SPP1+ macrophages have been identified as key players in the colorectal cancer (CRC) tumor microenvironment, but their function remains unclear. This study integrated single-cell and spatial transcriptomics with bulk sequencing to investigate the roles and mechanisms of SPP1 + macrophages in CRC. Our findings revealed a pronounced elevation of SPP1 + macrophages in CRC, especially within tumor territories. These macrophages served as markers for CRC initiation, progression, metastasis, and potential prognosis. Furthermore, they showed heightened transcriptional activity in genes linked to angiogenesis, epithelial-mesenchymal transition, glycolysis, hypoxia, and immunosuppression. SPP1 protein amplified CRC cell migration and invasion, potentially mediating cellular crosstalk via the SPP1-CD44, SPP1-PTGER4, and SPP1-a4b1 complex axes. Patients with a high proportion of SPP1 + macrophages could benefit more from immune checkpoint blockade therapy. Interestingly, CSF1R expression was significantly enriched in C1QC + macrophages versus SPP1 + macrophages, possibly explaining limited anti-CSF1R monotherapy effects. In conclusion, we propose an SPP1 + macrophage model in CRC, highlighting such macrophages as a promising therapeutic target due to their malignancy markers.

The role of laminin receptors in colorectal cancer (CRC) is the subject of ongoing research. Histopathological studies have suggested that the 67 kDa laminin receptor (67LR) is involved in the carcinogenesis of various malignancies, including CRC. However, the exact composition and nature of 67LR have been a source of confusion for many years. A recent study from our group reported that the 37 kDa form of RPSA participates as a laminin receptor renamed the RPSA-containing laminin receptor (RCLR) but is not the precursor form of the 67LR since the 67 kDa protein associated with 67LR corresponds to the 67 kDa elastin-binding protein (67EBP), which also acts as a laminin receptor. The present study aims to analyze the distinct expression patterns of these two laminin receptor components in CRC. Expressions of RCLR and 67EBP were analyzed in CRC tissues using Western blot and quantitative RT-PCR analyses. The primary colorectal adenocarcinoma tissues and corresponding resection margins showed an overexpression of both RPSA and 67EBP at the protein level in the CRC tissues. An analysis of the publicly available CRC datasets confirmed the overexpression of RPSA and 67EBP in CRC tissues. In conclusion, the elevated expression of these two non-integrin laminin receptors in CRC lesions suggests their critical roles in colorectal carcinogenesis and emphasizes their potential usefulness as tissue biomarkers.

Colorectal cancer (CRC) is one of the major cancer types associated with increased mortality worldwide. Hence, identifying reliable biomarkers make it very essential for early diagnosis and prognosis of CRC. Numerous studies have been conducted to decipher molecular mechanisms underlying CRC, however more deep insightful knowledge is the need of the hour. The purpose of this study was to identify promising key candidate genes in colorectal cancer (CRC) and assess their expression and clinical significance. To clarify and verify promising key biomarkers with signal transduction pathways in colorectal cancer, we integrated 11 microarray datasets from NCBI-GEO. This study utilized multiple bioinformatics tools and databases, including OncoDB, GEO2R, UALCAN, GEIPA, TIMER, and DAVID. The gene expression profiles of eleven datasets (GSE10714, GSE113513, GSE13471, GSE15960, GSE24514, GSE32323, GSE41258, GSE4183, GSE44076, GSE44861, GSE9348) were screened. In 11 gene expression profiles, 3 downregulated genes were identified and validated by databases such as OncoDB, UALCAN, GEIPA and TIMER. Downregulation of SLC4A4 with significant predictive value was validated by multi-omic data analysis and validated by Gene Expression Omnibus (GEO). GEIPA survival analysis showed that low SLC4A4 expression correlated with poorer overall survival among CRC patients. Based on this study, we identified SLC4A4 as a potential candidate biomarker for colorectal cancer (CRC), enabling early diagnosis and prognosis with molecular targeted therapy.

The role of cancer-associated fibroblasts (CAFs) in modulating the tumor microenvironment (TME) is gaining attention, yet their impact on prognosis and therapeutic response in colon cancer remains unclear. Here, we identified genes associated with CAF infiltration via weighted gene co-expression network analysis (WGCNA) utilizing data from The Cancer Genome Atlas (TCGA) and GSE39582 cohorts. Univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses were used to construct CAF molecular signatures (CAFscore). Patients were categorized into high and low CAFscore groups to analyze clinicopathological traits, somatic mutations, immune evasion, and treatment responses. In this study, a total of 244 genes were correlated with CAF infiltration, with 11 linked to overall survival. Notably, FSTL3, CRIP2, and SLC2A3 were selected for the CAFscore. A higher CAFscore was associated with poorer prognoses, increased malignancy, and therapeutic resistance, particularly among patients with high tumor mutation burden and microsatellite instability. Furthermore, elevated FSTL3 expression was associated with reduced CD8+ T cell infiltration, indicating a suppressive TME. Mechanistically, CAFs may promote immune evasion via NAMPT ligand-receptor interactions based on single-cell RNA sequencing data. Thus, the CAFscore is crucial for personalizing treatment strategies and identifying patients who require more aggressive management.

FOLFIRI, a combination of folinic acid, 5-fluorouracil, and irinotecan, is one of the recommended first-line chemotherapeutic treatments for metastatic colorectal cancer. Unfortunately, acquired FOLFIRI resistance represents a common obstacle in the treatment of metastatic colorectal cancer patients. Thus, we aimed to identify mechanisms, gene alterations, and gene expression signatures contributing to acquired FOLFIRI resistance by mimicking this problem in a cell culture model and subsequent translation in clinical data sets. Three FOLFIRI-resistant colorectal cancer (CRC) cell lines were established by continuous FOLFIRI treatment. Comparative mutation screening (161 genes) and transcriptomics (pathway and differential expression analyses) were performed in parental and resistant cells. Data reconciliation was performed in GSE62322, a clinical FOLFIRI responder data set (intrinsic resistance). Relapse-free survival (RFS) associations of identified differentially expressed genes and potential gene signatures were investigated in 8 clinical CRC data sets. No mutual genetic alterations were found in FOLFIRI-resistant derivatives. Resistant cell lines displayed activation of mitogen-activated protein kinase, immune response, and epithelial-mesenchymal transition pathways. Twelve differentially expressed genes, significantly differentially expressed in at least 2 of the 3 resistant cell lines, were identified. Comparison with GSE62322 and subsequent survival analyses revealed a 5-gene FOLFIRI signature comprised of CAV2, TNC, TACSTD2, SERPINE2, and PERP that was associated with RFS in multiple data sets including the cancer genome atlas CRC (hazard ratio [HR] =2.634, P = 4.53 × 10-6), in pooled samples of all data sets (all stages [N = 1981]: HR = 1.852, P = 6.44 × 10-13; stage IV [N = 260]: HR = 2.462, P = 5.22 × 10-9). A multivariate Cox regression analysis identified the 5-gene signature as an independent prognostic factor in the cancer genome atlas data set (HR = 1.89, P = .0202). Our analyses revealed a 5-gene FOLFIRI resistance signature associated with RFS that may help predict FOLFIRI resistance and thus avoid unnecessary ineffective treatment. Signature members might also represent targets to fight FOLFIRI resistance.

