Molecular-Subtype-Specific Biomarkers Improve Prediction of Prognosis in Colorectal Cancer

N‑glycosylation and receptor tyrosine kinase signaling affect claudin‑3 levels in colorectal cancer cells

Changes in protein levels in different components of the apical junctional complex occur in colorectal cancer (CRC). Claudin-3 is one of the main constituents of tight junctions, and its overexpression can increase the paracellular flux of macromolecules, as well as the malignant potential of CRC cells. The aim of this study was to investigate the molecular mechanisms involved in the regulation of claudin-3 and its prognostic value in CRC. In silico evaluation in each of the CRC consensus molecular subtypes (CMSs) revealed that high expression levels of CLDN3 (gene encoding claudin-3) in CMS2 and CMS3 worsened the patients' long-term survival, whereas a decrease in claudin-3 levels concomitant with a reduction in phosphorylation levels of epidermal growth factor receptor (EGFR) and insulin-like growth factor 1 receptor (IGF1R) could be achieved by inhibiting N-glycan biosynthesis in CRC cells. We also observed that specific inactivation of these receptor tyrosine kinases (RTKs) led to a decrease in claudin-3 levels, and this regulation seems to be mediated by phospholipase C (PLC) and signal transducer and activator of transcription 3 (STAT3) in CRC cells. RTKs are modulated by their N-linked glycans, and inhibition of N-glycan biosynthesis decreased the claudin-3 levels; therefore, we evaluated the correlation between N-glycogenes and CLDN3 expression levels in each of the CRC molecular subtypes. The CMS1 (MSI immune) subtype concomitantly exhibited low expression levels of CLDN3 and N-glycogenes (MGAT5, ST6GAL1, and B3GNT8), whereas CMS2 (canonical) exhibited high gene expression levels of CLDN3 and N-glycogenes (ST6GAL1 and B3GNT8). A robust positive correlation was also observed between CLDN3 and B3GNT8 expression levels in all CMSs. These results support the hypothesis of a mechanism integrating RTK signaling and N-glycosylation for the regulation of claudin-3 levels in CRC, and they suggest that CLDN3 expression can be used to predict the prognosis of patients identified as CMS2 or CMS3.

Detection of molecular signatures and pathways shared in inflammatory bowel disease and colorectal cancer: A bioinformatics and systems biology approach

Emerging evidence indicates IBD is a risk factor for the increasing incidence of colorectal cancer (CRC) development. We used a system biology approach to identify common molecular signatures and pathways that interact between IBD and CRC and the indispensable pathological mechanisms. First, we identified 177 common differentially expressed genes (DEGs) between IBD and CRC. Gene set enrichment, protein-protein, DEGs-transcription factors, DEGs-microRNAs, protein-drug interaction, gene-disease association, Gene Ontology, pathway enrichment analyses were conducted to these common genes. The inclusion of common DEGs with bimolecular networks disclosed hub proteins (LYN, PLCB1, NPSR1, WNT5A, CDC25B, CD44, RIPK2, ASAP1), transcription factors (SCD, SLC7A5, IKZF3, SLC16A1, SLC7A11) and miRNAs (mir-335-5p, mir-26b-5p, mir-124-3p, mir-16-5p, mir-192-5p, mir-548c-3p, mir-29b-3p, mir-155-5p, mir-21-5p, mir-15a-5p). Analysis of the interaction between protein and drug discovered ASAP1 interacts with cysteine sulfonic acid and double oxidized cysteine drug compounds. Gene-disease association analysis retrieved ASAP1 also associated with pulmonary and bladder neoplasm diseases.

