The Cancer Genome Atlas Colon Adenocarcinoma Research Articles

Exploration of bacterial lipopolysaccharide-related genes signature based on T cells for predicting prognosis in colorectal cancer.

The intratumoral microorganisms participates in the progression and immunotherapy of colorectal cancer (CRC). However, due to technical limitations, the impact of microorganisms on CRC has not been fully understood. Therefore, we conducted a systematic analysis of relationship between bacterial lipopolysaccharide (LPS)-associated genes and immune cells to explore new biomarkers for predicting the prognosis of CRC. The single-cell RNA sequencing data and the Comparative Toxicogenomics Database were used to screen T cells-associated LPS-related genes (TALRGs). Then, we established and validated the TALRGs risk signature in The Cancer Genome Atlas Colon Adenocarcinoma (TCGA-COAD) cohort and GSE39582 cohort. Besides, we compared the differences in tumor-infiltrating immune cell types, immunotherapeutic response, somatic mutation profiles, and tumor mutation burden (TMB) between high-risk group and low-risk group. In addition, the immunotherapeutic cohort (Imvigor210) treated with an anti-PD-L1 agent was performed to explore the potential value of the TALRGs signature on immunotherapy. Five prognostic TALRGs were identified and selected to build the prognostic model. The high-risk group had poor prognosis in both TCGA-COAD cohort (P < 0.0001) and GSE39582 cohort (P = 0.00019). The areas under the curves (AUCs) of TALRGs signature were calculated (TCGA-COAD cohort: 0.624 at 1 years, 0.639 at 3 years, 0.648 at 5 years; anti-PD-L1 cohort was 0.59). The high-risk group had advanced pathological stages and higher TMN stages in both TCGA-COAD cohort and GSE39582 cohort. The high-risk group had the higher infiltration of immunosuppressive cells, the expressions of immune checkpoint molecules, the IC50 values of chemotherapy drugs, and TP53 mutation rate (P < 0.05). In addition, patients with high TMB had worse prognosis (P < 0.05). Furthermore, the Imvigor210 also showed patients with high-risk scores had poor prognosis (platinum-treated cohort: P = 0.0032; non-platinum-treated cohort: P = 0.00017). Microorganisms are closely related to the tumor microenvironment to influence the progression and immune response of CRC via stimulating T cells through LPS-related genes. The TALRGs signature contributed to predict the prognosis and immunotherapy of CRC, and became new therapeutic targets and biomarkers of CRC.

Identification of differentially expressed genes and splicing events in early-onset colorectal cancer.

The incidence of colorectal cancer (CRC) has been steadily increasing in younger individuals over the past several decades for reasons that are incompletely defined. Identifying differences in gene expression profiles, or transcriptomes, in early-onset colorectal cancer (EOCRC, < 50 years old) patients versus later-onset colorectal cancer (LOCRC, > 50 years old) patients is one approach to understanding molecular and genetic features that distinguish EOCRC. We performed RNA-sequencing (RNA-seq) to characterize the transcriptomes of patient-matched tumors and adjacent, uninvolved (normal) colonic segments from EOCRC (n=21) and LOCRC (n=22) patients. The EOCRC and LOCRC cohorts were matched for demographic and clinical characteristics. We used The Cancer Genome Atlas Colon Adenocarcinoma (TCGA-COAD) database for validation. We used a series of computational and bioinformatic tools to identify EOCRC-specific differentially expressed genes, molecular pathways, predicted cell populations, differential gene splicing events, and predicted neoantigens. We identified an eight-gene signature in EOCRC comprised of ALDOB, FBXL16, IL1RN, MSLN, RAC3, SLC38A11, WBSCR27 and WNT11, from which we developed a score predictive of overall CRC patient survival. On the entire set of genes identified in normal tissues and tumors, cell type deconvolution analysis predicted a differential abundance of immune and non-immune populations in EOCRC versus LOCRC. Gene set enrichment analysis identified increased expression of splicing machinery in EOCRC. We further found differences in alternative splicing (AS) events, including one within the long non-coding RNA, HOTAIRM1. Additional analysis of AS found seven events specific to EOCRC that encode potential neoantigens. Our transcriptome analyses identified genetic and molecular features specific to EOCRC which may inform future screening, development of prognostic indicators, and novel drug targets.