Our work demonstrates that the bidirectional interplay between sympathetic nerves and NGF-expressing CAFs drives colorectal tumorigenesis. This study also offers novel mechanistic insights into catecholamine action in colorectal cancer. Inhibiting the neuro-mesenchymal interaction by TRK blockade could be a potential strategy for treating colorectal cancer.

The cell adhesion molecule L1CAM (L1), mainly known for its function in brain cells, is a Wnt/β-catenin signaling target gene in colorectal cancer (CRC) cells, where it promotes invasion and liver metastasis. We interrogated which genes are expressed at increased levels in human CRC tissue and induced in CRC cell lines overexpressing L1. We found increased cyclin D2 levels in CRC tissue and LS 174T and HCT 116 human CRC cells overexpressing L1. Increased cyclin D2 in CRC cells was associated with higher proliferation rates, faster motility, tumorigenesis, and liver metastasis. The suppression of cyclin D2 expression by shRNA to cyclin D2 blocked the increase in these cellular properties of L1-expressing cells. The overexpression of cyclin D2 in the absence of L1 also conferred tumorigenic properties similar to L1 expression. The pathways involved in the elevation of cyclin D2 by L1 include NF-κB, Akt, and β-catenin signaling but not the Erk pathway. We found that in a significant percentage of human CRC tissue samples, cyclin D2 is expressed at high levels in the nuclei of cancer cells. At the same time, the adjacent normal mucosa was negative for cyclin D2 staining. The results suggest that the increased cyclin D2 expression by L1 is required to induce proliferative, motile tumor development in CRC tissue and can serve as a diagnostic marker and a target for CRC therapy.

Chemokines are integral components of the immune system and deeply involved in the pathogenesis and progression of inflammatory bowel disease (IBD) and colorectal cancer (CRC). Although a considerable amount of transcriptome data has been accumulated on these diseases, most of them are limited to a specific stage of the disease. The purpose of this study is to visually demonstrate the dynamic changes in chemokines across various stages of bowel diseases by integrating relevant datasets. Integrating the existing datasets for IBD and CRC, we compare the expression changes of chemokines across different pathological stages. This study collected 11 clinical databases from various medical centers around the world. Patients: Data of patient tissue types were classified into IBD, colorectal adenoma, primary carcinoma, metastasis, and healthy control according to the publisher's annotation. The expression changes in chemokines in various pathological stages are statistically analyzed. The chemokines were clustered by different expression patterns. The chemokine family was clustered into four distinct expression patterns, which correspond to varying expression changes in different stages of colitis and tumor development. Certain chemokines and receptors associated with inflammation and tumorigenesis have been identified. Furthermore, it was confirmed that the 2,4,6-trinitrobenzenesulfonic acid (TNBS)-induced colitis model and the azoxymethane (AOM)/ dextran sulfate sodium (DSS)-induced colon cancer model shows stronger correlations with the clinical data in terms of chemokine expression levels. This study paints a panoramic picture of the expression profiles of chemokine families at multiple stages from IBD to advanced colon cancer, facilitating a comprehensive understanding of the regulation patterns of chemokines and guiding the direction of drug development. This study provides researchers with a clear atlas of chemokine expression in the pathological processes of inflammatory bowel disease and colon cancer.

Aging of the male prostate is an inevitable process in which the prostate undergoes hyperplasia, and this growth may lead to compression of the urethra, resulting in voiding dysfunction and associated symptoms, and an increased risk of prostate cancer. Despite the significance of prostate aging, the molecular mechanisms involved are still not fully understood.

Prostate split by lobes from young (2 months) and aged (24 months) mice were collected for single-cell RNA sequencing (scRNA-seq) analysis. Tissues from both anterior prostate (AP) and ventral/dorsal/lateral prostate (VDLP) were included in the study. Data analysis included unsupervised clustering using the uniform manifold approximation and projection (UMAP) algorithm to identify distinct cell types based on marker gene expression. Differential gene expression analysis was performed to identify age-related changes in gene expression across different cell types. Functional enrichment analysis was conducted to elucidate biological pathways associated with differentially expressed genes. Additionally, cellular interactions and developmental trajectories were analyzed to characterize cellular dynamics during prostate aging.

The single-cell transcriptome analysis of the mouse prostate during aging revealed heterogeneity across various cell types and their changes during the aging process. We found a significant increase in the proportion of mesenchymal and immune cells in aged mice. Our study unveiled alterations in genes and pathways associated with cellular senescence, oxidative stress, and regeneration in epithelial cells. Furthermore, we observed that basal cells may undergo epithelial-mesenchymal transition (EMT) to become mesenchymal cells, particularly prominent in aged mice. Additionally, immune cells, notably macrophages and T cells, exhibited a heightened inflammatory response in aged mice.

In summary, our study provides a comparative analysis of the single-cell transcriptome of the aged and young mice prostates, elucidating cellular and molecular changes between the aged and young mice prostates.

The mitochondrial Ca2+ uniporter (MCU) plays crucial role in intramitochondrial Ca2+ uptake, allowing Ca2+-dependent activation of oxidative metabolism. In recent decades, the role of MCU pore-forming proteins has been highlighted in cancer. However, the contribution of MCU-associated regulatory proteins mitochondrial calcium uptake 1 and 2 (MICU1 and MICU2) to pathophysiological conditions has been poorly investigated. Here, we describe the role of MICU2 in cell proliferation and invasion using in vitro and in vivo models of human colorectal cancer (CRC). Transcriptomic analysis demonstrated an increase in MICU2 expression and the MICU2/MICU1 ratio in advanced CRC and CRC-derived metastases. We report that expression of MICU2 is necessary for mitochondrial Ca2+ uptake and quality of the mitochondrial network. Our data reveal the interplay between MICU2 and MICU1 in the metabolic flexibility between anaerobic glycolysis and OXPHOS. Overall, our study sheds light on the potential role of the MICUs in diseases associated with metabolic reprogramming.