MethCORR modelling of methylomes from formalin-fixed paraffin-embedded tissue enables characterization and prognostication of colorectal cancer

Transcriptional characterization and classification has potential to resolve the inter-tumor heterogeneity of colorectal cancer and improve patient management. Yet, robust transcriptional profiling is difficult using formalin-fixed, paraffin-embedded (FFPE) samples, which complicates testing in clinical and archival material. We present MethCORR, an approach that allows uniform molecular characterization and classification of fresh-frozen and FFPE samples. MethCORR identifies genome-wide correlations between RNA expression and DNA methylation in fresh-frozen samples. This information is used to infer gene expression information in FFPE samples from their methylation profiles. MethCORR is here applied to methylation profiles from 877 fresh-frozen/FFPE samples and comparative analysis identifies the same two subtypes in four independent cohorts. Furthermore, subtype-specific prognostic biomarkers that better predicts relapse-free survival (HR = 2.66, 95%CI [1.67-4.22], P value < 0.001 (log-rank test)) than UICC tumor, node, metastasis (TNM) staging and microsatellite instability status are identified and validated using DNA methylation-specific PCR. The MethCORR approach is general, and may be similarly successful for other cancer types.

Biomarker-guided therapy for colorectal cancer: strength in complexity

The number of molecularly stratified treatment options available to patients with colorectal cancer (CRC) is increasing, with a parallel rise in the use of biomarkers to guide prognostication and treatment decision-making. The increase in both the number of biomarkers and their use has resulted in a progressively complex situation, evident both from the extensive interactions between biomarkers and from their sometimes complex associations with patient prognosis and treatment benefit. Current and emerging biomarkers also reflect the genomic complexity of CRC, and include a wide range of aberrations such as point mutations, amplifications, fusions and hypermutator phenotypes, in addition to global gene expression subtypes. In this Review, we provide an overview of current and emerging clinically relevant biomarkers and their role in the management of patients with CRC, illustrating the intricacies of biomarker interactions and the growing treatment opportunities created by the availability of comprehensive molecular profiling.

psSubpathway: a software package for flexible identification of phenotype-specific subpathways in cancer progression

Summary

Subpathways, which are defined as local gene subregions within a biological pathway, have been reported to be associated with the occurrence and development of cancer. The recent subpathway identification tools generally identify differentially expressed subpathways between normal and cancer samples. psSubpathway is a novel systems biology R-based software package that enables flexible identification of phenotype-specific subpathways in a cancer dataset with multiple categories (such as multiple subtypes and developmental stages of cancer). The operation modes include extraction of subpathways from pathway networks, inference with subpathway activities in the context of gene expression data, identification of subtype-specific subpathways, identification of dynamic-changed subpathways associated with the cancer developmental stage and visualization of subpathway activities of samples in different phenotypes. Its capabilities enable psSubpathway to find specific abnormal subpathways in the datasets with multi-phenotype categories and to fill the gaps in the recent tools. psSubpathway may identify more specific biomarkers to facilitate the development of tailored treatment for patients with cancer.

Availability and implementation

The package is implemented in R and available under GPL-2 license from the CRAN website (https://cran.r-project.org/web/packages/psSubpathway/).

Supplementary information

Supplementary data are available at Bioinformatics online.

DAPK1 loss triggers tumor invasion in colorectal tumor cells

Colorectal cancer (CRC) is one of the leading cancer-related causes of death worldwide. Despite the improvement of surgical and chemotherapeutic treatments, as of yet, the disease has not been overcome due to metastasis to distant organs. Hence, it is of great relevance to understand the mechanisms responsible for metastasis initiation and progression and to identify novel metastatic markers for a higher chance of preventing the metastatic disease. The Death-associated protein kinase 1 (DAPK1), recently, has been shown to be a potential candidate for regulating metastasis in CRC. Hence, the aim of the study was to investigate the impact of DAPK1 protein on CRC aggressiveness. Using CRISPR/Cas9 technology, we generated DAPK1-deficient HCT116 monoclonal cell lines and characterized their knockout phenotype in vitro and in vivo. We show that loss of DAPK1 implemented changes in growth pattern and enhanced tumor budding in vivo in the chorioallantoic membrane (CAM) model. Further, we observed more tumor cell dissemination into chicken embryo organs and increased invasion capacity using rat brain 3D in vitro model. The novel identified DAPK1-loss gene expression signature showed a stroma typical pattern and was associated with a gained ability for remodeling the extracellular matrix. Finally, we suggest the DAPK1-ERK1 signaling axis being involved in metastatic progression of CRC. Our results highlight DAPK1 as an anti-metastatic player in CRC and suggest DAPK1 as a potential predictive biomarker for this cancer type.

