A Combined ULBP2 and SEMA5A Expression Signature as a Prognostic and Predictive Biomarker for Colon Cancer

Molecular portraits of colorectal cancer morphological regions

Heterogeneity of colorectal carcinoma (CRC) represents a major hurdle towards personalized medicine. Efforts based on whole tumor profiling demonstrated that the CRC molecular subtypes were associated with specific tumor morphological patterns representing tumor subregions. We hypothesize that whole-tumor molecular descriptors depend on the morphological heterogeneity with significant impact on current molecular predictors. We investigated intra-tumor heterogeneity by morphology-guided transcriptomics to better understand the links between gene expression and tumor morphology represented by six morphological patterns (morphotypes): complex tubular, desmoplastic, mucinous, papillary, serrated, and solid/trabecular. Whole-transcriptome profiling by microarrays of 202 tumor regions (morphotypes, tumor-adjacent normal tissue, supportive stroma, and matched whole tumors) from 111 stage II-IV CRCs identified morphotype-specific gene expression profiles and molecular programs and differences in their cellular buildup. The proportion of cell types (fibroblasts, epithelial and immune cells) and differentiation of epithelial cells were the main drivers of the observed disparities with activation of EMT and TNF-α signaling in contrast to MYC and E2F targets signaling, defining major gradients of changes at molecular level. Several gene expression-based (including single-cell) classifiers, prognostic and predictive signatures were examined to study their behavior across morphotypes. Most exhibited important morphotype-dependent variability within same tumor sections, with regional predictions often contradicting the whole-tumor classification. The results show that morphotype-based tumor sampling allows the detection of molecular features that would otherwise be distilled in whole tumor profile, while maintaining histopathology context for their interpretation. This represents a practical approach at improving the reproducibility of expression profiling and, by consequence, of gene-based classifiers.

CSRP1 expression is associated with a mesenchymal, stroma-rich tumor profile and poor prognosis in colon cancer

Background/aim

Cysteine and glycine-rich protein 1 (CSRP1) is involved in the cysteine-rich protein family and is a marker of smooth muscle lineages. In colon cancer, the expression of this gene is associated with poor prognosis. In this study, the aim was to reevaluate its prognostic relationship in independent cohorts and explore potential underlying biological processes that are linked to aggressive behavior in tumors with high CSRP1 expression, such as epithelial-to-mesenchymal transition (EMT), stromal fractions in the tumor microenvironment, and consensus molecular subtypes (CMSs).

Materials and methods

RNA sequencing (RNAseq)-, microarray-, and single-cell RNAseq (scRNAseq)-based transcriptomic data were obtained from public databases. The EMT score was calculated based on the expression of E-cadherin and vimentin genes using a previously published method. The stromal score generated by the ESTIMATE method was utilized for the analysis of correlation with the CSRP1 expression. The scRNAseq data were analyzed via the Seurat R package. The immunohistochemistry-based protein level expression of CSRP1 was evaluated using the Human Protein Atlas database.

Results

Lower CSRP1 expression was noted in colon tumors compared to normal colon tissue. Patients with a high CSRP1 expression had shorter recurrence-free, overall, and disease-specific survivals in the GSE39582 and GSE17536 datasets (p < 0.05). The methylation level of the CSRP1 gene was negatively correlated (r = -0.57, p < 0.0001) with CSRP1 expression in The Cancer Genome Atlas colon adenocarcinoma dataset. CSRP1 expression was positively correlated with the expression of mesenchymal markers, EMT score, and stromal score obtained via the ESTIMATE method. CMS4 colon tumors had a significantly higher CSRP1 expression compared to other CMSs. Analysis of the scRNAseq data revealed that CSRP1 was expressed by epithelial cells and cancer-associated fibroblasts in the colorectal tumor microenvironment, which was also confirmed by the protein expression data from the Human Protein Atlas database.

