Survival marker genes of colorectal cancer derived from consistent transcriptomic profiling

Integrated analysis of public datasets for the discovery and validation of survival-associated genes in solid tumors

Identifying genes with prognostic significance that can act as biomarkers in solid tumors can help stratify patients and uncover novel therapy targets. Here, our goal was to expand our previous ranking analysis of survival-associated genes in various solid tumors to include colon cancer specimens with available transcriptomic and clinical data. A Gene Expression Omnibus search was performed to identify available datasets with clinical data and raw gene expression measurements. A combined database was set up and integrated into our Kaplan-Meier plotter, making it possible to identify genes with expression changes linked to altered survival. As a demonstration of the utility of the platform, the most powerful genes linked to overall survival in colon cancer were identified using uni- and multivariate Cox regression analysis. The combined colon cancer database includes 2,137 tumor samples from 17 independent cohorts. The most significant genes associated with relapse-free survival with a false discovery rate below 1% in colon cancer carcinoma were RBPMS (hazard rate [HR] = 2.52), TIMP1 (HR = 2.44), and COL4A2 (HR = 2.36). The three strongest genes associated with shorter survival in stage II colon cancer include CSF1R (HR = 2.86), FLNA (HR = 2.88), and TPBG (HR = 2.65). In summary, a new integrated database for colon cancer is presented. A colon cancer analysis subsystem was integrated into our Kaplan-Meier plotter that can be used to mine the entire database (https://www.kmplot.com). The portal has the potential to be employed for the identification and prioritization of promising biomarkers and therapeutic target candidates in multiple solid tumors including, among others, breast, lung, ovarian, gastric, pancreatic, and colon cancers.

Stratification of Colorectal Patients Based on Survival Analysis Shows the Value of Consensus Molecular Subtypes and Reveals the CBLL1 Gene as a Biomarker of CMS2 Tumours

The consensus molecular subtypes (CMSs) classification of colorectal cancer (CRC) is a system for patient stratification that can be potentially applied to therapeutic decisions. Hakai (CBLL1) is an E3 ubiquitin-ligase that induces the ubiquitination and degradation of E-cadherin, inducing epithelial-to-mesenchymal transition (EMT), tumour progression and metastasis. Using bioinformatic methods, we have analysed CBLL1 expression on a large integrated cohort of primary tumour samples from CRC patients. The cohort included survival data and was divided into consensus molecular subtypes. Colon cancer tumourspheres were used to analyse the expression of stem cancer cells markers via RT-PCR and Western blotting. We show that CBLL1 gene expression is specifically associated with canonical subtype CMS2. WNT target genes LGR5 and c-MYC show a similar association with CMS2 as CBLL1. These mRNA levels are highly upregulated in cancer tumourspheres, while CBLL1 silencing shows a clear reduction in tumoursphere size and in stem cell biomarkers. Importantly, CMS2 patients with high CBLL1 expression displayed worse overall survival (OS), which is similar to that associated with CMS4 tumours. Our findings reveal CBLL1 as a specific biomarker for CMS2 and the potential of using CMS2 with high CBLL1 expression to stratify patients with poor OS.

Multi-omics prognostic signatures of IPO11 mRNA expression and clinical outcomes in colorectal cancer using bioinformatics approaches

The most prevalent malignant illness of the gastrointestinal system, colorectal cancer, is the third most prevalent cancer in males and the second most prevalent cancer in women. Importin-11 is a protein that acts as a regulator of cancer cell proliferation in colorectal tumours by conveying β -catenin to the cell nucleus. However, the IPO11 gene was found to encode a protein called Importin-11, which functions as a nucleus importer for the cell. As a result, preventing β -catenin from entering the nucleus requires blocking Importin-11. As a result, we conducted a multi-omics investigation to assess IPO11 gene potential as a therapeutic biomarker for human colorectal cancer (CC). Oncomine, GEPIA2, immunohisto-chemistry, and UALCAN databases were used to analyses the mRNA expression profiles of IPO11 in CC. The investigation has yielded clear evidence of the increase of IPO11 expression in CC subtypes, as indicated by the data acquired. Analysing CC research from the cBioPortal database, the study discovered three new missense mutations in the importin-11 protein sequence at a frequency of 0.00-1.50% copy number changes. Additionally, the Kaplan-Meier plots demonstrated a strong connection concerning IPO11 downregulation and a poorer CC patient survival rate. The co-expressed gene profile of IPO11 was likewise associated with the onset of CC. IPO11 co-expressed gene profile was also linked to CC development. Moreover, the correlation analysis using bc-GenExMiner and the UCSC Xena server identified KIF2A as the most positively co-expressed gene. The study found that KIF2A and its co-expressed genes were involved in a wide variety of cancer progression pathways using the Enrichr database. Cumulatively, this result will not only provide new information about the expression of IPO11 associated with CC progression and patient survival, but could also serve as a therapeutic biomarker for treating CC in a significant and worthwhile manner.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13755-023-00259-2.

LncRNA NONRATT014888.2 contributes to cancer-induced bone pain through downregulation of natriuretic peptide receptor 3 in rats

Long noncoding RNA (lncRNA) is implicated in both cancer development and pain process. However, the role of lncRNA in the development of cancer-induced bone pain (CIBP) is unclear. LncRNA NONRATT014888.2 is highly expressed in tibia related dorsal root ganglions (DRGs) in CIBP rats which function is unknown. CIBP was induced by injection of Walker 256 mammary gland tumor cells into the tibia canal of female SD rats. Paw withdrawal threshold (PWT) and paw withdrawal latency (PWL) of rats were measured. Down-regulation of NONRATT014888.2 by siRNA in CIBP rats markedly attenuated hind-paw mechanical pain hypersensitivity. LncRNA-predicted target mRNAs analysis and mRNA sequencing results cued Socs3, Npr3 were related with NONRATT014888.2. Intrathecal injection of NONRATT014888.2-siR206 upregulated Npr3 both in mRNA and protein level. Npr3 was co-expressed in NONRATT014888.2-positive DRGs neurons and mainly located in cytoplasm, but not in Glial fibrillary acidic protein (GFAP)-positive cells. Intrathecal injection of ADV-Npr3 upregulated Npr3 expression and enhanced the PWT of CIBP rats. Our results suggest that upregulated lncRNA NONRATT014888.2 contributed to hyperalgesia in CIBP rats, and the mechanism may through downregulation of Npr3.

CRISPR/Cas9-mediated inactivation of miR-34a and miR-34b/c in HCT116 colorectal cancer cells: comprehensive characterization after exposure to 5-FU reveals EMT and autophagy as key processes regulated by miR-34

The miR-34a and miR-34b/c encoding genes represent direct targets of the p53 transcription factor, and presumably mediate part of the tumor suppressive effects of p53. Here, we sought to determine their functional relevance by inactivating miR-34a and/or miR-34b/c using a CRISPR/Cas9 approach in the colorectal cancer (CRC) cell line HCT116. Concomitant deletion of miR-34a and miR-34b/c resulted in significantly reduced suppression of proliferation after p53 activation, enhanced migration, invasion and EMT, as well as reduced sensitivity to chemotherapeutics, increased stress-induced autophagic flux, decreased apoptosis and upregulation of autophagy-related genes after 5-FU treatment. However, inactivation of singular miR-34a or miR-34b/c had little effects on the aforementioned processes. RNA-Seq analysis revealed that concomitant deletion of miR-34a/b/c caused EMT signature enrichment, impaired gene repression by the p53-DREAM pathway and elevated autophagy after 5-FU treatment. A gene signature comprised of mRNAs significantly upregulated after combined inactivation of miR-34a and miR-34b/c showed a significant association with the invasive colon cancer subtype CMS4 and poor overall survival in two CRC patient cohorts, and with 5-FU resistance in CRC cell lines. In miR-34a/b/c-deficient cells the upregulated miR-34 target FOXM1 directly induced p62 and ATG9A, which increased autophagy and consequently attenuated apoptosis and rendered the miR-34a/b/c-KO cells more resistant to 5-FU. Inhibition of autophagy by depletion of ATG9A or chloroquine re-sensitized miR-34a/b/c-deficient HCT116 cells to 5-FU. In summary, our findings show a complementary role of miR-34a and miR-34b/c in the regulation of EMT and autophagy which may be relevant for CRC therapy in the future.