Novel DNA methylation biomarkers show high sensitivity and specificity for blood-based detection of colorectal cancer-a clinical biomarker discovery and validation study

Background

Early detection plays an essential role to reduce colorectal cancer (CRC) mortality. While current screening methods suffer from poor compliance, liquid biopsy-based strategies for cancer detection is rapidly gaining promise. Here, we describe the development of TriMeth, a minimal-invasive blood-based test for detection of early-stage colorectal cancer. The test is based on assessment of three tumour-specific DNA methylation markers in circulating cell-free DNA.

Results

A thorough multi-step biomarker discovery study based on DNA methylation profiles of more than 5000 tumours and blood cell populations identified CRC-specific DNA methylation markers. The DNA methylation patterns of biomarker candidates were validated by bisulfite sequencing and methylation-specific droplet digital PCR in CRC tumour tissue and peripheral blood leucocytes. The three best performing markers were first applied to plasma from 113 primarily early-stage CRC patients and 87 age- and gender-matched colonoscopy-verified controls. Based on this, the test scoring algorithm was locked, and then TriMeth was validated in an independent cohort comprising 143 CRC patients and 91 controls. Three DNA methylation markers, C9orf50, KCNQ5, and CLIP4, were identified, each capable of discriminating plasma from colorectal cancer patients and healthy individuals (areas under the curve 0.86, 0.91, and 0.88). When combined in the TriMeth test, an average sensitivity of 85% (218/256) was observed (stage I: 80% (33/41), stage II: 85% (121/143), stage III: 89% (49/55), and stage IV: 88% (15/17)) at 99% (176/178) specificity in two independent plasma cohorts.

Conclusion

TriMeth enables detection of early-stage colorectal cancer with high sensitivity and specificity. The reported results underline the potential utility of DNA methylation-based detection of circulating tumour DNA in the clinical management of colorectal cancer.

A molecular sub-cluster of colon cancer cells with low VDR expression is sensitive to chemotherapy, BRAF inhibitors and PI3K-mTOR inhibitors treatment

Gene expression based consensus molecular subtypes (CMS) and non-negative matrix factorization (NMF) sub-clusters are robust colon cancer classification systems. Although, the molecular features are clear, colon cancer subgroups based interventions are limited. To address this problem, we analyze the CMS and NMF subgroup guided drug sensitivity in colon cancer cell lines. CMS3 subtype cells are sensitive to 5-Fluorouracil, while, CMS4 subtype cells are sensitive to cisplatin treatment. In NMF classification, a sub-cluster is specifically sensitive to chemotherapy, BRAF inhibitors, PI3K-mTOR inhibitors and NOTCH inhibitor treatment. This sub-cluster has low frequency of TP53, POLE, PIK3CA and BRAF mutation. Transcriptional analysis demonstrates low NOTCH signaling activity, low CDX2 and VDR expression in this sub-cluster. CDX2 and VDR are significantly associated with the sensitivity of chemotherapy, BRAF inhibitors and PI3K-mTOR inhibitors. Moreover, a positive correlation between VDR and CDX2 is identified. VDR and CDX2 mediated regulatory networks are constructed. At last, three or four sub-clusters classification is validated in colon cancer patients. Overall, our results suggest a molecular sub-cluster of colon cancer cells with low CDX2 and VDR expression is sensitive to chemotherapy, BRAF inhibitors and PI3K-mTOR inhibitors treatment and provide an example of translation of cancer classification to subgroup guided therapies.

Novel reference genes in colorectal cancer identify a distinct subset of high stage tumors and their associated histologically normal colonic tissues

Background

Reference genes are often interchangeably called housekeeping genes due to 1) the essential cellular functions their proteins provide and 2) their constitutive expression across a range of normal and pathophysiological conditions. However, given the proliferative drive of malignant cells, many reference genes such as beta-actin (ACTB) and glyceraldehyde-3-phosphate-dehydrogenase (GAPDH) which play critical roles in cell membrane organization and glycolysis, may be dysregulated in tumors versus their corresponding normal controls

Methods

Because Next Generation Sequencing (NGS) technology has several advantages over hybridization-based technologies, such as independent detection and quantitation of transcription levels, greater sensitivity, and increased dynamic range, we evaluated colorectal cancers (CRC) and their histologically normal tissue counterparts by NGS to evaluate the expression of 21 “classical” reference genes used as normalization standards for PCR based methods. Seventy-nine paired tissue samples of CRC and their patient matched healthy colonic tissues were subjected to NGS analysis of their mRNAs.

