Subtypes Of Colorectal Cancer Research Articles

Unraveling the Interplay of Autophagy Genes and KLF3/KLF8 in Colorectal Cancer Metastasis: A Bioinformatics and cellular Exploration

Background Colorectal cancer (CRC) is a widespread malignancy globally, yet effective therapeutic approaches for advanced, metastatic, and chemo-resistant cases remain limited. In this study, we knocked out CRC cell line HCT 116 for two autophagy genes (ATG5 and ATG7), then we conducted a transcriptomic analysis on those isogenic cell lines. which revealed an upregulation of Krϋppel-like factor 3 (KLF3) expression, that was biologically validated. Methods In this study, we performed CRISPR/Cas9 gene editing on HCT 116 followed with transcriptomics analysis on HCT 116 KO cells for ATG5 and ATG7. Various bioinformatics analyses were performed to investigate the KLF3/8 with autophagy and affected functional pathways, and immune genes related to the different types. Validation of expression in different cell lines were done using qPCR and Western blot. Results To further investigate the role of autophagy genes in CRC, we utilized publicly available data and web-based tools. Our analysis showed a marked correlation between KLF3/KLF8 and the expression of autophagy genes in CRC, denoting that its upregulation is likely to be a compensatory mechanism. We also examined the co-expression of autophagy genes and KLF3/KLF8 with multiple markers of epithelial-to-mesenchymal transition (EMT), and significant positive correlations were observed. Moreover, KLF8 expression was upregulated at the mRNA level in the metastatic cell lines LoVo and SK-CO-1, compared to HCT 116. Interestingly, KLF3/KLF8 expression was high in MSS molecular subtype of CRC as shown in HCT 116 cell line knocked in with MLH gene as well as they were negatively correlated with crucial immune-infiltrating cells such as CD8+ cells, indicating their potential as a negative biomarker for response to immunotherapy. Conclusion Our study proposes that a synergistic approach involving the inhibition of KLF8 and autophagy holds a potential therapeutic target for effectively tackling metastatic CRC cells, especially in cases characterized by deficient mismatch repair (MMR).

Height, body mass index, physical activity, and risk of colorectal cancer in relation to expression of insulin receptor: The Japan Public Health Center-based Prospective Study.

To ascertain the involvement of insulin receptors (IRs) in colorectal carcinogenesis, we investigated the association of height, body mass index (BMI), and physical activity with colorectal cancer (CRC) and two subtypes of CRC according to the expression level of IR. We utilized data from a large-scale, population-based prospective cohort study of 18,158 middle-aged and elderly subjects in Akita and Okinawa, Japan. In the statistical analysis, we used the Cox proportional hazards model and estimated hazard ratios (HRs) and 95% confidence intervals (CIs) for the risk of CRC and its subtypes as defined by immunohistochemistry of IRβ, a transmembrane subunit of IR. In the IRβ-defined subtypes, height showed no apparent association with the risk of IRβ-positive CRC. In contrast, a multivariable HR of IRβ-positive CRC was 1.77 (95% CI = 1.04-3.03) with a BMI of ≥30.0 kg/m2 (i.e., obesity), compared to a BMI of <25.0 kg/m2. Further, an increase in physical activity was significantly associated with decreased risk of IRβ-positive CRC (multivariable HR per 5 METs-hour/day = 0.93, 95% CI = 0.88-0.99). Meanwhile, we found no significant association between any exposure and IRβ-negative CRC. Likewise, heterogeneity between the two subtypes of CRC was not statistically significant. These findings imply that obesity and physical activity exert promoting and suppressing effects on the development of CRC expressing IRs, respectively.

High expression of RUNX1 in colorectal cancer subtype accelerates malignancy by inhibiting HMGCR

Colorectal cancer (CRC) presents a complex landscape, characterized by both inter-tumor and intra-tumor heterogeneity. RUNX1, a gene implicated in modulating tumor cell growth, survival, and differentiation, remains incompletely understood regarding its impact on CRC prognosis. In our investigation, we discerned a positive correlation between elevated RUNX1 expression and aggressive phenotypes across various CRC subtypes. Notably, knockdown of RUNX1 demonstrated efficacy in restraining CRC proliferation both in vitro and in vivo, primarily through inducing apoptosis and impeding cell proliferation. Mechanistically, we unveiled a direct regulatory link between RUNX1 and cholesterol synthesis, mediated by its control over HMGCR expression. Knockdown of RUNX1 in CRC cells triggered HMGCR transcriptional activation, culminating in elevated cholesterol levels that subsequently hindered cancer progression. Clinically, heightened RUNX1 expression emerged as a prognostic marker for adverse outcomes in CRC patients. Our findings underscore the pivotal involvement of RUNX1 in CRC advancement and its potential as a therapeutic target. The unique influence of RUNX1 on cholesterol synthesis and HMGCR transcriptional regulation uncovers a novel pathway contributing to CRC progression.

