bluuebunny/crossref_metadata_2025 huggingface dataset:
Abstract B071: A genetic approach to selectively inhibit macropinocytosis while sparing autophagy
Authors: Lim Rebecca M , Chu Brandon , Edinger Aimee Lara
Published: February 2024

Macropinocytosis is a bulk endocytic process that can fuel tumor growth and drug resistance by providing access to extracellular protein and necrotic cell debris. This process is primarily studied by utilizing the chemical inhibitor, 5-(N-ethyl-N-isopropyl)-Amiloride (EIPA), but this inhibitor is nonselective can hinder proliferation even in non-macropinocytic breast cancer cells. Hence, a more selective, genetic approach is needed. Formation of macropinosomes is dependent on the actin cytoskeleton, which in turn is regulated by CARMIL1, a large multimeric protein that regulates the actin capping protein. CARMIL1 is essential for macropinocytosis, and mutation of two residues in the Capping-Protein Interaction (CPI) region of CARMIL1 to alanine (CARMIL1-AA) limits the CARMIL1-capping protein interaction and more importantly, inhibits macropinocytosis upon introduction of exogenous CARMIL1-AA in tumor cells. Therefore, CARMIL1-AA is a genetic tool to study the effects of macropinocytosis on other cellular processes. However, autophagy, a lysosome-dependent recycling system that enables cell survival, additionally utilizes actin to form autophagosomes. The overall goal of this project is to determine whether CARMIL1-AA specifically inhibits macropinocytosis while still supporting autophagy. CARMIL1-WT and -AA mutant cells were generated using the MMTV-PyMT tumor model and HeLa cell lines and validated for CARMIL1 expression by western blot and quantitative PCR and for macropinocytosis by dextran analysis. These cells were evaluated for autophagic flux by western blot for LC3 I/II and by utilizing a GFP-LC3-RFP-LC3ΔG reporter. Our observation that CARMIL1-AA does not impact autophagy enables further investigation of the importance of macropinocytosis in therapeutic resistance and in shaping the tumor microenvironment.

Citation Format: Rebecca M Lim, Brandon Chu, Aimee Lara Edinger. A genetic approach to selectively inhibit macropinocytosis while sparing autophagy [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Breast Cancer Research; 2023 Oct 19-22; San Diego, California. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_1):Abstract nr B071.
Abstract B072: Loss of the tumor and metastasis suppressor RasGAP DAB2IP mediates therapeutic resistance in HER2+ breast cancer
Authors: Perurena Naiara , Schade Amy , Pilla Natalie , Loi Patrick , Rodriguez Carrie , Gardner Alycia , Cichowski Karen
Published: February 2024

Resistance to HER2 inhibitors remains a clinical challenge in HER2+ breast cancer. Therefore, there is an urgent need to 1) understand the mechanisms that underlie resistance to these current treatments and 2) develop improved, and more importantly, curative combination therapies. We previously showed that the RasGAP DAB2IP is a tumor and metastasis suppressor in breast cancer. Interestingly, we have now generated robust data demonstrating that the loss of DAB2IP also mediates therapeutic resistance in HER2+ breast cancer. First, we genetically ablated DAB2IP in multiple HER2+ breast cancer cell lines and performed manual counting experiments after 6 days of HER2 TKI treatment. In all cell lines, DAB2IP knockdown conferred resistance to HER2 inhibitors. Since HER2 inhibitors are known to induce both apoptosis and senescence, we next investigated how DAB2IP loss specifically affects these phenotypes. Interestingly, DAB2IP knockdown prevented TKI-induced caspase-3/7 activation, measured by Incucyte live cell imaging, and enabled the regrowth of cells in long-term 10-day treatment and drug washout experiments, monitored by Incucyte or crystal violet staining. Mechanistically, stable knockdown of DAB2IP reduced the suppression of the AKT and ERK pathways and the induction of the pro-apoptotic protein Bim upon HER2i treatment. In addition, cell cycle progression pathways were enriched in DAB2IP-deficient cells on lapatinib treatment and immunoblots revealed higher residual levels of pRb and low levels of p27 in these cells. Interestingly, the levels of these proteins were restored and regrowth in low density assays was inhibited with co-treatment with an NF-kB inhibitor. We next evaluated the relevance of DAB2IP loss in mediating HER2 inhibitor resistance in a SUM190 orthotopic xenograft model. Importantly, while control tumors regressed upon lapatinib treatment, DAB2IP-deficient tumors did not regress and grew with kinetics comparable to vehicle-treated tumors after few days on treatment. Further understanding the pathways deregulated by DAB2IP loss upon HER2i treatment will be essential for developing effective therapeutic strategies to combat resistance induced by DAB2IP loss.