Conclusion

CSRP1 expression is associated with CMS4, a more mesenchymal stroma-rich molecular profile, and poor prognosis in colon cancer.

ULBP2 is a biomarker related to prognosis and immunity in colon cancer

The study aimed to determine whether ULBP2 was associated with prognosis and immune infiltration in colon cancer (CC) and provided important molecular basis in order to early non-invasive diagnosis and immunotherapy of CC. Using The Cancer Genome Atlas database (TCGA) and ImmPort database, we extracted messenger RNA (mRNA) data of CC and immune-related genes, then we used "limma" package, "survival" package, and Venn overlap analysis to obtain the differentially expressed mRNA (DEmRNA) associated with prognosis and immunity of CC patients. "pROC" package was used to analyze receiver operating characteristics (ROC) of target gene. We used chi-square test and two-class logistics model to identify clinicopathological parameters that correlated with target gene expression. In order to determine the effects of target gene expression and clinicopathological parameters on survival, univariate and multivariate cox regression analyses were performed. We analyzed the related functions and signaling pathways of target gene by enrichment analysis. Finally, the correlation between target gene and tumor immune infiltrating was explored by ssGSEA and spearman correlation analysis. Results showed that ULBP2 was a target gene associated with immunity and prognosis in CC patients. CC patients with higher ULBP2 expression had poor outcomes. In terms of ROC, ULBP2 had an area under the curve (AUC) of 0.984. ULBP2 was associated with T stage, N stage, and pathologic stage of CC patients, and served as an independent predictor of overall survival in CC patients. Functional enrichment analysis revealed ULBP2 was obviously enriched in pathways connected with carcinogenesis and immunosuppression. The expression of ULBP2 was significantly associated with tumor immune cells and immune checkpoints according to ssGSEA and spearman correlation analysis. To conclude, our study suggested that ULBP2 was associated with tumor immunity, and might be a biomarker associated with the diagnosis and prognosis of CC patients, and a potential target of CC immunotherapy.

A Novel Gene List Identifies Tumors with a Stromal-Mesenchymal Phenotype and Worse Prognosis in Gastric Cancer

BACKGROUND

Molecular biomarkers that predict disease progression can help identify tumor subtypes and shape treatment plans. In this study, we aimed to identify robust biomarkers of prognosis in gastric cancer based on transcriptomic data obtained from primary gastric tumors.

METHODS

Microarray, RNA sequencing, and single-cell RNA sequencing-based gene expression data from gastric tumors were obtained from public databases. Freshly frozen gastric tumors (n = 42) and matched FFPE (formalin-fixed, paraffin-embedded) (n = 40) tissues from a Turkish gastric cancer cohort were used for quantitative real-time PCR and immunohistochemistry-based assessments of gene expression, respectively.

RESULTS

A novel list of 20 prognostic genes was identified and used for the classification of gastric tumors into two major tumor subgroups with differential stromal gene expression ("Stromal-UP" (SU) and "Stromal-DOWN" (SD)). The SU group had a more mesenchymal profile with an enrichment of extracellular matrix-related gene sets and a poor prognosis compared to the SD group. Expression of the genes within the signature correlated with the expression of mesenchymal markers ex vivo. A higher stromal content in FFPE tissues was associated with shorter overall survival.

CONCLUSIONS

A stroma-rich, mesenchymal subgroup among gastric tumors identifies an unfavorable clinical outcome in all cohorts tested.

