Cancer Biology Research Articles

Abstract 1287: The ACCESS consortium: Advancing childhood cancer experience, science and survivorship in Canada

Abstract In Canada, >4,300 children, adolescents and young adults are diagnosed with cancer each year. 1/3 have refractory/metastatic disease or will relapse with an expected 5-year survival rate of <15%. The prognosis for most pediatric cancers has stagnated in the past 30 years and Canada trails the US and Europe in providing accessible clinical trials and improved outcomes. Advocacy for change by patients and families led to a federal government investment of $30M in pediatric cancer research. $23M was allocated to establishing a national pediatric cancer consortium. “ACCESS: advancing childhood cancer experience, science and survivorship” is the new multi-stakeholder network created with a vision that every Canadian child with cancer has access to the latest scientific advances, diagnostic tools, therapies and supportive care leading to better outcomes and quality of life. ACCESS will connect the Canadian pediatric cancer community, build partnerships, leverage research and clinical expertise across cancer types and ages, implement transformative change and create a unified national strategy. To date, >350 clinicians, researchers, policymakers, advocates, people with lived experience (PWLE; patients, families and survivors) and other stakeholders have been engaged, with a goal of representing Canada’s ethno-cultural, socioeconomic and geographic diversity. ACCESS is building partnerships between children, families, professionals, and existing programs to collaborate in coordinated research and knowledge mobilization. The goal is to implement transformative change in the delivery of fair, fast, effective and safe cancer care for all Canadian children. ACCESS has developed a statement of its values that includes patient/survivor and family centred; collaborative; anti-oppressive; innovation and excellence; accountable. Uniquely, ACCESS is an interdisciplinary and inclusive organization that directly engages and collaborates with PWLE at all levels of research and governance. ACCESS is organized into 7 themes that will address gaps, advance research and educate through all phases of the pediatric cancer journey: cancer biology; clinical trials; access to innovative therapies and optimal care; regulation, policy and economics; education and training; ethical, legal, societal implications and implementation science; and psychosocial and survivorship. In addition, there are two cross cutting groups focusing on Knowledge mobilization and Social justice, Indigenization and Inclusion. Collaborations with local, provincial, national and international initiatives are being established through the development of a partnership strategy. Cross-consortium priorities are being implemented, and a data management strategy is in development. The publication of a strategic and sustainability plan for ACCESS is anticipated in 2024. Citation Format: Christine J. Williams, Stephanie A. Grover, Adrienne Co-Dyre, David Malkin, James A. Whitlock, on behalf of the ACCESS consortium. The ACCESS consortium: Advancing childhood cancer experience, science and survivorship in Canada [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 1287.

Abstract 1727: Silencing of novel m6A reader PRRC2A as a therapeutic strategy for oral cancer

Abstract Background: Oral squamous cell carcinoma (OSCC) poses a substantial global health challenge characterized by limited treatment options and unfavorable prognoses. Recent research has illuminated the pivotal role of N6-methyladenosine (m6A) modification and its regulators in cancer biology. However, the precise involvement of a novel m6A regulator (m6A reader), PRCC2A in OSCC remains inadequately understood. Objective: This study aims to unravel the role of PRCC2A in OSCC and ascertain its potential as both a diagnostic biomarker and a therapeutic target. Methods: We collected 76 OSCC tumor samples and 38 adjacent non-tumor samples from OSCC patients. Comprehensive analyses, including RT-qPCR, western blotting, histopathological examination, and associations with clinicopathological features, were performed to assess PRRC2A expression in cancer tissues. Furthermore, we explored its links with key factors like metastasis and its implications for patient prognosis. In vitro experiments were conducted using OSCC cell lines and human normal oral keratinocytes (NOKs). PRCC2A knockdown in OSCC cell lines was assessed for its effects on cell proliferation, apoptosis, cell cycle, migration, invasion, and sphere-forming abilities. The study also delved into its impact on immune cell infiltration and involvement in biological pathways. Results: Our investigation unveiled significant overexpression of PRCC2A in OSCC tissue samples and cell lines, relative to adjacent non-tumor tissues and NOKs (P < 0.001). These findings were further validated by the Cancer Genome Atlas - Head and Neck Squamous Cell Carcinoma (TCGA-HNSC) dataset. PRCC2A expression displayed significant correlations with nodal metastasis, higher tumor grades, and advanced cancer stages in OSCC samples, suggesting its crucial role in driving cancer progression and aggressiveness. Silencing PRCC2A in vitro led to reduced metastasis, diminished tumor colony formation, and increased apoptosis in oral cancer cell lines. Furthermore, the study uncovered PRCC2A intricate connections with immune regulatory genes, highlighting its potential to influence the tumor immune microenvironment. Conclusion: PRCC2A emerges as a promising candidate for both diagnosis and therapeutic intervention in OSCC. Its pronounced overexpression in oral cancer tissues, coupled with its associations with metastasis and intricate interactions with immune regulatory networks, underscores its significance in the context of oral cancer malignancies. This research offers valuable insights into the multifaceted role of PRCC2A in OSCC and lays the groundwork for future investigations and potential clinical applications. Citation Format: Balachander Kannan, Vijayashree Priyadharsini Jayaseelan, Senthil MuruganM, Paramasivam Arumugam. Silencing of novel m6A reader PRRC2A as a therapeutic strategy for oral 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 1727.

