INTRODUCTION
Colorectal cancer is the third most frequently diagnosed cancer in men worldwide, after prostate and lung cancer. Additionally, it is the second most commonly diagnosed cancer in women after breast cancer.[1] In recent years, the incidence of colon cancer has increased, and most patients are diagnosed in the middle or advanced stages.[2] Despite advancements in the postoperative overall survival of patients with colon cancer in recent years, 30–50% of patients experience postoperative recurrence, tumor metastasis, and ultimately, death.[3]
The invasion and metastasis of cancer cells are critical factors that influence the prognosis of patients with colon cancer. The presence of a tumor thrombus in blood vessels is a prerequisite for tumor invasion of the vascular system and lymph node metastasis, further exacerbating the severity of the disease.[4,5] Vascular tumorous thrombosis infiltration is an important prognostic factor for many malignant tumors such as endometrial,[6] breast,[7] gastric, and colon cancer.[8] Several studies have reported that the incidence rate of tumor thrombus in the midvein of patients with colon cancer ranges from 10% to 89.5%.[9-11] Colon cancer thrombi mainly include direct tumor invasion, blood reflux, tumor cell exfoliation, adhesion, infiltration, and proliferation.[12] Cancer cells can infiltrate the submucosa, which is rich in vascular systems, leading to the formation of vascular tumorous thrombosis. Genetic mutations are critical for the development of vascular tumorous thrombosis in colon cancer.[13] However, the relationship between gene alterations and vascular tumorous thrombosis remains unclear. Therefore, identifying potential biomarkers of vascular tumorous thrombosis is critical for the development of effective treatments for colon cancer.
Vascular tumorous thrombosis allows tumor cells to better tolerate injury and promotes tumor cell metastasis.[14] One study demonstrated that the risk of death was 1.748 times higher in the vascular tumorous thrombosis-positive group than in the negative group, resulting in a significant decrease in overall survival.[15] Lymphovascular infiltration is a critical risk factor for sentinel lymph node metastasis in colon cancer.[16] Therefore, patients with stage II colon cancer and positive vascular tumorous thrombosis infiltration should receive chemotherapy even in the absence of lymph node metastasis after surgery. These findings have important implications for guiding preoperative neoadjuvant therapy.
Antivascular and anti-lymphatic therapies are of great significance in the management of patients with vascular tumorous thrombosis. Agents such as bevacizumab and sunitinib can inhibit angiogenesis and reduce lymph node metastasis, thereby providing significant benefits to these patients.[17,18] At present, the most common method to detect vascular tumorous thrombosis is tissue section hematoxylin-eosin (HE) staining[19]; however, the detection rate of vascular tumorous thrombosis in stage II colorectal cancer varies from 5.2% to 30%.[20] Unfortunately, the ability to distinguish lymphovascular from blood vessel invasion is poor.
In this study, two genes – catenin alpha 3 (CTNNA3) and FERM and PDZ domain-containing 4 (FRMPD4) – were significantly downregulated in the vascular tumorous thrombosis of colon adenocarcinoma. Further analysis revealed that these genes are associated with microsatellite instability (MSI) and immune infiltration. Gene mutation analysis revealed that these genes were affected by amplification, deep deletions, missense mutations, and methylation. Additionally, immune cell infiltration analysis revealed that these two genes were associated with different types of immune cell infiltration. Finally, we found that these two genes were downregulated at the messenger ribonucleic acid (mRNA) and protein levels in patients with colon adenocarcinoma thrombus. These findings suggest that CTNNA3 and FRMPD4 are potential biomarkers for the diagnosis and treatment of colon adenocarcinoma thrombi and provide valuable insights for the development of targeted therapies.
MATERIALS AND METHODS
Patient data acquisition
Ribonucleic acid (RNA) sequencing microarray data (GSE127069) for colon adenocarcinoma tissues and adjacent tissues of third-stage colon cancer patients with blood vascular thrombus were downloaded from Gene Expression Omnibus (GEO) (https://www.ncbi.nlm.nih.gov/geo/). Twenty samples of colon adenocarcinoma, vascular tumorous thrombosis, and adjacent normal tissues were obtained from the Second People’s Hospital of Deyang City for gene expression analysis. All patients were admitted to the hospital from August 2021 to November 2021, and the patients with left colon cancer included nine males and 11 females. The clinical stages were stages II (n = 15) and III (n = 5). The pathological type of the tumor was tubular adenocarcinoma. Tumor cell clusters found in the intratumoral or perivascular spaces that are confirmed by HE morphology and validated by CD34 vascular markers are defined as tumor thrombus. This study was approved by the Second People’s Hospital Ethics Committee (DEYL-2021-11) and informed consent was obtained from all patients. All methods were performed in accordance with the relevant guidelines and regulations.
