Tumor Evolution Research Articles

Abstract 5324: Key antiviral response genes mediate the impact of chromosomal instability on breast cancer stemness

Abstract Chromosomal instability (CIN) is a recognized hallmark of cancer, pivotal in tumor evolution and metastasis. Our research unveils CIN as a stress during tumor initiation, uniquely tolerated by activated breast cancer stem cells (aCSCs). Elevated CIN, specific to tumors from aCSCs, contrasts with baseline levels akin to non-stem cell types. This transient increase in CIN, observed in low burden aCSC tumors, diminishes in established disease, suggesting a dynamic induction during initiation. Consist wit this we have observed increase in CIN tolerance in stem-like vs basal-like cells suggesting heterogeneity in response. CIN triggers a specific response, activating proinflammatory cancer autonomous immune signaling. We identified several CIN-induced proinflammatory stem cell-specific genes from our overlap studies. Knockdown assays targeting RSAD2 and PLAU showed a significant decrease in tumorsphere properties, emphasizing their functional relevance for cancer progression. AXL did not show any effect on tumorsphere but was important to tolerate CIN induced due to reversine. Mechanistically, AXL expression was induced by c-Jun stress signaling activation in aCSCs. These antiviral CIN-induced proinflammatory markers, emerge as a vital player in breast cancer progression. This study establishes a foundation for investigating antiviral genes as crucial contributors to cancer. Citation Format: Shahnawaz A. Baba, Samson Mugisha, Shreyas labhsetwar, Richard klemke, Jay Desgrosellier. Key antiviral response genes mediate the impact of chromosomal instability on breast cancer stemness [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5324.

Abstract 2268: CREDAC: Copy number-based reference-free expression deconvolution analysis of cancers

Abstract Introduction: Analyses of bulk RNA sequencing data are central to most large-scale tumor sequencing studies. Bulk expression data represent population averages and its interpretation is confounded by both normal cell contamination and somatic copy number alterations. Several computational methods to deconvolve have been developed recently. However, these methods often rely on a set of cell-type-specific reference signatures and ignore the effect of copy number changes. Methods: To address these issues, we have developed a method that formalizes the relationship between allele-specific copy number, expression and sample purity to deconvolve the expression profiles of tumor and normal cells from bulk RNA-seq in an unbiased manner. Our method was applied to sequencing data produced by the TRACERx consortium, a longitudinal study with multi-region whole-exome and RNA-seq of non-small-cell lung cancers. A total of 414 primary tumor regions and 140 adjacent normal tissue samples from 140 patients with matched DNA and RNA-seq data were processed. Results: We were able to directly deconvolve a median of ~2,000 genes per sample and indirectly infer tumor and normal expression profiles of ~10,000 genes using an scaled and weighted mean approach. The accuracy of the deconvolution was validated using (1) in-silico mixtures of patient-derived tumor and normal cells, (2) pseudo-bulk scRNAseq and (3) in regions with loss of heterogeneity (LOH) directly on the bulk sequencing data, where the total fraction of expression attributed to tumor cells can be computed directly using somatic mutations. CREDAC allows for single sample bulk-level tumor-normal differential expression analysis and revealed a strong and constitutive genome-wide overexpression in cancer compared to admixed normal cells, with a more pronounced overexpression in lung squamous cell carcinoma than lung adenocarcinoma (p<0.001). CREDAC adjusts for variations in copy number, thus facilitating the investigation of cancer-specific dosage compensatory responses triggered by aneuploidy. We revealed that a majority of genes (~65%) exhibit proportionality to copy number alterations, while a substantial proportion (~35%) shows anti-scaling or dosage compensation strategies. We show an enrichment of genes involved in cell cycle and expression processes within the dosage compensated group and revealed methylation as a key mechanism driving this compensatory process. Conclusion: Overall, our results suggest that CREDAC is able to accurately disentangle the expression of tumor and normal cells from bulk RNA-seq without any previous knowledge. It has potential applications in many studies that include matched RNA-seq and copy number data and can provide new insights functional characterization, the taxonomy of cancer, and tumor evolution. Citation Format: Carla Castignani, Jonas Demeulemeester, Oriol Pich, Tom Lesluyes, Robert E. Hynds, David R. Pearce, Elizabeth Larose Cadieux, Stefan C. Dentro, TRACERx Consortium, Nnenna Kanu, Charles Swanton, Peter Van Loo. CREDAC: Copy number-based reference-free expression deconvolution analysis of cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2268.

Abstract 1615: Balanced molecular feature selection unveils universally tumor-lineage informative methylation sites in colorectal cancer

Abstract In the era of precision medicine, performing comparative analysis over diverse patient populations is a fundamental step toward tailoring healthcare interventions. However, the critical aspect of equitably selecting molecular features across multiple patients is often overlooked. To address this challenge, we introduce FALAFL (FAir muLti-sAmple Feature seLection), a novel algorithmic approach based on integer linear programming. FALAFL is designed to bridge the gap between molecular feature selection and algorithmic fairness, ensuring a balanced selection of molecular features across different patient samples. We have applied FALAFL to the problem of selecting lineage-informative CpG sites within a cohort of 9 colorectal cancer patients subjected to low-coverage single-cell methylation sequencing. Our results demonstrate that FALAFL excels at rapidly determining the optimal set of CpG sites, which are well covered by cells across the vast majority of the patients, while ensuring that each patient contributes a similar number of sites to the final selection. An analysis of the FALAFL-selected CpG sites reveals that their lineage informativeness exhibits a strong association across diverse patient profiles, suggesting the non-stochasticity and universality of methylation changes in tumor evolution. Furthermore, these universally lineage-informative sites exhibit subclonal level alterations in the colorectal cancer primary tumors and are strongly associated with lineage-specific gene expression patterns. By integrating equity considerations into the molecular feature selection process, FALAFL is poised to propel equitable healthcare data science practices and advance our understanding of cancer and other complex diseases. Citation Format: Xuan Cindy Li, Yuelin Liu, Alejandro A. Schäffer, Stephen M. Mount, Süleyman C. Sahinalp. Balanced molecular feature selection unveils universally tumor-lineage informative methylation sites in colorectal cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1615.

