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Purpose: We aim to evaluate the prognostic significance of tumor-infiltrating lymphocyte on residual disease (RD-TIL) in HER2+ patients with breast cancer who failed to achieve pathologic complete response (pCR) after anti-HER2+ chemotherapy (CT)-based neoadjuvant treatment (NAT). We assessed the feasibility of combining the prognostic information provided by residual cancer burden (RCB) and RD-TILs into a composite score (RCB+TIL).
Experimental Design: HER2+ patients with breast cancer treated with CT+anti-HER2-based NAT at three institutions were retrospectively included. RCB and TIL levels were evaluated on hematoxylin and eosin-stained slides from surgical samples according to available recommendations. Overall survival (OS) was used as an outcome measure.
Results: A total of 295 patients were included, of whom 195 had RD. RCB was significantly associated with OS. Higher RD-TILs were significantly associated with poorer OS as compared with lower RD-TILs (15% cutoff). In multivariate analysis, both RCB and RD-TIL maintained their independent prognostic value. A combined score, RCB+TIL, was calculated from the estimated coefficient of RD-TILs and the RCB index in a bivariate logistic model for OS. The RCB+TIL score was significantly associated with OS. The C-index for OS of the RCB+TIL score was numerically higher than that of RCB and significantly higher than that of RD-TILs.
Conclusions: We have reported an independent prognostic impact of RD-TILs after anti-HER2+CT NAT, which might underlie an imbalance of the RD microenvironment towards immunosuppressive features. We provided a new composite prognostic score based on RCB+TIL, which was significantly associated with OS and proved to be more informative than the isolated evaluation of RCB and RD-TILs.
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http://dx.doi.org/10.1158/1078-0432.CCR-23-0480 | DOI Listing |
JCO Glob Oncol
May 2025
Department of Biochemistry, All India Institute of Medical Sciences, New Delhi, India.
Purpose: Breast cancer remains a significant public health challenge globally, as well as in India, where it is the most frequently diagnosed cancer in females. Significant disparities in incidence, mortality, and access to health care across India's sociodemographically diverse population highlight the need for increased awareness, policy reform, and research.
Design: This review consolidates data from national cancer registries, global cancer databases, and institutional findings from a tertiary care center to examine the epidemiology, clinical challenges, and management gaps specific to India.
J Med Screen
September 2025
The Cancer Registry of Norway, Department of Screening programs, Norwegian Institute of Public Health, Oslo, Norway.
ObjectiveTo study the implications of implementing artificial intelligence (AI) as a decision support tool in the Norwegian breast cancer screening program concerning cost-effectiveness and time savings for radiologists.MethodsIn a decision tree model using recent data from AI vendors and the Cancer Registry of Norway, and assuming equal effectiveness of radiologists plus AI compared to standard practice, we simulated costs, effects and radiologist person-years over the next 20 years under different scenarios: 1) Assuming a €1 additional running cost of AI instead of the €3 assumed in the base case, 2) varying the AI-score thresholds for single vs. double readings, 3) varying the consensus and recall rates, and 4) reductions in the interval cancer rate compared to standard practice.
View Article and Find Full Text PDFJ Natl Cancer Inst
September 2025
Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, Maryland, United States.
Background: Among childhood cancer survivors, germline rare variants in autosomal dominant cancer susceptibility genes (AD CSGs) could increase subsequent neoplasm (SNs) risks, but risks for rarer SNs and by age at onset are not well understood.
Methods: We pooled the Childhood Cancer Survivor Study and St Jude Lifetime Cohort (median follow-up = 29.7 years, range 7.
PLoS One
September 2025
Institute of Computational Science and Technology, Guangzhou University, Guangzhou, China.
MicroRNAs (miRNAs) are critical regulators of gene expression in cancer biology, yet their spatial dynamics within tumor microenvironments (TMEs) remain underexplored due to technical limitations in current spatial transcriptomics (ST) technologies. To address this gap, we present STmiR, a novel XGBoost-based framework for spatially resolved miRNA activity prediction. STmiR integrates bulk RNA-seq data (TCGA and CCLE) with spatial transcriptomics profiles to model nonlinear miRNA-mRNA interactions, achieving high predictive accuracy (Spearman's ρ > 0.
View Article and Find Full Text PDFPLoS One
September 2025
Department of Hepatobiliary Surgery, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China.
Objective: This study employs integrated network toxicology and molecular docking to investigate the molecular basis underlying 4-nonylphenol (4-NP)-mediated enhancement of breast cancer susceptibility.
Methods: We integrated data from multiple databases, including ChEMBL, STITCH, Swiss Target Prediction, GeneCards, OMIM and TTD. Core compound-disease-associated target genes were identified through Protein-Protein Interaction (PPI) network analysis.