A positive feedback loop driven by fibronectin and IL-1β sustains the inflammatory microenvironment in breast cancer

Inflammatory alterations of the extracellular matrix shape the tumor microenvironment and promote all stages of carcinogenesis. This study aims to determine the impact of cellular fibronectin on inflammatory facets of tumor-associated macrophages (TAMs) in breast cancer. Cellular fibronectin (FN) harboring the alternatively spliced extra domain A (FN-EDA) was determined to be a matrix component produced by the triple-negative breast cancer (TNBC) cells. High levels of FN-EDA correlated with poor survival in breast cancer patients. The proinflammatory cytokine IL-1β enhanced the expression of cellular fibronectin including FN-EDA. TAMs were frequently observed in the tumor areas rich in FN-EDA. Conditioned media from TNBC cells induced the differentiation of CD206⁺CD163⁺ macrophages and stimulated the STAT3 pathway, ex vivo. In the macrophages, the STAT3 pathway enhanced FN-EDA-induced IL-1β secretion and NF-κB signaling. In conclusion, our data indicate a self-reinforcing mechanism sustained by FN-EDA and IL-1β through NF-κB and STAT3 signaling in TAMs which fosters an inflammatory environment in TNBC.

Evaluation of an aldo-keto reductase gene signature with prognostic significance in colon cancer via activation of epithelial to mesenchymal transition and the p70S6K pathway

AKR1B1 and AKR1B10, members of the aldo-keto reductase family of enzymes that participate in the polyol pathway of aldehyde metabolism, are aberrantly expressed in colon cancer. We previously showed that high expression of AKR1B1 (AKR1B1HIGH) was associated with enhanced motility, inflammation and poor clinical outcome in colon cancer patients. Using publicly available datasets and ex vivo gene expression analysis (n = 51, Ankara cohort), we have validated our previous in silico finding that AKR1B1HIGH was associated with worse overall survival (OS) compared with patients with low expression of AKR1B1 (AKR1B1LOW) samples. A combined signature of AKR1B1HIGH and AKR1B10LOW was significantly associated with worse recurrence-free survival (RFS) in microsatellite stable (MSS) patients and in patients with distal colon tumors as well as a higher mesenchymal signature when compared with AKR1B1LOW/AKR1B10HIGH tumors. When the patients were stratified according to consensus molecular subtypes (CMS), AKR1B1HIGH/AKR1B10LOW samples were primarily classified as CMS4 with predominantly mesenchymal characteristics while AKR1B1LOW/AKR1B10HIGH samples were primarily classified as CMS3 which is associated with metabolic deregulation. Reverse Phase Protein Array carried out using protein samples from the Ankara cohort indicated that AKR1B1HIGH/AKR1B10LOW tumors showed aberrant activation of metabolic pathways. Western blot analysis of AKR1B1HIGH/AKR1B10LOW colon cancer cell lines also suggested aberrant activation of nutrient-sensing pathways. Collectively, our data suggest that the AKR1B1HIGH/AKR1B10LOW signature may be predictive of poor prognosis, aberrant activation of metabolic pathways, and can be considered as a novel biomarker for colon cancer prognostication.

Investigation and verification of the clinical significance and perspective of natural killer group 2 member D ligands in colon adenocarcinoma

This study investigated and verified the diagnostic and prognostic values of natural killer group 2 member D ligand (NKG2DL) genes in colon adenocarcinoma (COAD). We downloaded NKG2DLs expression data and corresponding clinical parameters from The Cancer Genome Atlas (TCGA) and used bioinformatics techniques to investigate the values of NKG2DLs in COAD. Then, we used the GSE40967 cohort to verify the prognostic value of NKG2DLs. Finally, we verified the ULBP2 expression level in tissues, and also investigated the diagnostic and prognostic values of ULBP2 in COAD. The diagnostic receiver operating characteristic curves showed that ULBP1, ULBP2, ULBP3, and RAET1L had high diagnostic values in COAD [Area Under Curve (AUC) > 0.9]. In TCGA cohort, the univariate and multivariate survival analyses suggested that ULBP2 was correlated with the prognosis of COAD recurrence-free survival (RFS) and overall survival (OS). In GSE40967 cohort, ULBP2 was associated with CC RFS and OS. Reverse transcription-quantitative polymerase chain reaction and immunohistochemistry results showed that ULBP2 was highly expressed in COAD tumor tissues (P < 0.05) and both had diagnostic values (AUC > 0.7). Validated survival analysis showed that the high expression of ULBP2 had a worse prognosis in COAD OS and RFS. Thus, ULBP2 might be an independent diagnostic and prognostic biomarker of COAD.

