Identification of hub genes related to metastasis and prognosis of osteosarcoma and establishment of a prognostic model with bioinformatic methods.

Osteosarcoma (OS) is the most common primary malignant bone tumor occurring in children and adolescents. Improvements in our understanding of the OS pathogenesis and metastatic mechanism on the molecular level might lead to notable advances in the treatment and prognosis of OS. Biomarkers related to OS metastasis and prognosis were analyzed and identified, and a prognostic model was established through the integration of bioinformatics tools and datasets in multiple databases. 2 OS datasets were downloaded from the Gene Expression Omnibus database for data consolidation, standardization, batch effect correction, and identification of differentially expressed genes (DEGs); following that, gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed on the DEGs; the STRING database was subsequently used for protein-protein interaction (PPI) network construction and identification of hub genes; hub gene expression was validated, and survival analysis was conducted through the employment of the TARGET database; finally, a prognostic model was established and evaluated subsequent to the screening of survival-related genes. A total of 701 DEGs were identified; by gene ontology and KEGG pathway enrichment analyses, the overlapping DEGs were enriched for 249 biological process terms, 13 cellular component terms, 35 molecular function terms, and 4 KEGG pathways; 13 hub genes were selected from the PPI network; 6 survival-related genes were identified by the survival analysis; the prognostic model suggested that 4 genes were strongly associated with the prognosis of OS. DEGs related to OS metastasis and survival were identified through bioinformatics analysis, and hub genes were further selected to establish an ideal prognostic model for OS patients. On this basis, 4 protective genes including TPM1, TPM2, TPM3, and TPM4 were yielded by the prognostic model.

The crosstalk between metabolic reprogramming and epithelial-mesenchymal transition and their synergistic roles in distant metastasis in breast cancer.

BACKGROUND: Metabolic reprogramming (MR) and epithelial-mesenchymal transition (EMT) are crucial phenomena involved in the distant metastasis of breast cancer (BRCA). This study aims to assess the risk of distant metastasis in BRCA patients based on MR and EMT processes and investigate their underlying mechanisms. METHODS: Gene sets related to EMT and MR were downloaded. MR-related genes (MRG) and EMT-related genes (ERG) were obtained. Principal Component Analysis method was used to define the EMT Potential Index (EPI) and MR Potential Index (MPI) to quantify the EMT and MR levels in each tumor tissue. A linear scoring model, the Metastasis Score, was derived using the union of MRGs and ERGs to evaluate the risk of distant metastasis/recurrence in BRCA. The Metastasis Score was then validated in multiple datasets. Additionally, our study explored the underlying mechanism of the Metastasis Score and its association with tumor immunity, focusing on HPRT1 gene expression in breast cancer tissues of transfer and untransferred groups using experimental methods. RESULTS: A total of 59 MRGs and 30 ERGs were identified in the present study. Stratifying the dataset based on EPI and MPI revealed significantly lower survival rates (P < .05) in the MPI_high and EPI_high groups. Kaplan-Meier analysis indicated the lowest survival rate in the EPI-high + MPI-high group. The Metastasis Score demonstrated its ability to distinguish prognoses in GSE2034, GSE17705, and TCGA-BRCA datasets. Additionally, differences in mutated genes were found between the high- and the low-Metastasis Score groups, displaying significant associations with immune cell infiltration and anti-tumor immune status. Notably, the 13 genes included in the Metastasis Score showed a strong association with prognosis and tumor immunity. Immunohistochemistry and western blot results revealed high expression of the HPRT1 gene in the transfer group. CONCLUSION: This study established the Metastasis Score as a reliable tool for evaluating the risk of distant metastasis/recurrence in BRCA patients. Additionally, we identified key genes involved in MR and EMT crosstalk, offering valuable insights into their roles in tumor immunity and other relevant aspects.

Modeling metastatic progression from cross-sectional cancer genomics data.

