The microRNA-429/DUSP4 axis regulates the sensitivity of colorectal cancer cells to nintedanib

Novel biomarkers used for early diagnosis and tyrosine kinase inhibitors as targeted therapies in colorectal cancer

Colorectal cancer (CRC) is the third most common and second most lethal type of cancer worldwide, presenting major health risks as well as economic costs to both people and society. CRC survival chances are significantly higher if the cancer is diagnosed and treated early. With the development of molecular biology, numerous initiatives have been undertaken to identify novel biomarkers for the early diagnosis of CRC. Pathological disorders can be diagnosed at a lower cost with the help of biomarkers, which can be detected in stool, blood, and tissue samples. Several lines of evidence suggest that the gut microbiota could be used as a biomarker for CRC screening and treatment. CRC treatment choices include surgical resection, chemotherapy, immunotherapy, gene therapy, and combination therapies. Targeted therapies are a relatively new and promising modality of treatment that has been shown to increase patients' overall survival (OS) rates and can inhibit cancer cell development. Several small-molecule tyrosine kinase inhibitors (TKIs) are being investigated as potential treatments due to our increasing awareness of CRC's molecular causes and oncogenic signaling. These compounds may inhibit critical enzymes in controlling signaling pathways, which are crucial for CRC cells' development, differentiation, proliferation, and survival. On the other hand, only one of the approximately 42 TKIs that demonstrated anti-tumor effects in pre-clinical studies has been licensed for clinical usage in CRC. A significant knowledge gap exists when bringing these tailored medicines into the clinic. As a result, the emphasis of this review is placed on recently discovered biomarkers for early diagnosis as well as tyrosine kinase inhibitors as possible therapy options for CRC.

LncRNA FALEC increases the proliferation, migration and drug resistance of cholangiocarcinoma through competitive regulation of miR-20a-5p/SHOC2 axis

BACKGROUND

LncRNA is an important regulatory factor in the human genome. We aim to explore the roles of LncFALEC and miR-20a-5p/SHOC2 axis on the proliferation, migration, and Fluorouracil (5-FU) resistance of cholangiocarcinoma (CCA).

METHODS

In this study, the expression of FALEC and miR-20a-5p in CCA tissues and cell lines (HuCCT1, QBC939, and Huh-28) was detected by RT-qPCR. The FALEC in 5-FU-resistant CCA cell lines (QBC939-R, Huh-28-R) was knocked down to evaluate its effects on cell proliferation, migration, invasion, and drug resistance.

RESULTS

Our analysis showed that compared with the adjacent non-tumor tissues, FALEC was significantly higher in the CCA tissues and even higher in the samples from 5-FU-resistant patients. Knockdown FALEC increased the sensitivity of 5-FU and decreased migration and invasion of CCA cells. Dual luciferase reporter confirmed that FALEC sponges miR-20a-5p and down-regulated its expression. Moreover, SHOC2 leucine-rich repeat scaffold protein (SHOC2) was the target gene of miR-20a-5p. We found overexpression of FALEC (FALEC-OE) increased resistance of CCA cells to 5-FU significantly, which might contribute to increased SHOC2 expression and activation of the ERK1/2 signaling pathway.

CONCLUSIONS

In summary, our study revealed that down-regulation of FALEC could inhibit the proliferation, migration, and invasion of CCA cells in vitro by regulating the miR-20a-5p/SHOC2 axis and participating in 5-FU resistance by mediating the ERK1/2 signaling pathway.

Gene Regulatory Network-Classifier: Gene Regulatory Network-Based Classifier and Its Applications to Gastric Cancer Drug (5-Fluorouracil) Marker Identification

The complex mechanisms of diseases involve the disturbance of the molecular network, rather than disorder in a single gene, implying that single gene-based analysis is insufficient to understand these mechanisms. Gene regulatory networks (GRNs) have attracted a lot of interest and various approaches have been developed for their statistical inference and gene network-based analysis. Although various computational methods have been developed, relatively little attention has been paid to incorporation of biological knowledge into the computational approaches. Furthermore, existing studies on network-based analysis perform prediction/classification of status of cell lines based on preconstructed GRNs, implying that we cannot extract prediction/classification-specific gene networks, leading to difficulty in interpretation of biological mechanisms and marker identification related to the status of cancer cell lines. We developed a novel strategy to build a GRN-based classifier, called a GRN-classifier. The proposed GRN-classifier estimates GRNs and classifies cell lines simultaneously, where the gene network is estimated to minimize error in gene network estimation and the negative log-likelihood for classifying cell lines. Thus, we can identify biological status-specific gene regulatory systems, enabling us to achieve biologically reliable interpretation of the classification. We also propose an algorithm to implement the GRN-classifier based on coordinate descent update. Monte Carlo simulations were conducted to examine performance of the GRN-classifier. Results: Our strategy provides effective results in feature selection in the classification model and edge selection in gene network estimation. The GRN-classifier also shows outstanding classification accuracy. We apply the GRN-classifier to classify cancer cell lines into anticancer drug-related status, that is, 5-fluorouracil (5-FU)-sensitive/resistant and 5-FU target/nontarget cancer cell lines. We then identified 5-FU markers based on 5-FU-related status classification-specific gene networks. The mechanisms of the identified markers were verified through literature survey. Our results suggest that the molecular interplay between MYOF and AHNAK2 may play a crucial role in drug resistance and can provide information on the chemotherapy efficiency of 5-FU. It is also suggested that suppression of the identified 5-FU markers, including MYOF/AHNAK2 and AKR1C1/AKR1C3 may improve 5-FU resistance of cancer cell lines.