LEM Domain Containing 1 Acts as a Novel Oncogene and Therapeutic Target for Triple-Negative Breast Cancer

Breast cancer is the most common deadly malignancy in women worldwide. In particular, triple-negative breast cancer (TNBC) exhibits the worst prognosis among four subtypes of breast cancer due to limited treatment options. Exploring novel therapeutic targets holds promise for developing effective treatments for TNBC. Here, we demonstrated for the first time that LEMD1 (LEM domain containing 1) is highly expressed in TNBC and contributes to reduced survival in TNBC patients, through analysis of both bioinformatic databases and collected patient samples. Furthermore, LEMD1 silencing not only inhibited the proliferation and migration of TNBC cells in vitro, but also abolished tumor formation of TNBC cells in vivo. Knockdown of LEMD1 enhanced the sensitivity of TNBC cells to paclitaxel. Mechanistically, LEMD1 promoted the progress of TNBC by activating the ERK signaling pathway. In summary, our study revealed that LEMD1 may act as a novel oncogene in TNBC, and targeting LEMD1 may be exploited as a promising therapeutic approach to enhance the efficacy of chemotherapy against TNBC.

Integrated analysis of multi-omics data for the discovery of biomarkers and therapeutic targets for colorectal cancer

The considerable burden of colorectal cancer and the rising trend in young adults emphasize the necessity of understanding its underlying mechanisms, providing new diagnostic and prognostic markers, and improving therapeutic approaches. Precision medicine is a new trend all over the world and identification of novel biomarkers and therapeutic targets is a step forward towards this trend. In this context, multi-omics data and integrated analysis are being investigated to develop personalized medicine in the management of colorectal cancer. Given the large amount of data from multi-omics approach, data integration and analysis is a great challenge. In this Review, we summarize how statistical and machine learning techniques are applied to analyze multi-omics data and how it contributes to the discovery of useful diagnostic and prognostic biomarkers and therapeutic targets. Moreover, we discuss the importance of these biomarkers and therapeutic targets in the clinical management of colorectal cancer in the future. Taken together, integrated analysis of multi-omics data has great potential for finding novel diagnostic and prognostic biomarkers and therapeutic targets, however, there are still challenges to overcome in future studies.

Targeted O-glycoproteomics for the development of diagnostic markers for advanced colorectal cancer

Aberrant glycosylation is a prominent feature of cancer, that can be used as targets to improve the existing cancer biomarkers, and help to assess metastasis risks, and therapeutic effects. We developed a targeted O-glycoproteomics method using serum specimens, and evaluated its utility in identifying advanced colorectal cancer (CRC) markers. To this end, we combined consecutive lectin affinity purification using Maclura pomifera lectin (MPL), jacalin, and Sambucus nigra lectin, which have affinities for the following O-glycans, that have received attention as cancer-related antigens, Tn (GalNAc-Ser/Thr), Sialyl Tn (Siaα2-6GalNAc-Ser/Thr), T (Galβ1-3GalNAc-Ser/Thr), Sialyl T (Siaα2-3Galβ1-GalNAc-Ser/Thr), and di-Sialyl T (Siaα2-3Galβ1-3[Siaα2-6] GalNAc-Ser/Thr), with a unique O-glycoproteomics approach. A total of 2,068 O-glycoforms derived from 265 proteins were identified in healthy individuals and patients with advanced CRC, of which 44 CRC-specific O-glycoforms were extracted. Particularly, five glycoproteins with T, Sialyl T, and di-Sialyl T antigens in specific peptide regions were evaluated quantitatively and statistically. We found that fibulin-2 (FBLN2) (aa330-349)/T antigen (area under the curve [AUC] = 0.92); macrophage colony-stimulating factor 1 (CSF1) (aa370-395)/(T + di-Sialyl T) (AUC = 0.94); macrophage mannose receptor 1 (MRC1) (aa1083-1101 and aa1215-1229)/T (AUC = 0.96 and 0.99); fibrinogen alpha chain (FGA) (aa354-367, aa511-527 and aa559-573)/Sialyl T (AUC = 0.98, 0.90 and 0.94); and complement component C7 (C7) (aa692-701)/di-Sialyl T (AUC = 1.00), can have high diagnostic efficacy to strategically predict advanced CRC groups. Hence, they could be promising markers for detection of advanced CRC, and provide new clinical test indicators along with lectins, such as MPL and jacalin. Our O-glycoproteomics platform provides a novel tool and resource, for researchers and clinicians seeking to better understand and treat advanced CRC.

Removing unwanted variation from large-scale RNA sequencing data with PRPS

Accurate identification and effective removal of unwanted variation is essential to derive meaningful biological results from RNA sequencing (RNA-seq) data, especially when the data come from large and complex studies. Using RNA-seq data from The Cancer Genome Atlas (TCGA), we examined several sources of unwanted variation and demonstrate here how these can significantly compromise various downstream analyses, including cancer subtype identification, association between gene expression and survival outcomes and gene co-expression analysis. We propose a strategy, called pseudo-replicates of pseudo-samples (PRPS), for deploying our recently developed normalization method, called removing unwanted variation III (RUV-III), to remove the variation caused by library size, tumor purity and batch effects in TCGA RNA-seq data. We illustrate the value of our approach by comparing it to the standard TCGA normalizations on several TCGA RNA-seq datasets. RUV-III with PRPS can be used to integrate and normalize other large transcriptomic datasets coming from multiple laboratories or platforms.

Identification of a gene expression signature associated with breast cancer survival and risk that improves clinical genomic platforms

Motivation

Modern genomic technologies allow us to perform genome-wide analysis to find gene markers associated with the risk and survival in cancer patients. Accurate risk prediction and patient stratification based on robust gene signatures is a key path forward in personalized treatment and precision medicine. Several authors have proposed the identification of gene signatures to assign risk in patients with breast cancer (BRCA), and some of these signatures have been implemented within commercial platforms in the clinic, such as Oncotype and Prosigna. However, these platforms are black boxes in which the influence of selected genes as survival markers is unclear and where the risk scores provided cannot be clearly related to the standard clinicopathological tumor markers obtained by immunohistochemistry (IHC), which guide clinical and therapeutic decisions in breast cancer.

Results

Here, we present a framework to discover a robust list of gene expression markers associated with survival that can be biologically interpreted in terms of the three main biomolecular factors (IHC clinical markers: ER, PR and HER2) that define clinical outcome in BRCA. To test and ensure the reproducibility of the results, we compiled and analyzed two independent datasets with a large number of tumor samples (1024 and 879) that include full genome-wide expression profiles and survival data. Using these two cohorts, we obtained a robust subset of gene survival markers that correlate well with the major IHC clinical markers used in breast cancer. The geneset of survival markers that we identify (which includes 34 genes) significantly improves the risk prediction provided by the genesets included in the commercial platforms: Oncotype (16 genes) and Prosigna (50 genes, i.e. PAM50). Furthermore, some of the genes identified have recently been proposed in the literature as new prognostic markers and may deserve more attention in current clinical trials to improve breast cancer risk prediction.

Availability and implementation

All data integrated and analyzed in this research will be available on GitHub (https://github.com/jdelasrivas-lab/breastcancersurvsign), including the R scripts and protocols used for the analyses.

Supplementary information

Supplementary data are available at Bioinformatics Advances online.

Topoisomerase IIβ binding protein 1 serves as a novel prognostic biomarker for stage II-III colorectal cancer patients

BACKGROUND

Colorectal cancer (CRC) is a commonly diagnosed human malignancy worldwide. Accumulating evidence has suggested DNA repair related proteins widely participate in CRC initiation and development. TOPBP1 is recently identified as a novel regulator for DNA repair, however, its biological role in CRC remains unknown.

METHODS

Firstly, the bioinformatics analysis was utilized to investigate the expression and clinical significance of TOPBP1 in CRC patients. Then, a retrospective study enrolling 129 stage II/III CRC patients was performed for validation. The CCK-8, colony formation, transwell assay and xenograft model were used to clarify the biological impact of TOPBP1 on CRC cells. Finally, transcriptome sequencing was performed to investigate the potential oncogenic mechanisms regulated by TOPBP1 in CRC development.

