Clinical and Translational Medicine最新文献

Solid tumours exhibit a well-defined architecture, comprising a differentiated core and a dynamic border that interfaces with the surrounding tissue. This border, characterised by distinct cellular morphology and molecular composition, serves as a critical determinant of the tumour's invasive behaviour. Notably, the invasive border of the primary tumour represents the principal site for intravasation of metastatic cells. These cells, known as circulating tumour cells (CTCs), function as ‘seeds’ for distant dissemination and display remarkable heterogeneity. Advancements in spatial sequencing technology are progressively unveiling the spatial biological features of tumours. However, systematic investigations specifically targeting the characteristics of the tumour border remain scarce. In this comprehensive review, we illuminate key biological insights along the tumour body-border-haematogenous metastasis axis over the past five years. We delineate the distinctive landscape of tumour invasion boundaries and delve into the intricate heterogeneity and phenotype of CTCs, which orchestrate haematogenous metastasis. These insights have the potential to explain the basis of tumour invasion and distant metastasis, offering new perspectives for the development of more complex and precise clinical interventions and treatments.

In this article, we have just realized the wrong usage of flow cytometry chart in the FAK siRNA group in Figure S7B of Supplementary Material.

The wrong Figure S7 is as follows.

The corrected Figure S7 is as follows.

RETRACTION: P. Xu, X. Zhang, J. Cao, J. Yang, Z. Chen, W. Wang, S. Wang, L. Zhang, L. Xie, L. Fang, Y. Xia, Z. Xuan, J. Lv, H. Xu, and Z. Xu, “The Novel Role of Circular RNA ST3GAL6 on Blocking Gastric Cancer Malignant Behaviours Through Autophagy Regulated by the FOXP2/MET/Mtor Axis,” Clinical and Translational Medicine 12, no.1 (2022): e707, https://doi.org/10.1002/ctm2.707.

The above article, published online on 21 January 2022 in Wiley Online Library (wileyonlinelibrary.com), has been retracted by agreement between the journal Editor-in-Chief, Xiangdong Wang; the Shanghai Institute of Clinical Bioinformatics; and John Wiley & Sons Australia, Ltd. The retraction has been agreed upon following an investigation into concerns raised by a third party, which revealed inappropriate duplications of image panels within the article (Figures 6H and 7J) and between this article (Figures 2D, 7B, 7K, 8E and 8J) and another article previously published elsewhere by an overlapping group of authors in a different scientific context. The authors were unable to provide a satisfactory explanation and the raw data they supplied could not explain the identified issues. In addition, the cell line SGC-7901 used in this study has been reported as contaminated with HeLa cells, making it a problematic model for gastric cancer [1,2]. Given the extent of the identified issues, the editors have lost confidence in the data presented and the article's conclusions can no longer be considered reliable.

References

[1] F. Ye, C. Chen, J. Qin, J. Liu, and C. Zheng, “Genetic Profiling Reveals an Alarming Rate of Cross-Contamination Among Human Cell Lines Used in China,” The FASEB Journal 29, no. 10 (2015):4268–4272, https://doi.org/10.1096/fj.14-266718.

[2] X. Bian, Z. Yang, H. Feng, H. Sun, and Y. Liu, “A Combination of Species Identification and STR Profiling Identifies Cross-contaminated Cells from 482 Human Tumor Cell Lines,” Scientific Reports 7, no. 1 (2017):9774, https://doi.org/10.1038/s41598-017-09660-w.

With rapid development and mature of single-cell measurements, single-cell biology and pathology become an emerging discipline to understand the disease. However, it is important to address concerns raised by clinicians as to how to apply single-cell measurements for clinical practice, translate the signals of single-cell systems biology into determination of clinical phenotype, and predict patient response to therapies. The present Perspective proposes a new system coined as the clinical artificial intelligent single-cell (caiSC) with the dynamic generator of clinical single-cell informatics, artificial intelligent analyzers, molecular multimodal reference boxes, clinical inputs and outs, and AI-based computerization. This system provides reliable and rapid information for impacting clinical diagnoses, monitoring, and prediction of the disease at the single-cell level. The caiSC represents an important step and milestone to translate the single-cell measurement into clinical application, assist clinicians’ decision-making, and improve the quality of medical services. There is increasing evidence to support the possibility of the caiSC proposal, since the corresponding biotechnologies associated with caiSCs are rapidly developed. Therefore, we call the special attention and efforts from various scientists and clinicians on the caiSCs and believe that the appearance of the caiSCs can shed light on the future of clinical molecular medicine.