Molecular subtypes of colorectal cancer in the era of precision oncotherapy: Current inspirations and future challenges.

Colorectal cancer (CRC) is among the most hackneyed malignancies. Even patients with identical clinical symptoms and the same TNM stage still exhibit radically different clinical outcomes after receiving equivalent treatment regimens, indicating extensive heterogeneity of CRC. Myriad molecular subtypes of CRC have been exploited for decades, including the most compelling consensus molecular subtype (CMS) classification that has been broadly applied for patient stratification and biomarker-drug combination formulation. Encountering barriers to clinical translation, however, CMS classification fails to fully reflect inter- or intra-tumor heterogeneity of CRC. As a consequence, addressing heterogeneity and precisely managing CRC patients with unique characteristics remain arduous tasks for clinicians. In this review, we systematically summarize molecular subtypes of CRC and further elaborate on their clinical applications, limitations, and future orientations. In recent years, exploration of subtypes through cell lines, animal models, patient-derived xenografts (PDXs), organoids, and clinical trials contributes to refining biological insights and unraveling subtype-specific therapies in CRC. Therapeutic interventions including nanotechnology, clustered regulatory interspaced short palindromic repeat/CRISPR-associated nuclease 9 (CRISPR/Cas9), gut microbiome, and liquid biopsy are powerful tools with the possibility to shift the immunologic landscape and outlook for CRC precise medicine.

PathoDuet: Foundation models for pathological slide analysis of H&E and IHC stains

Large amounts of digitized histopathological data display a promising future for developing pathological foundation models via self-supervised learning methods. Foundation models pretrained with these methods serve as a good basis for downstream tasks. However, the gap between natural and histopathological images hinders the direct application of existing methods. In this work, we present PathoDuet, a series of pretrained models on histopathological images, and a new self-supervised learning framework in histopathology. The framework is featured by a newly-introduced pretext token and later task raisers to explicitly utilize certain relations between images, like multiple magnifications and multiple stains. Based on this, two pretext tasks, cross-scale positioning and cross-stain transferring, are designed to pretrain the model on Hematoxylin and Eosin (H&E) images and transfer the model to immunohistochemistry (IHC) images, respectively. To validate the efficacy of our models, we evaluate the performance over a wide variety of downstream tasks, including patch-level colorectal cancer subtyping and whole slide image (WSI)-level classification in H&E field, together with expression level prediction of IHC marker, tumor identification and slide-level qualitative analysis in IHC field. The experimental results show the superiority of our models over most tasks and the efficacy of proposed pretext tasks. The codes and models are available at https://github.com/openmedlab/PathoDuet.

Elucidating the role of angiogenesis-related genes in colorectal cancer: a multi-omics analysis.

Angiogenesis plays a pivotal role in colorectal cancer (CRC), yet its underlying mechanisms demand further exploration. This study aimed to elucidate the significance of angiogenesis-related genes (ARGs) in CRC through comprehensive multi-omics analysis. CRC patients were categorized according to ARGs expression to form angiogenesis-related clusters (ARCs). We investigated the correlation between ARCs and patient survival, clinical features, consensus molecular subtypes (CMS), cancer stem cell (CSC) index, tumor microenvironment (TME), gene mutations, and response to immunotherapy. Utilizing three machine learning algorithms (LASSO, Xgboost, and Decision Tree), we screen key ARGs associated with ARCs, further validated in independent cohorts. A prognostic signature based on key ARGs was developed and analyzed at the scRNA-seq level. Validation of gene expression in external cohorts, clinical tissues, and blood samples was conducted via RT-PCR assay. Two distinct ARC subtypes were identified and were significantly associated with patient survival, clinical features, CMS, CSC index, and TME, but not with gene mutations. Four genes (S100A4, COL3A1, TIMP1, and APP) were identified as key ARCs, capable of distinguishing ARC subtypes. The prognostic signature based on these genes effectively stratified patients into high- or low-risk categories. scRNA-seq analysis showed that these genes were predominantly expressed in immune cells rather than in cancer cells. Validation in two external cohorts and through clinical samples confirmed significant expression differences between CRC and controls. This study identified two ARG subtypes in CRC and highlighted four key genes associated with these subtypes, offering new insights into personalized CRC treatment strategies.