Abstract 3679: Development and validation of prognostic signatures comprising neutrophil-specific long non-coding RNAs (LncRNAs) for predicting survival in urothelial carcinoma

Abstract Background: Tumor-associated neutrophils profoundly influence the tumor immune microenvironment (TME), impacting urothelial carcinoma (UC) progression, metastasis, and survival. Long non-coding RNAs (lncRNAs) have emerged as critical players in cancer biology. Recognizing neutrophils as influential contributors to tumor biology, our study aimed to explore neutrophil-specific lncRNAs and evaluate their prognostic significance in UC. Methods: In the GSE24890 dataset, 46 lncRNAs were identified with elevated expression in neutrophils compared to other immune cells, thus designating them as neutrophil-specific lncRNAs. To establish a tailored prognostic model, the TCGA BLCA dataset served as the internal training set. Candidate lncRNAs underwent filtration and selection through univariate Cox regression analysis, followed by the construction of a risk score employing LASSO and multivariate Cox regression algorithms. We used IMVigor210 dataset as external validation for this lncRNA model. Results: Ten lncRNAs exhibiting correlation with overall survival (OS) were initially identified through univariate Cox regression. Following LASSO regression and subsequent multivariate Cox regression analysis, a refined set of 9 lncRNAs was selected to construct the risk model, represented by the formula: Risk score = (-0.096 × FAM13A-AS1 expression level) + (0.157 × FAM27C expression level) + (-0.294 × HCG27 expression level) + (-0.037 × HOTAIRM1 expression level) + (-0.137 × LINC-PINT expression level) + (-0.279 × LINC00612 expression level) + (-0.058 × LINC00967 expression level) + (0.187 × LINC01018 expression level) + (-0.288 × LINC01138 expression level). Kaplan-Meier survival analysis of the BLCA cohort revealed that patients in the high-risk group experienced significantly worse OS compared to those in the low-risk group (p < 0.001). The area under the curve (AUC) values at 1, 3, and 5 years were 0.66, 0.67, and 0.66, respectively. In the multivariate Cox regression model, the risk score remained an independent prognostic factor (p < 0.001; HR 2.5; 95% CI 1.91-3.30). The validity of the risk score was further confirmed in the IMVigor210 dataset, demonstrating discriminative predictive ability for OS between high- and low-risk groups (p = 0.027). Conclusions: This study underscores the interplay between neutrophils and lncRNAs in UC. Neutrophil-related lncRNAs identified may serve as promising therapeutic targets and prognostic markers for UC. Citation Format: Harvey Yu-Li Su, Chang-Ting Lin, Shih-Yu Huang, Yi-Hua Chen, Chung-Wen Kuo. Development and validation of prognostic signatures comprising neutrophil-specific long non-coding RNAs (LncRNAs) for predicting survival in urothelial carcinoma [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 3679.

Abstract 1381: Characterization of the 12-lipoxygenase expression in the megakaryoblastic cell line, Dami

Abstract Megakaryocytes are myeloid cells produced primarily in the bone marrow and are best known for releasing platelets in the blood stream. In the platelet production process, megakaryocytes transfer their bioactive content, including the 12-lipoxygenase (12-LO) enzyme, into newly formed platelets. The 12-LO has been shown to be implicated in platelet activation and is overexpressed in several chronic inflammatory conditions, including several types of cancers. The 12-LO is responsible for the conversion of the arachidonic acid into the 12(S)-hydroxyeicosatetraenoic acid (12(S)-HETE), a key lipid mediator implicated in several steps of the metastatic cascade. While 12-LO is expressed in mature human megakaryocytes, we recently identified two megakaryoblast cell lines isolated from leukemia patients lacking 12-LO expression. However, only one of the two cell lines expresses functional 12-LO protein upon megakaryocyte maturation. The goal of this study is to characterize the 12-LO expression during the megakaryocyte maturation process. We hypothesize that 12-LO expression is increased during cell maturation and that inhibition of the 12-LO expression will result in dysfunctional platelets. Both the Dami cell and MEG-01 cells were induced with the co-incubation of both phorbol myristate acetate and eltrombopag, a thrombopoietin receptor agonist. The maturation and viability of the cells were confirmed by flow cytometry. Expression of the 12-LO was assessed by RT-qPCR and immunoblot. Quantification of the 12(S)-HETE was performed by reversed-phase high performance liquid chromatography. Platelet release was quantified by flow cytometry using CD41 fluorescent labelled antibodies. We observed a 3-fold increase in 12-LO protein expression following cell maturation in the Dami cell line. Interestingly, mRNA expression between the undifferentiated Dami cells and mature Dami cells remained unchanged. Furthermore, we did not detect any 12-LO protein expression in the MEG-01 after the cell’s maturation. Finally, we identified a specific 12-LO antisens non-coding RNA that is implicated in the regulation of the protein expression in megakaryocytes. Our study reports the first mechanistic regulation of 12-LO expression implicated in the megakaryocyte maturation process. Since both platelets and platelet-specific 12-LO play an important role in cancer biology, it is important to better understand how megakaryocytes package the enzyme inside these small cells. It remains elusive whether 12-LO enrichment in platelet correlates with the disease severity. Citation Format: Luc H. Boudreau, Vanessa L. Gauvin, Jaël Richard, Marie-France N. Soucy, Mathieu P.A. Hébert, Eric P. Allain. Characterization of the 12-lipoxygenase expression in the megakaryoblastic cell line, Dami [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 1381.

Abstract 1291: ASPIRE: Advocates and Scientists Partner in Research Education

Abstract UNC Lineberger Comprehensive Cancer Center (LCCC) has a robust and growing cancer patient advocacy community. UNC Lineberger is the flagship publicly funded comprehensive cancer center in North Carolina. We are constantly looking for ways to educate patient and community advocates on recent advances in cancer biology research and clinical trials. Our advocates are also valuable partners for our basic and clinical researchers that may be early in their career. We developed and implemented an inaugural research education program for new advocates. We model this program partly on the highly successful and popular AACR Scientist Survivor Program that recently celebrated it’s 25th anniversary. Some of the UNC LCCC advocates participate in the SSP and were motivated to develop our own local program. We will showcase our pilot 2024 ASPIRE education program that brings together cancer patient and community advocates and cancer researchers to learn from each other. The basic itinerary of the ASPIRE program is: 1.Three separate one-hour online presentations by UNC Lineberger researchers with a patient advocate moderator. The topics covered are: Cancer 101 : cancer biology, diagnosis, staging, treatment. Clinical Trials 101: clinical trials, phases, patient protection, progress with for example accrual of representative populations. Research 101: bench research, bioinformatic, AI, how research works and how it may lead to new treatments. To showcase a tissue donation program being developed by UNC Patient Advocates that will benefit researchers. 2.The lecture series is followed by a breakfast roundtable discussion for all the participants to discuss their experiences. There will be short presentations and discussions in small groups of researchers and cancer patient advocates. We will summarize our ASPIRE pilot experience, how our participation in the SSP program motivated this local program, and how we plan to incorporate feedback from participants to inform future programs. We hope this will lead to more informed patient advocates that can then be even more powerful in research advocacy. Citation Format: Laurie Betts, Jennifer Potter, Veronica Carlisle, Patricia A. Spears. ASPIRE: Advocates and Scientists Partner in Research Education [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 1291.

