Detection of postoperative plasma circulating tumour DNA and lack of CDX2 expression as markers of recurrence in patients with localised colon cancer

Construction and verification of a histone deacetylases-related prognostic signature model for colon cancer

Histone deacetylases (HDACs) contribute significantly to the initiation, progression, and prognosis of colorectal adenocarcinoma (COAD). Additionally, HDACs regulate the tumor microenvironment, immune escape, and tumor stem cells, and are closely linked to COAD prognosis. We developed a prognostic model for COAD that incorporates HDACs to evaluate their specific roles. The COAD dataset containing clinical and mutation data was collected using the TCGA and GEO databases to obtain genes associated with HDAC. LASSO analysis and univariate and multivariate Cox regression analysis were used to determine the presence of prognostic genes. Multivariate Cox analysis was also used to determine risk scores for HDAC-related features. Furthermore, genomic alterations, immune infiltration, and drug response were compared between high- and low-risk groups. Cellular experiments validated the potential regulatory role of BRD3 on COAD proliferation, migration, and apoptosis. The median risk scores, calculated based on the characteristics, demonstrated a more significant prognostic improvement in patients in the low-risk group. Furthermore, HDAC-related features were identified as important independent prognostic factors for patients with COAD. Additionally, genomic mutation status, immune infiltration, and function, as well as response to immunotherapy and chemotherapy, were found to be associated with risk scores. Subgroup analyses indicate that anti-PD-1 therapy may be beneficial for patients in the low-risk group. Additionally, a decrease in risk score was associated with a decrease in immune infiltration. Finally, HCT116 and HT29 cells exhibited inhibition of BRD3 gene proliferation and migration, as well as promotion of apoptosis. In patients with COAD, HDAC-related characteristics may be useful in predicting survival and selecting treatment.

Loss of CDX2 and high COX2 (PTGS2) expression in metastatic colorectal cancer

Lack of expression of the tumour suppressor gene caudal-type homeobox 2 (CDX2) associates with poor outcomes in early stage colorectal cancer (CRC). Yet its prognostic value in the context of other prognostic biomarkers in metastatic CRC (mCRC) is unknown. Overexpressed cyclooxygenase-2 (COX2) has been reported in advanced CRC. However, CDX2 and COX2 relationship in mCRC remains undetermined. We aimed to assess their expression in mCRC tumours from a clinically characterised cohort and their influence on overall survival (OS) and progression-free survival (PFS) in first line. Among 720 consecutive mCRC patients, 346 had tumour samples appropriate for tissue microarray assembly and immunohistochemistry analyses. Clinical and survival data were retrospectively assessed. Loss of CDX2 expression was detected in 27 (7.8%) samples, enriched in poorly differentiated tumours (20%; p < 0.01) and in those with the BRAF p.V600E variant (40%; p < 0.01). Most tumours (93.4%) expressed COX2. COX2-negative samples were enriched in poorly differentiated mCRC. In unadjusted analyses, median OS (p < 0.001) and median PFS (p < 0.05) were inferior for patients with CDX2-negative versus CDX2-positive tumours. In conclusion, loss of CDX2 was significantly associated with poorly differentiated mCRC and BRAF p.V600E allele and a prognostic marker of worse OS.

Machine-Learning Identifies a Strategy for Differentiation Therapy in Solid Tumors

BACKGROUND

Although differentiation therapy can cure some hematologic malignancies, its curative potential remains unrealized in solid tumors. This is because conventional computational approaches succumb to the thunderous noise of inter-/intratumoral heterogeneity. Using colorectal cancers (CRCs) as an example, here we outline a machine learning(ML)-based approach to track, differentiate, and selectively target cancer stem cells (CSCs).

METHODS

A transcriptomic network was built and validated using healthy colon and CRC tissues in diverse gene expression datasets (~5,000 human and >300 mouse samples). Therapeutic targets and perturbation strategies were prioritized using ML, with the goal of reinstating the expression of a transcriptional identifier of the differentiated colonocyte, CDX2, whose loss in poorly differentiated (CSC-enriched) CRCs doubles the risk of relapse/death. The top candidate target was then engaged with a clinical-grade drug and tested on 3 models: CRC lines in vitro, xenografts in mice, and in a prospective cohort of healthy (n = 3) and CRC (n = 23) patient-derived organoids (PDOs).

RESULTS

The drug shifts the network predictably, induces CDX2 and crypt differentiation, and shows cytotoxicity in all 3 models, with a high degree of selectivity towards all CDX2-negative cell lines, xenotransplants, and PDOs. The potential for effective pairing of therapeutic efficacy (IC50) and biomarker (CDX2-low state) is confirmed in PDOs using multivariate analyses. A 50-gene signature of therapeutic response is derived and tested on 9 independent cohorts (~1700 CRCs), revealing the impact of CDX2-reinstatement therapy could translate into a ~50% reduction in the risk of mortality/recurrence.

