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Colorectal cancer (CRC) is the third most common cancer and the second leading cause of cancer-related deaths in the United States. The purpose of this study was to evaluate the gene expression differences in different stages of CRC. Gene expression data on 433 CRC patient samples were obtained from The Cancer Genome Atlas (TCGA). Gene expression d...
Citations
... Several previous studies reported that AMIGO2 plays a role in cancer, but these studies exclusively investigated its role when expressed in tumor cells [17][18][19][20][21][22][23][24][25]. For example, knockdown of the AMIGO2 gene decreased proliferation, invasion and adhesion to liver endothelial cells, whereas overexpression accelerated these processes in CRC cell lines [17,18,22]. ...
... A putative role of AMIGO2 in CRC was previously investigated, but all of these studies exclusively focused on its expression in tumor cells [17][18][19][20][21][22][23][24][25]. Experimentally induced upregulation or inhibition of AMIGO2 expression activated or inhibited proliferation and migration of these cells, respectively [17,18,22]. ...
Secretomes of cancer-associated fibroblasts (CAFs) in colorectal cancer (CRC) contribute to malignancy. Detailed knowledge is available on the components and functions of CAF secretomes. Little is known about the regulation of CAF secretomes. Here, we searched for receptor-like membrane-bound molecules in CAFs, which may regulate the production and release of tumor-activating secretomes. The adhesion molecule with Ig-like domain 2 (AMIGO2) was significantly upregulated in cultivated CAFs compared to normal tissue-associated fibroblasts (NAFs), and this was confirmed in patient-derived tissues. AMIGO2 expression was low or absent in healthy colon, significantly increased in fibroblasts of primary CRC, and highest in the stromal tissues of CRC-derived liver metastases. AMIGO2 expression in CAFs correlated with a higher T-category, increased lymph node metastasis, progressed tumor stages and was associated with reduced survival in different cohorts of CRC patients. Interestingly, AMIGO2 expression was induced by transforming growth factor-β and higher in female patients, who exhibit a more aggressive disease course. In functional studies, conditioned media of NAFs with experimentally induced AMIGO2 overexpression enhanced proliferation and migration of different CRC tumor cells, while siRNA-mediated inhibition of AMIGO2 in CAFs attenuated these effects. Accordingly, therapeutic inhibition of the receptor-like AMIGO2 protein in CRC CAFs could prevent tumorigenic secretomes in CRC.
... The figure shows that for CRC, disregarding the ischemia time variable effects (for which T 1 is the reference variable), the tumor grade and stage as well as the alcohol consumption status of the patients relative to their respective references are the strongest predictors of differential biomolecule expression as expected [11,12]. High grade has not only high coefficient estimates, but also the highest number of biomolecules with significant effects in each modality (491, 79, and 72, for mRNA, protein and phosphosite, resp). ...
... To reveal independent variables which could dominate differential expression in addition to ischemia time, we performed a systematic confounder analysis. As Fig. 3 shows, increasing ischemia times even surpass the effect estimators of alcohol consumption, grade, and cancer stage in the CRC cohort, which are known to strongly affect biomolecule expression in cancer tissue [11,12]. However, the number of biomolecules for which the grade-covariable is significantly correlated to differential expression is not surpassed by the ischemia effect. ...
Tumor tissue collections are used to uncover pathways associated with disease outcomes that can also serve as targets for cancer treatment, ideally by comparing the molecular properties of cancer tissues to matching normal tissues. The quality of such collections determines the value of the data and information generated from their analyses including expression and modifications of nucleic acids and proteins. These biomolecules are dysregulated upon ischemia and decompose once the living cells start to decay into inanimate matter. Therefore, ischemia time before final tissue preservation is the most important determinant of the quality of a tissue collection. Here we show the impact of ischemia time on tumor and matching adjacent normal tissue samples for mRNAs in 1664, proteins in 1818, and phosphosites in 1800 cases (tumor and matching normal samples) of four solid tumor types (CRC, HCC, LUAD, and LUSC NSCLC subtypes). In CRC, ischemia times exceeding 15 min impacted 12.5% (mRNA), 25% (protein), and 50% (phosphosites) of differentially expressed molecules in tumor versus normal tissues. This hypoxia- and decay-induced dysregulation increased with longer ischemia times and was observed across tumor types. Interestingly, the proteomics analysis revealed that specimen ischemia time above 15 min is mostly associated with a dysregulation of proteins in the immune-response pathway and less so with metabolic processes. We conclude that ischemia time is a crucial quality parameter for tissue collections used for target discovery and validation in cancer research.