MOTIVATION: Metastasis formation is a hallmark of cancer lethality. Yet, metastases are generally unobservable during their early stages of dissemination and spread to distant organs. Genomic datasets of matched primary tumors and metastases may offer insights into the underpinnings and the dynamics of metastasis formation. RESULTS: We present metMHN, a cancer progression model designed to deduce the joint progression of primary tumors and metastases using cross-sectional cancer genomics data. The model elucidates the statistical dependencies among genomic events, the formation of metastasis, and the clinical emergence of both primary tumors and their metastatic counterparts. metMHN enables the chronological reconstruction of mutational sequences and facilitates estimation of the timing of metastatic seeding. In a study of nearly 5000 lung adenocarcinomas, metMHN pinpointed TP53 and EGFR as mediators of metastasis formation. Furthermore, the study revealed that post-seeding adaptation is predominantly influenced by frequent copy number alterations. AVAILABILITY AND IMPLEMENTATION: All datasets and code are available on GitHub at https://github.com/cbg-ethz/metMHN.

Integrating bulk and single-cell sequencing reveals metastasis-associated CAFs in head and neck squamous cell carcinoma.

AIMS: Cancer-associated fibroblasts (CAFs) have been shown to promote the metastasis of head and neck squamous cell carcinoma (HNSCC), but the underlying mechanisms remain unclear. The purpose of this study is to identify gene in CAFs that are associated with metastasis and to preliminarily validate its impact on the metastasis of HNSCC. MATERIALS AND METHODS: Scissor analysis was utilized to process single-cell and bulk RNA sequencing datasets, identifying genes associated with the metastasis of HNSCC through differential gene expression analysis. A risk model was constructed using LASSO regression analysis. Quantitative real time-PCR and Western blot were employed to measure mRNA and protein expressions, respectively. Multiplex immunohistochemistry (mIHC) was used to assess protein expression in CAFs. siRNA was utilized to achieve gene knockdown. CCK-8 and Transwell assays were employed to evaluate the biological characteristics of HNSCC cells. KEY FINDINGS: Compare to the nonmetastatic primary CAFs (nmCAFs), tissue inhibitors of metalloproteinase-1 (TIMP1) was founded to be overexpressed in the cells and tissues of metastatic primary CAFs (mCAFs). Knocking down TIMP1 in CAFs can signifucantly inhibit the proliferation, invasion, and migration of HNSCC cells. SIGNIFICANCE: CAFs facilitate HNSCC cell metastasis by upregulating TIMP1, highlighting TIMP1 as a potential therapeutic target in HNSCC metastasis management.

Integrated Epigenetic and Transcriptomic Analysis Identifies Interleukin 17 DNA Methylation Signature of Malignant Peripheral Nerve Sheath Tumor Progression and Metastasis.

PURPOSE: Sarcomas are a complex group of highly aggressive and metastatic tumors with over 100 distinct subtypes. Because of their diversity and rarity, it is challenging to generate multisarcoma signatures that are predictive of patient outcomes. MATERIALS AND METHODS: Here, we identify a DNA methylation signature for progression and metastasis of numerous sarcoma subtypes using multiple epigenetic and genomic patient data sets. Malignant Peripheral Nerve Sheath Tumors (MPNSTs) are highly metastatic sarcomas with frequent loss of the histone methyltransferase, PRC2. Loss of PRC2 is associated with MPNST metastasis and plays a critical noncanonical role in DNA methylation. RESULTS: We found that over 900 5'-C-phosphate-G-3' (CpGs) were hypermethylated in MPNSTs with PRC2 loss. Furthermore, we identified eight differentially methylated CpGs in the IL17D/RD family that correlate with the progression and metastasis of MPNSTs in two independent patient data sets. Similar trends were identified in other sarcoma subtypes, including osteosarcoma, rhabdomyosarcoma, and synovial sarcoma. Analysis of scRNAseq data sets determined that IL17D/RD expression occurs in both the tumor cells and the surrounding stromal populations. CONCLUSION: These results might have broad implications for the clinical management and surveillance of sarcoma.