Abstract 1765: The genetic landscape of head and neck cancer using brush biopsy

Abstract Oral premalignant lesions (OPLs) with genomic alterations have a heightened risk of evolving into oral squamous cell carcinoma (OSCC). Currently, genomic data are obtained through invasive tissue biopsy. Brush biopsy has been utilized for diagnosing dysplasia but its effectiveness in reflecting the complete genomic landscape of OPLs remains uncertain. This study investigates the potential of brush biopsy samples in accurately reconstructing the genomic profile of OPLs. The evolution and heterogeneity were assessed by assessing SNVs, copy number analysis, and subclonal architecture reconstruction of paired tissue-brush biopsy samples of oral epithelium, dysplastic lesion, and OSCC lesion. We found that brush biopsy accurately reflects the genomic landscape of oral lesions, mirroring about 90% of SNVs and comparable CNA profiles found in tissue biopsies. Genomic profiling with brush biopsy was tissue-specific, as SNVs identified in OPL or OSCC lesions were not found in adjacent normal mucosa. Shared SNVs and CNAs were observed between OPL and OSCC samples. This suggested a common ancestor giving rise to these lesions. Subclonal architecture reconstruction confirmed that both lesion types shared a common ancestor clone and then diverged evolutionarily. These findings underscore the potential of brush biopsies in accurately reconstructing the genomic profile of OPL and OSCC, highlighting their usefulness in understanding the biological processes involved in tumor evolution. Citation Format: Evit John, Tom Lesluyes, Toby Baker, Maxime Tarabichi, Peter Van Loo, Xiao Zhao. The genetic landscape of head and neck cancer using brush biopsy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1765.

Abstract 1395: Unraveling the interplay between tumor heterogeneity and microenvironment in pancreatic ductal adenocarcinoma evolution and its clinical implications

Abstract Intratumoral heterogeneity (ITH) and tumor microenvironment (TME) of pancreatic ductal adenocarcinoma (PDAC) play important roles in tumor evolution and patient outcomes. However, the precise characterization of diverse cell populations and their crosstalk associated with PDAC progression and metastasis is still challenging. We performed single-cell RNA sequencing of primary PDAC samples with and without paired liver metastasis samples to understand the interplay between ITH and TME in the PDAC evolution and its clinical associations. We discovered that even a small proportion (~30%) of basal-like ductal cells in primary PDAC was associated with poor chemotherapy response and patient survival and that epithelial-mesenchymal transition programs were largely subtype specific. The clonal homogeneity significantly increased with more prevalent and pronounced copy number gains of oncogenes, such as KRAS and ETV1, and losses of tumor suppressor genes, such as SMAD2 and MAP2K4, along PDAC progression. Diverse immune cell populations, including naive SELLhi regulatory T cells (Tregs) and activated TIGIThi Tregs, contributed to shaping immunosuppressive TMEs of PDAC through cellular interactions with malignant ductal cells. The proportion of basal-like ductal cells negatively correlated with that of immunoreactive cell populations, such as cytotoxic T cells, but positively correlated with that of immunosuppressive cell populations, such as Tregs. Overall, our study provides a valuable resource for better understanding the roles of ITH and TME in PDAC evolution and their clinical relevance in the treatment of PDAC. Citation Format: Hyemin Kim, Hyong-oh Jeong, Se-Hoon Lee, Kwang Hyuck Lee, Kyu Taek Lee, Jong Kyun Lee, Min Woo Lee, Semin Lee, Joo Kyung Park. Unraveling the interplay between tumor heterogeneity and microenvironment in pancreatic ductal adenocarcinoma evolution and its clinical implications [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1395.

Abstract 7602: Discovery of GH1581, a potent and selective WRN inhibitor as a cancer therapy

Abstract Defects in DNA mismatch repair (MMR) proteins could induce damage of genome, resulting microsatellite instability (MSI). MSI is highly correlated with the occurrence of several types of cancers, mainly in colon, gastric, endometrial, and ovarian cancers. Despite advances in the treatment of MSI-high cancers, tumor evolution and drug resistance remain the leading causes of treatment failure and death in cancer patients. About 50% MSI cancers have no response to immune checkpoint inhibitors. There is still unmet needs to be fulfilled for MSI-high patients. WRN is a RecQ family helicase involves in genome stability maintenance, DNA repair, replication, transcription, and telomere maintenance. Recent studies have identified WRN as a synthetic lethal target of MSI-high cancers. Employing structure-based drug design strategy, we have discovered a potent and selective WRN inhibitor, GH1581. In vitro, GH1581 displayed specific < 10 nM potency in ADP-Glo assay and < 10 nM potency in cell proliferation assay using MSI cancer cell lines. In vivo, GH1581 demonstrated favorable pharmacokinetic properties in different species. In SW48 xenograft model, it inhibited the tumor growth with 100% TGI at QD dosing of 10 mg/kg without severe adverse effect on body weight. In summary, we discovered GH1581 as a novel inhibitor of WRN with high in vitro and in vivo efficacy. Citation Format: Jiapeng Li, Guiping Zhang, Jie Jack Li. Discovery of GH1581, a potent and selective WRN inhibitor as a cancer therapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7602.

Abstract 1759: Integrative longitudinal genomic analysis of therapy-resistant and metastatic pediatric cancers

