Explore the vast range of titles available.

The rates and routes of lethal systemic spread in breast cancer are poorly understood owing to a lack of molecularly characterized patient cohorts with long-term, detailed follow-up data. Long-term follow-up is especially important for those with oestrogen-receptor (ER)-positive breast cancers, which can recur up to two decades after initial diagnosis 1 – 6 . It is therefore essential to identify patients who have a high risk of late relapse 7 – 9 . Here we present a statistical framework that models distinct disease stages (locoregional recurrence, distant recurrence, breast-cancer-related death and death from other causes) and competing risks of mortality from breast cancer, while yielding individual risk-of-recurrence predictions. We apply this model to 3,240 patients with breast cancer, including 1,980 for whom molecular data are available, and delineate spatiotemporal patterns of relapse across different categories of molecular information (namely immunohistochemical subtypes; PAM50 subtypes, which are based on gene-expression patterns 10 , 11 ; and integrative or IntClust subtypes, which are based on patterns of genomic copy-number alterations and gene expression 12 , 13 ). We identify four late-recurring integrative subtypes, comprising about one quarter (26%) of tumours that are both positive for ER and negative for human epidermal growth factor receptor 2, each with characteristic tumour-driving alterations in genomic copy number and a high risk of recurrence (mean 47–62%) up to 20 years after diagnosis. We also define a subgroup of triple-negative breast cancers in which cancer rarely recurs after five years, and a separate subgroup in which patients remain at risk. Use of the integrative subtypes improves the prediction of late, distant relapse beyond what is possible with clinical covariates (nodal status, tumour size, tumour grade and immunohistochemical subtype). These findings highlight opportunities for improved patient stratification and biomarker-driven clinical trials. A statistical framework for breast-cancer recurrence uses long-term follow-up data and a knowledge of molecular subcategories to model distinct disease stages and to predict the risk of relapse.

In patients with metastatic cancer, spatial heterogeneity of somatic alterations may lead to incomplete assessment of a cancer’s mutational profile when analyzing a single tumor biopsy. In this study, we perform sequencing of cell-free DNA (cfDNA) and distinct metastatic tissue samples from ten rapid autopsy cases with pre-treated metastatic cancer. We show that levels of heterogeneity in genetic biomarkers vary between patients but that gene expression signatures representative of the tumor microenvironment are more consistent. Across nine patients with plasma samples available, we are able to detect 62/62 truncal and 47/121 non-truncal point mutations in cfDNA. We observe that mutation clonality in cfDNA is correlated with the number of metastatic lesions in which the mutation is detected and use this result to derive a clonality threshold to classify truncal and non-truncal driver alterations with reasonable specificity. In contrast, mutation truncality is more often incorrectly assigned when studying single tissue samples. Our results demonstrate the utility of a single cfDNA sample relative to that of single tissue samples when treating patients with metastatic cancer. It is currently unclear if cell-free DNA samples from metastatic cancers are as informative as tissue ones for cancer profiling. Here the authors show that cell-free DNA samples from rapid autopsies capture clonal and subclonal alterations of metastatic tumours and reveal more driver alterations than single tissue samples.

Background Somatic alterations in the cancer genome, some of which are associated with changes in gene expression, have been characterized in multiple studies across diverse cancer types. However, less is known about germline variants that influence tumor biology by shaping the cancer transcriptome. Methods We performed expression quantitative trait loci (eQTL) analyses using multi-dimensional data from The Cancer Genome Atlas to explore the role of germline variation in mediating the cancer transcriptome. After accounting for associations between somatic alterations and gene expression, we determined the contribution of inherited variants to the cancer transcriptome relative to that of somatic variants. Finally, we performed an interaction analysis using estimates of tumor cellularity to identify cell type-restricted eQTLs. Results The proportion of genes with at least one eQTL varied between cancer types, ranging between 0.8% in melanoma to 28.5% in thyroid cancer and was correlated more strongly with intratumor heterogeneity than with somatic alteration rates. Although contributions to variance in gene expression was low for most genes, some eQTLs accounted for more than 30% of expression of proximal genes. We identified cell type-restricted eQTLs in genes known to be cancer drivers including LPP and EZH2 that were associated with disease-specific mortality in TCGA but not associated with disease risk in published GWAS. Together, our results highlight the need to consider germline variation in interpreting cancer biology beyond risk prediction.

