Multi-omics Approach Reveals Distinct Differences in Left- and Right-Sided Colon Cancer

Biomarker Profile of Colorectal Cancer: Current Findings and Future Perspective

OBJECTIVE

Breakthroughs in omics technology have led to a deeper understanding of the fundamental molecular changes that play a critical role in the development and progression of cancer. This review delves into the hidden molecular drivers of colorectal cancer (CRC), offering potential for clinical translation through novel biomarkers and personalized therapies.

METHODS

We summarizes recent studies utilizing various omics approaches, including genomics, transcriptomics, proteomics, epigenomics, metabolomics and data integration with computational algorithms, to investigate CRC.

RESULTS

Integrating multi-omics data in colorectal cancer research unlocks hidden biological insights, revealing new pathways and mechanisms. This powerful approach not only identifies potential biomarkers for personalized prognosis, diagnosis, and treatment, but also predicts patient response to specific therapies, while computational tools illuminate the landscape by deciphering complex datasets.

CONCLUSIONS

Future research should prioritize validating promising biomarkers and seamlessly translating them into clinical practice, ultimately propelling personalized CRC management to new heights.

Clinicopathological Differences between Right and Left Colorectal Cancer by Sex

Background: Until now, studies on colorectal cancer (CRC) have focused on clinicopathological characteristics based on location without considering sex differences. However, as men and women have fundamentally different physiological characteristics, research results in the clinical field are limited. We aimed to elucidate the differences in the clinicopathological characteristics between right-sided CRC (RCC) and left-sided CRC (LCC) according to sex. Methods: We classified 1492 South Korean patients with no history of colon surgery between July 2005 and June 2015 based on tumor location and sex. For these patients, differences in the clinical characteristics according to sex were compared using univariate and multivariate analyses. Results: Of the 1269 patients, 951 (74.9%) had LCC, and 318 (25.1%) had RCC, making LCC approximately three times more common than RCC. When sex was not taken into account, patients with RCC had significantly higher rates of anemia and undifferentiated cancers than the rates in those with LCC. Even considering sex, anemia and undifferentiated cancer were more prevalent in RCC than in LCC in both men and women. In contrast, age over 65 years and abnormal white blood cell count differed between RCC and LCC only in women. Conclusions: The clinicopathologic characteristics of CRC vary according to the location and sex. Therefore, sex must be considered as a fundamental characteristic of personalized treatment.

Identifying important microbial and genomic biomarkers for differentiating right- versus left-sided colorectal cancer using random forest models

BACKGROUND

Colorectal cancer (CRC) is a heterogeneous disease, with subtypes that have different clinical behaviours and subsequent prognoses. There is a growing body of evidence suggesting that right-sided colorectal cancer (RCC) and left-sided colorectal cancer (LCC) also differ in treatment success and patient outcomes. Biomarkers that differentiate between RCC and LCC are not well-established. Here, we apply random forest (RF) machine learning methods to identify genomic or microbial biomarkers that differentiate RCC and LCC.

METHODS

RNA-seq expression data for 58,677 coding and non-coding human genes and count data for 28,557 human unmapped reads were obtained from 308 patient CRC tumour samples. We created three RF models for datasets of human genes-only, microbes-only, and genes-and-microbes combined. We used a permutation test to identify features of significant importance. Finally, we used differential expression (DE) and paired Wilcoxon-rank sum tests to associate features with a particular side.

RESULTS

RF model accuracy scores were 90%, 70%, and 87% with area under curve (AUC) of 0.9, 0.76, and 0.89 for the human genomic, microbial, and combined feature sets, respectively. 15 features were identified as significant in the model of genes-only, 54 microbes in the model of microbes-only, and 28 genes and 18 microbes in the model with genes-and-microbes combined. PRAC1 expression was the most important feature for differentiating RCC and LCC in the genes-only model, with HOXB13, SPAG16, HOXC4, and RNLS also playing a role. Ruminococcus gnavus and Clostridium acetireducens were the most important in the microbial-only model. MYOM3, HOXC4, Coprococcus eutactus, PRAC1, lncRNA AC012531.25, Ruminococcus gnavus, RNLS, HOXC6, SPAG16 and Fusobacterium nucleatum were most important in the combined model.

CONCLUSIONS

Many of the identified genes and microbes among all models have previously established associations with CRC. However, the ability of RF models to account for inter-feature relationships within the underlying decision trees may yield a more sensitive and biologically interconnected set of genomic and microbial biomarkers.

Prognosis Prediction of Lung Adenocarcinoma Patients Based on Molecular Subgroups of DNA Methylation

Lung adenocarcinoma (LUAD) is a malignant tumor with high mortality. At present, the clinicopathologic feature is the main breakthrough to assess the prognosis of LUAD patients. However, in most cases, the results are less than satisfactory. Cox regression analysis was conducted in this study to obtain methylation sites with significant prognostic relevance based on mRNA expression, DNA methylation data, and clinical data of LUAD from The Cancer Genome Atlas Program database. LUAD patients were grouped into 4 subtypes according to different methylation levels using K-means consensus cluster analysis. By survival analysis, patients were grouped into high-methylation and low-methylation groups. Later, 895 differentially expressed genes (DEGs) were obtained. Eight optimal methylation signature genes associated with prognosis were screened by Cox regression analysis, and a risk assessment model was constructed based on these genes. Samples were then classified into high-risk and low-risk groups depending on the risk assessment model, and prognostic, predictive ability was assessed using survival and receiver operating characteristic (ROC) curves. The results showed that this risk model had a great efficacy in predicting the prognosis of patients, and it was, therefore, able to be an independent prognostic factor. At last, the enrichment analysis demonstrated that the signaling pathways, including cell cycle, homologous recombination, P53 signaling pathway, DNA replication, pentose phosphate pathway, and glycolysis gluconeogenesis were remarkably activated in the high-risk group. In general, we construct an 8-gene model based on DNA methylation molecular subtypes by a series of bioinformatics methods, which can provide new insights for predicting the prognosis of patients with LUAD.

Biomarkers in Metastatic Colorectal Cancer: Status Quo and Future Perspective

Colorectal cancer (CRC) is the third most frequent cancer worldwide, and its incidence is steadily increasing. During the last two decades, a tremendous improvement in outcome has been achieved, mainly due to the introduction of novel drugs, targeted treatment, immune checkpoint inhibitors (CPIs) and biomarker-driven patient selection. Moreover, progress in molecular diagnostics but also improvement in surgical techniques and local ablative treatments significantly contributed to this success. However, novel therapeutic approaches are needed to further improve outcome in patients diagnosed with metastatic CRC. Besides the established biomarkers for mCRC, such as microsatellite instability (MSI) or mismatch repair deficiency (dMMR), RAS/BRAF, sidedness and HER2 amplification, new biomarkers have to be identified to better select patients who derive the most benefit from a specific treatment. In this review, we provide an overview about therapeutic relevant and established biomarkers but also shed light on potential promising markers that may help us to better tailor therapy to the individual mCRC patient in the near future.