Results

We affirmed that 17 out of 21 classical reference genes had upregulated expression in tumors compared to normal colonic epithelial tissue and dramatically so in some cases. Indeed, tumors were distinguished from normal controls in both unsupervised hierarchical clustering analyses (HCA) and principal component analyses (PCA). We then identified 42 novel potential reference genes with minimal coefficients of variation (CV) across 79 CRC tumor pairs. Though largely consistently expressed across tumors and normal control tissues, a subset of high stage tumors (HSTs) as well as some normal tissue samples (HSNs) located adjacent to these HSTs demonstrated dysregulated expression, thus identifying a subset of tumors with a potentially distinct and aggressive biological profile.

Conclusion

While classical CRC reference genes were found to be differentially expressed between tumors and normal controls, novel reference genes, identified via NGS, were more consistently expressed across malignant and normal colonic tissues. Nonetheless, a subset of HST had profound dysregulation of such genes as did many of the histologically normal tissues adjacent to such HSTs, indicating that the HSTs so distinguished may have unique biological properties and that their histologically normal tissues likely harbor a small population of microscopically undetected but metabolically active tumors.

Electronic supplementary material

The online version of this article (10.1186/s12881-019-0867-y) contains supplementary material, which is available to authorized users.

High expression of meningioma 1 is correlated with reduced survival rates in colorectal cancer patients

The identification of prognostic markers for colorectal cancer (CRC) has important clinical implications. However, the association between meningioma 1 (MN1) expression and clinical outcomes of CRC has not been fully investigated. The aim of this study was to investigate the expression of MN1 in the clinical context of CRC. We first used immunohistochemistry (IHC) staining to examine and compare MN1 expression between multiple human cancer tissues and normal tissues. Initial screening revealed that the expression of MN1 proteins was significantly higher in tumor tissues of the breast, colon, and liver than in normal tissues. In further testing conducted on 59 paired CRC samples, we observed that the expression of MN1 in CRC tissue samples was significantly higher than in adjacent normal tissues. Moreover, high MN1 expression was not significantly associated with clinicopathological characteristics. Kaplan-Meier survival analysis revealed that high expression of MN1 mRNA or MN1 protein was significantly associated with poor CRC prognosis. Furthermore, univariate Cox analysis revealed that a high MN1 score was significantly associated with prognostic factors. Multivariate Cox analysis further indicated that gender, histologic grade, tumor-node-metastasis (TNM) stage, and a high MN1 score were independent factors of overall CRC survival rates. Finally, MN1 and PCNA protein levels were positively correlated, which suggests that MN1 may be involved in the cell proliferation process during CRC formation. Our results, which confirm those of other studies, indicate that (1) high levels of MN1 expression contribute to poor CRC prognosis and (2) MN1 can serve as a novel potential biomarker in predicting the prognosis of CRC patients.

DNA methylation and chromatin modifiers in colorectal cancer

Colorectal carcinogenesis is a multistep process involving the accumulation of genetic alterations over time that ultimately leads to disease progression and metastasis. Binding of transcription factors to gene promoter regions alone cannot explain the complex regulation pattern of gene expression during this process. It is the chromatin structure that allows for a high grade of regulatory flexibility for gene expression. Posttranslational modifications on histone proteins such as acetylation, methylation, or phosphorylation determine the accessibility of transcription factors to DNA. DNA methylation, a chemical modification of DNA that modulates chromatin structure and gene transcription acts in concert with these chromatin conformation alterations. Another epigenetic mechanism regulating gene expression is represented by small non-coding RNAs. Only very recently epigenetic alterations have been included in molecular subtype classification of colorectal cancer (CRC). In this chapter, we will provide examples of the different epigenetic players, focus on their role for epithelial-mesenchymal transition and metastatic processes and discuss their prognostic value in CRC.

