cell abundance and Simpson clonality of TCR variants adjusting by sex, age, tumor location, and stage (IIA and IIB). In the discovery dataset, higher TCR abundance was associated with better prognosis (hazard ratio [HR] for ≥Q1 = 0.25, 95% CI 0.10-0.63, P = 0.003). A functional analysis of gene expression on these tumors revealed enrichment in pathways related to immune response. Higher values of clonality index (lower diversity) were not associated with worse disease-free survival, though the HR for ≥Q3 was 2.32 (95% CI 0.90-5.97, P = 0.08). These results were replicated in an independent FF dataset (TCR abundance: HR = 0.30, 95% CI 0.12-0.72, P = 0.007; clonality: HR = 3.32, 95% CI 1.38-7.94, P = 0.007). Also, the association with prognosis was tested in 2 independent FFPE datasets. The same association was observed with TCR abundance (HR = 0.41, 95% CI 0.18-0.93, P = 0.03 and HR = 0.56, 95% CI 0.31-1, P = 0.042, respectively, for each FFPE dataset). However, the clonality index was associated with prognosis only in the FFPE dataset from Israel (HR = 2.45, 95% CI 1.39-4.32, P = 0.002). Finally, a combined analysis combining all microsatellite stable (MSS) samples demonstrated a clear prognosis value both for TCR abundance (HR = 0.39, 95% CI 0.26-0.57, P = 1.3e-06) and the clonality index (HR = 2.13, 95% CI 1.44-3.15, P = 0.0002). These associations were also observed when variables were considered continuous in the models (HR per log2 of TCR abundance = 0.85, 95% CI 0.78-0.93, P = 0.0002; HR per log2 or clonality index = 1.16, 95% CI 1.03-1.31, P = 0.016). LIMITATIONS: This is a retrospective study, and samples had been preserved with different methods. Validation series lack complete information about microsatellite instability (MSI) status and pathology assessment. The Molecular Epidemiology of Colorectal Cancer (MECC) study had information about overall survival instead of progression-free survival. CONCLUSION: Results from this study demonstrate that tumor lymphocytes, assessed by TCR repertoire quantification based on a sequencing method, are an independent prognostic factor in microsatellite stable stage II CRC.

Role of POLE and POLD1 in familial cancer.

PURPOSE: Germline pathogenic variants in the exonuclease domain (ED) of polymerases POLE and POLD1 predispose to adenomatous polyps, colorectal cancer (CRC), endometrial tumors, and other malignancies, and exhibit increased mutation rate and highly specific associated mutational signatures. The tumor spectrum and prevalence of POLE and POLD1 variants in hereditary cancer are evaluated in this study. METHODS: POLE and POLD1 were sequenced in 2813 unrelated probands referred for genetic counseling (2309 hereditary cancer patients subjected to a multigene panel, and 504 patients selected based on phenotypic characteristics). Cosegregation and case-control studies, yeast-based functional assays, and tumor mutational analyses were performed for variant interpretation. RESULTS: Twelve ED missense variants, 6 loss-of-function, and 23 outside-ED predicted-deleterious missense variants, all with population allele frequencies <1%, were identified. One ED variant (POLE p.Met294Arg) was classified as likely pathogenic, four as likely benign, and seven as variants of unknown significance. The most commonly associated tumor types were colorectal, endometrial and ovarian cancers. Loss-of-function and outside-ED variants are likely not pathogenic for this syndrome. CONCLUSIONS: Polymerase proofreading-associated syndrome constitutes 0.1-0.4% of familial cancer cases, reaching 0.3-0.7% when only CRC and polyposis are considered. ED variant interpretation is challenging and should include multiple pieces of evidence.

Algorithmic methods to infer the evolutionary trajectories in cancer progression.

The genomic evolution inherent to cancer relates directly to a renewed focus on the voluminous next-generation sequencing data and machine learning for the inference of explanatory models of how the (epi)genomic events are choreographed in cancer initiation and development. However, despite the increasing availability of multiple additional -omics data, this quest has been frustrated by various theoretical and technical hurdles, mostly stemming from the dramatic heterogeneity of the disease. In this paper, we build on our recent work on the "selective advantage" relation among driver mutations in cancer progression and investigate its applicability to the modeling problem at the population level. Here, we introduce PiCnIc (Pipeline for Cancer Inference), a versatile, modular, and customizable pipeline to extract ensemble-level progression models from cross-sectional sequenced cancer genomes. The pipeline has many translational implications because it combines state-of-the-art techniques for sample stratification, driver selection, identification of fitness-equivalent exclusive alterations, and progression model inference. We demonstrate PiCnIc's ability to reproduce much of the current knowledge on colorectal cancer progression as well as to suggest novel experimentally verifiable hypotheses.

