Abstract Background: Radiation Therapy (RT) is known to modulate the immune system and contribute to the generation of anti-tumor T cells . However, this anti-tumor-activity is countered by radiation-induced immunosuppression (RIIS), which destroys highly radiosensitive existing and newly formed lymphocytes (80% T cells). Optimizing RT treatment planning by considering circulating blood and lymphatics as a critical organ at risk may mitigate RIIS and lead to the creation and preservation of cytotoxic T lymphocytes, potentially converting the tumor from immunologically cold to a hot environment thereby increasing the efficacy of immunotherapy. Methods: We conducted a phase 2 randomized trial from 2020 to 2023, enrolling 51 stage I lung cancer patients treated with SBRT alone, to evaluate whether reducing the dose to circulate blood, lymphatics, and bone marrow could lower RIIS. Patients with baseline absolute lymphocyte counts (ALC) below 0.5x10⁹ cells/L were excluded. Participants were randomized into two groups: an experimental arm with RIIS-optimized treatment (lowering the dose to blood and lymphatic-rich organs) and a standard SBRT arm. All treatment plans followed national protocol guidelines. Peripheral blood samples were collected at baseline, end of treatment, 4 weeks and 6 months post-treatment. Contrasts within repeated measures models were used to determine the statistical significance. Results: Post SBRT ALC changes from baseline immediately, 4 weeks and 24 weeks post SBRT are: optimized arm: -16%, -22%, -16%, standard arm: -31%, -34% and -26%, leading to an overall-all-time-point improvement in ALC reduction in the optimized arm compared to the standard arm of 13.4 (5.3)%, 95% confidence interval [CI], 2.8 to 24.0; p = 0.01. Central tumors had the largest improvements, with ALC changes from baseline in the optimized arm of only -8%, -18%, -14% , and -39%, -43%, -47% in the standard arm, leading to an overall-all-time-point improvement in ALC reduction in the optimized arm compared to the standard arm of 29.5 (9.6)%, 95% confidence interval [CI], 10.1 to 48.9; p = 0.004. In the standard arm, 15.4% of patients experienced post-SBRT grade- 3 lymphopenia, while none in the optimized arm were lymphopenic. Two and a half times as many patients in the optimized arm observed a post SBRT ALC increase compared to the standard arm. In a multivariate Cox regression analysis, a trend towards increased Event Free Survival (two-year: 75.0% (SE = 10.8%) versus 59.8% (SE = 11.2%), p=0·095) and Overall Survival (two-year: 93.4% (SE=6.1%) versus 69.4% (SE=10.5%), p=0·135) was observed with optimized planning compared to status quo in treatment naïve patients. Conclusion: Reducing RT dose to blood and immune rich organs provided a significant reduction in RIIS compared to standard of care. Observed increase in OS and EFS needs further confirmation from a phase 3 trial. This has implications in enhancing immune system mediated anti-tumor activity. (Funded by National Cancer Institute and others. ClinicalTrials.gov number, NCT04273893). Citation Format: Krishni Wijesooriya, James Larner, Paul Read, Cam Nguyen, Mark Conaway, Timothy Showalter.Sparing blood and immune rich organs significantly reduces immune suppression during lung SBRT: Randomized, Phase 2 trial.[abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Targeted Therapies in Combination with Radiotherapy; 2025 Jan 26-29; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2025;31(2_Suppl):Abstract nr P014