Walking pathways with positive feedback loops reveal DNA methylation biomarkers of colorectal cancer

BACKGROUND

The search for molecular biomarkers of early-onset colorectal cancer (CRC) is an important but still quite challenging and unsolved task. Detection of CpG methylation in human DNA obtained from blood or stool has been proposed as a promising approach to a noninvasive early diagnosis of CRC. Thousands of abnormally methylated CpG positions in CRC genomes are often located in non-coding parts of genes. Novel bioinformatic methods are thus urgently needed for multi-omics data analysis to reveal causative biomarkers with a potential driver role in early stages of cancer.

METHODS

We have developed a method for finding potential causal relationships between epigenetic changes (DNA methylations) in gene regulatory regions that affect transcription factor binding sites (TFBS) and gene expression changes. This method also considers the topology of the involved signal transduction pathways and searches for positive feedback loops that may cause the carcinogenic aberrations in gene expression. We call this method "Walking pathways", since it searches for potential rewiring mechanisms in cancer pathways due to dynamic changes in the DNA methylation status of important gene regulatory regions ("epigenomic walking").

RESULTS

In this paper, we analysed an extensive collection of full genome gene-expression data (RNA-seq) and DNA methylation data of genomic CpG islands (using Illumina methylation arrays) generated from a sample of tumor and normal gut epithelial tissues of 300 patients with colorectal cancer (at different stages of the disease) (data generated in the EU-supported SysCol project). Identification of potential epigenetic biomarkers of DNA methylation was performed using the fully automatic multi-omics analysis web service "My Genome Enhancer" (MGE) (my-genome-enhancer.com). MGE uses the database on gene regulation TRANSFAC®, the signal transduction pathways database TRANSPATH®, and software that employs AI (artificial intelligence) methods for the analysis of cancer-specific enhancers.

CONCLUSIONS

The identified biomarkers underwent experimental testing on an independent set of blood samples from patients with colorectal cancer. As a result, using advanced methods of statistics and machine learning, a minimum set of 6 biomarkers was selected, which together achieve the best cancer detection potential. The markers include hypermethylated positions in regulatory regions of the following genes: CALCA, ENO1, MYC, PDX1, TCF7, ZNF43.

The Immune Subtypes and Landscape of Squamous Cell Carcinoma

PURPOSE

To identify immune subtypes and investigate the immune landscape of squamous cell carcinomas (SCC), which share common etiology and histologic features.

EXPERIMENTAL DESIGN

Based on the immune gene expression profiles of 1,368 patients with SCC in the Cancer Genome Atlas (TCGA), we used consensus clustering to identify robust clusters of patients and assessed their reproducibility in an independent pan-SCC cohort of 938 patients. We further applied graph structure learning-based dimensionality reduction to the immune profiles to visualize the distribution of individual patients.

RESULTS

We identified and independently validated six reproducible immune subtypes associated with distinct molecular characteristics and clinical outcomes. An immune-cold subtype had the least amount of lymphocyte infiltration and a high level of aneuploidy, and these patients had the worst prognosis. By contrast, an immune-hot subtype demonstrated the highest infiltration of CD8⁺ T cells, activated NK cells, and elevated IFNγ response. Accordingly, these patients had the best prognosis. A third subtype was dominated by M2-polarized macrophages with potent immune-suppressive factors such as TGFβ signaling and reactive stroma, and these patients had relatively inferior prognosis. Other subtypes showed more diverse immunologic features with intermediate prognoses. Finally, our analysis revealed a complex immune landscape consisting of both discrete clusters and continuous spectrum.

CONCLUSIONS

This study provides a conceptual framework to understand the tumor immune microenvironment of SCCs. Future work is needed to evaluate its relevance in the design of combination treatment strategies and guiding optimal selection of patients for immunotherapy.