Differentially expressed genes
The limma package was used to perform batch corrections for the GSE127069 database. R software (version 4.0.5) was used to identify differentially expressed genes in the normal (n = 3) and colon vascular tumorous thrombosis (n = 3) groups. The cutoff criteria were false discovery rate (FDR) (P < 0.05) and logFC >1.
Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis
The R software was used to perform GO and KEGG analyses. Eighty-eight differentially expressed genes and logFC values were selected for functional enrichment analysis of GO and KEGG. KEGG pathway data were obtained from Kanehisa Laboratories as described in previous studies.[21-23]
Protein-protein interaction
The protein-protein interaction (PPI) network was analyzed online using the STRING website (https://string-db.org/). The co-expression relationships of the 88 differentially expressed genes were visualized using a PPI network via “search,” “multiple proteins,” and “Homo sapiens” modules.
Association between gene expression and MSI in pan-cancer
The MSI score was obtained from The Cancer Genome Atlas (TCGA) database. Spearman’s correlation coefficient was used to evaluate the correlation between cancer gene expression and MSI. The radar map was designed using the ‘fmsb’ package from R software to visualize both indicators.
Correlation of gene expression with tumor immune microenvironment and immune cell infiltration
The ESTIMATE algorithm (“estimate” and “limma” packages in R software) was employed to calculate immune scores for predicting tumor purity and infiltrating immune cells in colon adenocarcinoma. The “ggplot2,” “ggpubr,” and “ggExtra” packages in R software were employed to evaluate the correlation between CTNNA3 or FRPMD4 mRNA expression and the tumor immune microenvironment.
Correlation analysis of immune cell infiltration
Pearson’s correlation coefficient was used to analyze the correlation between CTNNA3 and FRPMD4 mRNA expression and immune cell infiltration via “Gene,” “COAD,” and “submit” modules. The infiltration data of B cells, CD4+ T cells, CD8+ T cells, dendritic cells (DCs), macrophages, neutrophils, and T cell regulatory (Treg) cells can be downloaded from the Tumor IMmune Estimation Resource (TIMER) 2.0 database (http://timer.cistrome.org/).
cBioPortal online analysis
Gene mining and analysis were performed using the cBioPortal (https://www.cbioportal.org/), and the TCGA colon adenocarcinoma database was selected for “Explore Selected Studies.” The “OncoPrint,” “Plots,” “Mutations,” and “Genomics Alterations” modules were used to perform gene mining analysis.
Immunohistochemistry (IHC)
Human colon adenocarcinoma samples, colon adenocarcinoma thrombi, and adjacent normal tissues were used for HE and IHC staining. The brief steps for HE staining are as follows: place the slices in a 75% ethanol solution for defatting; immerse the tissue slices in a hematoxylin solution for 5 minutes of staining. After washing, stain with 0.5% eosin solution for 3 minutes. IHC was performed according to the manufacturer’s instructions (cat. no. SP9001; ZSGB-BIO). Primary antibodies anti-FRMPD, (ab113420, Abcam), anti-CTNNA3 (ab184916, Abcam), and anti-CD34 (ab81289, Abcam) were used for IHC. The secondary antibody used was a biotin-labeled rabbit anti-goat antibody. The specific operative steps were performed as previously described.[24] The immunoreactive score (IRS) was used to evaluate protein expression levels, which can be simplified as IRS = staining intensity (SI) × percentage of positive cells (PP). SI was assigned as follows: 0 = negative; 1 = weak positive; 2 = moderate positive; 3 = strong positive. The PP was defined as 0 = 0%; 1 = 0–25%; 2 = 25–50%; 3 = 50–75%; 4 = 75–100%.