Background:Conventional methods for detecting lung cancer early are often qualitative and subject to interpretation. Radiomics provides quantitative characteristics of pulmonary nodules (PNs) in medical images, but variability in medical image acquisition is an obstacle to consistent clinical application of these quantitative features. Correcting radiomic features' dependency on acquisition parameters is problematic when combining data from benign and malignant PNs, as is necessary when the goal is to diagnose lung cancer, because acquisition effects may differ between them due to their biological differences. Purpose:We evaluated whether we must account for biological differences between benign and malignant PNs when correcting the dependency of radiomic features on acquisition parameters, and we compared methods of doing this using ComBat harmonization. Methods:This study used a dataset of 567 clinical chest CT scans containing both malignant and benign PNs. Scans were grouped as benign, malignant, or lung cancer screening (mixed benign and malignant). Preprocessing and feature extraction from ROIs were performed using PyRadiomics. Optimized Permutation Nested ComBat harmonization was performed on extracted features to account for variability in four imaging protocols: contrast enhancement, scanner manufacturer, acquisition voltage, focal spot size. Three methods were compared: harmonizing all data collectively in the standard manner, harmonizing all data with a covariate to preserve distinctions between subgroups, and harmonizing subgroups separately. A significant (p ≤ 0.05) Kruskal-Wallis test determined whether harmonization removed a feature's dependency on an acquisition parameter. A LASSO-SVM pipeline was trained using acquisition-independent radiomic features to predict whether PNs were malignant or benign. To evaluate the predictive information made available by each harmonization method, the trained harmonization estimators and predictive model were applied to a corresponding unseen test set. Harmonization and predictive performance metrics were assessed over 10 trials of 5-fold cross validation. Results:Kruskal-Wallis defined an average 2.1% of features (95% CI: 1.9-2.4%) as acquisition-independent when data were harmonized collectively, 27.3% of features (95% CI: 25.7-28.9%) as acquisition-independent when harmonized with a covariate, and 90.9% of features (95% CI: 90.4-91.5%) as acquisition-independent when harmonized separately. LASSO-SVM models trained on data harmonized separately or with a covariate had higher ROC-AUC for lung cancer screening scans than models trained on data harmonized without distinction between benign and malignant tissues (Delong test, Holm-Bonferroni adjusted p ≤ 0.05). There was not a conclusive difference in ROC-AUC between models trained on data harmonized separately and models trained on data harmonized with a covariate. Conclusions:Radiomic features of benign and malignant PNs require different corrective transformations to recover acquisition-independent distributions. This can be done using separate harmonization or harmonization with a covariate. Separate harmonization enabled the greatest number of predictive features to be used in a machine learning model to retrospectively detect lung cancer. Features harmonized separately and features harmonized with a covariate enabled predictive models to achieve similar performance on lung cancer screening scans.

Purpose:Radiation Therapy (RT) can modulate the immune system and generate anti-tumor T cells. However, this anti-tumor-activity is countered by radiation-induced immunosuppression (RIIS). Clinical advantages of proactively sparing RT dose to immune rich organs have not previously been evaluated. Methods:We conducted a phase II randomized trial from 2020 to 2023, enrolling 51 early-stage lung cancer patients treated with SBRT, to evaluate the effect of dose reduction to immune rich organs on RIIS. Two groups were: RIIS-optimized-treatment (lowering the dose to blood, bone-marrow and lymph-node-stations) and standard-treatment. All treatments followed national protocol guidelines. Peripheral blood was collected at baseline, immediately, 4-weeks and 6-months post-treatment. Results:ALC changes from baseline immediately, 4-weeks and 6-months post-SBRT are: optimized-arm: -16%, -22%, -16%, standard-arm: -31%, -34%, -26%, leading to an overall-all-time-point improvement in ALC reduction in the optimized-arm compared to the standard-arm of 13.4 (5.3) % (95% CI, 2.8 to 24.0; p = 0.01). Central tumors had the largest improvement in ALC from baseline: optimized-arm: - 8%, -18%, -14%, standard-arm: -39%, -43%, -47%, leading to an overall-all-time-point improvement in ALC reduction in the optimized-arm compared to the standard-arm of 29.5 (9.6) % (95% CI, 10.1 to 48.9; p = 0.004). Grade 3 lymphopenia occurred in 15.4% of standard arm patients but was absent in the optimized arm. Additionally, 2.8 times more patients in the optimized arm experienced an ALC increase post-SBRT. Dose to organs such as the heart, great vessels, thoracic spine, and lymph nodes significantly correlated with RIIS. A trend towards increased Event-Free-Survival (two-year: 75.0% (SE = 10.8%) versus 59.8% (SE = 11.2%), p =0·10) and Overall Survival (two-year: 93.4% (SE=6.1%) versus 69.4% (SE=10.5%), p =0·14) was observed with optimized-planning compared to standard-planning in treatment naïve patients. Conclusion:Reducing RT dose to immune rich organs significantly reduces RIIS compared to standard-of-care. This has implications in enhancing immune system mediated anti-tumor-activity. (Funded by National Cancer Institute and others. ClinicalTrials.gov number, NCT04273893 ).

