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2025 Tianjin International Breast Cancer Conference |Professor Zhang Juliang: Skip the “Grand Narrative”—Even Small Questions Can Lead to Big Papers! Expert Advice on How Early- and Mid-Career Doctors Can Break Through With IITs
From “following evidence” to “creating evidence”, clinical research in breast cancer in China is entering a deep phase of high-quality development. Within the grand framework of precision medicine, industry-sponsored trials (ISTs) may serve as the gateway for innovative drugs to enter clinical practice, but investigator-initiated trials (IITs) are the master key to solving the “last…
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SABCS Expert Commentary | Professor Jin Feng: Reanalysis of the Landmark NSABP B-20 Trial—Can MMAI Become a Low-Cost Option for Risk Stratification?
At the 2025 San Antonio Breast Cancer Symposium (SABCS 2025), a reanalysis of the landmark NSABP B-20 trial (Abstract No. RF3-03) was presented, exploring the prognostic value and chemotherapy benefit–predictive potential of a multimodal artificial intelligence (MMAI) model based on digital pathology and clinical data in hormone receptor–positive (HR+), node-negative early breast cancer.
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SABCS Expert Commentary |Professor Jin Feng: Deep Learning Accurately Predicts Late Distant Metastasis in HR-Positive Early Breast Cancer and Guides Decisions on Extended Endocrine Therapy
At the 2025 San Antonio Breast Cancer Symposium (SABCS 2025), a study based on data from the NSABP B-42 and TAILORx trials (Abstract No. RF3-07) reported the development and validation of a multimodal, multitask deep learning model (Clarity BCR). By integrating routine digital pathology images with key clinical variables, this model accurately predicts the risk…
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SABCS Expert Commentary |Professor Jin Feng: New Evidence for Precision Immunotherapy in Early Triple-Negative Breast Cancer—Gene Expression Subtyping Predicts Response to Neoadjuvant Immunochemotherapy
At the 2025 San Antonio Breast Cancer Symposium (SABCS 2025), a study titled “Gene Expression-based Subtyping of Early Triple-Negative Breast Cancer for Prediction of Response to Neoadjuvant Immune-chemotherapy in the NSABP B-59/GBG-96-GeparDouze Trial” (Abstract No. RF3-02) was presented. The study provides an in-depth analysis of the heterogeneity of benefit from immunotherapy in early triple-negative breast…
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SABCS Expert Commentary | Professor Mao Xiaoyun: The ALTTO Study Confirms Superior DFS With Aromatase Inhibitors Over SERMs, Providing New Evidence for Endocrine Therapy in HR+/HER2+ Breast Cancer
In patients with HR-positive/HER2-positive early breast cancer, adjuvant anti-HER2 therapy constitutes the cornerstone of systemic treatment. However, robust high-level evidence has long been lacking to guide the choice between aromatase inhibitors (AIs) and tamoxifen (SERMs) for adjuvant endocrine therapy in this population.
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SABCS Expert Commentary | Professor Wang Xin: ctDNA Clearance Predicts pCR in HER2-Positive Breast Cancer and Supports Precision De-escalation Strategies
De-escalation therapy has become an important trend in the management of HER2-positive early breast cancer, yet accurately identifying patients who can safely omit chemotherapy remains a major challenge. At the 2025 San Antonio Breast Cancer Symposium (SABCS), the PHERGuide substudy innovatively incorporated circulating tumor DNA (ctDNA) monitoring into the neoadjuvant treatment framework. The study demonstrated…
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Professor Andrea Necchi: Precision Patient Selection and Recurrence Control—Key Challenges on the Bladder-Sparing Pathway
| 15th Shanghai Urologic Oncology Academic ConferencePlay Editor’s Note: With the continuous evolution of treatment concepts and the advancement of therapeutic strategies, the management landscape of muscle-invasive bladder cancer (MIBC)…
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Efficient Androgen Receptor Blockade, Survival Benefit, and Precision Stratification in Clinical Practice
| The 15th Shanghai Urologic Oncology Academic Conference Editor’s Note: The 15th Shanghai Urologic Oncology Academic Conference was held in Pudong, Shanghai, bringing together leading experts in urologic oncology from…
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