Quantitative real-time polymerase chain reaction (PCR)
RNA extraction, reverse transcription, and PCR amplification were performed according to the manufacturer’s instructions (Takara Bio, Inc.). The specific operative steps were performed as previously described.[25] The cDNA was used to perform reverse transcription-quantitative polymerase chain reaction (RT-qPCR). The thermocycling program consisted of an initial denaturation step at 95°C for 30 s, followed by 40 cycles of denaturation, annealing, elongation, and final extension (95°C for 5 s and 60°C for 30 s). The primer sequences were as follows: GAPDH sense, 5′-CAATGACCCCTTCATTGACC-3′ and antisense, 5′-GACAAGCTTCCCGTTCTCAG-3′; CTNNA3 sense, 5′- TTTCTTTGCTGAGCCTCGTCTG-3′ and antisense, 5′- GGTCCAAACATTCACCGTGGAG-3′. FRMPD4 sense, 5′- GGAGGAGGACCTTGAAGGAG-3′ and antisense, 5′- AAGCCTCTTGAGAGAACGTG-3′. Melting curve analysis revealed a single peak, indicating good specificity. All reactions were performed in triplicate. The relative expression of the gene to GAPDH (CTNNA3/GAPDH or FRMPD4/GAPDH) was calculated using the 2−∆∆Cq method.
Statistical analysis
GraphPad Prism 7.0 was used for statistical analysis. Student’s t-tests were used to perform differential comparisons between two groups. Comparisons between three or more groups are analyzed using one-way analysis of variance (ANOVA). A P value <0.05 was considered to be statistically significant. The integrated analysis of these data was performed using R software (version 4.0.3).
RESULTS
CTNNA3 and FRMPD4 are low expressed in colon adenocarcinoma tumor thrombus
Differential analysis of the gene expression profiles of the paranormal colon adenocarcinoma (n = 3) and the colon adenocarcinoma thrombus (n = 3) groups was performed using the GSE127069 chip. A volcano map [Figure 1a] and a heat map [Figure 1b] were used to visualize differentially expressed genes. The results showed that CTNNA3 and FRMPD4 were specifically downregulated in colon adenocarcinoma tumor thrombus samples. The protein-protein interaction network also visualized the co-expression of differentially expressed genes [Figure 2]. Analysis of the number of PPI nodes showed that the number of CTNNA3 and FRMPD4 nodes was the highest [Figure 1c]. In addition, GO and KEGG enrichment analyses were performed on the 88 differentially expressed genes [Figure 1d and e], which showed that the differentially expressed genes were related to second-messenger-mediated signaling, positive regulation of cytosolic calcium ion concentration, regulation of cytosolic calcium ion concentration, cellular calcium ion homeostasis, and calcium ion homeostasis. KEGG analysis showed that the differentially expressed genes were related to chemokine signaling pathways, cocaine addiction, amphetamine addiction, gastric acid secretion, and insulin secretion.
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Figure 1: Differentially expressed genes were selected from the GSE127069 datasets. (a) Visualization of differentially expressed genes in volcano maps. (b) The heatmap shows differential gene expression between adjacent and embolus tissues of colon cancer. (c) Analysis of PPI network nodes. (d and e) The GO and KEGG analysis results show that 88 differentially expressed genes were related to calcium ion, the chemokine signaling pathway, etc
Figure 2: The PPI network of differentially expressed genes
CTNNA3 and FRMPD4 are related to MSI and the immune microenvironment
To further verify the expression and function of CTNNA3 and FRMPD4 in colon adenocarcinoma, we performed pan-cancer analysis using the TCGA database. The results showed that the expression of CTNNA3 and FRMPD4 in colon adenocarcinoma was lower than that in normal tissues [Figure 3a and c]; however, there was no significant difference in their expression between tumor stages [Figure 3b and d]. MSI is caused by a defect in the mismatch repair gene and is strongly correlated with the occurrence of tumors. Clinically, MSI has been used as an important molecular marker for the prognosis of colorectal cancer and in the formulation of adjuvant treatment programs. We found that CTNNA3 and FRMPD4 positively correlated with MSI in colon adenocarcinoma [Figure 3e and f]. Owing to the tumor immune microenvironment, heterogeneity between tumor cells is activated, thereby increasing multidrug resistance and causing tumor cell progression and metastasis. Therefore, it was reasonable to explore the correlation between the tumor immune microenvironment and CTNNA3 and FRMPD4 expression in colon adenocarcinoma. The ESTIMATE algorithm was used to calculate the immune cell scores for colon adenocarcinoma. The results showed that the expression of CTNNA3 or FRMPD4 was positively correlated with immune scores in colon adenocarcinoma [Figure 3g and h], indicating that the levels of CTNNA3 and FRMPD4 expression were upregulated as the number of immune cells increased.