Tumor-infiltrated activated B cells suppress liver metastasis of colorectal cancers

More than 40% of patients with late-stage colorectal cancer (CRC) develop liver metastasis (LM). Which immune cells play important roles in CRC-LM and contribute to the difference between left-sided CRC (LCC) and right-sided CRC (RCC) remain unclear. By single-cell RNA sequencing (scRNA-seq), we not only find that activated B cells are significantly depleted in CRC with LM, but also find a subtype of B cells developed from activated B cells, namely immature plasma cell population alpha (iMPA), highly correlated with metastasis. Mechanistically, inhibition of the Wnt and transforming growth factor β (TGF-β) pathways in cancer cell promotes activated B cell migration via the SDF-1-CXCR4 axis. This study reveals that B cell subpopulations in the tumor immune microenvironment (TIME) play a key role in CRC-LM as well as in LCC and RCC. The preventive effects of modulating B cell subpopulations in CRC may provide a rationale for subsequent drug development and CRC-LM management.

Effects of Anesthetics on Proliferation and Apoptosis of Drug-Resistant Human Colon Cancer Cells

In recent years, people's living standards are getting higher and higher, and life pressure is also increasing, and there are also many problems in eating habits. This is also the direct cause of colon cancer. The aim of this paper was to investigate whether anesthetic drugs could positively affect the proliferation and apoptosis of colon cancer cells. In this paper, the significance of anesthetic drugs is proposed, and an artificial neural network algorithm based on artificial intelligence is proposed. It is well known that artificial neural networks play an important role in medicine. The experimental results of this paper show that the incidence of colon cancer in 2020 will be in the range of 5%-35%, and the incidence of colon cancer in 2021 will be in the range of 7%-30%. While colon cancer rates in 2021 do not appear to be as high as colon cancer rates in 2020, they are generally much higher than colon cancer rates in 2020. It can be seen that as the population ages, the number of colon cancer patients is increasing due to the lack of emphasis on health. This also means that the incidence of colon cancer is getting higher and higher, and traditional drug chemotherapy has been unable to play a good role in inhibiting the proliferation of colon cancer cells. Therefore, this paper investigated the effects of anesthetic drugs on the proliferation and apoptosis of human colon cancer cells.

Association Mining Identifies MAL2 as a Novel Tumor Suppressor in Colorectal Cancer

Introduction

Colorectal cancer (CRC) is a leading cause of cancer-related deaths worldwide. However, the driver genes that promote CRC metastasis remain poorly understood. Association mining mines and extracts the repeated correlations and relevance in a dataset to predict the appearance of other data items according to the appearance of one item.

Methods

Here, the Apriori algorithm was used to find the frequent mutational gene sets (FMGSs) and hidden association rules (ARs) within these FMGSs from 383 CRCs with whole exome sequencing datasets. The weighted correlation network analysis (WGCNA) was used to identify the hub genes in CRC. CCK8, colony formation, cell migration and invasion assays were adopted to detect the roles of hub genes in CRC.

Results

Intriguingly, we found that MAL2 (myelin and lymphocyte protein 2) was associated with TP53 and APC in stage IV of CRC, and further subnetwork exploration based on WGCNA identified MAL2 as a potent hub gene. To validate the metastasis-related role of MAL2 in CRC, a lentivirus-based overexpression system was utilized to construct MAL2-overexpressing human CRC LOVO cells. Overexpression of MAL2 remarkably inhibited CRC cell proliferation and invasion.

Conclusion

Our results highlighted that MAL2 acts as a tumor suppressor in CRC and could serve as a potential therapeutic target.

Identification of multi-omics biomarkers and construction of the novel prognostic model for hepatocellular carcinoma

Genome changes play a crucial role in carcinogenesis, and many biomarkers can be used as effective prognostic indicators in various tumors. Although previous studies have constructed many predictive models for hepatocellular carcinoma (HCC) based on molecular signatures, the performance is unsatisfactory. Because multi-omics data can more comprehensively reflect the biological phenomenon of disease, we hope to build a more accurate predictive model by multi-omics analysis. We use the TCGA to identify crucial biomarkers and construct prognostic models through difference analysis, univariate Cox, and LASSO/stepwise Cox analysis. The performances of predictive models were evaluated and validated through survival analysis, Harrell’s concordance index (C-index), receiver operating characteristic (ROC) curve, and decision curve analysis (DCA). Multiple mRNAs, lncRNAs, miRNAs, CNV genes, and SNPs were significantly associated with the prognosis of HCC. We constructed five single-omic models, and the mRNA and lncRNA models showed good performance with c-indexes over 0.70. The multi-omics model presented a robust predictive ability with a c-index over 0.77. This study identified many biomarkers that may help study underlying carcinogenesis mechanisms in HCC. In addition, we constructed multiple single-omic models and an integrated multi-omics model that may provide practical and reliable guides for prognosis assessment.

Dynamic Co-Evolution of Cancer Cells and Cancer-Associated Fibroblasts: Role in Right- and Left-Sided Colon Cancer Progression and Its Clinical Relevance

Simple Summary

The versatile crosstalk between cancer cells and cancer-associated fibroblasts (CAFs) of the tumour microenvironment (TME) drives colorectal carcinogenesis and heterogeneity. Colorectal cancer (CRC) can be classified by the anatomical sites from which the cancer arises, either from the right or left colon. Although the cancer cell–CAF interaction is being widely studied, its role in the progression of cancer in the right and left colon and cancer heterogeneity are still yet to be elucidated. Further insight into the complex interaction between different cellular components in the cancer niche, their evolutionary process and their influence on cancer progression would propel the discovery of effective targeted CRC therapy.

Abstract

Cancer is a result of a dynamic evolutionary process. It is composed of cancer cells and the tumour microenvironment (TME). One of the major cellular constituents of TME, cancer-associated fibroblasts (CAFs) are known to interact with cancer cells and promote colorectal carcinogenesis. The accumulation of these activated fibroblasts is linked to poor diagnosis in colorectal cancer (CRC) patients and recurrence of the disease. However, the interplay between cancer cells and CAFs is yet to be described, especially in relation to the sidedness of colorectal carcinogenesis. CRC, which is the third most commonly diagnosed cancer globally, can be classified according to the anatomical region from which they originate: left-sided (LCRC) and right-sided CRC (RCR). Both cancers differ in many aspects, including in histology, evolution, and molecular signatures. Despite occurring at lower frequency, RCRC is often associated with worse diagnosis compared to LCRC. The differences in molecular profiles between RCRC and LCRC also influence the mode of treatment that can be used to specifically target these cancer entities. A better understanding of the cancer cell–CAF interplay and its association with RCRC and LRCR progression will provide better insight into potential translational aspects of targeted treatment for CRC.