CONCLUSIONS

Findings not only validate the precision of the ML approach in targeting CSCs, and objectively assess its impact on clinical outcome, but also exemplify the use of ML in yielding clinical directive information for enhancing personalized medicine.

A Phase II Exploratory Study to Identify Biomarkers Predictive of Clinical Response to Regorafenib in Patients with Metastatic Colorectal Cancer Who Have Failed First-Line Therapy

Single-agent regorafenib is approved in Canada for metastatic colorectal cancer (mCRC) patients who have failed previous lines of therapy. Identifying prognostic biomarkers is key to optimizing therapeutic strategies for these patients. In this clinical study (NCT01949194), we evaluated the safety and efficacy of single-agent regorafenib as a second-line therapy for mCRC patients who received it after failing first-line therapy with an oxaliplatin or irinotecan regimen with or without bevacizumab. Using various omics approaches, we also investigated putative biomarkers of response and resistance to regorafenib in metastatic lesions and blood samples in the same cohort. Overall, the safety profile of regorafenib seemed similar to the CORRECT trial, where regorafenib was administered as ≥ 2 lines of therapy. While the mutational landscape showed typical mutation rates for the top five driver genes (APC, KRAS, BRAF, PIK3CA, and TP53), KRAS mutations were enriched in intrinsically resistant lesions. Additional exploration of genomic-phenotype associations revealed several biomarker candidates linked to unfavorable prognoses in patients with mCRC using various approaches, including pathway analysis, cfDNA profiling, and copy number analysis. However, further research endeavors are necessary to validate the potential utility of these promising genes in understanding patients' responses to regorafenib treatment.

Bioinformatics analysis-based screening of circRNA gene with mainstream expression trend in colorectal cancer and construction of a coexpression regulatory network

OBJECTIVE

Since circRNA can be utilized as a potential diagnostic marker for cancer, to explore the regulatory mechanism of colorectal cancer (CRC) using bioinformatics, the public database of circRNA was mined.

METHODS

CRC differentially expressed miRNAs were screened in the Cancer Genome Atlas (TCGA) database, CRC differentially expressed circRNAs were searched in the Gene Expression Omnibus (GEO) database, the two databases were combined to identify CRC differentially expressed mRNAs, and a circRNA-miRNA‒mRNA regulatory network was constructed by combining a plurality of target prediction databases to identify key genes. The upstream circRNA and regulatory axis of the key genes were identified for gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis to explore the biological functions of circRNA in CRC using the regulatory axis.

RESULTS

After the screening of the GSE21815 dataset, a total of 22 differentially expressed circRNAs were obtained, with 12 upregulated and 10 downregulated genes. Similarly, the GSE126094 dataset yielded 104 differentially expressed circRNAs, comprising 56 upregulated and 48 downregulated genes. Among the differentially expressed circRNAs, five were identified, with VDAC3 and SETD2 showing downregulated expression, while RAD23B, RPPH1, and MYBL2 exhibited upregulated expression. Following the selection process, five DEcircRNAs, eight target miRNAs, and 105 target DEmRNAs were identified. The protein-protein interaction (PPI) network revealed close relationships among the mRNAs, with E2F2, E2F3, CCND1, TNRC6A, and KAT2B identified as key genes. Notably, CCND1 emerged as a critical gene in the PPI network. Through the upregulation of has-circ-0087862, which binds to miR-892b, the translation inhibition of CCND1 by miR-892b was attenuated, leading to enhanced CCND1 expression. Functional enrichment analysis indicated that CCND1 was involved in protein binding and positive regulation of cellular processes, among other functions.

CONCLUSION

The differentially expressed genes (DEGs) in CRC markedly affected the survival time of patients. CircRNAs could be utilized as diagnostic markers of CRC, and the key genes in CRC could be screened out by bioinformatics, which would be helpful to understand the drug targets for the treatment of human immunodeficiency virus (HIV)-related CRC patients.

Sequencing paired tumor DNA and white blood cells improves circulating tumor DNA tracking and detects pathogenic germline variants in localized colon cancer

BACKGROUND

In the setting of localized colon cancer (CC), circulating tumor DNA (ctDNA) monitoring in plasma has shown potential for detecting minimal residual disease (MRD) and predicting a higher risk of recurrence. With the tumor-only sequencing approach, however, germline variants may be misidentified as somatic variations, precluding the possibility of tracking in up to 11% of patients due to a lack of known somatic mutations. In this study, we assess the potential value of adding white blood cells (WBCs) to tumor tissue sequencing to enhance the accuracy of sequencing results.