High-throughput proteomics of breast cancer interstitial fluid: identification of tumor subtype-specific serologically relevant biomarkers

Despite significant advancements in breast cancer (BC) research, clinicians lack robust serological protein markers for accurate diagnostics and tumor stratification. Tumor interstitial fluid (TIF) accumulates aberrantly externalized proteins within the local tumor space, which can potentially gain access to the circulatory system. As such, TIF may represent a valuable starting point for identifying relevant tumor-specific serological biomarkers. The aim of the study was to perform comprehensive proteomic profiling of TIF to identify proteins associated with BC tumor status and subtype. A liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis of 35 TIFs of three main subtypes: luminal (19), Her2 (4), and triple-negative (TNBC) (12) resulted in the identification of > 8800 proteins. Unsupervised hierarchical clustering segregated the TIF proteome into two major clusters, luminal and TNBC/Her2 subgroups. High-grade tumors enriched with tumor infiltrating lymphocytes (TILs) were also stratified from low-grade tumors. A consensus analysis approach, including differential abundance analysis, selection operator regression, and random forest returned a minimal set of 24 proteins associated with BC subtypes, receptor status, and TIL scoring. Among them, a panel of 10 proteins, AGR3, BCAM, CELSR1, MIEN1, NAT1, PIP4K2B, SEC23B, THTPA, TMEM51, and ULBP2, was found to stratify the tumor subtype-specific TIFs. In particular, upregulation of BCAM and CELSR1 differentiates luminal subtypes, while upregulation of MIEN1 differentiates Her2 subtypes. Immunohistochemistry analysis showed a direct correlation between protein abundance in TIFs and intratumor expression levels for all 10 proteins. Sensitivity and specificity were estimated for this protein panel by using an independent, comprehensive breast tumor proteome dataset. The results of this analysis strongly support our data, with eight of the proteins potentially representing biomarkers for stratification of BC subtypes. Five of the most representative proteomics databases currently available were also used to estimate the potential for these selected proteins to serve as putative serological markers.

Renin angiotensin system genes are biomarkers for personalized treatment of acute myeloid leukemia with Doxorubicin as well as etoposide

Despite the availability of various treatment protocols, response to therapy in patients with Acute Myeloid Leukemia (AML) remains largely unpredictable. Transcriptomic profiling studies have thus far revealed the presence of molecular subtypes of AML that are not accounted for by standard clinical parameters or by routinely used biomarkers. Such molecular subtypes of AML are predicted to vary in response to chemotherapy or targeted therapy. The Renin-Angiotensin System (RAS) is an important group of proteins that play a critical role in regulating blood pressure, vascular resistance and fluid/electrolyte balance. RAS pathway genes are also known to be present locally in tissues such as the bone marrow, where they play an important role in leukemic hematopoiesis. In this study, we asked if the RAS genes could be utilized to predict drug responses in patients with AML. We show that the combined in silico analysis of up to five RAS genes can reliably predict sensitivity to Doxorubicin as well as Etoposide in AML. The same genes could also predict sensitivity to Doxorubicin when tested in vitro. Additionally, gene set enrichment analysis revealed enrichment of TNF-alpha and type-I IFN response genes among sensitive, and TGF-beta and fibronectin related genes in resistant cancer cells. However, this does not seem to reflect an epithelial to mesenchymal transition per se. We also identified that RAS genes can stratify patients with AML into subtypes with distinct prognosis. Together, our results demonstrate that genes present in RAS are biomarkers for drug sensitivity and the prognostication of AML.

