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Mathematical models based on partial differential equations (PDEs) can be exploited to handle clinical data with space/time dimensions, e.g. tumor growth challenged by neoadjuvant therapy. A model based on simplified assessment of tumor malignancy and pharmacodynamics efficiency was exercised to discover new metrics of patient prognosis in the OLTRE trial. We tested in a 17-patients cohort affected by early-stage triple negative breast cancer (TNBC) treated with 3 weeks of olaparib, the capability of a PDEs-based reactive–diffusive model of tumor growth to efficiently predict the response to olaparib in terms of SUV max detected at 18 FDG-PET/CT scan, by using specific terms to characterize tumor diffusion and proliferation. Computations were performed with COMSOL Multiphysics. Driving parameters governing the mathematical model were selected with Pearson's correlations. Discrepancies between actual and computed SUV max values were assessed with Student’s t test and Wilcoxon rank sum test. The correlation between post-olaparib true and computed SUV max was assessed with Pearson’s r and Spearman’s rho. After defining the proper mathematical assumptions, the nominal drug efficiency (ε PD ) and tumor malignancy ( r c ) were computationally evaluated. The former parameter reflected the activity of olaparib on the tumor, while the latter represented the growth rate of metabolic activity as detected by SUV max . ε PD was found to be directly dependent on basal tumor-infiltrating lymphocytes (TILs) and Ki67% and was detectable through proper linear regression functions according to TILs values, while r c was represented by the baseline Ki67-to-TILs ratio. Predicted post-olaparib SUV* max did not significantly differ from original post-olaparib SUV max in the overall, gBRCA-mutant and gBRCA-wild-type subpopulations ( p  > 0.05 in all cases), showing strong positive correlation (r = 0.9 and rho = 0.9, p  < 0.0001 both). A model of simplified tumor dynamics was exercised to effectively produce an upfront prediction of efficacy of 3-week neoadjuvant olaparib in terms of SUV max . Prospective evaluation in independent cohorts and correlation of these outcomes with more recognized efficacy endpoints is now warranted for model confirmation and tailoring of escalated/de-escalated therapeutic strategies for early-TNBC patients.

Background During targeted treatment, HER2-positive breast cancers invariably lose HER2 DNA amplification. In contrast, and interestingly, HER2 proteins may be either lost or gained. To longitudinally and systematically appreciate complex/discordant changes in HER2 DNA/protein stoichiometry, HER2 DNA copy numbers and soluble blood proteins (aHER2/sHER2) were tested in parallel, non-invasively (by liquid biopsy), and in two-dimensions, hence HER2-2D. Methods aHER2 and sHER2 were assessed by digital PCR and ELISA before and after standard-of-care treatment of advanced HER2-positive breast cancer patients ( n =37) with the antibody-drug conjugate (ADC) Trastuzumab-emtansine (T-DM1). Results As expected, aHER2 was invariably suppressed by T-DM1, but this loss was surprisingly mirrored by sHER2 gain, sometimes of considerable entity, in most (30/37; 81%) patients. This unorthodox split in HER2 oncogenic dosage was supported by reciprocal aHER2/sHER2 kinetics in two representative cases, and an immunohistochemistry-high status despite copy-number-neutrality in 4/5 available post-T-DM1 tumor re-biopsies from sHER2-gain patients. Moreover, sHER2 was preferentially released by dying breast cancer cell lines treated in vitro by T-DM1. Finally, sHER2 gain was associated with a longer PFS than sHER2 loss (mean PFS 282 vs 133 days, 95% CI [210-354] vs [56-209], log-rank test p =0.047), particularly when cases ( n =11) developing circulating HER2-bypass alterations during T-DM1 treatment were excluded (mean PFS 349 vs 139 days, 95% CI [255-444] vs [45-232], log-rank test p =0.009). Conclusions HER2 gain is adaptively selected in tumor tissues and recapitulated in blood by sHER2 gain. Possibly, an increased oncogenic dosage is beneficial to the tumor during anti-HER2 treatment with naked antibodies, but favorable to the host during treatment with a strongly cytotoxic ADC such as T-DM1. In the latter case, HER2-gain tumors may be kept transiently in check until alternative oncogenic drivers, revealed by liquid biopsy, bypass HER2. Whichever the interpretation, HER2-2D might help to tailor/prioritize anti-HER2 treatments, particularly ADCs active on aHER2-low/sHER2-low tumors. Trial registration NCT05735392 retrospectively registered on January 31, 2023 https://www.clinicaltrials.gov/search?term=NCT05735392