Background Patients with BRCA1 -like tumors correlate with improved response to DNA double-strand break-inducing therapy. A gene expression-based classifier was developed to distinguish between BRCA1 -like and non- BRCA1 -like tumors. We hypothesized that these tumors may also be more sensitive to PARP inhibitors than standard treatments. Methods A diagnostic gene expression signature ( BRCA1 ness) was developed using a centroid model with 128 triple-negative breast cancer samples from the EU FP7 RATHER project. This BRCA1 ness signature was then tested in HER2-negative patients ( n  = 116) from the I-SPY 2 TRIAL who received an oral PARP inhibitor veliparib in combination with carboplatin (V-C), or standard chemotherapy alone. We assessed the association between BRCA1 ness and pathologic complete response in the V-C and control arms alone using Fisher’s exact test, and the relative performance between arms (biomarker × treatment interaction, likelihood ratio p  < 0.05) using a logistic model and adjusting for hormone receptor status (HR). Results We developed a gene expression signature to identify BRCA1 -like status. In the I-SPY 2 neoadjuvant setting the BRCA1 ness signature associated significantly with response to V-C ( p  = 0.03), but not in the control arm ( p  = 0.45). We identified a significant interaction between BRCA1 ness and V-C ( p  = 0.023) after correcting for HR. Conclusions A genomic-based BRCA1 -like signature was successfully translated to an expression-based signature ( BRC1A ness). In the I-SPY 2 neoadjuvant setting, we determined that the BRCA1 ness signature is capable of predicting benefit of V-C added to standard chemotherapy compared to standard chemotherapy alone. Trial registration I-SPY 2 TRIAL beginning December 31, 2009: Neoadjuvant and Personalized Adaptive Novel Agents to Treat Breast Cancer (I-SPY 2), NCT01042379 .

Objective: The study aimed to analyze the role of interdisciplinarity in Primary Health Care (PHC), identifying strategies that promote the integration of different professionals and their contribution to strengthening community health.   Theoretical Framework: The research was based on references from the literature on interdisciplinarity, multiprofessionalism, and interprofessionalism, highlighting the importance of the Family Health Strategy (FHS), the Expanded Family Health and Basic Care Centers (NASF-AB), and participatory management practices as central axes for the consolidation of comprehensive care.   Method: This is an integrative literature review conducted in the BVS, PubMed, and SciELO databases, with articles published between 2015 and 2025 in Portuguese, English, and Spanish. Initially, 263 works were identified, of which 31 met the inclusion criteria according to the PRISMA-ScR protocol.   Results and Discussion: The findings indicated that systematic meetings, integrated protocols, matrix support, continuing education, and integrative practices are key strategies for interprofessional cooperation. Despite barriers—such as the shortage of human resources and the persistence of hierarchical models—facilitators stand out for their positive impact on health indicators, therapeutic adherence, and user satisfaction.   Implications of the Research: The study provides insights for managers, professionals, and public policymakers, outlining paths for the consolidation of interdisciplinarity as a structuring strategy of Primary Health Care.   Originality/Value: The research contributes by systematizing current evidence on interdisciplinary practice, reinforcing its value for equity, comprehensiveness, and efficiency of the Unified Health System.

Lymphangiosarcoma, or Stewart-Treves syndrome, is a rare and aggressive malignancy. It is associated with poor prognosis due to its high risk of recurrence and metastasis. This case report highlights the surgical challenges faced in managing lymphangiosarcoma.We present a case of a woman in her 60s who underwent modified radical mastectomy and adjuvant therapy for breast carcinoma. She developed lymphangiosarcoma of the upper limb and underwent limb disarticulation. 6 months later, she presented with recurrent angiosarcoma at the amputation site. A wide local excision was performed, followed by reconstruction with a free anterolateral thigh flap.

Objective: This study aimed to analyze the effects of multiprofessional cooperation in the administration of high-complexity medications in hospital units, seeking to understand how this interaction impacts patient safety and therapeutic efficacy.   Theoretical Framework: The research was based on studies addressing the administration of critical drugs, the risks associated with the medication chain, and the benefits of joint action among health professionals. The main authors discuss the importance of standardized protocols and interprofessional communication to mitigate adverse events.   Method: This is an integrative literature review, composed of 20 articles selected from databases such as SciELO, LILACS, MEDLINE/PubMed, and BDENF, using inclusion criteria such as articles with results pertinent to the research goals, publications in Portuguese, English, and Spanish, and no more than 10 years old.   Results and Discussion: The findings indicate that the articulated action among healthcare professionals significantly contributes to medication safety, especially in high-pressure clinical contexts. The active presence of the pharmacist and the strategic role of nursing were pointed out as essential to reduce errors in drug administration.   Research Implications: The study highlights the need for institutional policies that encourage interprofessional practice, the standardization of protocols, and continued education, contributing to safer and more effective care.   Originality/Value: By integrating scientific evidence and collaborative practices, the study provides a relevant contribution to hospital care management, reinforcing the value of multiprofessional cooperation in the administration of high-complexity medications.