Abstract 888: Uncovering clinically relevant omics signatures from pan-cancer imaging and multi-omics data integration

Abstract Despite advancements in deep learning for histopathology, integrating these insights with multi-omics data to uncover clinically relevant omics pathway-level signatures remains a challenge. Our study addresses this gap by applying unsupervised learning techniques on pan-cancer multi-omics data, leveraging 3,080 Hematoxylin and Eosin (H&E) images from 1,010 patients in Clinical Proteomic Tumor Analysis Consortium (CPTAC) to uncover omics pathway-level signatures that drive discernable morphology phenotypes at the tissue level. First, imaging models were trained to predict clinical and mutation outcomes, and thereafter, integrated with transcriptomic and proteomic expression data using sparse canonical correlation analysis. Our findings reveal that images of TP53 mutated samples exhibited increased nuclear size and dense lymphoplasmacytic infiltration. These morphological changes correlated with neutrophil and macrophage signaling at the proteomic level, and IL-1 mediated signaling at the transcriptomic level, highlighting the complementary perspectives different omics can provide. To further elucidate immune interactions, we applied multi-omics deconvolution to identify 7 immune subtypes, characterizing each with gene set enrichment, germline DNA variations, and kinase activations. We show that imaging models trained to predict these subtypes differentiate tissue morphologies corresponding to immune enrichment (AUROC: 0.84). To further confirm the robustness of our approach, we trained models to predict co-regulated proteomic modules clustered by independent component analysis. We demonstrate a signature in pan-squamous tumors, consisting of T cell markers and interferon-gamma response proteins like CD4, CD48, and GBP5, which imaging models can successfully predict from histopathology. Manual review from pathologists confirmed lymphocytic T-cell density as a differentiator in samples with the highest and lowest T-cell signaling. Together, these approaches demonstrate that genomic characteristics discovered via unbiased mining of pan-cancer multi-omics data manifest as quantitative imaging phenotypes. These results underscore the potential of multi-omics and digital pathology to integratively uncover and confirm new cancer biology. Our ongoing work will explore predicting drug response and survival from morphology patterns related to multi-omics signatures. Citation Format: Joshua Wang, Runyu Hong, Jimin Tan, Wenke Liu, David Fenyȯ. Uncovering clinically relevant omics signatures from pan-cancer imaging and multi-omics data integration [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 888.

Abstract 3668: Plasma cell-free DNA profiling for deciphering cellular origins and immune competence in cancer patients

Abstract Plasma cell-free DNA (cfDNA) originates from apoptotic cells in the blood, providing a real-time insight into the biology of various cell types. The fragment coverage pattern of cfDNA across the genome is known to reflect the distinct chromatin status of originating cells. While extensive research has focused on fragments derived from cancer, known as circulating tumor DNA (ctDNA), for inference about cancer biology, cfDNA fragments from healthy cells have received little attention. Our study explores the potential of cfDNA to decipher the relative abundance of distinct blood cell types, particularly immune system cell types. We collected a cohort of 273 bladder (BC) and colorectal cancer (CRC) patients and 45 healthy controls for plasma whole genome sequencing and assessed the fragment coverage profile at transcription start sites (TSS) of protein coding genes. A significant negative correlation was observed between TSS coverage and whole blood gene expression (Spearman’s rho = -0.65). Furthermore, TSS coverage revealed a bimodal distribution, characterized by modes corresponding to high and low gene expression levels in blood cells. This may suggest the cfDNA coverage profile as a binary expression status classifier to distinguish between expressed and unexpressed genes in blood cells. We further evaluated TSS with differential coverage between age groups of healthy individuals and relapse status of cancer patients. Notably, out of the TSS that significantly differentiated middle-aged (aged 40-65) from older individuals (aged 65+), 31 were also able to distinguish relapse from non-relapse patients. Among these TSS were CD36, SLAMF7, TABBP and PDCD1, known to be involved in immune related pathways. Finally, we evaluated coverage at cell-type specific TSS and found dendritic cells (P-value: CRC = 8e-06, BC = 5.1e-3), monocytes (CRC = 1.6e-04, BC = 2.5e-3), and NK cells (CRC = 8.5e-04, BC = 0.026) to exhibit a significant increase in coverage in the cancer cohorts compared to healthy controls. Conversely, T-cells showed a decrease in coverage (CRC = 0.041, BC = 0.062). In conclusion, cfDNA coverage profile may identify TSS with differential coverage between patient groups and characterize a shift in blood cell type composition as a response to cancer. Future work may show if fragment coverage quantifies the relative contribution of cfDNA from distinct immune cell types. We anticipate our analysis to illuminate the utility of plasma cfDNA as a biomarker for cancer patient’s immune competency, enabling improved patient stratification for treatment, leveraging their distinct immune capabilities. Citation Format: Laura Andersen, Amanda Frydendahl, Tenna Vesterman Henriksen, Christina Demuth, Mads Heilskov Rasmussen, Iver Nordentoft, Karin Birkenkamp-Demtröder, Jakob Skou Pedersen, Søren Besenbacher, Lars Dyrskjøt, Claus L. Andersen, Nicolai J. Birkbak. Plasma cell-free DNA profiling for deciphering cellular origins and immune competence in cancer patients [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 3668.