Abstract 3496: EpigenPlot: A tool for the gene-level methylation analysis of colorectal tumors

Abstract Introduction. Aberrant DNA methylation patterns are frequent in colorectal adenocarcinoma (CRC) tissues. The investigation of this layer of epigenetic regulation holds the promise of a better understanding of tumour progression and the identification of novel biomarker candidates. Purpose. Our goal was to collect and analyse publicly available DNA methylation data of colorectal samples and create a user-friendly tool for exploring and visualizing the CRC methylome. Methods. We used Illumina Infinium Methylation Arrays, which is a popular platform for genome-wide methylation analysis of large cohorts. Gene Expression Omnibus database (GEO) and TCGA-COAD (The Cancer Genome Atlas Colon Adenocarcinoma) datasets including normal colorectal mucosa, adenoma, and adenocarcinoma samples were systematically collected and filtered. Differentially methylated regions were identified using the Kruskal-Wallis test. Genes with significant methylation changes were further analysed using ROC (Receiver Operator Characteristic) analysis. Finally, we established a web application using the shiny R package. Results. We assembled a database including methylation data of 2,586 samples. Adenoma and adenocarcinoma samples were globally hypomethylated. Hypermethylation (p &amp;lt; 0.05, Δβ &amp;gt;= 0.2) in adenocarcinoma samples was predominantly present in regions near proximal promoters. Out of the 74 previously proposed biomarkers examined, 50 had a cross-validated AUC of over 0.8. FDA-approved biomarkers BMP3, NDRG4, and SEPT9 have shown the highest performance in the TSS200 region (cvAUC = 0.8, 0.83, and 0.76, respectively). Genes with the highest performance were ITGA4 (5’UTR, first exon: cvAUC = 0.9), MDFI (5’UTR: cvAUC = 0.9), CNRIP1 (5’UTR, first exon: cvAUC = 0.89). The established web application can visualize methylation at CpG sites and gene regions, and KEGG pathway genes. The platform is available at https://epigenplot.com. Conclusion. We collected and analysed a sizeable database of colorectal tissue data. Gene regions with the best performance include previously proposed and novel diagnostic biomarker candidates. The web platform provides an tool for the efficient exploration of the assembled data. Citation Format: Dalma Müller, Balazs Gyorffy. EpigenPlot: A tool for the gene-level methylation analysis of colorectal tumors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3496.

Unraveling the MicroRNA tapestry: exploring the molecular dynamics of locoregional recurrent rectal cancer.

Colorectal cancer (CRC) ranks as the third most prevalent malignancy globally, with a concerning rise in incidence among young adults. Despite progress in understanding genetic predispositions and lifestyle risk factors, the intricate molecular mechanisms of CRC demand exploration. MicroRNAs (miRNAs) emerge as key regulators of gene expression and their deregulation in tumor cells play pivotal roles in cancer progression. NanoString's nCounter technology was utilized to measure the expression of 827 cancer-related miRNAs in tumor tissue and adjacent non-involved normal colon tissue from five patients with locoregional CRC progression. These expression profiles were then compared to those from the primary colon adenocarcinoma (COAD) cohort in The Cancer Genome Atlas (TCGA). Intriguingly, 156 miRNAs showed a contrasting dysregulation pattern in reccurent tumor compared to their expression in the TCGA COAD cohort. This observation implies dynamic alterations in miRNA expression patterns throughout disease progression. Our exploratory study contributes to understanding the regulatory landscape of recurrent CRC, emphasizing the role of miRNAs in disease relapse. Notable findings include the prominence of let-7 miRNA family, dysregulation of key target genes, and dynamic changes in miRNA expression patterns during progression. Univariate Cox proportional hazard models highlighted miRNAs associated with adverse outcomes and potential protective factors. The study underscores the need for more extensive investigations into miRNA dynamics during tumor progression and the value of stage specific biomarkers for prognosis.

A Ferroptosis-Related lncRNAs Signature Predicts Prognosis of Colon Adenocarcinoma.

(1) Ferroptosis is a type of cellular death caused by lipid-dependent iron peroxide, which plays a major role in cancer. Long noncoding RNAs (lncRNAs) are increasingly recognized as key regulating substances in ferroptosis; (2) RNA sequencing expressions and clinical data of 519 patients with colon adenocarcinoma (COAD) were downloaded from The Cancer Genome Atlas (TCGA) database. The expression levels of lncRNAs related to ferroptosis were screened with Pearson correlation analysis. Differential genes were enriched with Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. LncRNAs related to ferroptosis were determined with univariate Cox regression and multivariate Cox regression analyses, and patients with COAD were classified into high- and low-risk subgroups according to their median risk score. The prognostic value was further examined, and the association between ferroptosis-related lncRNAs (frlncRNAs) and survival in patients with high and low risks of COAD was validated. A TCGA-COAD data set was used for receiver operating characteristic (ROC) analysis and detrended correspondence analysis (DCA) to assess prediction accuracy. Finally, a nomogram was constructed to predict survival probability; (3) We obtained a model consisting of a five-frlncRNAs signature comprising AP003555.1, AP001469.3, ITGB1-DT, AC129492.1, and AC010973.2 for determining the overall survival (OS) of patients with COAD. The survival analysis and ROC curves showed that the model had good robustness and predictive performance on the TCGA training set; (4) We found that a five-frlncRNAs signature may play a potential role in anti-COAD immunity. Risk characteristics based on frlncRNAs can accurately predict the prognosis and immunotherapy response of patients with COAD.

