Special Interview with Dr. Yunxiang Zhou, Editorial Board Member of Clinical and Experimental Obstetrics & Gynecology: Insights into Precision Breast Cancer Diagnosis and Treatment, Translational Research, and Journal Development
15 May 2026
Dr. Yunxiang Zhou is an attending physician in the Department of Breast Surgery at the Second Affiliated Hospital of the Zhejiang University School of Medicine. He also serves as an Editorial Board member of Clinical and Experimental Obstetrics & Gynecology (CEOG) and other journals, as well as a reviewer for over 80 SCI-indexed journals. Recently, we had the privilege of inviting Dr. Zhou for an in-depth conversation covering his academic journey, the notable findings of the DANCER trial, the role of artificial intelligence in breast cancer, and his perspectives on the development of CEOG.
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Yunxiang Zhou, MD Department of Breast Surgery and Oncology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China Interests: breast cancer; surgical oncology; liquid biopsy; precision therapy; CDK4/6 inhibitor |
1. Could you please briefly introduce your academic background, your main research interests, and the key areas you are currently focusing on in both clinical practice and scientific research?
I received my undergraduate, master's, and MD degrees from Zhejiang University, where I was mentored by Professor Yiding Chen and Professor Yongchuan Deng. Since 2020, my work has focused on both clinical and basic research in breast cancer. My main interests include liquid biopsy, precision neoadjuvant treatment strategies, and the mechanisms of resistance to CDK4/6 inhibitors. I am also actively involved in several clinical trials as a sub-investigator, including the TAYLOR trial series.
2. You have received systematic training in oncology, and your recent research has progressively focused on breast cancer and precision therapy, among other interests. Could you share with us what led you to choose this particular research focus?
As we all know, breast cancer is a highly heterogeneous disease. It includes several major subtypes such as HER2-positive, HR-positive/HER2-negative, and triple-negative breast cancer. Even within the same subtype, there are further molecular subgroups with distinct biological features. Because of this complexity, patients can respond very differently to the same treatment. Although we have seen major progress in breast cancer therapy over the past decades, there is still a large unmet need for more precise and individualized treatment strategies. This is what motivated me to focus on this field.
3. We note that you are not only active in clinical and research work but also serve as a reviewer and guest editor for several journals. How do you balance clinical duties, research, and academic service? How has this multi-role experience deepened your understanding of translational research from “bench to bedside”?
To be honest, it is very difficult to truly balance these roles. It often comes with personal sacrifice. I have to give up a lot of time with my family, and I would like to take this opportunity to express both my gratitude and my apology to them. At the same time, I see academic service, such as reviewing and editorial work, as a valuable part of my development. It allows me to stay updated on emerging research topics and understand what journals are really looking for. This also helps me think more critically about how to design meaningful studies and how to translate research findings into clinical practice.
4. You have done extensive work on biomarkers in breast cancer, particularly on liquid biopsy markers such as ctDNA. In your view, which type or combination of biomarkers holds the greatest potential for rapid translation and application in future clinical practice? What are the main challenges in validating and implementing them?
In my view, ctDNA has the greatest potential for rapid clinical translation. One major challenge is sensitivity. Previous studies have shown that ctDNA detection rates are relatively low in early-stage breast cancer, especially in HR-positive/HER2-negative disease. However, in our own cohort of 99 patients with this subtype, we achieved a baseline ctDNA detection rate of 62.8%. Importantly, ctDNA in our study not only reflected tumor burden but also showed predictive value for treatment response. These data are very encouraging, and we expect to publish the full results soon. Looking forward, I think there are two key challenges: one is to further improve sensitivity, and the other is to reduce the cost to make this approach more accessible in routine clinical practice.
5. From your perspective, what are the major challenges or unresolved questions currently facing the field of precision diagnosis and treatment in breast cancer?
From where I stand, first, we still lack stable and reliable predictive biomarkers across different subtypes. Second, response-guided treatment strategies remain an important but unresolved area. This means adjusting subsequent treatment based on how a patient responds early during therapy. It is now a major focus in clinical trial design.
6. In recent years, the impact of AI development on medical diagnosis and treatment has drawn significant attention. In the field of breast cancer, what role do you believe AI will play in the next 5 to 10 years across different stages—such as screening and diagnosis, predicting treatment response, and treatment selection—and what do you see as the major challenges it faces?
AI has been most actively studied in cancer screening, and some tools have already been used in real-world settings. But for treatment response prediction, I think AI is still mainly at an exploratory and supportive stage. We need larger, well-designed cohorts to develop more robust and reliable prediction models. Moreover, building an AI model from cohort data and translating it into clinical practice requires substantial computational resources, manpower, and long-term maintenance, which can be costly. In addition, treatment response depends on many complex factors, making it difficult for AI models to achieve stable and generalizable performance. So overall, while AI has great potential, especially in cancer screening, its application in treatment decision-making will likely take more time before it can be widely adopted in routine clinical practice.
7. How did you first learn about Clinical and Experimental Obstetrics & Gynecology (CEOG), and what motivated you to join its Editorial Board? As an Editorial Board Member, what do you consider to be the future development direction or strategic positioning of the CEOG journal?
I was invited to join the Editorial Board of CEOG, and I am truly grateful for that honor. I really believe this journal has a bright future. The team includes senior experts who provide stability and guidance, and younger researchers who bring energy and fresh ideas. I believe that, with the support of IMR Press, CEOG has the potential to further enhance its academic impact and attract greater attention in the field of obstetrics and gynecology.
8. As an accomplished young researcher, what specific advice would you offer to early-career scholars who aspire to build a successful research career?
In my view, two things matter. First, choose the right mentor. A strong and supportive team already places you halfway to success. Second, know your own strengths—whether you are more suited for clinical or basic research—then make full use of your strengths and all your resources to achieve your goals.
9. As an Editorial Board Member, which aspects do you prioritize most when evaluating manuscripts?
I believe all aspects of a manuscript are important. But our first impressions come from the cover letter, title, abstract, and figures. They should clearly show the novelty, workload, and significance of the study.
10. During your work on the editorial board, what do you feel the journal's editorial office does well in supporting the editorial board's decision-making and communication efficiency? What aspects could be further improved?
A unique thing about IMR Press is that your China office is in Hangzhou, the city where I live. That makes everything—online or in person—very easy. Overall, the editorial office is very supportive in communication and decision-making. If I may suggest, perhaps one day I could be invited to the annual meeting. That would make me feel even more like part of the family.
Dr. Zhou’s insights in this interview highlighted the ongoing advances and challenges in precision breast cancer therapy, translational medicine, and the clinical application of AI. His reflections also demonstrated the important role young clinician-scientists play in bridging scientific innovation and patient care.
We sincerely thank Dr. Yunxiang Zhou for accepting this interview with Clinical and Experimental Obstetrics & Gynecology (CEOG). CEOG will continue to promote high-quality academic exchange in obstetrics, gynecology, and related interdisciplinary fields, while providing an open and international platform for researchers and clinicians worldwide.
Journal Homepage: Clinical and Experimental Obstetrics & Gynecology