Citation Format: Naiara Perurena, Amy Schade, Natalie Pilla, Patrick Loi, Carrie Rodriguez, Alycia Gardner, Karen Cichowski. Loss of the tumor and metastasis suppressor RasGAP DAB2IP mediates therapeutic resistance in HER2+ breast cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Breast Cancer Research; 2023 Oct 19-22; San Diego, California. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_1):Abstract nr B072.
Abstract B086: Association of breast cancer-relevant DNA repair genes with postmenopausal breast cancer risk in UK Biobank
Authors: Smotherman Carmen , Sprague Brian , Braithwaite Dejana , Qin Huaizhen , Yaghjyan Lusine
Published: February 2024

Purpose. Several polymorphisms have been described in DNA damage signaling and repair genes and some of the polymorphisms have been implicated in genetic susceptibility to breast cancer. However, there is no consensus result yet for most of these polymorphisms. In this study, we focused on evaluating selected SNPs in BRCA1, BRCA2, ATM, XRCC1, XRCC2, XRCC3, and XPD (ERCC2) genes that have been previously reported to be associated with breast cancer risk and are available in the UK Biobank. Methods. This study included 150,929 postmenopausal women (5,969 with BCa) from UK Biobank, a population-based prospective cohort. Cancer diagnoses were ascertained through the linkage to the UK National Health Service Central Registers. DNA was extracted from blood samples collected from participants at enrollment in UK Biobank. Samples were genotyped using the Applied Biosystems UK BiLEVE Axiom Array or the Applied Biosystems UK Biobank Axiom Array. The positions of markers in the data are in GRCh37 coordinates. SNPs with frequency < 1% in the study population were excluded from analyses. We included the following SNPs in the final analyses: XRCC3-rs861539, BRCA1-rs16942, BRCA1-rs4986852, XRCC1-rs25487, XRCC1-rs25489, XRCC1-rs1799782, XPD (ERCC2)-rs13181, XPD (ERCC2)-rs1799793, XRCC2-rs3218536, ATM-rs1800056, ATM-rs1800057, BRCA2-rs144848, BRCA2-rs4987117, and BRCA2-rs11571833. Information on breast cancer risk factors was collected at baseline. Cox proportional hazards regression models were used to analyze the association between each SNP and breast cancer risk while adjusting for known breast cancer risk factors. The risk estimates were presented as hazard rations (HRs) and their corresponding 95% confidence intervals (CIs). Results. The mean age of the study population at enrollment was 60.1 years (range 40-71 years). Heterozygous carriers of BRCA2-rs11571833 T allele were found to have an increased risk of breast cancer (HR=1.22, 95% CI 1.02, 1.46, p-trend = 0.033) compared to the homozygous carriers of the BRCA2-rs11571833 A allele. No other significant associations between other SNPs and breast cancer risk were found. Conclusions. We found a significant association between SNP BRCA2-rs11571833 and postmenopausal breast cancer risk. Our findings contribute to the existing evidence on the association of high-risk polymorphisms in DNA damage signaling and repair genes with postmenopausal breast cancer risk.

Citation Format: Carmen Smotherman, Brian Sprague, Dejana Braithwaite, Huaizhen Qin, Lusine Yaghjyan. Association of breast cancer-relevant DNA repair genes with postmenopausal breast cancer risk in UK Biobank [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Breast Cancer Research; 2023 Oct 19-22; San Diego, California. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_1):Abstract nr B086.
Abstract IA20: Hormonal action in breast cancer: Common features and unique properties that drive tumor development and outcome
Authors: Zwart Wilbert
Published: February 2024

Estrogen receptor (ER) occupies many thousands of regions throughout the human genome. Interestingly, the functional implications of most of these chromatin-bound sites remain completely elusive. In two interconnected stories, I will highlight distinct genomic features that differentiate ER genomic action between patient subgroups, but also between individual patients. Between patients subgroups, we identify clearlty distinct profiles of ER action, dictated by Glucocorticoid Receptor (GR) activity. We show that the activity status of GR determines luminal subtype identity and is associated with patient outcome. GR suppresses tumor growth by engaging with ER, leading to redistribution of ER on the chromatin and upregulation of the tumor suppressor gene ZBTB16. We importantly demonstrate that clinically available epigenetic inhibitors, which mimic GR-induced gene repression, can effectively suppress the growth of highly aggressive ER-positive breast cancer cells displaying absence of GR activity. In a second study, I will elaborate on the massive inter-patient heterogeneity of ER chromatin interactions, with direct biological and clinical implications. While the vast majorty of ER/DNA binding events are poorly conserved between patients, common ER sites are most-transcriptionally active and enriched for breast cancer risk SNPs. With that, we present a natural hierarchy of ER genomic action, identifying those regiosn with the most-direct impact on breast cancer development and progresion.