Abstract 514: Salt-inducible kinase inhibitor OMX-0407 drives cell-cycle arrest in vitro and in vivo: An in-depth MoA analysis by phospho-proteomics

Abstract Based on iOmx’ proprietary iOTargTM genetic screening platform, salt-inducible kinase (SIK) 3 was identified as a novel cell signaling modulator in cancer biology. OMX-0407, an orally available, spectrum-selective kinase inhibitor targets several members of the SIK family and is known to prevent tumor-promoting function of the SIK-family through repolarization of the tumor microenvironment by enhancing caspase-mediated apoptosis upon death-receptor signaling. In addition, OMX-0407 inhibits individual key members of the tyrosine and tyrosine-like kinase family that are involved in cancer cell proliferation and cell cycle regulation. Via this dual mode of action, OMX-0407 has the potential to effectively fight solid tumors as exemplified by its striking single-agent efficacy in multiple pre-clinical tumor models. A comprehensive anti-tumor viability screen of >200 human cancer cell lines revealed striking effects of OMX-0407 on cancer cell viability across various cancer indications, resulting in a distinct sensitivity profile across various tumor indications with particularly strong effects on renal cell carcinoma (RCC) and squamous non-small cell lung cancer (sqNSCLC). Phospho-proteomics screening demonstrated pharmacodynamic activity of OMX-0407 in sensitive tumor cell lines via inhibition of key cellular processes such as cell motility, proliferation, and cell cycle regulation across different indications. Orthogonal functional in vitro assays confirmed the association of the OMX-0407-mediated anti-tumor efficacy with the arrest of G1/S transition and corresponding downregulation of cell cycle associated proteins PAK1/2 and ARHGAP35. The profound impact of OMX-0407 on fundamental regulatory mechanisms of cell division and cancer cell apoptosis translates into dose-dependent single-agent, anti-tumor efficacy in various pre-clinical tumor models of selected indications. Combination with Axitinib, a selective orally available inhibitor of vascular endothelial growth factor receptor 2, significantly enhanced anti-tumor efficacy and pharmacodynamic inhibition of cell growth as well as angiogenesis. These data further strengthen the potential of OMX-0407 in the treatment of RCC as well as other indications. In summary, OMX-0407 is a novel spectrum selective kinase inhibitor, currently under evaluation in a clinical Phase I trial (NCT05826600). OMX-0407 demonstrates strong anti-tumor efficacy in monotherapy in selected sensitive indications through a dual-pronged MoA, by modulating the tumor microenvironment and exerting direct anti-tumor activity in solid tumor indications with high unmet medical need. Citation Format: Ilona-Petra Maser, Marisa Stebegg-Wagner, Bettina Bauer, Filippos Konstantinidis, Andreas Schirmer, Moritz Zulley, Sonja Lacher, Barbara Kracher, Parastou Kohvaei, Murray Yule, Hannes Loferer, Stefan Bissinger. Salt-inducible kinase inhibitor OMX-0407 drives cell-cycle arrest in vitro and in vivo: An in-depth MoA analysis by phospho-proteomics [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 514.

Abstract 7566: Identification of cancer subtypes with a ctDNA-based targeted methylation assay

Abstract Introduction: Identifying cancer subtypes is necessary for cancer diagnosis, prognosis determination, and treatment selection. Furthermore, as transformation between subtypes is increasingly recognized as a key resistance mechanism to targeted therapies, serial subtype reassessment is likely to gain adoption. Cancer subtypes have traditionally been determined by pathologists based on histology; more recently, molecular subtyping has been performed using IHC, RNAseq, or assays that detect genetic alterations. However, these methods have significant limitations, including tissue biopsy requirement (IHC and RNAseq), low discriminative resolution for distinct transcriptional programs (IHC and mutation detection), and poor reproducibility and feasibility (RNAseq). The GRAIL plasma-only, ctDNA-based targeted methylation platform is a robust, biopsy-free, scalable assay that can distinguish cancer methylation patterns between different cancer signal origins through the use of a proprietary classifier. Here, we explore the GRAIL platform’s potential to detect finer-scale differences in cancer biology by developing classification algorithms for subtyping of three common cancer types. Methods: As part of the Circulating Cell-free Genome Atlas (NCT02889978) and STRIVE (NCT03085888) studies, clinical data were recorded and plasma samples were collected, accessioned, stored, and processed through GRAIL’s targeted methylation assay from 3,989 cancer and 6,013 non-cancer participants. We developed algorithms to predict cancer status and subtype for breast (triple negative breast cancer [TNBC] model; 531 cancer training participants), lung (lung histology model; 334 cancer training participants), and head and neck (HPV model; 3090 cancer training participants) cancers. Dimensionality reduction of methylation data was performed to illustrate subtype separation within these cancer types. Performance of these three algorithms was assessed on a held-out cohort of cancer samples (184 breast, 241 lung, 67 head and neck) with detectable ctDNA. Results: The lung histology model correctly classified 95% (105/111) of adenocarcinomas, 88% (68/77) of squamous cell carcinomas, and 94% (59/63) of lung neuroendocrine carcinomas and tumors. The TNBC model correctly classified 84% (58/69) of TNBCs and 82% (94/115) of non-TNBCs. The HPV model correctly identified 98% (48/49) of HPV-positive head and neck cancers, and 89% (16/18) of HPV-negative head and neck cancers. Conclusions: GRAIL’s proprietary ctDNA-based targeted methylation platform demonstrates the ability to accurately predict cancer subtypes in multiple cancers using only a plasma sample without the need for tumor biopsy. Future efforts will be directed towards generalizing the GRAIL subtyping method to additional cohorts and cancer types. Citation Format: Tracy Nance, Timothy Shaver, Yifan Zhou, Margaret Antonio, Yinjie Gao, Jonathan Heiss, Robert Calef, Joseph Hiatt, Oliver Venn, Joerg Bredno, John Beausang, Lisa Newman, Charles Swanton, Chun Zhang. Identification of cancer subtypes with a ctDNA-based targeted methylation assay [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 7566.