PATIENTS AND METHODS

A total of 148 patients diagnosed with localized CC were prospectively recruited at the Hospital Clínico Universitario in Valencia (Spain). Employing a custom 29-gene panel, sequencing was conducted on tumor tissue, plasma and corresponding WBCs. Droplet digital PCR and amplicon-based NGS were performed on plasma samples post-surgery to track MRD. Oncogenic somatic variants were identified by annotating with COSMIC, OncoKB and an internal repository of pathogenic mutations database. A variant prioritization analysis, mainly characterized by the match of oncogenic mutations with the evidence levels defined in OncoKB, was carried out to select specific targeted therapies.

RESULTS

Utilizing paired tumor and WBCs sequencing, we identified somatic mutations in all patients (100%) within our cohort, compared to 89% using only tumor tissue. Consequently, the top 10 most frequently mutated genes for plasma monitoring were altered. The sequencing of WBCs identified 9% of patients with pathogenic mutations in the germline, with APC and TP53 being the most frequently mutated genes. Additionally, mutations in genes related to clonal hematopoiesis of indeterminate potential were detected in 27% of the cohort, with TP53, KRAS, and KMT2C being the most frequently altered genes. There were no observed differences in the sensitivity of monitoring MRD using ddPCR or amplicon-based NGS (p = 1). Ultimately, 41% of the patients harbored potentially targetable alterations at diagnosis.

CONCLUSION

The germline testing method not only enhanced sequencing results and raised the proportion of patients eligible for plasma monitoring, but also uncovered the existence of pathogenic germline variations, thereby aiding in the identification of patients at a higher risk of hereditary cancer syndromes.

The prognostic potential of CDX2 in colorectal cancer: Harmonizing biology and clinical practice

Adjuvant chemotherapy following surgical intervention remains the primary treatment option for patients with localized colorectal cancer (CRC). However, a significant proportion of patients will have an unfavorable outcome after current forms of chemotherapy. While reflecting the increasing complexity of CRC, the clinical application of molecular biomarkers provides information that can be utilized to guide therapeutic strategies. Among these, caudal-related homeobox transcription factor 2 (CDX2) emerges as a biomarker of both prognosis and relapse after therapy. CDX2 is a key transcription factor that controls intestinal fate. Although rarely mutated in CRC, loss of CDX2 expression has been reported mostly in right-sided, microsatellite-unstable tumors and is associated with aggressive carcinomas. The pathological assessment of CDX2 by immunohistochemistry can thus identify patients with high-risk CRC, but the evaluation of CDX2 expression remains challenging in a substantial proportion of patients. In this review, we discuss the roles of CDX2 in homeostasis and CRC and the alterations that lead to protein expression loss. Furthermore, we review the clinical significance of CDX2 assessment, with a particular focus on its current use as a biomarker for pathological evaluation and clinical decision-making. Finally, we attempt to clarify the molecular implications of CDX2 deficiency, ultimately providing insights for a more precise evaluation of CDX2 protein expression.

Feasibility of Inferring Spatial Transcriptomics from Single-Cell Histological Patterns for Studying Colon Cancer Tumor Heterogeneity

Background

Spatial transcriptomics involves studying the spatial organization of gene expression within tissues, offering insights into the molecular diversity of tumors. While spatial gene expression is commonly amalgamated from 1-10 cells across 50-micron spots, recent methods have demonstrated the capability to disaggregate this information at subspot resolution by leveraging both expression and histological patterns. However, elucidating such information from histology alone presents a significant challenge but if solved can better permit spatial molecular analysis at cellular resolution for instances where Visium data is not available, reducing study costs. This study explores integrating single-cell histological and transcriptomic data to infer spatial mRNA expression patterns in whole slide images collected from a cohort of stage pT3 colorectal cancer patients. A cell graph neural network algorithm was developed to align histological information extracted from detected cells with single cell RNA patterns through optimal transport methods, facilitating the analysis of cellular groupings and gene relationships. This approach leveraged spot-level expression as an intermediary to co-map histological and transcriptomic information at the single-cell level.

Results

Our study demonstrated that single-cell transcriptional heterogeneity within a spot could be predicted from histological markers extracted from cells detected within a spot. Furthermore, our model exhibited proficiency in delineating overarching gene expression patterns across whole-slide images. This approach compared favorably to traditional patch-based computer vision methods as well as other methods which did not incorporate single cell expression during the model fitting procedures. Topological nuances of single-cell expression within a Visium spot were preserved using the developed methodology.

Conclusion

This innovative approach augments the resolution of spatial molecular assays utilizing histology as a sole input through synergistic co-mapping of histological and transcriptomic datasets at the single-cell level, anchored by spatial transcriptomics. While initial results are promising, they warrant rigorous validation. This includes collaborating with pathologists for precise spatial identification of distinct cell types and utilizing sophisticated assays, such as Xenium, to attain deeper subcellular insights.

