None.
None.
Cao Yang
Department of Orthopaedics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology
Li G, Luo R, Zhang W, et al. m6A hypomethylation of DNMT3B regulated by ALKBH5 promotes intervertebral disc degeneration via E4F1 deficiency. Clinical and Translational Medicine. 2022;12.
In this article, the image in the upper panel of ALKBH5 in Figure 1I was misused. The updated Figure 1 is provided.
FIGURE 1 Original version
FIGURE 1 New version
We apologize for this error.
Despite guideline-directed therapies, most patients with advanced oesophageal squamous cell carcinoma (ESCC) derive limited benefit and are unable to tolerate iterative treatment modifications. Therefore, timely identification of resistant cases and the provision of alternative therapeutic options are urgently needed.
A large-scale patient-derived organoid model was established from locally advanced patients with ESCC who underwent perioperative chemotherapy and was validated for consistency with the parental tumours through histopathological, genomic and transcriptomic analysis. A novel two-step drug screening method based on growth rate inhibition (GR) was developed, and drug sensitivity results were compared with clinical outcomes. Additionally, in vivo assays were conducted to evaluate alternative therapies using the Cmax/GR100 index.
ESCC organoids demonstrated high consistency with parental tumours in histopathology, genomics and transcriptomics. The two-step drug screening method revealed a strong correlation with clinical responses (sensitivity 80%, specificity 85.7%, overall accuracy 83.3%) and significantly shortened the experimental timeline compared with the traditional drug screening method (23.08 ± 2.42 days vs. 45.75 ± 7.19 days, p < .001). Furthermore, we proposed a novel drug selection strategy based on Cmax/GR100 values, which provides a theoretical foundation for drug repurposing and offers alternative treatment options for patients resistant to TP (taxol + cisplatin) therapy, thereby facilitating precise re-treatment in drug-resistant subgroups.
This method exhibits strong clinical applicability, supporting more accurate and timely decision-making in ESCC management. The Cmax/GR100-based drug screening strategy can dynamically identify alternative sensitive drugs for patients who fail first-line therapies, enabling precise re-treatment. This approach provides a valuable tool for translating laboratory findings into clinical practice.
RNA methylation has emerged as a pivotal layer of post-transcriptional regulation that shapes the biological behavior of cancer cells. Among the diverse chemical modifications identified—such as N6-methyladenosine (m6A), N1-methyladenosine (m1A), 5-methylcytosine (m5C), 7-methylguanosine (m7G), 5-hydroxymethylcytosine (5hmC), and 2′-O-dimethyladenosine (m6Am)—the m7G modification has recently garnered increasing attention. Mounting evidence indicates that m7G methylation plays an essential role in RNA metabolism and profoundly influences cancer initiation and progression.
This Review synthesizes current advances in understanding the biological and clinical implications of m7G RNA methylation, with a particular focus on its key regulatory components, METTL1/WDR4 and eIF4E. We discuss how these enzymes and binding proteins orchestrate m7G deposition and recognition to modulate oncogenic processes, including cell growth, differentiation, metastasis, and therapeutic resistance. Furthermore, we highlight emerging evidence linking m7G-related pathways to broader signaling networks that govern cancer plasticity and tumor microenvironment remodeling.
m7G RNA methylation represents a rapidly evolving frontier in cancer epigenetics. The METTL1/WDR4 methyltransferase complex and eIF4E translation initiation factor have emerged as central nodes connecting RNA modification to oncogenic signaling. Targeting m7G-dependent pathways holds considerable promise for the development of novel diagnostic biomarkers and therapeutic strategies. Continued exploration of this modification may ultimately expand the landscape of RNA-based precision oncology.
[Chu Q, Fang N, Chen H, et al. Immune cell subset profiling and metabolic dysregulation define the divergent immune microenvironments in HIV immunological non-responders. Clin Transl Med. 2025;15(10):e70498. doi:10.1002/ctm2.70498]
[1. Adjustment of institutional affiliation order
We noticed that the order of institutional affiliations in the published version differs from our original submission. For consistency and accuracy, we kindly request that the following order be restored:
‘’Immune cell subset profiling and metabolic dysregulation define the divergent immune microenvironments in HIV immunological non-responders
Qingfei Chu1,2,3†, Ningye Fang4†, Huanhuan Chen4, Abdur Rashid5,6, Xia Luo1, Jianjun Li4*, Kang Li1,2,5*
1 Department of Microbiology, School of Basic Medicine, Guangxi Medical University, Nanning, Guangxi, China.
2 Guangxi Key Laboratory of AIDS Prevention and Treatment, School of Public Health, Guangxi Medical University, Nanning, 530021, China
3 Department of Infectious Diseases, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310009, China
4 Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, Nanning, China
5 National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing, China
6 Division of Infectious Disease & International Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL 33612, USA
† These authors contributed equally to this work.
Corresponding authors:
E-mail: [email protected] (J. Li); [email protected] (K. Li).]
2. Correction to the Author Contributions section
During the proofing process, an oversight occurred regarding the Author Contributions statement. We sincerely apologize for this error. The corrected version should read as follows:
“Kang Li, Jianjun Li and Qingfei Chu conceived and designed the research. Qingfei Chu, Ningye Fang and Huanhuan Chen performed experiments. Abdur Rashid and Xia Luo assisted with the statistical analyses. Qingfei Chu and Ningye Fang wrote the first draft of the article. Qingfei Chu, Ningye Fang, Huanhuan Chen, Abdur Rashid, Xia Luo, Jianjun Li and Kang Li reviewed and edited the manuscript. All authors have read and agreed to the final version of the manuscript.”
We apologize for this error.
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