Abstract Pediatric cancer patients are commonly profiled with gene-panel sequencing tests that yield few actionable results, in part due to the complex genomic alterations that define these malignancies. We hypothesized that integration of whole-genome (WGS) and RNA sequencing (RNAseq), would lead to a more comprehensive understanding of these diseases. Our study is uniquely focused on metastatic and relapsed disease, whereas previous studies focused on primary cases. We also prioritized longitudinal profiling, including with deep sequencing, to capture tumor evolution across primary and metastatic sites and to quantify the utility of resampling. We assembled a cohort of 219 high-risk pediatric oncology patients, including solid tumors, CNS tumors, leukemias/lymphomas, patients with relapsed/refractory disease (75), metastatic disease at diagnosis (7), rare diagnoses (17), prior cancer history, and estimated overall survival <50%. We characterized 286 samples with WGS (tumor ~60X; germline ~30X) and/or RNAseq (polyA selected, ≥20 million reads), including 95 samples taken from 44 patients at different time points (diagnosis, relapse, etc.). Variants, structural rearrangements, mutational signatures, and copy-number alterations were identified using WGS. RNAseq was used to profile gene expression outliers, gene fusions, and expression of variants. Integrated results were used to prioritize potentially actionable variants. For 20 patients (44 samples), we performed targeted deep sequencing of the DNA (~500X). RNAseq identified potentially druggable outlier gene expression and fusions, including 102 novel fusions where the 3’ gene is overexpressed. WGS identified aneuploidy, loss of heterozygosity and whole genome duplication across histotypes. Mutational burden and mutational signatures analyses identified profound effects from platinum drugs on tumor evolution, but treatment effects were not universal. Multiple sampling per patient uncovered drastic spatial and temporal differences in the genomes and transcriptomes of these tumors. Custom deep sequencing confirmed these findings, captured evolution missed by WGS, and furthered our understanding of the complex impacts of treatment on clonal evolution. Histotypes differed by whether actionability was higher for WGS or RNAseq alone, but in 66% of samples modality integration increased actionability. Integration also identified a subset of tumors that may be amenable to immunotherapy, but which lack canonical markers of response. Longitudinal analysis highlighted both the opportunities and risks of targeted therapy, with targetable variants gained and lost between timepoints. Our study shows that integrated multi-modality sequencing can elucidate novel insights into the biology of pediatric cancers and identify potential therapeutic targets not detected using gene-panel testing alone. Citation Format: Henry J. Martell, Avanthi T. Shah, Alex G. Lee, Stanley G. Leung, Soo-Jin Cho, María Pons Ventura, Ana Golla, Amanda E. Marinoff, Elizabeth P. Young, Bogdan Tanasa, Inge Behroozfard, Heng-Yi Liu, Aviv Spillinger, Michelle L. Turski, Nicole Elzie-Tuttle, Carlos Espinosa-Mendez, Arun Rangaswami, Tabitha M. Cooney, Cassie Kline, Anurag Agrawal, Jennifer Michlisch, Elliot Stieglitz, Mignon Loh, Amit J. Sabnis, Kieuhoa T. Vo, Sheri Spunt, Norman Lacayo, Holly C. Beal, Florette K. Hazard, Sophie Salama, David Haussler, Olena M. Vaske, Marcus R. Breese, E. Alejandro Sweet-Cordero. Integrative longitudinal genomic analysis of therapy-resistant and metastatic pediatric cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1759.

Abstract 3664: Evaluation of on-treatment tumor molecular dynamics using plasma whole genome sequencing (pWGS) and whole exome sequencing (pWES) of circulating tumor DNA (ctDNA) in patients (pts) with metastatic non-small cell lung cancer (NSCLC): An exploratory analysis of KEYNOTE-598

Abstract Background: ctDNA-based pWES is a promising tool to examine tumor genomics using a non-invasive liquid biopsy to serially monitor changes during tumor evolution and treatment. Here, we evaluate on-treatment tumor molecular dynamics using ctDNA-based pWGS and pWES in pts with metastatic NSCLC that responded to pembrolizumab (pembro) monotherapy and later experienced PD in KEYNOTE-598 (NCT03302234). Methods: In KEYNOTE-598, pts had metastatic NSCLC (PD-L1 tumor proportion score ≥50%) and received first-line pembro ± ipilimumab for ≤35 cycles. Cell-free DNA (cfDNA) was isolated and sequenced from plasma samples at baseline (BL), during on-treatment response (cycle 5 [C5]), and at PD (discontinuation [D]) from pts with objective response to pembro monotherapy and subsequent PD. ctDNA burden (tumor fraction [TF]) was estimated using low-pass pWGS by quantifying tumor content in cfDNA as a function of aneuploidy. All samples with TF >1.5% underwent high-depth pWES. ctDNA burden was estimated from pWES data using maximum somatic allele frequency (MSAF). Correlation between TF and MSAF was evaluated using the Spearman coefficient (r). Variant allele frequency (VAF) and normalized VAF (nVAF) were used to determine variant clonality. Results: In total, 23 pts with initial response to pembro and subsequent PD had plasma samples available from BL, C5, and D. Samples from 22 pts had TF >1.5% by pWGS and underwent pWES. MSAF by pWES was correlated with TF by pWGS at BL (r = 0.68), C5 (0.80), and D (0.59). ctDNA TFs at BL and D (mean = 8.1% and 4.9%, respectively) were higher than C5 (2.0%). In a pooled variant-level analysis (nVAF >0.25) of samples from pts with high TF (≥2.5%) at both BL and D (n = 10), 786 (46%) of variants were present at BL and D, 391 (23%) were present at BL only, and 540 (32%) were present at D only. Variants shared between BL and D had higher clonality (mean nVAF = 0.46) than BL-only (0.38) or D-only variants (0.4). In general, shared variants had similar nVAFs at BL and D but in some pts nVAFs increased at D, suggesting evolution of tumor subclones during treatment. TP53 was mutated in 9 of 10 pts with high TF and was shared at BL and D in 6 pts (mean nVAF = 0.49), present at BL only in 1 pt (0.11) and at D only in 2 pts (0.43). KRAS G12V and Q61H hotspot mutations were observed in 2 pts at D-only and may be related to immune editing. Conclusions: Comprehensive pWES is feasible with sufficient ctDNA burden (TF ≥2.5%). ctDNA dynamics demonstrated molecular profiles characteristic of recurrence with high TF at BL and D and were consistent with radiographic determination of response/progression. Tumor variants at BL and D generally had a common clonal trunk with clones disappearing or appearing de novo. Citation Format: Minita Shah, EJ Dettman, Andrew Albright, Cai Chen, Julie Kobie, Vinay Varadan, Ayman Samkari, Carol Peña, Razvan Cristescu, Z Alexander Cao. Evaluation of on-treatment tumor molecular dynamics using plasma whole genome sequencing (pWGS) and whole exome sequencing (pWES) of circulating tumor DNA (ctDNA) in patients (pts) with metastatic non-small cell lung cancer (NSCLC): An exploratory analysis of KEYNOTE-598 [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3664.