RESULTS

The expression of TOPBP1 was significantly higher in CRC tissues than that in normal tissues. High TOPBP1 expression was an independent unfavorable prognostic factor for overall and disease-free survival in II/III CRC patients. Knockdown of TOPBP1 not only significantly inhibited the proliferation, colony formation, invasion, migration and epithelial-mesenchymal transition (EMT) molecular phenotype of CRC cells, while the opposite was for TOPBP1 expression. Moreover, knockdown of TOPBP1 slowed down the growth speed of xenografts. The transcriptome sequencing identified MAP3K3 as a downstream gene of TOPBP1 and MAP3K3 knockdown inhibited the EMT molecular phenotype in CRC cells. Finally, the rescue assay indicated MAP3K3 overexpression counteracted the inhibitory effect of TOPBP1 knockdown on the proliferation, colony formation, invasion, migration and EMT phenotype of CRC cells.

CONCLUSION

TOPBP1 promotes the malignant progression of CRC through MAP3K3 induced EMT. TOPBP1 is a promising clinical biomarker or therapeutical target for CRC patients.

miR-451a suppresses papillary thyroid cancer cell proliferation and invasion and facilitates apoptosis through targeting DCBLD2 and AKT1

Papillary thyroid cancer (PTC) is a common malignancy. MicroRNAs (miRNAs) may act as oncogenes or tumor suppressor genes. However, the role of miR-451a in PTC is not fully understood. Hence, the objective of the study was to research the effect and mechanism of miR-451a in PTC. Differentially expressed miRNAs between GSE113629 and GSE103996 databases were assessed by Venn diagram. miR-451a and its downstream target genes were assessed by RT-PCR and Western blot. The proliferation, invasion, and apoptosis were determined by CCK-8, EdU, transwell, and flow cytometry assays. Dual-luciferase reporter assay were used to evaluated the target of miR-451a. Xenografted tumors was used to explore the function of miR-451a in vivo. Pathological changes and related protein expression were measured by HE staining and immunohistochemistry. MiR-451a was downregulated in PTC tissues and blood, and low expression of miR-451a was related to short overall survival, serious lymph node metastasis and high TNM grade in PTC patients. Moreover, increase of miR-451a restrained the proliferation and invasion and accelerated the apoptosis. Furthermore, miR-451a repressed VEGF signaling pathway. Importantly, miR-451a was demonstrated to target DCBLD2 and AKT1. Overexpression of DCBLD2 and AKT1 could restore the effect of miR-451a on PTC cells. In addition, miR-451a reduced the growth of xenografted tumors in vivo. The data suggested that miR-451a attenuated the proliferation, invasion and promoted apoptosis in PTC cells via inhibiting DCBLD2 and AKT1.

Low Expression of AGPAT5 Is Associated With Clinical Stage and Poor Prognosis in Colorectal Cancer and Contributes to Tumour Progression

Background:

Colorectal cancer (CRC) has a high prevalence and poor prognosis. This study aimed to identify biomarkers related to the clinical stage (I-IV) of CRC.

Methods:

The LinkedOmics database was used as the discovery cohort, and two Gene Expression Omnibus (GEO) databases (GSE41258 and GSE422848) served as validation cohorts. The trend test of genes related to clinical stage (I-IV) of CRC patients was identified by the Jonckheere-Terpstra test. The cBioPortal database, Gene Expression Profiling Interactive Analysis (GEPIA) and PrognoScan databases were used to explore the expression change and prognostic value of clinical stage-related genes in CRC patients. CRC cells overexpressed AGPAT5 were constructed and used for cell counting kit-8 (CCK-8), flow cytometric, and wound healing assays in vitro.

Results:

We identified four clinical stage-related genes, GSR, AGPAT5, CRLF1, and NPR3, in CRC. The CNA frequencies of GSR, CRLF1, AGPAT5, and NPR3 occurred in 11%, 2.4%, 13%, and 3% of patients, respectively. The expression of GSR and AGPAT5 tended to decrease with CRC stage (I-IV) progression, and the expression of CRLF1 and NPR3 tended to increase with CRC stage (I-IV) progression. Compared with the normal group, AGPAT5 expression was markedly decreased in stage IV CRC. Higher GSR and AGPAT5 expression levels were associated with better overall survival (OS) and disease-free survival (DFS) in CRC patients. Lower CRLF1 and NPR3 expression levels were associated with better OS and DFS in CRC. GSR, CRLF1, AGPAT5, and NPR3 expression were related to CRC progression, microsatellite instability, and tumour purity in CRC. Furthermore, AGPAT5 was downregulated in CRC cell lines, and overexpression of AGPAT5 inhibited cell proliferation and migration and promoted cell apoptosis in CRC cells.

Conclusion:

Low AGPAT5 expression may serve as a poor prognostic factor and clinical stage biomarker in CRC. In addition, AGPAT5 acts as a tumour suppressor in CRC progression.

Cancer-associated fibroblast-related gene signatures predict survival and drug response in patients with colorectal cancer

Background: Cancer-associated fibroblasts (CAFs) play an important role in the tumorigenesis, immunosuppression and metastasis of colorectal cancer (CRC), and can predict poor prognosis in patients with CRC. The present study aimed to construct a CAFs-related prognostic signature for CRC. Methods: The clinical information and corresponding RNA data of CRC patients were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The Estimation of STromal and Immune cells in MAlignant Tumor tissues (ESTIMATES) and xCell methods were applied to evaluate the tumor microenvironment infiltration from bulk gene expression data. Weighted gene co-expression network analysis (WGCNA) was used to construct co-expression modules. The key module was identified by calculating the module-trait correlations. The univariate Cox regression and least absolute shrinkage operator (LASSO) analyses were combined to develop a CAFs-related signature for the prognostic model. Moreover, pRRophetic and Tumor Immune Dysfunction and Exclusion (TIDE) algorithms were utilized to predict chemosensitivity and immunotherapy response. Human Protein Atlas (HPA) databases were employed to evaluate the protein expressions. Results: ESTIMATES and xCell analysis showed that high CAFs infiltration was associated with adverse prognoses. A twenty-gene CAFs-related prognostic signature (CAFPS) was established in the training cohort. Kaplan-Meier survival analyses reveled that CRC patients with higher CAFs risk scores were associated with poor prognosis in each cohort. Univariate and multivariate Cox regression analyses verified that CAFPS was as an independent prognostic factor in predicting overall survival, and a nomogram was built for clinical utility in predicting CRC prognosis. Patients with higher CAFs risk scores tended to not respond to immunotherapy, but were more sensitive to five conventional chemotherapeutic drugs. Conclusion: In summary, the CAFPS could serve as a robust prognostic indicator in CRC patients, which might help to optimize risk stratification and provide a new insight into individual treatments for CRC.

Association between CYP2E1 polymorphisms and colorectal cancer risk: a systematic review and meta-analysis

CYP2E1 encodes an enzyme that participates in the activation of several carcinogenic substances. Thus, numerous studies have investigated the association between CYP2E1 polymorphisms and colorectal cancer (CRC) risk, but inconclusive results have been obtained. We performed a meta-analysis to precisely evaluate the relationship of CYP2E1 rs2031920, rs3813867, and rs6413432 polymorphisms with the susceptibility to CRC. Scopus, Web of Science and PubMed databases were searched to identify eligible studies, and the association between the polymorphisms and CRC risk was then quantitatively synthesized using different genetic models. Eighteen studies with 23,598 subjects were selected for inclusion into the analysis. Significant association between rs2031920 and an increased CRC risk was observed in homozygous (OR = 1.496, 95% CI 1.177-1.901, P = 0.001), recessive (OR = 1.467, 95% CI  1.160-1.857, P = 0.001) and allele (OR = 1.162, 95% CI  1.001-1.349, P = 0.048) models. Significant association was not found for rs3813867 and rs6413432 (P > 0.05). In conclusion, our results suggest that rs2031920, but not rs3813867 and rs6413432, is associated with the risk of CRC.