Decoding the interplay between genetic and non-genetic drivers of metastasis.

Metastasis is a multistep process by which cancer cells break away from their original location and spread to distant organs, and is responsible for the vast majority of cancer-related deaths. Preventing early metastatic dissemination would revolutionize the ability to fight cancer. Unfortunately, the relatively poor understanding of the molecular underpinnings of metastasis has hampered the development of effective anti-metastatic drugs. Although it is now accepted that disseminating tumour cells need to acquire multiple competencies to face the many obstacles they encounter before reaching their metastatic site(s), whether these competencies are acquired through an accumulation of metastasis-specific genetic alterations and/or non-genetic events is often debated. Here we review a growing body of literature highlighting the importance of both genetic and non-genetic reprogramming events during the metastatic cascade, and discuss how genetic and non-genetic processes act in concert to confer metastatic competencies. We also describe how recent technological advances, and in particular the advent of single-cell multi-omics and barcoding approaches, will help to better elucidate the cross-talk between genetic and non-genetic mechanisms of metastasis and ultimately inform innovative paths for the early detection and interception of this lethal process.

WNT5B drives osteosarcoma stemness, chemoresistance and metastasis.

BACKGROUND: Treatment for osteosarcoma, a paediatric bone cancer with no therapeutic advances in over three decades, is limited by a lack of targeted therapies. Osteosarcoma frequently metastasises to the lungs, and only 20% of patients survive 5 years after the diagnosis of metastatic disease. We found that WNT5B is the most abundant WNT expressed in osteosarcoma tumours and its expression correlates with metastasis, histologic subtype and reduced survival. METHODS: Using tumor-spheroids to model cancer stem-like cells, we performed qPCR, immunoblotting, and immunofluorescence to monitor changes in gene and protein expression. Additionally, we measured sphere size, migration and forming efficiency to monitor phenotypic changes. Therefore, we characterised WNT5B's relevance to cancer stem-like cells, metastasis, and chemoresistance and evaluated its potential as a therapeutic target. RESULTS: In osteosarcoma cell lines and patient-derived spheres, WNT5B is enriched in stem cells and induces the expression of the stemness gene SOX2. WNT5B promotes sphere size, sphere-forming efficiency, and cell proliferation, migration, and chemoresistance to methotrexate (but not cisplatin or doxorubicin) in spheres formed from conventional cell lines and patient-derived xenografts. In vivo, WNT5B increased osteosarcoma lung and liver metastasis and inhibited the glycosaminoglycan hyaluronic acid via upregulation of hyaluronidase 1 (HYAL1), leading to changes in the tumour microenvironment. Further, we identified that WNT5B mRNA and protein correlate with the receptor ROR1 in primary tumours. Targeting WNT5B through inhibition of WNT/ROR1 signalling with an antibody to ROR1 reduced stemness properties, including chemoresistance, sphere size and SOX2 expression. CONCLUSIONS: Together, these data define WNT5B's role in driving osteosarcoma cancer stem cell expansion and methotrexate resistance and provide evidence that the WNT5B pathway is a promising candidate for treating osteosarcoma patients. KEY POINTS: WNT5B expression is high in osteosarcoma stem cells leading to increased stem cell proliferation and migration through SOX2. WNT5B expression in stem cells increases rates of osteosarcoma metastasis to the lungs and liver in vivo. The hyaluronic acid degradation enzyme HYAL1 is regulated by WNT5B in osteosarcoma contributing to metastasis. Inhibition of WNT5B with a ROR1 antibody decreases osteosarcoma stemness.

CD44 and RHAMM Are Microenvironmental Sensors with Dual Metastasis Promoter and Suppressor Functions.