Citation Format: Wilbert Zwart. Hormonal action in breast cancer: Common features and unique properties that drive tumor development and outcome [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Breast Cancer Research; 2023 Oct 19-22; San Diego, California. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_1):Abstract nr IA20.
Abstract A026: EGF/EGFR signaling in priming for resistance to BRAF/MEK inhibitors in melanoma
Authors: Vander Velde Robert J. , Shaffer Sydney M.
Published: February 2024

Targeted therapies kill cancer cells very efficiently. However, the effectiveness of targeted therapies is limited by the eventual emergence of resistance, arising from a small subset of cells capable of surviving therapy. Our work has shown genetically homogeneous cells, in distinct transcriptomic states, are capable of surviving combination BRAF and MEK inhibition. In the presence of targeted therapies these rare cells transform into resistant cells, we therefore call these cells ‘primed’ for resistance. Our research has focused on characterizing these primed cells, however, the mechanisms of survival remain unknown. Since primed cells overexpress receptor tyrosine kinases (RTKs), which are associated with growth and survival, we tested if overexpression of the RTK EGFR could explain priming and subsequent resistance. While melanoma cells in which we artificially overexpressed EGFR had no significant increase in resistance, EGFR overexpressing cells in the presence of exogenous EGF are highly resistant to combination BRAF/MEK inhibition. While EGF is not overexpressed in primed cells, preliminary data suggests that while most cells reduce EGF expression in the presence of BRAF/MEK inhibition, primed cells maintain their baseline expression, potentially maintaining EGF/EGFR signaling in these colonies. We are therefore testing if EGF/EGFR signaling is necessary in vitro by knocking out EGF or EGFR. Furthermore, to test if EGF/EGFR signaling can create a primed state, we used flow cytometry to determine expression of the prime cell marker NT5E. In cells with confirmed EGFR overexpression we observed an increased fraction of NT5E overexpressing cells, suggesting that EGF/EGFR signaling could initiate aspects of primeness beyond simple survival. Further research will determine if EGF/EGFR signaling can initiate an overall primed transcriptional state. The heritability of any primeness as a consequence of EGF/EGFR signaling will inform us if this signaling is a potential cause of priming or a mechanism by which paracrine signaling and/or stromal protection can eventually result in independent resistance.

Citation Format: Robert J. Vander Velde, Sydney M. Shaffer. EGF/EGFR signaling in priming for resistance to BRAF/MEK inhibitors in melanoma [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr A026.
Abstract A031: Investigating the mechanism and impact of frequency-dependent interactions in non-small cell lung cancer
Authors: King Eshan S. , Tadele Dagim S. , Strobl Maximillian A. R. , Scott Jacob G.
Published: February 2024

Introduction: Pre-treatment tumor heterogeneity in cancer is a major driver of drug resistance. Given that resistance mechanisms often impose a fitness cost, the presence of drug-resistant clones prior to treatment poses a paradox—less fit drug-resistant clones should be selected out of a growing population. Recent work has identified frequency-dependent interactions (FDIs) in cancer cell lines, where different proportions of drug-sensitive and resistant cells modulate their respective fitness. FDIs may help explain pre-treatment drug resistance in cancer. Here, we sought to characterize FDIs in a drug-resistant model of non-small cell lung cancer (NSCLC). Methods: We developed a drug-resistant cell line in NSCLC by transducing PC9 cells with BRAF V600E. We then quantified the frequency-dependent interaction between sensitive and resistant cell lines across a range of gefitinib concentrations using the previously published evolutionary game assay. We also implemented an agent-based spatial model of evolution to investigate the different potential molecular mechanisms of frequency-dependent interactions. Results: We found that, despite growing slower in monoculture, low proportions of resistant cells in co-culture with sensitive cells rescued their growth rate in the absence of drug. This phenomenon may help explain pre-treatment drug-resistance and may present a future targetable pathway. Using a computational model parameterized with this data, we investigated the impact of different molecular mechanisms of FDIs on tumor evolution. We found that a mechanism driven by compound diffusion, in contrast to a cell-cell contact mechanism, facilitates drug resistance to greater extent. Through a conditioned media transfer experiment, we found that the FDI in our experimental system is most likely governed by a compound released in the cell culture media. Conclusions: Here we have identified FDIs in an engineered model of drug resistance in NSCLC. Using a computational model, we demonstrated how different mechanisms of FDIs impact tumor evolution. Our ongoing work seeks to identify the specific molecular mechanism responsible for the observed FDIs. In the future, we may leverage this approach to modulate frequency-dependent interactions, allowing us to mitigate pre-treatment drug resistance in vivo.