A novel 20-gene prognostic score in pancreatic adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is among the most lethal cancers. Known risk factors for this disease are currently insufficient in predicting mortality. In order to better prognosticate patients with PDAC, we identified 20 genes by utilizing publically available high-throughput transcriptomic data from GEO, TCGA and ICGC which are associated with overall survival and event-free survival. A score generated based on the expression matrix of these genes was validated in two independent cohorts. We find that this “Pancreatic cancer prognostic score 20 –PPS20” is independent of the confounding factors in multivariate analyses, is dramatically elevated in metastatic tissue compared to primary tumor, and is higher in primary tumors compared to normal pancreatic tissue. Transcriptomic analyses show that tumors with low PPS20 have overall more immune cell infiltration and a higher CD8 T cell/Treg ratio when compared to those with high PPS20. Analyses of proteomic data from TCGA PAAD indicated higher levels of Cyclin B1, RAD51, EGFR and a lower E-cadherin/Fibronectin ratio in tumors with high PPS20. The PPS20 score defines not only prognostic and biological sub-groups but can predict response to targeted therapy as well. Overall, PPS20 is a stronger and more robust transcriptomic signature when compared to similar, previously published gene lists.

Assessment of the Usefulness of the SEMA5A Concentration Profile Changes as a Molecular Marker in Endometrial Cancer

BACKGROUND

Semaphorin 5A (SEMA5A) functions not only in the nervous system but also in cancer transformation where its role has not yet been sufficiently studied and described.

OBJECTIVE

The aim of the study was to determine the changes in SEMA5A expression in endometrial cancer at various degrees of its differentiation (G1-G3) compared to control.

MATERIALS AND METHODS

The study group consisted of 45 patients with endometrial cancer at various grades: G1, 17; G2, 15; G3, 13. The control consisted of 15 women without neoplastic changes in the routine gynecological examination. The statistical analysis of immunohistochemical assessment of SEMA5A level was carried out using the Statistica 12 program based on the Kruskal-Wallis test and Dunn's post-hoc test (p<0.05).

RESULTS

The expression of SEMA5A (optical density) was observed in the control group (Me = 103.43) and in the study group (G1, Me = 140.72; G2, Me = 150.88; G3, Me = 173.77). Differences in expression between each grade and control and between individual grades turned out to be statistically significant (p<0.01). The protein level of SEMA5A expression increased with the decreasing degree of endometrial cancer differentiation.

CONCLUSION

In our research, we indicated the overexpression of SEMA5A protein in endometrial cancer. It is a valuable starting point for further consideration of the role of SEMA5A as a new supplementary molecular marker in endometrial cancer.

MiR-873, as a suppressor in cervical cancer, inhibits cells proliferation, invasion and migration via negatively regulating ULBP2

BACKGROUND

Cervical cancer (CC) remains a large burden in the developing countries. The tumor inhibitory role of miR-873 has been verified in a variety of cancers, however, whether miR-873 has a suppressive effect on CC remains unclear.

OBJECTIVE

The purpose of this study was to investigate the functional role of miR-873 in CC, as well as explore the underlying molecular mechanism.

METHODS

The prognostic values of miR-873 were assessed by Kaplan-Meier methods and cox regression models using the data which were downloaded from TCGA database. The expression of miR-873 was measured by RT-qPCR. Cell counting Kit-8, clone formation, and Transwell assays were used to assess the cell viability and metastasis, appropriately. The targeting relationship between miR-873 and ULBP2 was predicted by biological software and confirmed by dual luciferase reporter assay. Rescue assays were conducted to investigate whether miR-873 affects the phenotype of CC cells via regulating ULBP2.

RESULTS

We observed that miR-873 was low-expressed in CC. Up-regulation of miR-873 notably restrained the proliferation, invasion and migration of C33a cells. Meanwhile, down-regulation of miR-873 in SiHa cells presented the opposite outcomes. ULBP2 was forecasted and certified as a target of miR-873. The results of rescue assays showed that overexpression of ULBP2 could restore the proliferation and motility of CC cells that inhibited by miR-873.

