Widespread interest in artificial intelligence (AI) in health care has focused mainly on deductive systems that analyze available real-world data to discover patterns not otherwise visible. Generative adversarial network, a new type of inductive AI, has recently evolved to generate high-fidelity virtual synthetic data (SD) trained on relatively limited real-world information. The AI system is fed with a collection of real data, and it learns to generate new augmented data while maintaining the general characteristics of the original data set. The use of SD to enhance clinical research and protect patient privacy has drawn a lot of interest in medicine and in the complex field of oncology. This article summarizes the main characteristics of this innovative technology and critically discusses how it can be used to accelerate data access for secondary purposes, providing an overview of the opportunities and challenges of SD generation for clinical cancer research and health care.

Significant sex-based differences exist in the immune system and antitumor immune responses, potentially leading to variations in both the efficacy and toxicity of anticancer immunotherapies. Women generally mount stronger innate and adaptive immune responses than men, which can result in more severe immune-related adverse events (irAEs) during treatments with immune checkpoint inhibitors (ICIs). However, the importance of sex dimorphism in the safety of cancer immunotherapy remains underexplored in clinical oncology, despite its profound implications for treatment outcomes. Our review highlights the critical influence of biological sex on pharmacokinetics, pharmacodynamics, and immune responses, shaping ICI efficacy and the prevalence, type, and severity of irAEs. Integrating sex as a critical variable in cancer treatment and clinical trial design is essential for personalizing therapeutic strategies, bridging existing knowledge gaps, and enhancing survival rates and quality of life for patients across genders.

Background: Sentinel lymph node biopsy (SLNB) has emerged as the standard procedure to replace axillary lymph node dissection (ALND) in breast cancer (BC) patients undergoing neo-adjuvant chemotherapy (NAC). SLNB is accepted in clinically node-negative (cN0) patients; however, its role in clinically node-positive (cN+) patients is debatable. Methods: We performed a retrospective analysis of BC patients undergoing NAC and SLNB. Our aim was to evaluate the clinical significance of SLNB in the setting of NAC. This was accomplished by comparing the characteristics and oncological outcomes between cN0 and cN+ patients prior to NAC and type of axillary surgery. Results: A total of 291 patients were included in the analysis: 131 were cN0 and 160 were cN+ who became ycN0 after NAC. At a median follow-up of 43 months, axillary recurrence occurred in three cN0 (2.3%) and two cN+ (1.3%) patients. However, there were no statistically significant differences in oncological outcomes (disease-free survival, distant disease-free survival, overall survival, and breast-cancer-specific survival) between cN0 and cN+ patients nor between patients treated with SLNB only or ALND. Conclusions: SLNB in the setting of NAC is an acceptable procedure with a general good prognosis and low axillary failure rates for both cN0 and cN+ patients.

Background: Loco-regional therapy (LRT) in de novo metastatic breast cancer (MBC) has been investigated in several clinical trials, with heterogeneous and conflicting results. Methods: We conducted a retrospective study of de novo MBC patients treated with front-line chemotherapy (FLC) followed by LRT of the primary tumor. Our aims were to evaluate the characteristics, treatment, and oncological outcomes in terms of progression-free survival (PFS), distant progression-free survival (DPFS), and overall survival (OS) of de novo MBC. We also investigated possible subgroups of patients with better outcomes according to menopausal status, biological sub-type, location, number of metastases, and radiologic complete response after FLC. Results: We included 61 patients in the study. After a median follow-up of 55 months, disease progression occurred in 60.7% of patients and 49.2% died. There were no significant differences in PFS, DPFS, and OS between different subgroups of de novo MBC patients. A trend toward better PFS and DPFS was observed in triple-positive tumors, without a statistically significant difference in OS. Conclusions: No specific subgroup of de novo MBC patients showed a statistically significant survival advantage after FLC followed by LRT of the primary tumor.

Background: Breast cancer is traditionally classified into three clinical subtypes based on hormone receptor and HER2 status (i.e., luminal-like, HER2-positive, and triple negative). Each subtype has distinct clinical-pathological and molecular characteristics and requires tailored treatments. Recent research efforts have been focusing on a new classification, identifying the so-called “HER2-low” category, including tumors characterized by a low level of HER2 expression (immunohistochemistry score 1+ or 2+ without in situ hybridization amplification). Emerging evidence shows that patients with HER2-low tumors can derive benefit from selected anti-HER2 therapies. This represents a major advancement in the field of breast oncology, where a broader proportion of patients with breast cancer can ultimately benefit from new effective targeted treatment strategies. Summary: The antibody-drug conjugate trastuzumab deruxtecan has proven impressive efficacy in patients with HER2-low breast cancer, and several other drugs are currently under investigation in this subset of patients. Additional investigation is needed to address open issues that exist in this field, including appropriate pathological assessment of HER2-low status, clarification of its prognostic implications, and global access to newly approved drugs. Key Message: Our review aims to summarize the available evidence regarding HER2-low breast cancer, illustrating the current challenges that are being addressed and the future perspectives in this exciting new field.

Backgrounds: The majority of breast cancer (BC) patients treated with neo-adjuvant chemotherapy (NAC) achieves a pathologic partial response with different patterns of residual disease. No clear correlation between these patterns and oncological results was described. Our aims were to define the predictive factors for different patterns of residual disease and compare the outcomes between the scattered versus the circumscribed pattern. Methods: We reviewed 219 postoperative surgical specimens. Patients were divided into two groups: scattered versus circumscribed. Disease-free survival (DFS), distant DFS (DDFS), and overall survival (OS) were analyzed. Results: The scattered and circumscribed patterns were assessed in 111 (50.7%) and 108 (49.3%) patients. Two independent predictive factors for the circumscribed pattern were identified: discontinuation of NAC cycles (p = 0.011), and tumor size post-NAC >18 mm (p = 0.022). No difference was observed in terms of DFS and DDFS. Patients with the scattered pattern exhibited a statistically significant better OS. Discontinuation of NAC cycles, tumor size >18 mm, triple-negative BC, and ypN+ were associated with increased recurrence and poorer survival. Conclusions: Discontinuation of NAC cycles and tumor size are independent factors associated with patterns of residual disease. The scattered pattern presents better survival. Understanding the relationship between NAC, the residual pattern, and differences in survival outcomes offers the potential to optimize the therapeutic approaches.