The Genomics of Colorectal Cancer in Populations with African and European Ancestry

Black people have a higher incidence of colorectal cancer and worse survival rates when compared with white people. Comprehensive genomic profiling was performed in 46,140 colorectal adenocarcinoma cases. Ancestry-informative markers identified 5,301 patients of African descent (AFR) and 33,770 patients of European descent (EUR). AFR were younger, had fewer microsatellite instability-high (MSI-H) tumors, and had significantly more frequent alterations in KRAS, APC, and PIK3CA. AFR had increased frequency of KRAS mutations, specifically KRASG12D and KRASG13. There were no differences in rates of actionable kinase driver alterations (HER2, MET, NTRK, ALK, ROS1, and RET). In patients with young-onset colorectal cancer (<50 years), AFR and EUR had a similar frequency of MSI-H and tumor mutational burden-high (TMB-H) tumors, and strikingly different trends in APC mutations by age, as well as differences in MAPK pathway alterations. These findings inform treatment decisions, impact prognosis, and underscore the need for model systems representative of the diverse U.S. population.

SIGNIFICANCE

KRAS (particularly KRASG12D/G13), APC, and PIK3CA were more frequently altered in AFR who had a lower frequency of MSI-H tumors. There were no differences in actionable kinase driver alterations. In young-onset colorectal cancer, both ancestries had a similar frequency of MSI-H/TMB-H tumors, but strikingly different trends in APC. See related commentary by Eng and Holowatyj, p. 1187. This article is highlighted in the In This Issue feature, p. 1171.

Bacterial Involvement in Progression and Metastasis of Colorectal Neoplasia

While the gut microbiome is composed of numerous bacteria, specific bacteria within the gut may play a significant role in carcinogenesis, progression, and metastasis of colorectal carcinoma (CRC). Certain microbial species are known to be associated with specific cancers; however, the interrelationship between bacteria and metastasis is still enigmatic. Mounting evidence suggests that bacteria participate in cancer organotropism during solid tumor metastasis. A critical review of the literature was conducted to better characterize what is known about bacteria populating a distant site and whether a tumor depends upon the same microenvironment during or after metastasis. The processes of carcinogenesis, tumor growth and metastatic spread in the setting of bacterial infection were examined in detail. The literature was scrutinized to discover the role of the lymphatic and venous systems in tumor metastasis and how microbes affect these processes. Some bacteria have a potent ability to enhance epithelial-mesenchymal transition, a critical step in the metastatic cascade. Bacteria also can modify the microenvironment and the local immune profile at a metastatic site. Early targeted antibiotic therapy should be further investigated as a measure to prevent metastatic spread in the setting of bacterial infection.

Use of Omics Technologies for the Detection of Colorectal Cancer Biomarkers

Colorectal cancer (CRC) is one of the most frequently diagnosed cancers with high mortality rates, especially when detected at later stages. Early detection of CRC can substantially raise the 5-year survival rate of patients, and different efforts are being put into developing enhanced CRC screening programs. Currently, the faecal immunochemical test with a follow-up colonoscopy is being implemented for CRC screening. However, there is still a medical need to describe biomarkers that help with CRC detection and monitor CRC patients. The use of omics techniques holds promise to detect new biomarkers for CRC. In this review, we discuss the use of omics in different types of samples, including breath, urine, stool, blood, bowel lavage fluid, or tumour tissue, and highlight some of the biomarkers that have been recently described with omics data. Finally, we also review the use of extracellular vesicles as an improved and promising instrument for biomarker detection.

Genomic and Metabolomic Landscape of Right-Sided and Left-Sided Colorectal Cancer: Potential Preventive Biomarkers

Colorectal cancer (CRC) is the third most common cancer worldwide. The incidence and mortality rates of CRC are significantly higher in Taiwan than in other developed countries. Genes involved in CRC tumorigenesis differ depending on whether the tumor occurs on the left or right side of the colon, and genomic analysis is a keystone in the study and treatment of CRC subtypes. However, few studies have focused on the genetic landscape of Taiwanese patients with CRC. This study comprehensively analyzed the genomes of 141 Taiwanese patients with CRC through whole-exome sequencing. Significant genomic differences related to the site of CRC development were observed. Blood metabolomic profiling and polygenic risk score analysis were performed to identify potential biomarkers for the early identification and prevention of CRC in the Taiwanese population. Our findings provide vital clues for establishing population-specific treatments and health policies for CRC prevention in Taiwan.

PSC associated inflammatory bowel disease: a distinct entity

INTRODUCTION

Primary sclerosing cholangitis (PSC) is a rare, chronic, and progressive cholestatic disease involving intra- and/or extrahepatic bile ducts. PSC in many patients results in end-stage liver diseases. Nearly 60% of the PSC patients suffer from concomitant inflammatory bowel diseases (IBDs). Classically, IBDs are divided into two principle types: Crohn's disease (CD) and ulcerative colitis (UC). However, with growing knowledge, PSC-associated IBD (PSC-IBD) seems to be a rather distinct entity with specific genetics, clinical, and microbiota characteristics.

AREAS COVERED

In this article, we aim to review the unique characteristics of PSC-IBD from clinical, genetic, and microbiota point of view.

EXPERT OPINION

PSC-IBD's unique characteristics contribute to the notion that it could be a distinct entity. Acknowledgment of PSC-IBD as a novel entity necessitates designing new clinical guidelines for diagnosis and developing novel therapies.

Master Transcription Regulators and Transcription Factors Regulate Immune-Associated Differences Between Patients of African and European Ancestry With Colorectal Cancer

Background and Aims

Individuals of African (AFR) ancestry have a higher incidence of colorectal cancer (CRC) than those of European (EUR) ancestry and exhibit significant health disparities. Previous studies have noted differences in the tumor microenvironment between AFR and EUR patients with CRC. However, the molecular regulatory processes that underpin these immune differences remain largely unknown.

Methods

Multiomics analysis was carried out for 55 AFR and 456 EUR patients with microsatellite-stable CRC using The Cancer Genome Atlas. We evaluated the tumor microenvironment by using gene expression and methylation data, transcription factor, and master transcriptional regulator analysis to identify the cell signaling pathways mediating the observed phenotypic differences.

Results

We demonstrate that downregulated genes in AFR patients with CRC showed enrichment for canonical pathways, including chemokine signaling. Moreover, evaluation of the tumor microenvironment showed that cytotoxic lymphocytes and neutrophil cell populations are significantly decreased in AFR compared with EUR patients, suggesting AFR patients have an attenuated immune response. We further demonstrate that molecules called "master transcriptional regulators" (MTRs) play a critical role in regulating the expression of genes impacting key immune processes through an intricate signal transduction network mediated by disease-associated transcription factors (TFs). Furthermore, a core set of these MTRs and TFs showed a positive correlation with levels of cytotoxic lymphocytes and neutrophils across both AFR and EUR patients with CRC, thus suggesting their role in driving the immune infiltrate differences between the two ancestral groups.