Background Pathological complete response (pCR) to neoadjuvant systemic therapy (NAST) is an established prognostic marker in breast cancer (BC). Multimodal deep learning (DL), integrating diverse data sources (radiology, pathology, omics, clinical), holds promise for improving pCR prediction accuracy. This systematic review synthesizes evidence on multimodal DL for pCR prediction and compares its performance against unimodal DL. Methods Following PRISMA, we searched PubMed, Embase, and Web of Science (January 2015–April 2025) for studies applying DL to predict pCR in BC patients receiving NAST, using data from radiology, digital pathology (DP), multi-omics, and/or clinical records, and reporting AUC. Data on study design, DL architectures, and performance (AUC) were extracted. A narrative synthesis was conducted due to heterogeneity. Results Fifty-one studies, mostly retrospective (90.2%, median cohort 281), were included. Magnetic resonance imaging and DP were common primary modalities. Multimodal approaches were used in 52.9% of studies, often combining imaging with clinical data. Convolutional neural networks were the dominant architecture (88.2%). Longitudinal imaging improved prediction over baseline-only (median AUC 0.91 vs. 0.82). Overall, the median AUC across studies was 0.88, with 35.3% achieving AUC ≥ 0.90. Multimodal models showed a modest but consistent improvement over unimodal approaches (median AUC 0.88 vs. 0.83). Omics and clinical text were rarely primary DL inputs. Conclusion DL models demonstrate promising accuracy for pCR prediction, especially when integrating multiple modalities and longitudinal imaging. However, significant methodological heterogeneity, reliance on retrospective data, and limited external validation hinder clinical translation. Future research should prioritize prospective validation, integration underutilized data (multi-omics, clinical), and explainable AI to advance DL predictors to the clinical setting.

Background NEPA is an oral fixed-dose combination of netupitant, a new highly selective neurokinin-1 receptor antagonist, and palonosetron. This study was conducted to evaluate whether the efficacy of NEPA against chemotherapy-induced nausea and vomiting (CINV) in cycle 1 would be maintained over subsequent chemotherapy cycles in breast cancer patients receiving adjuvant anthracycline plus cyclophosphamide (AC). The study also describes the relationship between efficacy on day 1 through 5 (overall period) and control of CINV on day 6 through 21 (very late period) in each cycle. Methods In this multicentre, phase II study, patients received both NEPA and dexamethasone (12 mg intravenously) just before chemotherapy. The primary efficacy endpoint was overall complete response (CR; no emesis and no rescue medication use) in cycle 1. Sustained efficacy was evaluated during the subsequent cycles by calculating the rate of CR in cycles 2–4 and by assessing the probability of sustained CR over multiple cycles. The impact of both overall CR and risk factors for CINV on the control of very late events (vomiting and moderate-to-severe nausea) were also examined. Results Of the 149 patients enrolled in the study, 139 were evaluable for a total of 552 cycles; 97.8% completed all 4 cycles. The proportion of patients with an overall CR was 70.5% (90% CI, 64.1 to 76.9) in cycle 1, and this was maintained in subsequent cycles. The cumulative percentage of patients with a sustained CR over 4 cycles was 53%. NEPA was well tolerated across cycles. In each cycle, patients with CR experienced a significantly better control of very late CINV events than those who experienced no CR. Among the patients with CR, the only predictor for increased likelihood of developing very late CINV was pre-chemotherapy (anticipatory) nausea (adjusted odds ratio = 0.65–0.50 for no CINV events on cycles 3 and 4). Conclusion The high anti-emetic efficacy seen with the NEPA regimen in the first cycle was maintained over multiple cycles of adjuvant AC for breast cancer. Preliminary evidence also suggests that patients achieving a CR during the overall period gain high protection even against very late CINV events in each chemotherapy cycle. Trial registration This trial was retrospectively registered at Clinicaltrials.gov identifier ( NCT03862144 ) on 05/Mar/2019.