The role of miR-200 family in the regulation of hallmarks of cancer

MiRNAs are short non-coding RNAs that regulate gene expression post-transcriptionally contributing to the development of different diseases including cancer. The miR-200 family consists of five members, miR-200a, miR-200b, miR-200c, miR-141, and miR-429. Their expression is dysregulated in cancer tissue and their level is altered in the body fluids of cancer patients. Moreover, the levels of miR-200 family members correlate with clinical parameters such as cancer patients' survival which makes them potentially useful as diagnostic and prognostic biomarkers. MiRNAs can act as either oncomiRs or tumor suppressor miRNAs depending on the target genes and their role in the regulation of key oncogenic signaling pathways. In most types of cancer, the miR-200 family acts as tumor suppressor miRNA and regulates all features of cancer. In this review, we summarized the expression pattern of the miR-200 family in different types of cancer and their potential utility as biomarkers. Moreover, we comprehensively described the role of miR-200 family members in the regulation of all hallmarks of cancer proposed by Hanahan and Weinberg with the focus on the epithelial-mesenchymal transition, invasiveness, and metastasis of tumor cells.

Loss of DUSP4 Expression as a Prognostic Biomarker in Clear Cell Renal Cell Carcinoma

Dual-specificity protein phosphatase 4 (DUSP4) is a negative regulator of mitogen-activated protein kinases. The prognostic impact of DUSP4 expression in renal cell carcinoma is not well studied. Therefore, we evaluated the clinicopathological implications of DUSP4 expression in clear cell renal cell carcinoma by performing immunohistochemistry (IHC). The clinical outcome according to DUSP4 expression was evaluated through survival analyses, and the association between mRNA expression and prognosis was confirmed by online analysis (Kaplan-Meier plotter). Loss of DUSP4 expression was noted in most histological subtypes of renal cell carcinoma. Loss of DUSP4 expression in clear cell renal cell carcinoma was significantly correlated with old age (p = 0.033), high histologic grade (p < 0.001), tumor necrosis (p < 0.001), and high pT category (p < 0.001). In survival analysis, loss of DUSP4 expression was associated with poor clinical outcomes in cancer-specific survival and recurrence-free survival (p = 0.010 and p = 0.007, respectively). Upon TCGA data analysis, patients with low DUSP4 mRNA expression showed a shorter overall survival (p = 0.023). These results suggest that loss of DUSP4 expression can be used as a potential biomarker for predicting clinical outcomes in clear cell renal cell carcinoma patients.

miR‑122‑5p suppresses the oncogenesis of PTC by inhibiting DUSP4 expression

MicroRNAs (miRNAs or miRs) play an important role in regulating the occurrence and development of papillary thyroid carcinoma (PTC). miR‑122‑5p is widely considered a tumour inhibitor, which has not been fully explored in PTC. Bioinformatics analysis identified dual specificity phosphatase 4 (DUSP4), a tumour promoter gene for PTC, as a downstream target of miR‑122‑5p. The aim of the present study was to investigate the role and molecular mechanism of miR‑122‑5p in PTC oncogenesis. In this study, the expression pattern of miR‑122‑5p in PTC cancer tissues and PTC cell lines was investigated via reverse transcription‑quantitative PCR. Furthermore, the roles of miR‑122‑5p in PTC were explored using gain‑of‑function and loss‑of‑function assays. The results revealed that the expression of miR‑122‑5p was significantly lower in PTC cancer tissues, especially in cancer tissues with significant invasion or metastasis. Overexpression of miR‑122‑5p caused by miR‑122‑5p mimics inhibited the proliferation, invasion, and migration of the PTC cell line K1, while knockdown of miR‑122‑5p by miR‑122‑5p inhibitors exhibited the opposite effect. Furthermore, in vivo assays revealed that miR‑122‑5p overexpression inhibited tumour growth. In addition, miR‑122‑5p was negatively correlated with DUSP4 expression in PTC cancer tissues. miR‑122‑5p overexpression inhibited DUSP4 expression in K1 cells, while miR‑122‑5p downregulation produced the inverse effect. Specifically, a luciferase reporter assay confirmed the binding sites of miR‑122‑5p on the 3'‑UTR of DUSP4, demonstrating the targeting effect of miR‑122‑5p on DUSP4. miR‑122‑5p inhibited the oncogenesis of PTC by targeting DUSP4, revealing the potential application value of miR‑122‑5p in the diagnosis and treatment of PTC.