Figure 3: Pan-cancer analysis of CTNNA3 and FRMPD4. (a and c) The expression of CTNNA3 and FRMPD4 in 33 cancers. *<0.05, **P < 0.01, ***P < 0.001. (b and d) The expression of CTNNA3 and FRMPD4 in the AJCC stage of colon cancer. (e and f) The relationship between CTNNA3 and FRMPD4 and MSI in 33 cancers. (g and h) The relationship between CTNNA3 and FRMPD4 and tumor immune microenvironment in colon cancer. MSI, microsatellite instability; AJCC, American Joint Committee on Cancer
CTNNA3 and FRMPD4 are related to the infiltration of immune cell subtypes
To analyze the relationship between CTNNA3 or FRMPD4 expression and immune cell infiltration in colon adenocarcinoma, the correlation between CTNNA3 or FRMPD4 expression and immune cell subtype infiltration was evaluated using TIMER 2.0. The results have shown that the correlation coefficients between purity, B cells, CD4+ T cells, CD8+ T cells, DCs, macrophages, neutrophils, Tregs, and CTNNA3 were −0.152, 0.005, 0.22, 0.044, 0.224, 0.27, 0.207, and 0.031, respectively [Figure 4a, P < 0.001]. Additionally, the correlation coefficients between purity, B cells, CD4+ T cells, CD8+ T cells, DCs, macrophages, neutrophils, Tregs, and FRMPD4 were −0.132, −0.207, 0.317, 0.098, 0.364, 0.318, 0.311, and −0.011, respectively [Figure 4b, P < 0.001].
Figure 4: Analysis of CTNNA3, FRMPD4, and immune cell subtype infiltration. (a) The correlation coefficients between expression of CTNNA3 and purity, B cells, CD4+ T cells, CD8+ T cells, DCs, macrophages, neutrophils, and Tregs, and CTNNA3 were −0.152, 0.005, 0.22, 0.044, 0.224, 0.27, 0.207, and 0.031, respectively. (b) The correlation coefficients between the expression of CTNNA3 and purity, B cells, CD4+ T cells, CD8+ T cells, DCs, macrophages, neutrophils, and Tregs, and FRMPD4 were −0.132, −0.207, 0.317, 0.098, 0.364, 0.318, 0.311, and −0.011, respectively
Gene mutations of CTNNA3 and FRMPD4 are associated with vascular invasion indicator
To further explore the functions of CTNNA3 and FRMPD4 in the colon adenocarcinoma thrombus, we used the cBioPortal online tool to analyze gene functions. The genetic changes in CTNNA3 or FRMPD4 and the relationship between vascular invasion indicators are shown in Figures 5a and 6a, respectively. The results indicated that missense mutations in CTNNA3 were related to vascular invasion indicators and that missense mutations and deep deletions of FRMPD4 were related to vascular invasion indicators. Next, we analyzed the genes related to genetic alterations and found that the genetic alteration of CTNNA3 was related to TNN, PIK3CA, MACF1, TENM3, and RIMS1 [Figure 5b], whereas the genetic alteration of FRMPD4 was related to TLR7, FAM9B, WWC3, MXRA5, and DMD [Figure 6b]. Analysis of the correlation between gene mRNA expression and copy number variation showed that the mRNA expression of CTNNA3 and FRMPD4 was related to shallow deletion, diploidy, and gain [Figure 5c and 6c]. Interestingly, the mRNA expression of CTNNA3 was also correlated to gene methylation (HM450) [Figure 5d, Spearman, R = 0.34; Pearson, R = 0.42, P < 0.001]. Mutation site analysis results showed that the mutation of CTNNA3 was located at Y414C [Figure 5e] and that the mutation site of FRMPD4 was located at E619A/D [Figure 6d].