Integrated analysis reveals a novel 5-fluorouracil resistance-based prognostic signature with promising implications for predicting the efficacy of chemotherapy and immunotherapy in patients with colorectal cancer.

5-Fluorouracil (5-FU) has been used as a standard first-line treatment for colorectal cancer (CRC) patients. Although 5-FU-based chemotherapy and immune checkpoint blockade (ICB) have achieved success in treating CRC, drug resistance and low response rates remain substantial limitations. Thus, it is necessary to construct a 5-FU resistance-related signature (5-FRSig) to predict patient prognosis and identify ideal patients for chemotherapy and immunotherapy. Using bulk and single-cell RNA sequencing data, we established and validated a novel 5-FRSig model using stepwise regression and multiple CRC cohorts and evaluated its associations with the prognosis, clinical features, immune status, immunotherapy, neoadjuvant therapy, and drug sensitivity of CRC patients through various bioinformatics algorithms. Unsupervised consensus clustering was performed to categorize the 5-FU resistance-related molecular subtypes of CRC. The expression levels of 5-FRSig, immune checkpoints, and immunoregulators were determined using quantitative real-time polymerase chain reaction (RT‒qPCR). Potential small-molecule agents were identified via Connectivity Map (CMap) and molecular docking. The 5-FRSig and cluster were confirmed as independent prognostic factors in CRC, as patients in the low-risk group and Cluster 1 had a better prognosis. Notably, 5-FRSig was significantly associated with 5-FU sensitivity, chemotherapy response, immune cell infiltration, immunoreactivity phenotype, immunotherapy efficiency, and drug selection. We predicted 10 potential compounds that bind to the core targets of 5-FRSig with the highest affinity. We developed a valid 5-FRSig to predict the prognosis, chemotherapeutic response, and immune status of CRC patients, thus optimizing the therapeutic benefits of chemotherapy combined with immunotherapy, which can facilitate the development of personalized treatments and novel molecular targeted therapies for patients with CRC.

Changes in US colorectal cancer mortality trends over the past 20 years.

e15543 Background: In the last two decades, colorectal cancer (CRC) mortality has been decreasing in the United States (US). However, the mortality trends for the different subtypes of CRC, including different sides of colon, rectosigmoid, and rectal cancer remain unclear. Methods: We analyzed death certificate data from CDC WONDER from 1999 to 2020. We calculated age-adjusted mortality rates (AAMR) per 100,000 individuals of CRC and its different subtypes and examined the trends over time by estimating the average annual percent change (AAPC) using the Joinpoint Regression Program. Results: From 1999 to 2020, 1,166,099 deaths were attributed to CRC, of which 957,182 deaths (82.08%) were due to colon cancer, 148,862 deaths (12.77%) from rectal cancer, and 60,055 deaths (5.15%) from rectosigmoid cancer. The overall CRC rates decreased significantly from 26.42 (95% CI, 26.20-26.64) to 15.98 (95% CI, 15.84-16.12) per 100,000 individuals, with AAPC of -2.41 (95% CI, -2.55, -2.27). However, the AAMR of rectosigmoid cancer increased significantly from 0.82 (95% CI, 0.78 -0.86) to 1.08 (95% CI, 1.04-1.11) per 100,000 individuals and the AAMR of right-sided colon cancer increased from 0.57 (95% CI, 0.54-0.60) to 0.70 (95% CI, 0.67-0.73) per 100,000 individuals, with AAPC of +1.10 (95%, 0.21-2.00) and +2.06 (95% CI, 0.85 - 3.27) respectively. Men had higher AAMR of CRC than women (23.90 [95% CI, 23.84-23.96] vs. 17.03 [95% CI, 16.99-17.08] per 100,000 individuals). African Americans had the highest AAMR of CRC (26.93 [95% CI, 26.79-27.07]), followed by Whites (19.60 [95%, 19.56-19.64] per 100,000 individuals), American Indians (14.53 [95%, 14.15-14.92] per 100,000 individuals), and Asians (13.04 [95%, 12.89-13.19] per 100,000 individuals). The overall AAMR of CRC decreased for those aged ≥ 50 years but increased significantly from 1.02 to 1.58 per 100,000 individuals for those aged 15-49 years, with an AAPC of +0.75. The AAMR from CRC was the highest in the Midwest (21.04 [95% CI, 20.96-21.12] per 100,000 individuals), followed by the South (20.51 [95% CI, 20.44-20.57]), the Northeast (20.30 [95% CI, 20.22-20.38] per 100,000 individuals), and the West (18.03 [95% CI, 17.95-18.10] per 100,000 individuals). Rural populations had higher AAMR than urban populations (22.40 [95% CI, 22.30-22.49] vs. 19.60 [95%, 19.56-19.64] per 100,000 individuals). Conclusions: Although overall CRC mortality declined, there were rising trends in young-onset CRC, rectosigmoid cancer, and right-sided colon cancer. Disparities persist in terms of sex, race, geographic region, and urbanization level, emphasizing the need for targeted public health measures.