Pan-cancer analysis of the prognosis and immunological role of AKAP12: A potential biomarker for resistance to anti-VEGF inhibitors

The primary or acquired resistance to anti-VEGF inhibitors remains a common problem in cancer treatment. Therefore, identifying potential biomarkers enables a better understanding of the precise mechanism. Through the GEO database, three profiles associated with bevacizumab (BV) resistance to ovarian cancer, glioma, and non-small-cell lung carcinoma, respectively, were collected for the screening process, and two genes were found. A-kinase anchor protein 12 (AKAP12), one of these two genes, correlates with tumorigenesis of some cancers. However, the role of AKAP12 in pan-cancer remains poorly defined. The present study first systematically analyzed the association of AKAP12 with anti-VEGF inhibitors’ sensitivity, clinical prognosis, DNA methylation, protein phosphorylation, and immune cell infiltration across various cancers via bioinformatic tools. We found that AKAP12 was upregulated in anti-VEGF therapy-resistant cancers, including ovarian cancer (OV), glioblastoma (GBM), lung cancer, and colorectal cancer (CRC). A high AKAP12 expression revealed dismal prognoses in OV, GBM, and CRC patients receiving anti-VEGF inhibitors. Moreover, AKAP12 expression was negatively correlated with cancer sensitivity towards anti-VEGF therapy. Clinical prognosis analysis showed that AKAP12 expression predicted worse prognoses of various cancer types encompassing colon adenocarcinoma (COAD), OV, GBM, and lung squamous cell carcinoma (LUSC). Gene mutation status may be a critical cause for the involvement of AKAP12 in resistance. Furthermore, lower expression of AKAP12 was detected in nearly all cancer types, and hypermethylation may explain its decreased expression. A decreased phosphorylation of T1760 was observed in breast cancer, clear-cell renal cell carcinoma, and lung adenocarcinoma. For the immunologic significance, AKAP12 was positively related to the abundance of pro-tumor cancer-associated fibroblasts (CAFs) in various types of cancer. The results of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis suggested that “cell junction organization” and “MAPK pathway” participated in the effect of AKAP12. Importantly, we discovered that AKAP12 expression was greatly associated with metastasis of lung adenocarcinoma as well as differential and angiogenesis of retinoblastoma through investigating the single-cell sequencing data. Our study showed that the dual role of AKAP12 in various cancers and AKAP12 could serve as a biomarker of anti-VEGF resistance in OV, GBM, LUSC, and COAD.

Pyroptosis is related to immune infiltration and predictive for survival of colon adenocarcinoma patients

Pyroptosis is a novel type of programmed cell death, initiated by inflammasome. Pyroptosis inhibits the development and metastasis of colon cancer and is associated with patients’ prognosis. However, how the pyroptosis-related genes predict the survival of patients is still unclear. In the study, colon adenocarcinoma (COAD) patients were divided into two groups according to the expression of pyroptosis-related regulators through consensus clustering. DEGs between two clusters were analyzed by using COX and Lasso regression. Then, regression coefficients in Lasso were used to calculate the risk score for every patient. Patients were classified into two types: low- and high-risk group according to their risk score. The difference of immune microenvironment infiltration and clinicopathological characteristics between subgroups was performed. Moreover, the nomogram model was built on the bases of risk model and clinicopathological factors. The TCGA-COAD cohort and GEO cohort were used as training and validating set respectively. 398 COAD patients in TCGA training set were identified as two regulation patterns via unsupervised clustering method. Patients in cluster 2 showed better prognosis (P = 0.002). Through differentiated expression analysis, COX and Lasso regression, a 5-gene prognostic risk model was constructed. This risk model was significantly associated with OS (HR: 2.088, 95% CI: 1.183–3.688, P = 0.011), validated in GEO set (HR:1.344, 95%CI: 1.061–1.704, P = 0.014), and patients with low risk had better prognosis (P < 0.001 in TCGA; P = 0.038 in GEO). Through ROC analysis, it can be found that this model presented better predictive accuracy for long-term survival. Clinical analyses demonstrated that high-risk group had more advanced N stage, higher risk of metastasis and later pathological stage. Immune-related analysis illustrated that low-risk group had more immune cell infiltration and more activated immune pathways. The pyroptosis-related risk model can be predictive for the survival of COAD patients. That patients with higher risk had poorer prognosis was associated with more advanced tumor stage and higher risk of metastasis, and resulted from highly activated pro-tumor pathways and inhibited immune system and poorer integrity of intestinal epithelial. This study proved the relationship between pyroptosis and immune, which offered basis for future studies.

Prognosis prediction of stage IV colorectal cancer patients by mRNA transcriptional profile

BACKGROUND

Stage IV colorectal cancer patients with liver metastasis represent a special group of CRC patients with poor prognosis. The prognostic factors have not been investigated for stage IV CRC patients undergoing primary cancer resection but not candidates for metastasis resection.

METHODS

Ninety-nine stage IV CRC patients who underwent primary cancer resection without metastasis resection were retrospectively recruited. Both whole-exome sequencing (WES) and RNA-seq were performed with frozen primary cancer tissues, using para-cancerous normal tissues as the control. Valid data were obtained from 78 patients for WES and 84 patients for RNA-seq. Univariate, multivariate Cox analyses were performed and Nomogram model was established to predict patient prognosis.

RESULTS

The correlation between patient prognosis and clinicopathological factors, mutational status, or mRNA level changes was examined. Univariate (p = 0.0007) and subsequent multivariate analyses on clinicopathological factors showed that location (left or right) was the only independent risk factor for patient prognosis (HR = 3.63; 95% CI: 1.56-8.40, p = 0.003), while T, N, M staging, gender, race, location (rectum or colon), and pathological types were not stratifying factors. The mutational status of APC, TP53, KRAS, TTN, SYNE1, SMAD4, PIK3CA, RYR2, and BRAF did not show significant stratification in patient prognosis. RNA-seq showed that genes related to membrane function, ion channels, transporters, or receptors were among those with significant mRNA level alterations. Univariate analysis identified 97 genes with significantly altered mRNA levels, while NEUROD1, FGF18, SFTA2, PLAC1, SAA2, DSCAML1, and OTOP3 were significant in multivariate analysis. A risk model was established to stratify the prognosis of stage IV CRC patients. A Nomogram model was established with these genes to predict individual patient prognosis.

CONCLUSIONS

A panel of eight genes with significant mRNA level alterations was capable of predicting the prognosis and risk of the specific patient group. Future prospective study is needed to validate the model.

Lysosomal-associated membrane protein family member 5 promotes the metastatic potential of gastric cancer cells

BACKGROUND

Metastatic gastric cancer (GC) has a poor prognosis, and elucidating the molecular mechanisms involved in metastasis may lead to the development of novel therapeutic modalities.

METHODS

Transcriptome analysis of surgically resected metastatic tissue from GC patients and noncancerous tissue was performed to identify novel metastasis-related genes. Analyses of in vitro cell function, apoptosis, the cell cycle and cancer stemness were performed using GC cell lines with a stable knockout of a candidate gene. In vivo percutaneous, peritoneal dissemination and liver metastasis xenograft models were also generated. PCR array and proteome analyses were performed. Expression of the candidate gene was analyzed in GC tissues from 300 patients.

RESULTS

Lysosomal Associated Membrane Protein Family Member 5 (LAMP5) was upregulated in the metastatic tissues. LAMP5 knockout significantly suppressed proliferation, invasion, and migration of GC cells and increased apoptosis, cell cycle arrest and cancer stemness. LAMP5 knockout virtually suppressed tumor growth in in vivo percutaneous, peritoneal dissemination and liver metastasis models. EMT- and autophagy-related genes were associated with LAMP5. High LAMP5 mRNA levels were significantly associated with a worse prognosis.

CONCLUSION

LAMP5 plays a vital role in metastasis formation and may be a promising novel target of drug development for metastatic GC in the future.

