BACKGROUND:With steadily rising survival rates, the cause-of-death landscape for breast cancer patients is evolving. This study. AIMS:to delineate mortality patterns and demographic disparities to inform long-term survivorship strategies. METHODS:We performed a retrospective analysis of 839,698 breast cancer patients from U.S. population-based registries (2000-2021). Standardized Mortality Ratios (SMRs) and Incidence Rate Ratios (IRRs) were calculated to assess the risk of non-cancer deaths across age and racial/ethnic groups. RESULTS:By 10 years of follow-up, 48.6% of all deaths were attributed to non-cancer causes. Significant disparities emerged: Black patients (aged 0-54) exhibited the highest all-cause mortality risk (IRR: 1.70; 95% CI: 1.66-1.74), whereas Asian/Pacific Islanders (aged 65-74) showed the lowest (IRR: 0.67; 95% CI: 0.65-0.69). Notably, patients faced drastically elevated risks for external causes, including suicide (SMR: 17.4; 95% CI: 16.1-18.8) and homicide (SMR: 10.1; 95% CI: 8.37-12.13), alongside cardiovascular/non-cancer diseases. CONCLUSION:Mortality in breast cancer survivors is progressively shifting from malignancy to non-cancer causes, with distinct racial and age-dependent patterns. These findings necessitate a paradigm shift toward personalized, risk-stratified survivorship care that integrates cardiovascular monitoring and psychosocial interventions.

e12674 Background: While the addition of immune checkpoint inhibitors (ICIs) to neoadjuvant chemotherapy (NAC) has improved systemic control and pathologic complete response in TNBC, its effect on de-escalation of axillary surgery and associated overall survival remains unclear. We investigated whether the addition of ICIs to NAC facilitates safe de-escalation of axillary lymph node dissection (ALND) to sentinel lymph node biopsy (SLNB) in patients presenting with clinically node-positive (cLN+) disease. Methods: Women > 18y cN1-3, cM0 TNBC diagnosed 2018-2022 were identified from the National Cancer Database. Patients were stratified by systemic therapy (NAC vs NAC+ICIs) and surgical procedure (SLNB vs ALND). Propensity score matching (PSM) and restricted mean survival time (RMST, truncated at 48 months) were utilized to assess overall survival (OS). Results: 4336 patients were included for analysis (cN1 = 3658 [84.4%], cN2 = 321 [7.4%], cN3 = 357 [8.2%]). NAC+ICI was associated with improved OS in the SLNB group (RMST 46.6 vs 46.1 mos, p = 0.03) but not the ALND group (RMST 46.4 vs 46.3, p = 0.91). In the NAC-alone cohort, SLNB was associated with significantly inferior survival vs ALND (5-year OS ALND 87.8% vs SLNB 83.0%, p = 0.027) and was independently associated with increased risk of mortality (HR 1.63, 95% CI 1.12–2.38, p = 0.01). Notably, in the NAC+ICI cohort, this survival difference did not persist, with SLNB and ALND having comparable survival (5-year OS ALND 93.6% vs SLNB 90.1%, p = 0.99) and identical 48-month RMSTs (46.4 months). Multivariable analysis confirmed that SLNB was not associated with worse survival in the immunotherapy setting (HR 1.19, 95% CI 0.54–2.61, p = 0.67). Conclusions: Among SLNB recipients, ICIs were associated with improved unadjusted OS, but this benefit was not observed among ALND recipients, suggesting the burden of axillary disease necessitating ALND aligns with overall worse prognosis and was less affected by ICI receipt. Patients receiving SLNB after NAC-alone had worse survival vs those receiving ALND, but it is unclear whether this survival difference is due to omission of axillary clearance or patient-level factors associated with the decision to omit ICIs in the first place (e.g., co-morbidities that might also have led to omission of ALND). Notable, however, among those receiving both NAC and ICIs, survival was comparable between SLNB and ALND recipients, suggesting ICIs safely facilitate axillary de-escalation and effectively control tumor burden without the need for axillary clearance beyond SLNB.

