Biomedical subjects

Giuseppe Curigliano

Publications and source records attributed to Giuseppe Curigliano.

3 recordsLinked to original sources

PubMed2026

Molecular and immune profiling of HER2-low, HER2 ultra-low, and HER2-null male breast cancer.

BACKGROUND: HER2 expression is described along a biological continuum from null to positive and serves as a critical biomarker for therapeutic guidance in breast cancer (BC). While HER2-low and ultra-low categories have emerged as actionable targets for antibody-drug conjugates (ADCs) in female BC, their molecular and immune characteristics remain largely unexplored in male breast cancer. METHODS: We profiled 214 male breast tumors using next-generation sequencing and whole-transcriptome sequencing to assess mutational, transcriptomic, and immune landscapes. Tumor mutational burden (TMB) was defined as high if > 10 mutations/Mb. Immune cell fractions were inferred using Quantiseq deconvolution. RESULTS: Among 214 samples, 66 (30.8%) were HER2-null, 53 (24.8%) HER2 ultra-low, 80 (37.4%) HER2-low, and 15 (7.0%) HER2-positive. HER2 ultra-low tumors exhibited a higher prevalence of PIK3CA mutations (39.2% vs 22.6%, p ≤ 0.05) compared to HER2-null. No significant differences were observed in TMB-high frequency or PD-L1 expression across subgroups. Immune composition differed primarily between HER2-null and HER2-expressing subgroups: HER2-ultra-low tumors showed higher B-cell infiltration, whereas HER2-null tumors were enriched in neutrophils. Transcriptomic analysis revealed upregulation of selected stemness-associated genes (NANOG, KLF4, POU5F1) and CEACAM1 in HER2-null tumors, while HER2-low and HER2-ultra-low tumors were largely similar across most molecular and immune readouts in this cohort. CONCLUSIONS: HER2-null male breast cancer appears to represent the most biologically divergent subgroup within the HER2-negative spectrum, whereas HER2-low and HER2-ultra-low tumors were largely similar in this cohort. These findings support further investigation of HER2-null disease as a distinct biological state and provide hypothesis-generating data for biomarker development in this rare population.

Male↗

PubMed2026

Availability and public reimbursement of early breast cancer care across European expert centres: a PORTRAIT from an EUSOMA initiative.

BACKGROUND: Cross-country disparities in access to guideline-recommended early breast cancer care persist across Europe. PORTRAIT is a clinician-reported, cross-sectional access study mapping availability and state reimbursement of key services across the early breast cancer pathway. METHODS: A 49-item survey covering diagnostics, pathology and genomics, systemic therapy, surgery, radiotherapy, and supportive care was emailed from June to September 2024 to multidisciplinary teams at one expert breast centre in 42 European countries. Respondents provided a consensus perspective on service availability and reimbursement. Descriptive proportions with full, partial, or no access were calculated. RESULTS: Thirty-nine countries responded (93%). Core diagnostics were widely available, but gaps persisted: MRI-guided biopsy was absent in 29% of countries and vacuum-assisted biopsy was fully reimbursed in 66%. Genomic assays were unavailable in 14% and not fully reimbursed in 35%. Public funding gaps were reported for PARP inhibitors (33%) and CDK4/6 inhibitors (26%). Immediate implant-based reconstruction and biological meshes lacked reimbursement in 21% and 33%, respectively. Despite broad availability of hypofractionated radiotherapy, 38% of countries still used per-fraction reimbursement. Psycho-oncology was limited in 35%, fertility preservation in 46%, and patient-reported outcome measures absent in 43%. CONCLUSION: Basic services are nearly universal, but gaps persist in advanced imaging, molecular testing, targeted therapies, radiotherapy reimbursement, reconstructive/oncoplastic surgery, and survivorship care. PORTRAIT identifies practical targets for policy audit, reimbursement alignment, and resource stewardship. Findings reflect clinician perspectives from expert centres, potentially representing best specialist care rather than average national care, and are not population-representative estimates or direct measures of patient outcomes.

Humans↗

PubMed2026

Artificial intelligence-based tumour infiltrating lymphocyte quantification in patients with triple-negative breast cancer: an independent validation study.

BACKGROUND: Tumour-infiltrating lymphocytes (TILs) are a robust prognostic marker in patients with triple-negative breast cancer. Artificial intelligence (AI)-derived computational tools assessing TILs could improve efficiency, but require independent validation against clinical outcomes. We aimed to compare the prognostic performance of AI-derived TIL scores with pathologist-scored TILs in a large, prospectively collected dataset pooled from randomised controlled trials. METHODS: CATALINA was an independent, external validation study using prospectively collected long-term clinical outcome data pooled from seven randomised clinical trials conducted at multiple sites. We independently evaluated two previously validated AI pipelines that generate five computationally assessed tumour-infiltrating lymphocyte (cTIL) scores by masked, independent deployment of locked models. cTIL scores were correlated with the mean of the pathologist-scored stromal TILs (sTILs) in 220 digitised haematoxylin and eosin whole slide images in a cohort of patients with early-stage triple-negative or HER-2 positive breast cancer, previously scored by trained pathologists in a TIL-reproducibility study. Prognostic performance was assessed in a separate cohort of patients with early triple-negative breast cancer pooled from seven prospective, randomised adjuvant trials. Multivariable Cox regression models adjusted for clinicopathological factors and study heterogeneity assessed associations of cTIL score and sTIL score with invasive disease-free survival, distant disease-free survival, and overall survival. 5-year discrimination was estimated using time-dependent area under the receiver operating characteristic curve (AUC). FINDINGS: Individual data were collated from 1759 patients, of whom 1356 had complete clinicopathological data, pathologist sTIL scores, and cTIL scores available. Modest correlation (r 0·375-0·473) was observed between cTIL scores and the mean pathologist sTIL score. Both sTIL and cTIL were independently associated with 5-year invasive disease-free survival, distant disease-free survival, and overall survival after adjustment for clinicopathological factors (hazard ratio for invasive disease-free survival was 0·73 [95% CI 0·66-0·82]; q<0·0001, distant disease-free survival was 0·70 [0·61-0·79]; q<0·0001, and overall survival was 0·72 [0·63-0·82]; q<0·0001 for sTIL scores and 0·80 [0·73-0·89]; q<0·0001, 0·77 [0·69-0·86]; q<0·0001, and 0·79 [0·70-0·88]; q=0·0002, respectively, for percentage_lymphocyte scores). In models adjusted for clinicopathological variables and sTIL score, cTIL score did not maintain a statistically significant prognostic association. Both sTIL and cTIL scores improved the 5-year AUC over clinicopathological variables alone, while cTIL score did not significantly further improve AUC when combined with clinicopathological variables and sTIL score. INTERPRETATION: Two cTIL models deployed entirely without retraining or modification provided statistically significant prognostic information and improved risk discrimination compared with clinicopathological variables alone in this large, platform-based, independent validation study. Although cTIL score did not incrementally improve prognostication compared with models combining clinicopathological variables with sTIL score, these findings support the application of cTILs as a reproducible prognostic biomarker, particularly in settings where routine or widespread pathologist assessment is unavailable. FUNDING: Breast Cancer Research Foundation (USA).

Humans↗