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Background: Understanding to what extent a breast tumor's genetic composition may change over the course of a few months of neoadjuvant therapy has implications for optimal therapeutic approach. However, genomic changes observed across treatment may result from either treatment-induced clonal evolution or geographically disparate sampling of a heterogeneous tumor. We sought to characterize the geographic heterogeneity in primary breast tumors, and to incorporate this information into analysis of clonal evolution with neoadjuvant therapy. Methods: We assembled the largest cohort to date of multi-region (n=2-3) whole-exome sequenced (WES) or whole-genome sequenced untreated primary breast tumors with matched normal and adequate tumor purity for analysis: four tumors with data generated for this study and five tumors compiled from three previous studies. We also generated the first cohort of multi-region (n=2-6) WES breast tumors post-neoadjuvant HER2-targeted therapy and chemotherapy, sequencing one region from a pre-treatment diagnostic specimen, multiple regions from the post-treatment surgical specimen, and matched normal for five HER2+ breast tumors that did not achieve a pathologic complete response. We used an agent-based model of spatial tumor growth to investigate whether the mutational patterns we observed with treatment were consistent with pre-existing heterogeneity or treatment-induced selection. Results: In untreated primary breast tumors, on average 30% (range 1-70%) of apparently clonal mutations from a single region were absent or rare in a second, spatially disparate region (high-frequency regional, or HFR). Intra-tumor heterogeneity was similar post-treatment (HFR 28%, range 10-54%), and was higher in breast tumors than in previously analyzed colon, brain, lung, and esophageal tumors. Simulation studies confirmed that with high heterogeneity as observed in breast tumors, analysis of one pre-treatment and one post-treatment region could not distinguish treatment-induced clonal evolution from pre-existing heterogeneity; however, obtaining at least two post-treatment regions allowed for detection of clonal shifts with treatment. Analysis of multi-region data revealed that clonal replacement occurred with neoadjuvant therapy in two of the five tumors. Candidate causes of therapeutic resistance included amplifications in CCND1, ERBB4, and MYC in one subclone, and functional protein-altering mutations in ERCC2, SMO, and WT1 in another. Mathematical modeling suggested that these putative resistant subclones comprised 0.02-12.5% of the overall pre-treatment cell population, substantially larger than previous estimates of resistant tumor clone size. Conclusions: WES data from multiple regions of untreated and treated primary breast tumors revealed considerable heterogeneity that remained present throughout treatment with chemotherapy and HER2-targeted therapy, even while major clonal sweeps took place in a minority of tumors. Obtaining at least two samples for analysis from breast tumors post-neoadjuvant therapy may reveal the tumor's evolutionary path and, especially as increasing numbers of molecular and immune therapeutic targets are identified, inform new clinical strategies. Citation Format: Caswell-Jin JL, McNamara K, Reiter JG, Sun R, Hu Z, Ma Z, Suarez CJ, Tilk S, Raghavendra A, Forte V, Chin S-F, Bardwell H, Provenzano E, Caldas C, Lang J, West R, Tripathy D, Press MF, Curtis C. Clonal evolution and heterogeneity in breast tumors treated with neoadjuvant HER2-targeted therapy [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P3-06-01.

Cancers often arise from a mutated cell that undergoes premalignant clonal expansion, all the while accruing additional mutations. These somatic mutations accumulate and spread in phenotypically normal tissues prior to apparent morphological changes, with aneuploidy and driver gene mutations often preceding cancer diagnosis by years. Identifying the causes of malignant transformation requires characterization of abnormal molecular phenotypes that precede this event in a tissue-specific manner. However, repeated sampling of healthy tissue or pre-neoplasia is not practical. Critically, neither the order of somatic alterations nor the clonal dynamics that precede malignant transformation can be reliably inferred from genomic sequencing of established tumors. New approaches are therefore needed to characterize pre-neoplastic clonal evolution. Here we model this occult process via CRISPR/dCas9 engineering of human epithelial organoids, followed by multi-year experimental evolution. Through longitudinal genome sequencing, transcriptional profiling and lineage tracing, we define causal relationships between common initiating genetic lesions and resulting phenotypes. The resultant data illuminate evolutionary constraints and barriers to malignant transformation with implications for early detection and risk stratification. Citation Format: Christina Curtis. Charting genotype to phenotype maps of tumorigenesis [abstract]. In: Proceedings of the AACR Special Conference on the Evolutionary Dynamics in Carcinogenesis and Response to Therapy; 2022 Mar 14-17. Philadelphia (PA): AACR; Cancer Res 2022;82(10 Suppl):Abstract nr IA026.