Background Macrophage-related genes (MRGs), a group of pivotal regulators governing macrophage differentiation, polarization, and function, have increasingly been recognized as critical modulators in tumor progression and immune evasion. However, the molecular expression profiles of MRGs and their intricate relationships with the immune microenvironment in breast cancer (BRCA) remain insufficiently investigated.Methods We first used bulk RNA sequencing and single-cell RNA sequencing data from the TCGA and GEO databases, we analyzed the molecular expression patterns and clinical relevance of MRGs in BRCA. A prognostic model was developed using these genes, and the variations in the immune microenvironment between the high-risk and low-risk groups were evaluated. Additionally, the model's predictive ability for immunotherapy response was assessed. Finally, we conducted in vivo and in vitro experiments to study the biological functions of HAGHL.Results Multi-omics analysis identified a group of MRGs with prognostic value, leading to the successful development of a model that stratified BRCA patients into high- and low-risk categories. The model demonstrated high accuracy in predicting patient survival. Immune microenvironment-related analysis revealed significant differences between risk groups, and the model effectively predicted responses to immunotherapy. CellChat analysis suggested potential macrophage pathways in BRCA. Our results also show that HAGHL, as a carcinogenic factor in BRCA, knockdown can inhibit the proliferation and invasion of BRCA cells.Conclusions We developed a prognostic model based on MRGs, which holds promise for predicting outcomes in BRCA patients and responses to immunotherapy. Our findings offer new insights and potential guidance for personalized treatment strategies in BRCA. Additionally, we identified HAGHL as a potential oncogene, laying the groundwork for future research.

Breast cancer is the most common malignancy among women worldwide and exhibits marked heterogeneity. Among its various subtypes, triple-negative breast cancer (TNBC) is associated with an inferior prognosis. Although molecular stratification tools such as Oncotype DX and MammaPrint have been adopted in clinical settings, prognostic models based on chromosomal instability remain inadequate. The centromere protein (CENP) family, as a key regulator of genomic stability, has been closely linked to tumor progression due to its aberrant expression. In this study, we integrated multi-omics data—including RNA transcriptomic profiles and single-cell RNA sequencing—and employed weighted gene co-expression network analysis (WGCNA) to identify core gene modules associated with CENPA. A prognostic risk model was developed using Cox regression analysis and the LASSO algorithm. Validation in independent cohorts demonstrated that the model effectively stratified patients into high- and low-risk groups, with the high-risk group showing significantly reduced five-year survival (p < 0.001). Furthermore, the single-cell analysis revealed that CENPA-high subpopulations were enriched in proliferative tumor cells and were associated with an immunosuppressive tumor microenvironment. This study is the first to systematically construct a CENP-based prognostic model for breast cancer, providing novel molecular biomarkers and potential therapeutic targets for personalized treatment. The biological function of the key molecule MMP1 in breast cancer was further validated through both in vitro and in vivo experiments.

Introduction Survival outcomes for early-stage breast cancer have improved substantially; however, many survivors experience persistent treatment-related toxicities that adversely affect long-term quality of life (QoL) and functional recovery. Prospective survivorship data from China remain limited. The PERSEVERE study aims to characterise longitudinal trajectories of QoL and treatment-related toxicities among Chinese women treated for stage I–III breast cancer and to identify factors associated with suboptimal recovery.Methods and analysis PERSEVERE is a prospective, multicentre, observational cohort study enrolling approximately 3000 women with newly diagnosed stage I–III invasive breast cancer across cancer centres in China. Data are collected at baseline and serially for up to 5 years, including clinical variables, a validated suite of patient-reported outcome measures collected via a centralised REDCap electronic platform and baseline biospecimens. The primary outcome is the change in the European Organisation for Research and Treatment of Cancer (EORTC) QLQ-C30 global health status/QoL score from baseline to 12 months. Longitudinal and time-to-event analytical approaches appropriate for observational cohort studies will be applied, with exploratory analyses planned to investigate symptom trajectories and biological correlates.Ethics and dissemination The study protocol (ID: NCC25/629-5575) has been approved by the Independent Ethics Committee of the National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences. Written informed consent will be obtained from all participants. Study findings will be disseminated through peer-reviewed open-access publications and presentations at national and international conferences, with summaries shared with clinicians and patient advocacy groups.Trial registration number NCT07010939.