Abstract 5665: Native nanopore sequencing of multiple tumor sites reveals genetic and epigenetic intra-tumor heterogeneity in canine osteosarcoma

Abstract Osteosarcoma (OS) is an aggressive bone malignancy affecting children and young adults. Implementation and optimization of neoadjuvant chemotherapy led to significant improvements in outcome, but patients with recurrence or metastases at diagnosis continue to have poor prognosis. Whole genome sequencing (WGS) revealed that a hallmark of OS is a highly rearranged genome with complex copy number aberrations rather than point mutations. A better understanding of the key genomic and epigenetic factors driving clonal evolution may provide insights into the tumor progression and the therapy response. Canine OS recapitulates the majority of the hallmark genetic and molecular factors of human OS and is recognized as an informative model. A significant difference is that initial surgery in canine OS allows us to explore tumor evolution unperturbed by treatment, providing invaluable resources to study the genetic and molecular landscape of tumor evolution. Here, we present the first study to date in which we performed bulk WGS of multiple tumor sites and distal normal tissue in two dogs using nanopore long-read sequencing to analyze the genetic and epigenetic evolution of OS. In both subjects, somatic structural variation detection using Severus revealed chromothripsis-like rearrangements in chr11, leading to the deletion of Cdkn2a, a known cell cycle regulator and tumor suppressor. Interestingly, in one of the subjects, the majority of the SVs (n = 131) shared across all the samples were localized on chr5, coinciding with perturbed copy number profiles and bi-allelic frequency of the SNVs, with all mutations identified using complementary bioinformatics analysis of the same native nanopore reads. The multi-site sample analysis identified subclonal structural alterations in TP53 and ATRX genes. With phased nanopore reads, we observed subject-specific copy-neutral loss-of-heterozygosity events and long identical-by-descent blocks. Haplotype-specific copy-number analysis of tumors showed different aneuploidy patterns in both subjects, highlighted clonal compositions of samples from distinct sites, and identified regions of copy-number heterogeneity. Furthermore, phased nanopore reads also revealed haplotype-specific 5mC and 5hmC methylation differences across tumor samples, where samples from different sites of the same tumor demonstrate distinct methylation patterns that overlap DLG2, RUNX2, KDR, and other genes known as mutational hotspots in canine/human OS. Overall, we showcase how a single sequencing assay allows for a joint analysis of genetic and epigenetic tumor alterations, thus providing a richer understanding of the drivers of somatic evolution and their association with the molecular landscape in the canine OS. These findings can be translated into human disease and shed light on tumor progression and therapy response. Citation Format: Ayse Keskus, Sergey Aganezov, Tanveer Ahmad, Xiaoguang Dai, Robert Walker, John Beaulaurier, Scott Hickey, Sissel Juul, Amy Kathleen LeBlanc, Paul S. Meltzer, Mikhail Kolmogorov. Native nanopore sequencing of multiple tumor sites reveals genetic and epigenetic intra-tumor heterogeneity in canine osteosarcoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5665.

Abstract 4093: Modeling tumor immunoediting under immune selective pressure to inform neoantigen landscape dynamics for effective cancer vaccines

Abstract Tumor specific neoantigens, encoded by somatic mutations, are recognized by T cells, inducing anti-tumor immune responses. This renders neoantigens viable targets for personalized cancer vaccines. However, the identification of immunogenic neoantigens remains suboptimal. Understanding how immune selective pressure-mediated tumor evolution and neoantigen editing contribute to emergence of immunogenic neoantigens may improve prediction accuracy. In this study, we aimed to model tumor evolution and heterogeneity under immune pressure using three preclinical models of lung cancer with common driver mutations, Kras G12D/+ and p53 -/-, namely KPA, KPC, and HKP1, subcutaneously implanted in immunocompetent C57BL/6 (B6) and immune-deficient Rag1-/- mice. Our data suggest that despite shared driver mutations identified by whole exome and RNA-seq, tumor growth in vivo varied between tumor models. KPA tumors were immunogenic, as they were controlled in B6 mice but rapidly progressed in Rag1-/- mice, suggesting immunoediting of KPA-specific neoantigens. In contrast, HKP1 was non-immunogenic, with tumors progressing regardless of immune competency. KPC showed moderate tumor control in B6 mice, which was lost in Rag1-/- mice. We then estimated the cancer cell fraction on every mutation based on phylogenetic reconstruction. Immunogenic KPA tumors had significantly lower mutation burden in B6 than in Rag1-/- mice and the fraction of cell line mutations edited in vivo was significantly higher, suggesting active immunoediting in the former. Non-immunogenic HKP1 tumors did not show significant differences in mutation burden nor fraction of mutations edited between B6 and Rag1-/- mice. The immunogenicity was reflected in the immune infiltrate levels within tumors, with KPA being highly infiltrated by activated CD4 and CD8 T cells compared to KPC. HKP1 tumors showed increased infiltration of suppressive regulatory T cells. T cell receptor (TCR) sequencing on lung tumors showed that clonal expansion is strongly associated with immunogenicity. KPA tumors showed significantly higher TCR clustering with less diversity compared to KPC and more than HKP1. Following a simple approach to study the immunogenicity of shared neoantigens to elicit cross-protective anti-tumor responses, mice were immunized with whole irradiated (IR) tumor cell lines and implanted with live tumor cells (matched and unmatched). While immunization with IR-KPA protected against corresponding tumor implant and moderately against KPC, it did not protect against HKP1, indicating lack of immunogenicity of mutations shared between KPA and HKP1. Further studies testing the anti-tumor responses and characteristics of neoantigens shared between these three related tumor cell lines will inform the conditions under which tumors may escape or regress and help improve neoantigen identifying algorithms. Citation Format: Mariam Mathew George, Jayon Lihm, Hyejin Choi, Yuval Elhanati, Stephen Martis, Marta Luksza, Benjamin Greenbaum, Jedd D. Wolchok, Taha Merghoub. Modeling tumor immunoediting under immune selective pressure to inform neoantigen landscape dynamics for effective cancer vaccines [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4093.