Charting heterogeneity and spatial landscape of consensus molecular subtypes in colorectal cancer.

e15647 Background: High inter-patient heterogeneity and spatial diversity within tumors represent significant challenges to improving outcomes in colorectal cancer (CRC). Despite elucidation of consensus molecular subtypes (CMS), little progress has been made in translating this knowledge into clinical gain. Intratumoral CMS heterogeneity remains a relatively unexplored area and understanding of the interplay between subtypes holds promise for improving prognostication. We leverage spatial transcriptomics (ST) to enhance understanding of CMS heterogeneity and spatial distribution, with the goal of advancing personalized therapy through high resolution molecular sub-typing. Methods: ST using the 10x Genomics Visium platform was performed on paraffin-embedded CRC specimens for which comprehensive clinicopathological and long-term clinical outcome data were available. ST data were deconvoluted with respect to CMS single-cell RNA sequencing (scRNA-seq) data, yielding maps of CMS landscapes at a resolution of 55 microns. A pre-trained deep learning model was used to identify distinct CRC tissue classes (tumor epithelium, stroma, etc.) within H&amp;E images, enabling spatial correlation of histomorphology with CMS. Cellular composition within these CMS maps was quantified through deconvolution of six major cell types using reference scRNA-seq data. Pseudo-bulk samples were generated from the ST data to evaluate CMS behaviors and compute pathway activities. Results: 40 CRC patients were assayed using ST and H&amp;E profiling (13, 8, 14, and 5 from stages 1-4, respectively). Median follow-up was 112 months (Range 1–192). Intratumoral CMS heterogeneity was evident in all patients, with diverse CMS compositions. Using Simpson diversity index to quantify this heterogeneity, we observed significant correlation of heterogeneity with disease specific survival (DSS) (p = .03). CMS landscapes displayed spatial patterns that were distinct among tissue categories (average F1-score: testing = .92, validation = .89. Tissue categories based on deep learning from H&amp;E images). Tumors with higher levels of CMS1 or 4 were associated with worse outcome. Stratification by the composite CMS biomarker (CMS1+CMS4)/(CMS2+CMS3) yielded significant separation of the Kaplan-Meier curve for DSS (p = .018). Conclusions: This study demonstrates that CRC tumors contain significant intratumoral CMS heterogeneity that is not detectable using bulk classification methods. Spatial patterns in CMS transcriptional topographies correlate with H&amp;E-derived morphology, suggesting the potential for estimating CMS composition from histopathological features. Importantly, we show that spatially composite CMS-derived biomarkers possess strong prognostic potential. The capacity to decode CMS topographic patterns and associate these with clinical outcome offers great potential to advance personalized therapy for CRC.

Lectin microarray based glycan profiling of exosomes for dynamic monitoring of colorectal cancer progression

BackgroundExosomes, as emerging biomarkers in liquid biopsies in recent years, offer profound insights into cancer diagnostics due to their unique molecular signatures. The glycosylation profiles of exosomes have emerged as potential biomarkers, offering a novel and less invasive method for cancer diagnosis and monitoring. Colorectal cancer (CRC) represents a substantial global health challenge and burden. Thus there is a great need for the aberrant glycosylation patterns on the surface of CRC cell-derived exosomes, proposing them as potential biomarkers for tumor characterization. ResultsThe interactions of 27 lectins with exosomes from three CRC cell lines (SW480, SW620, HCT116) and one normal colon epithelial cell line (NCM460) have been analyzed by the lectin microarray. The result indicates that Ulex Europaeus Agglutinin I (UEA-I) exhibits high affinity and specificity towards exosomes derived from SW480 cells. The expression of glycosylation related genes within cells has been analyzed by high-throughput quantitative polymerase chain reaction (HT-qPCR). The experimental result of HT-qPCR is consistent with that of lectin microarray. Moreover, the limit of detection (LOD) of UEA-I microarray is calculated to be as low as 2.7 × 105 extracellular vehicles (EVs) mL−1 (three times standard deviation (3σ) of blank sample). The UEA-I microarray has been successfully utilized to dynamically monitor the progression of tumors in mice-bearing SW480 CRC subtype, applicable in tumor sizes ranging from 2 mm to 20 mm in diameter. SignificanceThe results reveal that glycan expression pattern of exosome is linked to specific CRC subtypes, and regulated by glycosyltransferase and glycosidase genes of mother cells. Our findings illuminate the potential of glycosylation molecules on the surface of exosomes as reliable biomarkers for diagnosis of tumor at early stage and monitoring of cancer progression.