Comprehensive analysis of CXCL14 uncovers its role during liver metastasis in colon cancer

BACKGROUND

The most common cause of death for colon cancer patients is liver metastasis.

METHODS

All the data enrolled in this study were downloaded from two public databases, The Cancer Genome Atlas Program, the TCGA-COAD project and Gene Expression Omnibus, GSE41258 project. All the analysis was performed in R software.

RESULTS

In our study, we systematically explored the molecules involved in the liver metastasis process of colon cancer. The biological role of these molecules was identified through the GO and KEGG analysis. Moreover, we identified that the molecules SERPINA3, SERPINA1, MMP3, ALDH1A3, PBK and CXCL14 were the independent factors for patients survival. The CXCL14 was selected for further analysis for its most significant P value. Single-cell analysis showed that the CXCL14 was mainly expressed in the fibroblasts. Meanwhile, the biological role of fibroblasts in the colon cancer microenvironment was investigated. Further, the clinical role of CXCL14 in colon cancer was also explored. The result showed that the CXCL14 is a protective factor against colon cancer independent of other clinical parameters like age, gender, clinical stage, and TNM classifications. Then, biological enrichment analysis indicated that the CXCL14 is predominantly involved in the activating of the WNT/β/catenin pathway, pancreas beta cells, peroxisome and bile acid metabolism. Immune infiltration analysis showed that for the patients with high CXCL14 levels, the plasma B cells, CD8 + T cells, neutrophil and NK cells might infiltrate more, in contrast to B cells, monocyte and macrophages. Furthermore, we found that the patients with low CXCL14 expression might be more sensitive to etoposide, rapamycin and sunitinib.

CONCLUSIONS

Our result could improve the understanding of the liver metastasis process in colon cancer. Also, CXCL14 was identified as an underlying therapeutic target for colon cancer.

Identification of Spatial Proteomic Signatures of Colon Tumor Metastasis: A Digital Spatial Profiling Approach

Over 150,000 Americans are diagnosed with colorectal cancer (CRC) every year, and annually >50,000 individuals are estimated to die of CRC, necessitating improvements in screening, prognostication, disease management, and therapeutic options. CRC tumors are removed en bloc with surrounding vasculature and lymphatics. Examination of regional lymph nodes at the time of surgical resection is essential for prognostication. Developing alternative approaches to indirectly assess recurrence risk would have utility in cases where lymph node yield is incomplete or inadequate. Spatially dependent, immune cell-specific (eg, tumor-infiltrating lymphocytes), proteomic, and transcriptomic expression patterns inside and around the tumor-the tumor immune microenvironment-can predict nodal/distant metastasis and probe the coordinated immune response from the primary tumor site. The comprehensive characterization of tumor-infiltrating lymphocytes and other immune infiltrates is possible using highly multiplexed spatial omics technologies, such as the GeoMX Digital Spatial Profiler. In this study, machine learning and differential co-expression analyses helped identify biomarkers from Digital Spatial Profiler-assayed protein expression patterns inside, at the invasive margin, and away from the tumor, associated with extracellular matrix remodeling (eg, granzyme B and fibronectin), immune suppression (eg, forkhead box P3), exhaustion and cytotoxicity (eg, CD8), Programmed death ligand 1-expressing dendritic cells, and neutrophil proliferation, among other concomitant alterations. Further investigation of these biomarkers may reveal independent risk factors of CRC metastasis that can be formulated into low-cost, widely available assays.

Principles of Molecular Utility for CMS Classification in Colorectal Cancer Management

Colorectal cancer (CRC) is the second cause of cancer-related deaths in both sexes globally and presents different clinical outcomes that are described by a range of genomic and epigenomic alterations. Despite the advancements in CRC screening plans and treatment strategies, the prognosis of CRC is dismal. In the last two decades, molecular biomarkers predictive of prognosis have been identified in CRC, although biomarkers predictive of treatment response are only available for specific biological drugs used in stage IV CRC. Translational clinical trials mainly based on "omic" strategies allowed a better understanding of the biological heterogeneity of CRCs. These studies were able to classify CRCs into subtypes mainly related to prognosis, recurrence risk, and, to some extent, also to treatment response. Accordingly, the comprehensive molecular characterizations of CRCs, including The Cancer Genome Atlas (TCGA) and consensus molecular subtype (CMS) classifications, were presented to improve the comprehension of the genomic and epigenomic landscapes of CRCs for a better patient management. The CMS classification obtained by the CRC subtyping consortium categorizes CRC into four consensus molecular subtypes (CMS1-4) characterized by different prognoses. In this review, we discussed the CMS classification in different settings with a focus on its relationships with precursor lesions, tumor immunophenotype, and gut microbiota, as well as on its role in predicting prognosis and/or response to pharmacological treatments, as a crucial step towards precision medicine.