Development of a 5-mRNAsi-related gene signature to predict the prognosis of colon adenocarcinoma.

To create a prognosis model based on mRNA-based stem index (mRNAsi) for evaluating the prognostic outcomes of colon adenocarcinoma (COAD). Generation of heterogeneous COAD cells could be promoted by the self-renewal and differentiation potential of cancer stem cells (CSCs). Biomarkers contributing to the development of COAD stem cells remained to be discovered. To develop and validate an mRNAsi-based risk model for estimating the prognostic outcomes of patients suffering from COAD. Samples were collected from Rectal Adenocarcinoma (TCGA-READ) PanCancer Atlas datasets, The Cancer Genome Atlas Colon Adenocarcinoma (TCGA-COAD), and the GSE87211 dataset. MRNAsi was calculated by one-class logistic regression (OCLR) algorithm. Under the criterion of correlation greater than 0.4, genes related to mRNAsi were screened and clustered. Meanwhile, differentially expressed genes (DEGs) between molecular subtypes were identified to establish a risk model. According to the median risk score value for immunotherapy and results from immune cell infiltration and clinicopathological analyses, clusters and patients were divided into high-RiskScore and low-RiskScore groups. Cell apoptosis and viability were detected by flow cytometer and Cell Counting Kit-8 (CCK-8) assay, respectively. A negative correlation between mRNAsi and clinical stages was observed. Three clusters of patients (C1, C2, and C3) were defined based on a total of 165 survival-related mRNAsi genes. Specifically, C1 patients had greater immune cell infiltration and a poorer prognosis. A 5-mRNAsi-gene signature (HEYL, FSTL3, FABP4, ADAM8, and EBF4) served as a prediction index for COAD prognosis. High-RiskScore patients had a poorer prognosis and higher level of immune cell infiltration. In addition, the five genes in the signature all showed a high expression in COAD cells. Knocking down HEYL promoted COAD cell apoptosis and inhibited viability. Our mRNAsi risk model could better predict the prognosis of COAD patients.

Spatially aware graph neural networks and cross-level molecular profile prediction in colon cancer histopathology: a retrospective multi-cohort study

Digital whole-slide images are a unique way to assess the spatial context of the cancer microenvironment. Exploring these spatial characteristics will enable us to better identify cross-level molecular markers that could deepen our understanding of cancer biology and related patient outcomes. We proposed a graph neural network approach that emphasises spatialisation of tumour tiles towards a comprehensive evaluation of predicting cross-level molecular profiles of genetic mutations, copy number alterations, and functional protein expressions from whole-slide images. We introduced a transformation strategy that converts whole-slide image scans into graph-structured data to address the spatial heterogeneity of colon cancer. We developed and assessed the performance of the model on The Cancer Genome Atlas colon adenocarcinoma (TCGA-COAD) and validated it on two external datasets (ie, The Cancer Genome Atlas rectum adenocarcinoma [TCGA-READ] and Clinical Proteomic Tumor Analysis Consortium colon adenocarcinoma [CPTAC-COAD]). We also predicted microsatellite instability and result interpretability. The model was developed on 459 colon tumour whole-slide images from TCGA-COAD, and externally validated on 165 rectum tumour whole-slide images from TCGA-READ and 161 colon tumour whole-slide images from CPTAC-COAD. For TCGA cohorts, our method accurately predicted the molecular classes of the gene mutations (area under the curve [AUCs] from 82·54 [95% CI 77·41-87·14] to 87·08 [83·28-90·82] on TCGA-COAD, and AUCs from 70·46 [61·37-79·61] to 81·80 [72·20-89·70] on TCGA-READ), along with genes with copy number alterations (AUCs from 81·98 [73·34-89·68] to 90·55 [86·02-94·89] on TCGA-COAD, and AUCs from 62·05 [48·94-73·46] to 76·48 [64·78-86·71] on TCGA-READ), microsatellite instability (MSI) status classification (AUC 83·92 [77·41-87·59] on TCGA-COAD, and AUC 61·28 [53·28-67·93] on TCGA-READ), and protein expressions (AUCs from 85·57 [81·16-89·44] to 89·64 [86·29-93·19] on TCGA-COAD, and AUCs from 51·77 [42·53-61·83] to 59·79 [50·79-68·57] on TCGA-READ). For the CPTAC-COAD cohort, our model predicted a panel of gene mutations with AUC values from 63·74 (95% CI 52·92-75·37) to 82·90 (73·69-90·71), genes with copy number alterations with AUC values from 62·39 (51·37-73·76) to 86·08 (79·67-91·74), and MSI status prediction with AUC value of 73·15 (63·21-83·13). We showed that spatially connected graph models enable molecular profile predictions in colon cancer and are generalised to rectum cancer. After further validation, our method could be used to infer the prognostic value of multiscale molecular biomarkers and identify targeted therapies for patients with colon cancer. This research has been partially funded by ARO MURI 805491, NSF IIS-1793883, NSF CNS-1747778, NSF IIS 1763523, DOD-ARO ACC-W911NF, and NSF OIA-2040638 to Dimitri N Metaxas.