An Updated Review on Molecular Biomarkers in Diagnosis and Therapy of Colorectal Cancer.

Colorectal cancer is one of the most common cancer types worldwide. Since colorectal cancer takes time to develop, its incidence and mortality can be treated effectively if it is detected in its early stages. As a result, non-invasive or invasive biomarkers play an essential role in the early diagnosis of colorectal cancer. Many experimental studies have been carried out to assess genetic, epigenetic, or protein markers in feces, serum, and tissue. It may be possible to find biomarkers that will help with the diagnosis of colorectal cancer by identifying the genes, RNAs, and/or proteins indicative of cancer growth. Recent advancements in the molecular subtypes of colorectal cancer, DNA methylation, microRNAs, long noncoding RNAs, exosomes, and their involvement in colorectal cancer have led to the discovery of novel biomarkers. In small-scale investigations, most biomarkers appear promising. However, large-scale clinical trials are required to validate their effectiveness before routine clinical implementation. Hence, this review focuses on small-scale investigations and results of big data analysis that may provide an overview of the biomarkers for the diagnosis, therapy, and prognosis of colorectal cancer.

Immune checkpoint inhibitors for POLE or POLD1 proofreading-deficient metastatic colorectal cancer

POLE and POLD1 proofreading deficiency (POLE/D1pd) define a rare subtype of ultramutated metastatic colorectal cancer (mCRC; over 100 mut/Mb). Disease-specific data about the activity and efficacy of immune checkpoint inhibitors (ICIs) in POLE/D1pd mCRC are lacking and it is unknown whether outcomes may be different from mismatch repair-deficient (dMMR)/microsatellite instability-high (MSI-H) mCRCs treated with ICIs. In this global study, we collected 27 patients with mCRC harboring POLE/D1 mutations leading to proofreading deficiency and treated with anti-programmed cell death-ligand 1 alone+/- anti-cytotoxic T-lymphocyte antigen-4 agents. We collected clinicopathological and genomic characteristics, response, and survival outcomes after ICIs of POLE/D1pd mCRC and compared them with a cohort of 610 dMMR/MSI-H mCRC patients treated with ICIs. Further genomic analyses were carried out in an independent cohort of 7241 CRCs to define POLE and POLD1pd molecular profiles and mutational signatures. POLE/D1pd was associated with younger age, male sex, fewer RAS/BRAF driver mutations, and predominance of right-sided colon cancers. Patients with POLE/D1pd mCRC showed a significantly higher overall response rate (ORR) compared to dMMR/MSI-H mCRC (89% versus 54%; P= 0.01). After a median follow-up of 24.9 months (interquartile range: 11.3-43.0 months), patients with POLE/D1pd showed a significantly superior progression-free survival (PFS) compared to dMMR/MSI-H mCRC [hazard ratio (HR)= 0.24, 95% confidence interval (CI) 0.08-0.74, P= 0.01] and superior overall survival (OS) (HR= 0.38, 95% CI 0.12-1.18, P= 0.09). In multivariable analyses including the type of DNA repair defect, POLE/D1pd was associated with significantly improved PFS (HR= 0.17, 95% CI 0.04-0.69, P=0.013) and OS (HR= 0.24, 95% CI 0.06-0.98, P= 0.047). Molecular profiling showed that POLE/D1pd tumors have higher tumor mutational burden (TMB). Responses were observed in both subtypes and were associated with the intensity of POLE/D1pd signature. Patients with POLE/D1pd mCRC showed more favorable outcomes compared to dMMR/MSI-H mCRC to treatment with ICIs in terms of tumor response and survival.