Figure 5: Analysis of gene characteristics of CTNNA3. (a) CTNNA3 gene mutation distribution and its relationship with markers of vascular infiltration. (b) Genes related to genetic changes in CTNNA3. (c) The relationship between CTNNA3 mRNA expression and copy number variation. (d) The relationship between CTNNA3 mRNA expression and methylation (HM450). (e) The mutation site of CTNNA3
Figure 6: Analysis of gene characteristics of FRMPD4. (a) FRMPD4 gene mutation distribution and its relationship with markers of vascular infiltration. (b) Genes related to genetic changes in FRMPD4. (c) The relationship between FRMPD4 mRNA expression and copy number variation. (d) The mutation site of FRMPD4
CTNNA3 and FRMPD4 were downregulated in patients with colon adenocarcinoma thrombus
Finally, to validate the expression of CTNNA3 and FRMPD4 in clinical practice, we collected data from 20 patients (15 at stage II and five at stage III) with colon adenocarcinoma thrombus. We performed gene mRNA expression verification, which showed that the expression of CTNNA3 and FRMPD4 mRNA in stage II and III colon adenocarcinoma emboli was lower than that in normal adjacent tissues [Figure 7a, b, d, and e]. HE and CD34 staining were used to determine the morphology of the tumor tissue and tumor thrombus, respectively [Figure 7g, h]. The expression of CTNNA3 and FRMPD4 in stages II and III tumor thrombus tissues was lower than that in normal tissues [Figure 7i and j]. There was no difference in the expression of CTNNA3 or FRMPD4 in stage II and colon adenocarcinoma emboli [Figure 7c–j].
Figure 7: Expression of CTNNA3 and FRMPD4 in patients with colon vascular tumorous thrombosis (II stage and III stage). (a–f) CTNNA3 and FRMPD4 mRNA expression in normal tissues and tumor thrombus adjacent to colon cancer. (g and h) Immunohistochemical staining (CTNNA3, FRMPD4, and CD34) and HE staining of normal tissues adjacent to colon cancer and tumor thrombus (×200). (i and j) Immunohistochemical scores of normal tissue adjacent to colon cancer and tumor thrombus. Data are presented as mean ± standard deviation, ** P < 0.01, *** P < 0.001. n.s., not significant
DISCUSSION
In this study, we analyzed the gene expression profiles of colon adenocarcinoma tissues with a vascular tumorous thrombosis from GSE127069 and identified potential biomarkers using the CTNNA3 and FRMPD4 nodes. The functions of these genes were further explored using the TCGA and cBioPortal databases. Subsequently, the expression levels of these genes were validated using collected clinical samples. These findings suggest that CTNNA3 and FRMPD4 may serve as biomarkers of vascular tumorous thrombosis in colon adenocarcinoma. Vascular tumorous thrombosis is a hallmark of tumor cells invading adjacent blood and lymphatic vessels and is often an early indicator of lymph node metastasis.[26] Both domestic and foreign guidelines regard vascular tumorous thrombosis as one of the items used to evaluate risk factors for colorectal cancer.[27,28]
Vascular tumorous thrombosis not only indicates a poor prognosis but also signifies micrometastasis.[29] Several studies have demonstrated that vascular invasion is related to the depth of tumor invasion and lymph node metastasis.[30] Our findings revealed that CTNNA3 and FRMPD4 were downregulated in vascular tumorous thrombosis in colon cancer and were related to calcium ion homeostasis. Calcium metabolism is closely associated with thrombosis,[31] which could explain why CTNNA3 and FRMPD4 have been identified as potential biomarkers of vascular tumorous thrombosis in colon adenocarcinoma. Some studies have found that tumor cells can promote the formation and stability of vascular tumorous thrombosis by enhancing the calcium signaling pathway, and calcium ion channels and calcium-binding proteins may play a key role in this process.[32] In addition, calcium ions can regulate various biological behaviors of tumor cells such as growth, invasion, and metastasis.[33] However, the specific mechanism of the relationship between vascular tumorous thrombosis and calcium homeostasis is not yet fully understood and requires further investigation.
In the human genome, MSI refers to a class of short tandem repeat DNA sequences comprising one to six nucleotides and arranged in tandem repeats. Due to differences in the number of core repeat units, MSI exhibits population polymorphism. Popat S, et al.[34] reported a meta-analysis of 7,642 patients with stage II colorectal cancer. Compared with patients with microsatellite stability (MSS), the risk of death in patients with high-level MSI (MSI-H) was 0.65 (95% CI, 0.59–0.71), representing a reduction of up to 35%. Currently, there is ample evidence to support the use of MSI-H as a reliable marker for the prognosis of patients with stage II colorectal cancer.[35] It has also been observed that tumors with MSI-H typing have high immune cell infiltration against new antigens, but this effect is offset by immune checkpoint suppressor ligands, such as PD-L1, which bind to PD-1 and prevent T-cell activation.[36] Studies have reported that patients with MSI-H, intrahepatic cholangiocarcinoma (ICC), and thrombosis may benefit from treatment with immune checkpoint inhibitors (ICIs; pembrolizumab), suggesting that MSI-H could serve as a therapeutic reference for patients with vascular tumorous thrombosis.[37] Consistent with previous studies, we observed that CTNNA3 and FRMPD4 were positively correlated with MSI, immune microenvironment, and immune cell subtype infiltration. Moreover, studies have shown that the methylation level of DNAH17 can effectively predict vascular tumorous thrombosis.[32] In summary, MSI, tumor immune subtype, and methylation are related to vascular tumorous thrombosis.