Abstract 1611: DNA methylation co-operates with genomic alterations during non-small cell lung cancer evolution

Abstract Aberrant DNA methylation patterns have been described in nearly all human cancers, yet their interplay with genomic alterations during tumor evolution is poorly understood. To explore this crosstalk, we performed reduced representation bisulfite sequencing on 217 tumor regions from 59 patients from the TRACERx study, all with matched adjacent normal tissue, to deconvolve tumor methylation rates. We combined two new metrics for integrative evolutionary analysis with DNA and RNA sequencing data. I-TMD (intra-tumoral methylation distance) quantifies intra-tumor DNA methylation heterogeneity. MR/MN classifies genes based on the rate of hypermethylation at regulatory (MR) versus non-regulatory (MN) CpGs, to identify driver genes exhibiting recurrent functional hypermethylation. We observed early DNA methylation of VIPR2 and ZNF714 co-occurring with driver mutations in CDKN2A and STK11, respectively. Finally, we found DNA methylation-linked dosage compensation of essential genes co-amplified with neighboring oncogenes. Our identification of hypermethylated driver genes under positive selection may open new avenues for therapeutic stratification of patients with non-small cell lung cancer. Citation Format: Francisco Gimeno-Valiente, Carla Castignani, Elizabeth Cadieux L. Cadieux, Nana E. Mensah, Olga Chervova, Mariam Jamal-Hanjani, Nicholas McGranahan, Stephan Beck, Jonas Demeulemeester, Miljana Tanic, Charles Swanton, Peter Van Loo, Nnennya Kanu. DNA methylation co-operates with genomic alterations during non-small cell lung cancer evolution [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1611.

Abstract 1612: Timing ecDNA acquisition across cancer

Abstract Extrachromosomal DNA (ecDNA) are acentric, circular DNA fragments which form after DNA double strand breaks. They segregate randomly during mitosis, promoting high-level amplifications of positively selected oncogenes such as EGFR and MYC. The prevalence of ecDNA across several cancer types, such as glioblastoma and sarcoma, has made promising therapeutic targets. However, while DNA damage is a hallmark of nearly all cancers, the formation of ecDNA is not, and the determinants for ecDNA acquisition are unclear. Furthermore, whether the timing of tumors’ acquisition of ecDNA (i.e., early or late clonal or sub-clonal) affects patient survival and drug resistance is unclear. Here, we leverage orthoganol information from ecDNA amplicons, such as mutation allele frequency and sequence synteny, to develop computational methods for elucidating the evolutionary history of ecDNA. Applying these to several cancer subtypes in TCGA, we find that most ecDNAs arise early in tumor evolution. We expect these results will help identify determinants of ecDNA acquisition and its temporal influence on patient survival. Citation Format: Andrew R. Lynch, Peter Van Loo. Timing ecDNA acquisition across cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1612.

Abstract 6905: A multi-targeted approach to evaluate therapeutic selection and efficacy in preclinical GBM models

Abstract Glioblastoma (GBM) is a devastating primary brain cancer with approximately 10,000 new US diagnoses annually. The current standard of care (SOC) for GBM includes surgical resection followed by radiation therapy (RT) and temozolomide (TMZ), however, there is near universal recurrence and development of resistance after treatment. Relapse in disease is tightly linked with dynamic changes in gene expression during tumor evolution, highlighting the need for stronger preclinical GBM models. Here, we report developing a pair of patient-derived xenograft (PDX) models from surgical resections obtained from initial GBM incidence in a patient (BarneyOI™ Cancer Model CRT00433) and subsequent recurrence following treatment (BarneyOI Cancer Model CRT00435) to study disease progression and novel treatment strategies. Recent studies have suggested the utilization of combination therapy approaches for GBM patients to address TMZ resistance. To this end, Certis has developed a personalized, AI-based approach to predict and test combination therapies in preclinical cancer models. Accuracy of the predicted sensitivities to treatment was evaluated in vivo using both subcutaneous (SC) and orthotopic (OT) mouse models. Luciferase-tagged CRT00433 and CRT00435 spheroid cell lines were transduced with firefly luciferase and implanted intracranially by stereotactic surgery for OT monitoring. Optical bioluminescence imaging (BLI) and murine-scale MRI from Aspect Imaging were used to assess therapeutic response of AI-predicted combination therapies and SOC treatment. Citation Format: Emily Eastwood, Bianca Carapia, Javier Rodriguez, Kristen Buck, Derrick Gorospe, Elizabeth Valencia, Bridget Corcoran, Raffaella Pippa, Yuan-Hung Chien, Warren Andrews, Long Do, Jonathan K. Nakashima, Jantzen Sperry. A multi-targeted approach to evaluate therapeutic selection and efficacy in preclinical GBM models [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6905.

Abstract 3952: Multiomic single-cell tumor evolution models of minimal residual disease in pediatric B-cell acute lymphoblastic leukemia

Abstract Detection of minimal residual disease (MRD) after initial diagnosis (IDX) and therapy is a strong prognostic marker for relapse in pediatric B-cell acute lymphoblastic leukemia (B-ALL). Previous studies have explored clonal genetic and gene expression changes between initial diagnosis and relapse. However, studying tumor cells present at MRD is challenging due to their low abundance. Examining the genomic profiles of leukemia cells that resist induction chemotherapy and understanding their evolutionary relationship to cells present at diagnosis may lead to a better understanding of the cells that eventually seed relapse. We analyzed somatic point mutations, indels, and copy number variants from 41 pediatric B-ALL patients with high-risk B-ALL. We specifically focused on patients from the following four common high-risk subtypes: KMT2A-rearranged, Ph+, Ph-like, and iAMP21, who had detectable disease at the end of induction. Leukemic burden at end-induction (day 29) ranged from 0.03% to 66.00%. Data were generated in partnership with the National Cancer Institute’s Human Tumor Atlas Network and the Children’s Oncology Group. Our data set of 41 patients includes 39 with paired initial diagnostic and end-induction samples that we used to create tumor evolution models based on single cells across disease stages. We produced single-cell multiome gene expression (scRNA) and chromatin accessibility (scATAC) profiles (10x Genomics) with a median of 7428 leukemic blast cells at IDX (range: 2490-14219) and 1907 at MRD (range: 240-10167) after filtering. We called somatic mutations from scRNA and scATAC using SComatic and Monopogen, and we detected copy number changes using Numbat and EpiAneufinder. We also designed a targeted DNA sequencing panel including 335 variants based on B-ALL literature and database searches to produce scDNA (Mission Bio) for 24 patients (16 IDX-MRD pairs) with a median of 2346 cells profiled at IDX (range: 340-8849) and 1828 at MRD (range: 596-5133). We built tumor phylogenies based on somatic SNVs and CNVs with COMPASS. Using multiple tools and complementary single-cell omics data types to detect somatic changes improved our confidence in the events used for tumor evolution tree construction. Our approach allowed us to define recurrent genomic events and patterns across pediatric B-ALL subtypes and to describe the clonal evolution of cells measured at initial diagnostic and end-induction disease stages. We were also able to link cell-specific mutation events to their transcriptional and epigenomic signatures, including mapping mutation events along the B-cell development trajectory and within differentially expressed gene pathways. Some cases showed dramatic shifts in subclonal structure between IDX and MRD that may be related to therapy-induced clonal selection, such as a loss of NRAS hotspot mutation. Citation Format: Steven M. Foltz, Avi Loren, Changya Chen, Rushabh Mehta, Elizabeth Li, Jason Xu, Fatemeh Alikarami, Kathrin M. Bernt, Kai Tan. Multiomic single-cell tumor evolution models of minimal residual disease in pediatric B-cell acute lymphoblastic leukemia [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3952.

