Citations

Abstract Forward genetic screens are powerful tools for novel biological discoveries because they do not require a priori knowledge of genes controlling a phenotype of interest. The Sleeping Beauty (SB) transposon system is one of many commonly employed genetic screen tools used to induce both gain and loss of gene function mutations via insertional mutagenesis. In the past, SB screens have been successfully utilized to discover several cancer driver genes that could serve as potential therapeutic targets. More recently, SB technologies have been extended to other applications, including the discovery of mechanisms contributing to drug resistance and novel targets for immunotherapy. Importantly, existing tools for SB screen data analysis do not support data-driven case–control comparisons capable of analyzing screens with this design. To this end, we developed a network-based common insertion site (NetCIS) analysis tool to robustly identify common insertion sites (CISes) in a case–control phenotype selection screen. NetCIS uses an efficient graph-based algorithm for discovering statistically significant CISes that differ between cases and controls. We benchmark NetCIS against other insertional mutagenesis analysis tools using a previously published SB dataset and show that NetCIS is able to prioritize previous biologically validated genes similarly or better than competing methods, is the only method that effectively utilizes a case–control experimental setup, and can identify CISes involving unannotated regions of the genome that are overlooked by existing methods. Code for NetCIS and an accompanying tutorial can be found at https://github.com/RogersLabGroup/NetCIS.

Abstract Background: Male breast cancer (MaBC) is a rare malignancy, accounting for approximately 1% of all breast cancer cases. Our previous studies suggest that MaBC is biologically distinct from female breast cancer (FeBC), exhibiting a unique mutational profile and immune-genomic microenvironment. While the impact of these molecular alterations on site-specific metastases has been explored in FeBC, it remains poorly understood in MaBC. This gap limits accurate risk stratification and prediction of disease trajectory in male patients. In this study, we investigated site-specific genomic and immune alterations across metastatic sites in MaBC. Methods: 238 MaBC samples were tested by NGS (592, NextSeq; WES, NovaSeq) and WTS (NovaSeq; Caris Life Sciences, Phoenix, AZ). We performed analysis in hormone receptor-positive (HR+) and HER2-negative (HER2-) subtypes which are most common in male. HR+HER2- was defined as estrogen receptor (ER) or progesterone receptor (PR) positive and HER2 IHC 1+ or 2+ with negative chromogenic in situ hybridization (CISH) assay. Immune cells were estimated using WTS deconvolution (Quantiseq). Gene expression profiles were analyzed for T-cell inflamed score, interferon-gamma (IFN-gamma) score and MAPK Activation Score. We classified patients by site of biopsy/specimen site. Statistical significance was assessed with chi-square and Mann-Whitney U tests, p<0.05 is considered statistically significant. Results: Our cohort included 86 HR+HER2- MaBC samples biopsied from primary breast cancer (pBC) (n=39), bone (n=15), liver (n=8), lung (n=8), lymph nodes (n=7), and skin (n=9) mets. We report here only the data on statistically significant differences, but the overall landscape has been depicted across all defined-sites investigated. pBC showed a significantly lower prevalence of PIK3CA mutations (23.6% vs. 53.3%, p<0.05) compared to bone mets. ESR1 mutations were absent in pBC but present in 25% of liver and 25% of lung mets (all comparisons p<0.05). Immune profiling revealed reduced infiltration of M2 macrophages (4.3% vs. 6%, p<0.05) and neutrophil (2.2% vs. 6.9%, p<0.05) in pBC relative to bone Mets. Further, CD4+ T cells were lower in pBC compared to lymph nodes (0% vs. 2.4%, p<0.05). pBC had lower expression of immune checkpoint genes (PDCD1LG2, HAVCR2 and CD47) compared to other mets. pBC exhibited lower MAPK pathway activation score (-1.6 vs. 0.17, p=0.03) and a trend toward lower T cell-inflamed gene expression scores (-65 vs. 8, p=0.06) compared to bone mets. Bone mets had higher infiltration of M2 macrophage compared to lung (6% vs. 4.4%, p<0.05) and lymph node (6% vs. 4.5%, p<0.05). Neutrophil infiltration was elevated in bone versus liver (6.9% vs. 2%, p<0.05) but T regulatory cells were lower in bone compared to lymph nodes (1% vs. 2.4%, p<0.05). Bone showed reduced expression of CD47 (median TPM 50.6 vs. 109.9, p<0.05) compared to skin. Further bone had lower IFN-gamma scores (-0.41 vs. -0.17, p<0.05) compared to lymph node. Data on prior number and types of cancer treatment to give a context to the findings will be presented at the meeting. Conclusions: Our study highlights that each MaBC metastatic site harbors a unique genomic and immune landscape that can influence tumor behavior and potentially impact patient prognosis. Better understanding of metastatic site-specific molecular features in larger cohorts can help in the future research efforts and guiding treatment decisions. Citation Format: D. Trapani, S. Deshmukh, S. Wu, J. Xiu, N. Lin, G. Curigliano, P. Spanheimer, P. Advani, P. Barreto Coelho, M. Lustberg, G. Sledge Jr, S. Tolaney, J. Leone. Site specific Genomic and Immune Landscapes Underpinning in metastatic Male Breast Cancer [abstract]. In: Proceedings of the San Antonio Breast Cancer Symposium 2025; 2025 Dec 9-12; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2026;32(4 Suppl):Abstract nr PS2-08-04.

