Lung cancer is the leading cause of cancer-related mortality worldwide, and its tumorigenesis involves the accumulation of genetic and epigenetic events in the respiratory epithelium. Epigenetic modifications, such as DNA methylation, RNA modification, and histone modifications, have been widely reported to play an important role in lung cancer development and in other pulmonary diseases. Whereas the functionality of DNA and chromatin modifications referred to as epigenetics is widely characterized, various modifications of RNA nucleotides have recently come into prominence as functionally important. N6-methyladosine (m6A) is the most prevalent internal modification in mRNAs, and its machinery of writers, erasers, and readers is well-characterized. However, several other nucleotide modifications of mRNAs and various noncoding RNAs have also been shown to play an important role in the regulation of biological processes and pathology. Such epitranscriptomic modifications play an important role in regulating various aspects of RNA metabolism, including transcription, translation, splicing, and stability. The dysregulation of epitranscriptomic machinery has been implicated in the pathological processes associated with carcinogenesis including uncontrolled cell proliferation, migration, invasion, and epithelial-mesenchymal transition. In recent years, with the advancement of RNA sequencing technology, high-resolution maps of different modifications in various tissues, organs, or disease models are being constantly reported at a dramatic speed. This facilitates further understanding of the relationship between disease development and epitranscriptomics, shedding light on new therapeutic possibilities. In this review, we summarize the basic information on RNA modifications, including m6A, m1A, m5C, m7G, pseudouridine, and A-to-I editing. We then demonstrate their relation to different kinds of lung diseases, especially lung cancer. By comparing the different roles RNA modifications play in the development processes of different diseases, this review may provide some new insights and offer a better understanding of RNA epigenetics and its involvement in pulmonary diseases.

The efficient and safe delivery of therapeutic drugs, proteins, and nucleic acids are essential for meaningful therapeutic benefits. The field of nanomedicine shows promising implications in the development of therapeutics by delivering diagnostic and therapeutic compounds. Nanomedicine development has led to significant advances in the design and engineering of nanocarrier systems with supra-molecular structures. Smart mesoporous silica nanoparticles (MSNs), with excellent biocompatibility, tunable physicochemical properties, and site-specific functionalization, offer efficient and high loading capacity as well as robust and targeted delivery of a variety of payloads in a controlled fashion. Such unique nanocarriers should have great potential for challenging biomedical applications, such as tissue engineering, bioimaging techniques, stem cell research, and cancer therapies. However, in vivo applications of these nanocarriers should be further validated before clinical translation. To this end, this review begins with a brief introduction of MSNs properties, targeted drug delivery, and controlled release with a particular emphasis on their most recent diagnostic and therapeutic applications.

Induced pluripotent stem cells (iPSCs) can be differentiated into mesenchymal stem cells (iPSC-MSCs), retinal ganglion cells (iPSC-RGCs), and retinal pigmental epithelium cells (iPSC-RPEs) to meet the demand of regeneration medicine. Since the production of iPSCs and iPSC-derived cell lineages generally requires massive and time-consuming laboratory work, artificial intelligence (AI)-assisted approach that can facilitate the cell classification and recognize the cell differentiation degree is of critical demand. In this study, we propose the multi-slice tensor model, a modified convolutional neural network (CNN) designed to classify iPSC-derived cells and evaluate the differentiation efficiency of iPSC-RPEs. We removed the fully connected layers and projected the features using principle component analysis (PCA), and subsequently classified iPSC-RPEs according to various differentiation degree. With the assistance of the support vector machine (SVM), this model further showed capabilities to classify iPSCs, iPSC-MSCs, iPSC-RPEs, and iPSC-RGCs with an accuracy of 97.8%. In addition, the proposed model accurately recognized the differentiation of iPSC-RPEs and showed the potential to identify the candidate cells with ideal features and simultaneously exclude cells with immature/abnormal phenotypes. This rapid screening/classification system may facilitate the translation of iPSC-based technologies into clinical uses, such as cell transplantation therapy.

Neuromuscular diseases (NMDs) belong to a class of functional impairments that cause dysfunctions of the motor neuron-muscle functional axis components. Inherited monogenic neuromuscular disorders encompass both muscular dystrophies and motor neuron diseases. Understanding of their causative genetic defects and pathological genetic mechanisms has led to the unprecedented clinical translation of genetic therapies. Challenged by a broad range of gene defect types, researchers have developed different approaches to tackle mutations by hijacking the cellular gene expression machinery to minimize the mutational damage and produce the functional target proteins. Such manipulations may be directed to any point of the gene expression axis, such as classical gene augmentation, modulating premature termination codon ribosomal bypass, splicing modification of pre-mRNA, etc. With the soar of the CRISPR-based gene editing systems, researchers now gravitate toward genome surgery in tackling NMDs by directly correcting the mutational defects at the genome level and expanding the scope of targetable NMDs. In this article, we will review the current development of gene therapy and focus on NMDs that are available in published reports, including Duchenne Muscular Dystrophy (DMD), Becker muscular dystrophy (BMD), X-linked myotubular myopathy (XLMTM), Spinal Muscular Atrophy (SMA), and Limb-girdle muscular dystrophy Type 2C (LGMD2C).

Human pluripotent stem cells (PSCs), including both embryonic stem cells (ESCs) and induced pluripotent stem cells (iPSCs), represent valuable cell sources to replace diseased or injured tissues in regenerative medicine. iPSCs exhibit the potential for indefinite self-renewal and differentiation into various cell types and can be reprogrammed from somatic tissue that can be easily obtained, paving the way for cell therapy, regenerative medicine, and personalized medicine. Cell therapies using various iPSC-derived cell types are now evolving rapidly for the treatment of clinical diseases, including Parkinson’s disease, hematological diseases, cardiomyopathy, osteoarthritis, and retinal diseases. Since the first interventional clinical trial with autologous iPSC-derived retinal pigment epithelial cells (RPEs) for the treatment of age-related macular degeneration (AMD) was accomplished in Japan, several preclinical trials using iPSC suspensions or monolayers have been launched, or are ongoing or completed. The evolution and generation of human leukocyte antigen (HLA)-universal iPSCs may facilitate the clinical application of iPSC-based therapies. Thus, iPSCs hold great promise in the treatment of multiple retinal diseases. The efficacy and adverse effects of iPSC-based retinal therapies should be carefully assessed in ongoing and further clinical trials.

Glaucoma is a progressive and irreversible blindness-causing disease. However, the underlying genetic factors and molecular mechanisms remain poorly understood. Previous genome-wide association studies (GWAS) have made tremendous progress on the SNP-based disease association and characterization. However, most of them were conducted for Europeans. Since differential genetic characteristics among ethnic groups were evident in glaucoma, it is worthwhile to complete its genetic landscape from the larger cohorts of Asian individuals. Here, we present a GWAS based on the Taiwan Biobank. Among 1013 glaucoma patients and 36,562 controls, we identified a total of 138 independent glaucoma-associated SNPs at the significance level of p < 1 × 10−5. After clumping genetically linked SNPs (LD clumping), 134 independent SNPs with p < 10−4 were recruited to construct a Polygenic Risk Score (PRS). The model achieved an area under the receiver operating characteristic curve (AUC) of 0.8387 (95% CI = [0.8269–0.8506]), and those within the top PRS quantile had a 45.48-fold increased risk of glaucoma compared with those within the lowest quantile. The PRS model was validated with an independent cohort that achieved an AUC of 0.7283, thereby showing the effectiveness of our polygenic risk score in predicting individuals in the Han Chinese population with higher glaucoma risks.