Abstract 1815: Optimization of Lin28 inhibitors: A promising therapeutic approach for the suppression of cancer cell proliferation, stemness properties, and spheroid growth

Abstract Background: The pluripotency factor known as Lin28 plays a crucial role in the regulation of cancer cell stem-like characteristics, hence facilitating the formation of cancer and the evolution of therapy-resistant tumors. The protein exerts its function by utilizing its cold shock domain and zinc knuckle domain (ZKD) to engage with the Let-7 pre-microRNA and impede the process of Let-7 production. The implementation of chemical agents to hinder the interaction between Lin28 and Let-7 has been proven as a therapeutic approach for treating aggressive tumors. Methods: Computer-aided drug design techniques were employed in the development of a novel series of small molecule inhibitors, which are derivatives of our previously identified lead compounds Ln115, Ln15, and Ln7. Fluorescent Polarization Assay (FP), and Electrophoretic Mobility Shift Assay (EMSA) were used to screen the chemicals as Lin28-Let7 interaction disruptors using Lin28A/B ZKD domain. To further screen the chemicals, the Incucyte cell proliferation assay was performed using two Lin28A and Lin28B positive cells, IGROV-1, and DuNE cells, respectively. The inhibition of Lin28 activity was subsequently evaluated by measuring Let-7 micro-RNA and Lin28 protein levels using RT-PCR and Western Blot. Then, the metabolism profile was explored using Microsomal Stability Assay. Incucyte proliferation assay and MTS assay determined the IC50 of lead compound in Lin28 positive cells. The anti-stemness properties of the lead compound were subsequently evaluated through assays for stem gene expression levels and colony formation. To evaluate the potential of the lead compound to further move into animal studies, we tested it on a newly developed 3D Neuroendocrine Prostate Cancer (NEPC) model. Results: In this study, we provide a novel set of derivatives, within which, Ln268 was chosen as the lead compound. Ln268 shows higher metabolic stability with a half-life time of 462 min and clearance rate of 5 ul/min/mg, compared to its father compound at 347 min and 46 ul/min/mg, respectively. Ln268 treatment resulted in a time-dependent inhibition of cell growth with an IC50 of 2.5 uM at 72 hrs. Ln268 reduces mRNA levels of stemness and neurodifferentiation markers such as CHGA, CHG, SYP, SCGN, OCT3/4, NANOG, ID4, FOXC1, ALDH1A2, and FOXO3. In the 3D NEPC model, Ln268 suppresses spheroid growth in a dose- and time-dependent manner. Ln268 achieved 100% spheroid growth inhibition at the concentration of 100 uM, while the current commercially available C1632 only reached 50%. Conclusion: We discovered a novel Ln15 derivative named Ln268, which has a better metabolism profile and increased inhibitory activity to distrust Lin28-Let7 interaction and cancer cell proliferation. Ln268 has the potential to be improved and used as an anti-cancer treatment for a variety of malignancies, such as prostate cancer. Citation Format: Victor M. Matias-Barrios, Mariia Radaeva, Graciella Rosellinny, Artem Cherkasov, Xuesen Dong. Optimization of Lin28 inhibitors: A promising therapeutic approach for the suppression of cancer cell proliferation, stemness properties, and spheroid growth [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1815.

Abstract 1200: A novel algorithm for deconvolving cancer allele-specific clone copy number and copy number evolution

Abstract Both single nucleotide variants (SNVs) and somatic copy number alterations (SCNAs) accumulate in cancer cells during tumor development, fuelling clonal evolution. However, accurate inference of their coevolution from bulk DNA sequencing is challenging. We present ALPACA (ALlele-specific Phylogenetic Analysis of clone Copy number Alterations), a novel algorithm to allow the practical inference of SNV and SCNA coevolution. ALPACA is framed as an optimisation problem, that takes as input bulk tumor sample copy number mixtures and the tumor phylogenetic tree constructed from SNVs, and deconvolves the optimal, allele-specific integer copy number profiles for every distinct clone present in the tumor. To circumvent the challenge of joint SNV/SCNA inference, we postulate that in high mutation burden tumors all relevant SCNA clones are identifiable by their unique SNVs, hence ALPACA leverages phylogenetic trees constructed from bulk tumor sequencing data using SNVs. Secondly, to restrict the clone-specific copy number search space, ALPACA leverages constraints imposed by multisample sequencing, specifically in cases where clones are present across multiple samples or clones from different samples are phylogenetically related. Finally, ALPACA relies on parsimony and biologically informed constraints to further guide the deconvolution process. We demonstrate that ALPACA infers the copy number evolution of complex simulated tumors with higher accuracy than current state-of-the-art methods. We apply ALPACA to the large, multisample non-small cell lung cancer (NSCLC) cohort from the recent longitudinal, prospective TRACERx421 study, and show that ALPACA uncovers loss of heterozygosity and amplification events in minor subclones that were previously missed using standard approaches. ALPACA's assignment of SCNA driver events to branches of the phylogenetic tree reveals the evolutionary ordering of SNVs and SCNAs during NSCLC tumor evolution, such as late focal amplifications affecting the TERT gene locus occurring in subclones which expand and dominate a tumor sample. ALPACA enables an in-depth analysis of the coevolution of mutations and SCNAs in the tumor’s evolutionary history, revealing distinct patterns of copy number evolution. Notably, ALPACA identifies common patterns of copy number changes across the genome characterizing metastatic seeding clones, revealing that they harbor an increased number of SCNAs compared to clones that do not metastasize. Additionally, ALPACA uncovers subclonal enrichment for CCND1 amplification in primary tumor subclones that seed metastasis, and an overall increase of SCNA events occurring in both tumors with polyclonal seeding and extrathoracic metastases. Clone-level results obtained with ALPACA can offer new clinical insights and enable new types of analysis, e.g. copy number signature analysis including temporal order of SCNA acquisition. Citation Format: Piotr Pawlik, Kristiana K. Grigoriadis, Abigail Bunkum, Simone Zaccaria, Nicholas McGranahan, Charles Swanton. A novel algorithm for deconvolving cancer allele-specific clone copy number and copy number evolution [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1200.

