The biological significance of micro (mi)RNAs has traditionally been evaluated according to their RNA expression levels based on the assumption that miRNAs recognize and regulate their targets in an unvarying fashion. Here we show that a fraction of mature miRNAs including miR-17-5p, -21-5p, and -200c-3p and let-7a-5p harbor methyl marks that potentially alter their stability and target recognition. Importantly, methylation of these miRNAs was significantly increased in cancer tissues as compared to paired normal tissues. Furthermore, miR-17-5p methylation level in serum samples distinguished early pancreatic cancer patients from healthy controls with extremely high sensitivity and specificity. These findings provide a basis for diagnostic strategies for early-stage cancer and add a dimension to our understanding of miRNA biology.

Cancer stem cells (CSCs) are involved in metastatic colorectal cancer recurrence, but no effective therapy targeting these cells is currently available. Because trifluridine (FTD)/tipiracil therapy is used for refractory colorectal cancer, we sought to determine whether FTD is effective against CSC-like cells. CD44⁺CD133⁺high-expressing and other populations of human DLD-1 colon cancer cells were separately isolated through fluorescence-activated cell sorting. The sphere-forming activity of each population and the anti-sphere-forming effects of FTD and fluorouracil (5-FU) on CD44⁺CD133⁺cells were then measured. CD44⁺CD133⁺DLD-1 cells formed substantially more spheres than other cells. Moreover, treating CD44⁺CD133⁺DLD-1 cells with subtoxic concentrations of FTD (1 µM) inhibited sphere formation, and this was superior to the effect of subtoxic concentrations (1 µM) of 5-FU. The associated inhibition rates for FTD and 5-FU were 58.2% and 26.1%, respectively. Further, CD44⁺CD133⁺DLD-1 cells expressed higher levels of thymidine kinase 1, which is responsible for FTD phosphorylation, than DLD-1 cells, and FTD was incorporated into the DNA of CD44⁺CD133⁺DLD-1 cells. Thus, our data show that FTD treatment is effective against CSC-like cells and might be applied as CSC-targeting chemotherapy for tumor subtypes with high CD44 and CD133 expression.

Since the infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was reported in China during December 2019, the coronavirus disease 2019 (COVID-19) has spread on a global scale, causing the World Health Organization (WHO) to issue a warning. While novel vaccines and drugs that target SARS-CoV-2 are under development, this review provides information on therapeutics which are under clinical trials or are proposed to antagonize SARS-CoV-2. Based on the information gained from the responses to other RNA coronaviruses, including the strains that cause severe acute respiratory syndrome (SARS)-coronaviruses and Middle East respiratory syndrome (MERS), drug repurposing might be a viable strategy. Since several antiviral therapies can inhibit viral replication cycles or relieve symptoms, mechanisms unique to RNA viruses will be important for the clinical development of antivirals against SARS-CoV-2. Given that several currently marketed drugs may be efficient therapeutic agents for severe COVID-19 cases, they may be beneficial for future viral pandemics and other infections caused by RNA viruses when standard treatments are unavailable.

Mitochondrial pyruvate carrier (MPC) is known to cause different expressions in normal and cancer cells. We observed a change in phenotype with the suppression of MPC expression. We knocked down MPC1 and/or MPC2 using siRNA or shRNA. We observed its cell morphology and accompanying molecular marker. Furthermore, the radioresistance of the MPC knockdown cell line was examined using a colony formation assay. MPC1‐suppressed cells changed their morphology to a spindle shape. Epithelial‐mesenchymal transition (EMT) was suspected, and examination of the EMT marker by PCR showed a decrease in E‐cadherin and an increase in fibronectin. Focusing on glutamine metabolism as the mechanism of this phenomenon, we knocked down the glutamine‐metabolizing enzyme glutaminase (GLS). EMT was also observed in GLS‐suppressed cells. Furthermore, when MPC1‐suppressed cells were cultured in a glutamine‐deficient medium, changes in EMT markers were suppressed. In addition, MPC1‐suppressed cells also increased with a significant difference in radioresistance. Decreased MPC1 expression favorably affects EMT and radioresistance of cancer.

Cancer stem cells (CSCs), defined by their differentiation capacity, self-renewal capacity, and maintenance of proliferation, have been identified in many tumors, including cervical cancer. Current studies identify CSCs by several specific biomarkers; however, it is difficult to monitor cervical CSCs in real-time in vitro and in vivo. Recent research reported the visualization of CSCs in breast cancer and gliomas using green fluorescent protein, ZsGreen, fused to a degron motif ornithine decarboxylase (ODC), which is destroyed by proteasomes. Accordingly, CSCs have low 26S proteasome activity, whereas non-CSCs have high 26S proteasome activity. Therefore, it is possible to observe CSCs by their accumulation of the fluorescent ZsGreen protein. In this study, we investigated optical imaging parameters to evaluate CSCs using two human cervical cancer cell lines: CaSki and HeLa. We defined populations as cell types having high- and low ZsGreen-cODC (high- and low-Zs, respectively) expression levels. The results of a sphere-forming assay revealed that the self-renewal ability of the high-Zs population was significantly higher than that of the low-Zs population. A tumorigenicity assay confirmed that the high-Zs population exhibited higher tumorigenic potential than the low-Zs population. The radioresistance of the high-Zs population of both HeLa and CaSki cells and the chemoresistance of the high-Zs population of CaSki cells were confirmed by a clonogenic survival assay and the tetrazolium dye assay, respectively. These results indicate that high-Zs populations of both the HeLa and CaSki cell lines possess CSC-like properties and therapeutic resistance. In conclusion, we successfully visualized CSC-like cells using a fluorescent protein system.

It is known that single or isolated tumor cells enter cancer patients’ circulatory systems. These circulating tumor cells (CTCs) are thought to be an effective tool for diagnosing cancer malignancy. However, handling CTC samples and evaluating CTC sequence analysis results are challenging. Recently, the convolutional neural network (CNN) model, a type of deep learning model, has been increasingly adopted for medical image analyses. However, it is controversial whether cell characteristics can be identified at the single-cell level by using machine learning methods. This study intends to verify whether an AI system could classify the sensitivity of anticancer drugs, based on cell morphology during culture. We constructed a CNN based on the VGG16 model that could predict the efficiency of antitumor drugs at the single-cell level. The machine learning revealed that our model could identify the effects of antitumor drugs with ~0.80 accuracies. Our results show that, in the future, realizing precision medicine to identify effective antitumor drugs for individual patients may be possible by extracting CTCs from blood and performing classification by using an AI system.