e13671 Background: Gene expression–based prognostic models and multigene panels are widely used for risk stratification in oncology. However, their performance often degrades when applied across heterogeneous cohorts, cancer types, or underrepresented populations, due to limited target sample sizes and variability in gene–outcome associations. Existing approaches relying on target-only modeling or naive pooling of external datasets may result in instability or bias. We sought to develop a transfer learning framework for genomic time-to-event analysis that enables population-aware prognostic modeling and gene panel recalibration while accounting for cross-cohort heterogeneity. Methods: We developed two complementary transfer learning approaches for high-dimensional survival data. TransSurv performs multi-study genomic survival modeling by selectively borrowing information from auxiliary cohorts using a penalized Cox proportional hazards framework with cohort-level screening to mitigate negative transfer. TransInf focuses on recalibration of existing multigene prognostic panels by integrating target cohort data with compatible external cohorts through gene-level transfer-aware inference. The methods were evaluated using transcriptomic and clinical data from The Cancer Genome Atlas (TCGA), METABRIC, and an independent triple-negative breast cancer (TNBC) cohort from Fudan University Shanghai Cancer Center. Model performance was assessed using concordance index (C-index) and time-dependent area under the curve (AUC) under repeated train–test splits. Results: Across multiple TCGA cancer types and stage-defined subcohorts, TransSurv demonstrated improved discrimination for overall survival compared with target-only penalized Cox models and a state-of-the-art multi-study survival learning approach, with consistent gains in C-index and time-dependent AUC. In the external FUSCC TNBC cohort, TransSurv achieved higher C-index for recurrence-free survival compared with target-only modeling. Using TransInf, recalibrated gene panels derived from established signatures showed improved prognostic discrimination in race-stratified TCGA cohorts and in the TNBC cohort relative to target-only or pooled analyses. The recalibrated panels retained biologically relevant genes while excluding features with inconsistent target-level associations. Conclusions: This transfer learning framework enables robust genomic survival modeling and gene panel recalibration across heterogeneous cohorts by selectively leveraging external data while preserving target-specific inference. The proposed methods support population-aware risk stratification and adaptation of existing prognostic tools, with potential relevance for precision oncology applications in settings with limited target cohort sizes.

Malignant tumors remain a major global health challenge due to their heterogeneity, poor therapeutic specificity, and frequent development of multidrug resistance. Conventional treatment strategies are often hindered by limited tumor penetration, systemic toxicity, and the immunosuppressive tumor microenvironment. In recent years, nanorobots—engineered nanoscale devices with autonomous or guided navigation capabilities—have emerged as a transformative platform in precision oncology. These intelligent systems integrate active targeting, stimuli-responsive drug release, and multifunctional therapeutic modules, enabling dynamic interactions with the tumor milieu. This review systematically summarizes recent advances in nanorobot materials, modular design strategies, and propulsion mechanisms, and highlights their applications across central nervous system, breast, urological, and gastrointestinal tumors. Furthermore, we address key translational barriers, including biosafety, navigation precision, and regulatory challenges, and propose future directions leveraging artificial intelligence and clinical trial integration. By bridging materials science, robotics, and biomedicine, nanorobots hold promise to redefine minimally invasive cancer treatment paradigms.

Although cancer immunotherapy has revolutionized oncology, its clinical efficacy remains substantially limited by both primary and acquired resistance. These resistance mechanisms are largely driven by complex biological barriers within the tumor microenvironment (TME) and insufficient tumor immunogenicity. Nanotechnology offers a promising strategy to overcome these barriers by enabling precise spatiotemporal control of immune activation. This review provides a comprehensive analysis of emerging nanoparticle-based strategies designed to overcome immunotherapy resistance. Moving beyond conventional drug delivery, we highlight the paradigm shift from empirical engineering to artificial intelligence (AI)-driven design and precision medicine. We critically examine advanced mechanisms for remodeling the hypoxic TME, normalizing tumor vasculature, and reversing immunosuppression by activating the Stimulator of Interferon Genes (STING) pathway and inducing immunogenic cell death (ICD). Furthermore, we discuss integrating AI and machine learning to predict tumor-specific neoantigens and optimize nanocarrier properties, enabling the development of personalized mRNA nanovaccines. Finally, we address key translational challenges—including safety considerations, scalable manufacturing, and regulatory frameworks—that must be addressed to bridge the gap between laboratory innovation and clinical application. Collectively, these advances provide a roadmap for the next generation of smart, mechanism-driven nano-immunotherapeutics capable of transforming immunologically "cold" tumors into "hot" ones.