The genomic landscape of breast cancer is complex, and inter- and intra-tumour heterogeneity are important challenges in treating the disease. In this study, we sequence 173 genes in 2,433 primary breast tumours that have copy number aberration (CNA), gene expression and long-term clinical follow-up data. We identify 40 mutation-driver (Mut-driver) genes, and determine associations between mutations, driver CNA profiles, clinical-pathological parameters and survival. We assess the clonal states of Mut-driver mutations, and estimate levels of intra-tumour heterogeneity using mutant-allele fractions. Associations between PIK3CA mutations and reduced survival are identified in three subgroups of ER-positive cancer (defined by amplification of 17q23, 11q13–14 or 8q24). High levels of intra-tumour heterogeneity are in general associated with a worse outcome, but highly aggressive tumours with 11q13–14 amplification have low levels of intra-tumour heterogeneity. These results emphasize the importance of genome-based stratification of breast cancer, and have important implications for designing therapeutic strategies. Much effort has recently been devoted to understanding the genomics of breast cancer. In this study, the authors integrate somatic mutation data with previously published copy number aberration and gene expression information for nearly 2,500 breast cancer samples.

The genomic landscape of breast cancer is complex, and inter- and intra-tumour heterogeneity are important challenges in treating the disease. In this study, we sequence 173 genes in 2,433 primary breast tumours that have copy number aberration (CNA), gene expression and long-term clinical follow-up data. We identify 40 mutation-driver (Mut-driver) genes, and determine associations between mutations, driver CNA profiles, clinical-pathological parameters and survival. We assess the clonal states of Mut-driver mutations, and estimate levels of intra-tumour heterogeneity using mutant-allele fractions. Associations between PIK3CA mutations and reduced survival are identified in three subgroups of ER-positive cancer (defined by amplification of 17q23, 11q13-14 or 8q24). High levels of intra-tumour heterogeneity are in general associated with a worse outcome, but highly aggressive tumours with 11q13-14 amplification have low levels of intra-tumour heterogeneity. These results emphasize the importance of genome-based stratification of breast cancer, and have important implications for designing therapeutic strategies.

Triple negative (TN) breast cancers make up some 15% of all breast cancers. Approximately 10–15% are mutant for the tumor suppressor, BRCA1. BRCA1 is required for homologous recombination-mediated DNA repair and deficiency results in genomic instability. BRCA1-mutated tumors have a specific pattern of genomic copy number aberrations that can be used to classify tumors as BRCA1-like or non-BRCA1-like. BRCA1 mutation, promoter methylation, BRCA1-like status and genome-wide expression data was determined for 112 TN breast cancer samples with long-term follow-up. Mutation status for 21 known DNA repair genes and PIK3CA was assessed. Gene expression and mutation frequency in BRCA1-like and non-BRCA1-like tumors were compared. Multivariate survival analysis was performed using the Cox proportional hazards model. BRCA1 germline mutation was identified in 10% of patients and 15% of tumors were BRCA1 promoter methylated. Fifty-five percent of tumors classified as BRCA1-like. The functions of genes significantly up-regulated in BRCA1-like tumors included cell cycle and DNA recombination and repair. TP53 was found to be frequently mutated in BRCA1-like (P < 0.05), while PIK3CA was frequently mutated in non-BRCA1-like tumors (P < 0.05). A significant association with worse prognosis was evident for patients with BRCA1-like tumors (adjusted HR = 3.32, 95% CI = 1.30–8.48, P = 0.01). TN tumors can be further divided into two major subgroups, BRCA1-like and non-BRCA1-like with different mutation and expression patterns and prognoses. Based on these molecular patterns, subgroups may be more sensitive to specific targeted agents such as PI3K or PARP inhibitors. •Triple negative breast cancers subdivide into 2 groups: BRCA1-like, non-BRCA1-like.•In a retrospective analysis, patients with BRCA1-like tumors have a worse outcome.•Mutation and gene expression patterns reveal potential therapy targets in subgroups.