Abstract 2782: Characterization of quiescence-associated secretory profile (QuASP) in cancer: A novel defining feature and therapeutic target

Abstract Senescent cells have a unique senescence-associated secretory profile (SASP) and understanding SASP has contributed to numerous advances in knowledge on aging and cancer biology. Quiescence, which is an important yet poorly understood mechanism for chemoresistance, is related but distinct from senescence. Quiescence shares a non-proliferative feature with senescence but is a reversible state in which quiescent cells can reenter the cell cycle. We hypothesized that, analogous to senescent cells, quiescent cells have a distinct quiescence-associated secretory profile (QuASP) and that defining the QuASP will uncover new genes and pathways associated with cancer cell viability and therapeutic resistance. Indeed, suggesting quiescent cells have a unique and biologically important secretome, we found that tumor conditioned medium (TCM) from quiescent ovarian cancer cells (qOvCa) vs. TCM from proliferating cancer cells increased chemoresistance. Similarly, TCM from quiescent cancer cells vs. TCM from proliferating cancer cells suppressed T cell proliferation and INF-gamma/Granzyme B secretion, suggesting a QuASP immunosuppressive effect. RNASeq analysis of qOvCa cells revealed the secreted factor Follistatin (FST) is upregulated in qOvCa and acted as a paracrine pattern to induce chemoresistance. Furthermore, FST was found to be upregulated in peritumoral fluid following chemotherapy and FST levels in patients with OvCa predicted poor prognosis. To identify additional QuASP factors, we used an ER-BIOID labeled system and LC-MS/MS to characterize the secreted proteins from qOvCa induced by serum starvation compared with normal cells in three OvCa cell lines (PT412, PT340, HEY1). Quiescent OvCa cells indeed have a secretome that is highly unique from proliferating cells, with 137/577 upregulated proteins (LFC>1) and 65/577 downregulated proteins (LFC←1 or no detection in quiescence). Several proteins identified as upregulated have been linked to immunosuppression and/or chemoresistance, oncogenesis and cell cycle were selected for validation and further analysis (CLU, VGF, SERPINE1). In conclusion, we find quiescent cells have a unique quiescence associated secretory profile and that the QuASP induces chemoresistance and immunosuppression. As such, this study has important implications for cancer therapy. Citation Format: Qi Jiang, Santiago Panesso-Gómez, Divya Natesan, Matthew L. MacDonald, Ronald J. Buckanovich. Characterization of quiescence-associated secretory profile (QuASP) in cancer: A novel defining feature and therapeutic target [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 2782.

Abstract 4451: Regulation of lipid metabolism and ferroptosis by DAXX

Abstract Intracellular lipid production in cancer cells supplies lipids to synthesize cell membranes and signaling molecules during rapid cell proliferation and tumor growth. Cancer cells also utilize fatty acid oxidation (FAO) to generate ATP to meet their energy demand. Notably, lipid metabolites can inhibit and trigger ferroptosis due to iron-dependent oxidation of polyunsaturated fatty acids (PUFAs). Therefore, identifying regulators that maintain the intricate balance of lipid biosynthesis required for cell proliferation and survival is critical in cancer biology and therapy. Lipid metabolism is regulated by two oncogenic signaling pathways: the RAS-RAF-MEK-MAPK and the mammalian target of rapamycin (mTOR) pathways. About 30% of all cancers harbor constitutively active mutations in KRAS, HRAS, or NRAS, resulting in hyperactive RAS-RAF-MEK-MAPK signaling to drive tumorigenesis, metastatic progression, immune evasion, and resistance to therapy. KRAS regulates lipid uptake, lipid synthesis, and FAO. mTOR is a serine/threonine kinase acting as a key intracellular signaling hub to regulate nutrient homeostasis, metabolism, protein synthesis, and autophagy. The mTORC1 complex promotes lipogenesis. The RAS and mTOR signaling pathways exhibit both positive and negative cross-regulation. The coordinated activity of both pathways is critical to sustained tumor growth. Notably, mTORC1 signaling inhibition enhances RAS-RAF-MEK-MAPK signaling to promote cancer cell survival and proliferation. Furthermore, constitutive mTORC1 signaling induces cell death when the supply of unsaturated FAs is limited. However, the molecular link for coordinating the activity of the RAS and mTOR signaling pathways remains poorly defined. Death domain-associated protein (DAXX) is essential for mouse embryonic development and has ill-defined pro-cell survival functions. Our lab has a long-standing interest in deciphering DAXX’s complex biological functions. Our recent study shows that DAXX drives tumorigenesis by promoting lipogenic gene expression and lipid synthesis through interacting with sterol regulatory element-binding proteins SREBP1 and SREBP2 (SREBP1/2) (Mahmud et al., 2023, PMID 37045819). Unexpectedly, our new data reveal that DAXX inhibits ferroptosis. Significantly, phosphorylation via RAS signaling appears to regulate DAXX’s activity in lipid synthesis and resistance to ferroptosis. Remarkably, disruption of DAXX-mediated lipid synthesis potentiates ferroptosis due to mTORC1 activity. Based on these observations, we propose that stimulated by the RAS-RAF-MEK-MAPK oncogenic signaling, DAXX promotes tumorigenesis through upregulating genes for lipid synthesis and resistance to ferroptosis, and that the lack of DAXX-mediated lipid synthesis leads to sensitization of cells to ferroptosis due to mTORC1’s proliferative effects. (Supported by FDOH grant 23K03). Citation Format: Wenlin Yang, Nikee Awasthee, Qi Chen, Seth Hale, Daiqing Liao. Regulation of lipid metabolism and ferroptosis by DAXX [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 4451.

Abstract 3015: HD-PTP mediates tumor suppression via modulation of anti-tumor immunity