Regularized survival learning and cross-database analysis enabled identification of colorectal cancer prognosis-related immune genes

Colon adenocarcinoma is the most common type of colorectal cancer. The prognosis of advanced colorectal cancer patients who received treatment is still very poor. Therefore, identifying new biomarkers for prognosis prediction has important significance for improving treatment strategies. However, the power of biomarker analyses was limited by the used sample size of individual database. In this study, we combined Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA) databases to expand the number of healthy tissue samples. We screened differentially expressed genes between the GTEx healthy samples and TCGA tumor samples. Subsequently, we applied least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox analysis to identify nine prognosis-related immune genes: ANGPTL4, IDO1, NOX1, CXCL3, LTB4R, IL1RL2, CD72, NOS2, and NUDT6. We computed the risk scores of samples based on the expression levels of these genes and divided patients into high- and low-risk groups according to this risk score. Survival analysis results showed a significant difference in survival rate between the two risk groups. The high-risk group had a significantly lower overall survival rate and poorer prognosis. We found the receiver operating characteristic based on the risk score was showed to accurately predict patients' prognosis. These prognosis-related immune genes may be potential biomarkers for colorectal cancer diagnosis and treatment. Our open-source code is freely available from GitHub at https://github.com/gutmicrobes/Prognosis-model.git.

The pathogenic roles of lncRNA-Taurine upregulated 1 (TUG1) in colorectal cancer

Colorectal cancer (CRC) is a gastrointestinal tumor that develops from the colon, rectum, or appendix. The prognosis of CRC patients especially those with metastatic lesions remains unsatisfactory. Although various conventional methods have been used for the treatment of patients with CRC, the early detection and identification of molecular mechanisms associated with CRC is necessary. The scientific literature reports that altered expression of long non-coding RNAs (lncRNAs) contributed to the pathogenesis of CRC cells. LncRNA TUG1 was reported to target various miRNAs and signaling pathways to mediate CRC cell proliferation, migration, and metastasis. Therefore, TUG1 might be a potent predictive/prognostic biomarker for diagnosis of CRC.

CDX2 as a Predictive Biomarker Involved in Immunotherapy Response Suppresses Metastasis through EMT in Colorectal Cancer

Background

Studies have confirmed that Caudal Type Homeobox 2 (CDX2) plays a tumor suppressor role in colorectal cancer (CRC) and as a prognostic and predictive marker for colorectal cancer. The epithelial to mesenchymal transition (EMT) is a transdifferentiation process, providing migratory and invasive properties to cancer cells during tumor progression. However, the role of CDX2 during the activation of EMT in CRC maintains controversial.

Aim

To investigate whether CDX2 is associated with EMT in CRC.

Methods

Forty-six CRC patients were included in the study. Expressions of CDX2, E-cadherin, and N-cadherin in all CRC patients were detected by IHC. ROC assays were applied to detect cut-off points for IHC scores to distinguish high and low expressions of CDX2 in 46 CRC samples. The prognostic value of CDX2 was statistically analyzed. MTT, Western blot, invasion, and migration assays in vitro were employed to explore the function of CDX2.

Results

We observed that high expressions of CDX2 and E-cadherin as well as low expressions of N-cadherin were significantly correlated with favorable prognosis. The levels of CDX2 protein exhibited a positive associated with E-cadherin while negative correlation with N-cadherin. Then, the low expression of CDX2 and high expression of CA199 in combination are positively related with poor prognosis. Overexpression of CDX2 reduced expression of MMP-2 and diminished cell proliferation, invasion, and migration, while knockdown CDX2 enhanced MMP-2 expression and increased cell proliferation, invasion, and migration in HCT-116 cells. CDX2 was correlated with expression of EMT markers. Overexpression of CDX2 suppressed the EMT markers indicating that CDX2 suppresses CRC cell viability, invasion, and metastasis through inhibiting EMT. Finally, we found that the expression of CDX2 was negatively associated with Th1 cells, macrophages, Th2 cells, cytotoxic cells, T cells, and T helper cells.

Conclusions

These results indicated CDX2 as prognostic biomarkers involved in immunotherapy response for CRC. CDX2 loss promotes metastasis in CRC through a CDX2-dependent mechanism.

Integrative Proteo-Genomic Analysis for Recurrent Survival Prognosis in Colon Adenocarcinoma

Background

The survival prognosis is the hallmark of cancer progression. Here, we aimed to develop a recurrence-related gene signature to predict the prognosis of colon adenocarcinoma (COAD).