LEM domain containing 1 (LEMD1) transcriptionally activated by SRY-related high-mobility-group box 4 (SOX4) accelerates the progression of colon cancer by upregulating phosphatidylinositol 3-kinase (PI3K)/protein kinase B (Akt) signaling pathway

Colon cancer is a highly malignant tumor in the digestive system. LEM domain containing 1 (LEMD1) is supposed to be a survival marker of poor prognosis in colon cancer. We aimed to explore the role and mechanism of LEMD1 in colon cancer progression. GEPIA database analyzed LEMD1 expression in colon cancer tissues and prognosis of colon cancer patients. LEMD1 expression in tumor cells was tested by RT-qPCR and western blotting. Proliferation of colon cancer cells was estimated by CCK-8 and colony formation assays. Transwell and wound healing assays were used to appraise the cell invasion and migration. Meanwhile, tube formation assays were used to evaluate angiogenesis. The possible binding sites between SRY-related high-mobility-group box 4 (SOX4) and LEMD1 were predicted by JASPAR database. Besides, SOX4 expression in colon cancer tissues and the correlation between SOX4 and LEMD1 were examined using the GEPIA database. Luciferase reporter and ChIP assays were used to verify the interaction between SOX4 and LEMD1. The expression of proteins in PI3K/Akt signaling was evaluated by western blotting. LEMD1 was overexpressed in colon cancer tissues and cells and associated with poor prognosis. Functionally, LEMD1 deficiency impeded the proliferation, migration, invasion and angiogenesis of colon cancer cells. Additionally, SOX4 had a positive correlation with LEMD1 and could bind to LEMD1 promoter. Rescue assays validated that SOX4 elevation reversed the suppressive role of LEMD1 deletion in the development of colon cancer and the expression of p-PI3K and p-AKT. Collectively, LEMD1 induced by SOX4 drove the progression of colon cancer by activating PI3K/Akt signaling.

Predictors of colorectal cancer survival using cox regression and random survival forests models based on gene expression data

Understanding and identifying the markers and clinical information that are associated with colorectal cancer (CRC) patient survival is needed for early detection and diagnosis. In this work, we aimed to build a simple model using Cox proportional hazards (PH) and random survival forest (RSF) and find a robust signature for predicting CRC overall survival. We used stepwise regression to develop Cox PH model to analyse 54 common differentially expressed genes from three mutations. RSF is applied using log-rank and log-rank-score based on 5000 survival trees, and therefore, variables important obtained to find the genes that are most influential for CRC survival. We compared the predictive performance of the Cox PH model and RSF for early CRC detection and diagnosis. The results indicate that SLC9A8, IER5, ARSJ, ANKRD27, and PIPOX genes were significantly associated with the CRC overall survival. In addition, age, sex, and stages are also affecting the CRC overall survival. The RSF model using log-rank is better than log-rank-score, while log-rank-score needed more trees to stabilize. Overall, the imputation of missing values enhanced the model’s predictive performance. In addition, Cox PH predictive performance was better than RSF.

A Gene Signature Derived from the Loss of CDKN1A (p21) Is Associated with CMS4 Colorectal Cancer

Simple Summary

A gene signature derived from the loss of CDKN1A (p21) gene, obtained in HCT116 p21-/- colorectal cancer cells, is identified in a large cohort of primary colorectal (CRC) tumors and is associated with the Consensus Molecular Subtype (CMS) of colon cancer that has a worse relapse-free and overall survival, that is, CMS4 (also called mesenchymal subtype). The presented gene signature can help to uncover the early molecular mechanisms of epithelial–mesenchymal transition (EMT), which is known to be associated with high stemness and drug resistance.

Abstract

The epithelial–mesenchymal transition (EMT) is associated with tumor aggressiveness and increased invasion, migration, metastasis, angiogenesis, and drug resistance. Although the HCT116 p21-/- cell line is well known for its EMT-associated phenotype, with high Vimentin and low E-cadherin protein levels, the gene signature of this rather intermediate EMT-like cell line has not been determined so far. In this work, we present a robust molecular and bioinformatics analysis, to reveal the associated gene expression profile and its correlation with different types of colorectal cancer tumors. We compared the quantitative signature obtained with the NanoString platform with the expression profiles of colorectal cancer (CRC) Consensus Molecular Subtypes (CMS) as identified, and validated the results in a large independent cohort of human tumor samples. The expression signature derived from the p21-/- cells showed consistent and reliable numbers of upregulated and downregulated genes, as evaluated with two machine learning methods against the four CRC subtypes (i.e., CMS1, 2, 3, and 4). High concordance was found between the upregulated gene signature of HCT116 p21-/- cells and the signature of the CMS4 mesenchymal subtype. At the same time, the upregulated gene signature of the native HCT116 cells was similar to that of CMS1. Using a multivariate Cox regression model to analyze the survival data in the CRC tumor cohort, we selected genes that have a predictive risk power (with a significant gene risk incidence score). A set of genes of the mesenchymal signature was proven to be significantly associated with poor survival, specifically in the CMS4 CRC human cohort. We suggest that the gene signature of HCT116 p21-/- cells could be a suitable metric for mechanistic studies regarding the CMS4 signature and its functional consequences in CRC. Moreover, this model could help to discover the molecular mechanisms of intermediate EMT, which is known to be associated with extraordinarily high stemness and drug resistance.

Colon Cancer Progression Is Reflected to Monotonic Differentiation in Gene Expression and Pathway Deregulation Facilitating Stage-specific Drug Repurposing

BACKGROUND/AIM

Colon cancer is one of the most common cancer types and the second leading cause of death due to cancer. Many efforts have been performed towards the investigation of molecular alterations during colon cancer progression. However, the identification of stage-specific molecular markers remains a challenge. The aim of this study was to develop a novel computational methodology for the analysis of alterations in differential gene expression and pathway deregulation across colon cancer stages in order to reveal stage-specific biomarkers and reinforce drug repurposing investigation.

MATERIALS AND METHODS

Transcriptomic datasets of colon cancer were used to identify (a) differentially expressed genes with monotonicity in their fold changes (MEGs) and (b) perturbed pathways with ascending monotonic enrichment (MEPs) related to the number of the participating differentially expressed genes (DEGs), across the four colon cancer stages. Through an in silico drug repurposing pipeline we identified drugs that regulate the expression of MEGs and also target the resulting MEPs.

RESULTS

Our methodology highlighted 15 MEGs and 32 candidate repurposed drugs that affect their expression. We also found 51 MEPs divided into two groups according to their rate of DEG content alteration across colon cancer stages. Focusing on the target MEPs of the highlighted repurposed drugs, we found that one of them, the neuroactive ligand-receptor interaction, was targeted by the majority of the candidate drugs. Moreover, we observed that two of the drugs (PIK-75 and troglitazone) target the majority of the resulting MEPs.

CONCLUSION

These findings highlight significant genes and pathways that can be used as stage-specific biomarkers and facilitate the discovery of new potential repurposed drugs for colon cancer. We expect that the computational methodology presented can be applied in a similar way to the analysis of any progressive disease.

Long non-coding RNA LINC00958 promotes colorectal cancer progression by enhancing the expression of LEM domain containing 1 via microRNA miR-3064-5p

Colorectal cancer is a common cause of cancer-related death worldwide. Thus, there is an urgent need to determine the mechanism of progression of colorectal cancer. In this study, we investigated the function and mechanism of long non-coding RNA LINC00958, providing a new biomarker for colorectal cancer. The expression of LINC00958, miR-3064-5p, and LEM domain containing 1 (LEMD1) in colorectal cancer tissues and cell lines was analyzed using reverse transcription quantitative polymerase chain reaction (RT-qPCR). The interaction between LINC00958, miR-3064-5p, and LEMD1 was assessed using the luciferase assay. The viability, proliferation, migration, invasion, and apoptosis of colorectal cancer cells with silenced LINC00958, miR-3064-5p, and LEMD1 were investigated using the cell counting kit-8 (CCK-8), 5′-Bromo-2′-deoxyuridine (BrdU), flow cytometry, wound healing, and transwell assays. Phosphorylated phosphoinositide 3-kinase (p-PI3K) and phosphorylated protein kinase B (p-AKT) protein levels were measured by western blotting. LINC00958 and LEMD1 were found to have increased, while the expression of miR-3064-5p was decreased in colorectal cancer tissues and cell lines. Silencing of LINC00958 hampered cell viability, proliferation, migration, and invasion, while enhancing the apoptosis in colorectal cancer cells. Notably, LINC00958 inhibited miR-3064-5p and promoted LEMD1; the miR-3064-5p inhibitor abrogated the effect of LINC00958 silencing in colorectal cancer cells. Additionally, LEMD1 knockdown inhibited the activation of PI3K/AKT signaling. Our analyses have shown that LINC00958 could facilitate the progression of colorectal cancer by sponging miR-3064-5p and releasing LEMD1, leading to the activation of the PI3K/AKT pathway. Thus, LINC00958 may be considered as an effective biomarker for the treatment of colorectal cancer.