Colon-specific eQTL analysis to inform on functional SNPs.

BACKGROUND: Genome-wide association studies on colorectal cancer have identified more than 60 susceptibility loci, but for most of them there is no clear knowledge of functionality or the underlying gene responsible for the risk modification. Expression quantitative trail loci (eQTL) may provide functional information for such single nucleotide polymorphisms (SNPs). METHODS: We have performed detailed eQTL analysis specific for colon tissue on a series of 97 colon tumours, their paired adjacent normal mucosa and 47 colon mucosa samples donated by healthy individuals. R package MatrixEQTL was used to search for genome-wide cis-eQTL and trans-eQTL fitting linear models adjusted for age, gender and tissue type to rank transformed expression data. RESULTS: The cis-eQTL analyses has revealed 29,073 SNP-gene associations with permutation-adjusted P-values < 0.01. These correspond to 363 unique genes. The trans-eQTL analysis identified 10,665 significant SNP-gene associations, most of them in the same chromosome, further than 1 Mb of the gene. We provide a web tool to search for specific SNPs or genes. The tool calculates Pearson or Spearman correlation, and allows to select tissue type for analysis. Data and plots can be exported. CONCLUSIONS: This resource should be useful to prioritise SNPs for further functional studies and to identify relevant genes behind identified loci.

Telomere length alterations in microsatellite stable colorectal cancer and association with the immune response.

Telomeres are repetitive sequences (TTAGGG) located at the end of chromosomes. Telomeres progressively shorten with each cell replication cycle, ultimately leading to chromosomal instability and loss of cell viability. Telomere length anomaly appears to be one of the earliest and most prevalent genetic alterations in malignant transformation. Here we aim to estimate telomere length from whole-exome sequencing data in colon tumors and normal colonic mucosa, and to analyze the potential association of telomere length with clinical factors and gene expression in colon cancer. Reads containing at least five repetitions of the telomere sequence (TTAGGG) were extracted from the raw sequences of 42 adjacent normal-tumor paired samples. The number of reads from the tumor sample was normalized to build the Tumor Telomere Length Ratio (TTLR), considered an estimation of telomere length change in the tumor compared to the paired normal tissue. We evaluated the associations between TTLR and clinical factors, gene expression and copy number (CN) aberrations measured in the same tumor samples. Colon tumors showed significantly shorter telomeres than their paired normal samples. No significant association was observed between TTLR and gender, age, tumor location, prognosis, stromal infiltration or molecular subtypes. The functional gene set enrichment analysis showed pathways related to immune response significantly associated with TLLR. By extracting a relative measure of telomere length from whole-exome sequencing data, we have assessed that colon tumor cells predominantly shorten telomeres, and this alteration is associated with expression changes in genes related to immune response and inflammation in tumor cells.

Comprehensive analysis of copy number aberrations in microsatellite stable colon cancer in view of stromal component.

BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.

Molecular approaches for classifying endometrial carcinoma.

Endometrial carcinoma is the most common cancer of the female genital tract. This review article discusses the usefulness of molecular techniques to classify endometrial carcinoma. Any proposal for molecular classification of neoplasms should integrate morphological features of the tumors. For that reason, we start with the current histological classification of endometrial carcinoma, by discussing the correlation between genotype and phenotype, and the most significant recent improvements. Then, we comment on some of the possible flaws of this classification, by discussing also the value of molecular pathology in improving them, including interobserver variation in pathologic interpretation of high grade tumors. Third, we discuss the importance of applying TCGA molecular approach to clinical practice. We also comment on the impact of intratumor heterogeneity in classification, and finally, we will discuss briefly, the usefulness of TCGA classification in tailoring immunotherapy in endometrial cancer patients. We suggest combining pathologic classification and the surrogate TCGA molecular classification for high-grade endometrial carcinomas, as an option to improve assessment of prognosis.

