OTOP2, Inversely Modulated by miR-3148, Inhibits CRC Cell Migration, Proliferation and Epithelial–Mesenchymal Transition: Evidence from Bioinformatics Data Mining and Experimental Verification

Guanylate cyclase-C Signaling Axis as a theragnostic target in colorectal cancer: a systematic review of literature

Introduction

Colorectal cancer (CRC) is a devastating disease that affects millions of people worldwide. Recent research has highlighted the crucial role of the guanylate cyclase-C (GC-C) signaling axis in CRC, from the early stages of tumorigenesis to disease progression. GC-C is activated by endogenous peptides guanylin (GU) and uroguanylin (UG), which are critical in maintaining intestinal fluid homeostasis. However, it has been found that these peptides may also contribute to the development of CRC. This systematic review focuses on the latest research on the GC-C signaling axis in CRC.

Methods

According to the aim of the study, a systematic literature search was conducted on Medline and PubMed databases. Ultimately, a total of 40 articles were gathered for the systematic review.

Results

Our systematic literature search revealed that alterations in GC-C signaling compartments in CRC tissue have demonstrated potential as diagnostic, prognostic, and therapeutic markers. This research highlights a potential treatment for CRC by targeting the GC-C signaling axis. Promising results from recent studies have explored the use of this signaling axis to develop new vaccines and chimeric antigen receptors that may be used in future clinical trials.

Conclusion

The findings presented in this review provide compelling evidence that targeting the GC-C signaling axis may be an advantageous approach for treating CRC.

Microarray profiling of serum micro-RNAs in women with Chlamydia trachomatis-associated recurrent spontaneous abortion: A case control study

Chlamydia trachomatis infection is a major cause of sexually transmitted diseases and adverse pregnancy outcomes such as recurrent spontaneous abortion (RSA). Micro-RNAs (miRNAs) have been known to be upregulated/downregulated in various reproductive-associated diseases such as ectopic pregnancy, preterm birth and pre-eclampsia. However, there is paucity of literature on miRNA profile in C. trachomatis-infected RSA. The present study aimed to determine the profile of serum miRNAs followed by their validation in C. trachomatis-infected RSA and to find target genes involved in biological pathways. Non-heparinized blood and first void urine were collected from 30 non-pregnant women with RSA and 30 non-pregnant women with ≥2 successful deliveries (controls) attending Department of Obstetrics and Gynaecology, Safdarjung hospital, New Delhi, India. C. trachomatis detection was done in urine by PCR and chlamydial load was determined by quantitative real-time PCR (qRT-PCR). miRNA expression was studied by microarray analysis followed by in vitro validation by qRT-PCR. Analysis of target genes/pathways was characterized in silico. 06 RSA patients were infected with C. trachomatis, while chlamydial load was found to be 6000-12,000 copies/ml. 110 circulating miRNAs were expressed differentially in infected RSA patients compared with controls. Of these, 16 were overexpressed and 94 downregulated. 06 differentially expressed circulating miRNAs were selected to validate the microarray results. qRT-PCR data confirmed the reliability of the microarray results: miR-4443, -5100, -7975 showed statistically significant upregulation, while miR-6808-5p, -3148, -6727-5p were significantly downregulated in infected RSA patients versus controls. Chlamydial load was positively correlated with these upregulated miRNAs. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed that target genes of miRNAs in RSA are involved in AMPK, Akt and mTOR signaling pathways. Overall results indicate that differentially expressed circulating miRNAs are involved in pathogenesis of C. trachomatis-associated RSA and have the potential to be used as biomarkers for predicting RSA.

Spatial tumour gene signature discriminates neoplastic from non-neoplastic compartments in colon cancer: unravelling predictive biomarkers for relapse

BACKGROUND

Opting for or against the administration of adjuvant chemotherapy in therapeutic management of stage II colon cancer remains challenging. Several studies report few survival benefits for patients treated with adjuvant therapy and additionally revealing potential side effects of overtreatment, including unnecessary exposure to chemotherapy-induced toxicities and reduced quality of life. Predictive biomarkers are urgently needed. We, therefore, hypothesise that the spatial tissue composition of relapsed and non-relapsed colon cancer stage II patients reveals relevant biomarkers.