... [34] NEK4 promotes malignant progression by regulating transformation in lung cancer, [35,36] and it may predict the stages of cancer. [37] NEK5 can facilitate the proliferation of BC cells [38,39] and the invasion of nasopharyngeal carcinoma (NPC). [40] NEK6 is overexpressed in several cancers, including THCA, [41] HCC, [42] BC, [43] PC, [12] colon adenocarcinoma, [44] and RCC. ...
Clear cell renal cell carcinoma (ccRCC) is a fatal urological malignancy. Members of the never-in mitosis gene A (NIMA)-related kinase (NEK) family have been found to participate in the progression of several cancers and could be used as target genes to treat corresponding diseases. Nonetheless, the prognostic value and immune infiltration levels of NEK family genes in ccRCC remain unknown. The GSCA, TIMER, and GEPIA databases were utilized to examine the differential expression of NEK family members in ccRCC, and the Kaplan–Meier plotter was utilized to analyze the prognosis. The STRING database was used to construct a protein-protein interaction network. Analysis of function was performed by the Sangerbox tool. In addition, the relationship between NEK family genes and immune cells was explored using the TIMER and TISIDB databases. Finally, we used quantitative real-time PCR (qPCR) and immunohistochemistry (IHC) for experimental verification. Transcriptional levels of NEK2, NEK3, NEK5, NEK6, and NEK11 significantly differed between ccRCC and normal tissues. Moreover, there was a significant correlation between NEK1, NEK2, NEK4, NEK8, NEK9, and NEK10 and their clinicopathological stages in patients with ccRCC. Based on survival analysis, ccRCC patients with high transcriptional levels of NEK2, NEK3, NEK8, and NEK10 and low transcriptional levels of NEK1, NEK4, NEK5, NEK6, NEK7, NEK9, NEK11 had shorter survival times. Additionally, a significant relationship was observed between NEK family members and immune cell infiltration, immune cell markers, and immune subtypes. These results indicate that NEK family members are significantly differentially expressed in ccRCC, and a significant correlation exists between the NEK family and prognosis and immune infiltration. NEK family members may act as therapeutic targets and prognostic indicators in ccRCC.
... The figure shows that for CRC, disregarding the ischemia time variable effects (for which T 1 is the reference variable), the tumour grade and stage as well as the alcohol consumption status of the patients relative to their respective references are the strongest predictors of differential biomolecule expression as expected [12,13]. High grade has not only high coefficient estimates, but also the highest number of biomolecules with significant effects in each modality (491, 79, and 72, for mRNA, protein and phosphosite, resp.). ...
... To reveal independent variables which could dominate differential expression in addition to ischemia time, we performed a systematic confounder analysis. As Figure 3 shows, increasing ischemia times even surpass the effect estimators of alcohol consumption, grade, and cancer stage in the CRC cohort, which are known to strongly affect biomolecule expression in cancer tissue [12,13]. However, the number of biomolecules for which the grade-covariable is significanctly correlated to differential expression is not surpassed by the ischemia effect. ...
Tumour tissue collections are used to uncover pathways associated with disease outcomes that can also serve as targets for cancer treatment, ideally by comparing the molecular properties of cancer tissues to matching normal tissues. The quality of such collections determines the value of the data and information generated from their analyses including expression and modifications of nucleic acids and proteins. These biomolecules are dysregulated upon ischemia and decomposed once the living cells start to decay into inanimate matter. Therefore, ischemia time before final tissue preservation is the most important determinant of the quality of a tissue collection. Here we show the impact of ischemia time on tumour and matching adjacent normal tissue samples for mRNAs in 1,664, proteins in 1,818 and phosphoproteins in 1,800 cases (tumour and matching normal samples) of four solid tumour types (CRC, HCC, LUAD and LUSC NSCLC subtypes). In CRC, ischemia times exceeding 15 minutes impacted 12.5% (mRNA), 25% (protein) and 50% (phosphosites) of differentially expressed molecules in tumour versus normal tissues. This hypoxia- and decay-induced dysregulation increased with longer ischemia times and was observed across tumour types. Interestingly, the proteomics analysis revealed that specimen ischemia time above 15 minutes is mostly associated with a dysregulation of proteins in the immune response pathway and less so with metabolic processes. We conclude that ischemia time is a crucial quality parameter for tissue collections used for target discovery and validation in prognostic cancer research.