Methods

The proteomic data from the Clinical Proteomic Tumor Analysis Consortium (CPTAC) and genomic data from the cancer genomic maps [The Cancer Genome Atlas (TCGA)] dataset were analyzed to identify co-differentially expressed genes (cDEGs) between recurrence samples and non-recurrence samples in COAD using limma package. Functional enrichment analysis, including Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway was conducted. Univariate and multivariate Cox regressions were applied to identify the independent prognostic feature cDEGs and establish the signature whose performance was evaluated by Kaplan–Meier curve, receiver operating characteristic (ROC), Harrell’s concordance index (C-index), and calibration curve. The area under the receiver operating characteristic (ROC) curve (AUROC) and a nomogram were calculated to assess the predictive accuracy. GSE17538 and GSE39582 were used for external validation. Quantitative real-time PCR and Western blot analysis were carried out to validate our findings.

Results

We identified 86 cDEGs in recurrence samples compared with non-recurrence samples. These genes were primarily enriched in the regulation of carbon metabolic process, fructose and mannose metabolism, and extracellular exosome. Then, an eight-gene-based signature (CA12, HBB, NCF1, KBTBD11, MMAA, DMBT1, AHNAK2, and FBLN2) was developed to separate patients into high- and low-risk groups. Patients in the low-risk group had significantly better prognosis than those in the high-risk group. Four prognostic clinical features, including pathological M, N, T, and RS model status, were screened for building the nomogram survival model. The PCR and Western blot analysis results suggested that CA12 and AHNAK2 were significantly upregulated, while MMAA and DMBT1 were downregulated in the tumor sample compared with adjacent tissues, and in non-recurrent samples compared with non-recurrent samples in COAD.

Conclusion

These identified recurrence-related gene signatures might provide an effective prognostic predictor and promising therapeutic targets for COAD patients.

Finding Waldo: The Evolving Paradigm of Circulating Tumor DNA (ctDNA)—Guided Minimal Residual Disease (MRD) Assessment in Colorectal Cancer (CRC)

Simple Summary

After the surgical removal of colorectal cancer (CRC), residual cancer cells undetectable by standard blood tests and imaging studies are responsible for cancer recurrence. Currently, chemotherapy is often administered after surgery to eradicate residual cancer cells, a decision guided by clinical and pathologic criteria, which are imprecise. Circulating tumor DNA (ctDNA) consists of DNA fragments in the bloodstream derived from cancer cells, and the presence of ctDNA likely indicates the presence of residual cancer cells. The current article discusses how ctDNA technology can help guide treatment in patients with CRC after curative surgery.

Abstract

Circulating tumor DNA (ctDNA), the tumor-derived cell-free DNA fragments in the bloodstream carrying tumor-specific genetic and epigenetic alterations, represents an emerging novel tool for minimal residual disease (MRD) assessment in patients with resected colorectal cancer (CRC). For many decades, precise risk-stratification following curative-intent colorectal surgery has remained an enduring challenge. The current risk stratification strategy relies on clinicopathologic characteristics of the tumors that lacks precision and results in over-and undertreatment in a significant proportion of patients. Consequently, a biomarker that can reliably identify patients harboring MRD would be of critical importance in refining patient selection for adjuvant therapy. Several prospective cohort studies have provided compelling data suggesting that ctDNA could be a robust biomarker for MRD that outperforms all existing clinicopathologic criteria. Numerous clinical trials are currently underway to validate the ctDNA-guided MRD assessment and adjuvant treatment strategies. Once validated, the ctDNA technology will likely transform the adjuvant therapy paradigm of colorectal cancer, supporting ctDNA-guided treatment escalation and de-escalation. The current article presents a comprehensive overview of the published studies supporting the utility of ctDNA for MRD assessment in patients with CRC. We also discuss ongoing ctDNA-guided adjuvant clinical trials that will likely shape future adjuvant therapy strategies for patients with CRC.

lncRNA TUG1 Facilitates Colorectal Cancer Stem Cell Characteristics and Chemoresistance by Enhancing GATA6 Protein Stability

Background

Chemoresistance and tumor recurrence lead to high deaths in colorectal cancer (CRC) patients. Cancer stem cells (CSCs) contribute to these pathologic properties, but the exact mechanisms are still poorly understood. This study identified that long noncoding RNA (lncRNA) TUG1 was highly expressed in CRC stem cells and investigated its mechanism.

Methods

After the CD133⁺/CD44⁺ cells with cancer stem cell (CSC) characteristics were isolated and identified by flow cytometry, lncRNA TUG1 expression was quantified by quantitative real-time PCR. The lncRNA TUG1 function was further investigated using gain- and loss-of-function assays, sphere formation, Western blot, Cell Counting Kit-8 assay, and cell apoptosis detection. Moreover, the mechanism was explored by RNA pull-down assay, RNA immunoprecipitation, and cycloheximide- (CHX-) chase assays.