Conclusion

Our study provides an insight into the intricate regulatory landscape of MTRs and TFs that orchestrate the differences in the tumor microenvironment between patients with CRC of AFR and EUR ancestry.

CoSMeD: a user-friendly web server to estimate 5-year survival probability of left-sided and right-sided colorectal cancer patients using molecular data

SUMMARY

Colorectal cancer is a heterogeneous disease with diverse prognoses between left-sided and right-sided patients; therefore, it is necessary to precisely evaluate the survival probability of side-specific colorectal cancer patients. Here, we collected multi-omics data from The Cancer Genome Atlas program, including gene expression, DNA methylation and microRNA expression. Specificity measure and robust likelihood-based survival analysis were used to identify 6 left-sided and 28 right-sided prognostic biomarkers. Compared to the performance of clinical prognostic models, the addition of these biomarkers could significantly improve the discriminatory ability and calibration in predicting side-specific 5-year survival for colorectal cancer. Additional dataset derived from Gene Expression Omnibus was used to validate the prognostic value of side-specific genes. Finally, we constructed colorectal cancer side-specific molecular database (CoSMeD), a user-friendly interface for estimating side-specific colorectal cancer 5-year survival probability, which can lay the basis for personalized management of left-sided and right-sided colorectal cancer patients.

AVAILABILITY AND IMPLEMENTATION

CoSMeD is freely available at https://mulongdu.shinyapps.io/cosmed.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Regulatory Network Analysis of Mutated Genes Based on Multi-Omics Data Reveals the Exclusive Features in Tumor Immune Microenvironment Between Left-Sided and Right-Sided Colon Cancer

Left-sided colon cancer (LCC) and right-sided colon cancer (RCC) have distinct characteristics in tumor immune microenvironment (TIME). Although existing studies have shown a strong association between gene mutations and TIME, whether the regulatory mechanisms between gene mutations and TIME are different between RCC and LCC is still unclear. In this study, we showed the fractions of CD8+ T cells were higher while those of regulatory T cells were lower in RCC. Besides, a stronger association between gene mutations and TIME was observed in RCC. Specifically, using multi-omics data, we demonstrated the mutations of most top mutated genes (TMGs) including BRAF, PCLO, MUC16, LRP2, ANK3, KMT2D, RYR2 made great contributions to elevated fraction of immune cells by up-regulating immune-related genes directly or indirectly through miRNA and DNA methylation, whereas the effects of APC, TP53 and KRAS mutations on TIME were reversed in RCC. Remarkably, we found the expression levels of several immune checkpoint molecules such as PD-1 and LAG3 were correlated with corresponding DNA methylation levels, which were associated with the mutations of TMGs in RCC. In contrast, the associations between gene mutations and TIME were less significant in LCC. Besides, survival analyses showed APC mutation had adverse impact on immunotherapy while patients with BRAF mutation were more suitable for immunotherapy in colon cancer. We hope that our results will provide a deeper insight into the sophisticated mechanism underlying the regulation between mutations and TIME, and thus boost the discovery of differential immunotherapeutic strategies for RCC and LCC.

Comparative analysis of clonal evolution among patients with right- and left-sided colon and rectal cancer

Tumor multiregion sequencing reveals intratumor heterogeneity (ITH) and clonal evolution playing a key role in tumor progression and metastases. Large-scale high-depth multiregional sequencing of colorectal cancer, comparative analysis among patients with right-sided colon cancer (RCC), left-sided colon cancer (LCC), and rectal cancer (RC), as well as the study of lymph node metastasis (LN) with extranodal tumor deposits (ENTDs) from evolutionary perspective remain weakly explored. Here, we recruited 68 patients with RCC (18), LCC (20), and RC (30). We performed high-depth whole-exome sequencing of 206 tumor regions including 176 primary tumors, 19 LN, and 11 ENTD samples. Our results showed ITH with a Darwinian pattern of evolution and the evolution pattern of LCC and RC was more complex and divergent than RCC. Genetic and evolutionary evidences found that both LN and ENTD originated from different clones. Moreover, ENTD was a distinct entity from LN and evolved later.

Identification of Novel Mutations in Colorectal Cancer Patients Using AmpliSeq Comprehensive Cancer Panel

Biomarker discovery would be an important tool in advancing and utilizing the concept of precision and personalized medicine in the clinic. Discovery of novel variants in local population provides confident targets for developing biomarkers for personalized medicine. We identified the need to generate high-quality sequencing data from local colorectal cancer patients and understand the pattern of occurrence of variants. In this report, we used archived samples from Saudi Arabia and used the AmpliSeq comprehensive cancer panel to identify novel somatic variants. We report a comprehensive analysis of next-generation sequencing results with a coverage of >300X. We identified 466 novel variants which were previously unreported in COSMIC and ICGC databases. We analyzed the genes associated with these variants in terms of their frequency of occurrence, probable pathogenicity, and clinicopathological features. Among pathogenic somatic variants, 174 were identified for the first time in the large intestine. APC, RET, and EGFR genes were most frequently mutated. A higher number of variants were identified in the left colon. Occurrence of variants in ERBB2 was significantly correlated with those of EGFR and ATR genes. Network analyses of the identified genes provide functional perspective of the identified genes and suggest affected pathways and probable biomarker candidates. This report lays the ground work for biomarker discovery and identification of driver gene mutations in local population.

HomeoboxC6 promotes metastasis by orchestrating the DKK1/Wnt/β-catenin axis in right-sided colon cancer

Patients with right-sided colon cancer (RCC) generally have a poorer prognosis than those with left-sided colon cancer (LCC). We previously found that homeobox C6 (HOXC6) was the most significantly upregulated gene in RCC compared to LCC. However, it remains unclear whether HOXC6 plays a role in tumor proliferation and metastasis. Our study aimed to explore the potential oncogenic role and the detailed molecular mechanism of HOXC6 in RCC. In this study, HOXC6 was validated to be overexpressed in RCC and associated with poor prognosis. Furthermore, overexpression of HOXC6 promoted the migration and invasion of colon cancer cells through inducing EMT by activating the Wnt/β-catenin signaling pathway and inhibition of DKK1 secretion. Lastly, we preliminary explored the translational effect of HOXC6 and found that silencing of HOXC6 made HCT116 and HT29 cells more sensitive to irinotecan.