However, the detection technology for vascular cancer thrombi varies, resulting in a significant difference in the detection rate and a high incidence of false negatives, which may limit the value of vascular cancer thrombi and hinder our understanding. A study of 75 cases of colorectal cancer found that the lymphatic infiltration rate of HE staining was 19%, while the detection rate of lymphatic invasion by the monoclonal antibody D2-40 was 40% (P < 0.001).[38] Morgantetti G, et al.[39] suggested that the CD34 antibody is the preferred marker for evaluating vascular cancer thrombi owing to its stability, sensitivity, and repeatability in detecting capillaries and small vascular endothelial cells in tumors. In our study, we used CD34 as a marker for vascular thrombus verification using IHC, which further confirmed the expression of candidate genes in vascular tumorous thrombosis.
We further found that both CTNNA3 and FRMPD4 had a high proportion of deep deletions in gene mutations in colon adenocarcinoma, which explains the downregulation of these genes in the vascular tumorous thrombosis of colon adenocarcinoma. CTNNA3 is a tumor suppressor gene that is frequently mutated in laryngeal carcinoma and is downregulated in bladder urothelial carcinoma.[40] It also acts as a tumor suppressor in hepatocellular carcinoma by inhibiting the proliferation, migration, and invasion of tumor cells by inhibiting the V-Akt Murine Thymoma Viral Oncogene Homolog (AKT) signaling pathway and reducing the expression of PCNA and MMP-9.[41] Although FRMPD4 has not been extensively studied in tumors, it plays a crucial role in normal cognitive development and function in humans and mice. Mutations in FRMPD4 may lead to X-linked mental retardation syndrome by altering the morphology of dendritic spines in glutamatergic neurons.[42] Additionally, we observed downregulation of CTNNA3 and FRMPD4 in stages II and III colon cancer vascular tumorous thrombosis, respectively, suggesting that they may serve as biomarkers for vascular tumorous thrombosis in colon adenocarcinoma.
This study has several strengths, including the utilization of multiple databases to analyze selected candidate genes and the verification of results using clinical samples. However, this study has several limitations. For instance, the number of clinical samples available for verification is limited, and the biological functions of these candidate genes have not been fully explored. Although there is currently no direct evidence showing the exact mechanisms by which CTNNA3 and FRMPD4 contribute to tumor thrombosis formation, future studies should be designed to further explore this. In future studies, we will collect colon vascular tumorous thrombosis tissue and conduct double fluorescent staining experiments for candidate genes (CTNNA3 and FRMPD4) and the vascular marker CD34. We will design experiments to overexpress or silence candidate genes and validate their effects on the proliferation and metastasis of colon cancer cells while observing their impact on colon vascular tumorous thrombosis formation in mice.
CONCLUSION
Our study has several strengths, including the integration of multiple databases and the use of clinical samples to validate our findings. Our analysis revealed that CTNNA3 and FRMPD4 are associated with important cancer-related biological functions, including MSI, immune subtype infiltration, and methylation, in colon adenocarcinoma. Additionally, mutations in these genes are linked to indicators of vascular invasion, suggesting that they may serve as potential biomarkers for patients with colon adenocarcinoma thrombi.
Availability of data and materials
GSE127069 was downloaded from Gene Expression Omnibus (GEO) (https://www.ncbi.nlm.nih.gov/geo/). The TCGA datasets were visualized in cBioPortal (https://www.cbioportal.org/).
Financial support and sponsorship
Nil.
Conflicts of interest
There are no conflicts of interest.
Acknowledgments
We thank the TCGA, Kanehisa Laboratories, and GSE127069 for sharing large amounts of data.
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