Results

lncRNA TUG1 was elevated in CD133⁺/CD44⁺ cells with CSC characteristics. Functionally, lncRNA TUG1 increased the characteristics and oxaliplatin resistance of CRC stem cells. Mechanically, lncRNA TUG1 interacted with GATA6 and positively regulated its protein level and the rescue assays corroborated that lncRNA TUG1 knockdown repressed the characteristics and oxaliplatin resistance of CRC stem cells by decreasing GATA6 and functioned in CRC by targeting the GATA6-BMP signaling pathway. Furthermore, the in vivo assay verified the lncRNA TUG1 function in facilitating the characteristics and oxaliplatin resistance of CRC stem cells.

Conclusion

lncRNA TUG1 facilitated CRC stem cell characteristics and chemoresistance by enhancing GATA6 protein stability.

A Novel Cancer Stemness-Related Signature for Predicting Prognosis in Patients with Colon Adenocarcinoma

Objective

To explore the cancer stemness features and develop a novel cancer stemness-related prognostic signature for colon adenocarcinoma (COAD).

Methods

We downloaded the mRNA expression data and clinical data of COAD from TCGA database and GEO database. Stemness index, mRNAsi, was utilized to investigate cancer stemness features. Weighted gene coexpression network analysis (WGCNA) was used to identify cancer stemness-related genes. Univariate and multivariate Cox regression analyses were applied to construct a prognostic risk cancer stemness-related signature. We then performed internal and external validation. The relationship between cancer stemness and COAD immune microenvironment was investigated.

Results

COAD patients with higher mRNAsi score or EREG-mRNAsi score have significant longer overall survival (OS). We identified 483 differently expressed genes (DEGs) between the high and low mRNAsi score groups. We developed a cancer stemness-related signature using fifteen genes (including RAB31, COL6A3, COL5A2, CCDC80, ADAM12, VGLL3, ECM2, POSTN, DPYSL3, PCDH7, CRISPLD2, COLEC12, NRP2, ISLR, and CCDC8) for prognosis prediction of COAD. Low-risk score was associated with significantly preferable OS in comparison with high-risk score, and the area under the ROC curve (AUC) for OS prediction was 0.705. The prognostic signature was an independent predictor for OS of COAD. Macrophages, mast cells, and T helper cells were the vital infiltration immune cells, and APC costimulation and type II IFN response were the vital immune pathways in COAD.

Conclusions

We developed and validated a novel cancer stemness-related prognostic signature for COAD, which would contribute to understanding of molecular mechanism in COAD.

Effect of the duration of the capecitabine regimen following colon cancer surgery in an elderly population: a retrospective cohort study

Background

Only 50–70% of elderly colon cancer patients could complete the recommended 6 months of postoperative chemotherapy. It is unknown whether a shorter duration of postoperative capecitabine-alone chemotherapy would compromise survival. We thus conducted this study to analyze the association between postoperative chemotherapy duration of a capecitabine-alone regimen and cancer-specific survival (CSS) and disease-free survival (DFS) of surgery-treated elderly colon cancer patients.

Methods

We performed a retrospective cohort study of surgically treated stage III and high-risk stage II colon cancer patients aged ≥ 70 treated at two medical centers. Cox proportional hazard regression models were utilized to calculate crude and adjusted hazard ratios (HRs). The nonlinear relationship between postoperative chemotherapy duration and survival was analyzed through restricted cubic spline regression analysis, and the threshold effect was calculated by the two-piecewise Cox proportional hazard model.

Results

A total of 1217 surgery-treated colon cancer patients between August 1, 2013, and September 1, 2019, were reviewed, and 257 stage III and high-risk stage II patients aged ≥ 70 were enrolled. Postoperative chemotherapy with capecitabine was administered to 114 patients, and 143 patients only received surgery. As the duration of chemotherapy increased by 1 week, the risk of cancer-specific death was reduced by 11% (HR = 0.89, 95% confidence interval (CI) 0.82–0.96), and the risk of recurrence was reduced by 10% (HR = 0.90, 0.82–0.96). Nonlinearity exploration suggested a threshold effect of capecitabine duration on CSS in stage III disease. The HR for death was 0.79 (95% CI, 0.68–0.92) with duration ≤ 16 weeks and 1.34 (95% CI, 0.91–1.97) with duration > 16 weeks.

Conclusions

The postoperative capecitabine duration was significantly associated with a decrease in death risk and recurrence risk in elderly colon cancer patients. However, the threshold effect of capecitabine duration on survival suggests that short-term chemotherapy may improve survival in elderly stage III colon cancer patients.

