Abnormal N6-methyladenosine (m6A) modification is closely associated with the occurrence, development, progression and prognosis of cancer, and aberrant m6A regulators have been identified as novel anticancer drug targets. Both traditional medicine-related approaches and modern drug discovery platforms have been used in an attempt to develop m6A-targeted drugs. Here, we provide an update of the latest findings on m6A modification and the critical roles of m6A modification in cancer progression, and we summarize rational sources for the discovery of m6A-targeted anticancer agents from traditional medicines and computer-based chemosynthetic compounds. This review highlights the potential agents targeting m6A modification for cancer treatment and proposes the advantage of artificial intelligence (AI) in the discovery of m6A-targeting anticancer drugs. Three stages of m6A-targeting anticancer drug discovery: traditional medicine-based natural products, modern chemical modification or synthesis, and artificial intelligence (AI)-assisted approaches for the future. 

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m6A modification: recent advances, anticancer targeted drug discovery and beyond

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Cancer is one of the leading causes of death globally. The development of drug resistance is the main contributor to cancer-related mortality. Cancer cells exploit multiple mechanisms to reduce the therapeutic effects of anticancer drugs, thereby causing chemotherapy failure. Natural products are accessible, inexpensive, and less toxic sources of chemotherapeutic agents. Additionally, they have multiple mechanisms of action to inhibit various targets involved in the development of drug resistance. In this review, we have summarized the basic research and clinical applications of natural products as possible inhibitors for drug resistance in cancer. The molecular targets and the mechanisms of action of each natural product are also explained. Diverse drug resistance biomarkers were sensitive to natural products. P-glycoprotein and breast cancer resistance protein can be targeted by a large number of natural products. On the other hand, protein kinase C and topoisomerases were less sensitive to most of the studied natural products. The studies discussed in this review will provide a solid ground for scientists to explore the possible use of natural products in combination anticancer therapies to overcome drug resistance by targeting multiple drug resistance mechanisms.

Targeting Drug Chemo-Resistance in Cancer Using Natural Products

New 3d Multifunctional Metal Chelates of Sulfonamide: Spectral, Vibrational, Molecular Modeling, DFT, Medicinal and In Silico Studies

Cancer is still one of the most widespread diseases globally, it is considered a vital health challenge worldwide and one of the main barriers to long life expectancy. Due to the potential toxicity and lack of selectivity of conventional chemotherapeutic agents, discovering alternative treatments is a top priority. Plant-derived natural products have high potential in cancer treatment due to their multiple mechanisms of action, diversity in structure, availability in nature, and relatively low toxicity. In this review, the anticancer mechanisms of the most common phytochemicals were analyzed. Furthermore, a detailed discussion of the anticancer effect of combinations consisting of natural product or natural products with chemotherapeutic drugs was provided. This review should provide a strong platform for researchers and clinicians to improve basic and clinical research in the development of alternative anticancer medicines.

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Combination Anticancer Therapies Using Selected Phytochemicals

Purpose This study aimed to investigate the effects of quercetin on the efficacy of various chemotherapeutic drugs in cervical cancer cells.
 Methods
 All drug experiments were performed in HeLa and SiHa cells. The cell viability was detected by Cell Counting Kit-8 assay, and cell proliferation was estimated by bromodeoxyuridine assay. CompuSyn software was utilized to calculate the combination index (CI) and evaluate the synergistic or antagonistic effect of quercetin with cisplatin, paclitaxel, 5-fluorouracil and doxorubicin on cell viability. Cell migration and invasion abilities were detected by transwell assays, and cell apoptosis was measured by flow cytometry. The expression levels of matrix metallopeptidase 2 (MMP2), ezrin, P-glycoprotein (P-Gp) and methyltransferase-like 3 (METTL3) protein treated with various drugs were analyzed by Western blotting.
 Results
 Quercetin inhibited the viability of HeLa and SiHa cells in a dose- and time-dependent manner. The CI values of quercetin with cisplatin, paclitaxel, 5-fluorouracil and doxorubicin were 1, >1 and >1, respectively. The effect of combination of quercetin and cisplatin on cell proliferation was stronger than their individual effects. Co-treatment group could inhibit more cell migration and invasion in contrast to single-drug group. Besides, quercetin combined with cisplatin group induced more cell apoptosis in contrast to single-drug group. The results of Western blotting showed that the expression levels of MMP2, ezrin, P-Gp and METTL3 in co-treatment group were lower than in cisplatin group, respectively.
 Conclusion
 Quercetin and cisplatin had synergistic inhibitory effect on cervical cancer cells. Quercetin might enhance the antitumor effect of cisplatin via inhibiting proliferation, migration and invasion and elevating apoptosis through weakening MMP2, ezrin, METTL3 and P-Gp expression of cancer cells.