The progression of primary tumors to metastases remains a significant roadblock to the treatment of most cancers. Emerging evidence has identified genes that specifically affect metastasis and are potential therapeutic targets for managing tumor progression. However, these genes can have dual tumor promoter and suppressor functions that are contextual in manifestation, and that complicate their development as targeted therapies. CD44 and RHAMM/HMMR are examples of multifunctional proteins that can either promote or suppress metastases, as demonstrated in experimental models. These two proteins can be viewed as microenvironmental sensors and this minireview addresses the known mechanistic underpinnings that may determine their metastasis suppressor versus promoter functions. Leveraging this mechanistic knowledge for CD44, RHAMM, and other multifunctional proteins is predicted to improve the precision of therapeutic targeting to achieve more effective management of metastasis.

Quantifying Y chromosome loss in primary and metastatic prostate cancer by chromosome painting.

Somatic Y chromosome loss in hematopoietic cells is associated with higher mortality in men. However, the status of the Y chromosome in cancer tissue is not fully known due to technical limitations, such as difficulties in labelling and sequencing DNA from the Y chromosome. We have developed a system to quantify Y chromosome gain or loss in patient-derived prostate cancer organoids. Using our system, we observed Y chromosome loss in 4 of the 13 (31%) patient-derived metastatic castration-resistant prostate cancer (mCRPC) organoids; interestingly, loss of Yq (long arm of the Y chromosome) was seen in 38% of patient-derived organoids. Additionally, potential associations were observed between mCRPC and Y chromosome nullisomy. The prevalence of Y chromosome loss was similar in primary and metastatic tissue, suggesting that Y chromosome loss is an early event in prostate cancer evolution and may not a result of drug resistance or organoid derivation. This study reports quantification of Y chromosome loss and gain in primary and metastatic prostate cancer tissue and lays the groundwork for further studies investigating the clinical relevance of Y chromosome loss or gain in mCRPC.

Personalized identification and characterization of genome-wide gene expression differences between patient-matched intracranial and extracranial melanoma metastasis pairs.

Melanoma is the most serious type of skin cancer that frequently spreads to other organs of the human body. Especially melanoma metastases to the brain (intracranial metastases) are hard to treat and a major cause of death of melanoma patients. Little is known about molecular alterations and altered mechanisms that distinguish intra- from extracranial melanoma metastases. So far, almost all existing studies compared intracranial metastases from one set of patients to extracranial metastases of an another set of melanoma patients. This neglects the important facts that each melanoma is highly individual and that intra- and extracranial melanoma metastases from the same patient are more similar to each other than to melanoma metastases from other patients in the same organ. To overcome this, we compared the gene expression profiles of 16 intracranial metastases to their corresponding 21 patient-matched extracranial metastases in a personalized way using a three-state Hidden Markov Model (HMM) to identify altered genes for each individual metastasis pair. This enabled three major findings by considering the predicted gene expression alterations across all patients: (i) most frequently altered pathways include cytokine-receptor interaction, calcium signaling, ECM-receptor interaction, cAMP signaling, Jak-STAT and PI3K/Akt signaling, (ii) immune-relevant signaling pathway genes were downregulated in intracranial metastases, and (iii) intracranial metastases were associated with a brain-like phenotype gene expression program. Further, the integration of all differentially expressed genes across the patient-matched melanoma metastasis pairs led to a set of 103 genes that were consistently down- or up-regulated in at least 11 of the 16 of the patients. This set of genes contained many genes involved in the regulation of immune responses, cell growth, cellular signaling and transport processes. An analysis of these genes in the TCGA melanoma cohort showed that the expression behavior of 11 genes was significantly associated with survival. Moreover, a comparison of the 103 genes to three closely related melanoma metastasis studies revealed a core set of eight genes that were consistently down- or upregulated in intra- compared to extracranial metastases in at least two of the three related studies (down: CILP, DPT, FGF7, LAMP3, MEOX2, TMEM119; up: GLDN, PMP2) including FGF7 that was also significantly associated with survival. Our findings contribute to a better characterization of genes and pathways that distinguish intra- from extracranial melanoma metastasis and provide important hints for future experimental studies to identify potential targets for new therapeutic approaches.