Understanding cell-cell communication and signaling in the colorectal cancer microenvironment

Carcinomas are complex heterocellular systems containing epithelial cancer cells, stromal fibroblasts, and multiple immune cell-types. Cell-cell communication between these tumor microenvironments (TME) and cells drives cancer progression and influences response to existing therapies. In order to provide better treatments for patients, we must understand how various cell-types collaborate within the TME to drive cancer and consider the multiple signals present between and within different cancer types. To investigate how tissues function, we need a model to measure both how signals are transferred between cells and how that information is processed within cells. The interplay of collaboration between different cell-types requires cell-cell communication. This article aims to review the current in vitro and in vivo mono-cellular and multi-cellular cultures models of colorectal cancer (CRC), and to explore how they can be used for single-cell multi-omics approaches for isolating multiple types of molecules from a single-cell required for cell-cell communication to distinguish cancer cells from normal cells. Integrating the existing single-cell signaling measurements and models, and through understanding the cell identity and how different cell types communicate, will help predict drug sensitivities in tumor cells and between- and within-patients responses.

Unsupervised subtyping and methylation landscape of pancreatic ductal adenocarcinoma

Pancreatic Ductal Adenocarcinoma (PDAC) is an aggressive form of pancreatic cancer that typically manifests itself at an advanced stage and does not respond to most treatment modalities. The survival rate of a PDAC patient is less than 5%, with a median survival of just a couple of months. A better understanding of the molecular pathology of PDAC is needed to guide research for the development of better clinical treatment modalities for PDAC patients. Gene expression studies performed to date have identified different subtypes of PDAC with prognostic and clinical relevance. Subtypes identified to date are highly heterogeneous since pancreatic cancer is heterogeneous cancer. Tumor microenvironment and stroma constitute a major chunk of PDAC and contribute to the heterogeneity. Better subtyping methods are need of the hour for better prognosis and classification of PDAC for future personalized treatment. In this work, we have performed an integrated analysis of DNA methylation and gene expression datasets to provide better mechanistic and molecular insights into Pancreatic cancers, especially PDAC. The use of varied and diverse datasets has provided valuable insights into different cancer types and can play an integral role in revealing the complex nature of underlying biological mechanisms. We performed subtyping of TCGA-PAAD gene expression and methylation datasets into different subtypes using state-of-the-art normalization methods and unsupervised clustering methods that reveal latent hidden factors, leading to additional insights for subtyping. Differential expression and differential methylation were performed for each of the subtypes obtained from clustering. Our analysis gave a consensus of five cluster solution with relevant pathways like MAPK, MET. The five subtypes corresponded to the tumor and stromal subtypes. This analysis helps in distinguishing and identifying different subtypes based on enriched putative genes. These results help propose novel experimentally-verifiable PDAC subtyping and demonstrate that using varied data sets and integrated methods can contribute to disease prognostication and precision medicine in PDAC treatment.

Characterization of genomic alterations in Chinese colorectal cancer patients

OBJECTIVE

Colorectal cancer is one of the most prevalent types of cancer worldwide. Right-sided and left-sided colorectal cancer (RCC and LCC) patients respond differently to treatment. We aimed to identify the different mutational profile between RCC and LCC and provided evidence for future precision therapy.

METHODS

A total of 630 Chinese colorectal cancer patients, including 467 (74.1%) LCC and 163 (25.9%) RCC, were enrolled in this cohort. Both formalin-fixed paraffin-embedded tumor tissues and matching blood samples were collected and deep sequenced targeting 450 cancer genes for genomic alteration analysis. Tumor mutational burden was measured by an algorithm developed in-house. Correlation analysis was performed by Fisher's exact test.

RESULTS

The most common mutated genes were TP53 (77.0%), APC (71.7%), KRAS (50.0%), SMAD4 (19.8%), PIK3CA (18.3%), FBXW7 (17.5%), TCF7L2 (12.5%), SOX9 (11.3%), LRP1B (10.8%), ARID1A (10.3%) and FAT4 (10.3%). The mutation frequencies of TP53 and APC in LCC were significantly higher than that of RCC, while the mutation frequency of PIK3CA was lower than that of RCC. Six gene fusions were specifically detected in RCC patients. Colorectal cancer sites were associated with gender (P = 4.15 × 10-5) and tumor differentiation (P = 0.059). In LCC, the gender-associated genes were FAT4, EP300, FAT1, LRP1, ARID1B, AR, FYN and TAF1, while in RCC, they were ARID1A, SMARCA4, LRP1 and GRIN2A. The mutations of 18 genes were associated with tumor differentiation (8 for LCC and 10 for RCC). High tumor mutational burden was more common in RCC. Our results implied more potential targeted drug therapy opportunities for RCC.

CONCLUSION

We describe the different molecular characteristics of LCC and RCC. Our result supported a better prognosis of RCC than LCC in Chinese colorectal cancer patients.

Intestinal region-specific Wnt signalling profiles reveal interrelation between cell identity and oncogenic pathway activity in cancer development

BACKGROUND

Cancer results from the accumulation of mutations leading to the acquisition of cancer promoting characteristics such as increased proliferation and resistance to cell death. In colorectal cancer, an early mutation leading to such features usually occurs in the APC or CTNNB1 genes, thereby activating Wnt signalling. However, substantial phenotypic differences between cancers originating within the same organ, such as molecular subtypes, are not fully reflected by differences in mutations. Indeed, the phenotype seems to result from a complex interplay between the cell-intrinsic features and the acquired mutations, which is difficult to disentangle when established tumours are studied.

METHODS

We use a 3D in vitro organoid model to study the early phase of colorectal cancer development. From three different murine intestinal locations we grow organoids. These are transformed to resemble adenomas after Wnt activation through lentiviral transduction with a stable form of β-Catenin. The gene expression before and after Wnt activation is compared within each intestinal origin and across the three locations using RNA sequencing. To validate and generalize our findings, we use gene expression data from patients.

RESULTS

In reaction to Wnt activation we observe downregulation of location specific genes and differentiation markers. A similar effect is seen in patient data, where genes with significant differential expression between the normal left and right colon are downregulated in the cancer samples. Furthermore, the signature of Wnt target genes differs between the three intestinal locations in the organoids. The location specific Wnt signatures are dominated by genes which have been lowly expressed in the tissue of origin, and are the targets of transcription factors that are activated following enhanced Wnt signalling.

CONCLUSION

We observed that the region-specific cell identity has a substantial effect on the reaction to Wnt activation in a simple intestinal adenoma model. These findings provide a way forward in resolving the distinct biology between left- and right-sided human colon cancers with potential clinical relevance.

Discovering the molecular differences between right- and left-sided colon cancer using machine learning methods

Background

In recent years, the differences between left-sided colon cancer (LCC) and right-sided colon cancer (RCC) have received increasing attention due to the clinicopathological variation between them. However, some of these differences have remained unclear and conflicting results have been reported.

Methods

From The Cancer Genome Atlas (TCGA), we obtained RNA sequencing data and gene mutation data on 323 and 283 colon cancer patients, respectively. Differential analysis was firstly done on gene expression data and mutation data between LCC and RCC, separately. Machine learning (ML) methods were then used to select key genes or mutations as features to construct models to classify LCC and RCC patients. Finally, we conducted correlation analysis to identify the correlations between differentially expressed genes (DEGs) and mutations using logistic regression (LR) models.