Abstract The role of circulating extracellular vesicles in cancer biology is an area of intense research interest. Here, we reveal a tumor suppressor mechanism of HD-PTP (His Domain Protein Tyrosine Phosphatase, encoded by PTPN23), a protein associated with ESCRT (endosomal sorting complex required for transport), a complex that controls endosome sorting and exosome secretion. While loss of HD-PTP is known to be tumorigenic in mice and is frequently observed in human cancers including Triple Negative Breast Cancer (TNBC), the relevant pathways have remained obscure. We find that inhibition of HD-PTP in vivo promotes tumor progression selectively in a syngeneic, immune-competent TNBC model but not in a matched immune-deficient model. Through systematic profiling of the exosomal proteome in HD-PTP proficient and deficient cells, we identify PD-L1 as a key exosomal cargo selectively enriched due to loss of HD-PTP. Mechanistically, we show that inhibition of HD-PTP results in PD-L1 stabilization, its co-localization with the exosomal marker CD63, the enrichment of endosomal PD-L1 and subsequent increase in ExoPD-L1 release. Exosomes produced post HD-PTP loss inhibits antigen-dependent T cell activity in vitro, and HD-PTP inhibition in a syngeneic TNBC model promotes non-cell-autonomous, exosome- and PD-L1-dependent tumor progression, associated with reduced T cell infiltration and altered macrophage polarization. Consistent with these findings, low HD-PTP levels in human solid tumors are associated with decreased tumor infiltrating lymphocytes, poor response to immune checkpoint inhibition and inferior overall survival. Taken together, our studies unveil a novel tumor suppressor pathway controlling PD-L1 trafficking and ExoPD-L1 secretion, highlighting the critical roles of HD-PTP and ESCRT in anti-tumor immunity. Citation Format: Chenxu Guo, Sheng Sun, Nayana Thimmiah, Agustina Maccio, Siang Koh, Leif Ellisen. HD-PTP mediates tumor suppression via modulation of anti-tumor immunity [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 3015.

Abstract 6210: The cancer omics and drug experimental response dataset (CODERData): A harmonized benchmark dataset for machine learning models of drug response prediction

Abstract Background: Determining a patient’s response to a specific therapy is a vital step in developing personalized cancer treatment. Personalized treatment relies on two key technological advancements: algorithms tailored to each patient’s molecular profiles, and comprehensive datasets detailing the effects of patient diversity on drug response. Despite recent advancements in machine learning-based models, each new algorithm requires curation of numerous datasets, which poses a significant burden to researchers who need to evaluate and compare various algorithms. Currently, datasets include extensive genomics, transcriptomics, proteomics and metabolomics measurements along with drug response data (i.e., cell viability) for each cell line, collected through the Cancer Cell Line Encyclopedia (CCLE) and other initiatives. Additional omics data is available for tumor organoids and patient samples generated by consortia such as Human Cancer Model Initiative (HCMI) and the Clinical Proteomic Tumor Analysis Consortium (CPTAC). However, to date there has been little public effort to annotate and harmonize these data across repositories. Methods: To address this need, we developed the Python package coderdata that collates the most up-to-date cancer omics and drug response data. We curated four public cancer datasets, establishing reproducible pipelines that standardize data retrieval, formatting, and integration so the datasets can be built on a cluster if needed. The datasets undergo bi-monthly synchronization with FigShare, ensuring the data is up to date and available. Scientists can use coderdata to retrieve and format data on the command line interface as well as within Python scripts. Results: Coderdata is a straightforward Python package that will enable the development and benchmarking of diverse machine learning applications in cancer research. At its core, it represents reproducible data harmonization that enables heterogeneous datasets to be analyzed in bulk. This Python package downloads and standardizes data from multiple consortia-related resources including HCMI, CPTAC, CCLE, and BeatAML, together representing 4931 multi-omics samples from across 250+ cancer types. These datasets include cancer data metrics such as copy number, mutation, transcriptomics, proteomics, miRNA, methylation, and drug response data. Conclusions: The applications of machine learning in cancer biology are hampered by the distributed nature of existing datasets. As such, the collection and standardization of data by coderdata substantially reduces the time investment required for data curation in cancer research. Direct access to benchmark multi-omics and drug response datasets enables scientists to focus on algorithm development for tumor drug response prediction, potentially accelerating the discovery of therapeutic strategies. Citation Format: Jeremy Jacobson, Sydney Schwartz, M. Ryan Weil, Neeraj Kumar, Sara Gosline. The cancer omics and drug experimental response dataset (CODERData): A harmonized benchmark dataset for machine learning models of drug response prediction [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 6210.

Abstract 7393: Tumor model to tumor treatment: Applying deep learning approaches to map multimodal data from cancer model systems to patients

Abstract Despite large-scale efforts to measure the effect of drug screens in cancer cell lines, mapping the effects of drugs to patient samples has been a challenge. Biological differences between cell lines and patients, such as lack of immune system or microbiome, in-vitro survival adaptations, and biases in measurement technologies create differences across sample modalities that can confound analysis including prediction with machine learning. In this work, we propose a multiway batch correction strategy to enable algorithmic prediction of tumor drug response across model systems and patient data.Recent advances in batch correction algorithms have been motivated by the need to correct for batch effects in single-cell omics and include diverse approaches such as variational autoencoders (VAEs) and generative adversarial networks (GANs). Given the successes of these generative deep learning methods in single cell sequencing analysis, we worked to employ similar approaches to correct large omics measurements across various cancer datasets. Here, we describe mapping of datasets from diverse data sources and model systems to the same space, so that a predictive model of drug response built in a system such as cell lines can be used in biologically relevant models such as organoids, patient derived xenografts, and tumor data. Specifically, we introduce a modified loss function in a VAE using cosine similarity distance to minimize the effect of different cancer model systems in predicting cancer types. We evaluate the method on standard data types for drug response prediction - gene expression, copy number variation, and protein abundance. For this method, the cosine similarity is added as an additional term to the VAE reconstruction and Kullback-Leibler divergence loss terms. This injects a quantification of the dissimilarity between the tumor and tumor model distributions into the backpropagation and gradient descent for updating the model parameters resulting in an encoded representation of the data where the effect of data source has been attenuated while preserving the phenotypic signal. We evaluate our approach for biological signal preservation while reducing model system-specific noise with logistic regression and Euclidean distance. Our results show that the proposed VAE can effectively correct for platform effects and improve the accuracy of downstream integrative analyses. This study has the potential to improve the accuracy and translatability of proteogenomic drug response studies. The proposed modified VAE could be used to correct for platform effects in a variety of datasets, including those from different studies, different platforms, and different cancer types. This could lead to new insights into cancer biology, calibration of cancer patient digital twins, and the development of new diagnostic and therapeutic strategies. Citation Format: Brian Karlberg, Raphael Kirchgaessner, Jeremy R. Jacobson, Kyle Ellrott, Sara J. Gosline. Tumor model to tumor treatment: Applying deep learning approaches to map multimodal data from cancer model systems to patients [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 7393.