Integrating spatial and single-cell transcriptomics reveals tumor heterogeneity and intercellular networks in colorectal cancer

Single cell RNA sequencing (scRNA-seq), a powerful tool for studying the tumor microenvironment (TME), does not preserve/provide spatial information on tissue morphology and cellular interactions. To understand the crosstalk between diverse cellular components in proximity in the TME, we performed scRNA-seq coupled with spatial transcriptomic (ST) assay to profile 41,700 cells from three colorectal cancer (CRC) tumor-normal-blood pairs. Standalone scRNA-seq analyses revealed eight major cell populations, including B cells, T cells, Monocytes, NK cells, Epithelial cells, Fibroblasts, Mast cells, Endothelial cells. After the identification of malignant cells from epithelial cells, we observed seven subtypes of malignant cells that reflect heterogeneous status in tumor, including tumor_CAV1, tumor_ATF3_JUN | FOS, tumor_ZEB2, tumor_VIM, tumor_WSB1, tumor_LXN, and tumor_PGM1. By transferring the cellular annotations obtained by scRNA-seq to ST spots, we annotated four regions in a cryosection from CRC patients, including tumor, stroma, immune infiltration, and colon epithelium regions. Furthermore, we observed intensive intercellular interactions between stroma and tumor regions which were extremely proximal in the cryosection. In particular, one pair of ligands and receptors (C5AR1 and RPS19) was inferred to play key roles in the crosstalk of stroma and tumor regions. For the tumor region, a typical feature of TMSB4X-high expression was identified, which could be a potential marker of CRC. The stroma region was found to be characterized by VIM-high expression, suggesting it fostered a stromal niche in the TME. Collectively, single cell and spatial analysis in our study reveal the tumor heterogeneity and molecular interactions in CRC TME, which provides insights into the mechanisms underlying CRC progression and may contribute to the development of anticancer therapies targeting on non-tumor components, such as the extracellular matrix (ECM) in CRC. The typical genes we identified may facilitate to new molecular subtypes of CRC.

Investigation of ENO2 as a promising novel marker for the progression of colorectal cancer with microsatellite instability-high

BackgroundMicrosatellite instability-high (MSI-H) has emerged as a significant biological characteristic of colorectal cancer (CRC). Studies reported that MSI-H CRC generally had a better prognosis than microsatellite stable (MSS)/microsatellite instability-low (MSI-L) CRC, but some MSI-H CRC patients exhibited distinctive molecular characteristics and experienced a less favorable prognosis. In this study, our objective was to explore the metabolic transcript-related subtypes of MSI-H CRC and identify a biomarker for predicting survival outcomes.MethodsSingle-cell RNA sequencing (scRNA-seq) data of MSI-H CRC patients were obtained from the Gene Expression Omnibus (GEO) database. By utilizing the copy number variation (CNV) score, a malignant cell subpopulation was identified at the single-cell level. The metabolic landscape of various cell types was examined using metabolic pathway gene sets. Subsequently, functional experiments were conducted to investigate the biological significance of the hub gene in MSI-H CRC. Finally, the predictive potential of the hub gene was assessed using a nomogram.ResultsThis study revealed a malignant tumor cell subpopulation from the single-cell RNA sequencing (scRNA-seq) data. MSI-H CRC was clustered into two subtypes based on the expression profiles of metabolism-related genes, and ENO2 was identified as a hub gene. Functional experiments with ENO2 knockdown and overexpression demonstrated its role in promoting CRC cell migration, invasion, glycolysis, and epithelial-mesenchymal transition (EMT) in vitro. High expression of ENO2 in MSI-H CRC patients was associated with worse clinical outcomes, including increased tumor invasion depth (p = 0.007) and greater likelihood of perineural invasion (p = 0.015). Furthermore, the nomogram and calibration curves based on ENO2 showed potential prognosis predictive performance.ConclusionOur findings suggest that ENO2 serves as a novel prognostic biomarker and is associated with the progression of MSI-H CRC.

Differential expression of angiogenesis-related genes ‘VEGF’ and ‘angiopoietin-1’ in metastatic and EMAST-positive colorectal cancer patients