High Expression of ATP6V1C2 Predicts Unfavorable Overall Survival in Patients With Colon Adenocarcinoma.

Aims: Colon adenocarcinoma (COAD) is responsible for 90% of all colorectal cancer cases and is one of the most common causes of cancer-related deaths worldwide. ATP6V1s (cytosolic V1 domain of vacuolar adenosine triphosphatase) participate in the biological process of transporting hydrogen ions and are implicated in tumor growth and metastasis. ATP6V1C2 as a family member has been documented to associate with esophageal carcinoma and renal clear cell carcinoma, while its roles in COAD remain elusive. Methods: The expression status, potential molecular mechanism, and prognostic value of ATP6V1C2 in COAD were investigated using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. In addition, its biological roles in COAD were explored through in vitro studies. Results: ATP6V1C2 showed a significantly higher expression level in COAD compared with matched non-cancerous tissues. High expression of ATP6V1C2 predicted a shorter overall survival both in TCGA and GEO COAD datasets, and ATP6V1C2 was identified as an independent factor associated with overall survival in COAD. Bioinformatic analyses showed that high expression of ATP6V1C2 was associated with high epithelial–mesenchymal transition (EMT) score and Wnt signaling pathway was significantly enriched from differentially expressed genes between ATP6V1C2-high and -low group. We also found that high expression of ATP6V1C2 could decrease pathway activity of CD8 T effector implicated in tumor microenvironment (TME). In vitro study revealed that ATP6V1C2 knockdown resulted in aberrant expression of Wnt- and EMT-related genes and inhibited COAD cell proliferation and growth. Conclusion: This is the first study to reveal the molecular functions of ATP6V1C2 in COAD. Our study suggests that overexpressed ATP6V1C2 might promote EMT by activating Wnt signaling pathway, resulting in cancer metastasis and poor prognosis. This study paves the way for understanding potential molecular mechanisms and therapeutic perspectives in COAD.

Cancer-Associated Stromal Fibroblast-Derived Transcriptomes Predict Poor Clinical Outcomes and Immunosuppression in Colon Cancer.

Background: Previous studies revealed that colonic cancer-associated fibroblasts (CAFs) are associated with the modulation of the colon tumor microenvironment (TME). However, identification of key transcriptomes and their correlations with the survival prognosis, immunosuppression, tumor progression, and metastasis in colon cancer remains lacking. Methods: We used the GSE46824, GSE70468, GSE17536, GSE35602, and the cancer genome atlas (TCGA) colon adenocarcinoma (COAD) datasets for this study. We identified the differentially expressed genes (DEGs), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, hub genes, and survival-associated genes in colon cancer. Finally, we investigated the correlation of key genes with the survival prognosis, immunosuppression, and metastasis. Results: We identified 246 common DEGs between the GSE46824 and GSE70468 datasets of colonic CAFs, which included 72 upregulated and 174 downregulated genes. The upregulated pathways are mainly involved with cancers and cellular signaling, and downregulated pathways are involved with immune regulation and cellular metabolism. The search tool for the retrieval of interacting genes (STRING)-based analysis identified 15 hub genes and 9 significant clusters in colonic CAFs. The upregulation of CTHRC1, PDGFC, PDLIM3, NTM, and SLC16A3 and downregulation of FBN2 are correlated with a shorter survival time in colon cancer. The CTHRC1, PDGFC, PDLIM3, and NTM genes are positively correlated with the infiltration of tumor-associated macrophages (TAM), macrophages, M2 macrophages, the regulatory T cells (Tregs), T cell exhaustion, and myeloid-derived suppressor cells (MDSCs), indicating the immunosuppressive roles of these transcriptomes in colon cancer. Moreover, the CTHRC1, PDGFC, PDLIM3, NTM, and SLC16A3 genes are gradually increased from normal tissue to the tumor and tumor to the metastatic tumor, and FBN2 showed the reverse pattern. Furthermore, the CTHRC1, FBN2, PDGFC, PDLIM3, and NTM genes are positively correlated with the metastatic scores in colon cancer. Then, we revealed that the expression value of CTHRC1, FBN2, PDGFC, PDLIM3, NTM, and SLC16A3 showed the diagnostic efficacy in colonic CAFs. Finally, the expression level of CTHRC1, PDGFC, and NTM genes are consistently altered in colon tumor stroma as well as in the higher CAFs-group of TCGA COAD patients. Conclusion: The identified colonic CAFs-derived key genes are positively correlated with survival prognosis, immunosuppression, tumor progression, and metastasis.