SCISSOR™: a single-cell inferred site-specific omics resource for tumor microenvironment association study

Tumor tissues are heterogeneous with different cell types in tumor microenvironment, which play an important role in tumorigenesis and tumor progression. Several computational algorithms and tools have been developed to infer the cell composition from bulk transcriptome profiles. However, they ignore the tissue specificity and thus a new resource for tissue-specific cell transcriptomic reference is needed for inferring cell composition in tumor microenvironment and exploring their association with clinical outcomes and tumor omics. In this study, we developed SCISSOR™ (https://thecailab.com/scissor/), an online open resource to fulfill that demand by integrating five orthogonal omics data of >6031 large-scale bulk samples, patient clinical outcomes and 451 917 high-granularity tissue-specific single-cell transcriptomic profiles of 16 cancer types. SCISSOR™ provides five major analysis modules that enable flexible modeling with adjustable parameters and dynamic visualization approaches. SCISSOR™ is valuable as a new resource for promoting tumor heterogeneity and tumor–tumor microenvironment cell interaction research, by delineating cells in the tissue-specific tumor microenvironment and characterizing their associations with tumor omics and clinical outcomes.

A Novel Signature Constructed by Immune-Related LncRNA Predicts the Immune Landscape of Colorectal Cancer

Colorectal cancer (CRC) has the characteristics of high morbidity and mortality. LncRNA not only participates in the progression of CRC through genes and transcription levels, but also regulates the tumor microenvironment and leads to the malignant phenotype of tumors. Therefore, we identified immune-related LncRNAs for the construction of clinical prognostic model. We searched The Cancer Genome Atlas (TCGA) database for original data. Then we identified differentially expressed irlncRNA (DEirlncRNA), which was paired and verified subsequently. Next, univariate analysis, Lasso and Cox regression analysis were performed on the DEirlncRNA pair. The ROC curve of the signature was drawn, and the optimal cut-off value was found. Then the cohort was divided into a high-risk and a low-risk group. Finally, we re-evaluated the signature from different perspectives. A total of 16 pairs of DEirlncRNA were included in the construction of the model. After regrouping according to the cut-off value of 1.275, the high-risk group showed adverse survival outcomes, progressive clinicopathological features, specific immune cell infiltration status, and high sensitivity to some chemotherapy drugs. In conclusion, we constructed a signature composed of immune-related LncRNA pair with no requirement of the specific expression level of genes, which shows promising clinical predictive value in CRC patients.

NPR3, transcriptionally regulated by POU2F1, inhibits osteosarcoma cell growth through blocking the PI3K/AKT pathway

Natriuretic peptide receptor 3 (NPR3), mediates natriuretic peptides degradation, was reported to act as a tumor suppressor or promoter in some types of cancer. Previous studies showed that NPR3 was significantly decreased in osteosarcoma (OS) samples. However, the function and potential regulatory mechanism of NPR3 in OS development are unknown. By analyzing the protein expression of NPR3 in OS cell lines (n = 5) and human osteoblast cell line hFOB 1.19, we found that NPR3 expression was also significantly decreased in OS cells. The loss/gain-of-function analysis indicated that NPR3 overexpression observably decreased OS cell viability, arrested cell cycle, and induced apoptosis. However, NPR3 knockdown further enhanced the malignant phenotype of OS cells. Furthermore, NPR3 downregulation activated the PI3K/AKT pathway in OS cells, and the effects of NPR3 silencing on cell proliferation were reversed by the blockade of PI3K/AKT pathway. Of note, dual-luciferase reported assay and site-directed mutagenesis assay indicated that transcription factor POU domain class 2 transcription factor 1 (POU2F1) was proved to suppress NPR3 promoter activity by mainly binding to the -900 to -800 bp region of NPR3 promoter. Moreover, NPR3 overexpression inversed the promotion effect of POU2F1 on cell proliferation. In vivo experiments confirmed that NPR3 overexpression suppressed the growth of xenograft tumors. Taken together, the present study demonstrates that NPR3 may serve as a novel tumor suppressive factor through blocking the PI3K/AKT pathway and transcriptionally regulated by POU2F1.

B7-H3 suppresses doxorubicin-induced senescence-like growth arrest in colorectal cancer through the AKT/TM4SF1/SIRT1 pathway

Emerging evidence suggests that cellular senescence induced by chemotherapy has been recognized as a new weapon for cancer therapy. This study aimed to research novel functions of B7-H3 in cellular senescence induced by a low dose of doxorubicin (DOX) in colorectal cancer (CRC). Here, our results demonstrated that B7-H3 knockdown promoted, while B7-H3 overexpression inhibited, DOX-induced cellular senescence. B7-H3 knockdown dramatically enhanced the growth arrest of CRC cells after low-dose DOX treatment, but B7-H3 overexpression had the opposite effect. By RNA-seq analysis and western blot, we showed that B7-H3 prevented cellular senescence and growth arrest through the AKT/TM4SF1/SIRT1 pathway. Blocking the AKT/TM4SF1/SIRT1 pathway dramatically reversed B7-H3-induced resistance to cellular senescence. More importantly, B7-H3 inhibited DOX-induced cellular senescence of CRC cells in vivo. Therefore, targeting B7-H3 or the B7-H3/AKT/TM4SF1/SIRT1 pathway might be a new strategy for promoting cellular senescence-like growth arrest during drug treatment in CRC.

Transcriptomic Profiling Identifies DCBLD2 as a Diagnostic and Prognostic Biomarker in Pancreatic Ductal Adenocarcinoma

Background: Accumulating evidence shows that the elevated expression of DCBLD2 (discoidin, CUB and LCCL domain-containing protein 2) is associated with unfavorable prognosis of various cancers. However, the correlation of DCBLD2 expression value with the diagnosis and prognosis of pancreatic ductal adenocarcinoma (PDAC) has not yet been elucidated. Methods: Univariate Cox regression analysis was used to screen robust survival-related genes. Expression pattern of selected genes was investigated in PDAC tissues and normal tissues from multiple cohorts. Kaplan–Meier (K–M) survival curves, ROC curves and calibration curves were employed to assess prognostic performance. The relationship between DCBLD2 expression and immune cell infiltrates was conducted by CIBERSORT software. Biological processes and KEGG pathway enrichment analyses were adopted to clarify the potential function of DCBLD2 in PDAC. Results: Univariate analysis, K–M survival curves and calibration curves indicated that DCBLD2 was a robust prognostic factor for PDAC with cross-cohort compatibility. Upregulation of DCBLD2 was observed in dissected PDAC tissues as well as extracellular vesicles from both plasma and serum samples of PDAC patients. Both DCBLD2 expression in tissue and extracellular vesicles had significant diagnostic value. Besides, DCBLD2 expression was correlated with infiltrating level of CD8⁺ T cells and macrophage M2 cells. Functional enrichment revealed that DCBLD2 might be involved in cell motility, angiogenesis, and cancer-associated pathways. Conclusion: Our study systematically analyzed the potential diagnostic, prognostic and therapeutic value of DCBLD2 in PDAC. All the findings indicated that DCBLD2 might play a considerably oncogenic role in PDAC with diagnostic, prognostic and therapeutic potential. These preliminary results of bioinformatics analyses need to be further validated in more prospective studies.

