Zhang, Xu‐Chao

Abstract Background Lung adenocarcinoma in never-smokers is a major public health burden, especially among East Asian women. Polygenic risk scores (PRSs) are promising for risk stratification but are primarily developed in European-ancestry populations. We aimed to develop and validate single- and multi-ancestry PRSs for East Asian never-smokers to improve lung adenocarcinoma risk prediction. Methods PRSs were developed using genome-wide association study summary statistics from East Asian (8002 cases; 20 782 controls) and European (2058 cases; 5575 controls) populations. Single-ancestry models included a PRS with 25 single nucleotide variants (PRS-25), PRS clumping and thresholding (CT), and LDpred2; multi-ancestry models included LDpred2 plus European PRS-128, PRS-CSx, and clumping and thresholding, super learning, empirical Bayes (CT-SLEB). Performance was evaluated in independent East Asian data from the Female Lung Cancer Consortium and externally validated in the Nanjing Lung Cancer Cohort. We assessed predictive accuracy via area under the curve operating procedure (AUC), with 10-year and (ages 30-80 years) absolute risks estimates. Results The best multi-ancestry PRS, using East Asian and European data via CT-SLEB, outperformed the best East Asian-only (LDpred2; AUC = 0.629, 95% confidence interval [CI] = 0.618 to 0.641), achieving an AUC of 0.640 (95% CI = 0.629 to 0.653) and odds ratio of 1.71 (95% CI = 1.61 to 1.82) per standard deviation increase. Nanjing Lung Cancer Cohort validation confirmed robust performance (AUC = 0.649, 95% CI = 0.623 to 0.676). The top 20% PRS group had a 3.92-fold higher lung adenocarcinoma risk than the bottom 20%. Further, the top 5% PRS group reached a 6.69% lifetime absolute risk. Notably, this group reached the average population 10-year lung adenocarcinoma risk at age 50 years (0.42%) by age 41 years, 9 years earlier. Conclusions Multi-ancestry PRS approaches enhance lung adenocarcinoma risk stratification in East Asian never-smokers, with consistent external validation, suggesting future clinical utility.

Abstract Background: In breast cancer, the spatial relationship between immune and tumor cells is increasingly recognized as critical in determining the efficacy of neoadjuvant therapy (NAT). This study investigated how the distribution of immune cells, particularly CD8+ T cells, relative to tumor cells affects treatment outcomes. Methods: Biopsies from 104 breast cancer patients were examined, both pre- and post-NAT, using multiplex immunohistochemistry (mIHC). This study focused on the density and distribution of CD8+ T cells, CD68+ macrophages, FoxP3+ regulatory T cells, and other immune markers. Results: The spatial proximity of CD8+ T cells within 20 µm of cancer cells (N20-CD8+T) was strongly correlated with improved clinical outcomes across diverse tumor subtypes and NAT regimens. A significant post-NAT decrease in CD4+, CD68+, and FoxP3+ cells highlights notable shifts in the tumor immune landscape. A noteworthy finding was the positive correlation between CXCL9 expression and N20-CD8+T cells, suggesting a mechanism for immune cell recruitment and interaction within the tumor microenvironment. These results highlight the complex interplay among NAT, immune cell modifications, and patient outcomes. Conclusions: This study revealed that the proximity of N20-CD8+ T cells to tumor cells is consistently associated with favorable NAT outcomes, transcending tumor subtypes, and treatment differences. This highlights the potential of immune cell dynamics, especially CD8+ T cells, as predictive biomarkers for therapeutic responses in breast cancer, underscoring their vital role in tumor immunity.