Relationship between ATOH1 and tumor microenvironment in colon adenocarcinoma patients with different microsatellite instability status

BackgroundColon adenocarcinoma (COAD) is one of the major varieties of malignant tumors threatening human health today. Immune checkpoint inhibitors (ICIs) have recently begun to emerge as an effective option for the treatment of COAD patients, but not all patients can benefit from ICI treatment. Previous studies have suggested that ICIs boast significant clinical effects on patients with microsatellite instability-high (MSI-H), while conversely patients with microsatellite-stable/microsatellite instability-low (MSS/MSI-L) have shown limited response.MethodsWe used ATAC-seq, RNA-seq, and mutation data from The Cancer Genome Atlas Colon adenocarcinoma (TCGA-COAD) cohort to perform multi-omics differential analysis on COAD samples with different MSI statuses, then further screened genes by additionally combining these results with survival analysis. We analyzed the effects of the screened genes on the tumor microenvironment and immunogenicity of COAD patients, and subsequently determined their influence on the efficacy of ICIs in COAD patients using a series of predictive indexes.ResultsTwelve genes were screened in the TCGA-COAD cohort, and after the combined survival analysis, we identified ATOH1 as having significant effects. ATOH1 is characterized by high chromatin accessibility, high expression, and high mutation in COAD patients in the MSI-H group. COAD patients with high ATOH1 expression are associated with a better prognosis, unique immune microenvironment, and higher efficacy in ICI treatment. Enrichment analysis showed that COAD patients with high ATOH1 expression displayed significant upregulation in their humoral immunity and other related pathways.ConclusionsWe speculate that ATOH1 may influence the efficacy of ICIs therapy in patients with COAD by affecting the immune microenvironment and immunogenicity of the tumor.

Изоформы микроРНК miR-148a и miR-203a предположительно играют роль супрессоров колоректального рака

MicroRNAs are short non-coding molecules which regulate translation in a gene-specific manner. MicroRNA isoforms that differ by few extra or missing nucleotides at the 5'-terminus (5'-isomiR) show strikingly different target specificity. This study aimed to identify functional roles of 5′-isomiR in colorectal cancers. Transcriptomic targets of microRNA isoforms were predicted using bioinformatics tools miRDB and TargetScan. The sets of putative targets identified for 5′-isomiR were integrated with mRNA and microRNA sequencing data for primary colorectal tumors retrieved from The Cancer Genome Atlas Colon Adenocarcinoma (TCGA-COAD) database. The network of interactions among miRNA, their targets and transcription factors was built using the miRGTF-net algorithm. The results indicate that microRNA isoforms highly expressed in colorectal cancer and differing by a single nucleotide position at the 5'-terminus have ≤ 30% common targets. The regulatory network of interactions enables identification of the most engaged microRNA isoforms. Anti-correlated expression levels of canonical microRNA hsa-miR-148a-3p and its putative targets including CSF1, ETS1, FLT1, ITGA5, MEIS1, MITF and RUNX2 proliferation regulators suggest an anti-tumor role for this molecule. The canonical microRNA hsa-miR-203a-3p|0 and its 5′-isoform bind different sets of anti-correlated putative targets, although both of them interact with genes involved in the epithelial-mesenchymal transition: SNAI2 and TNC.

ECM-Receptor Regulatory Network and Its Prognostic Role in Colorectal Cancer.

Interactions of the extracellular matrix (ECM) and cellular receptors constitute one of the crucial pathways involved in colorectal cancer progression and metastasis. With the use of bioinformatics analysis, we comprehensively evaluated the prognostic information concentrated in the genes from this pathway. First, we constructed a ECM–receptor regulatory network by integrating the transcription factor (TF) and 5’-isomiR interaction databases with mRNA/miRNA-seq data from The Cancer Genome Atlas Colon Adenocarcinoma (TCGA-COAD). Notably, one-third of interactions mediated by 5’-isomiRs was represented by noncanonical isomiRs (isomiRs, whose 5’-end sequence did not match with the canonical miRBase version). Then, exhaustive search-based feature selection was used to fit prognostic signatures composed of nodes from the network for overall survival prediction. Two reliable prognostic signatures were identified and validated on the independent The Cancer Genome Atlas Rectum Adenocarcinoma (TCGA-READ) cohort. The first signature was made up by six genes, directly involved in ECM–receptor interaction: AGRN, DAG1, FN1, ITGA5, THBS3, and TNC (concordance index 0.61, logrank test p = 0.0164, 3-years ROC AUC = 0.68). The second hybrid signature was composed of three regulators: hsa-miR-32-5p, NR1H2, and SNAI1 (concordance index 0.64, logrank test p = 0.0229, 3-years ROC AUC = 0.71). While hsa-miR-32-5p exclusively regulated ECM-related genes (COL1A2 and ITGA5), NR1H2 and SNAI1 also targeted other pathways (adhesion, cell cycle, and cell division). Concordant distributions of the respective risk scores across four stages of colorectal cancer and adjacent normal mucosa additionally confirmed reliability of the models.