Back to the Colorectal Cancer Consensus Molecular Subtype Future

PURPOSE OF REVIEW

This review seeks to provide an informed prospective on the advances in molecular profiling and analysis of colorectal cancer (CRC). The goal is to provide a historical context and current summary on how advances in gene and protein sequencing technology along with computer capabilities led to our current bioinformatic advances in the field.

RECENT FINDINGS

An explosion of knowledge has occurred regarding genetic, epigenetic, and biochemical alterations associated with the evolution of colorectal cancer. This has led to the realization that CRC is a heterogeneous disease with molecular alterations often dictating natural history, response to treatment, and outcome. The consensus molecular subtypes (CMS) classification classifies CRC into four molecular subtypes with distinct biological characteristics, which may form the basis for clinical stratification and subtype-based targeted intervention. This review summarizes new developments of a field moving "Back to the Future." CRC molecular subtyping will better identify key subtype specific therapeutic targets and responses to therapy.

Heterogeneity in Colorectal Cancer: A Challenge for Personalized Medicine?

High inter-patient variability and high spatial heterogeneity are features of colorectal cancer (CRC). This may influence the molecular characterization of tumor tissue, now mandatory for patients with metastatic CRC who are candidates for treatment with an anti-EGFR mAb, as false-negative results can occur, leading to non optimal therapy. Moreover, temporal molecular heterogeneity during treatment is known to influence the response to therapy and prognosis. We present a literature overview of advances made in characterizing molecular heterogeneity in CRC, underlining that the analysis of liquid biopsy could represent an efficient non-invasive tool to overcome the problem. We believe that understanding CRC heterogeneity is fundamental for a more accurate diagnosis, for selecting the best targets to ensure prolonged antitumor response, and for monitoring minimal residual disease and the onset of resistance to therapy, all essential components of successful personalized treatment.

An Integrated Approach for Identifying Molecular Subtypes in Human Colon Cancer Using Gene Expression Data

Identifying molecular subtypes of colorectal cancer (CRC) may allow for more rational, patient-specific treatment. Various studies have identified molecular subtypes for CRC using gene expression data, but they are inconsistent and further research is necessary. From a methodological point of view, a progressive approach is needed to identify molecular subtypes in human colon cancer using gene expression data. We propose an approach to identify the molecular subtypes of colon cancer that integrates denoising by the Bayesian robust principal component analysis (BRPCA) algorithm, hierarchical clustering by the directed bubble hierarchical tree (DBHT) algorithm, and feature gene selection by an improved differential evolution based feature selection method (DEFSW) algorithm. In this approach, the normal samples being completely and exclusively clustered into one class is considered to be the standard of reasonable clustering subtypes, and the feature selection pays attention to imbalances of samples among subtypes. With this approach, we identified the molecular subtypes of colon cancer on the mRNA gene expression dataset of 153 colon cancer samples and 19 normal control samples of the Cancer Genome Atlas (TCGA) project. The colon cancer was clustered into 7 subtypes with 44 feature genes. Our approach could identify finer subtypes of colon cancer with fewer feature genes than the other two recent studies and exhibits a generic methodology that might be applied to identify the subtypes of other cancers.

Strategy to targeting the immune resistance and novel therapy in colorectal cancer

Assessing the CRC subtypes that can predict the outcome of colorectal cancer (CRC) in patients with immunogenicity seems to be a promising strategy to develop new drugs that target the antitumoral immune response. In particular, the disinhibition of the antitumoral T‐cell response by immune checkpoint blockade has shown remarkable therapeutic promise for patients with mismatch repair (MMR) deficient CRC. In this review, the authors provide the update of the molecular features and immunogenicity of CRC, discuss the role of possible predictive biomarkers, illustrate the modern immunotherapeutic approaches, and introduce the most relevant ongoing preclinical study and clinical trials such as the use of the combination therapy with immunotherapy. Furthermore, this work is further to understand the complex interactions between the immune surveillance and develop resistance in tumor cells. As expected, if the promise of these developments is fulfilled, it could develop the effective therapeutic strategies and novel combinations to overcome immune resistance and enhance effector responses, which guide clinicians toward a more “personalized” treatment for advanced CRC patients.