Abstract 5475: Development of high-throughput 3D bioprinted pediatric models for precision medicine

Abstract Childhood cancer patients with high-risk disease have poor prognosis. Therapies given to treat these patients are often highly toxic and determined empirically, exposing children to damaging and ineffective therapies. Precision medicine is a promising strategy for these patients. However, tumor biopsies often lack sufficient sample for phenotypic drug screening, requiring cell expansion via primary cell culture or development of patient-derived xenograft models - a slow process with variable success rates. There is an unmet need for sensitive, predictive, and timely drug testing models. Dynamic interactions between cells and the extracellular matrix (ECM) impact cellular signaling and response to cancer therapy. The development of patient-derived tumor models that are reflective of the patient sample and achieved in a clinically relevant timeframe will be game changing. In-silico analysis of 265 ECM gene expression from a high-risk neuroblastoma and sarcoma patient cohort (n=145) identified collagens and fibronectin to be the most abundantly expressed ECM genes in the tumor samples. To reflect this environment, we developed tuneable tissue ECM-like bioinks where cells are embedded within the bioink that mimics growth constraints within a tumor [1]. Specifically, we functionalized the bioinks with peptides of collagen I, fibronectin, and laminin to mimic the ECM environment and combined this with HTP 3D bioprinting technology to create patient-derived tumoroids. In this proof-of-concept study, we identified conditions that enable the growth and expansion of the neuroblastoma and sarcoma cells in a 3D ECM-like environment. The tumor samples proliferate in the bioinks and HTP drug screening was used to determine drug sensitivity. Importantly, the bioprinted cells reflect the genetic and phenotypic characteristics of the original patient tumors and retained their tumorigenic capacity in vivo. Collectively, we have successfully generated preclinical models that reflect patient tumors and are directly compatible with preclinical drug testing. Importantly, our 3D bioprinting platform has the potential to advance cancer precision medicine in a clinically relevant timeframe. These findings have broader applications for a range of cancer types for preclinical testing, drug discovery and cancer biology.1. Utama, RH, et al. Macromolecular Bioscience, 2021. 21(9):e2100125 Citation Format: Valentina Poltavets, MoonSun Jung, Joanna Skhinas, Kathleen Kimpton, Alvin Kamili, Gabe Tax, Jie Mao, Louise Cui, Marie Wong, Mark J. Cowley, Loretta Lau, Emmy ME Dolman, John J. Gooding, Maria Kavallaris. Development of high-throughput 3D bioprinted pediatric models for precision medicine [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 5475.

Abstract 3417: Dissecting tumor microenvironment to predict clinical outcome in prostate cancer

Abstract Prostate cancer is one of the major causes of cancer death in males, and its prevalence is particularly high in developed countries such as the United States and Western Europe. However, death rates in developing and underdeveloped countries are greater, presumably, due to a lack of routine clinical check-ups, poor health awareness, inadequate screening resources, and clinical intervention. Much progress has already been made using cutting-edge technologies like whole genome sequencing, RNAseq, phosphoproteomics, and targeted transcriptomic Nanostring profiling, etc. However, understanding of the prostate tumor microenvironment as a whole in clinical samples remains very limited. Here we use the latest genomic, proteomics, and metabolomic tools not only to understand the biology of prostate cancers but also their correlation with patient demography and clinical outcome. We recruited 80 patients from both tertiary research hospitals and clinical centers in the eastern region of India. All of their demographic information is collected along with their clinical outcome. Pathological evaluation revealed only 50 patients with positive Prostate Carcinoma. We performed a detailed analysis using experimental data (from genomic, and proteomic) in a cohort of patients' routine biomarkers (PSA and PSMA), histopathology, and clinical outcome. Our data demonstrate no linear correlation of any of the individual markers or parameters like AR status, PSA, Prostate Specific Acid Phosphatase, Prostate-Specific Membrane Antigen (PSMA), Alpha-methylacyl-CoA racemase (AMACR), Mesothelin, PD-L1, and other potential genomic and proteomic alterations or any histopathological readouts. However, a clear understanding of the relationship between these multiparameter data, disease pathology, and clinical outcomes in a group of patients has been established. The heterogeneity of these individual data for tumor microenvironments will lead us to identify novel biomarkers for the clinical response of targeted drugs, accelerating personalized treatment strategies. Citation Format: Aritri Bhattacharjee, Manjusha Biswas, Amjad Husain, Asim Kr Das, Sourav Karmakar Karmakar, Tapan Mondal, Pinaki Roy, Manas Kr Mondal, Badal Kumar Sahu, Nabendu Murmu, Partho Nath, Chandra C. Ghosh, Pradip Kumar Majumder. Dissecting tumor microenvironment to predict clinical outcome in prostate 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 3417.

Abstract 4979: Genomic profiling of early-onset metastatic colorectal cancer based on tumor sample location

Abstract Background: Here, we describe analyses towards identifying and comparing genetic variations between the primary and metastatic sites in early-onset metastatic colorectal cancer patients. Methods: We selected patients with early-onset metastatic colorectal cancer (under 50 years old) using data from the American Association for Cancer Research Project GENIE (version 14.1). We used the Fisher exact test to compare genetic mutations between the primary tumor and metastatic sites, complemented by the Benjamini-Hochberg adjustment method. Results: In a total of 1,791 patients with early-onset metastatic colorectal cancer, 27.1% had tumor samples from metastatic sites, while the majority, 72.9%, were from the primary tumor location. The most common mutations found were in the TP53 gene (77.6%), followed by APC (76.0%), KRAS (42.4%), and PIK3CA (19.0%). Notably, the metastatic samples had a significantly higher occurrence of SMAD4 mutations compared to their primary site counterparts (20.8% vs. 14.0%, p<0.001, q<0.001). Conversely, the primary tumor samples exhibited higher frequencies of TCF7L2 and ARID1A mutations (16.9% vs. 10.6%, p<0.001, q<0.001, and 13.0% vs. 6.4%, p<0.001, q<0.001, respectively). Conclusion: Determining the specific genes responsible for the formation of metastatic tumors is crucial for a deeper understanding of the disease's underlying biology in early-onset metastatic colorectal cancer. Such genomic details are crucial to pave the way to the discovery of potential biomarkers for diagnosis and the development of new cancer therapeutics. Citation Format: Muhammet Ozer, Suleyman Y. Goksu, Busra Bacik Goksu, Nina N. Sanford, Amy Jones, Nilesh Verma, Syed Kazmi. Genomic profiling of early-onset metastatic colorectal cancer based on tumor sample location [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 4979.