USH2A Mutation is Associated With Tumor Mutation Burden and Antitumor Immunity in Patients With Colon Adenocarcinoma.

Colon adenocarcinoma (COAD) is one of the diseases with the highest morbidity and mortality in the world. At present, immunotherapy has become a valuable method for the treatment of COAD. Tumor mutational burden (TMB) is considered to be the most common biomarker for predicting immunotherapy. According to reports, the mutation rate of COAD ranks third. However, whether these gene mutations are related to TMB and immune response is still unknown. Here, COAD somatic mutation data were downloaded from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases. Bioinformatics methods were used to study the relationships among gene mutations, COAD survival prognosis, and tumor immune response. A total of 22 of the top 40 mutations in TCGA and ICGC databases were the same. Among them, the USH2A mutation was associated with high TMB and poor clinical prognosis. According to Gene Set Enrichment Analysis (GSEA) and the CIBERSORT algorithm, we determined that the USH2A mutation upregulates signaling pathways involved in the immune system and the antitumor immune response. In cases with a USH2A mutation, the immune score and MSI score of TCGA samples increased, the expression of immune checkpoint genes decreased significantly, and the TIDE score decreased significantly. Dependent on the presence or absence of a USH2A mutation, TCGA COAD samples were analyzed for differentially expressed genes, 522 of which were identified. Using a univariate Cox analysis and LASSO COX analysis of these differential genes, a prediction model was established, which established significant differences in the infiltration of immune cells, immune checkpoint gene expression, immune score, MSI score, TMB, and TIDE in patients in high- and low-risk groups. In conclusion, mutation of USH2A is frequent in COAD and is related to an increase in TMB and the antitumor immunity. The differential genes screened by USH2A mutation allowed the construction of a risk model for predicting the survival and prognosis of cancer patients, in addition to providing new ideas for COAD immunotherapy.

Pilot Nanostring PanCancer pathway analysis of colon adenocarcinoma in a tertiary healthcare centre in Kerala, India.

The prevalence of microsatellite instability and deoxyribonucleic acid mismatch repair deficiency in colorectal adenocarcinoma (CRC) cases is higher in India compared to western populations. No major study on the molecular pathogenesis is currently available in the Indian population. We conducted a pilot study to explore the differences in molecular pathogenesis of microsatellite stable (MSS) and microsatellite unstable CRC from a tertiary care centre in Kerala, South India. Using Nanostring PanCancer panel assay in Stage II colorectal adenocarcinoma, tumour tissues (n = 11) were compared against normal colon tissues (n = 4). Differentially expressed (DE) genes were identified and super-imposed onto colon adenocarcinoma cohort of The Cancer Genome Atlas (TCGA) data (TCGA Colon Adenocarcinoma (TCGA COAD)), from the Genome Expression Profiling Interactive Analysis and Tumor Immune Estimation Resource (TIMER) to compare the gene associations. Significant DE genes were 59 out of 730 (false discovery rate adj. p-value < 0.05), 18 of which had a fold-change |FC(log2)| ≥ 2. On superimposition to TCGA COAD, 33 genes were significant in both TCGA and current study. ETV4 was expressed significantly higher in MSS with no immune cell infiltration. Other significant DE genes with high FC(log2), unique to the study were INHBA, COL1A1, COL11A1, COMP, SFRP4 and SPP1, which were clustered in STRING network analysis and correlated with tumour-infiltrating immune cells in TIMER, suggesting a specific interaction pathway. The preliminary study suggests a distinct pathogenesis of MSS CRC involving ETV4 in the Indian population and warrants further clinically extensive and high-dimensional expression studies.

Low expression of CD24 is associated with poor survival in colorectal cancer

In this study we analyzed expression of CD24 in a cohort of colorectal cancer patients using immunohistochemistry staining of CD24. We found a significant association between absence or low expression of CD24 (10% of membranous and 55% of cytoplasmic staining) and shortened patient survival. Protein localization played a crucial role in the prognosis: membranous form was the major and prognostic one in primary tumors, while cytoplasmic expression was elevated in liver metastases compared to the primary tumors and contained prognostic information. Then, using The Cancer Genome Atlas Colon Adenocarcinoma (TCGA-COAD) RNA-seq data, we showed that CD24 mRNA level was two-fold decreased in primary colorectal cancers compared to adjacent normal mucosa. Like the protein staining data, ten percent of patients with the lowest mRNA expression levels of CD24 in primary tumors had reduced survival compared to the ones with higher expression. To explain these findings mechanistically, shRNA-mediated CD24 knockdown was performed in HT-29 colorectal cancer cells. It resulted in the increase of cell migration in vitro, no changes in proliferation and apoptosis, and a slight decrease in cell invasion. As increased cell migration is a hallmark of metastasis formation, this finding corroborates the association of a decreased CD24 expression with poor prognosis. Differential gene expression analysis revealed upregulation of genes involved in cell migration in the group of patients with low CD24 expression, including integrin subunit α3 and α3, β3 subunits of laminin 332. Further co-expression analysis identified SPI1, STAT1 and IRF1 transcription factors as putative master-regulators in this group.