Colorectal cancer: genetic abnormalities, tumor progression, tumor heterogeneity, clonal evolution and tumor-initiating cells

Colon cancer is the third most common cancer worldwide. Most colorectal cancer occurrences are sporadic, not related to genetic predisposition or family history; however, 20-30% of patients with colorectal cancer have a family history of colorectal cancer and 5% of these tumors arise in the setting of a Mendelian inheritance syndrome. In many patients, the development of a colorectal cancer is preceded by a benign neoplastic lesion: either an adenomatous polyp or a serrated polyp. Studies carried out in the last years have characterized the main molecular alterations occurring in colorectal cancers, showing that the tumor of each patient displays from two to eight driver mutations. The ensemble of molecular studies, including gene expression studies, has led to two proposed classifications of colorectal cancers, with the identification of four/five non-overlapping groups. The homeostasis of the rapidly renewing intestinal epithelium is ensured by few stem cells present at the level of the base of intestinal crypts. Various experimental evidence suggests that colorectal cancers may derive from the malignant transformation of intestinal stem cells or of intestinal cells that acquire stem cell properties following malignant transformation. Colon cancer stem cells seem to be involved in tumor chemoresistance, radioresistance and relapse.

Clinical importance of DNA repair in sporadic colorectal cancer

Colorectal cancer (CRC) is the third major cause of cancer-related deaths worldwide. However, despite the scientific efforts to provide a molecular classification to improve CRC clinical practice management, prognosis and therapeutic decision are still strongly dependent on the TNM staging system. Mismatch repair system deficiencies can occur in many organs, but it is mainly a hallmark of CRC influencing clinical outcomes and response to therapy. This review will discuss the effect of the modulation of other DNA repair pathways (direct, excision and double strand break repairs) in the clinical and pathological aspects of colorectal cancer and its potential as prognostic and predictive biomarkers.

Epigenetic and epitranscriptomic changes in colorectal cancer: Diagnostic, prognostic, and treatment implications

A cancer cell is the final product of a complex mixture of genetic, epigenetic and epitranscriptomic alterations, whose final interplay contribute to cancer onset and progression. This is specifically true for colorectal cancer, a tumor with a strong epigenetic component, which acts earlier than any other genetic alteration in promoting cancer cell malignant transformation. The pattern of progressive, and usually subtype-specific, DNA and histone modifications that occur in colorectal cancer has been extensively studied in the last decade, providing plenty of data to explore. For this tumor, it became recently evident that also RNA modifications play a relevant role in the activation of oncogenes or repression of tumor suppressor genes. In this review we provide a brief overview of all epigenetic and epitranscriptomic changes that have been found associated to colorectal cancer till now. We explore the impact of these alterations in cancer prognosis and response to treatment and discuss their potential use as cancer biomarkers.

Proteome Heterogeneity in Colorectal Cancer

Tumor heterogeneity is an important feature of colorectal cancer (CRC) manifested by dynamic changes in gene expression, protein expression, and availability of different tumor subtypes. Recent publications in the past 10 years have revealed proteome heterogeneity between different colorectal tumors and within the same tumor site. This paper reviews recent research works on the proteome heterogeneity in CRC, which includes the heterogeneity within a single tumor (intratumor heterogeneity), between different anatomical sites at the same organ, and between primary and metastatic sites (intertumor heterogeneity). The potential use of proteome heterogeneity in precision medicine and its implications in biomarker discovery and therapeutic outcomes will be discussed. Identification of the unique proteome landscape between and within individual tumors is imperative for understanding cancer biology and the management of CRC patients.