Abstract Background: Hispanic/Latinx (HL) and African American (AA) breast cancer (BC) patients (pts) have increased prevalence of high-risk features such as incidence of BC at age <50 and estrogen receptor negativity. We previously showed that AA and HL had a lower fraction of neutrophils and M2 macrophages (Mɸ) despite higher percentage of PD-L1 positive cases. This study aims to further characterize differences in the tumor immune microenvironment between racial and ethnic groups, with a focus on how these differences vary by site of biopsy. Methods: We analyzed 19,459 BC samples tested by NGS (592, NextSeq; WES, NovaSeq) and WTS (NovaSeq; Caris Life Sciences). Race/ethnicity data were self-reported by pts. Immune cell proportions were estimated using WTS deconvolution (Quantiseq). Gene expression was analyzed for T-cell inflammed score (TIS), MAPK Activation Score (MPAS) and interferon-gamma (IFNy) score. Real-world overall survival (OS) data were derived from insurance claims, calculated from tissue collection or treatment initiation to last contact, and analyzed using Kaplan-Meier. Statistical significance was assessed by chi-square and Mann-Whitney U test with p-values adjusted for multiple comparisons (q<0.05). Results: There were 9674 Non-Hispanic Whites (NHW) (primary BC, defined as biopsy (bx) from breast) pBC: n=3,537, 36.6%; (metastatic BC, defined as biopsy outside of the breast) mBC: n=6,137 63.4%, 1800 AA (pBC: n=750, 42%, mBC: n=1,050, 58%), and 1795 HL (pBC: n=842, 47%; mBC n=953, 53%) samples. There were 2364 TNBC (66% NHW, 19% NHB, 15% HL), 4318 HR+/HER2- (76% NHW, 11.6% NHB, 12.4% HL), and 893 HER2+ (68% NHW, 15% NHB, 17% HL). In pBC overall, AA had lower median cell fraction (%) of B cells (4.8% vs 5.3%), M2 Mɸ (3.4% vs 4.4%), but higher median cell fraction of dendritic cells (DC) (2.8% vs 2.6%) compared to NHW while HL had lower median cell fraction of M2 Mɸ (3.9% vs 4.4%) and higher median cell fraction of CD8+ T cell (0.4% vs 0.2%), all q<0.05. In pBC, HL had higher IFNy score (-0.3 vs -0.34), while AA had lower MPAS (-1.2 vs -0.96), all q<0.05. In lymph node bx, AA had lower median % of M2 Mɸ (3.4% vs 4.4%, q<0.05). No significant differences were seen in the liver bx by race but notably there were lower median cell fractions of CD4+, CD8+, and regulatory T cells (0.0 across NHW, AA, HL) across all race/ethnicities vs. other biopsy sites. By subtype, TNBC primary bx yielded much of the significant changes with AA having lower median cell fraction of M2 Mɸ (2.49% vs 3.04%, q= 0.01) compared to NHW. In primary bx, AA (35.6 m vs 48.5 m, HR 1.4, 95% CI 1.2-1.5, p<0.001) and HL (42.4 m vs 48.5 m, HR 1.2, 95% CI 1.1-1.4, p<0.001) had worse median OS versus NHW. In lymph node bx, AA also had worse OS (29.2 m vs 37.2 m, HR 1.2, 95% CI 1-1.5, p=0.03) compared to NHW. In liver bx, there was worse mOS overall but no difference by race (NHW 18.65m, AA 18.79m, HL 20.6m, p =0.73). In HR+/HER2- liver bx AA had worse OS (14.2 m vs 20.9 m, HR 1.3, 95% CI 1-1.7, p=0.03) versus NHW. In HER2+ primary bx, HL had worse OS (43.2m vs 66.9m, HR 1.7, 95% CI 1.1-2.6, p=0.009). There was a trend towards worse mOS in TNBC AA patients receiving pembrolizumab (18.42m vs HL 23.69m vs NHW 35.30m; p=0.16) and HER2+ AA patients receiving trastuzumab deruxtecan (AA: 16.06m vs HL: 26.81m vs NHW: not reached; p = 0.05). Conclusions: We found race and biopsy site specific differences in the breast cancer immune microenvironment. AA pts had lower M2 Mɸ in primary and lymph node bx while NHW pts showed higher CD8+ T cell in primary tumors. Liver biopsies exhibited low T cell infiltration across all groups. AA pts had worse mOS in primary and lymph node bx compared to NHW but not in liver bx of which we saw worse mOS in all races. These results highlight the need to consider both race and bx site in treatment decisions. Citation Format: R. Hsu, S. Deshmukh, N. Gyabaah-Kessie, E. Rallos, B. Al-Zubeidy, E. Gonzalez, A. G. Baugh, S. Carrel, M. Li, D. Zavala, A. Martynova, P. Jayachandran, D. Stewart, D. Spicer, S. Wu, J. Xiu, G. W. Sledge Jr., R. L. Mahtani, A. C. Sandoval Leon, S. Gandhi, S. Chumsri, M. Lustberg, M. C. Stern, E. T. Roussos Torres. Immune microenvironment and survival differences among Hispanic and African American breast cancer cases by biopsy site [abstract]. In: Proceedings of the San Antonio Breast Cancer Symposium 2025; 2025 Dec 9-12; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2026;32(4 Suppl):Abstract nr PS3-12-06.