Background: Stereotactic body radiation therapy (SBRT) is known to modulate the immune system and contribute to the generation of anti-tumor T cells and stimulate T cell infiltration into tumors. Radiation-induced immune suppression (RIIS) is a side effect of radiation therapy that can decrease immunological function by killing naive T cells as well as SBRT-induced newly created effector T cells, suppressing the immune response to tumors and increasing susceptibility to infections. Purpose: RIIS varies substantially among patients and it is currently unclear what drives this variability. Models that can accurately predict RIIS in near real time based on treatment plan characteristics would allow treatment planners to maintain current protocol specific dosimetric criteria while minimizing immune suppression. In this paper, we present an algorithm to predict RIIS based on a model of circulating blood using early stage lung cancer patients treated with SBRT. Methods: This Python-based algorithm uses DICOM data for radiation therapy treatment plans, dose maps, patient CT data sets, and organ delineations to stochastically simulate blood flow and predict the doses absorbed by circulating lymphocytes. These absorbed doses are used to predict the fraction of lymphocytes killed by a given treatment plan. Finally, the time dependence of absolute lymphocyte count (ALC) following SBRT is modeled using longitudinal blood data up to a year after treatment. This model was developed and evaluated on a cohort of 64 patients with 10-fold cross validation. Results: Our algorithm predicted post-treatment ALC with an average error of 0.24 +/- 0.21 x 10(9) of 0.24 +/- 0.21 x 10(9) cells/L with 89% of the patients having a prediction error below 0.5 x 109 cells/L. The accuracy was consistent across a wide range of clinical and treatment variables. Our model is able to predict post-treatment ALC < 0.8 (grade 2 lymphopenia), with a sensitivity of 81% and a specificity of 98%. This model has a similar to 38-s end-to-end prediction time of post treatment ALC. Conclusion: Our model performed well in predicting RIIS in patients treated using lung SBRT. With near-real time model prediction time, it has the capability to be interfaced with treatment planning systems to prospectively reduce immune cell toxicity while maintaining national SBRT conformity and plan quality criteria.

8060 Background: Genomic testing is important for early-stage NSCLC due to benefits of adjuvant EGFR and ALK targeted therapies and implications for neoadjuvant immunotherapy decisions. The purpose of this study is to evaluate the completion rates and timeliness of NGS prior to treatment initiation for patients with stage II-III NS-NSCLC, with reflex NGS testing protocols in place. Methods: Patients with stage II-III NS-NSCLC diagnosed between 2015 and 2022 at UVA Cancer Center were identified retrospectively. A reflex tissue-based NGS testing protocol was initiated at UVA in early 2015 using in-house TruSight Tumor and later PGDx platforms. Targeted pyrosequencing was performed in cases of NGS failures. The primary outcomes of the study were to evaluate the NGS completion rate and median time from biopsy to results and to any first line treatment (1L), including surgery, radiation, or systemic therapy. Actionable mutation incidence, proportion of patients with test results prior to treatment, and overall survival (OS) were all assessed. Statistical analysis included both descriptive statistics and Kaplan-Meier methodology for overall survival (OS). Results: 171 patients met eligibility, 92 (54%) female, 80 (47%) stage II and 91 (53%) stage III. 159 (93%) had known 1L start dates and 99 (58%) received systemic therapy with known dates. Testing completion rates and time to results are shown in the table. Actionable mutations identified included: KRAS 39% (G12C 15%), EGFR 7%, BRAF 4%, MET 2%, RET 1%, and NTRK 1%. There was no difference in NGS success rates between patients with stage II and III diseases, X2 (1, N = 171) = 2.667, p = 0.102. Median OS was 64.1 months in those with complete NGS testing and 53.4 months in those without complete NGS (p=0.222). Conclusions: Reflexive, in-house NGS resulted in a shorter median time from biopsy to results (17 days) and higher completion rate (NGS, 77%; at least limited testing, 92%) compared to historical controls. The majority of patients had NGS results available to inform systemic therapy decisions (69%). While OS was numerically higher for patients with complete NGS, this was not statistically significant. Reflex NGS testing protocols increase the likelihood of obtaining timely results in the new era of adjuvant tyrosine kinase inhibitors and neoadjuvant chemotherapy and immunotherapy. [Table: see text]

Repair of DSB induced by IR is primarily carried out by Non-Homologous End Joining (NHEJ), a pathway in which 53BP1 plays a key role. We have discovered that the EMT-inducing transcriptional repressor ZEB1 (i) interacts with 53BP1 and that this interaction occurs rapidly and is significantly amplified following exposure of cells to IR; (ii) is required for the localization of 53BP1 to a subset of double-stranded breaks, and for physiological DSB repair; (iii) co-localizes with 53BP1 at IR-induced foci (IRIF); (iv) promotes NHEJ and inhibits Homologous Recombination (HR); (v) depletion increases resection at DSBs and (vi) confers PARP inhibitor (PARPi) sensitivity on BRCA1-deficient cells. Lastly, ZEB1's effects on repair pathway choice, resection, and PARPi sensitivity all rely on its homeodomain. In contrast to the well-characterized therapeutic resistance of high ZEB1-expressing cancer cells, the novel ZEB1-53BP1-shieldin resection axis described here exposes a therapeutic vulnerability: ZEB1 levels in BRCA1-deficient tumors may serve as a predictive biomarker of response to PARPis.