Andersen C. Characterization of genetic intratumor heterogeneity in colorectal cancer and matching patient-derived spheroid cultures

Patient-derived in vitro cultures of colorectal cancer (CRC) may help guide treatment strategies prior to patient treatment. However, most previous studies have been performed on a single biopsy per tumor. The purpose of this study was to analyze multiple spatially distinct biopsies from CRCs and see how well intratumor heterogeneity (ITH) was recapitulated in matching patient-derived spheroids. Three to five biopsies were collected from six CRC tumors. Each biopsy was split in two; one half was used for spheroid culturing, while the other half was used for DNA and RNA purification. For two patients, lymph node metastases were analyzed. Somatic mutations were called from whole exome sequencing data. Each tumor contained mutations shared across all biopsies and spheroids, including major CRC drivers such as APC, KRAS, and TP53. At the same time, all tumors exhibited ITH on both mutation and copy number level. The concordance between biopsies and spheroids ranged between 40 and 70% for coding mutations. For three patients, the biopsy and spheroid from matching areas clustered together, meaning that the spheroid resembled the area of origin more than the other areas. However, all biopsies and spheroids contained private mutations. Therefore, multiple cultures from spatially distinct sites of the tumor increase the insight into the genetic profile of the entire tumor. Molecular subtypes were called from RNA sequencing data. When based on transcripts from both cancer and noncancerous cells, the subtypes were largely independent of sampling site. In contrast, subtyping based on cancer cell transcripts alone was dependent on sample site and genetic ITH. In conclusion, all examined CRC tumors showed genetic ITH. Spheroid cultures partly reflected this ITH, and having multiple cultures from distinct tumor sites improved the representation of the genetic tumor subclones. This should be taken into account when establishing patient-derived models for drug screening.

Prognostic value of lymph node metastasis in patients with T1-stage colorectal cancer from multiple centers in China

AIM

To explore the features and prognostic value of lymph node metastasis in patients with T1-stage colorectal cancer (CRC).

METHODS

In all, 321 cases of T1-stage CRC were selected from 10132 patients with CRC who received surgical therapy in six large-scale hospitals in China and were retrospectively analyzed. Univariate and multivariate analyses were performed to analyze the risk factors for lymphatic metastasis. A survival analysis was then performed to analyze the prognostic value of lymph node metastasis.

RESULTS

The occurrence rate of T1 stage was 3.17% (321/10132); of these patients, the lymph node metastasis rate was 8.41% (27/321), and the non-lymph node metastasis rate was 91.59% (294/321). Univariate analysis showed that preoperative serum CEA, preoperative serum CA199, preoperative serum CA724, vascular invasion, and degree of differentiation were associated with lymph node metastasis in T1-stage CRC (P < 0.05 for all). Multivariate analysis indicated that preoperative serum CA724, vascular invasion, and degree of differentiation were closely related to lymph node metastasis (P < 0.05 for all). Log-rank survival analysis showed that age, preoperative serum CEA, preoperative serum CA199, vascular invasion, degree of differentiation, and lymph node metastasis (χ² = 24.180, P < 0.001) were predictors of 5-year overall survival (OS) (P < 0.05 for all). COX regression analysis demonstrated that preoperative serum CA199 and lymph node metastasis (HR = 5.117; P < 0.05; 95%CI: 0.058-0.815) were independent prognostic indicators of 5-year OS in patients with T1-stage CRC (P < 0.05 for both).

CONCLUSION

The morbidity of T1-stage CRC was 3.17% for all CRC cases. Preoperative serum CA724, vascular invasion, and degree of differentiation are independent risk factors for lymph node metastasis. Lymph node metastasis is an independent prognostic factor for OS in patients with T1-stage CRC.

CMScaller: an R package for consensus molecular subtyping of colorectal cancer pre-clinical models

Colorectal cancers (CRCs) can be divided into four gene expression-based biologically distinct consensus molecular subtypes (CMS). This classification provides a potential framework for stratified treatment, but to identify novel CMS-drug associations, translation of the subtypes to pre-clinical models is essential. The currently available classifier is dependent on gene expression signals from the immune and stromal compartments of tumors and fails to identify the poor-prognostic CMS4-mesenchymal group in immortalized cell lines, patient-derived organoids and xenografts. To address this, we present a novel CMS classifier based on a filtered set of cancer cell-intrinsic, subtype-enriched gene expression markers. This new classifier, referred to as CMScaller, recapitulated the subtypes in both in vitro and in vivo models (551 in total). Importantly, by analyzing public drug response data from patient-derived xenografts and cell lines, we show that the subtypes are predictive of response to standard CRC drugs. CMScaller is available as an R package.