Introduction Postoperative depressive symptoms are common after breast cancer surgery and can adversely affect recovery and quality of life. This multicentre trial aims to determine whether a single intraoperative subanaesthetic dose of esketamine, as an adjunct to antidepressant therapy, improves postoperative depressive outcomes at postoperative day (POD) 30.Methods and analysis This multicentre, prospective, randomised, triple-blind, placebo-controlled trial will enrol 824 women aged 18–80 years with stage I–III breast cancer (American Society of Anesthesiologists physical status I–III) who are scheduled to undergo surgery. Participants will be randomised 1:1 to receive 0.2 mg/kg esketamine or an equivalent volume of normal saline after anaesthesia induction and before surgical incision. The primary outcome is the incidence of depressive symptoms at POD 30, assessed using the Hospital Anxiety and Depression Scale Depression (score ≥8). Secondary outcomes include acute and chronic pain, and anxious symptoms, etc. Primary analysis will use a generalised linear mixed model with a logit link on an intention-to-treat basis.Ethics and dissemination The study protocol has been formally approved by the institutional ethics committee of the National Cancer Center (Approval No.25/483-5429). Written informed consent will be obtained from all participants prior to enrolment. Results will be disseminated through peer-reviewed journals and international scientific conferences.Trial registration number ChiCTR2600117573.

ObjectiveTo compare long-term survival in early-stage breast cancer patients treated with different radiation therapy modalities.MethodsData was retrospectively derived from SEER database. We compared overall survival (OS), breast cancer specific survival (BCSS) and second primary malignancies (SPM) in early-stage breast cancer patients treated with postoperative radiotherapy (PORT) versus those treated neoadjuvant radiotherapy (NART) and intraoperative radiotherapy (IORT) after propensity score matching by 1:1.ResultsA total of 457,166 patients were included in this study. After matching, the 20-year OS of 1441 patients in NART cohort was lower than that in PORT cohort (p < 0.01), particularly in hormone receptor positive patients (p < 0.01). NART were dependent prognostic factors for 20-year OS [Hazard Ratio (HR):1.21, 95%CI: 1.06-1.38, p < 0.01). No significant difference in BCSS was observed between NART and PORT treatments. Additionally, patients undergoing NART had a lower risk of all SPM (p = 0.01) and second solid cancers (p = 0.02) but a comparable risk of second hematological malignancies (p = 0.55) than patients administered PORT. HR-positive was a risk factor for SPM. No OS, BCSS or SPM risk difference were significantly observed in the 2096 pairs of IORT and PORT groups.ConclusionCompared to PORT, NART and IORT don't offer survival advantages for early-stage breast cancer patients. Altering the sequence of radiotherapy requires careful evaluation.

BACKGROUND:Suspicious calcifications in breast cancer (BC) often limit eligibility for breast-conserving surgery (BCS) after neoadjuvant chemotherapy (NAC). This study assessed the impact of ductal carcinoma in situ (DCIS) status and post-NAC imaging changes on pathological complete response (pCR), BCS feasibility, and prognosis. METHODS:We retrospectively analyzed 163 BC patients with suspicious calcifications treated with NAC (median follow-up, 38.9 months). Logistic regression identified predictors of pCR, associations between calcification changes and pCR were assessed using Cramer's V, and OS and DFS were evaluated using Kaplan-Meier analysis. RESULTS:73 patients had DCIS and 90 had non-DCIS. Calcification reduction after NAC was more frequent in non-DCIS group (56.7%; p = 0.012). pCR rates were higher in non-DCIS group than in DCIS group (73.7% vs 26.3%; p = 0.015). After adjustment, DCIS was associated with reduced pCR rates (OR: 0.26, 95% CI: 0.08-0.73). Overall BCS rate was 11%. Calcification reduction showed a weak correlation with pCR (Cramer's V = 0.321). No significant OS, DFS, or BCS differences were observed by DCIS status or calcification change within follow-up. CONCLUSION:DCIS is associated with reduced pCR after NAC. Calcification findings alone should be interpreted cautiously, and BCS feasibility should be assessed using comprehensive surgical criteria.