Clinical Impact of X-Ray Repair Cross-Complementary 1 (XRCC1) and the Immune Environment in Colorectal Adenoma-Carcinoma Pathway Progression.

PurposeColorectal cancer (CRC) can develop via a hypermutagenic pathway characterized by frequent somatic DNA base-pair mutations. Alternatively, the immunogenicity of tumor cells themselves may influence the anticancer activity of the immune effector cells. Impaired DNA repair mechanisms drive mutagenicity, which then increase the neoantigen load and immunogenicity. However, no studies have analyzed immune checkpoint protein expression, particularly programmed death-1 (PD-1)/programmed death-ligand 1 (PD-L1), in adenoma–carcinoma progression and its relationship with the emergence of other DNA repair gene mutation.Materials and MethodsWe investigated mutations of 10 genes involved in DNA repair function: XRCC1, TP53, MLH1, MSH, KRAS, GSTP, UMP, MTHF, DPYD, and ABCC2. We performed sequencing to determine mutations and immunohistochemistry of immune checkpoints in clinical samples and determined changes in XRCC1 expression during progression through the adenoma–carcinoma pathway. We further investigated the prognostic associations of gene XRCC1 according to the expression, mutational profile, and immune profile using The Cancer Genome Atlas-colon adenocarcinoma (TCGA-COAD) dataset.ResultsFrom clinical samples, XRCC1 mutation demonstrated the strongest association with adenomas with a mutation frequency of 56.2% in adenomas and 34% in CRCs (p =0.016). XRCC1 was abnormally expressed and altered by mutations contributing to adenoma carcinogenesis. High expression of XRCC1, CD4, FOXP3, and PD-1/PD-L1 showed an overall upward trend with increased lesion severity (all p < 0.01). PD-1/PD-L1 expression and CD4+ intraepithelial lymphocytes (IELs) correlated with cytological dysplasia progression, specifically in patients with wild-type XRCC1 (all p < 0.01), whereas FOXP3 expression was independently associated with adenoma–carcinoma progression. From TCGA-COAD analysis, XRCC1 expression was associated with patients survival, tumor-infiltrating lymphocytes and immune marker expression.ConclusionIncreased IEL density and PD-1/PD-L1 expression correlate with cytological dysplasia progression and specifically with the XRCC1 mutation status in CRC. Our findings support a stepwise dysplasia-carcinoma sequence of adenoma carcinogenesis and an XRCC1 hypermutated phenotypic mechanism of lesions.

Controlling for cellular heterogeneity using single-cell deconvolution of gene expression reveals novel markers of colorectal tumors exhibiting microsatellite instability.

Approximately 15% of colorectal cancer (CRC) cases present with high levels of microsatellite instability (MSI-H). Bulk RNA-sequencing approaches have been employed to elucidate transcriptional differences between MSI-H and microsatellite stable (MSS) CRC tumors. These approaches are frequently confounded by the complex cellular heterogeneity of tumors. We performed single-cell deconvolution of bulk RNA-sequencing on The Cancer Genome Atlas colon adenocarcinoma (TCGA-COAD) dataset. Cell composition within each dataset was estimated using CIBERSORTx. Cell composition differences were analyzed using linear regression. Significant differences in abundance were observed for 13 of 19 cell types between MSI-H and MSS/MSI-L tumors in TCGA-COAD. This included a novel finding of increased enteroendocrine (q = 3.71E-06) and reduced colonocyte populations (q = 2.21E-03) in MSI-H versus MSS/MSI-L tumors. We were able to validate some of these differences in an independent biopsy dataset. By incorporating cell composition into our regression model, we identified 3,193 differentially expressed genes (q = 0.05), of which 556 were deemed novel. We subsequently validated many of these genes in an independent dataset of colon cancer cell lines. In summary, we show that some of the challenges associated with cellular heterogeneity can be overcome using single-cell deconvolution, and through our analysis we highlight several novel gene targets for further investigation.

Improving the Prognosis of Colon Cancer through Knowledge-Based Clinical-Molecular Integrated Analysis.