Body image, a complex interplay of perceptions, thoughts, and feelings about one’s physical appearance, has been a subject of extensive research. It is a dynamic construct that evolves throughout a woman’s lifespan, influenced by a multitude of biological, psychological, and sociocultural factors. From adolescence, marked by the onset of puberty and societal pressures to conform to specific beauty standards, to adulthood and the physical changes associated with aging, women’s body image undergoes significant transformations. Aging is a universal process that affects all organs, including the female genitalia. The vaginal tract undergoes significant atrophy due to declining estrogen levels, particularly during and after menopause. Aesthetic gynecology offers a range of procedures to address both functional and aesthetic concerns related to aging genitalia. Aesthetic gynecology, a burgeoning field within women’s health, provides various procedures aimed at enhancing genital appearance and function. It also helps balance the hormonal and anatomical changes that every woman experiences over time. The goal is to strengthen each patient’s intimate well-being and self-esteem, enabling them to experience intimacy peacefully. While often driven by concerns about physical attractiveness and sexual satisfaction, the psychological implications of these procedures are complex and multifaceted. It is crucial to recognize the interplay between psychological factors and the decision to undergo these procedures. Collaboration between surgeons and mental health professionals can ensure that candidates are psychologically prepared and have realistic expectations. By adopting a patient-centered approach and conducting rigorous research, healthcare providers can ensure that aesthetic gynecology is used as a tool for empowerment rather than exploitation. This article explores the intricate relationship between psychological well-being and aesthetic gynecology, examining how these procedures can impact body image, self-esteem, and overall quality of life.

Tumor dissemination to the central nervous system (CNS) is almost a rule in the treatment journey of advanced HER2+ breast cancer (BC). Recent results demonstrated high intracranial efficacy with Trastuzumab Deruxtecan (T-DXd). However, a real-world evidence is lacking in literature. We conducted a multicenter, observational, retrospective real-world analysis on 39 cases collected at 12 Italian Oncological Units. Patients with brain metastases (BMs) from HER2 + BC treated with T-DXd in various treatment lines were enrolled. Primary endpoint was the intracranial overall response rate (iORR). Secondary endpoints were intra- and global progression free survival (iPFS - gPFS); other secondary objectives were the intracranial disease control rate (iDCR), duration of response (iDoR), clinical benefit rate at 6 and 12 months (iCBr), overall survival, and safety. iORR was 59%, iPFS was 15.6 months, gPFS was 11.8 months. iDCR was 94.9%, iDoR was 11.9 months, and iCBr at 6 and 12 months were 69.2% and 59%, respectively. OS was not reached, with an overall rate of 77.9% of patients alive at 12 months. This study confirmed the high intracranial efficacy and manageable safety profile of T-DXd in this first-ever real world analysis.

Mesenchymal tumors of the breast constitute a rare and heterogeneous group of neoplasms, representing only 0.5% to 1% of all breast tumors. Originating from mesenchymal tissues, these tumors include various histological subtypes. They are particularly aggressive, characterized by a high propensity for local recurrence and an overall poor prognosis. The rarity of these cases has impeded the development of comprehensive clinical studies, leading to a lack of standardized diagnostic protocols and treatment guidelines. This review provides a thorough synthesis of current knowledge on breast mesenchymal tumors with a specific focus on malignant variants such as phyllodes tumors and breast sarcomas. It also addresses the diagnostic challenges faced by clinicians, evaluates current therapeutic strategies, and emphasizes the crucial role of surgical treatment. Additionally, it examines the evolving roles of chemotherapy and radiotherapy in enhancing patient outcomes.