Most COVID-19 patients have a positive prognosis, but patients with additional underlying diseases are more likely to have severe illness and increased fatality rates. Numerous studies indicate that cancer patients are more prone to contract SARS-CoV-2 and develop severe COVID-19 or even dying. In the recent transcriptome investigations, it is demonstrated that the fructose metabolism is altered in patients with SARS-CoV-2 infection. However, cancer cells can use fructose as an extra source of energy for growth and metastasis. Furthermore, enhanced living conditions have resulted in a notable rise in fructose consumption in individuals' daily dietary habits. We therefore hypothesize that the poor prognosis of cancer patients caused by SARS-CoV-2 may therefore be mediated through fructose metabolism. Using CRC cases from four distinct cohorts, we built and validated a predictive model based on SARS-CoV-2 producing fructose metabolic anomalies by coupling Cox univariate regression and lasso regression feature selection algorithms to identify hallmark genes in colorectal cancer. We also developed a composite prognostic nomogram to improve clinical practice by integrating the characteristics of aberrant fructose metabolism produced by this novel coronavirus with age and tumor stage. To obtain the genes with the greatest potential prognostic values, LASSO regression analysis was performed, In the TCGA training cohort, patients were randomly separated into training and validation sets in the ratio of 4: 1, and the best risk score value for each sample was acquired by lasso regression analysis for further analysis, and the fifteen genes CLEC4A, FDFT1, CTNNB1, GPI, PMM2, PTPRD, IL7, ALDH3B1, AASS, AOC3, SEPINE1, PFKFB1, FTCD, TIMP1 and GATM were finally selected. In order to validate the model's accuracy, ROC curve analysis was performed on an external dataset, and the results indicated that the model had a high predictive power for the prognosis prediction of patients. Our study provides a theoretical foundation for the future targeted regulation of fructose metabolism in colorectal cancer patients, while simultaneously optimizing dietary guidance and therapeutic care for colorectal cancer patients in the context of the COVID-19 pandemic.

Colorectal cancer is a predominant contributor to global cancer-related morbidity and mortality. The oncogene PTOV1 has been linked to various human malignancies, yet its specific role in CRC pathogenesis requires further elucidation.

Our study used a comprehensive array of authoritative bioinformatics tools, such as TIMER, UCSC Xena, GEO, Human Protein Atlas, UALCAN, CIBERSORTx and others which used to investigate the complex effects of PTOV1 on gene expression profiles, diagnostic and prognostic biomarkers, tumor immunology, signaling pathways, epigenetic alterations, and genetic mutations. Gene expression validation was conducted using Western blot and qRT-PCR. The in vitro proliferative and migratory potentials of CRC cells were evaluated using CCK-8 assays, colony formation, and transwell migration assays, respectively. MSP was applied to assess the methylation status of the PTOV1 promoter region.

Our results reveal a significant association between increased PTOV1 expression, driven by promoter hypomethylation, and poor patient prognosis in CRC. Elevated PTOV1 levels were positively correlated with the enrichment of diverse immune cell subsets and immune-related molecules within the tumor microenvironment. In vitro assays demonstrated that PTOV1 knockdown markedly reduced CRC cell proliferation, colony formation, and migration, while ectopic PTOV1 expression had the opposite effect. Importantly, PTOV1 was shown to regulate the PI3K-AKT signaling pathway, significantly influencing the phosphorylation of AKT1 and the expression of cell cycle regulators P21 and P27. The pharmacological inhibition of AKT1 phosphorylation using MK2206 effectively counteracted the proliferative effects induced by PTOV1 overexpression.

The ability of PTOV1 to enhance CRC cell proliferation via modulation of the AKT1 signaling pathway establishes it as a potential therapeutic target and a promising biomarker for prognostic stratification in CRC.

Cuproptosis may represent a potential biomarker for predicting prognosis and immunotherapy response, but the available evidence is insufficient.

The multiple single-cell RNA sequencing (scRNA-seq) datasets were analyzed to investigate the specific occurrence of cuproptosis in distinct cell populations. Utilizing 28 scRNA-seq datasets, TCGA pan-cancer cohort, and 10 immunotherapy cohorts, we developed a cuproptosis signature (Cup.Sig). This signature was used to construct prediction models for immunotherapy response and identify potential prognostic biomarkers for pan-cancer using 11 different machine learning algorithms.

Malignant cells demonstrate the higher cuproptosis scores in comparison to other cell types across diverse cancer types. The Cup.Sig exhibits significant associations with cancer hallmarks and immune cell response in multiple cancer types. Leveraging the Cup.Sig, the robust pan-cancer immunotherapy prediction model and prognostic biomarker have been established and validated using diverse datasets from various platforms.

We developed a pan-cancer cuproptosis signature for predicting survival and immunotherapy response.

The significance of USP11 as a critical regulator in cancer has garnered substantial attention, primarily due to its catalytic activity as a deubiquitinating enzyme. Nonetheless, a thorough evaluation of USP11 across various cancer types in pan-cancer studies remains absent. Our analysis integrates data from a variety of sources, including five immunotherapy cohorts, thirty-three cohorts from The Cancer Genome Atlas (TCGA), and sixteen cohorts from the Gene Expression Omnibus (GEO), two of which involve single-cell transcriptomic data. Our findings indicate that aberrant USP11 expression is predictive of survival outcomes across various cancer types. The highest frequency of genomic alterations was observed in uterine corpus endometrial carcinoma (UCEC), with single-cell transcriptome analysis revealing significantly higher USP11 expression in plasmacytoid dendritic cells and mast cells. Notably, USP11 expression was associated with the infiltration levels of CD8+ T cells and natural killer (NK) activated cells. Additionally, in the skin cutaneous melanoma (SKCM) phs000452 cohort, patients with higher USP11 mRNA levels during immunotherapy experienced a significantly shorter median progression-free survival. USP11 emerges as a promising molecular biomarker with significant potential for predicting patient prognosis and immunoreactivity across various cancer types.