Citation Format: Eshan S. King, Dagim S. Tadele, Maximillian A. R. Strobl, Jacob G. Scott. Investigating the mechanism and impact of frequency-dependent interactions in non-small cell lung cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr A031.
Abstract A035: Mutation of NOTCH1 is selected within normal esophageal tissues, yet leads to selective epistasis suppressive of further evolution into cancer
Authors: Glasmacher Kira A. , Cannataro Vincent L. , Mandell Jeffrey D. , Jackson Mia , Fisk J. Nic , Townsend Jeffrey P.
Published: February 2024

Sequencing of tissues from histologically normal esophagus, among other organs, has revealed that normal tissues acquire somatic variants that are also found in cancers arising from the same tissue types. Our understanding of how somatic mutations that are commonly found in normal tissue can contribute to tumorigenesis is limited: common somatic mutations may or may not confer phenotypes compatible with oncogenesis. However, the strength of selection for somatic variants that appear in both normal and cancer tissues can be quantified in each context using evolutionary modeling approaches. We studied the evolutionary trajectory from normal esophageal tissue to esophageal squamous-cell carcinoma (ESCC) by analysis of sequencing data from previous studies on normal esophageal epithelium and ESCC to reveal the stepwise contributions of somatic mutations to increased cellular division and survival. We also analyzed pairwise selective epistasis between somatically mutated genes that may lead to stepwise substitution patterns. We found that NOTCH1 substitutions are at high prevalence in normal tissue, and scaled selection coefficients indicate that NOTCH1 mutations are highly selected in normal esophageal tissue. In contrast, there is little to no positive selection for NOTCH1 mutations in ESCC, suggesting that NOTCH1 substitutions do not drive tumorigenesis. Indeed, NOTCH1 mutations have recently been shown to favor clonal expansion in normal esophageal tissue. Furthermore, we calculate that mutations in NOTCH1 exhibit antagonistic epistasis with well-known cancer drivers, including TP53, reducing selection for progressive mutations in tumorigenesis. This antagonistic epistasis likely underlies the low likelihood of tumor progression in the presence of NOTCH1 mutations in the esophagus.

Citation Format: Kira A. Glasmacher, Vincent L. Cannataro, Jeffrey D. Mandell, Mia Jackson, J. Nic Fisk, Jeffrey P. Townsend. Mutation of NOTCH1 is selected within normal esophageal tissues, yet leads to selective epistasis suppressive of further evolution into cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr A035.
Abstract A039: Metabolic evolution in breast cancer predicts organ-specific metastasis
Authors: Mathur Deepti , Liao Chen , Lin Wendy , La Ferlita Alessandro , Alaimo Salvatore , Taylor Samuel , Zhong Yi , Iacobuzio-Donahue Christine , Ferro Alfredo , Xavier Joao
Published: February 2024

The metastatic cascade is a critical component of cancer evolution. Understanding the rewired metabolism in organ-specific metastasis in breast cancer could help identify strategies to improve the treatment and prevention of metastatic disease. Here, we used a systems biology approach to assess the evolution of metabolic fluxes from parental breast cancer cells to their brain- and lung-homing metastatic derivatives. We found that divergent lineages had distinct, heritable metabolic fluxes. Lung-homing cells maintained adaptations for high glycolytic flux despite low levels of glycolytic intermediates, constitutively activating a pathway sink into lactate. This exacerbated Warburg effect –– stronger than the Warburg effect in the primary tumor –– was associated with a high ratio of lactate dehydrogenase (LDH) to pyruvate dehydrogenase (PDH) expression, a signature which correlated with lung metastasis in patients with breast cancer. While feature classification models trained on clinical characteristics alone were unable to predict tropism, the LDH/PDH ratio was a significant predictor of a patient's future metastasis to the lung but not to other organs, independent of other transcriptomic signatures. Lung- and brain-homing lineages had differential selection patterns in acidic metabolic microenvironments. High lactate efflux was also a trait in lung-homing metastatic pancreatic cancer cells, suggesting that lactate production may be a convergent phenotype in lung metastasis. Together, these analyses highlight the essential role that metabolic evolution plays in organ-specific cancer metastasis and identify a putative biomarker for predicting lung metastasis in breast cancer patients.

Citation Format: Deepti Mathur, Chen Liao, Wendy Lin, Alessandro La Ferlita, Salvatore Alaimo, Samuel Taylor, Yi Zhong, Christine Iacobuzio-Donahue, Alfredo Ferro, Joao Xavier. Metabolic evolution in breast cancer predicts organ-specific metastasis [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr A039.
Abstract B007: Reconstruction of cellular phylogenies and analysis of gene expression variation in single cells
Authors: Miura Sayaka , Kumar Sudhir
Published: February 2024