Supplementary Figure Legends

Structure of drugs used in this manuscript

Background Despite its common epigenetic suppression in multiple cancers, STING signaling has emerged as a major pathway for augmenting tumor cell antigenicity and initiation of T cell responses.1 2 Another aspect of intact activation of STING signaling in tumor cells is downstream induction of T cell-homing chemokines including CXCL10 and CCL5. These chemokines are also among our earlier reported 12-chemokine (12-CK) gene expression signature (GES) predicting the presence of tumor-localized tertiary lymphoid structures (TLSs), which are increasingly shown to correlate with improved survival in certain solid tumor types.3 4 Based on these findings, we hypothesized that epigenetic silencing of STING signaling genes through promoter hypermethylation would be inversely associated with the presence of TLSs. Methods We assessed the correlation between the expression of STING signaling genes and the chemokines present in the 12-CK GES across melanomas and urothelial bladder carcinomas using cBioPortal datasets. To extend these studies beyond these tumor types, we performed correlative and survival analyses using the TCGA PanCancer Atlas. Additionally, we determined the correlation between the promoter methylation levels of STING signaling genes and the 12-CK GES score. We also evaluated STING expression in TLS+ and TLS- melanoma samples in situ by immunohistochemistry (IHC). Results We identified a distinct correlation between STING-expressing tumors and each of the twelve chemokines among melanoma and urothelial bladder carcinoma samples. In particular, STING expression was positively correlated with secondary lymphoid organ-associated chemokines, CCL19 (p=0.0077), CCL21 (p=0.0046), and CXCL13 (p=0.0034) in urothelial bladder carcinomas. The presence of TLSs in STING-expressing melanomas was further confirmed by IHC. Using TCGA PanCancer datasets, we observed a strong correlation between the expression of cGAS (Pearson’s r=0.46) and STING (Pearson’s r=0.37) with the 12-CK GES score. In contrast, the methylation levels of cGAS and STING were inversely correlated with the 12-CK GES score (Pearson’s r=-0.37 and -0.41, respectively). Similarly, hypermethylation of STING was correlated with inferior disease-specific survival (DSS) (p<0.0001) in lung adenocarcinomas. Survival analysis on the TCGA skin cutaneous melanoma (SKCM) dataset also indicated significant DSS advantage in 12-CK GES scoreHigh cGASHighpatients (p<0.0001). Conclusions We provide evidence that epigenetic state of cGAS and STING cannot only shape tumor antigenicity but is also associated with the 12-CK GES and the presence of TLSs. Considering the well-established prognostic value of TLSs, these findings argue that targeting epigenetic suppression of STING signaling should be considered as a strategy to guide effective immunotherapy-based interventions. Acknowledgements This work was supported by the Moffitt Cancer Center Tissue Core and Analytic Microscopy Core Facilities, all comprehensive cancer center facilities designated by the National Cancer Institute (P30 CA076292). This work was funded by: NCI-NIH (1R01 CA148995, 1R01 CA184845, P30 CA076292, P50 CA168536), CJG Fund, Chris Sullivan Fund, V Foundation, Melanoma Research Foundation, and Dr. Miriam and Sheldon G. Adelson Medical Research Foundation. References Falahat R, Berglund A, Putney RM, Perez-Villarroel P, Aoyama S, Pilon- Thomas S, Barber GN, Mulé JJ. Epigenetic reprogramming of tumor cell-intrinsic STING function sculpts antigenicity and T cell recognition of melanoma. PNAS. 2021;118(15). Falahat R, Berglund A, Perez-Villarroel P, Putney RM, Hamaidi I, Kim S, Pilon-Thomas S, Barber GN, Mulé JJ. Epigenetic state determines the in vivo efficacy of STING agonist therapy. Nature Communications. 2023;14(1):1573. Messina JL, Fenstermacher DA, Eschrich S, Qu X, Berglund AE, Lloyd MC, Schell MJ, Sondak VK, Weber JS, Mulé JJ. 12-Chemokine gene signature identifies lymph node-like structures in melanoma: potential for patient selection for immunotherapy?. Scientific reports. 2012;2(1):765. Schumacher TN, Thommen DS. Tertiary lymphoid structures in cancer. Science. 2022;375(6576):eabf9419.