Abstract Objective To develop a comprehensive risk stratification model to identify patients at high risk of cesarean surgical site infection (cSSI) based on information available at the time of hospital discharge. Methods This is a retrospective cohort study based on datasets from two independent level IV academic medical centers to improve generalizability. The first study includes 2336 cesarean deliveries for analysis with 109 instances of cSSI (4.7%). The second study includes 2936 cesarean deliveries with 72 instances of cSSI (2.5%). The first study cohort was utilized for both model training and internal validation, using the 15 shared features present in both datasets. Random search with cross‐validation was used to choose the type of machine learning (ML) model and its hyperparameters, with area under the receiver operating characteristic curve (AUC) as the validation metric. The second study cohort was then used to evaluate testing accuracy (external validation) and generalization capability of this model. The predictive importance of each feature was evaluated using permutation importance applied to the second cohort. Risk stratification cutoff scores were defined based on centiles over the first patient cohort and evaluated on the second cohort. Results The ML model with the highest validation AUC was an XGBoost classifier. This trained model achieved an AUC of 0.78 on the training data and a 0.72 cross‐validated AUC. When tested on data from the second study cohort, it achieved an AUC of 0.69. The features showing the strongest predictive generalization, as measured by permutation importance, were length of hospital stay, primary indication for cesarean delivery, and estimated blood loss. Using the second cohort to test our model, the model shows a 22.7% positive predictive value (PPV) of cSSI among women in the highest risk group, and a 0.8% PPV among women in the bottom risk group, compared with 2.5% cSSI incidence for the study population at large. Conclusion We developed and validated a predictive ML model for cSSI with information available to healthcare professionals at the time of hospital discharge. This model suggests that the most predictive risk factors for cSSI include length of hospital stay, primary indication for cesarean delivery, and estimated blood loss. Additionally, the model provides reasonable risk stratifications for individual patients. This tool may be used for identifying subgroups at higher risk of cSSI and identifying those who may require closer surveillance or clinical intervention.

Abstract Isolated/idiopathic rapid eye movement sleep behavior disorder (iRBD) is a usually prodromal manifestation of neurodegenerative disorders with α-synuclein pathology: Parkinson’s disease (PD), dementia with Lewy bodies (DLB), and multiple system atrophy (MSA). Clinical trials in the iRBD population face substantial barriers: limited access to well-characterized cohorts, inconsistent assessment protocols across centers, and the absence of validated biomarkers of disease burden. The North American Prodromal Synucleinopathy (NAPS) Consortium was established to address these challenges and facilitate clinical trials for neuroprotective therapies targeting synucleinopathy at the earliest known stages. In this multi-site, longitudinal, observational study, nine academic centers across North America will enroll and follow over 500 individuals with iRBD from existing sleep centers. Sixty control participants, matched for age, sex, and race will also be recruited. A harmonized protocol—including a standardized clinical battery assessing motor, cognitive, autonomic, psychiatric, sensory, and sleep function; structured diagnostic adjudication; biospecimen collection; and centralized analysis of both polysomnography and neuroimaging data—is outlined herein and reflects NAPS Stage 2. Each participants completes these assessments annually, and are replaced in the event of phenoconversion. By unifying assessments and expanding geographic reach, NAPS lays the groundwork for efficient, well-powered clinical trials designed to delay or prevent progression of iRBD to overt PD, DLB, or MSA—ultimately enabling earlier, more effective therapeutic intervention for neurodegenerative disease. Registered at clinicaltrials.gov (NCT05826457).