Machine Learning Gene Signature to Metastatic ccRCC Based on ceRNA Network.

Clear-cell renal-cell carcinoma (ccRCC) is a silent-development pathology with a high rate of metastasis in patients. The activity of coding genes in metastatic progression is well known. New studies evaluate the association with non-coding genes, such as competitive endogenous RNA (ceRNA). This study aims to build a ceRNA network and a gene signature for ccRCC associated with metastatic development and analyze their biological functions. Using data from The Cancer Genome Atlas (TCGA), we constructed the ceRNA network with differentially expressed genes, assembled nine preliminary gene signatures from eight feature selection techniques, and evaluated the classification metrics to choose a final signature. After that, we performed a genomic analysis, a risk analysis, and a functional annotation analysis. We present an 11-gene signature: SNHG15, AF117829.1, hsa-miR-130a-3p, hsa-mir-381-3p, BTBD11, INSR, HECW2, RFLNB, PTTG1, HMMR, and RASD1. It was possible to assess the generalization of the signature using an external dataset from the International Cancer Genome Consortium (ICGC-RECA), which showed an Area Under the Curve of 81.5%. The genomic analysis identified the signature participants on chromosomes with highly mutated regions. The hsa-miR-130a-3p, AF117829.1, hsa-miR-381-3p, and PTTG1 were significantly related to the patient's survival and metastatic development. Additionally, functional annotation resulted in relevant pathways for tumor development and cell cycle control, such as RNA polymerase II transcription regulation and cell control. The gene signature analysis within the ceRNA network, with literature evidence, suggests that the lncRNAs act as "sponges" upon the microRNAs (miRNAs). Therefore, this gene signature presents coding and non-coding genes and could act as potential biomarkers for a better understanding of ccRCC.

Deep learning and machine learning approaches to classify stomach distant metastatic tumors using DNA methylation profiles.

Distant metastasis of cancer is a significant contributor to cancer-related complications, and early identification of unidentified stomach adenocarcinoma is crucial for a positive prognosis. Changes inDNA methylation are being increasingly recognized as a crucial factor in predicting cancer progression. Within this research, we developed machine learning and deep learning models for distinguishing distant metastasis in samples of stomach adenocarcinoma based on DNA methylation profile. Employing deep neural networks (DNN), support vector machines (SVM), random forest (RF), Naive Bayes (NB) and decision tree (DT), and models for forecasting distant metastasis in stomach adenocarcinoma. The results show that the performance of DNN is better than that of other models, AUC and AUPR achieving 99.9 % and 99.5 % respectively. Additionally, a weighted random sampling technique was utilized to address the issue of imbalanced datasets, enabling the identification of crucial methylation markers associated with functionally significant genes in stomach distant metastasis tumors with greater performance.

Hypoxic Exosomal circPLEKHM1-Mediated Crosstalk between Tumor Cells and Macrophages Drives Lung Cancer Metastasis.

Intercellular communication often relies on exosomes as messengers and is critical for cancer metastasis in hypoxic tumor microenvironment. Some circular RNAs (circRNAs) are enriched in cancer cell-derived exosomes, but little is known about their ability to regulate intercellular communication and cancer metastasis. Here, by systematically analyzing exosomes secreted by non-small cell lung cancer (NSCLC) cells, a hypoxia-induced exosomal circPLEKHM1 is identified that drives NSCLC metastasis through polarizing macrophages toward to M2 type. Mechanistically, exosomal circPLEKHM1 promoted PABPC1-eIF4G interaction to facilitate the translation of the oncostatin M receptor (OSMR), thereby promoting macrophage polarization for cancer metastasis. Importantly, circPLEKHM1-targeted therapy significantly reduces NSCLC metastasis in vivo. circPLEKHM1 serves as a prognostic biomarker for metastasis and poor survival in NSCLC patients. This study unveils a new circRNA-mediated mechanism underlying how cancer cells crosstalk with macrophages within the hypoxic tumor microenvironment to promote metastasis, highlighting the importance of exosomal circPLEKHM1 as a prognostic biomarker and therapeutic target for lung cancer metastasis.