CONCLUSION

MiR-873 suppressed the CC cells proliferation, invasion and migration via negatively regulating ULBP2, suggesting that miR-873 could serve as a valuable therapeutic target for CC therapy.

A Stemness and EMT Based Gene Expression Signature Identifies Phenotypic Plasticity and is A Predictive but Not Prognostic Biomarker for Breast Cancer

Aims: Molecular heterogeneity of breast cancer results in variation in morphology, metastatic potential and response to therapy. We previously showed that breast cancer cell line sub-groups obtained by a clustering approach using highly variable genes overlapped almost completely with sub-groups generated by a drug cytotoxicity-profile based approach. Two distinct cell populations thus identified were CSC(cancer stem cell)-like and non-CSC-like. In this study we asked whether an mRNA based gene signature identifying these two cell types would explain variation in stemness, EMT, drug sensitivity, and prognosis in silico and in vitro. Main methods:In silico analyses were performed using publicly available cell line and patient tumor datasets. In vitro analyses of phenotypic plasticity and drug responsiveness were obtained using human breast cancer cell lines. Key findings: We find a novel gene list (CNCL) that can generate both categorical and continuous variables corresponding to the stemness/EMT (epithelial to mesenchymal transition) state of tumors. We are presenting a novel robust gene signature that unites previous observations related either to EMT or stemness in breast cancer. We show in silico, that this signature perfectly predicts behavior of tumor cells tested in vitro, and can reflect tumor plasticity. We thus demonstrate for the first time, that breast cancer subtypes are sensitive to either Lapatinib or Midostaurin. The same gene list is not capable of predicting prognosis in most cohorts, except for one that includes patients receiving neo-adjuvant taxene therapy. Significance: CNCL is a robust gene list that can identify both stemness and the EMT state of cell lines and tumors. It can be used to trace tumor cells during the course of phenotypic changes they undergo, that result in altered responses to therapeutic agents. The fact that such a list cannot be used to identify prognosis in most patient cohorts suggests that presence of factors other than stemness and EMT affect mortality.

High Expression Levels of Long Noncoding RNA Small Nucleolar RNA Host Gene 18 and Semaphorin 5A Indicate Poor Prognosis in Multiple Myeloma

BACKGROUND

The aim of this study was to detect the expression of long noncoding RNA small nucleolar RNA host gene 18 (SNHG18) andsemaphorin 5A (SEMA5A) genes in multiple myeloma (MM) patients and to explore the correlation of the expression of these genes with the clinical characteristics and prognosis of MM patients.

METHODS

Forty-seven newly diagnosed MM, 18 complete remission MM, 13 refractory/relapse MM, and 22 iron deficiency anemia (serving as control) samples were extracted at the Department of Hematology, Second Affiliated Hospital of Xian Jiaotong University between January 2015 and December 2016. The clinical features of the MM patients are summarized. Real-time quantitative PCR was performed to analyze the relative expression levels of the SNHG18 and SEMA5Agenes. The clinical characteristics and overall survival (OS) of the MM patients were statistically analyzed while measuring different levels of SNHG18 and SEMA5Agene expression. At the same time, the correlation between the expression of SNHG18 and SEMA5A was also analyzed.

RESULTS

The analysis confirmed that SNHG18 and its possible target gene SEMA5A were both highly expressed in newly diagnosed MM patients. After analyzing the clinical significance of SNHG18 and SEMA5A in MM patients, we found that the expression of SNHG18 and SEMA5A was related to the Durie-Salmon (DS), International Staging System (ISS), and Revised International Staging System (R-ISS) classification systems, and the Mayo Clinic Risk Stratification for Multiple Myeloma (mSMART; p < 0.05). Moreover, we observed a significant difference in OS between the SNHG18/SEMA5A high expression group and the low expression group. We found a positive correlation between SNHG18 and SEMA5A expression (r = 0.709, p < 0.01). Surprisingly, the expected median OS times of both the SNHG18 and SEMA5Ahigh expression groups were significantly decreased, which was in contrast to those of both the SNHG18 and SEMA5Alow expression groups and the single-gene high expression group (p < 0.05).

