Over 17 and 160 types of chemical modifications have been identified in DNA and RNA, respectively. The interest in understanding the various biological functions of DNA and RNA modifications has lead to the cutting-edged fields of epigenomics and epitranscriptomics. Developing chemical and biological tools to detect specific modifications in the genome or transcriptome has greatly facilitated their study. Here, we review the recent technological advances in this rapidly evolving field. We focus on high-throughput detection methods and biological findings for these modifications, and discuss questions to be addressed as well. We also summarize third-generation sequencing methods, which enable long-read and single-molecule sequencing of DNA and RNA modification.

The gut microbiota plays a critical role in the progression of human diseases, especially cancer. In recent decades, there has been accumulating evidence of the connections between the gut microbiota and cancer immunotherapy. Therefore, understanding the functional role of the gut microbiota in regulating immune responses to cancer immunotherapy is crucial for developing precision medicine. In this review, we extract insights from state-of-the-art research to decipher the complicated crosstalk among the gut microbiota, the systemic immune system, and immunotherapy in the context of cancer. Additionally, as the gut microbiota can account for immune-related adverse events, we discuss potential interventions to minimize these adverse effects and discuss the clinical application of five microbiota-targeted strategies that precisely increase the efficacy of cancer immunotherapy. Finally, as the gut microbiota holds promising potential as a target for precision cancer immunotherapeutics, we summarize current challenges and provide a general outlook on future directions in this field.

Artificial intelligence has made significant contributions to oncology through the availability of high-dimensional datasets and advances in computing and deep learning. Cancer precision medicine aims to optimize therapeutic outcomes and reduce side effects for individual cancer patients. However, a comprehensive review describing the impact of artificial intelligence on cancer precision medicine is lacking. By collecting and integrating large volumes of data and applying it to clinical tasks across various algorithms and models, artificial intelligence plays a significant role in cancer precision medicine. Here, we describe the general principles of artificial intelligence, including machine learning and deep learning. We further summarize the latest developments in artificial intelligence applications in cancer precision medicine. In tumor precision treatment, artificial intelligence plays a crucial role in individualizing both conventional and emerging therapies. In specific fields, including target prediction, targeted drug generation, immunotherapy response prediction, neoantigen prediction, and identification of long non-coding RNA, artificial intelligence offers promising perspectives. Finally, we outline the current challenges and ethical issues in the field. Recent clinical studies demonstrate that artificial intelligence is involved in cancer precision medicine and has the potential to benefit cancer healthcare, particularly by optimizing conventional therapies, emerging targeted therapies, and individual immunotherapies. This review aims to provide valuable resources to clinicians and researchers and encourage further investigation in this field.

The transcription factor family activator protein 2 (TFAP2) is vital for regulating both embryonic and oncogenic development. The TFAP2 family consists of five DNA-binding proteins, including TFAP2A, TFAP2B, TFAP2C, TFAP2D and TFAP2E. The importance of TFAP2 in tumor biology is becoming more widely recognized. While TFAP2D is not well studied, here, we mainly focus on the other four TFAP2 members. As a transcription factor, TFAP2 regulates the downstream targets directly by binding to their regulatory region. In addition, the regulation of downstream targets by epigenetic modification, posttranslational regulation, and interaction with noncoding RNA have also been identified. According to the pathways in which the downstream targets are involved in, the regulatory effects of TFAP2 on tumorigenesis are generally summarized as follows: stemness and EMT, interaction between TFAP2 and tumor microenvironment, cell cycle and DNA damage repair, ER- and ERBB2-related signaling pathway, ferroptosis and therapeutic response. Moreover, the factors that affect TFAP2 expression in oncogenesis are also summarized. Here, we review and discuss the most recent studies on TFAP2 and its effects on carcinogenesis and regulatory mechanisms.

Digital Health Technologies (DHTs) have become a cornerstone of modern healthcare, significantly improving quality and safety across clinical practice, public health, and medical research. Originating in the mid-to-late 20th century, DHTs have facilitated substantial progress in personalized medicine, predictive analytics, and remote patient monitoring through the implementation of artificial intelligence (AI), wearable devices, and telemedicine platforms. During the Coronavirus Disease 2019 (COVID-19) pandemic, these technologies proved indispensable for epidemic surveillance and precision containment, while also mitigating healthcare access disruptions. Nevertheless, critical challenges including the digital ethics and equity, technical and regulatory policy restrictions, privacy and data security concerns, and clinical workflow integration issues remain to be addressed. This narrative review explores the transformative role of DHTs throughout the disease management continuum—from prevention to prognosis—and evaluates their contributions to healthcare quality and safety. It also provides strategies for stakeholders to address existing barriers. By overcoming these challenges, DHTs can further elevate healthcare standards, fostering a safer and more efficient global healthcare system.

Cancer immunotherapy enhances the prognosis of cancer patients; however, it has been shown to be associated with potentially fatal cardiac risks, which requires further confirmation. This study aimed to explore the cardiotoxicity of immune checkpoint inhibitors (ICIs) in solid tumors. A systematic review and meta-analysis was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and registered in the PROSPERO database, CRD42024614721. All randomized controlled trials (RCTs) comparing ICI with placebo and reporting complete adverse events in solid tumors were included. The primary outcome is the relative risk (RR) of cardiotoxicity for the purpose of discerning the disparities between the two groups. Data were pooled using random-effects model. A total of 101 RCTs involving 58,698 patients were included. The incidence of all-grade cardiotoxicity was 3.0% in the ICI group and 2.3% in the placebo group. The pooled relative risk for cardiotoxicity was higher with ICI compared with placebo (RR = 1.31, 95% CI = 1.17–1.48, P<0.001). Regarding individual cardiac adverse event, the pooled relative risks for myocarditis (RR = 1.79, 95%CI = 1.11–2.91, p = 0.018) and arrhythmia (RR = 1.22, 95%CI = 1.04–1.44, p = 0.016) were also higher with ICI compared with placebo. Sensitivity analysis demonstrated consistency in the overall estimate. Our study illustrated an increased cardiotoxicity of the use of ICI as single or combination regimens including myocarditis and arrhythmia based on a large number of the latest RCTs. More cautious attention should be paid on the ICIs-induced cardiotoxicities during cancer immunotherapy, especially for myocarditis and arrhythmia.