Background:Adding immune checkpoint inhibitors (ICIs) to neoadjuvant chemotherapy (NAC) enhances systemic efficacy in triple-negative breast cancer (TNBC). However, its impact on the survival outcomes of axillary surgical de-escalation remains undefined. This study evaluates whether chemo-immunotherapy mitigates survival risks historically associated with omitting axillary lymph node dissection (ALND) for sentinel lymph node biopsy (SLNB) in clinically node-positive (cN+) disease. Methods:In this retrospective cohort study using the National Cancer Database (2018-2022), we identified women with cN1-3, cM0 TNBC who received NAC ± ICIs and achieved ypN0 (axillary pathological complete response), followed by axillary surgery (SLNB or ALND). Overall survival (OS) was evaluated using restricted mean survival time (RMST) and propensity score matching. Multivariable Cox models assessed the independent effect of surgical extent (SLNB vs. ALND) on OS. Results:Out of 1,315,170 breast cancer cases, 4,336 eligible patients were included. The therapeutic regimen significantly interacted with the survival impact of axillary de-escalation. With NAC alone, SLNB was independently associated with inferior OS compared to ALND [5-year OS: 83.0% vs. 87.8%, P = .027; adjusted hazard ratio (aHR)=1.63, 95% CI = 1.12-2.38, P = .01]. Strikingly, adding ICIs neutralized this disparity: in the NAC+ICI cohort, SLNB yielded OS comparable to ALND (5-year OS: 90.1% vs. 93.6%, P = .99; identical 48-month RMST), with no significant survival detriment in multivariable analysis (aHR=1.19, 95% CI = 0.54-2.61, P = .67). Conclusions:The enhanced systemic control conferred by ICIs appears to compensate for the reduced surgical clearance of the axilla when ALND is omitted, effectively mitigating the survival risks associated with omitting ALND in cN+ TNBC. These real-world findings suggest modern chemo-immunotherapy facilitates axillary de-escalation without compromising overall survival, establishing a compelling rationale for prospective clinical trials.

Tall Cell Carcinoma with Reversed Polarity (TCCRP) is a rare and distinct subtype of invasive breast carcinoma, first described in 2003. It is histologically characterized by tall columnar epithelial cells with reversed nuclear polarity and shares morphological features with papillary thyroid carcinoma (PTC). However, its unique molecular signature, including IDH2 and PIK3CA mutations, differentiates it from other breast cancer subtypes. A retrospective systematic study of 91 published cases of TCCRP was conducted, including two cases from our institution. Clinical, pathological, molecular, and treatment-related data were collected and analyzed. Descriptive statistics and Kaplan-Meier survival analysis were employed to evaluate disease-free survival (DFS) and overall survival (OS). Subgroup analyses explored associations between clinical features, molecular markers, and outcomes. The median age at diagnosis was 64 years, with a predominance of small tumors (mean size: 10.4 mm, T1 stage). Histologically, hallmark features included reversed nuclear polarity (100 %), nuclear grooves, and intranuclear pseudoinclusions. Immunohistochemical analysis confirmed a triple-negative profile (ER-/PR-/HER2-) in most cases, with consistent breast-specific marker expression (GATA3, CK7). Molecular testing revealed frequent IDH2 R172 (84.6 %) and PIK3CA (72.5 %) mutations. Surgical management, predominantly breast-conserving surgery (BCS), was the primary treatment, with adjuvant therapies rarely utilized. At a median follow-up of 35.8 months, recurrence occurred in only 2.2 % of cases, and the overall survival rate was 100 %. TCCRP is a rare, low-grade breast cancer subtype with a favorable prognosis and low recurrence risk based on currently available data, but longer follow-up studies are needed to confirm this observation. Its distinct histological and molecular features enable accurate diagnosis and differentiation from other breast cancers and metastatic thyroid carcinoma. Given its indolent nature, conservative treatment strategies, including BCS, are effective, and adjuvant therapies can be minimized. Future research should explore targeted therapies for IDH2 and PIK3CA mutations to expand treatment options for this unique subtype.