Abstract Background PET visual reads for multi‐center studies are conducted centrally by one or a few experts. In CLARiTI, a broader network of raters will perform the reads, necessitating methods to ensure their accuracy and reliability. Method All ADRC sites ( N = 37) will prospectively acquire amyloid PET scans for 800 cognitively unimpaired and 1200 cognitively impaired participants. Each site can use one of four amyloid PET tracers ([ 18 F]florbetaben, [ 18 F]florbetapir, [ 11 C]PIB, [ 18 F]NAV4694). PET scans will be visually interpreted by ten PET neuroimaging experts located across eight ADRCs, using their preferred hardware, software, and file format (DICOM, NIFTI). Calibration requires readers to perform blinded, independent visual interpretation of 180 amyloid PET scans (30 unique and 15 duplicate scans per tracer), previously read and selected by an expert (Table 1). An even mix of visually non‐elevated and elevated scans were selected, with quantitation spanning ‐26‐123 Centiloids (Figure 1), and 15% were visually borderline (similar proportion to ADNI4), with quantitation spanning 4‐48 Centiloids (mean 21). Kruskal‐Wallis H test showed no significant difference in the distribution of Centiloid values for scans in each tracer group, Χ 2 (3)=2.133, p = 0.545. Result Calibration scans were read by a second expert not serving in CLARiTI. There was 97% concordance and almost perfect agreement between readers (κ=0.932, p <0.001; Figure 2). Discordantly read scans were visually borderline elevated ( N = 2), borderline non‐elevated ( N = 1), and negative ( N = 1), with quantitation of 8‐21 Centiloids (mean 14). Intra‐rater reads were 98% concordant and had almost perfect agreement (κ=0.966, p <0.001). These findings hold promise for scaling‐up visual reads in CLARiTI, and we expect ≥80% concordance and substantial to almost perfect agreement (κ≥0.7) for inter/intra‐rater reliability. Conclusion Calibration is essential for accurate/reliable amyloid PET visual reads in large multi‐center studies with multiple raters. Through the calibration process, we will develop methods to improve the adjudication of borderline/challenging scans and formalize methods for visual reads of amyloid PET tracers that are investigational (i.e., [ 11 C]PIB, [ 18 F]NAV4694). Involving multiple raters across different sites, who use diverse hardware/software/file format combinations, will mirror the natural heterogeneity present in real‐world clinical practice. This calibration set can also serve as a standardized training tool for other studies incorporating amyloid PET visual reads.

Abstract Background PET visual reads for multi‐center studies are conducted centrally by one or a few experts. In CLARiTI, a broader network of raters will perform the reads, necessitating methods to ensure their accuracy and reliability. Method All ADRC sites ( N = 37) will prospectively acquire amyloid PET scans for 800 cognitively unimpaired and 1200 cognitively impaired participants. Each site can use one of four amyloid PET tracers ([ 18 F]florbetaben, [ 18 F]florbetapir, [ 11 C]PIB, [ 18 F]NAV4694). PET scans will be visually interpreted by ten PET neuroimaging experts located across eight ADRCs, using their preferred hardware, software, and file format (DICOM, NIFTI). Calibration requires readers to perform blinded, independent visual interpretation of 180 amyloid PET scans (30 unique and 15 duplicate scans per tracer), previously read and selected by an expert (Table 1). An even mix of visually non‐elevated and elevated scans were selected, with quantitation spanning ‐26‐123 Centiloids (Figure 1), and 15% were visually borderline (similar proportion to ADNI4), with quantitation spanning 4‐48 Centiloids (mean 21). Kruskal‐Wallis H test showed no significant difference in the distribution of Centiloid values for scans in each tracer group, Χ 2 (3)=2.133, p = 0.545. Result Calibration scans were read by a second expert not serving in CLARiTI. There was 97% concordance and almost perfect agreement between readers (κ=0.932, p <0.001; Figure 2). Discordantly read scans were visually borderline elevated ( N = 2), borderline non‐elevated ( N = 1), and negative ( N = 1), with quantitation of 8‐21 Centiloids (mean 14). Intra‐rater reads were 98% concordant and had almost perfect agreement (κ=0.966, p <0.001). These findings hold promise for scaling‐up visual reads in CLARiTI, and we expect ≥80% concordance and substantial to almost perfect agreement (κ≥0.7) for inter/intra‐rater reliability. Conclusion Calibration is essential for accurate/reliable amyloid PET visual reads in large multi‐center studies with multiple raters. Through the calibration process, we will develop methods to improve the adjudication of borderline/challenging scans and formalize methods for visual reads of amyloid PET tracers that are investigational (i.e., [ 11 C]PIB, [ 18 F]NAV4694). Involving multiple raters across different sites, who use diverse hardware/software/file format combinations, will mirror the natural heterogeneity present in real‐world clinical practice. This calibration set can also serve as a standardized training tool for other studies incorporating amyloid PET visual reads.