Colorectal cancer is a significant global health concern with high mortality rates. Silibinin is a compound derived from milk thistle with anticancer properties and may be a potential treatment option for colorectal cancer. Its poor solubility limits its clinical application, but various strategies, such as nanoparticle encapsulation, have shown promise. In this study, a PEGylated niosomal drug delivery system was used to enhance the solubility of silibinin, and its anti-proliferative effects were evaluated against human colorectal cancer cell lines.

The silibinin-loaded PEGylated niosomal nanoparticles (NIO-SIL) were fabricated using the thin-film hydration method and characterized with dialysis bag, AFM, SEM, DLS, and FTIR systems. Finally, the cancerous cells and human normal cells were treated with NIO-SIL and pure silibinin. The proliferation, apoptosis, and cell cycle of these cells were evaluated. Subsequently, the expression of Bax, Bcl-2, p53, and cyclin D1 genes was measured using real-time PCR.

The drug release profile, size, morphology, and chemical interactions of the synthesized PEGylated niosomal nanoparticles were suitable for use as a drug delivery system. Both pure silibinin and NIO-SIL could reduce the proliferation of cancerous cells, induce apoptosis, and cause cell cycle arrest, with no significant negative effects reported on human normal cells. Both pure silibinin and NIO-SIL reduced the expression of the Bcl-2 and cyclin D1 genes while increasing the expression of Bax and p53. (p-value < 0.05 *).

The outcomes of this study indicate the high potential of PEGylated niosomal nanoparticles for encapsulation and delivery of silibinin to cancer cells, with no negative effects on normal cells.

Copy number alterations (CNAs), resulting from the gain or loss of genetic material from as little as 50 base pairs or as big as entire chromosome(s), have been associated with many congenital diseases, de novo syndromes and cancer. It is established that CNAs disturb the dosage of genomic regions including enhancers/promoters, long non-coding RNA and gene(s) among others, ultimately leading to an altered balance of key cellular functions. In cancer, CNAs have been associated with almost all steps of the disease: predisposition, initiation, development, maintenance, response to treatment, resistance, and relapse. Therefore, understanding how specific CNAs contribute to tumourigenesis may provide prognostic insight and ultimately lead to the development of new therapeutic approaches to improve patient outcomes. In this review, we provide a snapshot of what is currently known about CNAs and cancer, incorporating topics regarding their detection, clinical impact, origin, and nature, and discuss the integration of innovative genetic engineering strategies, to highlight the potential for targeting CNAs using novel, dosage-sensitive and less toxic therapies for CNA-driven cancer.

Targeted therapies have improved outcomes for patients with metastatic colorectal cancer, but their impact is limited by rapid emergence of resistance. We hypothesized that an understanding of the underlying genetic mechanisms and intrinsic tumor features that mediate resistance to therapy will guide new therapeutic strategies and ultimately allow the prevention of resistance.

We assembled a series of 52 patients with paired pretreatment and progression samples who received therapy targeting EGFR (n = 17), BRAF V600E (n = 17), KRAS G12C (n = 15), or amplified HER2 (n = 3) to identify molecular and clinical factors associated with time on treatment (TOT).

All patients stopped treatment for progression and TOT did not vary by oncogenic driver (P = 0.5). Baseline disease burden (≥3 vs. <3 sites, P = 0.02), the presence of hepatic metastases (P = 0.02), and gene amplification on baseline tissue (P = 0.03) were each associated with shorter TOT. We found evidence of chromosomal instability (CIN) at progression in patients with baseline MAPK pathway amplifications and those with acquired gene amplifications. At resistance, copy-number changes (P = 0.008) and high number (≥5) of acquired alterations (P = 0.04) were associated with shorter TOT. Patients with hepatic metastases demonstrated both higher number of emergent alterations at resistance and enrichment of mutations involving receptor tyrosine kinases.

Our genomic analysis suggests that high baseline CIN or effective induction of enhanced mutagenesis on targeted therapy underlies rapid progression. Longer response appears to result from a progressive acquisition of genomic or chromosomal instability in the underlying cancer or from the chance event of a new resistance alteration.

Activated TGFβ signaling in the tumor microenvironment, which occurs independently of epithelial cancer cells, has emerged as a key driver of tumor progression in late-stage colorectal cancer (CRC). This study aimed to elucidate the contribution of TGFβ-activated stroma to serrated carcinogenesis, representing approximately 25% of CRCs and often characterized by oncogenic BRAF mutations. We used a transcriptional signature developed based on TGFβ-responsive, stroma-specific genes to infer TGFβ-dependent stromal activation and conducted in silico analyses in 3 single-cell RNA-seq datasets from a total of 39 CRC samples and 12 bulk transcriptomic datasets consisting of 2014 CRC and 416 precursor samples, of which 33 were serrated lesions. Single-cell analyses validated that the signature was expressed specifically by stromal cells, effectively excluding transcriptional signals derived from epithelial cells. We found that the signature was upregulated during malignant transformation and cancer progression, and it was particularly enriched in CRCs with mutant BRAF compared to wild-type counterparts. Furthermore, across four independent precursor datasets, serrated lesions exhibited significantly higher levels of TGFβ-responsive stromal activation compared to conventional adenomas. This large-scale analysis suggests that TGFβ-dependent stromal activation occurs early in serrated carcinogenesis. Our study provides novel insights into the molecular mechanisms underlying CRC development via the serrated pathway.

The cytokine tumor necrosis factor (TNF) plays a crucial role in the proliferation and metastasis of colorectal cancer (CRC) cells, but the underlying mechanisms remain poorly understood. Here, we report that chondroitin polymerizing factor 2 (CHPF2) promotes CRC cell proliferation and metastasis mediated by TNF, independently of its enzymatic activity. CHPF2 is highly expressed in CRC, and its elevated expression is associated with poor prognosis of CRC patients. Mechanistically, upon TNF stimulation, CHPF2 is phosphorylated at the T588 residue by MEK, enabling CHPF2 to interact with both TAK1 and IKKα. This interaction enhances the binding of TAK1 and IKKα, leading to increased phosphorylation of the IKK complex and activation of NF-κB signaling. As a result, the expression of early growth factors (EGR1) is upregulated to promote CRC cell proliferation and metastasis. In contrast, introduction of a phospho-deficient T588A mutation in CHPF2 weakened the interaction between CHPF2 and TAK1, thus impairing NF-κB signaling. CHPF2 T588A mutation reduced the ability of CHPF2 to promote the proliferation and metastasis of CRC in vitro and in vivo. Furthermore, the NF-κB RELA subunit promotes CHPF2 expression, further amplifying TNF-induced NF-κB signaling activation. These findings identify a moonlighting function of CHPF2 in promoting tumor cell proliferation and metastasis and provide insights into the mechanism by which CHPF2 amplifies TNF-mediated NF-κB signaling activation. Our study provides a molecular basic for the development of therapeutic strategies for CRC treatment.