Abstract 6924: Structural variant dynamics in melanoma: Unraveling tumor heterogeneity and evolution

Abstract Melanoma is characterized by significant intratumoral heterogeneity and complex evolutionary dynamics. This diversity in genomic alterations leads to the emergence of various subclonal populations within a single tumor. In our research, we established a new model system composed of 24 single-cell-derived clonal sublines (C1-C24), originating from the M4 melanoma model. This model was developed using a genetically engineered hepatocyte growth factor (HGF)-transgenic mouse. We employed Trisicell (Triple-toolkit for single-cell intratumor heterogeneity inference), a cutting-edge computational tool for scalable analysis of intratumor heterogeneity and evaluation based on single-cell RNA mutations. This enabled us to construct a phylogeny tree, revealing melanoma’s intricate branching evolutionary patterns. These patterns show ancestral clones evolving into genetically distinct subclones, which demonstrate varied phenotypic traits such as drug sensitivity or resistance, cellular plasticity, and immunogenicity. In our study, we conducted long-read sequencing on these clonal sublines in the phylogeny and identified structural variants (SVs) using Severus, a tool optimized for phasing in long-read sequencing. The types of SVs we discovered include deletions, insertions, amplifications, translocations, and inversions. We explored their roles in subclonal evolution, particularly focusing on how they disrupt genes and accumulate during melanoma progression. Our initial data from eleven sublines indicated a higher prevalence of ancestral SVs, shared by all sublines, compared to subline-specific SVs, representing later events. Notably, the individual sublines showed a higher rate of gene disruption by SVs, hinting at potential functional selection. Our analysis further revealed that SVs common to all sublines are linked with genes in key cell growth pathways, such as Rap1, Hippo, and calcium signaling pathways. In contrast, subline-specific SVs primarily affect genes involved in neurophysiological pathways, such as glutamatergic synapse and morphine addiction pathways. These findings suggest that different genes, associated with various pathways, are disrupted at distinct stages of melanoma progression, providing insights into the genetic factors that may predispose individual melanocytes to melanomagenesis. This methodology presents a comprehensive tool for characterizing tumor genomes and understanding their relationship with disease progression and therapy resistance. We are continuing our analysis to map SVs across the entire mutation-based phylogeny of all sublines, which will further our understanding of melanoma’s genomic landscape. Citation Format: Xiwen Cui, Ayse G. Keskus, Farid R. Mehrabadi, Salem Malikic, Mikhail Kolmogorov, Chi-Ping Day, Glenn Merlino, S. Cenk Sahinalp. Structural variant dynamics in melanoma: Unraveling tumor heterogeneity and evolution [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6924.

Abstract 7407: Melanoma clonal subline analysis reveals genetic factors driving intra-tumor heterogeneity

Abstract Melanoma is the most invasive skin cancer caused by the malignant melanocytes. The use of immune checkpoint blockade (ICB) improved the survival rate in advanced melanoma. Yet, the response rate to ICB varies across patients due to the highly heterogeneous nature of melanoma. Recent studies reported genomic and epigenetic factors contributing to the therapeutic response. Identifying these factors involved in clonal evolution in melanoma is a key to better understanding the tumor progression and divergence in the therapy response. To study melanoma heterogeneity, we generated twenty-four clonal sublines, each derived from a single cell isolated from a parental cell line derived from the M4 mouse melanoma model. DNA prepared from each subline and a spleen from a healthy mouse were subjected to long-read sequencing. Importantly, long-read sequencing allows direct detection of methylation states, small variants, and structural variants in the same run. The results thus provide excellent means to study genetic and epigenetic factors in clonal evolution. Each of these sublines was also implanted in distinct mice for survival and tumor growth analysis and further functional evaluation. We developed Severus, a structural variation (SV) caller for long reads, which works with single (germline), paired (tumor-normal), and multiple samples (e.g., multi-site or time series). Severus takes advantage of improved phasing in long-read sequencing, attributes somatic variants to germline haplotype, and builds a haplotype-specific breakpoint graph that is used to cluster multi-break rearrangements and represent the derived chromosomal structure. We benchmarked Severus using multiplatform validated COLO829 truthset and CHM1/CHM13 haploid genomes, and Severus outperformed all other methods in terms of recall and precision. The structural variation (SV) analysis using Severus with all the sublines showed enrichment of possibly clonal SVs in chr4, chr11, and mainly in chr13. Further investigation revealed SVs in chr13 were not distributed across the chromosome but clustered in certain regions. Analysis of somatic SNVs in chr13 corroborates the localized hypermutation profile, which indicates a possible kataegis. Interestingly, a loss of the chr13 copy affected by kataegis in one of the sublines coincides with a better survival rate, as compared to other sublines, in an allograft melanoma mouse model, which further supports the association between the kataegis and tumor progression. We also identified other clonal and subclonal events, including the homozygous deletion of Cdkn2a in most of the sublines, associated with their aggressiveness in vivo. Our analysis allowed us to identify clonal and subclonal genetic and epigenetic factors involved in tumor progression and evolution in a melanoma model, which can potentially translate to human disease. Citation Format: Ayse Keskus, Anton Goretsky, Yuelin Liu, Xiwen Cui, Tanveer Ahmad, Eva Perez Guijarro, Asher Bryant, Erin Malloy, Salem Malikic, Glenn Merlino, Chi-Ping Day, Cenk Sahinalp, Mikhail Kolmogorov. Melanoma clonal subline analysis reveals genetic factors driving intra-tumor heterogeneity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7407.