In cancer, somatic mutations occur continuously, causing cell populations to evolve. These somatic mutations result in the evolution of cellular gene expression patterns that can also change due to epigenetic modifications and environmental changes. By exploring the concordance of gene expression changes with molecular evolutionary trajectories of cells, we can examine the role of somatic variation on the evolution of gene expression patterns. In these endeavors, reliable inference of the evolutionary relationship of single cells is a key step. However, single-cell sequences contain many errors and missing bases, which necessitate advancing standard molecular phylogenetics approaches for applications in analyzing these datasets. We first show our new computational approach (TopHap+) that integratively applies standard phylogenetic optimality principles and patterns of co-occurrence of sequence variations to produce more expansive and accurate cellular phylogenies from single-cell sequence datasets. We then present Multi-Omics Concordance Analysis (MOCA) software to jointly analyze gene expressions and genetic variations from single-cell RNA sequencing profiles. MOCA outputs cells and genes showing convergent and divergent gene expression patterns in functional genomics.

Citation Format: Sayaka Miura, Sudhir Kumar. Reconstruction of cellular phylogenies and analysis of gene expression variation in single cells [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr B007.
Abstract B015: Tobacco-derived miRNAs and their crosstalk with human transcripts towards carcinogenesis: A cross kingdom approach
Authors: Patel Saumya , Bhavsar Manasi , Rawal Rakesh
Published: February 2024

There are more than 70 different species of Nicotiana reported around the world; however, Nicotiana tabacum (common tobacco) and Nicotiana rustica (aztec tobacco) are widely used for snuffing, chewing, smoking, etc., worldwide. Early reports have described that tobacco causes cancer and is associated with many neurological and cardiac disorders. The current study was an effort to understand the paradoxical regulatory mechanism of tobacco-derived miRNAs on human transcripts at 3’ untranslated regions (UTRs) through a computational and experimental genomics approach. This is the first attempt at cross-kingdom analysis where tobacco-specific miRNAs were predicted from different available sources like express sequence tags (EST), genome-wide approaches, and deep sequencing. The miRNA-derived plant targets were identified using stringent bioinformatics methods. A total of 164 mature reported miRNAs, 38 miRNAs from EST datasets, and 21 miRNAs from the genome were studied in detail for cross-kingdom regulation. The potential predicted and reported tobacco-derived miRNAs were analysed against human transcripts. Interestingly, we found tobacco-derived miRNAs such as miR156, miR403, miR7997, miR8011, and miR8036 target tumour suppressor genes and have a putative role in pathways in cancer. Collectively, we have identified a comprehensive set of miRNAs from small RNA sequencing of N. rustica and revealed 842 new miRNAs that have not been reported yet and have putative targets in cancer pathways like AMPK and WNT signalling pathways. Conclusively, this study is the first report of intra- and interspecies relationships using N. tabacum miRNAs with Human and has created a clear road map to focus on specific cancer targets that are modulated by tobacco-derived miRNAs for future studies.

Citation Format: Saumya Patel, Manasi Bhavsar, Rakesh Rawal. Tobacco-derived miRNAs and their crosstalk with human transcripts towards carcinogenesis: A cross kingdom approach [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr B015.
Abstract B023: Paracrine enhancement of tumor cell proliferation provides indirect stroma-mediated chemoresistance via acceleration of tumor recovery between chemotherapy cycles
Authors: Miroshnychenko Daria , Miti Tatiana , Kumar Pragya , Miller Anna , Laurie Mark , Giraldo Nathalia , Bui Marilyn M. , Altrock Philipp M. , Basanta David , Marusyk Anriy
Published: February 2024

The ability of tumors to survive therapy reflects both cell-intrinsic and microenvironmental mechanisms. Across many cancers, including triple-negative breast cancer (TNBC), a high stroma/tumor ratio correlates with poor survival. In many contexts, this correlation can be explained by the direct reduction of therapy sensitivity by stroma-produced paracrine factors. We sought to explore whether this direct effect contributes to the link between stroma and poor responses to chemotherapies. Our in vitro studies with panels of TNBC cell line models and stromal isolates failed to detect a direct modulation of chemoresistance. At the same time, consistent with prior studies, we observed treatment-independent enhancement of tumor cell proliferation by fibroblast-produced secreted factors. Using spatial statistics analyses, we found that proximity to stroma is often associated with enhanced tumor cell proliferation in vivo. Based on these observations, we hypothesized an indirect link between stroma and chemoresistance, where stroma-augmented proliferation potentiates the recovery of residual tumors between chemotherapy cycles. To evaluate the feasibility of this hypothesis, we developed a spatial agent-based model of stroma impact on proliferation/death dynamics. The model was quantitatively parameterized using inferences from histological analyses and experimental studies. We found that the observed enhancement of tumor cell proliferation within stroma-proximal niches can enable tumors to avoid elimination over multiple chemotherapy cycles. Therefore, our study supports the existence of a novel, indirect mechanism of environment-mediated chemoresistance that might contribute to the negative correlation between stromal content and poor therapy outcomes.