Results

We found distinct gene mutation and expression patterns between LCC and RCC patients and further selected the 30 most important mutations and 17 most important gene expression features using ML methods. The classification models created using these features classified LCC and RCC patients with high accuracy (areas under the curve (AUC) of 0.8 and 0.96 for mutation and gene expression data, respectively). The expression of PRAC1 and BRAF V600E mutation (rs113488022) were the most important feature for each model. Correlations of mutations and gene expression data were also identified using LR models. Among them, rs113488022 was found to have significance relevance to the expression of four genes, and thus should be focused on in further study.

Conclusions

On the basis of ML methods, we found some key molecular differences between LCC and RCC, which could differentiate these two groups of patients with high accuracy. These differences might be key factors behind the variation in clinical features between LCC and RCC and thus help to improve treatment, such as determining the appropriate therapy for patients.

Molecular heterogeneity of guanine nucleotide binding-protein γ subunit 4 in left- and right-sided colon cancer

Molecular heterogeneity determines the differences in the pathological features, prognosis and survival after relapse when comparing left-sided colon cancer (LCC) and right-sided colon cancer (RCC). At present, the discrepancy in the underlying molecular events between the two types of colon cancer has not been thoroughly investigated. The present study aimed to explore novel targets to predict the disease stage and prognosis of LCC and RCC. Expression analysis of guanine nucleotide binding-protein γ subunit 4 (GNG4) was performed using the Gene Expression Profiling Interactive Analysis (GEPIA) and Oncomine databases. Survival and association analyses were performed using GEPIA and the colon adenocarcinoma dataset from The Cancer Genome Atlas database. GNG4-positive cells in a tissue microarray were examined using immunohistochemistry. According to the GNG4 expression data from Caucasian patients included in the TCGA dataset, GNG4 was highly expressed and positively associated with pathological stage and overall survival (OS) rates in colon cancer. GNG4 expression was higher in LCC than in RCC. Patients with LCC with high GNG4 expression exhibited higher pathological stage and lower survival rates, whereas this was not observed in patients with RCC. In addition, the clinical tissues used in the microarray showed that GNG4 expression was increased in Chinese patients with LCC compared with that in patients with RCC. Consistently, GNG4 expression was negatively associated with OS in patients with LCC, but not in patients with RCC. However, no association was observed between GNG4 expression and the disease stage of colon cancer in both patients with LCC and RCC. Overall, the molecular heterogeneity of GNG4 in LCC and RCC suggests that GNG4 may be used as a diagnostic and prognostic biomarker in patients with LCC.

A Pilot Integrative Analysis of Colonic Gene Expression, Gut Microbiota, and Immune Infiltration in Primary Sclerosing Cholangitis-Inflammatory Bowel Disease: Association of Disease With Bile Acid Pathways

BACKGROUND

Although a majority of patients with PSC have colitis [PSC-IBD; primary sclerosing cholangitis-inflammatory bowel disease], this is phenotypically different from ulcerative colitis [UC]. We sought to define further the pathophysiological differences between PSC-IBD and UC, by applying a comparative and integrative approach to colonic gene expression, gut microbiota and immune infiltration data.

METHODS

Colonic biopsies were collected from patients with PSC-IBD [n = 10], UC [n = 10], and healthy controls [HC; n = 10]. Shotgun RNA-sequencing for differentially expressed colonic mucosal genes [DEGs], 16S rRNA analysis for microbial profiling, and immunophenotyping were performed followed by multi-omic integration.

RESULTS

The colonic transcriptome differed significantly between groups [p = 0.01]. Colonic transcriptomes from HC were different from both UC [1343 DEGs] and PSC-IBD [4312 DEGs]. Of these genes, only 939 had shared differential gene expression in both UC and PSC-IBD compared with HC. Imputed pathways were predominantly associated with upregulation of immune response and microbial defense in both disease cohorts compared with HC. There were 1692 DEGs between PSC-IBD and UC. Bile acid signalling pathways were upregulated in PSC-IBD compared with UC [p = 0.02]. Microbiota profiles were different between the three groups [p = 0.01]; with inferred function in PSC-IBD also being consistent with dysregulation of bile acid metabolism. Th17 cells and IL17-producing CD4 cells were increased in both PSC-IBD and UC when compared with HC [p < 0.05]. Multi-omic integration revealed networks involved in bile acid homeostasis and cancer regulation in PSC-IBD.

CONCLUSIONS

Colonic transcriptomic and microbiota analysis in PSC-IBD point toward dysregulation of colonic bile acid homeostasis compared with UC. This highlights important mechanisms and suggests the possibility of novel approaches in treating PSC-IBD.

A novel prognostic model based on multi-omics features predicts the prognosis of colon cancer patients

Background

As a common malignant tumor in the colon, colon cancer (CC) has high incidence and recurrence rates. This study is designed to build a prognostic model for CC.

Methods

The gene expression dataset, microRNA‐seq dataset, copy number variation (CNV) dataset, DNA methylation dataset, and transcription factor (TF) dataset of CC were downloaded from UCSC Xena database. Using limma package, the differentially methylated genes (DMGs), and differentially expressed genes (DEGs) and miRNAs (DEMs) were identified. Based on random forest method, prognostic model for each omics dataset were constructed. After the omics features related to prognosis were selected using logrank test, the prognostic model based on multi‐omics features was built. Finally, the clinical phenotypes correlated with prognosis were screened using Kaplan–Meier survival analysis, and the nomogram model was established.

Results

There were 1625 DEGs, 268 DEMs, and 386 DMGs between the tumor and normal samples. A total of 105, 29, 159, five, and six genes/sites significantly correlated with prognosis were identified in the gene expression dataset (GABRD), miRNA‐seq dataset (miR‐1271), CNV dataset (RN7SKP247), DNA methylation dataset (cg09170112 methylation site [located in SFSWAP]), and TF dataset (SIX5), respectively. The prognostic model based on multi‐omics features was more effective than those based on single omics dataset. The number of lymph nodes, pathologic_M stage, and pathologic_T stage were the clinical phenotypes correlated with prognosis, based on which the nomogram model was constructed.

Conclusion

The prognostic model based on multi‐omics features and the nomogram model might be valuable for the prognostic prediction of CC.

Molecular Analyses of Left- and Right-Sided Tumors in Adolescents and Young Adults with Colorectal Cancer

BACKGROUND

The incidence of colorectal cancer (CRC), particularly left-sided tumors (LT), in adolescents and young adults (AYA) is rising. Epigenetic events appear to play an important role in tumorigenesis and cancer progression, especially in younger patients. We compared molecular features of LT to right-sided tumors (RT) in AYA.