Comprehensive analysis of tumor mutation burden and immune microenvironment in gastric cancer

Tumor mutation burden (TMB) was a promising marker for immunotherapy. We aimed to investigate the prognostic role of TMB and its relationship with immune cells infiltration in gastric cancer (GC). We analyzed the mutation landscape of all GC cases and TMB of each GC patient was calculated and patients were divided into TMB-high and TMB-low group. Differentially expressed genes (DEGs) between the two groups were identified and pathway analysis was performed. The immune cells infiltration in each GC patient was evaluated and Kaplan-Meier analysis was performed to investigate the prognostic role of immune cells infiltration. At last, hub immune genes were identified and a TMB prognostic risk score (TMBPRS) was constructed to predict the survival outcome of GC patients. The relationships between mutants of hub immune genes and immune infiltration level in GC was investigated. We found higher TMB was correlated with better survival outcome and female patients, patients with T1-2 and N0 had higher TMB score. Altogether 816 DEGs were harvested and pathway analysis demonstrated that patients in TMB-high group were associated with neuroactive ligand-receptor interaction, cAMP signaling pathway, calcium signaling pathway. The infiltration of activated CD4+ memory T cells, follicular helper T cells, resting NK cells, M0 and M1 macrophages and neutrophils in TMB-high group were higher compared than that in TMB-low group and high macrophage infiltration was correlated with inferior survival outcome of GC patients. Lastly, the TMBPRS was constructed and GC patients with high TMBPRS had poor prognosis.

The clinical relevance of gene expression based prognostic signatures in colorectal cancer

Colorectal cancer (CRC) is one of the most prevalent cancers, with more than one million new cases every year. In the last few decades, several advancements in therapeutic and preventative levels have reduced the mortality rate, but new biomarkers are required for improved prognosis. The alterations at the genetic and epigenetic level have been recognized as major players in tumorigenesis. The products of gene expression in the form of mRNA, microRNA, and long-noncoding RNA, have started to emerge as important regulatory molecules, playing an important role in cancer. Gene-expression based prognostic risk scores, which quantify and compare their expression, have emerged as promising biomarkers with enormous clinical value. These composite multi-gene models in which more than one gene is used to predict prognosis have been shown to be significantly effective in identifying patients with multiple clinico-pathological risks like overall mortality, response to chemotherapy, risk of metastasis, etc. The advent of microarray and advanced sequencing technologies have led to the generation of large datasets like TCGA (The Cancer Genome Atlas) and GEO (Gene Expression Omnibus), which have fueled the search for new biomarkers. Continuous evaluation of these candidate biomarkers in clinical settings is promising to improve the management of CRC. These composite gene signatures provide potential in identifying high-risk patients, which might help clinicians to better manage these patients and design appropriate personalized therapeutic interventions. In this review, we emphasize on composite prognostic scores from diverse resources with clinical utility in CRC.

Identification of Hypoxia Signature to Assess the Tumor Immune Microenvironment and Predict Prognosis in Patients with Ovarian Cancer

BACKGROUND

The 5-year overall survival rate of ovarian cancer (OC) patients is less than 40%. Hypoxia promotes the proliferation of OC cells and leads to the decline of cell immunity. It is crucial to find potential predictors or risk model related to OC prognosis. This study aimed at establishing the hypoxia-associated gene signature to assess tumor immune microenvironment and predicting the prognosis of OC.

METHODS

The gene expression data of 378 OC patients and 370 OC patients were downloaded from datasets. The hypoxia risk model was constructed to reflect the immune microenvironment in OC and predict prognosis.

RESULTS

8 genes (AKAP12, ALDOC, ANGPTL4, CITED2, ISG20, PPP1R15A, PRDX5, and TGFBI) were included in the hypoxic gene signature. Patients in the high hypoxia risk group showed worse survival. Hypoxia signature significantly related to clinical features and may serve as an independent prognostic factor for OC patients. 2 types of immune cells, plasmacytoid dendritic cell and regulatory T cell, showed a significant infiltration in the tissues of the high hypoxia risk group patients. Most of the immunosuppressive genes (such as ARG1, CD160, CD244, CXCL12, DNMT1, and HAVCR1) and immune checkpoints (such as CD80, CTLA4, and CD274) were upregulated in the high hypoxia risk group. Gene sets related to the high hypoxia risk group were associated with signaling pathways of cell cycle, MAPK, mTOR, PI3K-Akt, VEGF, and AMPK.

CONCLUSION

The hypoxia risk model could serve as an independent prognostic indicator and reflect overall immune response intensity in the OC microenvironment.

Mapping a Circular RNA-microRNA-mRNA-Signaling Regulatory Axis That Modulates Stemness Properties of Cancer Stem Cell Populations in Colorectal Cancer Spheroid Cells

Spheroidal cancer cell cultures have been used to enrich cancer stem cells (CSC), which are thought to contribute to important clinical features of tumors. This study aimed to map the regulatory networks driven by circular RNAs (circRNAs) in CSC-enriched colorectal cancer (CRC) spheroid cells. The spheroid cells established from two CRC cell lines acquired stemness properties in pluripotency gene expression and multi-lineage differentiation capacity. Genome-wide sequencing identified 1503 and 636 circRNAs specific to the CRC parental and spheroid cells, respectively. In the CRC spheroids, algorithmic analyses unveiled a core network of mRNAs involved in modulating stemness-associated signaling pathways, driven by a circRNA–microRNA (miRNA)–mRNA axis. The two major circRNAs, hsa_circ_0066631 and hsa_circ_0082096, in this network were significantly up-regulated in expression levels in the spheroid cells. The two circRNAs were predicted to target and were experimentally shown to down-regulate miR-140-3p, miR-224, miR-382, miR-548c-3p and miR-579, confirming circRNA sponging of the targeted miRNAs. Furthermore, the affected miRNAs were demonstrated to inhibit degradation of six mRNA targets, viz. ACVR1C/ALK7, FZD3, IL6ST/GP130, SKIL/SNON, SMAD2 and WNT5, in the CRC spheroid cells. These mRNAs encode proteins that are reported to variously regulate the GP130/Stat, Activin/Nodal, TGF-β/SMAD or Wnt/β-catenin signaling pathways in controlling various aspects of CSC stemness. Using the CRC spheroid cell model, the novel circRNA–miRNA–mRNA axis mapped in this work forms the foundation for the elucidation of the molecular mechanisms of the complex cellular and biochemical processes that determine CSC stemness properties of cancer cells, and possibly for designing therapeutic strategies for CRC treatment by targeting CSC.

Combined Methylome and Transcriptome Analyses Reveals Potential Therapeutic Targets for EGFR Wild Type Lung Cancers with Low PD-L1 Expression

Simple Summary

Low expression of programmed death-ligand 1 (PD-L1), epidermal growth factor receptor (EGFR) wild-type non-small cell lung cancer (NSCLCs) are refractory, and only few therapeutic options exist. This study aims to clarify the molecular basis of this special subtype of NSCLC and identify potential therapeutic targets. We performed integrating data from multiple sources including transcriptome, methylome, and clinical outcome to uncover the effect of epigenetic changes acting this special subtype lung cancer. We elucidated both aberrant methylation and associated aberrant gene expression and the emerging methylation-transcription patterns were classified as HypoUp, HypoDown, HyperUp, or HyperDown. We found that the aberrant methylation-transcription patterns significantly affect the overall survival time of the patients. We used protein–drug interaction data and molecular docking analysis to identify potential therapeutic candidates. This study uncovered the distinct methylation-transcription characteristics of this special subtype lung cancer, and provided an adaptable way to identify potential therapeutic targets.

Abstract

Immune checkpoint inhibitors (ICIs) targeting PD-1/PD-L1 have demonstrated remarkable treatment efficacy in advanced non-small cell lung cancer (NSCLC). However, low expression of programmed death-ligand 1 (PD-L1), epidermal growth factor receptor (EGFR) wild-type NSCLCs are refractory, and only few therapeutic options exist. Currently, combination therapy with ICIs is frequently used in order to enhance the treatment response rates. Yet, this regimen is still associated with poor treatment outcome. Therefore, identification of potential therapeutic targets for this subgroup of NSCLC is strongly desired. Here, we report the distinct methylation signatures of this special subgroup. Moreover, several druggable targets and relevant drugs for targeted therapy were incidentally identified. We found hypermethylated differentially methylated regions (DMRs) in three regions (TSS200, TSS1500, and gene body) are significantly higher than hypomethylated ones. Downregulated methylated genes were found to be involved in negative regulation of immune response and T cell-mediated immunity. Moreover, expression of four methylated genes (PLCXD3 (Phosphatidylinositol-Specific Phospholipase C, X Domain Containing 3), BAIAP2L2 (BAR/IMD Domain Containing Adaptor Protein 2 Like 2), NPR3 (Natriuretic Peptide Receptor 3), SNX10 (Sorting Nexin 10)) can influence patients’ prognosis. Subsequently, based on DrugBank data, NetworkAnalyst 3.0 was used for protein–drug interaction analysis of up-regulated differentially methylated genes. Protein products of nine genes were identified as potential druggable targets, of which the tumorigenic potential of XDH (Xanthine Dehydrogenase), ATIC (5-Aminoimidazole-4-Carboxamide Ribonucleotide Formyltransferase/IMP Cyclohydrolase), CA9 (Carbonic Anhydrase 9), SLC7A11 (Solute Carrier Family 7 Member 11), and GAPDH (Glyceraldehyde-3-Phosphate Dehydrogenase) have been demonstrated in previous studies. Next, molecular docking and molecular dynamics simulation were performed to verify the structural basis of the therapeutic targets. It is noteworthy that the identified pemetrexed targeting ATIC has been recently approved for first-line use in combination with anti-PD1 inhibitors against lung cancer, irrespective of PD-L1 expression. In future work, a pivotal clinical study will be initiated to further validate our findings.