METHODS

The spatial tissue composition of stage II colon cancer patients was examined by a novel spatial transcriptomics technology with sub-cellular resolution, namely in situ sequencing. A panel of 176 genes investigating specific cancer-associated processes such as apoptosis, proliferation, angiogenesis, stemness, oxidative stress, hypoxia, invasion and components of the tumour microenvironment was designed to examine differentially expressed genes in tissue of relapsed versus non-relapsed patients. Therefore, FFPE slides of 10 colon cancer stage II patients either classified as relapsed (5 patients) or non-relapsed (5 patients) were in situ sequenced and computationally analysed.

RESULTS

We identified a tumour gene signature that enables the subclassification of tissue into neoplastic and non-neoplastic compartments based on spatial expression patterns obtained through in situ sequencing. We developed a computational tool called Genes-To-Count (GTC), which automates the quantification of in situ signals, accurately mapping their position onto the spatial tissue map and automatically identifies neoplastic and non-neoplastic tissue compartments. The GTC tool was used to quantify gene expression of biological processes upregulated within the neoplastic tissue in comparison to non-neoplastic tissue and within relapsed versus non-relapsed stage II colon patients. Three differentially expressed genes (FGFR2, MMP11 and OTOP2) in the neoplastic tissue compartments of relapsed patients in comparison to non-relapsed patients were identified predicting recurrence in stage II colon cancer.

CONCLUSIONS

In depth spatial in situ sequencing showed potential to provide a deeper understanding of the underlying mechanisms involved in the recurrence of disease and revealed novel potential predictive biomarkers for disease relapse in colon cancer stage II patients. Our open-access GTC-tool allowed us to accurately capture the tumour compartment and quantify spatial gene expression in colon cancer tissue.

Molecular mechanisms investigation for liver metastasis of colorectal cancer by combined bioinformatic gene expression profile analysis

BACKGROUND

Colorectal cancer (CRC) is one of the most common cancers worldwide. As the molecular mechanism for liver metastasis of CRC has not yet been completely discovered, identification of hub genes and pathways of this disease is of importance for revealing potential molecular mechanism of colorectal cancer progression. This study aimed to identify potential biomarkers and survival analysis of hub genes for CRC treatment.

METHODS

The differentially expressed genes (DEGs) between colorectal cancer liver metastasis and primary tumor were screened using microarray data from two datasets GSE179979, GSE144259 obtained from the Gene Expression Omnibus (GEO) database. Gene ontology (GO) and KEGG pathway enrichment analyses were performed for DEGs using DAVID database, the protein-protein interaction (PPI) network was constructed using the Cytoscape software, and module analysis was performed using MCODE. Then, overall survival (OS), progression free interval (PFI) and disease specific survival (DSS) analysis of hub genes was performed by using TCGA database. The correlations between hub genes and clinical values were validated through CRN and immunohistochemistry (IHC) stain.

RESULTS

A total of 64 DEGs were obtained, KEGG pathway analysis showed that the significant pathways included PPAR signaling pathway, Complement and coagulation cascades. Four hub genes (ITIH2, ALB, CPB2, HGFAC) and two biomarkers (CPB2, HGFAC) with significantly prognostic values were verified by Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) cohort.

CONCLUSIONS

 CPB2 and HGFAC may serve as new biomarkers in diagnosing liver metastasis of CRC or potential drug target.

Alterations in Gene Pair Correlations as Potential Diagnostic Markers for Colon Cancer

Colorectal cancer (CRC) is a leading cause of death from cancer in Canada. Early detection of CRC remains crucial in managing disease prognosis and improving patient survival. It can also facilitate prevention, screening, and treatment before the disease progresses to a chronic stage. In this study, we developed a strategy for identifying colon cancer biomarkers from both gene expression and gene pair correlation. Using the RNA-Seq dataset TCGA-COAD, a panel of 71 genes, including the 20 most upregulated genes, 20 most downregulated genes and 31 genes involved in the most significantly altered gene pairs, were selected as potential biomarkers for colon cancer. This signature set of genes could be used for early diagnosis. Furthermore, this strategy could be applied to other types of cancer.