Citation Format: Daria Miroshnychenko, Tatiana Miti, Pragya Kumar, Anna Miller, Mark Laurie, Nathalia Giraldo, Marilyn M. Bui, Philipp M. Altrock, David Basanta, Anriy Marusyk. Paracrine enhancement of tumor cell proliferation provides indirect stroma-mediated chemoresistance via acceleration of tumor recovery between chemotherapy cycles [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr B023.
Abstract IA004: Insights into lung cancer evolution and metastases in TRACERx and PEACE
Authors: Jamal-Hanjani Mariam
Published: February 2024

TRACERx is a prospective longitudinal cancer evolution programme which investigates the relationship between intratumour heterogeneity and clinical outcomes in non-small cell lung cancer (NSCLC). In an interim cohort of 421 patients with extended follow up, matched primary and metastatic tumour analysis has demonstrated the impact of cancer evolution on patient outcomes. Large dominant subclones in primary tumours were associated with positive subclonal selection, and mutations in specific genes were found to be under significant subclonal, and not clonal, selection. Subclonal genome doubling was identified in 20% of tumours and multiple genome doubling events were identified in 10% of tumours. Patients with tumours containing large recent subclonal expansions had significantly shorter disease-free survival (DFS), and as previously demonstrated, chromosomal instability was associated with poor outcomes, in particular, extrathoracic disease relapse. Metastatic relapse was found to occur late in tumour evolution in 75% of tumours, and early divergence (25% of tumours) was found to occur at predicted tumour volumes below the threshold for further investigation using radiological imaging, suggesting potential implications for clinical intervention. Metastasis-seeding subclones in primary tumours were subject to subclonal expansion, likely reflective of the acquisition of subclonal driver mutations and somatic copy number alterations. ctDNA analyses in this larger cohort demonstrated the value of ctDNA to predict the likelihood of future relapse, but also its use in tracking tumour growth dynamics and emergence of relapse. Patients who develop relapsed disease in TRACERx after surgery are co-recruited into PEACE, a national research autopsy programme. Early findings from PEACE have demonstrated the genomic complexity of cancer relapse and metastatic heterogeneity and the different patterns of cellular migration that aid metastatic dissemination with both primary-to-metastasis and metastasis-to-metastasis seeding.

Citation Format: Mariam Jamal-Hanjani. Insights into lung cancer evolution and metastases in TRACERx and PEACE [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr IA004.
Abstract IA005: Novel insights into pancreatic cancer evolution from carcinogenesis to metastasis
Authors: Iacobuzio-Donahue Christine
Published: February 2024

While the genetic features of pancreatic cancer are well described, the evolutionary features of this tumor type have not been systematically studied to date. We assembled a large cohort of pancreatic cancer research autopies to investigate evolutionary metrics across clinical contexts. The timing of driver mutations, including truncal and subtruncal events, do not differ significantly across stages at diagnosis or types of clinical management. However, high truncal mutation density is significantly associated with worse overall survival after adjusting for stage at diagnosis, age, smoking history and Type II diabetes status, representing a novel prognostic biomarker. Oligometastatic tumors have fewer drivers and allelic losses compared to aggressive metastases, suggesting a more genomically stable subset of tumors. These findings reveal novel insights into pancreatic cancer evolution beyond established paradigms.

Citation Format: Christine Iacobuzio-Donahue. Novel insights into pancreatic cancer evolution from carcinogenesis to metastasis [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr IA005.
Abstract IA007: Improving cancer treatment through data-driven game theory
Authors: Stankova Katerina
Published: February 2024

Standard of care in metastatic cancers typically applies the Maximum Tolerable Dose (MTD) of treatment or treatment combinations, either continuously or in repeated identical cycles, until unacceptable toxicity, cancer progression, or cure. Cure is rare due to fast-evolving therapy resistance. I will explain how game theory can help us not only understand why MTD fails but also design the first evolutionary anti-cancer therapies—therapies that anticipate and forestall the evolution of treatment-induced resistance in cancer cells. Such therapies can be designed through Stackelberg evolutionary games (SEGs), i.e., games between a rational leader (here, a physician) and evolutionary followers (here, evolving cancer cells). I will demonstrate how data science and machine learning can empower game theory to design evolutionary anti-cancer therapies and how evolutionary therapies lead to a better quality and quantity of patients’ lives.