C9orf10/Ossa regulates the bone metastasis of established lung adenocarcinoma cell subline H322L-BO4 in a mouse model.

Lung cancer frequently metastasizes to the bones. An in vivo model is urgently required to identify potential therapeutic targets for the prevention and treatment of lung cancer with bone metastasis. We established a lung adenocarcinoma cell subline (H322L-BO4) that specifically showed metastasis to the leg bones and adrenal glands. This was achieved by repeated isolation of metastatic cells from the leg bones of mice. The cells were intracardially injected into nude mice. Survival was prolonged for mice that received H322L-BO4 cells versus original cells (H322L). H322L-BO4 cells did not exhibit obvious changes in general in vitro properties associated with the metastatic potential (e.g., cell growth, migration, and invasion) compared with H322L cells. However, the phosphorylation of chromosome 9 open reading frame 10/oxidative stress-associated Src activator (C9orf10/Ossa) was increased in H322L-BO4 cells. This result confirmed the increased anchorage independence through C9orf10/Ossa-mediated activation of Src family tyrosine kinase. Reduction of C9orf10/Ossa by shRNA reduced cells' metastasis to the leg bone and prolonged survival in mice. These findings indicate that H322L-BO4 cells can be used to evaluate the effect of candidate therapeutic targets against bone metastatic lung cancer cells. Moreover, C9orf10/Ossa may be a useful target for treatment of lung cancer with bone metastasis.

Integrated Multiomics Reveals Silencing of has_circ_0006646 Promotes TRIM21-Mediated NCL Ubiquitination to Inhibit Hepatocellular Carcinoma Metastasis.

Recent studies suggest that circular RNA (circRNA)-mediated post-translational modification of RNA-binding proteins (RBP) plays a pivotal role in metastasis of hepatocellular carcinoma (HCC). However, the specific mechanism and potential clinical therapeutic significance remain vague. This study attempts to profile the regulatory networks of circRNA and RBP using a multi-omics approach. Has_circ_0006646 (circ0006646) is an unreported circRNA in HCC and is associated with a poor prognosis. Silencing of circ0006646 significantly hinders metastasis in vivo. Mechanistically, circ0006646 prevents the interaction between nucleolin (NCL) and the E3 ligase tripartite motif-containing 21 to reduce the proteasome-mediated degradation of NCL via K48-linked polyubiquitylation. Furthermore, the change of NCL expression is proven to affect the phosphorylation levels of multiple proteins and inhibit p53 translation. Moreover, patient-derived tumor xenograft and lentivirus injection, which is conducted to simulate clinical treatment confirmed the potential therapeutic value. Overall, this study describes the integrated multi-omics landscape of circRNA-mediated NCL ubiquitination degradation in HCC metastasis and provides a novel therapeutic target.

DNMT3A Cooperates with YAP/TAZ to Drive Gallbladder Cancer Metastasis.