MATERIALS AND METHODS

A total of 246 LT and 56 RT were identified in a cohort of 612 AYA with primary CRC. Tumors were examined by next-generation sequencing (NGS), protein expression, and gene amplification. Tumor mutational burden (TMB) and microsatellite instability (MSI) were determined based on NGS data.

RESULTS

RT showed higher mutation rates compared with LT in several genes including BRAF (10.3% vs. 2.8%), KRAS (64.1% vs. 45.5%), PIK3CA (27% vs. 11.2%), and RNF43 (24.2% vs. 2.9%). Notably, additional mutations in distinct genes involved in histone modification and chromatin remodeling, as well as genes associated with DNA repair and cancer-predisposing syndromes, were characteristic of RT; most frequently KMT2D (27.8% vs. 3.4%), ARID1A (53.3% vs. 21.4%), MSH6 (11.1% vs. 2.3%), MLH1 (10.5% vs. 2.3%), MSH2 (10.5% vs. 1.2%), POLE (5.9% vs. 0.6%), PTEN (10.8% vs. 2.3%), and BRCA1 (5.4% vs. 0.6%). MSI was seen in 20.8% of RT versus 4.8% of LT. RT had a higher frequency of TMB-high regardless of MSI status.

CONCLUSION

Molecular profiling of AYA CRC revealed different molecular characteristics in RT versus LT. Epigenetic mechanisms and alteration in DNA repair genes warrant further investigation and may be a promising treatment target for CRC in AYA.

IMPLICATIONS FOR PRACTICE

Colorectal cancer (CRC) in adolescents and young adults (AYA) comprises a distinct entity with different clinicopathologic features and prognosis compared with older patients. Molecular profiling of right- and left-sided tumors in AYA is needed to gain novel insight into CRC biology and to tailor targeted treatment in this age group. This study found that right- and left-sided CRC show distinct molecular features in AYA, overall and in subgroups based on microsatellite instability status. Alterations in DNA double-strand break repair and homologous recombination repair, as well as epigenetic mechanisms, appear to play a critical role. The present molecular profiling data may support the development of personalized treatment strategies in the AYA population.

Right and left-sided colon cancers - specificity of molecular mechanisms in tumorigenesis and progression

Background

Given the differences in embryonic origin, vascular and nervous supplies, microbiotic burden, and main physiological functions of left and right colons, tumor location is increasingly suggested to dictate tumor behavior affecting pathology, progression and prognosis. Right-sided colon cancers arise in the cecum, ascending colon, hepatic flexure and/or transverse colon, while left-sided colon cancers arise in the splenic flexure, descending, and/or sigmoid colon. In contrast to prior reports, we attempt to delineate programs of tumorigenesis independently for each side.

Methods

Four hundred and eleven samples were extracted from The Cancer Genome Atlas-COAD cohort, based on a conservative sample inclusion criterion. Each side was independently analyzed with respect to their respective normal tissue, at the level of transcription, post-transcription, miRNA control and methylation in both a stage specific and stage-agnostic manner.

Results

Our results indicate a suppression of enzymes involved in various stages of carcinogen breakdown including CYP2C8, CYP4F12, GSTA1, and UGT1A within right colon tumors. This implies its reduced capacity to detoxify carcinogens, contributing to a genotoxic tumor environment, and subsequently a more aggressive phenotype. Additionally, we highlight a crucial nexus between calcium homeostasis (sensing, mobilization and absorption) and immune/GPCR signaling within left-sided tumors, possibly contributing to its reduced proliferative and metastatic potential. Interestingly, two genes SLC6A4 and HOXB13 show opposing regulatory trends within right and left tumors. Post-transcriptional regulation mediated by both RNA-binding proteins (e.g. NKRF (in left) and MSI2 (in right)) and miRNAs (e.g. miR-29a (in left); miR-155, miR181-d, miR-576 and miR23a (in right)) appear to exhibit side-specificity in control of their target transcripts and is pronounced in right colon tumors. Additionally, methylation results depict location-specific differences, with increased hypomethylation in open seas within left tumors, and increased hypermethylation of CpG islands within right tumors.

Conclusions

Differences in molecular mechanisms captured here highlight distinctions in tumorigenesis and progression between left and right colon tumors, which will serve as the basis for future studies, influencing the efficacies of existing and future diagnostic, prognostic and therapeutic interventions.

Contribution of Immunoscore and Molecular Features to Survival Prediction in Stage III Colon Cancer

Background

The American Joint Committee on Cancer staging and other prognostic tools fail to account for stage-independent variability in outcome. We developed a prognostic classifier adding Immunoscore to clinicopathological and molecular features in patients with stage III colon cancer.

Methods

Patient (n = 559) data from the FOLFOX arm of adjuvant trial NCCTG N0147 were used to construct Cox models for predicting disease-free survival (DFS). Variables included age, sex, T stage, positive lymph nodes (+LNs), N stage, performance status, histologic grade, sidedness, KRAS/BRAF, mismatch repair, and Immunoscore (CD3⁺, CD8⁺ T-cell densities). After determining optimal functional form (continuous or categorical) and within Cox models, backward selection was performed to analyze all variables as candidate predictors. All statistical tests were two-sided.

Results

Poorer DFS was found for tumors that were T4 vs T3 (hazard ratio [HR] = 1.76, 95% confidence interval [CI] = 1.19 to 2.60; P = .004), right- vs left-sided (HR = 1.52, 95% CI = 1.14 to 2.04; P = .005), BRAF ^V600E (HR = 1.74, 95% CI = 1.26 to 2.40; P < .001), mutant KRAS (HR = 1.66, 95% CI = 1.08 to 2.55; P = .02), and low vs high Immunoscore (HR = 1.69, 95% CI = 1.22 to 2.33; P = .001) (all P < .02). Increasing numbers of +LNs and lower continuous Immunoscore were associated with poorer DFS that achieved significance (both Ps< .0001). After number of +LNs, T stage, and BRAF/KRAS, Immunoscore was the most informative predictor of DFS shown multivariately. Among T_1–3 N₁ tumors, Immunoscore was the only variable associated with DFS that achieved statistical significance. A nomogram was generated to determine the likelihood of being recurrence-free at 3 years.

Conclusions

The Immunoscore can enhance the accuracy of survival prediction among patients with stage III colon cancer.