... Moreover, the expression of NEK2 is highly linked to cancer occurrence, development, and drug resistance [11]. Additionally, NEK4 has been shown to play a key role in lung and colorectal cancers [12,13]. However, the roles of the different NEK family members in STAD have not been elucidated. ...
Never in mitosis gene A-related kinase (NEK) is an 11-membered family of serine/threonine kinases (NEK1-NEK11), which are known to play important roles in the formation and development of cancer. However, few studies have examined the roles of these kinases in the development of stomach adenocarcinoma (STAD). In this study, we conducted a comprehensive analysis of the relationships between the NEKs family members and STAD. The differential expression of the NEK genes in STAD was validated using The Cancer Genome Atlas (TCGA) and Tumor Immune Estimation Resource (TIMER) databases, and their prognostic and diagnostic values of NEKs in STAD were assessed using the Kaplan-Meier plotter and TCGA data. The effect of NEK expression on immune cell infiltration in STAD was analysed using the TIMER and TISIDB databases. The expression levels of the majority of the NEK family members were consistently upregulated in STAD, whereas that of NEK10 was downregulated. The upregulation of NEK2/3/4/5/6/8 was closely associated with clinicopathological parameters of patients, and the overexpressed levels of these proteins had good diagnostic value for the disease. NEK1/8/9/10/11 expression correlated with poor overall survival and post-progressive survival, whereas a higher NEK1/6/9/11 level implied worse first progressive survival. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses revealed that the NEKs may be related to immunological responses. Additionally, our study confirmed that these kinases correlated with immune cell infiltration and different immune infiltration subtypes in STAD. Our results suggest that NEK9 in particular has the potential to be used as a diagnostic and prognostic biomarker of STAD development and progression and an immune target for treatment of the disease. These findings expand our understanding of the biological functions of the NEK family members in STAD.
... It is upregulated during carcinogenesis and tumor progression in the colorectal adenoma-carcinoma sequence [18]. A recent study based on TCGA data identified RNF34 among the most significant differential expressed genes in CRC [19]. ...
... Moreover, high mRNA levels are strongly associated with unfavorable overall survival and are associated with aggressive and advanced tumor stages. Overexpression of RNF34 in CRC cell lines resulted in resistance to 5-fluorouracil (5-FU)-induced apoptosis via nuclear factor-kappa B (NF-kappaB) and enriched BCL-2 and BCL-X expression [19]. In RCC, enriched BCL-2 and BCL-X expression and NF-kappaB activation are also observed and might also contribute to chemotherapy resistance [20][21][22]. ...
... In RCC, enriched BCL-2 and BCL-X expression and NF-kappaB activation are also observed and might also contribute to chemotherapy resistance [20][21][22]. Interestingly, in CRC, RNF34 showed lower expression in advanced cancer stages [19]. Based on this observation, Huo et al. deduce an improved response to therapy with 5-FU in advanced CRC. ...
Introduction: Ring finger proteins play pivotal roles in diverse cellular processes and are implicated in contribution to cancer. Ring finger protein 34 (RNF34) has antiapoptotic and oncogenic properties. RNF34 is upregulated during carcinogenesis and tumor progression in the colorectal adenoma-carcinoma sequence and was already described to mediate chemoresistance. In clear cell renal cell carcinoma (ccRCC), however, the role and expression patterns of RNF34 are unknown.
Methods: First, we investigated the association of RNF34 mRNA expression with clinicopathological parameters and survival using data obtained from The Cancer Genome Atlas (TCGA) ccRCC cohort (N = 533). To assess RNA34 protein expression, we performed immunohistochemical (IHC) staining of an established ccRCC cohort (University of Bonn) in a tissue microarray (TMA) format. This validation cohort contains 109 primary ccRCC samples. IHC data were associated with clinicopathological parameters and overall survival (Kaplan-Meier analysis). Adjustment for covariables was done using the Cox regression model.