Development of an Immune Infiltration-Related Eight-Gene Prognostic Signature in Colorectal Cancer Microenvironment

Objective

Stromal cells and immune cells have important clinical significance in the microenvironment of colorectal cancer (CRC). This study is aimed at developing a CRC gene signature on the basis of stromal and immune scores.

Methods

A cohort of CRC patients (n = 433) were adopted from The Cancer Genome Atlas (TCGA) database. Stromal/immune scores were calculated by the ESTIMATE algorithm. Correlation between prognosis/clinical characteristics and stromal/immune scores was assessed. Differentially expressed stromal and immune genes were identified. Their potential functions were annotated by functional enrichment analysis. Cox regression analysis was used to develop an eight-gene risk score model. Its predictive efficacies for 3 years, 5 years, overall survival (OS), and progression-free survival interval (PFI) were evaluated using time-dependent receiver operating characteristic (ROC) curves. The correlation between the risk score and the infiltering levels of six immune cells was analyzed using TIMER. The risk score was validated using an independent dataset.

Results

Immune score was in a significant association with prognosis and clinical characteristics of CRC. 736 upregulated and two downregulated stromal and immune genes were identified, which were mainly enriched into immune-related biological processes and pathways. An-eight gene prognostic risk score model was conducted, consisting of CCL22, CD36, CPA3, CPT1C, KCNE4, NFATC1, RASGRP2, and SLC2A3. High risk score indicated a poor prognosis of patients. The area under the ROC curves (AUC) s of the model for 3 years, 5 years, OS, and PFI were 0.71, 0.70, 0.73, and 0.66, respectively. Thus, the model possessed well performance for prediction of patients' prognosis, which was confirmed by an external dataset. Moreover, the risk score was significantly correlated with immune cell infiltration.

Conclusion

Our study conducted an immune-related prognostic risk score model, which could provide novel targets for immunotherapy of CRC.

Detecting Cancer Survival Related Gene Markers Based on Rectified Factor Network

Detecting gene sets that serve as biomarkers for differentiating patient survival groups may help diagnose diseases robustly and develop multi-gene targeted therapies. However, due to the exponential growth of search space imposed by gene combinations, the performance of existing methods is still far from satisfactory. In this study, we developed a new method called BISG (BIclustering based Survival-related Gene sets detection) based on a rectified factor network (RFN) model, which allows efficiently biclustering gene subsets. By correlating genes in each significant bicluster with patient survival outcomes using a log-rank test and multi-sampling strategy, multiple survival-related gene sets can be detected. We applied BISG on three different cancer types, and the resulting gene sets were tested as biomarkers for survival analyses. Secondly, we systematically analyzed 12 different cancer datasets. Our analysis shows that the genes in all the survival-related gene sets are mainly from five gene families: microRNA protein coding host genes, zinc fingers C2H2-type, solute carriers, CD (cluster of differentiation) molecules, and ankyrin repeat domain containing genes. Moreover, we found that they are mainly enriched in heme metabolism, apoptosis, hypoxia and inflammatory response-related pathways. We compared BISG with two other methods, GSAS and IPSOV. Results show that BISG can better differentiate patient survival groups in different datasets. The identified biomarkers suggested by our study provide useful hypotheses for further investigation. BISG is publicly available with open source at https://github.com/LingtaoSu/BISG.

Identification of Four Pathological Stage-Relevant Genes in Association with Progression and Prognosis in Clear Cell Renal Cell Carcinoma by Integrated Bioinformatics Analysis

Clear cell renal cell carcinoma (ccRCC) is a major histological subtype of renal cell carcinoma and can be clinically divided into four stages according to the TNM criteria. Identifying clinical stage-related genes is beneficial for improving the early diagnosis and prognosis of ccRCC. By using bioinformatics analysis, we aim to identify clinical stage-relevant genes that are significantly associated with the development of ccRCC. First, we analyzed the gene expression microarray data sets: GSE53757 and GSE73731. We divided these data into five groups by staging information-normal tissue and ccRCC stages I, II, III, and IV-and eventually identified 500 differentially expressed genes (DEGs). To obtain precise stage-relevant genes, we subsequently applied weighted gene coexpression network analysis (WGCNA) to the GSE73731 dataset and KIRC data from The Cancer Genome Atlas (TCGA). Two modules from each dataset were identified to be related to the tumor TNM stage. Several genes with high inner connection inside the modules were considered hub genes. The intersection results between hub genes of key modules and 500 DEGs revealed UBE2C, BUB1B, RRM2, and TPX2 as highly associated with the stage of ccRCC. In addition, the candidate genes were validated at both the RNA expression level and the protein level. Survival analysis also showed that 4 genes were significantly correlated with overall survival. In conclusion, our study affords a deeper understanding of the molecular mechanisms associated with the development of ccRCC and provides potential biomarkers for early diagnosis and individualized treatment for patients at different stages of ccRCC.

A comparative analysis of RNA sequencing methods with ribosome RNA depletion for degraded and low-input total RNA from formalin-fixed and paraffin-embedded samples

Background

Formalin-fixed and paraffin-embedded (FFPE) blocks held in clinical laboratories are an invaluable resource for clinical research, especially in the era of personalized medicine. It is important to accurately quantitate gene expression with degraded and small amounts of total RNA from FFPE materials.

Results

High concordance in transcript quantifications were shown between FF and FFPE samples using the same kit. The gene expression using the TaKaRa kit showed a difference with other kits, which may be due to the different principle of rRNA depletion or the amount of input total RNA. For seriously degraded RNA from FFPE samples, libraries could be constructed with as low as 50 ng of total RNA, although there was residual rRNA in the libraries. Data analysis with HISAT demonstrated that the unique mapping ratio, percentage of exons in unique mapping reads and number of detected genes decreased along with the decreasing quality of input RNA.

Conclusions

The method of RNA library construction with rRNA depletion can be used for clinical FFPE samples. For degraded and low-input RNA samples, it is still possible to obtain repeatable RNA expression profiling but with a low unique mapping ratio and high residual rRNA.

Antagonism between the RNA-binding protein Musashi1 and miR-137 and its potential impact on neurogenesis and glioblastoma development

RNA-binding proteins (RBPs) and miRNAs are critical gene expression regulators that interact with one another in cooperative and antagonistic fashions. We identified Musashi1 (Msi1) and miR-137 as regulators of a molecular switch between self-renewal and differentiation. Msi1 and miR-137 have opposite expression patterns and functions, and Msi1 is repressed by miR-137. Msi1 is a stem-cell protein implicated in self-renewal while miR-137 functions as a proneuronal differentiation miRNA. In gliomas, miR-137 functions as a tumor suppressor while Msi1 is a prooncogenic factor. We suggest that the balance between Msi1 and miR-137 is a key determinant in cell fate decisions and disruption of this balance could contribute to neurodegenerative diseases and glioma development. Genomic analyses revealed that Msi1 and miR-137 share 141 target genes associated with differentiation, development, and morphogenesis. Initial results pointed out that these two regulators have an opposite impact on the expression of their target genes. Therefore, we propose an antagonistic model in which this network of shared targets could be either repressed by miR-137 or activated by Msi1, leading to different outcomes (self-renewal, proliferation, tumorigenesis).