The combination of atezolizumab and nab-paclitaxel is recommended in the EU as first-line treatment for PD-L1-positive metastatic triple-negative breast cancer (mTNBC), based on the results of phase III IMpassion130 trial. However, ‘real-world’ data on this combination are limited. The ANASTASE study (NCT05609903) collected data on atezolizumab plus nab-paclitaxel in PD-L1-positive mTNBC patients enrolled in the Italian Compassionate Use Program. A retrospective analysis was conducted in 29 Italian oncology centers among patients who completed at least one cycle of treatment. Data from 52 patients were gathered. Among them, 21.1% presented de novo stage IV; 78.8% previously received (neo)adjuvant treatment; 55.8% patients had only one site of metastasis; median number of treatment cycles was five (IQR: 3–8); objective response rate was 42.3% (95% CI: 28.9–55.7%). The median time-to-treatment discontinuation was 5 months (95% CI: 2.8–7.1); clinical benefit at 12 months was 45.8%. The median duration of response was 12.7 months (95% CI: 4.1–21.4). At a median follow-up of 20 months, the median progression-free survival was 6.3 months (95% CI: 3.9–8.7) and the median time to next treatment or death was 8.1 months (95% CI: 5.5–10.7). At 12 months and 24 months, the overall survival rates were 66.3% and 49.1%, respectively. The most common immune-related adverse events included rash (23.1%), hepatitis (11.5%), thyroiditis (11.5%) and pneumonia (9.6%). Within the ANASTASE study, patients with PD-L1-positive mTNBC treated with first-line atezolizumab plus nab-paclitaxel achieved PFS and ORR similar to those reported in the IMpassion130 study, with no unexpected adverse events.

Background: Given the low chance of response to neoadjuvant chemotherapy (NACT) in luminal breast cancer (LBC), the identification of predictive factors of pathological complete response (pCR) represents a challenge. A multicenter retrospective analysis was performed to develop and validate a predictive nomogram for pCR, based on pre-treatment clinicopathological features. Methods: Clinicopathological data from stage I–III LBC patients undergone NACT and surgery were retrospectively collected. Descriptive statistics was adopted. A multivariate model was used to identify independent predictors of pCR. The obtained log-odds ratios (ORs) were adopted to derive weighting factors for the predictive nomogram. The receiver operating characteristic analysis was applied to determine the nomogram accuracy. The model was internally and externally validated. Results: In the training set, data from 539 patients were gathered: pCR rate was 11.3% [95% confidence interval (CI): 8.6–13.9] (luminal A-like: 5.3%, 95% CI: 1.5–9.1, and luminal B-like: 13.1%, 95% CI: 9.8–13.4). The optimal Ki67 cutoff to predict pCR was 44% (area under the curve (AUC): 0.69; p < 0.001). Clinical stage I–II (OR: 3.67, 95% CI: 1.75–7.71, p = 0.001), Ki67 ⩾44% (OR: 3.00, 95% CI: 1.59–5.65, p = 0.001), and progesterone receptor (PR) <1% (OR: 2.49, 95% CI: 1.15–5.38, p = 0.019) were independent predictors of pCR, with high replication rates at internal validation (100%, 98%, and 87%, respectively). According to the nomogram, the probability of pCR ranged from 3.4% for clinical stage III, PR > 1%, and Ki67 <44% to 53.3% for clinical stage I–II, PR < 1%, and Ki67 ⩾44% (accuracy: AUC, 0.73; p < 0.0001). In the validation set (248 patients), the predictive performance of the model was confirmed (AUC: 0.7; p < 0.0001). Conclusion: The combination of commonly available clinicopathological pre-NACT factors allows to develop a nomogram which appears to reliably predict pCR in LBC.

Hormone receptor-positive/HER2-negative breast cancer (BC) is the most common subtype of BC and typically occurs as an early, operable disease. In patients receiving neoadjuvant chemotherapy (NACT), pathological complete response (pCR) is rare and multiple efforts have been made to predict disease recurrence. We developed a framework to predict pCR using clinicopathological characteristics widely available at diagnosis. The machine learning (ML) models were trained to predict pCR ( n  = 463), evaluated in an internal validation cohort ( n  = 109) and validated in an external validation cohort ( n  = 151). The best model was an Elastic Net, which achieved an area under the curve (AUC) of respectively 0.86 and 0.81. Our results highlight how simpler models using few input variables can be as valuable as more complex ML architectures. Our model is freely available and can be used to enhance the stratification of BC patients receiving NACT, providing a framework for the development of risk-adapted clinical trials.