Subclonal architectures are prevalent across cancer types. However, the temporal evolutionary dynamics that produce tumor subclones remain unknown. Here we measure clone dynamics in human cancers by using computational modeling of subclonal selection and theoretical population genetics applied to high-throughput sequencing data. Our method determined the detectable subclonal architecture of tumor samples and simultaneously measured the selective advantage and time of appearance of each subclone. We demonstrate the accuracy of our approach and the extent to which evolutionary dynamics are recorded in the genome. Application of our method to high-depth sequencing data from breast, gastric, blood, colon and lung cancer samples, as well as metastatic deposits, showed that detectable subclones under selection, when present, consistently emerged early during tumor growth and had a large fitness advantage (>20%). Our quantitative framework provides new insight into the evolutionary trajectories of human cancers and facilitates predictive measurements in individual tumors from widely available sequencing data.

The functional impact of most genomic alterations found in cancer, alone or in combination, remains largely unknown. Here we integrate tumor barcoding, CRISPR/Cas9-mediated genome editing and ultra-deep barcode sequencing to interrogate pairwise combinations of tumor suppressor alterations in autochthonous mouse models of human lung adenocarcinoma. We map the tumor suppressive effects of 31 common lung adenocarcinoma genotypes and identify a landscape of context dependence and differential effect strengths.

Models of estrogen receptor–positive breast cancer are used to explore the rationale for androgen receptor agonists as treatments for breast cancer.

Given the implications of tumor dynamics for precision medicine, there is a need to systematically characterize the mode of evolution across diverse solid tumor types. In particular, methods to infer the role of natural selection within established human tumors are lacking. By simulating spatial tumor growth under different evolutionary modes and examining patterns of between-region subclonal genetic divergence from multiregion sequencing (MRS) data, we demonstrate that it is feasible to distinguish tumors driven by strong positive subclonal selection from those evolving neutrally or under weak selection, as the latter fail to dramatically alter subclonal composition. We developed a classifier based on measures of between-region subclonal genetic divergence and projected patient data into model space, finding different modes of evolution both within and between solid tumor types. Our findings have broad implications for how human tumors progress, how they accumulate intratumoral heterogeneity, and ultimately how they may be more effectively treated.

Mutated clones in healthy tissues may hold clues for the earlier detection of malignancy

The initiation of cell division integrates a large number of intra- and extracellular inputs. D-type cyclins (hereafter, cyclin D) couple these inputs to the initiation of DNA replication1. Increased levels of cyclin D promote cell division by activating cyclin-dependent kinases 4 and 6 (hereafter, CDK4/6), which in turn phosphorylate and inactivate the retinoblastoma tumour suppressor. Accordingly, increased levels and activity of cyclin D–CDK4/6 complexes are strongly linked to unchecked cell proliferation and cancer2,3. However, the mechanisms that regulate levels of cyclin D are incompletely understood4,5. Here we show that autophagy and beclin 1 regulator 1 (AMBRA1) is the main regulator of the degradation of cyclin D. We identified AMBRA1 in a genome-wide screen to investigate the genetic basis of the response to CDK4/6 inhibition. Loss of AMBRA1 results in high levels of cyclin D in cells and in mice, which promotes proliferation and decreases sensitivity to CDK4/6 inhibition. Mechanistically, AMBRA1 mediates ubiquitylation and proteasomal degradation of cyclin D as a substrate receptor for the cullin 4 E3 ligase complex. Loss of AMBRA1 enhances the growth of lung adenocarcinoma in a mouse model, and low levels of AMBRA1 correlate with worse survival in patients with lung adenocarcinoma. Thus, AMBRA1 regulates cellular levels of cyclin D, and contributes to cancer development and the response of cancer cells to CDK4/6 inhibitors. AMBRA1 is the main regulator of the degradation of D-type cyclins, and loss of AMBRA1 promotes cell proliferation and tumour growth, and reduces the sensitivity of cancer cells to inhibition of CDK4 and CDK6.

Metastasis is the primary cause of cancer-related deaths, but the natural history, clonal evolution and impact of treatment are poorly understood. We analyzed whole-exome sequencing (WES) data from 457 paired primary tumor and metastatic samples from 136 patients with breast, colorectal and lung cancer, including untreated (n = 99) and treated (n = 100) metastases. Treated metastases often harbored private ‘driver’ mutations, whereas untreated metastases did not, suggesting that treatment promotes clonal evolution. Polyclonal seeding was common in untreated lymph node metastases (n = 17 out of 29, 59%) and distant metastases (n = 20 out of 70, 29%), but less frequent in treated distant metastases (n = 9 out of 94, 10%). The low number of metastasis-private clonal mutations is consistent with early metastatic seeding, which we estimated occurred 2–4 years before diagnosis across these cancers. Furthermore, these data suggest that the natural course of metastasis is selectively relaxed relative to early tumorigenesis and that metastasis-private mutations are not drivers of cancer spread but instead associated with drug resistance. Analysis of whole-exome sequencing data from paired primary tumors and metastases from patients with breast, colorectal and lung cancer identifies clonal remodeling associated with therapy and few metastasis-private clonal mutations, consistent with early metastatic seeding.