Claudin-1 becomes overexpressed during the transformation of normal colonic mucosa to colorectal cancer (CRC).

Patient-derived organoids expressed clinically relevant target levels and genetic heterogeneity, and were established from human adenoma and normal colons. Colonoids were implanted orthotopically in the colon of immunocompromised mice. This pre-clinical model of CRC provides an intact microenvironment and representative vasculature. Colonoid growth was monitored using white light endoscopy. A peptide specific for claudin-1 was fluorescently labeled for intravenous administration. NIR fluorescence images were collected using endoscopy and endomicroscopy.

NIR fluorescence images collected using wide-field endoscopy showed a significantly greater target-to-background (T/B) ratio for adenoma versus normal (1.89 ± 0.35 and 1.26 ± 0.06) colonoids at 1 h post-injection. These results were confirmed by optical sections collected using endomicroscopy. Optical sections were collected in vivo with sub-cellular resolution in vertical and horizontal planes. Greater claudin-1 expression by individual epithelial cells in adenomatous versus normal crypts was visualized. A human-specific cytokeratin stain ex vivo verified the presence of human tissues implanted adjacent to normal mouse colonic mucosa.

Increased claudin-1 expression was observed from adenoma versus normal colonoids in vivo using imaging with wide field endoscopy and endomicrosopy.

The goal of this study was to use a new interpretable machine-learning framework based on max-logistic competing risk factor models to identify a parsimonious set of differentially expressed genes (DEGs) that play a pivotal role in the development of colorectal cancer (CRC). Transcriptome data from nine public datasets were analyzed, and a new Chinese cohort was collected to validate the findings. The study discovered a set of four critical DEGs - CXCL8, PSMC2, APP, and SLC20A1 - that exhibit the highest accuracy in detecting CRC in diverse populations and ethnicities. Notably, PSMC2 and CXCL8 appear to play a central role in CRC, and CXCL8 alone could potentially serve as an early-stage marker for CRC. This work represents a pioneering effort in applying the max-logistic competing risk factor model to identify critical genes for human malignancies, and the interpretability and reproducibility of the results across diverse populations suggests that the four DEGs identified can provide a comprehensive description of the transcriptomic features of CRC. The practical implications of this research include the potential for personalized risk assessment and precision diagnosis and tailored treatment plans for patients.

The cancer biomarker field has been an object of thorough investigation in the last decades. Despite this, colorectal cancer (CRC) heterogeneity makes it challenging to identify and validate effective prognostic biomarkers for patient classification according to outcome and treatment response. Although a massive amount of proteomics data has been deposited in public data repositories, this rich source of information is vastly underused. Here, we attempted to reuse public proteomics datasets with two main objectives: i) to generate hypotheses (detection of biomarkers) for their posterior/downstream validation, and (ii) to validate, using an orthogonal approach, a previously described biomarker panel. Twelve CRC public proteomics datasets (mostly from the PRIDE database) were re-analysed and integrated to create a landscape of protein expression. Samples from both solid and liquid biopsies were included in the reanalysis. Integrating this data with survival annotation data, we have validated in silico a six-gene signature for CRC classification at the protein level, and identified five new blood-detectable biomarkers (CD14, PPIA, MRC2, PRDX1, and TXNDC5) associated with CRC prognosis. The prognostic value of these blood-derived proteins was confirmed using additional public datasets, supporting their potential clinical value. As a conclusion, this proof-of-the-concept study demonstrates the value of re-using public proteomics datasets as the basis to create a useful resource for biomarker discovery and validation. The protein expression data has been made available in the public resource Expression Atlas.

Colorectal cancer exhibits dynamic cellular and genetic heterogeneity during progression from precursor lesions toward malignancy. Analysis of spatial multi-omic data from 31 human colorectal specimens enabled phylogeographic mapping of tumor evolution that revealed individualized progression trajectories and accompanying microenvironmental and clonal alterations. Phylogeographic mapping ordered genetic events, classified tumors by their evolutionary dynamics, and placed clonal regions along global pseudotemporal progression trajectories encompassing the chromosomal instability (CIN+) and hypermutated (HM) pathways. Integrated single-cell and spatial transcriptomic data revealed recurring epithelial programs and infiltrating immune states along progression pseudotime. We discovered an immune exclusion signature (IEX), consisting of extracellular matrix regulators DDR1, TGFBI, PAK4, and DPEP1, that charts with CIN+ tumor progression, is associated with reduced cytotoxic cell infiltration, and shows prognostic value in independent cohorts. This spatial multi-omic atlas provides insights into colorectal tumor-microenvironment co-evolution, serving as a resource for stratification and targeted treatments.

CXCL14 is one of the most evolutionarily conserved members of the chemokine family and is constitutionally expressed in multiple organs, suggesting that it is involved in the homeostasis maintenance of the system. CXCL14 is highly expressed in colon epithelial cells and shows obvious gene silencing in clinical colon cancer samples, suggesting that its silencing is related to the immune escape of cancer cells. In this paper, we analyzed the expression profiles of multiple human clinical colon cancer datasets and mouse colon cancer models to reveal the variation trend of CXCL14 expression during colitis, colon polyps, primary colon cancer, and liver metastases. The relationship between CXCL14 gene silencing and promoter hypermethylation was revealed through the colorectal carcinoma methylation database. The results suggest that CXCL14 is a tumor suppressor gene in colorectal carcinoma which is activated first and then silenced during the process of tumor occurrence and deterioration. Promoter hypermethylation is the main cause of CXCL14 silencing. The methylation level of CXCL14 is correlated with the anatomic site of tumor occurrence, positively correlated with patient age, and associated with prognosis. Reversing the hypermethylation of CXCL14 may be an epigenetic therapy for colon cancer.

