The role of cell surface proteins gene expression in diagnosis, prognosis, and drug resistance of colorectal cancer: In silico analysis and validation

Simultaneous Detection of Collagen I Alpha II and Cytokeratin 19 mRNA by Multiplex qPCR in Liquid Biopsy in Diagnosis of Patients with Resectable Solid Tumors

The early detection of tumors is one of the key factors in increasing overall survival in cancer patients. A wide range of cancers still do not have a system of early diagnosis; therefore, the development of new non-invasive tools in this line is essential. Accordingly, the objective of our work was to develop a non-invasive screening method for the early detection of various carcinomas in plasma using a panel that combines two markers using RT-qPCR. A retrospective case-control study was conducted to develop a cancer screening test based on the detection of stromal and epithelial biomarkers (COL1A2 and KRT19) in plasma. The expression of biomarkers was evaluated using multiplex quantitative PCR applied to 47 cases with non-metastatic tumors and 13 control participants. For both biomarkers, a cut-off value was stablished using Youden's J index through ROC curve analysis and areas under the curve (AUC) were calculated. The plasma mRNA expression level of both biomarkers was significantly higher in diseased versus healthy patients. Moreover, ROC curve analysis showed an AUC value of 0.897 for the combined model. This model also resulted in a cutoff value of 0.664, as well as a sensitivity of 83% and a specificity of 84.6%. These results suggest that the plasma expression levels of COL1A2 and KRT19 could a have potential role in detecting various types of cancer at the early stages. The combined analysis of both stromal and epithelial biomarkers would provide a non-invasive screening method that would allow us to differentiate patients with an active neoplastic process.

Site-specific immobilization of the endosialidase reveals QSOX2 is a novel polysialylated protein

Polysialic acid (polySia) is a linear polymer of α2,8-linked sialic acid residues that is of fundamental biological interest due to its pivotal roles in the regulation of the nervous, immune, and reproductive systems in healthy human adults. PolySia is also dysregulated in several chronic diseases, including cancers and mental health disorders. However, the mechanisms underpinning polySia biology in health and disease remain largely unknown. The polySia-specific hydrolase, endoneuraminidase NF (EndoN), and the catalytically inactive polySia lectin EndoNDM, have been extensively used for studying polySia. However, EndoN is heat stable and remains associated with cells after washing. When studying polySia in systems with multiple polysialylated species, the residual EndoN that cannot be removed confounds data interpretation. We developed a strategy for site-specific immobilization of EndoN on streptavidin-coated magnetic beads. We showed that immobilizing EndoN allows for effective removal of the enzyme from samples, while retaining hydrolase activity. We used the same strategy to immobilize the polySia lectin EndoNDM, which enabled the enrichment of polysialylated proteins from complex mixtures such as serum for their identification via mass spectrometry. We used this methodology to identify a novel polysialylated protein, QSOX2, which is secreted from the breast cancer cell line MCF-7. This method of site-specific immobilization can be utilized for other enzymes and lectins to yield insight into glycobiology.

Exploring the role of interleukin 11 in cancer progression, patient survival, and therapeutic insights

BACKGROUND

The Interleukin (IL)-11 gene, which is one of the members of the cytokine family, has an oncogenic role in some cancers. The main goal of this study is to analyze IL-11 expression level in 14 prevalent cancers and highlights its role in patients' survival, drug resistance, and sensitivities. Also, an association of this gene with metastasis and inflammation pathways has been investigated.

METHODS AND RESULTS

Using the cancer genome atlas (TCGA) data, the level of IL-11 expression and its role in prognosis and survival rate were evaluated in 13 common cancers. Then, confirming the obtained in-silico outcomes, the relative expression level of this gene in colorectal cancer (CRC) samples and their adjusted tissues were assayed by the RT-qPCR method. Furthermore, to examine the association between IL-11 expression and drug resistance and sensitivity, PharmacoGX data was applied. The co-expression network was used to recognize the pathways in which IL-11 was involved. The results from the TCGA dataset indicated that the expression level of IL-11 increased significantly in 13 prevalence cancers compared to the control groups. Interestingly, this enhanced expression level is associated with a high rate of mortality in patients with bladder, stomach, colorectal, and endometrial cancers. Also, the co-expression network analysis showed a strong correlation between IL-11 and the genes of metastasis pathway and the genes related to the inflammation process. Finally, regarding drug sensitivity, IL-11 expression level can be introduced as a remarkable biomarker for cancer detection due to area under curve (AUC).