The study analysis plan, Figures S1-S6, Table S1

PDF file - 19 KB, Supplemental Table 1. Sequence of primers designed for RT-qPCR amplification of p53 regulated genes. Supplementary Table 2. Sequence of primers designed for amplification of genomic DNA of p53 regulated genes containing or in close proximity to p53BS.

Legend for Supplementary Figure S1.

LNCaP cells were infected with lentivirus to overexpress Plk1, treated as indicated, tested for cell Viability.

Objective:Because time to treatment has been shown to be associated with increase in the risk of death for Non Small Cell Lung Cancer (NSCLC) patients, we examined the prevalence and magnitude of racial disparities in mean time to radiation therapy (TTRT) for Stage I-III non-small cell lung cancer patients across a variety of treatment facilities.Methods:Utilizing the United States National Cancer Database (NCDB), we determined differences in TTRT between different races and different treatment facilities.Results:Concordant with past research, we found that non-White patients and patients treated at academic facilities, regardless of race, have longer mean TTRT, and that racial disparities in TTRT extend across all treatment facilities (all p<0.05).Conclusions:These findings shed light on the potential presence of and impact of structural racism on patients seeking cancer treatment, and the need for further investigation behind the reasonings behind longer TTI for non-White patients. To elucidate the real-world applicability of these results, further investigation into the societal determinants that perpetuate disparity in time to radiation therapy, and potential interventions in the clinical setting to improve cultural and racial sensitivity among healthcare professionals is recommended.

In the past decade, defective DNA repair has been increasingly linked with cancer progression. Human tumors with markers of defective DNA repair and increased replication stress exhibit genomic instability and poor survival rates across tumor types. Seminal studies have demonstrated that genomic instability develops following inactivation of BRCA1, BRCA2, or BRCA-related genes. However, it is recognized that many tumors exhibit genomic instability but lack BRCA inactivation. We sought to identify a pan-cancer mechanism that underpins genomic instability and cancer progression in BRCA-wildtype tumors. Methods: Using multi-omics data from two independent consortia, we analyzed data from dozens of tumor types to identify patient cohorts characterized by poor outcomes, genomic instability, and wildtype BRCA genes. We developed several novel metrics to identify the genetic underpinnings of genomic instability in tumors with wildtype BRCA. Associated clinical data was mined to analyze patient responses to standard of care therapies and potential differences in metastatic dissemination. Results: Systematic analysis of the DNA repair landscape revealed that defective single-strand break repair, translesion synthesis, and non-homologous end-joining effectors drive genomic instability in tumors with wildtype BRCA and BRCA-related genes. Importantly, we find that loss of these effectors promotes replication stress, therapy resistance, and increased primary carcinoma to brain metastasis. Conclusions: Our results have defined a new pan-cancer class of tumors characterized by replicative instability (RIN). RIN is defined by the accumulation of intra-chromosomal, gene-level gain and loss events at replication stress sensitive (RSS) genome sites. We find that RIN accelerates cancer progression by driving copy number alterations and transcriptional program rewiring that promote tumor evolution. Clinically, we find that RIN drives therapy resistance and distant metastases across multiple tumor types.

Genome-wide association studies (GWASs) for bone mineral density (BMD) in humans have identified over 1100 associations to date. However, identifying causal genes implicated by such studies has been challenging. Recent advances in the development of transcriptome reference datasets and computational approaches such as transcriptome-wide association studies (TWASs) and expression quantitative trait loci (eQTL) colocalization have proven to be informative in identifying putatively causal genes underlying GWAS associations. Here, we used TWAS/eQTL colocalization in conjunction with transcriptomic data from the Genotype-Tissue Expression (GTEx) project to identify potentially causal genes for the largest BMD GWAS performed to date. Using this approach, we identified 512 genes as significant using both TWAS and eQTL colocalization. This set of genes was enriched for regulators of BMD and members of bone relevant biological processes. To investigate the significance of our findings, we selected PPP6R3 , the gene with the strongest support from our analysis which was not previously implicated in the regulation of BMD, for further investigation. We observed that Ppp6r3 deletion in mice decreased BMD. In this work, we provide an updated resource of putatively causal BMD genes and demonstrate that PPP6R3 is a putatively causal BMD GWAS gene. These data increase our understanding of the genetics of BMD and provide further evidence for the utility of combined TWAS/colocalization approaches in untangling the genetics of complex traits.