N6‑methyladenosine (m6A) serves an essential role in RNA modulation and is implicated in multiple malignancies, including colorectal cancer (CRC). Methyltransferase‑like 3 (METTL3) is an important writer in m6A modification, however its role in CRC in modifying small nucleolar RNA host gene 1 (SNHG1), an oncogenic long noncoding RNA, remains unclear. In the present study, METTL3 expression in CRC was assessed using online bioinformatics analysis, immunohistochemistry staining, western blotting, reverse transcription (RT)‑quantitative PCR (qPCR) and cell transfections. Cell proliferation, migration and invasion were determined using functional Cell Counting Kit‑8 (CCK‑8) and Transwell assays. SNHG1 expression in CRC was evaluated using online bioinformatics analysis and RT‑qPCR. Methylated RNA immunoprecipitation qPCR was performed to assess m6A modification changes of SNHG1 mRNA. The present study demonstrated that METTL3 is upregulated in CRC tissues and cell lines. Moreover, METTL3 expression was associated with several unfavourable clinical features in patients with CRC, including the stage of lymph node metastases and overall survival. Functional Transwell and CCK‑8 assays demonstrated that knockdown of METTL3 suppressed CRC cell proliferation and migration. Furthermore, METTL3 was positively correlated with SNHG1 in CRC tissue, as indicated by analysis of data from The Cancer Genome Atlas. Mechanistically, SNHG1 contains 18 m6A modification sites. Through cell transfections and actinomycin D assays, the present study found that METTL3‑mediated m6A modification at these sites enhances the stability of SNHG1 in CRC cells. Finally, it was demonstrated that SNHG1 knockdown partially diminished the facilitative effect of METTL3 on CRC cell migration and proliferation. The present study concluded that METTL3, a potential biomarker for assessing overall survival and metastasis in CRC, may serve as an oncogene, promote SNHG1 m6A modification, improve the stability of SNHG1 and enhance SNHG1‑mediated oncogenic function in CRC.

Numerous studies have confirmed that the leucine zipper tumor suppressor (LZTS) gene family plays a vital role in modulating transcription and cell cycle control, especially in colorectal cancer. This study aimed to evaluate the potential of leucine zipper tumor suppressor family member 3 (LZTS3) as a marker for COAD.

Bioinformatics, immunohistochemistry, and Western blotting were applied to assess the expression of LZTS3 in tissues. Gene overexpression or silencing was used to examine the biological roles of LZTS3 and validated using an in vivo nude mouse-human tumor model.

The results obtained in this study indicate that LZTS3 is highly expressed in COAD. RTCA, Transwell, actin stain, and in vitro transfection experiments confirmed that LZTS3 expression inhibits tumor cell proliferation and cell migration. The results obtained in the nude mouse-human tumor model are consistent with those obtained in vitro. In particular, LZTS3 may exert biological effects by targeting the NOTCH signaling pathway. Furthermore, TAGLN was demonstrated to be a downstream target of LZTS3.

This is the first study to demonstrate the important role of LZTS3 in the proliferation and migration of COAD and to shed light on the molecular mechanism underlying the tumor-suppressing role of LZTS3.

Patients with microsatellite stable (MSS) colorectal cancer with liver metastases are resistant to immune checkpoint inhibitor (ICI) therapy, while about one-third of patients with colorectal cancer without liver metastases, particularly those with lung-only metastases, respond to ICI. We analyzed primary colorectal cancer tumors and major metastatic sites (liver, lung, peritoneal) using multiplex immunofluorescence and whole-slide spatial analyses to identify variations in immune contexture and regional localization within the tumor microenvironment. While levels of T and B cells within peritumoral regions were similar, their levels were significantly lower within the tumor core of liver and peritoneal metastases compared with lung metastases. In contrast, antigen-presenting cells (APC) and APC-T cell interactions were more abundant in all regions of lung metastases. We also identified an abundance of lymphoid aggregates throughout lung metastases, but these were present only within peritumoral regions of liver and peritoneal metastases. Larger lymphoid aggregates consistent with features of tertiary lymphoid structures were observed within or adjacent to primary tumors, but not metastatic lesions. Our findings were validated using NanoString GeoMx DSP, which further showed that liver metastases had higher expression of immune-suppressive markers, while lung metastases showed higher proinflammatory activity and T-cell activation markers. Peritoneal metastases demonstrated higher expression of cancer-associated fibroblast-related proteins and upregulated PD-1/PD-L1 signaling molecules. Our results demonstrate that functional status and spatial distribution of immune cells vary significantly across different metastatic sites. These findings suggest that metastatic site-dependent immune contexture may underlie discordant responses to ICI therapy in patients with MSS colorectal cancer.

Our results demonstrate that functional status and spatial distribution of immune cells vary significantly across different metastatic sites in MSS colorectal cancer. These findings suggest that metastatic site-dependent immune contexture may underlie discordant responses to ICI therapy in patients with MSS colorectal cancer.

Microsatellite instability (MSI) is a hypermutator phenotype caused by DNA mismatch repair deficiency. MSI has been reported in various human cancers, particularly colorectal, gastric and endometrial cancers. MSI is a promising biomarker for cancer prognosis and immune checkpoint blockade immunotherapy. Several computational methods have been developed for MSI detection using DNA- or RNA-based approaches based on next-generation sequencing. Epigenetic mechanisms, such as DNA methylation, regulate gene expression and play critical roles in the development and progression of cancer. We here developed MSI-XGNN, a new computational framework for predicting MSI status using bulk RNA-sequencing and DNA methylation data. MSI-XGNN is an explainable deep learning model that combines a graph neural network (GNN) model to extract features from the gene-methylation probe network with a CatBoost model to classify MSI status. MSI-XGNN, which requires tumor-only samples, exhibited comparable performance with two well-known methods that require tumor-normal paired sequencing data, MSIsensor and MANTIS and better performance than several other tools. MSI-XGNN also showed good generalizability on independent validation datasets. MSI-XGNN identified six MSI markers consisting of four methylation probes (EPM2AIP1|MLH1:cg14598950, EPM2AIP1|MLH1:cg27331401, LNP1:cg05428436 and TSC22D2:cg15048832) and two genes (RPL22L1 and MSH4) constituting the optimal feature subset. All six markers were significantly associated with beneficial tumor microenvironment characteristics for immunotherapy, such as tumor mutation burden, neoantigens and immune checkpoint molecules such as programmed cell death-1 and cytotoxic T-lymphocyte antigen-4. Overall, our study provides a powerful and explainable deep learning model for predicting MSI status and identifying MSI markers that can potentially be used for clinical MSI evaluation.