Results: RNF34 expression is correlated with adverse clinicopathological parameters. Survival analysis revealed an association between RNF34 expression and shortened survival. Cox regression analysis confirmed RNF34 expression as an independent prognostic parameter.
Conclusion: Our study provides evidence for RNF34 as a prognostic biomarker in ccRCC and points toward a major role of this protein in renal cell carcinoma carcinogenesis.
... Down-regulation of the AMIGO2 limits proliferation, migration, and invasion in gastric cancer cell lines [27]. Up-regulation of the AMIGO2 is related to terminal stage of colon cancer patients [28]. AMIGO2 also acts as a key promoter of malignant phenotype in breast cancer [29]. ...
Pancreatic ductal adenocarcinoma (PDAC) is a common kind of lethal cancer, with low early diagnostic rate and poor prognosis. In this study, we identified and verified the AMIGO2 with significant diagnostic and prognostic value in PDAC through LASSO regression combined with multiple machines learning methods, including RVM-RFE and Random Forest in TCGA and GEO datasets. The relevance between the expression of AMIGO2 and M2 polarization of macrophages was identified through pancancer, normal tissue, and cell lines data in TCGA, GTEx and CCLE datasets. The relevance between AMIGO2 and M2 polarization was then further identified in our local PDAC cohort. Finally, the role of AMIGO2 as cancer promoter and pivotal factor enrolled in M2 polarization was verified through siRNA transfection and M2 macrophages induction. These findings could facilitate diagnosis and treatment of PDAC. In addition, further research was deemed necessary on the deep mechanism between AMIGO2 and M2 polarization of macrophages in PDAC.
... Moreover, the transcriptome data of CRC available through TCGA [49] has been reanalyzed to find relevant genes related to different features of CRC. A differentially expressed gene analysis of CRC stages found 11 genes (NEK4, RNF34, HIST3H2BB, NUDT6, LRCh4, GLB1L, HIST2H4A, TMEM79, AMIGO2, C20orf135, and SPSB3) that change their expression depending on the stage [50]. For example, the NEK4 gene, which is involved in the senescence of cells, showed higher expression in stage I and the lowest expression in stage IV [50]. ...
... A differentially expressed gene analysis of CRC stages found 11 genes (NEK4, RNF34, HIST3H2BB, NUDT6, LRCh4, GLB1L, HIST2H4A, TMEM79, AMIGO2, C20orf135, and SPSB3) that change their expression depending on the stage [50]. For example, the NEK4 gene, which is involved in the senescence of cells, showed higher expression in stage I and the lowest expression in stage IV [50]. However, the whole gene expression pattern of the CRC patients was not different between stages since the principal component analysis was not able to show clear patterns [50]. ...
... For example, the NEK4 gene, which is involved in the senescence of cells, showed higher expression in stage I and the lowest expression in stage IV [50]. However, the whole gene expression pattern of the CRC patients was not different between stages since the principal component analysis was not able to show clear patterns [50]. In addition, TCGA data were used to find genes associated with overall survival [51]. ...
Colorectal cancer is a major health concern since it is a highly diagnosed cancer and the second cause of death among cancers. Thus, the most suitable biomarkers for its diagnosis, prognosis, and treatment have been studied to improve and personalize the prevention and clinical management of colorectal cancer. The emergence of omic techniques has provided a great opportunity to better study CRC and make personalized medicine feasible. In this review, we will try to summarize how the analysis of the omic layers can be useful for personalized medicine and the existing difficulties. We will discuss how single and multiple omic layer analyses have been used to improve the prediction of the risk of CRC and its outcomes and how to overcome the challenges in the use of omic layers in personalized medicine.
... High heterogeneity was observed in CRC, contributed by tumor cells and their tumor microenvironment (TME). Numerous studies have focused on the molecular mechanisms of increased heterogeneity in CRC, such as genetic alteration, transcriptome, non-coding RNA regulation, cancer-associated protein, and metabolism [5][6][7][8][9]. Three different pathways of genomic instability, including chromosomal instability, microsatellite instability, and CpG island methylation, have been recognized in the complex development of CRC. ...
... Although analysis of different transcriptomic features between tumor and normal mucosa is essential and is able to unveil potential therapeutic targets and early screening markers, the difference in genomic, transcriptomic, and proteomic features between early-stage and advanced-stage tumors is also important but has been rarely reported [15][16][17]. Several studies assessed the altered features of CRC during progression based on genomic or transcriptomic sequencing [5,[18][19][20]. Limited by a mixture of RNA-seq, the source of heterogeneity was difficult to be identified. ...