BACKGROUND:Angiosarcoma, a rare and highly aggressive malignancy originating from vascular endothelial cells, is characterized by its rapid progression, high invasiveness, and poor prognosis. Due to the limited understanding of its tumor microenvironment (TME) and the absence of effective treatments, further research is essential to elucidate its pathogenic mechanisms and improve therapeutic strategies. OBJECTIVE:This study aims to characterize the cellular heterogeneity and unique TME of primary breast angiosarcoma using single-cell RNA sequencing (scRNA-seq), to identify potential therapeutic targets and improve clinical outcomes. METHODS:Tumor samples were obtained from a patient with bilateral primary breast angiosarcoma and two patients with invasive breast cancer. Single-cell RNA sequencing (scRNA-seq) was conducted to capture the transcriptomic profiles of individual cells within the tumor samples. Following stringent quality control, a total of 31,771 cells were analyzed using comprehensive bioinformatics approaches. Cell populations were identified and classified into distinct cell types, and differential gene expression analysis was performed to explore key signaling pathways. Functional enrichment analysis was used to identify pathways related to tumor progression and immune evasion. Additionally, cell-cell communication networks were mapped to understand interactions within the TME, with a focus on pathways that may serve as therapeutic targets. RESULTS:The scRNA-seq analysis revealed significant differences in the distribution of perivascular cells, fibroblasts, T cells, endothelial cells, and myeloid cells in breast angiosarcoma compared to invasive breast cancer. Key pathways enriched in angiosarcoma samples included growth factor binding, platelet-derived growth factor binding, and ribosome biogenesis, with abnormal expression of several ribosomal proteins. Notably, genes such as FAT4, KDR, FN1, and KIT were highly expressed in angiosarcoma endothelial cells, correlating with poor prognosis. Cell communication analysis highlighted the CXCL12-CXCR4 axis as a crucial mediator of the TME in angiosarcoma. CONCLUSION:This study provides critical insights into the TME of primary breast angiosarcoma, highlighting potential molecular targets and pathways for therapeutic intervention. These findings may inform the development of more effective treatment strategies for this rare and challenging tumor type.

BackgroundBreast cancer (BC) is the most common malignancy among women and shows significant heterogeneity in its prognosis. Among the subtypes, triple-negative breast cancer (TNBC) has the poorest prognosis. Despite advancements in molecular stratification tools, such as Oncotype DX and MammaPrint, prognostic models based on chromosomal instability are still insufficient. The centromere protein (CENP) family, which plays a crucial role in maintaining genomic stability, is associated with tumor progression due to aberrant expression.MethodsIn this study, we integrated multi-omics data, including RNA transcriptomic profiles and single-cell RNA sequencing, to identify gene modules linked to CENPA using weighted gene co-expression network analysis (WGCNA). We developed a prognostic model employing Cox regression and the LASSO algorithm. Validation was performed on independent cohorts, and the model's performance was tested by stratifying patients into high- and low-risk groups based on their five-year survival rates (p < 0.001).ResultsThe prognostic model effectively identified high- and low-risk patient groups, with the high-risk group showing significantly reduced five-year survival. Single-cell analysis revealed that CENPA-high subpopulations were enriched in proliferative tumor cells and were associated with an immunosuppressive tumor microenvironment.ConclusionThis study is the first to establish a CENP-based prognostic model for BC, offering novel biomarkers and potential therapeutic targets for personalized treatment. Additionally, the biological function of the key molecule MMP1 was validated through both in vitro and in vivo experiments.