Germline Mutations in FAN1 Cause Hereditary Colorectal Cancer by Impairing DNA Repair.

Identification of genes associated with hereditary cancers facilitates management of patients with family histories of cancer. We performed exome sequencing of DNA from 3 individuals from a family with colorectal cancer who met the Amsterdam criteria for risk of hereditary nonpolyposis colorectal cancer. These individuals had mismatch repair-proficient tumors and each carried nonsense variant in the FANCD2/FANCI-associated nuclease 1 gene (FAN1), which encodes a nuclease involved in DNA inter-strand cross-link repair. We sequenced FAN1 in 176 additional families with histories of colorectal cancer and performed in vitro functional analyses of the mutant forms of FAN1 identified. We detected FAN1 mutations in approximately 3% of families who met the Amsterdam criteria and had mismatch repair-proficient cancers with no previously associated mutations. These findings link colorectal cancer predisposition to the Fanconi anemia DNA repair pathway, supporting the connection between genome integrity and cancer risk.

Altered pathways and colorectal cancer prognosis.

The identification of molecular markers with prognostic value in colorectal cancer is a challenging task that is needed to define therapeutic guidelines. Clinical factors are insufficient to identify those patients with stage II at risk of relapse or those patients with stage III at low risk. There is a current effort to define a consensus in molecular subtypes based on expression profiles, which are characterized by a distinctive prognostic outcome. Also several gene expression signatures based on individual genes have been proposed to predict prognosis, but they show low consistency and reproducibility. Slattery et al. describe a pathway-based approach to analyze gene expression differences between normal and colon cancer tissues. The most interesting finding is that having more deregulated pathways is associated with good prognosis. If these findings are properly validated, new insights into the mechanisms of colon carcinogenesis may be revealed. Please see related article: http://dx.doi.org/10.1186/s12916-015-0292-9 .

A transcriptome-proteome integrated network identifies endoplasmic reticulum thiol oxidoreductase (ERp57) as a hub that mediates bone metastasis.

Bone metastasis is the most common distant relapse in breast cancer. The identification of key proteins involved in the osteotropic phenotype would represent a major step toward the development of new prognostic markers and therapeutic improvements. The aim of this study was to characterize functional phenotypes that favor bone metastasis in human breast cancer. We used the human breast cancer cell line MDA-MB-231 and its osteotropic BO2 subclone to identify crucial proteins in bone metastatic growth. We identified 31 proteins, 15 underexpressed and 16 overexpressed, in BO2 cells compared with parental cells. We employed a network-modeling approach in which these 31 candidate proteins were prioritized with respect to their potential in metastasis formation, based on the topology of the protein-protein interaction network and differential expression. The protein-protein interaction network provided a framework to study the functional relationships between biological molecules by attributing functions to genes whose functions had not been characterized. The combination of expression profiles and protein interactions revealed an endoplasmic reticulum-thiol oxidoreductase, ERp57, functioning as a hub that retained four down-regulated nodes involved in antigen presentation associated with the human major histocompatibility complex class I molecules, including HLA-A, HLA-B, HLA-E, and HLA-F. Further analysis of the interaction network revealed an inverse correlation between ERp57 and vimentin, which influences cytoskeleton reorganization. Moreover, knockdown of ERp57 in BO2 cells confirmed its bone organ-specific prometastatic role. Altogether, ERp57 appears as a multifunctional chaperone that can regulate diverse biological processes to maintain the homeostasis of breast cancer cells and promote the development of bone metastasis.

Identification of candidate susceptibility genes for colorectal cancer through eQTL analysis.