Citation Format: Katerina Stankova. Improving cancer treatment through data-driven game theory [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr IA007.
Abstract IA009: Stem cells, clonal evolution and therapeutic resistance
Authors: Laplane Lucie
Published: February 2024

Cancer stem cells (CSCs) are the units of selection in cancer (Greaves and Maley 2012; Greaves 2013). If they exist. After a first stage of excitement and strong evidence for CSCs in blood cancers, the concept of CSC and their involvement in solid cancers have been subject to much debate. To understand the role of CSC in clonal evolution and treatment resistance, we need a clear understanding of what CSC are. Several attempts have been made by scientists and philosophers, leading to a dichotomous view of normal and cancer stem cells: either they refer to entities or to a plastic cell states. In the first case, CSCs are the units of selection, and they are involved in treatment resistance. The latter case comes instead with a rejection of the CSC model: in case of plasticity, CSCs are neither a privilege unit of selection, nor a target for cancer treatment. In this talk, I will show that this current dichotomous view is misleading and conflates parameters that need to be distinguished if we want to understand what CSCs are and what is their role in clonal evolution and treatment resistance. By deconvoluting these parameters, we can have a much more precise characterization of CSCs. From this characterization, we can make testable predictions about therapeutic resistance and open new avenues on how to think about cancer treatment.

Citation Format: Lucie Laplane. Stem cells, clonal evolution and therapeutic resistance [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr IA009.
Abstract IA011: The epigenetic-based liquid biopsy odyssey of bedside pancreatic cancer diagnostics
Authors: Ahuja Nita
Published: February 2024

Pancreatic cancer (PC), often diagnosed at an advanced stage, urgently requires innovative early detection methods to improve patient outcomes. Presently, there is no approved screening method for pancreas cancer and its high-risk individuals (HRIs), as existing techniques rely on costly and invasive imaging modalities, which face challenges in detecting interval cancers. This study presents an innovative approach that utilizes liquid biopsy technology combined with blood-based DNA methylation biomarkers—ADAMTS1, BNC1, and LRFN5. These biomarkers demonstrate a remarkable 94% diagnostic accuracy for early-stage PC detection, providing a transformative strategy in precision medicine. In line with precision medicine principles, the potential application of this liquid biopsy-based DNA methylation panel for monitoring HRIs offers a promising path toward personalized surveillance. The creation of an affordable bedside test with exceptional diagnostic accuracy has the potential to revolutionize early detection strategies for PCs. Identifying early curable stage PC through this liquid biopsy technique aligns perfectly with precision medicine, promising increased patient survival. If successfully integrated into routine healthcare, early detection could significantly advance the fight against pancreatic cancer, paving the way for more effective and patient-centric diagnostic approaches.

Citation Format: Nita Ahuja. The epigenetic-based liquid biopsy odyssey of bedside pancreatic cancer diagnostics [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr IA011.
Abstract IA012: Leveraging multiomics and machine learning towards a stepwise approach to multi-cancer screening
Authors: Lin Jimmy
Published: February 2024

Early cancer discovery is challenging due to heterogeneity of different cancers and even within cancers from the same organ. In order to tackle this problem, Freenome has built a multiomics discovery platform that looks for signals along the entire central dogma-DNA, methylation, RNA, protein, immunoprofiling, extracellular vesicles, circulating cells, among others. In order to featurize, train, and build the best models that are generalizable and robust, we have created our own machine learning platform incorporating different computational biological signals. All this is aligned with a step-wise investigation of cancers that can most benefit the population and make a difference to patients, starting with colorectal cancer and advanced adenoma. During this talk, we will discuss the clinical, scientific, and computational strategy that we think is important to create the best products to benefit the most patients.

Citation Format: Jimmy Lin. Leveraging multiomics and machine learning towards a stepwise approach to multi-cancer screening [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr IA012.
Abstract IA019: Multiscale systems approach to target tumor ecosystem responses for therapeutic benefit
Authors: Heiser Laura M.
Published: February 2024

Breast tumors arise and progress via processes that involve intrinsic deregulation of epithelial cells and that also alter the composition and function of associated stromal and immune cells. Together, these tumor-intrinsic and microenvironmental changes enable malignant epithelial cells in the tumor to acquire key cancer hallmarks, including proliferation, migration, immune evasion and further evolution. The resulting collection of cancer and stromal cells comprise a complex, adaptive tumor ecosystem. Long-term therapeutic success will require that drugs attack malignant cells, favorably activate the immune system, and create a tumor microenvironment that does not support tumor (re)growth. Creating a process for treatment selection will require an integrated systems biology approach to develop, test and refine a robust computational framework that takes into account the states, signaling relationships, and spatial organization that determine the emergent properties inherent in complex interacting systems. Toward this goal, we have developed a coordinated experimental-computational approach designed to enable identification of effective treatment strategies. To examine therapeutic responses of diverse aspects of the tumor ecosystem, we have deployed a novel drug delivery microdevice that enables rapid, high-throughput assessment of the effects of multiple therapies on tumor cells and the surrounding microenvironment. When coupled with multiplex tissue imaging, this platform provides a comprehensive assessment of the state and spatial organization of the tumor ecosystem as it adapts to therapy. Initial studies demonstrated that many drugs designed to target malignant epithelial cells strongly impact stromal and immune cells, providing new insights into the importance of considering multiple aspects of the tumor ecosystem when designing effective therapeutic strategies. The resultant data are being used to guide development of a multiscale computational model that considers the functional relationships between different tumor components and can be used to predict the effects of therapies on diverse aspects of tumor ecosystems. In total, our approach has the potential to transform cancer treatments through rational identification of effective therapeutic strategies that lead to long-term durable control of tumors.