CONCLUSION

High expression of both SNHG18 and SEMA5A is associated with poor prognosis in patients with MM.

Identification of Transcriptional Signatures of Colon Tumor Stroma by a Meta-Analysis

Background

The tumor stroma plays pivotal roles in influencing tumor growth, invasion, and metastasis. Transcriptional signatures of colon tumor stroma (CTS) are significantly associated with prognosis of colon cancer. Thus, identification of the CTS transcriptional features could be useful for colon cancer diagnosis and therapy.

Methods

By a meta-analysis of three CTS gene expression profiles datasets, we identified differentially expressed genes (DEGs) between CTS and colon normal stroma. Furthermore, we identified the pathways, upstream regulators, and protein-protein interaction (PPI) network that were significantly associated with the DEGs. Moreover, we analyzed the enrichment levels of immune signatures in CTS. Finally, we identified CTS-associated gene signatures whose expression was significantly associated with prognosis in colon cancer.

Results

We identified numerous significantly upregulated genes (such as CTHRC1, NFE2L3, SULF1, SOX9, ENC1, and CCND1) and significantly downregulated genes (such as MYOT, ASPA, KIAA2022, ARHGEF37, BCL-2, and PPARGC1A) in CTS versus colon normal stroma. Furthermore, we identified significantly upregulated pathways in CTS that were mainly involved in cellular development, immune regulation, and metabolism, as well as significantly downregulated pathways in CTS that were mostly metabolism-related. Moreover, we identified upstream TFs (such as SUZ12, NFE2L2, RUNX1, STAT3, and SOX2), kinases (such as MAPK14, CSNK2A1, CDK1, CDK2, and CDK4), and master metabolic transcriptional regulators (MMTRs) (such as HNF1A, NFKB1, ZBTB7A, GATA2, and GATA5) regulating the DEGs. We found that CD8+ T cells were more enriched in CTS than in colon normal stroma. Interestingly, we found that many of the DEGs and their regulators were prognostic markers for colon cancer, including CEBPB, PPARGC1, STAT3, MTOR, BCL2, JAK2, and CDK1.

Conclusions

The identification of CTS-specific transcriptional signatures may provide insights into the tumor microenvironment that mediates the development of colon cancer and has potential clinical implications for colon cancer diagnosis and treatment.

Comprehensive analysis of metastasis-related genes reveals a gene signature predicting the survival of colon cancer patients

Objective

The mechanism underlying colon cancer metastasis remain unclear. This study aimed to elucidate the genes alteration during the metastasis of colon cancer and identify genes that crucial to the metastasis and survival of colon cancer patients.

Methods

The dataset of primary and metastasis tissue of colon cancer, and dataset of high and low metastasis capability of colon cancer cells were selected as training cohort, and the overlapped differentially expressed genes (DEGs) were screened from the training cohort. The functional enrichment analysis for the overlapped DEGs was performed. The prognostic value of overlapped DEGs were analyzed in The Cancer Genome Atlas dataset, and a gene signature was developed using genes that related to the overall survival (OS). The prognostic value of the gene signature was further confirmed in a validation cohort.

Results

A total of 184 overlapped DEGs were screened from the training cohort. Functional enrichment analysis revealed the significant gene functions and pathways of the overlapped DEGs. Four hub genes (3-oxoacid CoA-transferase 1, actinin alpha 4, interleukin 8, integrin subunit alpha 3) were identified using protein–protein network analysis. Six genes (aldehyde dehydrogenase 2, neural precursor cell expressed, developmentally down-regulated 9, filamin A, lamin B receptor, twinfilin actin binding protein 1, serine and arginine rich splicing factor 1) were closely related to the OS of colon cancer patients. A gene signature was developed using these six genes based on their risk score, and the validation cohort indicated that the prognostic value of this gene signature was high in the prediction of colon cancer patients.