Abstract 3401: Uncovering virus induced dysregulated processes in cancer and their impact on outcomes

Abstract The National Cancer Institute has designated several viruses such as EBV, HBV, HCV, HIV, HPV, and HTLV as agents that either cause cancer or increase the risk of developing cancer. However, extensive analyses of tumor genome and transcriptome datasets have identified numerous additional virus types, the functional implications of which remain largely unknown. Viral infection often dysregulates unique molecular processes within tumor cells and alters the composition of immune cells in the tumor microenvironment. For instance, HPV-positive tumors have been shown to exhibit a significantly elevated expression of the DNA editing enzyme APOBEC3B compared to HPV-negative tumors. Furthermore, HPV positive tumors display and increased number of C-to-T mutations induced by this protein. The genome and transcriptome of tumor tissue biopsies contain a wealth of information about these virus-associated signatures. However, advanced signal processing approaches are needed to extract these viral signatures from complex tumor datasets, and elucidate their specific roles in cancer. Here, we developed a quantitative approach to investigate the link between viral infection and dysregulation of a seven-membered A3 enzyme family (A3A/B/C/D/F/G/H). The primary role of these enzymes is to restrict viral infections by inducing C-to-U mutations in viral genomes. However, at least three members of this enzyme family (A3A/B/H) can also induce mutations in cellular DNA, and drive tumor formation and evolution. We used NMF (Nonnegative Matrix Factorization) to deconvolute the expression profiles of A3 enzymes in >10,000 bulk RNAseq datasets from diverse TCGA tumors. This analysis revealed the expression profiles of A3 enzymes within tumor and tumor microenvironment cells including various immune cells. Next, we conducted an association analysis to identify the link between the presence of viral infection and the proportion of each of these tumor and tumor microenvironment expression profiles. As expected, our analyses revealed strong associations between tumor-specific A3 expression profiles and infections by oncolytic viruses such as HPV. Notably, and somewhat unexpectedly, our analyses also revealed associations with viruses about which little is known in the field of cancer. For example, in certain tumors, we identified a robust association between bacteriophages and a tumor-specific A3 expression profile characterized by A3B upregulation. Taken together, our analyses provide evidence for the link between A3 dysregulation and infection by viruses including bacteriophages. Citation Format: Mohadeseh Soleimanpour moghadam, Azad Khosh, Diako Ebrahimi. Uncovering virus induced dysregulated processes in cancer and their impact on outcomes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3401.

Abstract 6406: Clinical and translational results of the academic ARIANES Phase 2 basket study: Longitudinal single-cell analysis of patient tumors identifies biological correlates of response to PARP inhibitors and anti-PD-L1 therapy

Abstract Background: Poly (ADP-ribose) polymerase inhibitors (PARPi) have immunomodulatory properties that may potentiate anti-PD-L1 therapy. To explore this, we developed the academic ARIANES phase 2 basket trial, which evaluated the PARPi rucaparib (R) and the anti-PD-L1 atezolizumab (A) in selected patients (pts). We performed single-cell RNA + T cell receptor sequencing (scRNA+TCR-seq) on 3 sequential tumor biopsies in a pts subset. Methods: ARIANES comprised 4 molecularly-selected DNA damage response deficient (DDRd), 3 platinum-sensitive, and 2 unselected cohorts of pts with non-small cell lung (NSCLC), prostate (CRPC), and other non-breast non-ovarian cancers. R was administered for 3 weeks, followed by R+A. Primary endpoint was overall response rate (ORR) at 12 weeks per cohort. scRNA+TCR-seq was performed on fresh biopsies collected at baseline, on R, and on R + A in the same lesion, with concomitant plasma collection. We tracked the evolution over time of tumor and microenvironment cells, differentially expressed genes and signatures within each cell population, and TCR clonal dynamics. Results: ARIANES enrolled 130 pts, including 27 DDRd CRPC and 3 DDRd NSCLC pts, on which we focus here. Best ORR by RECIST v1.1 was 22% (6/27) in CRPC pts, and mPFS: 7.9 months (95% CI 4 - 11.1) at data cut-off. ORR was 0% in NSCLC pts. We successfully profiled 3 sequential fresh biopsies in 2 BRCA2-mutant CRPC, 1 ATM-mutant, and 1 RAD54L-mutant NSCLC pts. Tumor, T and B lymphoid, myeloid, plasma, dendritic, NK, endothelial, and stromal cells were identified in all samples. Differential expression testing unveiled PARP1 upregulation in tumor cells on R. One CRPC pt with prolonged partial response displayed activation of innate immune sensing pathways (including cGAS-STING and IFN signaling) in tumor and immune cells, as well as JAK/STAT and CCL5, all increasing gradually on R and R + A; scTCR-seq revealed the expansion of specific T cell clonotypes on R + A. One ATM-mutant NSCLC pt with 6-month stable disease displayed increased cGAS/STING, JAK/STAT and CCL5 activation on R in NK cells only, and no TCR expansion. None of the above was observed in the 2 pts who progressed. Complete clinical and translational study results will be presented at the congress. Conclusion: Sequential scRNA+TCR-seq enables the dynamic assessment of tumor and immune cells on therapy. Our data confirms the potential of R to activate innate immune pathways in pt tumors, and R + A to induce T cell activation and clonal expansion. To our knowledge, this is the first study providing a longitudinal single-cell resolution analysis of the clonal evolution of tumor and immune cells in pts on PARPi + anti-PD-L1. We identify potential biological correlates of therapy response, including the activation of innate immune pathways and TCR expansion. Citation Format: Julien Vibert, Clémence Hénon, Lambros Tselikas, Baptiste Bonnet, Arnaud Pagès, Alice Bernard-Tessier, Léo Colmet-Daage, Roman Chabanon, Nicolas Dorvault, Clémence Astier, Anas Gazzah, Aurore Jeanson, Aurélien Parpaleix, Ronan Flippot, Natacha Naoun, Anna Patrikidou, Pernelle Lavaud, Giulia Baciarello, Emeline Colomba, Alina Fuerea, Laurence Albiges, Christophe Massard, Santiago Ponce, Yohann Loriot, Stéphane Champiat, Capucine Baldini, Fanny Bouquet, Nathalie Droin, Karim Fizazi, Damien Vasseur, Patricia Martin-Romano, Etienne Rouleau, Kaïssa Ouali, Sophie Postel-Vinay. Clinical and translational results of the academic ARIANES Phase 2 basket study: Longitudinal single-cell analysis of patient tumors identifies biological correlates of response to PARP inhibitors and anti-PD-L1 therapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6406.