Abnormal angiogenesis leads to tumor progression and metastasis in colorectal cancer (CRC). This study aimed to elucidate the association between angiogenesis-related genes, including VEGF-A, ANGPT-1, and ANGPT-2 with both metastatic and microsatellite alterations at selected tetranucleotide repeats (EMAST) subtypes of CRC. We conducted a thorough assessment of the ANGPT-1, ANGPT-2, and VEGF-A gene expression utilizing publicly available RNA sequencing and microarray datasets. Then, the experimental validation was performed in 122 CRC patients, considering their disease metastasis and EMAST+/− profile by using reverse transcription polymerase chain reaction (RT-PCR). Subsequently, a competing endogenous RNA (ceRNA) network associated with these angiogenesis-related genes was constructed and analyzed. The expression level of VEGF-A and ANGPT-2 genes were significantly higher in tumor tissues as compared with normal adjacent tissues (P-value < 0.001). Nevertheless, ANGPT-1 had a significantly lower expression in tumor samples than in normal colon tissue (P-value < 0.01). We identified a significantly increased VEGF-A (P-value = 0.002) and decreased ANGPT-1 (P-value = 0.04) expression in EMAST+ colorectal tumors. Regarding metastasis, a significantly increased VEGF-A and ANGPT-2 expression (P-value = 0.001) and decreased ANGPT-1 expression (P-value < 0.05) were established in metastatic CRC patients. Remarkably, co-expression analysis also showed a strong correlation between ANGPT-2 and VEGF-A gene expressions. The ceRNA network was constructed by ANGPT-1, ANGPT-2, VEGF-A, and experimentally validated miRNAs (hsa-miR-190a-3p, hsa-miR-374c-5p, hsa-miR-452-5p, and hsa-miR-889-3p), lncRNAs (AFAP1-AS1, KCNQ1OT1 and MALAT1), and TFs (Sp1, E2F1, and STAT3). Network analysis revealed that colorectal cancer is amongst the 82 significant pathways. We demonstrated a significant differential expression of VEGF-A and ANGPT-1 in colorectal cancer patients exhibiting the EMAST+ phenotype. This finding provides novel insights into the molecular pathogenesis of colorectal cancer, specifically in EMAST subtypes. Yet, the generalization of in silico findings to EMAST+ colorectal cancer warrants future experimental investigations. In the end, this study proposes that the EMAST biomarker could serve as an additional perspective on CMS4 biology which is well-defined by activated angiogenesis and worse overall survival.

Chemokine‑ and chemokine receptor-based subtypes predict prognosis, immunotherapy and chemotherapy response in colorectal cancer patients

BackgroundThe clinical significance and comprehensive characteristics of chemokines and chemokine receptors in colorectal cancer (CRC) have not been previously reported. Our study aims to investigate the expression profiles of chemokines and chemokine receptors, as well as establish subtypes in CRC. Methods1009 CRC samples were enrolled in our study. Consensus unsupervised clustering analysis was conducted to establish subtypes, and a risk score model was developed using univariate Cox regression and least absolute shrinkage and selection operator (LASSO) analyses. 36 pairs of tissue specimens of CRC patients and two CRC cell lines were used to validate the subtypes and risk score in vitro. Quantitative real-time PCR and western blotting were employed to validate mRNA and protein expression levels, respectively. Flow cytometry was utilized for analyzing cell apoptosis, while cell viability assay and EdU assay were conducted to assess cell proliferation ability. ResultsThe Cluster B group shares similarities with the low-risk group in terms of exhibiting a higher level of immune cell infiltration and belonging to hot tumor. Patients CRC in the Cluster B group demonstrate a more favorable prognosis and exhibit better response to immunotherapy and chemotherapy. On the other hand, the Cluster A group resembles the high-risk group as it displays lower levels of immune cell infiltration, indicating a cold tumor phenotype. CRC patients in the Cluster A group have poorer prognoses and show less therapeutic efficacy towards immunotherapy and chemotherapy. Furthermore, we utilized a total of 36 pairs of tissue samples obtained from patients with CRC, along with two CRC cell lines for validation in vitro. This comprehensive approach further enhances the scientific validity and reliability of the identified subtypes and risk score in their ability to predict prognosis, response to immunotherapy, and response to chemotherapy among CRC patients. ConclusionWe first established robust prognostic subtypes based on chemokines and chemokine receptors, which could potentially serve as a novel biomarker for guiding individualized treatment in patients with CRC undergoing immunotherapy and chemotherapy.

Integrating single-cell and spatial analysis reveals MUC1-mediated cellular crosstalk in mucinous colorectal adenocarcinoma.