Background Colon cancer has high morbidity and mortality rates among cancers. Existing clinical staging systems cannot accurately assess the prognostic risk of colon cancer patients. This study was aimed at improving the prognostic performance of the colon cancer clinical staging system through knowledge-based clinical-molecular integrated analysis. Methods 374 samples from The Cancer Genome Atlas Colon Adenocarcinoma (TCGA-COAD) dataset were used as the discovery set. 98 samples from the Clinical Proteomic Tumor Analysis Consortium (CPTAC) dataset were used as the validation set. After converting gene expression data into pathway dysregulation scores (PDSs), the random survival forest and Cox model were used to identify the best prognostic supplementary factors. The corresponding clinical-molecular integrated prognostic model was built, and the improvement of prognostic performance was assessed by comparing with the clinical prognostic model. Results The PDS of 14 pathways played important roles in prognostic prediction together with clinical prognostic factors through the random survival forest. Further screening with the Cox model revealed that the PDS of the pathway hsa00532 was the best clinical prognostic supplementary factor. The integrated prognostic model constructed with clinical factors and the identified molecular factor was superior to the clinical prognostic model in discriminative performance. Kaplan-Meier (KM) curves of patients grouped by PDS suggested that patients with a higher PDS had a poorer prognosis, and stage II patients could be distinctly distinguished. Conclusions Based on the knowledge-based clinical-molecular integrated analysis, a clinical-molecular integrated prognostic model and corresponding nomogram for colon cancer overall survival prognosis was built, which showed better prognostic performance than the clinical prognostic model. The PDS of the pathway hsa00532 is a considerable clinical prognostic supplementary factor for colon cancer and may represent a potential prognostic marker for stage II colon cancer. The PDS calculation involves only 16 genes, which supports its potential for clinical application.

Single-Cell Atlas of Infiltrating B Cells and Their Clinical Outcomes in Colorectal Cancer

Background: B cells constitute a major component of infiltrating immune cells in colorectal cancer (CRC). However, the characterization of B cells and their clinical significance remain unclear. Methods: We performed single-cell RNA sequencing to identify the features of B cells in the CRC tumor microenvironment (TME), and validated these findings using flow cytometry and multicolor immunofluorescence staining experiments. B cell-related cellular interactions within the TME were estimated using CellChat and in vitro chemotaxis assay. We then derived gene signatures to construct TME compositions for The Cancer Genome Atlas Colon Adenocarcinoma (TCGA-COAD) dataset using the single sample gene set enrichment analysis (ssGSEA) method and unsupervised consensus clustering analysis was employed to identify four colon immune classes (CICs). Finally, we reviewed the landscape of gene mutations across these four CICs. Findings: We identified five distinct subtypes of B cells with their marker genes, distribution patterns, and functional properties in the CRC TME. We found an increased ratio of IgG/IgA plasma cells in tumor sites compared with adjacent normal mucosal tissue. In addition, the CXCL13-producing CD8+ T cells in the tumor tissue could recruit tertiary lymphoid structure (TLS) B cells and CCL28-CCR10 axis are pivotal for IgG plasma cell migration to the intratumor tissue. Finally, we identified four distinct CICs (CIC: A–D) and found that CD20+ B cells within TLS were enriched in one immune-inflamed or hot tumor group (CIC-D). This B cell-rich group, characterized by strong antigen presentation, IgG plasma cell accumulation, microsatellite instability-high (MSI-H) and high tumor mutation burden (TMB-H), as well as immunosuppressive property in particular, might become a potential predictive biomarker for future immunotherapy. Interpretation: Our analysis provides deep insight into infiltrating B cells and their potential clinical implications for immunotherapy in colorectal cancer. Funding Information: This study was financially supported by project grants from the Medical System of Shanghai Minhang District (grant number 2020MWDXK02). Declaration of Interests: The authors declare no competing interests. Ethics Approval Statement: This study was approved by the Ethical Committee of The Fifth People’s Hospital of Shanghai, Fudan University. All animal experiment were conducted under the approved protocol Guidelines for the Care and Use of Laboratory Animals.

GABRD promotes progression and predicts poor prognosis in colorectal cancer.

Little is known about the functional roles of gamma-aminobutyric acid type A receptor subunit delta (GABRD) in colorectal cancer (CRC). The expression of GABRD between CRCs and adjacent normal tissues (NTs), metastasis and primary tumors was compared using public transcriptomic datasets. A tissue microarray and immunohistochemical staining (IHC) were used to determine the clinical and prognostic significance of the GABRD in CRC. We used gain-of-function and loss-of-function experiments to investigate the in vitro roles of GABRD in cultured CRC cells. We characterized the potential mechanism of GABRD’s activities in CRC using a Gene Set Enrichment Analysis (GSEA) with The Cancer Genome Atlas Colon Adenocarcinoma (TCGA-COAD) dataset. We found that the GABRD expression was significantly increased in CRCs compared to that in NTs, but was similar between metastasis and primary tumors. Overexpression of GABRD was significantly associated with later pTNM stages and unfavorable patient survival. Overexpression of GABRD accelerated while knock-down of GABRD inhibited cell growth and migration. Mechanistically, the function of GABRD might be ascribed to its influence on major oncogenic events such as epithelial–mesenchymal transition (EMT), angiogenesis, and hedgehog signaling. Collectively, GABRD could be a novel prognostic predictor for CRC that deserves further investigation.