CONCLUSION

Altered expression of the IL-11 gene is observed in 13 common cancers and is associated with prognosis and mortality rate in patients. Moreover, this gene can be considered a prognostic biomarker in different types of cancer, such as CRC.

ALDH3A2, ODF2, QSOX2, and MicroRNA-503-5p Expression to Forecast Recurrence in TMPRSS2-ERG-Positive Prostate Cancer

Following radical surgery, patients may suffer a relapse. It is important to identify such patients so that therapy tactics can be modified appropriately. Existing stratification schemes do not display the probability of recurrence with enough precision since locally advanced prostate cancer (PCa) is classified as high-risk but is not ranked in greater detail. Between 40 and 50% of PCa cases belong to the TMPRSS2-ERG subtype that is a sufficiently homogeneous group for high-precision prognostic marker search to be possible. This study includes two independent cohorts and is based on high throughput sequencing and qPCR data. As a result, we have been able to suggest a perspective-trained model involving a deep neural network based on both qPCR data for mRNA and miRNA and clinicopathological criteria that can be used for recurrence risk forecasts in patients with TMPRSS2-ERG-positive, locally advanced PCa (the model uses ALDH3A2 + ODF2 + QSOX2 + hsa-miR-503-5p + ISUP + pT, with an AUC = 0.944). In addition to the prognostic model’s use of identified differentially expressed genes and miRNAs, miRNA–target pairs were found that correlate with the prognosis and can be presented as an interactome network.

Target-Based Small Molecule Drug Discovery for Colorectal Cancer: A Review of Molecular Pathways and In Silico Studies

Colorectal cancer is one of the most prevalent cancer types. Although there have been breakthroughs in its treatments, a better understanding of the molecular mechanisms and genetic involvement in colorectal cancer will have a substantial role in producing novel and targeted treatments with better safety profiles. In this review, the main molecular pathways and driver genes that are responsible for initiating and propagating the cascade of signaling molecules reaching carcinoma and the aggressive metastatic stages of colorectal cancer were presented. Protein kinases involved in colorectal cancer, as much as other cancers, have seen much focus and committed efforts due to their crucial role in subsidizing, inhibiting, or changing the disease course. Moreover, notable improvements in colorectal cancer treatments with in silico studies and the enhanced selectivity on specific macromolecular targets were discussed. Besides, the selective multi-target agents have been made easier by employing in silico methods in molecular de novo synthesis or target identification and drug repurposing.

Circ_0030998 Restrains Cisplatin Resistance Through Mediating miR-1323/PDCD4 Axis in Non-small Cell Lung Cancer

We aimed to explore the underlying mechanism behind the cisplatin (DDP) resistance of non-small cell lung cancer (NSCLC) cells to identify novel potential therapeutic targets to overcome chemoresistance. Real-time quantitative polymerase chain reaction (RT-qPCR) and Western blot assay were applied to analyze RNA and protein expression, respectively. Cell Counting Kit-8 (CCK8) assay was conducted to analyze the DDP resistance of NSCLC cells. Colony formation assay and 5-Ethynyl-2'-deoxyuridine (EdU) assay were performed to analyze cell proliferation ability. Flow cytometry was applied to assess cell apoptosis. Cell migration and invasion were assessed by transwell assays. Cell glycolytic metabolism was analyzed using commercial kits. Dual-luciferase reporter assay and RNA immunoprecipitation (RIP) assay were performed to test the intermolecular target relations. Circular RNA_0030998 (circ_0030998) was down-regulated in DDP-resistant NSCLC tissues and cell lines. Circ_0030998 overexpression restrained the DDP resistance, proliferation, migration, invasion and glycolytic metabolism and triggered the apoptosis of NSCLC cells. Circ_0030998 overexpression contributed to the anti-tumor effect of DDP in the growth of xenograft tumor in vivo. MicroRNA-1323 (miR-1323) was a molecular target of circ_0030998 in NSCLC cells. Circ_0030998 overexpression-mediated effects on the DDP resistance and malignant properties of NSCLC cells were largely based on its negative regulation of miR-1323. MiR-1323 interacted with programmed cell death 4 (PDCD4). Circ_0030998 positively regulated PDCD4 expression partly through sponging miR-1323. MiR-1323 silencing restrained DDP resistance and progression of NSCLC partly through up-regulating PDCD4. Circ_0030998 suppressed DDP resistance and NSCLC progression depending on the regulation of miR-1323/PDCD4 axis.