BACKGROUND:Oncoplastic breast-conserving surgery (OBCS) improves satisfaction in patients who would fare otherwise sub-optimal cosmetic outcomes while bringing challenges in tumor-bed identification during adjuvant radiotherapy. The ultra-hypofractionated breast radiotherapy further shortens treatment sessions from moderately hypofractionated regimens. To circumscribe the difficulty in tumor-bed contouring and the additional toxicity from larger boost volumes, the authors, propose to move forward with the boost session preoperatively from the adjuvant radiation part. Thus, the present study aims to evaluate the feasibility of a new treatment paradigm of preoperative primary-tumor boost before breast-conserving surgery (BCS) or OBCS followed by adjuvant ultra-hypofractionated whole-breast irradiation (u-WBRT) for patients with early-stage breast cancer. METHODS:There was a phase II study. Patients younger than 55 years old, with a biopsy confirmed mono-centric breast cancer, without lymph node involvement were enrolled. A preoperative primary-tumor boost was given by a single 10 Gy in 1 fraction, and BCS or OBCS was conducted within 2 weeks afterwards. Adjuvant u-WBRT (26 Gy/5.2 Gy/5 f) was given in 6 weeks postoperatively without any boost, after the full recovery from surgery. Surgical complications and patient-reported outcomes, as assessed via Breast-Q questionnaires, were documented. A propensity score matching approach was employed to identify a control group at a 1:1 ratio for BREAST-Q outcomes comparison. RESULTS:From May 2022 to September 2023, 36 patients were prospectively enrolled. Surgical complications were observed in seven cases (19.4%), including three cases with Clavien-Dindo (CD) grade 1-2 and four cases with CD grade 3 complications. All but four patients (11.1%) started the planned u-WBRT within 1 week after the predefined due dates postoperatively (≤49 days). Four patients (11.1%) developed grade 2 radiodermatitis after chemotherapy initiation. Compared to the study group, the control patients reported higher scores in chest physical well-being ( P =0.045) and in their attitudes towards arm swelling ( P =0.01). No significant difference was detected in the other of domains (Satisfaction with Breasts, Sexual and Psychosocial Well-Being, and Adverse Effects of Radiation). With a median follow-up period of 9.8 months (2.4-18.9 months), none had any sign of relapse. CONCLUSION:This Phase II clinical trial confirmed the technical and safety feasibility of a novel radiation schedule in patients undergoing BCS or OBCS. According to the BREAST-Q questionnaire, patients who underwent novel radiation schedules reported lower satisfaction in chest physical well-being. A randomized controlled trial is necessary to further investigate these findings. Additionally, long-term follow-up is required to assess oncological outcomes.

ObjectiveTo assess the global and Chinese disease burden of early-onset lung cancer(diagnosed in patients aged 15-49 years) and its major risk factors.MethodsBased on the GLOBOCAN 2022 and Global Burden of Disease(GBD) 2021 datasets, we evaluated the disease burden and associated risk factors of early-onset lung cancer globally and in China, stratified by age, sex, geographic location, and human development index(HDI). Key indicators included age-standardized incidence rate(ASIR), age-standardized mortality rate(ASMR), and disability adjusted life years(DALYs) attributable to risk factors.ResultsIn 2022, there were 137 705 new cases and 72 646 deaths from early-onset lung cancer globally, with ASIR and ASMR of 3.43 per 100 000 and 1.82 per 100 000 population, respectively. The disease burden was higher in males than in females(ASIR: 3.72 per 100 000 vs. 3.14 per 100 000; ASMR: 2.31 per 100 000 vs. 1.33 per 100 000). High-HDI regions exhibited the highest ASIR(5.51 per 100 000) and ASMR(2.57 per 100 000), with health inequality analysis revealing a concentration of disease burden in higher-HDI areas. China bore the heaviest burden, accounting for 48.69% of global new cases and 35.77% of deaths. China's ASIR(8.21 per 100 000) and ASMR(3.17 per 100 000) exceeded global averages, with incidence higher in females(8.78 per 100 000 vs. 7.67 per 100 000) but mortality higher in males(4.01 per 100 000 vs. 2.29 per 100 000). Smoking and ambient particulate matter pollution were the leading risk factors globally(DALYs contribution: 42.01% and 15.62%) and in China(DALYs contribution: 46.78% and 20.84%). Globally, household air pollution ranked third, whereas in China, secondhand smoke replaced it as the third leading risk factor, with household air pollution dropping to fifth. Risk factor profiles varied significantly across age groups, with modifiable risks contributing less to disease burden in the 15-24 age group.ConclusionsThe burden of early-onset lung cancer varies markedly by sex, region, and HDI, with China facing a disproportionately high burden. Policymakers should prioritize equitable resource allocation and targeted interventions, particularly in tobacco control and air pollution mitigation, to enhance cancer prevention and control efforts.