In this study, we aimed to elucidate the crosstalk between the Wnt/β-catenin signaling pathway and colorectal cancer (CRC) associated with inflammatory bowel disease (IBD) using a bioinformatics analysis of putative common biomarkers and a systems biology approach.

The following criteria were used to search the GEO and ArrayExpress databases for terms related to CRC and IBD: 1. The dataset containing the transcriptomic data, and 2. Untreated samples by medications or drugs. A total of 42 datasets were selected for additional analysis. The GEO2R identified the differentially expressed genes. The genes involved in the Wnt signaling pathway were extracted from the KEGG database. Enrichment analysis and miRNA target prediction were conducted through the ToppGene online tool.

In CRC datasets, there were 1168 up- and 998 down-regulated probes, whereas, in IBD datasets, there were 256 up- and 200 down-regulated probes. There were 65 upregulated and 57 downregulated genes shared by CRC and IBD. According to KEGG, there were 166 genes in the Wnt pathway. FriZZled5 (FZD5) was a down-regulated gene in both CRC and IBD, as determined by the intersection of CRC- and IBD-related DEGs with the Wnt pathway. It was also demonstrated that miR-191, miR-885-5p, miR-378a-3p, and miR-396-3p affect the FriZZled5 gene expression.

It is possible that increased expression of miR-191 and miR-885-5p, or decreased expression of miR-378a -3p and miR396-3, in IBD and CRC results in decreased expression of the FZD5 gene. Based on the function of this gene, FZD5 may be a potential therapeutic target in IBD that progresses to CRC.

Cancer poses a significant global health problem with profound personal and economic implications on National Health Care Systems. The reprograming of metabolism is a major trait of the cancer phenotype with a clear potential for developing effective therapeutic strategies to combat the disease. Herein, we summarize the relevant role that the mitochondrial ATP synthase and its physiological inhibitor, ATPase Inhibitory Factor 1 (IF1), play in metabolic reprogramming to an enhanced glycolytic phenotype. We stress that the interplay in the ATP synthase/IF1 axis has additional functional roles in signaling mitohormetic programs, pro-oncogenic or anti-metastatic phenotypes depending on the cell type. Moreover, the same axis also participates in cell death resistance of cancer cells by restrained mitochondrial permeability transition pore opening. We emphasize the relevance of the different post-transcriptional mechanisms that regulate the specific expression and activity of ATP synthase/IF1, to stimulate further investigations in the field because of their potential as future targets to treat cancer. In addition, we review recent findings stressing that mitochondria metabolism is the primary altered target in lung adenocarcinomas and that the ATP synthase/IF1 axis of OXPHOS is included in the most significant signature of metastatic disease. Finally, we stress that targeting mitochondrial OXPHOS in pre-clinical mouse models affords a most effective therapeutic strategy in cancer treatment.

There is an urgent need for markers to predict the efficacy of different chemotherapy drugs. Herein, we examined whether microsatellite instability (MSI) status can predict tumor multidrug sensitivity and explored the underlying mechanisms. We downloaded data from several public databases. Drug sensitivity was compared between the high microsatellite instability (MSI-H) and microsatellite-stable/low microsatellite instability (MSS/MSI-L) groups. In addition, we performed pathway enrichment analysis and cellular chemosensitivity assays to explore the mechanisms by which MSI status may affect drug sensitivity and assessed the differences between drug-treated and control cell lines. We found that multiple MSI-H tumors were more sensitive to a variety of chemotherapy drugs than MSS/MSI-L tumors, and especially for CRC, chemosensitivity is enhanced through the downregulation of DDR pathways such as NHEJ. Additional DNA damage caused by chemotherapeutic drugs results in further downregulation of DDR pathways and enhances drug sensitivity, forming a cycle of increasing drug sensitivity.

VPS4 series proteins play a crucial role in the endosomal sorting complexes required for the transport (ESCRT) pathway, which is responsible for sorting and trafficking cellular proteins and is involved in various cellular processes, including cytokinesis, membrane repair, and viral budding. VPS4 proteins are ATPases that mediate the final steps of membrane fission and protein sorting as part of the ESCRT machinery. They disassemble ESCRT-III filaments, which are vital for forming multivesicular bodies (MVBs) and the release of intraluminal vesicles (ILVs), ultimately leading to the sorting and degradation of various cellular proteins, including those involved in cancer development and progression. Recent studies have shown a potential relationship between VPS4 series proteins and cancer. Evidence suggests that these proteins may have crucial roles in cancer development and progression. Several experiments have explored the association between VPS4 and different types of cancer, including gastrointestinal and reproductive system tumors, providing insight into the underlying mechanisms. Understanding the structure and function of VPS4 series proteins is critical in assessing their potential role in cancer. The evidence supporting the involvement of VPS4 series proteins in cancer provides a promising avenue for future research and therapeutic development. However, further researches are necessary to fully understand the mechanisms underlying the relationship between VPS4 series proteins and cancer and to develop effective strategies for targeting these proteins in cancer therapy. This article aims to review the structures and functions of VPS4 series proteins and the previous experiments to analyze the relationship between VPS4 series proteins and cancer.

Left-sided colon cancer (LC) and right-sided colon cancer (RC) are 2 essentially different diseases, and the potential mechanisms regulating them remain unidentified. In this study, we applied weighted gene co-expression network analysis (WGCNA) to confirm a yellow module, mainly enriched in metabolism-related signaling pathways related to LC and RC. Based on the RNA-seq data of colon cancer in The Cancer Genome Atlas (TCGA) and GSE41258 dataset with their corresponding clinical information, a training set (TCGA: LC: n = 171; RC: n = 260) and a validation set (GSE41258: LC: n = 94; RC: n = 77) were divided. Least absolute shrinkage and selection operator (LASSO) penalized COX regression analysis identified 20 prognosis-related genes (PRGs) and helped constructed 2 risk (LC-R and RC-R) models in LC and RC, respectively. The model-based risk scores accurately performed in risk stratification for colon cancer patients. The high-risk group of the LC-R model showed associations with ECM-receptor interaction, focal adhesion, and PI3K-AKT signaling pathway. Interestingly, the low-risk group of the LC-R model showed associations with immune-related signaling pathways like antigen processing and presentation. On the other hand, the high-risk group of the RC-R model showed enrichment for cell adhesion molecules and axon guidance signaling pathways. Furthermore, we identified 20 differentially expressed PRGs between LC and RC. Our findings provide new insights into the difference between LC and RC, and uncover the potential biomarkers for the treatment of LC and RC.