Abstract 5868: Upregulation of HER3 and MET in non-small cell lung cancer cells resistant to EGFR tyrosine kinase inhibitor

Abstract Introduction: Prior research demonstrates the importance of studying epidermal growth factor receptor (EGFR) activating mutations for better understanding the biology of non-small cell lung cancer (NSCLC), which comprises the majority (~80%) of lung cancers. EGFR-targeted tyrosine kinase inhibitors (TKIs) have been used in the clinic to treat NSCLC with EGFR activating mutations. First and second-generation EGFR-TKIs are effective in NSCLC patients with the most common EGFR mutations (exon 19 deletion (Del19) and exon 21-point mutation (L858R)). A third generation EGFR-TKI, osimertinib (AZD9291), has been developed to target the T790M resistance mutation, but patients are starting to show resistance to this line of therapy as well. Our study aims to elucidate the underlying mechanism(s) of EGFR-TKI resistance in NSCLC cells. Methods: NSCLC cell lines, including PC-9 and HCC827, which have the Del19 EGFR activating mutation, were utilized for experiments. From the parental cell lines, several cell lines resistant to the EGFR-TKIs were previously established. Cell proliferation (MTS) assays were used to confirm the resistance phenotype of the established cell lines. Western blot assays and RT-qPCR were utilized to determine changes in the expression level of several membrane receptors and their downstream effectors. Results: Our preliminary analysis showed that both human epidermal growth factor 3 (HER3) and mesenchymal-epithelial transition factor (MET) were upregulated in the EGFR-TKI-resistant cell lines as compared to their parental counterparts. Further studies revealed an increased level of phosphorylated STAT3 (p-STAT3) and ERK1/2 (p-ERK1/2) in the resistant cell lines when compared to the parental cell lines, suggesting the possible involvement of HER3 and/or MET in the activation of downstream signaling pathways. Upregulation of HER3 and MET was found at both the protein and mRNA level. Conclusion: Based on our initial findings, membrane receptors, including HER3 and MET, could be working together to continue activating downstream signaling pathways to evade the effects of osimertinib, resulting in resistance. Additional work is underway to define the role of HER3 and MET in the NSCLC cells resistant to EGFR-TKIs. Citation Format: Margaret Larsen, Hui Lyu, CongCong Tan, Yakun Wu, Bolin Liu. Upregulation of HER3 and MET in non-small cell lung cancer cells resistant to EGFR tyrosine kinase inhibitor [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 5868.

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 2769: Long non coding RNA H19/cell adhesion molecules circuitry as novel target and diagnostic tool for metastatic prostate cancer

Abstract In the complex tumor biology of prostate cancer (PCa), we previously contributed by demonstrating that estrogen receptor and hypoxia signaling promoted transcription of progression-associated genes. Notably, combined treatment, estrogens plus hypoxia, caused a significant down regulation of the long noncoding RNA H19, one of the most sensitive to these pro-tumoral stimuli. Mechanistically, H19 acts as transcriptional repressor: H19 over-expression decreases E-cadherin (CDH1) level causing epithelial-to-mesenchymal transition whereas H19 reduction promotes the expression of E-cadherin and β4 integrin (ITGB4) switching the tumor dissemination program toward an alternative mechanism, specifically the cohesive metastatic phenotype. We focused on this H19/cell adhesion molecules circuitry by investigating its role as: 1.Novel prognostic biomarker at the time of biopsies. eNOS, HIF2a and β4 integrin expression was evaluated by immunohistochemistry, H19 and CDH1 transcripts by Droplet Digital PCR on FFPE-biopsies in a retrospective cohort of PCa patients [n = 30; Gleason score GS≤ 7(3+4) n= 17, GS ≥7(4+3) n= 13; biochemical, local, or metastatic recurrence defining disease progression (n=8/30; time of recurrence: range 2-6 years)]. Importantly, multivariate analysis of combined biomarkers, named “Bioscore”, defined by the presence of at least 3 among HIF-2α, eNOS, CDH1, β4 integrin ≥cut off or H19≤cut off revealed its prognostic value for progression and Progression-Free Survival determined using the ROC analysis (p=0.003) and Kaplan Meier curve (p= 0.005), respectively. 2.Master regulator of metastatic program in vivo and ex vivo PCa experimental models. Upon H19 silencing, mimicking combined estrogens plus hypoxia treatment, luciferase-positive PC-3 and 22Rv1 cells led to increased E-cadherin and β4 integrin expression, enhanced tumor growth and metastasis formation at bone, lung, and liver in PCa mouse models. Further, treatment with H3K27 demethylase inhibitor, GSK-J4, rescued cell adhesion molecules expression by modulating H3K27me3 level at gene promoters, reduced metastasis number and size, and induced cell death in PCa-derived Organotypic Slice Cultures. Additionally, treatment with JQ1 and dBET6 BET protein family inhibitors) markedly reduced both E-cadherin and β4 integrin levels, cell proliferation and in vivo tumor growth. Intriguingly, H19 silencing increased BRD3 and BRD4 levels, implicating H19 in BRD transcription. Overall, this research enhances our understanding of the molecular mechanisms driving aggressive prostate cancer phenotypes, providing a foundation for new diagnostic and therapeutic strategies in prostate cancer management. Citation Format: Valeria Pecci, Aurora Aiello, Sara De Martino, Cristian Ripoli, Dante Rotili, Francesco Pierconti, Francesco Pinto, Claudio Grassi, Carlo Gaetano, Alfredo Pontecorvi, Lidia Strigari, Antonella Farsetti, Simona Nanni. Long non coding RNA H19/cell adhesion molecules circuitry as novel target and diagnostic tool for metastatic prostate 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 2769.