Citation Format: Laura M. Heiser. Multiscale systems approach to target tumor ecosystem responses for therapeutic benefit [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr IA019.
Abstract PR001: Learning to adapt: Rational personalization of adaptive therapy using deep reinforcement learning
Authors: Gallagher Kit , Strobl Maximilian , Gatenby Robert , Maini Philip , Anderson Alexander
Published: February 2024

Standard-of-care treatment regimens have long been designed for maximal cell kill, yet these strategies often fail when applied to metastatic cancers due to the emergence of drug resistance. Adaptive treatment strategies have been developed as an alternative approach, dynamically adjusting treatment to suppress the growth of treatment-resistant populations, delaying, or even preventing, tumor progression. Promising clinical results in prostate cancer indicate the potential to optimize adaptive treatment protocols. We propose the application of deep reinforcement learning (DRL) to guide adaptive drug scheduling, and demonstrate that these treatment schedules can outperform the current adaptive protocols in a mathematical model calibrated to prostate cancer dynamics, more than doubling the time to progression. We show that the DRL strategies are robust to patient variability, including both tumor dynamics and clinical monitoring schedules. We demonstrate that the DRL framework can produce interpretable, adaptive strategies based on a single tumor burden threshold, replicating and informing optimal treatment strategies. Given the DRL framework has no knowledge of the underlying mathematical tumor model, this demonstrates the capability of DRL to help develop treatment strategies in novel or complex settings. Finally, we propose a five-step pathway combining mechanistic modeling with the DRL framework to translate this approach to the clinic with limited information for a given patient. Integrating conventional tools to ensure the interpretability of traditionally `black-box' DRL models, we generate personalized treatment schedules that consistently outperform clinical standard-of-care protocols.

Citation Format: Kit Gallagher, Maximilian Strobl, Robert Gatenby, Philip Maini, Alexander Anderson. Learning to adapt: Rational personalization of adaptive therapy using deep reinforcement learning [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr PR001.
Abstract PR002: Somatic mutation rates and strength of selection on driver genes change by age in melanoma
Authors: Liu Yihan , Rajaei Moein , Mandell Jeff , Townsend Jeffrey
Published: February 2024

The frequencies of driver mutations in melanoma vary in patients of different ages. However, it is unclear whether these differences in frequency are driven by variation in underlying mutation rates or by a changing selective regime in the aging body. Employing a bulk tumor sequence dataset from 5472 melanomas (459 whole-exome sequences and 5013 cancer gene-panel sequences) analyzed with the cancereffectsizeR package, we quantified somatic mutation rates and the strength of selection on somatic mutations, measuring the survival advantage conferred by a somatic mutation across the tumorigenic trajectory. Likelihood ratio tests were used to compare cancer effect sizes between age groups: <40 y/o, 40-59 y/o and ≥ 60 y/o. The proportion of cancer effect attributable to each mutational source was calculated by averaging over bootstrapped resample of mutational signature weights. Mann-Whitney U statistics were used to test the difference in signature weights and cancer effect sources across the groups.The underlying mutation rate increased with age, with a mean of 4.49e-6, 4.88e-6, 6.45e-6 in patients <40 y/o, 40-59 y/o and ≥ 60 y/o respectively. From the whole-exome and panel data, 23 variants differed significantly across age groups, among which BRAF V600E had the largest effect sizes, followed by NRAS Q61R, NRAS Q61K, NRAS Q61L. BRAF V600E were significantly larger in patients <40 y/o, while NRAS Q61R, NRAS Q61K, NRAS Q61L were significantly larger in patients 40-59 y/o and ≥ 60 y/o. Although underlying mutation rates and strengths of selection varied across age groups, the origin of melanomas from patients in all three age groups was predominantly attributed to UV light. These observations illuminate numerous theoretical questions regarding the origins of cancer at different ages. They are helpful to widespread implementation of prevention strategies. Moreover, understanding the relative strength of selection on driver mutations within patients at distinct ages is crucial for improving precision therapeutic interventions.

Citation Format: Yihan Liu, Moein Rajaei, Jeff Mandell, Jeffrey Townsend. Somatic mutation rates and strength of selection on driver genes change by age in melanoma [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr PR002.