Droplet digital polymerase chain reaction assay for the detection of the minor clone of KIT D816V in paediatric acute myeloid leukaemia especially showing RUNX1-RUNX1T1 transcripts

KIT D816V mutation within exon 17 has been particularly reported as one of the poor prognostic factors in pediatric acute myeloid leukemia (AML) with RUNX1-RUNX1T1. The exact frequency and the prognostic impact of KIT D816V minor clones at diagnosis were not examined. In this study, the minor clones were examined and the prognostic significance of KIT D816V mutation in pediatric patients was investigated. Consequently, 24 KIT D816V mutations (7.2%) in 335 pediatric patients were identified, and 12 of 24 were only detected via the digital droplet polymerase chain reaction method. All 12 patients were confined in core binding factor (CBF)-AML patients. The 5 year event-free survival of the patients with KIT D816V mutation was significantly inferior to those without KIT D816V mutation (44.1% [95% confidence interval (CI), 16.0%-69.4%] vs. 74.7% [95% CI, 63.0%-83.2%] P-value = 0.02, respectively). The 5 year overall survival was not different between the two groups (92.9% [95% CI, 59.0%-NA vs. 89.7% [95% CI, 69.6%-96.8%] P-value = 0.607, respectively). In this study, KIT D816V minor clones in patients with CBF-AML were confirmed and KIT D816V was considered as a risk factor for relapse in patients with RUNX1-RUNX1T1-positive AML.

Epigenetic Mechanisms Are Involved in the Oncogenic Properties of ZNF518B in Colorectal Cancer

Simple Summary

The ZNF518B gene, which is up-regulated in colorectal cancer, plays a role in metastasis, but neither the mechanisms involved in this process nor the role of the different isoforms of the gene are known. Here we show that the ratio of these isoforms is related to the relapsing of the disease, and that the protein ZNF518B interacts with enzymes able to introduce epigenetic changes, which may affect the activity of many genes. We also report a list of genes affected in common by ZNF518B and by two of those related enzymes, namely, G9A and EZH2. An in-depth analysis of five of those genes revealed that ZNF518B is involved in the recruitment of the enzymes and in the deposition of the corresponding epigenetic marks. The results highlight the relevance of epigenetic changes in cancer development, and open the possibility of developing therapeutic approaches, as the introduction of epigenetic modifications is reversible.

Abstract

The ZNF518B gene, which is up-regulated in colorectal cancer, plays a role in cell dissemination and metastasis. It encodes a zinc-finger protein, which interacts with histone methyltransferases G9A and EZH2. The expression of the two major mRNA isoforms 1 (coding for the full protein) and 2 was quantified by RT-qPCR in a cohort of 66 patients. The effects of silencing ZNF518B on the transcriptome of DLD1 and HCT116 cells were analysed by Clariom-S assays and validated by RT-qPCR. The recruitment of methyltransferases and the presence of H3K27me3 were studied by chromatin immunoprecipitation (ChIP). The ratio (isoform 2)/(isoform 1) negatively correlated with the relapsing of disease. The study of the transcriptome of DLD1 and HCT116 cells revealed that many genes affected by silencing ZNF518B are related to cancer. After crossing these results with the list of genes affected by silencing the histone methyltransferases (retrieved in silico), five genes were selected. ChIP analysis revealed that the recruitment of EZH2 is ZNF518B-dependent in KAT2B, RGS4 and EFNA5; the level of H3K27me3 changes in accordance. G9A also binds RGS4 and PADI3 in a ZNF518B-dependent manner. The results highlight the importance of epigenetics in cancer and open a novel therapeutic possibility, as inhibition of histone methyltransferases may reverse the disease-linked histone marks.

Minimal Residual Disease, Metastasis and Immunity

Progression from localized to metastatic disease requires cancer cells spreading to distant organs through the bloodstream. Only a small proportion of these circulating tumor cells (CTCs) survives dissemination due to anoikis, shear forces and elimination by the immune system. However, all metastases originate from CTCs capable of surviving and extravasating into distant tissue to re-initiate a tumor. Metastasis initiation is not always immediate as disseminated tumor cells (DTCs) may enter a non-dividing state of cell dormancy. Cancer dormancy is a reversible condition that can be maintained for many years without being clinically detectable. Subsequently, late disease relapses are thought to be due to cancer cells ultimately escaping from dormant state. Cancer dormancy is usually associated with minimal residual disease (MRD), where DTCs persist after intended curative therapy. Thus, MRD is commonly regarded as an indicator of poor prognosis in all cancers. In this review, we examine the current understanding of MRD and immunity during cancer progression to metastasis and discuss clinical perspectives for oncology.