Background
Tumor heterogeneity is contributed by tumor cells and the microenvironment. Dynamics of tumor heterogeneity during colorectal cancer (CRC) progression have not been elucidated.
Methods
Eight single-cell RNA sequencing (scRNA-seq) data sets of CRC were included. Milo was utilized to reveal the differential abundance of cell clusters during progression. The differentiation trajectory was imputed by using the Palantir algorithm and metabolic states were assessed by using scMetabolism. Three spatial transcription sequencing (ST-seq) data sets of CRC were used to validate cell-type abundances and colocalization. Cancer-associated regulatory hubs were defined as communication networks affecting tumor biological behaviors. Finally, quantitative reverse transcription polymerase chain reaction and immunohistochemistry staining were performed for validation.
Results
TM4SF1+, SOX4+, and MKI67+ tumor cells; CXCL12+ cancer-associated fibroblasts; CD4+ resident memory T cells; Treg; IgA+ plasma cells; and several myeloid subsets were enriched in stage IV CRC, most of which were associated with overall survival of patients. Trajectory analysis indicated that tumor cells from patients with advanced-stage CRC were less differentiated, when metabolic heterogeneity showed a highest metabolic signature in terminal states of stromal cells, T cells, and myeloid cells. Moreover, ST-seq validated cell-type abundance in a spatial context and also revealed the correlation of immune infiltration between tertiary lymphoid structures and tumors followed by validation in our cohort. Importantly, analysis of cancer-associated regulatory hubs revealed a cascade of activated pathways including leukocyte apoptotic process, MAPK pathway, myeloid leukocyte differentiation, and angiogenesis during CRC progression.
Conclusions
Tumor heterogeneity was dynamic during progression, with the enrichment of immunosuppressive Treg, myeloid cells, and fibrotic cells. The differential state of tumor cells was associated with cancer staging. Assessment of cancer-associated regulatory hubs suggested impaired antitumor immunity and increased metastatic ability during CRC progression.
... NEK4 is highly expressed in lung cancer, which promotes malignant progression by regulating transformation [35,36]. NEK4 was also found to be differentially expressed at each pathological stage in colorectal cancer, and thus it may predict the stages of cancer [37]. NEK5 is overexpressed in nasopharyngeal carcinoma. ...
Background
Clear cell renal cell carcinoma (ccRCC) is a fatal urological malignancy, and surgery remains the primary treatment. Members of the never in mitosis gene A (NIMA)-related kinase (NEK) family have been found to participate in the progression of several cancers and could be used as target genes to treat corresponding diseases. Nonetheless, the prognostic value and immune infiltration levels of NEK family genes in ccRCC remain unknown.
Methods
Gene Set Cancer Analysis (GSCA), Tumor Immune Estimation Resource (TIMER), and Gene Expression Profiling Interactive Analysis (GEPIA) databases were utilized to examine the differential expression of NEK family genes in ccRCC, and the Kaplan-Meier plotter was utilized to analyze the prognosis. The Search Tool for Retrieval of Interacting Genes(STRING) database was used to construct a protein-protein interaction network. Analysis of function was performed by the Sangerbox tool. Finally, the relationship between NEK family genes and immune cell infiltration was explored using the TIMER database.
Results
Transcriptional levels of NEK2, NEK3, NEK5, NEK6, and NEK11 significantly differed between ccRCC and normal tissues. Moreover, there was a significant correlation between NEK1, NEK2, NEK4, NEK8, NEK9, and NEK10 and their clinicopathological stages in patients with ccRCC. Based on survival analysis, ccRCC patients with high transcriptional levels of NEK2, NEK3, NEK8, and NEK10 and low transcriptional levels of NEK1, NEK4, NEK5, NEK6, NEK7, NEK9, NEK11 had shorter survival times. Additionally, a significant relationship was observed between immune cell infiltration and NEK family members.
Conclusions
These results indicate that NEK family members are significantly differentially expressed in ccRCC, and a significant correlation exists between the NEK family and prognosis and immune infiltration. NEK family members may act as therapeutic targets and prognostic indicators in ccRCC.