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Effects of Quercetin on the Efficacy of Various Chemotherapeutic Drugs in Cervical Cancer Cells.

MEX3A, one member of the human MEX3 gene family, exerts different effects on a variety of human cancer cells. However, the biological functions and regulatory mechanism have not been explored in cervical cancer. In our study, we used multiple approaches to determine the functions and underlying molecular mechanism of MEX3A in cervical tumorigenesis, including CCK-8 assay, BrdU assay, FACS for cell cycle and apoptosis, wound healing assay, Transwell migration and invasion assays, immunohistochemistry (IHC) assay, Transfection, real-time RT-PCR and Western blotting analysis. IHC results showed that the expression levels of MEX3A were decreased in cervical cancer patients with advanced clinical stages and lymph node involvement. Moreover, upregulation of MEX3A attenuated cell proliferation, migration and invasion and induced cell cycle arrest at G0/G1 phase in human cervical cancer cells, whereas knockdown of MEX3A exhibited the opposite effects. Mechanistically, MEX3A exerted its tumor suppressive functions via inactivation of Akt signaling pathway and inhibiting epithelial to mesenchymal transition (EMT). Importantly, Akt activation by its activator SC79 reversed the biological functions of MEX3A overexpression. Furthermore, MEX3A inhibited tumor growth in xenograft models. Overall, our investigation suggested that MEX3A participated in antitumor activity in cervical cancer by inhibition of the Akt signaling pathway and EMT. Hence, targeting MEX3A might have a therapeutic potential to treat cervical cancer.

MEX3A suppresses proliferation and EMT via inhibiting Akt signaling pathway in cervical cancer.

Optical fiber seismic exploration technology has been widely used in marine oil and gas hydrate exploration due to its wide frequency band and high sensitivity. However, there are more types of noise in the collected data by optical fiber hydrophone than by a conventional piezoelectric seismic exploration system. Considering that the conventional denoising method is time-consuming, this paper proposes a convolutional neural network (CNN) and a ResUNet network based on deep learning to suppress the noises. ResUNet is improved on the basis of CNN; it is composed of a feature extraction part, a feature reconstruction part and a residual block. Both CNN and ResUNet networks achieved obvious denoising effects on optical fiber towed streamer seismic data and improved the signal-to-noise ratio of data effectively. The ResUNet network has better denoising effects than CNN, even better than conventional denoising methods. The ResUNet network can solve the problem of gradient disappearance caused by network deepening; it recovered edge data well, and it has high efficiency compared with conventional denoising methods. Two evaluation indexes, relative error (RE) and similarity structure degree (SSIM), were introduced to compare the denoising effect of the ResUNet network with that of CNN. The experimental results showed that the performance of the ResUNet network in these two aspects is better than that of CNN.

https://www.mdpi.com/1996-1073/15/9/3362/pdf?version=1651748793

Hongfei Qian

Papers

Effects of Quercetin on the Efficacy of Various Chemotherapeutic Drugs in Cervical Cancer Cells.

MEX3A suppresses proliferation and EMT via inhibiting Akt signaling pathway in cervical cancer.

Research on Noise Suppression Technology of Marine Optical Fiber Towed Streamer Seismic Data Based on ResUNet

Research on vertical cable seismic interferometry imaging

Research on combined processing techniques of air gun and sparker source towed streamer seismic data