Incidence of early-onset colorectal cancer (EOCRC), defined by a diagnosed age under 50 years, is increasing, but its heterogeneous etiologies that differ from general CRC remain undetermined. We initially characterize the genome, epigenome, transcriptome, and proteome of tumors from 79 patients in a Chinese CRC cohort. Data for an additional 126 EOCRC subjects are obtained from the International Cancer Genome Consortium Chinese cohort and The Cancer Genome Atlas European cohort. We observe that early-onset tumors have a high tumor mutation burden; increased DNA repair features by mutational signature 3 and multi-layer pathway enrichments; strong perturbations at effects of DNA methylation and somatic copy-number alteration on gene expression; and upregulated immune infiltration as hot tumors underlying immunophenotypes. Notably, LMTK3 exhibits ancestral mutation disparity, potentially being a functional modulator and biomarker that drives molecular alterations in EOCRC development and immunotherapies. This integrative omics study provides valuable knowledge for precision oncology of CRC.

With functionally heterogeneous cells, tumors comprise a complex ecosystem to promote tumor adaptability and evolution under strong selective pressure from the given microenvironment. Diversifying tumor cells or intra-tumor heterogeneity is essential for tumor growth, invasion, and immune evasion. However, no reliable method to classify tumor cell subtypes is yet available. In this study, we introduced the single-cell sequencing combined with copy number characteristics to identify the types of tumor cells in microsatellite stable (MSS) colorectal cancer (CRC).

To characterize the somatic copy number alteration (SCNA) of MSS CRC in a single cell profile, we analyzed 26 tissue samples from 19 Korean patients (GSE132465, the Samsung Medical Center [SMC] dataset) and then verified our findings with 15 tissue samples from five Belgian patients (GSE144735, the Katholieke Universiteit Leuven 3 [KUL3] dataset). The Cancer Genome Atlas (TCGA) cohort, GSE39582 cohort, and National Cancer Center (NCC) cohort (24 MSS CRC patients were enrolled in this study between March 2017 and October 2017) were used to validate the clinical features of prognostic signatures.

We employed single cell RNA-sequencing data to identify three types of tumor cells in MSS CRC by their SCNA characteristics. Among these three types of tumor cells, C1 and C3 had a higher SCNA burden; C1 had significant chromosome 13 and 20 amplification, whereas C3 was the polar opposite of C1, which exhibited deletion in chromosome 13 and 20. The three types of tumor cells exhibited various functions in the tumor microenvironment and harbored different mutations. C1 and C2 were linked to the immune response and hypoxia, respectively, while C3 was critical for cell adhesion activity and tumor angiogenesis. Additionally, one gene ( OLFM4 ) was identified as epithelium-specific biomarker of better prognosis of CRC (TCGA cohort: P  = 0.0110; GSE39582 cohort: P  = 0.0098; NCC cohort: P  = 0.0360).

On the basis of copy number characteristics, we illustrated tumor heterogeneity in MSS CRC and identified three types of tumor cells with distinct roles in tumor microenvironment. By understanding heterogeneity in the intricate tumor microenvironment, we gained an insight into the mechanisms of tumor evolution, which may support the development of therapeutic strategies.

Precision oncology promises accurate prediction of disease trajectories by utilizing molecular features of tumors. We present a systematic analysis of the prognostic potential of diverse molecular features across large cancer cohorts. We find that the mRNA expression of biologically coherent sets of genes (modules) is substantially more predictive of patient survival than single-locus genomic and transcriptomic aberrations. Extending our analysis beyond existing curated gene modules, we find a large novel class of highly prognostic DNA/RNA cis-regulatory modules associated with dynamic gene expression within cancers. Remarkably, in more than 82% of cancers, modules substantially improve survival stratification compared with conventional clinical factors and prominent genomic aberrations. The prognostic potential of cancer modules generalizes to external cohorts better than conventionally used single-gene features. Finally, a machine-learning framework demonstrates the combined predictive power of multiple modules, yielding prognostic models that perform substantially better than existing histopathological and clinical factors in common use.

The extracellular matrix (ECM) plays a vital role in progression, expansion, and prognosis of malignancies. In this study, we aimed to explore a novel ECM-based prognostic model for patients with colon cancer (CC).

ECM-related genes were obtained from Molecular Signatures database. Differential expression analysis was performed using the CC dataset from The Cancer Genome Atlas (TCGA) database. Four ECM-related genes related to overall survival were identified using the Cox regression and LASSO analysis. Then an ECM-related signature was developed and verified in three independent CC cohorts (GSE33882, GSE39582 and GSE29621) from the Gene Expression Omnibus (GEO). A prognostic nomogram was developed incorporating the ECM-related gene signature with clinical risk factors. CIBERSORT was used to explore the immune cell infiltration level. Human Protein Atlas (HPA) database was utilized to validate the expression levels of identified prognostic ECM genes.

Four ECM-related genes (CXCL13, CXCL14, SFRP5 and THBS4) were identified to develop an ECM-based gene signature and demarcated CC patients into the high- and low-risk groups. In training and validation datasets, patients in the low-risk group had better overall survival outcomes than those in the high-risk group (log-rank P<0.001). In addition, ECM-related signature was significantly associated with consensus molecular subtype 4 (CMS4) as well as other known clinical risk factors such as a higher Tumor, Nodal Involvement, Metastasis (TNM) stage. Moreover, the risk score derived from the ECM-based gene signature could be utilized as an independent prognostic factor for CC patients. A nomogram including the ECM-related gene signature, age and stage was developed to serve clinical practice. CIBERSORT analysis showed immune cell infiltration was different between high- and low-risk groups. The immunohistochemical results derived from HPA indicated differential expression of prognosis-related ECM genes in CC and normal tissues.

In the present study, a novel risk model based on ECM-signature could effectively reflect individual risk classification and provide potential therapeutic targets for CC patients. Moreover, the prognostic nomogram may help predict individualized survival.