Conclusions

Our study demonstrates a gene profiles related to the metastasis of colon cancer, and identify a six-gene signature that acts as an independent biomarker on the prognosis of colon cancer.

Independent prognostic genes and mechanism investigation for colon cancer

PROPOSE

We aimed to explore the potential molecular mechanism and independent prognostic genes for colon cancer (CC).

METHODS

Microarray datasets GSE17536 and GSE39582 were downloaded from Gene Expression Omnibus. Meanwhile, the whole CC-related dataset were downloaded from The Cancer Genome Atlas (TCGA) database. Differentially expressed mRNA (DEMs) were identified between cancer tissue samples and para-carcinoma tissue samples in TCGA dataset, followed by the KEGG pathway and GO function analyses. Furthermore, the clinical prognostic analysis including overall survival (OS) and disease-free survival (DFS) were performed in all three datasets.

RESULTS

A total of 633 up- and 321 down-regulated mRNAs were revealed in TCGA dataset. The up-regulated mRNAs were mainly assembled in functions including extracellular matrix and pathways including Wnt signaling. The down-regulated mRNAs were mainly assembled in functions like Digestion and pathways like Drug metabolism. Furthermore, up-regulation of UL16-binding protein 2 (ULBP2) was associated with OS in CC patients. A total of 12 DEMs including Surfactant Associated 2 (SFTA2) were potential DFS prognostic genes in CC patients. Meanwhile, the GRP and Transmembrane Protein 37 (TMEM37) were two outstanding independent DFS prognostic genes in CC.

CONCLUSIONS

ULBP2 might be a potential novel OS prognostic biomarker in CC, while GRP and TMEM37 could be served as the independent DFS prognostic genes in CC. Furthermore, functions including extracellular matrix and digestion, as well as pathways including Wnt signaling and drug metabolism might play important roles in the process of CC.

Opposing roles of the aldo-keto reductases AKR1B1 and AKR1B10 in colorectal cancer

PURPOSE

Aldo-keto reductases (including AKR1B1 and AKR1B10) constitute a family of oxidoreductases that have been implicated in the pathophysiology of diabetes and cancer, including colorectal cancer (CRC). Available data indicate that, despite their similarities in structure and enzymatic functions, their roles in CRC may be divergent. Here, we aimed to determine the expression and functional implications of AKR1B1 and AKR1B10 in CRC.

METHODS

AKR1B1 and AKR1B10 gene expression levels were analyzed using publicly available microarray data and ex vivo CRC-derived cDNA samples. Gene Set Enrichment Analysis (GSEA), The Cancer Genome Atlas (TCGA) RNA-seq data and The Cancer Proteome Atlas (TCPA) proteome data were analyzed to determine the effect of high and low AKR1B1 and AKR1B10 expression levels in CRC patients. Proliferation, cell cycle progression, cellular motility, adhesion and inflammation were determined in CRC-derived cell lines in which these genes were either exogenously overexpressed or silenced.

RESULTS

We found that the expression of AKR1B1 was unaltered, whereas that of AKR1B10 was decreased in primary CRCs. GSEA revealed that, while high AKR1B1 expression was associated with increased cell cycle progression, cellular motility and inflammation, high AKR1B10 expression was associated with a weak inflammatory phenotype. Functional studies carried out in CRC-derived cell lines confirmed these data. Microarray data analysis indicated that high expression levels of AKR1B1 and AKR1B10 were significantly associated with shorter and longer disease-free survival rates, respectively. A combined gene expression signature of AKR1B10 (low) and AKR1B1 (high) showed a better prognostic stratification of CRC patients independent of confounding factors.

CONCLUSIONS

Despite their similarities, the expression levels and functions of AKR1B1 and AKR1B10 are highly divergent in CRC, and they may have prognostic implications.