Mucinous colorectal adenocarcinoma (MCA) is a distinct subtype of colorectal cancer (CRC) with the most aggressive pattern, but effective treatment of MCA remains a challenge due to its vague pathological characteristics. An in-depth understanding of transcriptional dynamics at the cellular level is critical for developing specialised MCA treatment strategies. We integrated single-cell RNA sequencing and spatial transcriptomics data to systematically profile the MCA tumor microenvironment (TME), particularly the interactome of stromal and immune cells. In addition, a three-dimensional bioprinting technique, canonical ex vivo co-culture system, and immunofluorescence staining were further applied to validate the cellular communication networks within the TME. This study identified the crucial intercellular interactions that engaged in MCA pathogenesis. We found the increased infiltration of FGF7+/THBS1+ myofibroblasts in MCA tissues with decreased expression of genes associated with leukocyte-mediated immunity and T cell activation, suggesting a crucial role of these cells in regulating the immunosuppressive TME. In addition, MS4A4A+ macrophages that exhibit M2-phenotype were enriched in the tumoral niche and high expression of MS4A4A+was associated with poor prognosis in the cohort data. The ligand-receptor-based intercellular communication analysis revealed the tight interaction of MUC1+ malignant cells and ZEB1+ endothelial cells, providing mechanistic information for MCA angiogenesis and molecular targets for subsequent translational applications. Our study provides novel insights into communications among tumour cells with stromal and immune cells that are significantly enriched in the TME during MCA progression, presenting potential prognostic biomarkers and therapeutic strategies for MCA. Tumour microenvironment profiling of MCA is developed. MUC1+ tumour cells interplay with FGF7+/THBS1+ myofibroblasts to promote MCA development. MS4A4A+ macrophages exhibit M2 phenotype in MCA. ZEB1+ endotheliocytes engage in EndMT process in MCA.

Exploiting a subtype-specific mitochondrial vulnerability for successful treatment of colorectal peritoneal metastases

Peritoneal metastases (PMs) from colorectal cancer (CRC) respond poorly to treatment and are associated with unfavorable prognosis. For example, the addition of hyperthermic intraperitoneal chemotherapy (HIPEC) to cytoreductive surgery in resectable patients shows limited benefit, and novel treatments are urgently needed. The majority of CRC-PMs represent the CMS4 molecular subtype of CRC, and here we queried the vulnerabilities of this subtype in pharmacogenomic databases to identify novel therapies. This reveals the copper ionophore elesclomol (ES) as highly effective against CRC-PMs. ES exhibits rapid cytotoxicity against CMS4 cells by targeting mitochondria. We find that a markedly reduced mitochondrial content in CMS4 cells explains their vulnerability to ES. ES demonstrates efficacy in preclinical models of PMs, including CRC-PMs and ovarian cancer organoids, mouse models, and a HIPEC rat model of PMs. The above proposes ES as a promising candidate for the local treatment of CRC-PMs, with broader implications for other PM-prone cancers.

Weighting estimation in the cause-specific Cox regression with partially missing causes of failure.

Complex diseases are often analyzed using disease subtypes classified by multiple biomarkers to study pathogenic heterogeneity. In such molecular pathological epidemiology research, we consider a weighted Cox proportional hazard model to evaluate the effect of exposures on various disease subtypes under competing-risk settings in the presence of partially or completely missing biomarkers. The asymptotic properties of the inverse and augmented inverse probability-weighted estimating equation methods are studied with a general pattern of missing data. Simulation studies have been conducted to demonstrate the double robustness of the estimators. For illustration, we applied this method to examine the association between pack-years of smoking before the age of 30 and the incidence of colorectal cancer subtypes defined by a combination of four tumor molecular biomarkers (statuses of microsatellite instability, CpG island methylator phenotype, BRAF mutation, and KRAS mutation) in the Nurses' Health Study cohort.

Clinicopathological characteristics of Lynch-like syndrome.

Lynch-like syndrome (LLS) has recently been proposed as a third type of microsatellite instability (MSI) tumor after Lynch syndrome (LS) and sporadic MSI colorectal cancer (CRC) without either a germline variant of mismatch repair (MMR) genes or hypermethylation of the MLH1 gene. The present study aimed to clarify and compare the clinicopathological characteristics of LLS with those of the other MSI CRC subtypes. In total, 2634 consecutive patients with CRC who underwent surgical resection and subsequently received universal tumor screening (UTS), including MSI analysis were enrolled between January 2008 and November 2019. Genetic testing was performed in patients suspected of having Lynch syndrome. UTS of the cohort found 146 patients with MSI CRC (5.5%). Of these, excluding sporadic MSI CRC, 30 (1.1%) had a diagnosis of LS, and 19 (0.7%) had no germline pathogenic variants of the MMR gene. The CRC type in the latter group was identified as LLS. LLS occurred significantly more often in young patients, was left-sided, involved a KRAS variant and BRAF wild-type, and had a higher concordance rate with the Revised Bethesda Guidelines than sporadic MSI CRC. No significant differences were observed in terms of the clinicopathological factors between LLS and LS-associated MSI CRC; however, LLS had a lower frequency of LS-related neoplasms compared with LS. Distinguishing clinically between LS and LLS was challenging, but the incidence of neoplasms was higher in LS than in LLS, suggesting the need for different screening and surveillance methods for the two subtypes.