BackgroundTumor progression and chronic postsurgical pain (CPSP) in patients with breast cancer are both significantly influenced by inflammation. The associations between immunoinflammatory biomarkers and long-term survival, as well as CPSP, remain ambiguous. This study examined the predictive value of immunoinflammatory biomarkers for both long-term survival and CPSP.MethodsData on the clinicopathological characteristics and perioperative peripheral blood immunoinflammatory biomarkers of 80 patients who underwent breast cancer surgery were retrospectively collected. Optimal cut-off values for preoperative immunoinflammatory biomarkers, including the preoperative systemic immune-inflammation index (SII), systemic inflammation response index (SIRI), neutrophil-to-lymphocyte ratio (NLR), and pan-immune-inflammation value (PIV), were established via receiver operating characteristic (ROC) curves. Kaplan−Meier curves and Cox regression analysis were used to evaluate the relationships between preoperative immunoinflammatory biomarkers and long-term survival. The relationships among the perioperative neutrophil count (NEU), monocyte count (MONO), lymphocyte count (LYM), platelet count (PLT), SII, SIRI, NLR, PIV, dynamic changes in peripheral blood cell counts, and CPSP were further assessed using logistic regression analysis.ResultsKaplan−Meier curves revealed a considerable prolongation of disease-free survival (DFS) and overall survival (OS) in the low preoperative SII, SIRI, NLR, and PIV groups. Multivariate Cox regression analysis revealed that only an elevated preoperative SIRI was an independent risk factor for postoperative DFS (HR=8.890, P=0.038). The incidence of CPSP was 28.75%. Univariate logistic regression analysis revealed that body mass index (BMI), postoperative NEU, MONO, SIRI, and PIV were negatively correlated with the occurrence of CPSP, whereas subsequent multivariate logistic regression analysis revealed that only BMI was independently associated with CPSP (OR=0.262, P=0.023).ConclusionElevated preoperative SIRI was an independent risk factor for poor DFS in breast cancer patients after surgery. In contrast, perioperative immunoinflammatory biomarkers had limited potential for predicting CPSP in patients who underwent breast cancer surgery.

Background:Breast cancer (BC) remains a significant global public health challenge, and its incidence and mortality rates among adolescents and young adults (AYAs) aged 15-39 years are increasing. Compared with older adults, AYAs often face poorer prognoses and a higher disease burden. Understanding the trends and determinants of BC burden in AYAs is crucial for guiding preventive measures, early detection programs, and treatment strategies. The aim of this study is to systematically investigate the trends and distribution of the BC burden among AYAs aged 15-39 years across regions and countries and identify the contributing risk factors and disparities in incidence, mortality, and disability-adjusted life years (DALYs). Methods:Data on BC were collected from the Global Burden of Disease (GBD) 2021 database. The number of cases, age-standardized rates, mortality, and DALYs for BC were assessed for 204 countries and territories from 1990 to 2021. Joinpoint regression analysis was used to calculate the average annual percentage changes (AAPCs) in incidence, mortality, and DALYs. Risk factors that contribute to the BC burden were also evaluated. Results:According to GBD 2021 estimates, 180,791 new BC cases and 42,055 related deaths were observed among AYAs globally. Between 1990 and 2021, the global incidence rate increased by 33.4%, with the highest incidence observed in regions with a high sociodemographic index (SDI) and the highest mortality rates in low-SDI regions. Incidence rates in women showed a significant upward trend (AAPC, 3.03) and peaked in North Africa and the Middle East, whereas the most rapid increase in incidence in men was noted in East Asia (AAPC, 4.87). Projections indicated a decline in age-standardized incidence rates across most European countries by 2050, in contrast to rising trends in Asia and Africa. Risk factor analysis identified dietary risks (10.5%), tobacco smoking (2%), and high fasting plasma glucose (1.6%) as major contributors to DALYs. Conclusions:The global burden of AYA BC has increased significantly, particularly in regions with a middle and low SDI. The findings highlight the need for targeted preventive interventions for high-risk populations and provide critical insights for developing regional control strategies.