Jiaxin Qin

Despite the success of targeted therapies in cancer treatment, therapy-induced resistance remains a major obstacle to a complete cure. Tumor cells evade treatments and relapse via phenotypic switching driven by intrinsic or induced cell plasticity. Several reversible mechanisms have been proposed to circumvent tumor cell plasticity, including epigenetic modifications, regulation of transcription factors, activation or suppression of key signaling pathways, as well as modification of the tumor environment. Epithelial-to-mesenchymal transition, tumor cell and cancer stem cell formation also serve as roads towards tumor cell plasticity. Corresponding treatment strategies have recently been developed that either target plasticity-related mechanisms or employ combination treatments. In this review, we delineate the formation of tumor cell plasticity and its manipulation of tumor evasion from targeted therapy. We discuss the non-genetic mechanisms of targeted drug-induced tumor cell plasticity in various types of tumors and provide insights into the contribution of tumor cell plasticity to acquired drug resistance. New therapeutic strategies such as inhibition or reversal of tumor cell plasticity are also presented. We also discuss the multitude of clinical trials that are ongoing worldwide with the intention of improving clinical outcomes. These advances provide a direction for developing novel therapeutic strategies and combination therapy regimens that target tumor cell plasticity.

Abstract Protein phosphorylation is an important post‐transcriptional modification involving an extremely wide range of intracellular signaling transduction pathways, making it an important therapeutic target for disease intervention. At present, numerous drugs targeting protein phosphorylation have been developed for the treatment of various diseases including malignant tumors, neurological diseases, infectious diseases, and immune diseases. In this review article, we analyzed 303 small‐molecule protein phosphorylation kinase inhibitors (PKIs) registered and participated in clinical research obtained in a database named Protein Kinase Inhibitor Database (PKIDB), including 68 drugs approved by the Food and Drug Administration of the United States. Based on previous classifications of kinases, we divided these human protein phosphorylation kinases into eight groups and nearly 50 families, and delineated their main regulatory pathways, upstream and downstream targets. These groups include: protein kinase A, G, and C (AGC) and receptor guanylate cyclase (RGC) group, calmodulin‐dependent protein kinase (CaMK) group, CMGC [Cyclin‐dependent kinases (CDKs), Mitogen‐activated protein kinases (MAPKs), Glycogen synthase kinases (GSKs), and C dc2‐like kinases (CLKs)] group, sterile (STE)‐MAPKs group, tyrosine kinases (TK) group, tyrosine kinase‐like (TKL) group, atypical group, and other groups. Different groups and families of inhibitors stimulate or inhibit others, forming an intricate molecular signaling regulatory network. This review takes newly developed new PKIs as breakthrough point, aiming to clarify the regulatory network and relationship of each pathway, as well as their roles in disease intervention, and provide a direction for future drug development.

PURPOSE: The overall response of cisplatin-based chemotherapy in bladder urothelial carcinoma (BUC) remains unsatisfactory due to the complex pathological subtypes, genomic difference, and drug resistance. The genes that associated with cisplatin resistance remain unclear. Herein, we aimed to identify the cisplatin resistance associated genes in BUC. EXPERIMENTAL DESIGN: The cytotoxicity of cisplatin was evaluated in six bladder cancer cell lines to compare their responses to cisplatin. The T24 cancer cells exhibited the lowest sensitivity to cisplatin and was therefore selected to explore the mechanisms of drug resistance. We performed genome-wide CRISPR screening in T24 cancer cells in vitro, and identified that the gene heterogeneous nuclear ribonucleoprotein U (HNRNPU) was the top candidate gene related to cisplatin resistance. Epigenetic and transcriptional profiles of HNRNPU-depleted cells after cisplatin treatment were analyzed to investigate the relationship between HNRNPU and cisplatin resistance. In vivo experiments were also performed to demonstrate the function of HNRNPU depletion in cisplatin sensitivity. RESULTS: Significant correlation was found between HNRNPU expression level and sensitivity to cisplatin in bladder cancer cell lines. In the high HNRNPU expressing T24 cancer cells, knockout of HNRNPU inhibited cell proliferation, invasion, and migration. In addition, loss of HNRNPU promoted apoptosis and S-phase arrest in the T24 cells treated with cisplatin. Data from The Cancer Genome Atlas (TCGA) demonstrated that HNRNPU expression was significantly higher in tumor tissues than in normal tissues. High HNRNPU level was negatively correlated with patient survival. Transcriptomic profiling analysis showed that knockout of HNRNPU enhanced cisplatin sensitivity by regulating DNA damage repair genes. Furthermore, it was found that HNRNPU regulates chemosensitivity by affecting the expression of neurofibromin 1 (NF1). CONCLUSIONS: Our study demonstrated that HNRNPU expression is associated with cisplatin sensitivity in bladder urothelial carcinoma cells. Inhibition of HNRNPU could be a potential therapy for cisplatin-resistant bladder cancer.

Deciphering universal gene regulatory mechanisms in diverse organisms holds great potential for advancing our knowledge of fundamental life processes and facilitating clinical applications. However, the traditional research paradigm primarily focuses on individual model organisms and does not integrate various cell types across species. Recent breakthroughs in single-cell sequencing and deep learning techniques present an unprecedented opportunity to address this challenge. In this study, we built an extensive dataset of over 120 million human and mouse single-cell transcriptomes. After data preprocessing, we obtained 101,768,420 single-cell transcriptomes and developed a knowledge-informed cross-species foundation model, named GeneCompass. During pre-training, GeneCompass effectively integrated four types of prior biological knowledge to enhance our understanding of gene regulatory mechanisms in a self-supervised manner. By fine-tuning for multiple downstream tasks, GeneCompass outperformed state-of-the-art models in diverse applications for a single species and unlocked new realms of cross-species biological investigations. We also employed GeneCompass to search for key factors associated with cell fate transition and showed that the predicted candidate genes could successfully induce the differentiation of human embryonic stem cells into the gonadal fate. Overall, GeneCompass demonstrates the advantages of using artificial intelligence technology to decipher universal gene regulatory mechanisms and shows tremendous potential for accelerating the discovery of critical cell fate regulators and candidate drug targets.

The objectives of this trial were to study the growth and development of hair follicles and cashmere traits in cashmere goats and to provide a theoretical basis for the regulation of secondary hair follicle development and the scientific breeding selection of cashmere goats. Twelve single-fetal female kids were selected as research objects. A long-term tracking plan was created to regularly determine their growth performance, cashmere performance, and hair follicle traits. The results showed no significant difference in live weight after the first and second combing. The cashmere yield and unit yield of the first combing were significantly higher than those of the second combing (p < 0.05). Sections of hair follicles showed that the primary hair follicles are almost fully developed by 1 month, and the secondary hair follicles are fully developed by 5–6 months after birth. The primary hair follicle density (PFD) and secondary hair follicle density (SFD) were highest at birth and decreased within 1 month; and SFD was stable at 5–6 months of age. The change of MSFD took a maximum time of 2 to 3 months. The S:P increase reached its peak at 6 months. BMP4 expression increased with time. FGF2, FGF21 and BMP7 were higher at 3 months old than at the other two-time points. In conclusion, this study determined the total development time of primary and secondary hair follicles from morphology and speculated that FGF2, FGF21, and BMP7 may play a regulatory role in developing secondary hair follicles. Therefore, the period from birth to 6 months of age was the best time to regulate secondary hair follicle development in cashmere goats kids. The traits of the hair follicle and cashmere at 6 months of age could be breeding selection indicators for cashmere goats.