In this study, we aim to identify the genes responsible for colorectal cancer risk behind the loci identified in genome-wide association studies (GWAS). These genes may be candidate targets for developing new strategies for prevention or therapy. We analyzed the association of genotypes for 26 GWAS single nucleotide polymorphisms (SNPs) with the expression of genes within a 2 Mb region (cis-eQTLs). Affymetrix Human Genome U219 expression arrays were used to assess gene expression in two series of samples, one of healthy colonic mucosa (n = 47) and other of normal mucosa adjacent to colon cancer (n = 97, total 144). Paired tumor tissues (n = 97) were also analyzed but did not provide additional findings. Partial Pearson correlation (r), adjusted for sample type, was used for the analysis. We have found Bonferroni-significant cis-eQTLs in three loci: rs3802842 in 11q23.1 associated to C11orf53, COLCA1 (C11orf92) and COLCA2 (C11orf93; r = 0.60); rs7136702 in 12q13.12 associated to DIP2B (r = 0.63) and rs5934683 in Xp22.3 associated to SHROOM2 and GPR143 (r = 0.47). For loci in chromosomes 11 and 12, we have found other SNPs in linkage disequilibrium that are more strongly associated with the expression of the identified genes and are better functional candidates: rs7130173 for 11q23.1 (r = 0.66) and rs61927768 for 12q13.12 (r = 0.86). These SNPs are located in DNA regions that may harbor enhancers or transcription factor binding sites. The analysis of trans-eQTLs has identified additional genes in these loci that may have common regulatory mechanisms as shown by the analysis of protein-protein interaction networks.

Aberrant gene expression in mucosa adjacent to tumor reveals a molecular crosstalk in colon cancer.

BACKGROUND: 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. METHODS: 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). RESULTS: 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. CONCLUSIONS: 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.

Large differences in global transcriptional regulatory programs of normal and tumor colon cells.

BACKGROUND: Dysregulation of transcriptional programs leads to cell malfunctioning and can have an impact in cancer development. Our study aims to characterize global differences between transcriptional regulatory programs of normal and tumor cells of the colon. METHODS: Affymetrix Human Genome U219 expression arrays were used to assess gene expression in 100 samples of colon tumor and their paired adjacent normal mucosa. Transcriptional networks were reconstructed using ARACNe algorithm using 1,000 bootstrap replicates consolidated into a consensus network. Networks were compared regarding topology parameters and identified well-connected clusters. Functional enrichment was performed with SIGORA method. ENCODE ChIP-Seq data curated in the hmChIP database was used for in silico validation of the most prominent transcription factors. RESULTS: The normal network contained 1,177 transcription factors, 5,466 target genes and 61,226 transcriptional interactions. A large loss of transcriptional interactions in the tumor network was observed (11,585; 81% reduction), which also contained fewer transcription factors (621; 47% reduction) and target genes (2,190; 60% reduction) than the normal network. Gene silencing was not a main determinant of this loss of regulatory activity, since the average gene expression was essentially conserved. Also, 91 transcription factors increased their connectivity in the tumor network. These genes revealed a tumor-specific emergent transcriptional regulatory program with significant functional enrichment related to colorectal cancer pathway. In addition, the analysis of clusters again identified subnetworks in the tumors enriched for cancer related pathways (immune response, Wnt signaling, DNA replication, cell adherence, apoptosis, DNA repair, among others). Also multiple metabolism pathways show differential clustering between the tumor and normal network. CONCLUSIONS: These findings will allow a better understanding of the transcriptional regulatory programs altered in colon cancer and could be an invaluable methodology to identify potential hubs with a relevant role in the field of cancer diagnosis, prognosis and therapy.

dsRNAi-mediated silencing of PIAS2beta specifically kills anaplastic carcinomas by mitotic catastrophe.

The E3 SUMO ligase PIAS2 is expressed at high levels in differentiated papillary thyroid carcinomas but at low levels in anaplastic thyroid carcinomas (ATC), an undifferentiated cancer with high mortality. We show here that depletion of the PIAS2 beta isoform with a transcribed double-stranded RNA-directed RNA interference (PIAS2b-dsRNAi) specifically inhibits growth of ATC cell lines and patient primary cultures in vitro and of orthotopic patient-derived xenografts (oPDX) in vivo. Critically, PIAS2b-dsRNAi does not affect growth of normal or non-anaplastic thyroid tumor cultures (differentiated carcinoma, benign lesions) or cell lines. PIAS2b-dsRNAi also has an anti-cancer effect on other anaplastic human cancers (pancreas, lung, and gastric). Mechanistically, PIAS2b is required for proper mitotic spindle and centrosome assembly, and it is a dosage-sensitive protein in ATC. PIAS2b depletion promotes mitotic catastrophe at prophase. High-throughput proteomics reveals the proteasome (PSMC5) and spindle cytoskeleton (TUBB3) to be direct targets of PIAS2b SUMOylation at mitotic initiation. These results identify PIAS2b-dsRNAi as a promising therapy for ATC and other aggressive anaplastic carcinomas.