Tumor-suppressive function and mechanism of HOXB13 in right-sided colon cancer

Right-sided colon cancer (RCC) and left-sided colon cancer (LCC) differ in their clinical and molecular features. An investigation of differentially expressed genes (DEGs) between RCC and LCC could contribute to targeted therapy for colon cancer, especially RCC, which has a poor prognosis. Here, we identified HOXB13, which was significantly less expressed in RCC than in LCC and associated with prognosis in RCC, by using 5 datasets from the Gene Expression Omnibus (GEO). Tissue sample analysis showed that HOXB13 was differentially expressed between normal and only RCC tumor tissues. HOXB13 inhibited colon cancer cell proliferation and induced apoptosis both in vitro and in vivo. Furthermore, we found that HOXB13 might be regulated by DNMT3B and suppress C-myc expression to exert antitumor effects via β-catenin/TCF4 signals in RCC. In conclusion, the current study is the first to demonstrate that HOXB13 has a tumor-suppressive effect in RCC. High expression levels of HOXB13 are associated with prolonged overall survival in patients with RCC. The DNMT3B-HOXB13-C-myc signaling axis might be a molecular target for the treatment of RCC.

Molecular Pathway Analysis Indicates a Distinct Metabolic Phenotype in Women With Right-Sided Colon Cancer

Colon cancer is the third most commonly diagnosed cancer in the United States. Recent reports have shown that the location of the primary tumor is of clinical importance. Patients with right-sided colon cancers (RCCs) (tumors arising between the cecum and proximal transverse colon) have poorer clinical outcomes than those with left-sided colon cancers (LCCs) (tumors arising between the distal transverse colon and sigmoid colon, excluding the rectum). Interestingly, women have a lower incidence of colon cancer than men, but have a higher propensity for RCC. The reason for this difference is not known; however, identification of sex-specific differences in gene expression by tumor anatomical location in the colon could provide further insight. Moreover, it could reveal important predictive markers for response to various treatments. This study provides a comprehensive bioinformatic analysis of various genes and molecular pathways that correlated with sex and anatomical location of colon cancers using four publicly available annotated data sets housed in the National Center for Biotechnology Information's Gene Expression Omnibus. We identified differentially expressed genes in tumor tissues from women with RCC, which showed attenuated energy and nutrient metabolism when compared with women with LCC. Specifically, we showed the downregulation of 5′ AMP-activated protein kinase alpha subunit (AMPKα) and anti-tumor immune responses in women with RCC. This difference was not seen when comparing tumor tissues from men with RCC to men with LCC. Therefore, women with RCC may have a specific metabolic and immune phenotype which accounts for differences in prognosis and treatment response.

Subtyping of microsatellite instability-high colorectal cancer

Background

Patients with microsatellite instability-high (MSI-H) colorectal cancer (CRC) generally have a better prognosis than patients with microsatellite stable (MSS) CRC. However, some MSI-H CRC patients do not gain overall survival benefits from immune checkpoint-blockade treatment. In other words, heterogeneity within the subgroup of MSI-H tumors remains poorly understood. Thus, an in-depth molecular characterization of MSI-H tumors is urgently required.

Methods

Here, we use nonnegative matrix factorization (NMF)-based consensus clustering to define CRC MSI-H subtypes in The Cancer Genome Atlas and a French multicenter cohort GSE39582. CIBERSORT was used to calculate the proportions of 22 lymphocytes in tumor tissue in MSI-H subtypes.

Results

MSI-H CRC samples basically clustered into two subgroups (MSI-H1 and MSI-H2). MSI-H1 was characterized by a lower BRAF mutational status, higher frequency of chromosomal instability, global hypomethylation, and worse survival than MSI-H2. Further examination of the immune landscape showed that macrophages of the M2 phenotype were enriched in MSI-H1, which may be associated with poor prognosis in this subgroup.

Conclusions

Our results illustrate the genetic heterogeneity in MSI-H CRCs and macrophages may serve as good targets for anticancer therapy in MSI-H1.

Graphical abstract

Electronic supplementary material

The online version of this article (10.1186/s12964-019-0397-4) contains supplementary material, which is available to authorized users.

Comparative proteogenomic analysis of right-sided colon cancer, left-sided colon cancer and rectal cancer reveals distinct mutational profiles

Right-sided colon cancer (RCC) has worse prognosis compared to left-sided colon cancer (LCC) and rectal cancer. The reason for this difference in outcomes is not well understood. We performed comparative somatic and proteomic analyses of RCC, LCC and rectal cancers to understand the unique molecular features of each tumor sub-types. Utilizing a novel in silico clonal evolution algorithm, we identified common tumor-initiating events involving APC, KRAS and TP53 genes in RCC, LCC and rectal cancers. However, the individual role-played by each event, their order in tumor development and selection of downstream somatic alterations were distinct in all three anatomical locations. Some similarities were noted between LCC and rectal cancer. Hotspot mutation analysis identified a nonsense mutation, APC R1450* specific to RCC. In addition, we discovered new significantly mutated genes at each tumor location, Further in silico proteomic analysis, developed by our group, found distinct central or hub proteins with unique interactomes among each location. Our study revealed significant differences between RCC, LCC and rectal cancers not only at somatic but also at proteomic level that may have therapeutic relevance in these highly complex and heterogeneous tumors.

Deciphering molecular properties of hypermutated gastrointestinal cancer

Great mutational heterogeneity is observed both across cancer types (>1000-fold) and within a given cancer type, with a fraction harboring >10 mutations per million bases, thus termed hypermutation. We determined the genome-wide effects of high mutation load on the transcriptome and methylome of two cancer types; namely, colorectal cancer (CRC) and stomach adenocarcinoma (STAD). Briefly, hierarchical clustering of the expression and methylation profiles showed that the majority of CRC and STAD hypermutated samples were mixed and separated from their respective non-hypermutated samples, exceeding the boundary of tissue specificity. Further in-detailed exploration uncovered that the underlying molecular mechanism may be related to the perturbation of chromatin remodeling genes.

Plasma metabolomic profiling distinguishes right-sided from left-sided colon cancer

BACKGROUND

Many studies have demonstrated that right-sided colon cancer (RCC) has a higher mortality rate and worse prognosis than left-sided colon cancer (LCC). However, the underlying biological mechanism that can account for these differences is unclear.

METHODS

In this study, plasma metabolic profiles in 147 LCC patients and 105 RCC patients were systematically analyzed by the ultra high performance liquid chromatography quadruple time-of-flight mass spectrometry (UHPLC-QTOF/MS) platform in conjunction with univariate and multivariate statistical analysis.

RESULTS

Metabolic signatures revealed considerable differences between patients with RCC and LCC, and clear separations were observed between the two groups in partial least-squares discriminant analysis score plots. In total, six metabolites were identified as potential metabolite markers for tumor location in RCC compared with LCC, including upregulated trimethylamine N-oxide and indoxyl sulfate, and downregulated anserine, L-targinine, gamma-glutamyl-gamma-aminobutyraldehyde and pyridoxal 5'-phosphate. These differences highlight that significant alternations occur in the pathways of methane metabolism, arginine and proline metabolism, histidine metabolism, beta-alanine metabolism and vitamin B6 metabolism in RCC compared with LCC.

CONCLUSIONS

Identified biomarkers and metabolic pathways may facilate our understanding of the different mortality rates and prognoses between RCC and LCC.