Gallbladder cancer (GBC) is an extremely lethal malignancy with aggressive behaviors, including liver or distant metastasis; however, the underlying mechanisms driving the metastasis of GBC remain poorly understood. In this study, it is found that DNA methyltransferase DNMT3A is highly expressed in GBC tumor tissues compared to matched adjacent normal tissues. Clinicopathological analysis shows that DNMT3A is positively correlated with liver metastasis and poor overall survival outcomes in patients with GBC. Functional analysis confirms that DNMT3A promotes the metastasis of GBC cells in a manner dependent on its DNA methyltransferase activity. Mechanistically, DNMT3A interacts with and is recruited by YAP/TAZ to recognize and access the CpG island within the CDH1 promoter and generates hypermethylation of the CDH1 promoter, which leads to transcriptional silencing of CDH1 and accelerated epithelial-to-mesenchymal transition. Using tissue microarrays, the association between the expression of DNMT3A, YAP/TAZ, and CDH1 is confirmed, which affects the metastatic ability of GBC. These results reveal a novel mechanism through which DNMT3A recruitment by YAP/TAZ guides DNA methylation to drive GBC metastasis and provide insights into the treatment of GBC metastasis by targeting the functional connection between DNMT3A and YAP/TAZ.

Deep whole-genome analysis of 494 hepatocellular carcinomas.

Over half of hepatocellular carcinoma (HCC) cases diagnosed worldwide are in China1-3. However, whole-genome analysis of hepatitis B virus (HBV)-associated HCC in Chinese individuals is limited4-8, with current analyses of HCC mainly from non-HBV-enriched populations9,10. Here we initiated the Chinese Liver Cancer Atlas (CLCA) project and performed deep whole-genome sequencing (average depth, 120×) of 494 HCC tumours. We identified 6 coding and 28 non-coding previously undescribed driver candidates. Five previously undescribed mutational signatures were found, including aristolochic-acid-associated indel and doublet base signatures, and a single-base-substitution signature that we termed SBS_H8. Pentanucleotide context analysis and experimental validation confirmed that SBS_H8 was distinct to the aristolochic-acid-associated SBS22. Notably, HBV integrations could take the form of extrachromosomal circular DNA, resulting in elevated copy numbers and gene expression. Our high-depth data also enabled us to characterize subclonal clustered alterations, including chromothripsis, chromoplexy and kataegis, suggesting that these catastrophic events could also occur in late stages of hepatocarcinogenesis. Pathway analysis of all classes of alterations further linked non-coding mutations to dysregulation of liver metabolism. Finally, we performed in vitro and in vivo assays to show that fibrinogen alpha chain (FGA), determined as both a candidate coding and non-coding driver, regulates HCC progression and metastasis. Our CLCA study depicts a detailed genomic landscape and evolutionary history of HCC in Chinese individuals, providing important clinical implications.

Single-cell transcriptomic analysis deciphers heterogenous cancer stem-like cells in colorectal cancer and their organ-specific metastasis.

OBJECTIVE: Metastasis is the major cause of cancer death. However, what types of heterogenous cancer cells in primary tumour and how they metastasise to the target organs remain largely undiscovered. DESIGN: We performed single-cell RNA sequencing and spatial transcriptomic analysis in primary colorectal cancer (CRC) and metastases in the liver (lCRC) or ovary (oCRC). We also conducted immunofluorescence staining and functional experiments to examine the mechanism. RESULTS: Integrative analyses of epithelial cells reveal a stem-like cell cluster with high protein tyrosine phosphatase receptor type O (PTPRO) and achaete scute-like 2 (ASCL2) expression as the metastatic culprit. This cell cluster comprising distinct subpopulations shows distinct liver or ovary metastatic preference. Population 1 (P1) cells with high delta-like ligand 4 (DLL4) and MAF bZIP transcription factor A (MAFA) expression are enriched in primary CRC and oCRC, thus may be associated with ovarian metastasis. P3 cells having a similar expression pattern as cholangiocytes are found mainly in primary CRC and lCRC, presuming to be likely the culprits that specifically metastasise to the liver. Stem-like cells interacted with cancer-associated fibroblasts and endothelial cells via the DLL4-NOTCH signalling pathway to metastasise from primary CRC to the ovary. In the oCRC microenvironment, myofibroblasts provide cancer cells with glutamine and perform a metabolic reprogramming, which may be essential for cancer cells to localise and develop in the ovary. CONCLUSION: We uncover a mechanism for organ-specific CRC metastasis.