Introduction Cancer genomes exhibit surprisingly weak signatures of negative selection 1,2 . This may be because tumors evolve either under very weak selective pressures (‘weak selection’) or under conditions that prevent the elimination of many deleterious passenger mutations (‘poor efficacy of selection’)xs. Rationale The weak selection model argues that the majority of genes are only important for multicellular function. The poor efficacy of selection model argues, in contrast, that genome-wide linkage in cancer prevents many deleterious mutations from being removed via Hill-Robertson interference 3 . Since these linkage effects weaken as mutation rates decrease, we predict that cancers with lower mutational burdens should exhibit stronger signals of negative selection. Furthermore, because linkage affects driver mutations as well, low mutational burden cancers should also show stronger evidence of positive selection in driver genes. Neither pattern — in drivers or passengers — is expected under the weak selection model. We leverage the 10,000-fold variation in mutational burden across cancer subtypes to stratify tumors by their genome-wide mutational burden and used a normalized ratio of nonsynonymous to synonymous substitutions (dN/dS) to quantify the extent that selection varies with mutation rate. Results We find that appreciable negative selection (dN/dS ~ 0.4) is present in tumors with a low mutational burden, while the remaining cancers (96%) exhibit dN/dS ratios approaching 1, suggesting that the majority of tumors do not remove deleterious passengers. A parallel pattern is seen in drivers, where positive selection attenuates as the mutational burden of cancers increases. Both trends persist across tumor-types, are not exclusive to essential or housekeeping genes, and are present in clonal and subclonal mutations. Two additional orthogonal lines of evidence support the weak efficacy model: passengers are less damaging in low mutational burden cancers, and patterns of attenuated selection also emerge in Copy Number Alterations. Finally, we find that an evolutionary model incorporating Hill-Robertson interference can reproduce both patterns of attenuated selection in drivers and passengers if the average fitness cost of passengers is 1.0% and the average fitness benefit of drivers is 19%. Conclusion Collectively, our findings suggest that the lack of signals of negative selection in most tumors is not due to relaxed selective pressures, but rather the inability of selection to remove individual deleterious mutations in the presence of genome-wide linkage. As a result, despite the weak individual fitness effects of passengers, most cancers harbor a large mutational load (median ~40% total fitness cost) and succeed due to acquisition of additional strong drivers (~5 with an overall benefit of ~130%). Understanding how this deleterious load is overcome may help identify cancer vulnerabilities that may be targeted by new and existing therapies.

Breast cancer is the most common cancer among American women and a major cause of mortality. To identify metabolic pathways as potential targets to treat metastatic breast cancer, we performed metabolomics profiling on the breast cancer cell line MDA-MB-231 and its tissue-tropic metastatic subclones. Here, we report that these subclones with increased metastatic potential display an altered metabolic profile compared with the parental population. In particular, the mitochondrial serine and one-carbon (1C) unit pathway is upregulated in metastatic subclones. Mechanistically, the mitochondrial serine and 1C unit pathway drives the faster proliferation of subclones through enhanced de novo purine biosynthesis. Inhibition of the first rate-limiting enzyme of the mitochondrial serine and 1C unit pathway, serine hydroxymethyltransferase (SHMT2), potently suppresses proliferation of metastatic subclones in culture and impairs growth of lung metastatic subclones at both primary and metastatic sites in mice. Some human breast cancers exhibit a significant association between the expression of genes in the mitochondrial serine and 1C unit pathway with disease outcome and higher expression of SHMT2 in metastatic tumor tissue compared with primary tumors. In addition to breast cancer, a few other cancer types, such as adrenocortical carcinoma and kidney chromophobe cell carcinoma, also display increased SHMT2 expression during disease progression. Together, these results suggest that mitochondrial serine and 1C unit metabolism plays an important role in promoting cancer progression, particularly in late-stage cancer. Implications: This study identifies mitochondrial serine and 1C unit metabolism as an important pathway during the progression of a subset of human breast cancers. See interview with Jiangbin Ye, PhD, co-recipient of the 2022 MCR Michael B. Kastan Award for Research Excellence: https://vimeo.com/720728048

Immunotherapies that block inhibitory checkpoint receptors on T cells have transformed the clinical care of cancer patients. However, which tumor-specific T cells are mobilized following checkpoint blockade remains unclear. Here, we performed paired single-cell RNA- and T cell receptor (TCR)-sequencing on 79,046 cells from site-matched tumors from patients with basal cell carcinoma (BCC) or squamous cell carcinoma (SCC) pre- and post-anti-PD-1 therapy. Tracking TCR clones and transcriptional phenotypes revealed a coupling of tumor-recognition, clonal expansion, and T cell dysfunction: the T cell response to treatment was accompanied by clonal expansions of CD8+CD39+T cells, which co-expressed markers of chronic T cell activation and exhaustion. However, this expansion did not derive from pre-existing tumor infiltrating T cell clones; rather, it comprised novel clonotypes, which were not previously observed in the same tumor. Clonal replacement of T cells was preferentially observed in exhausted CD8+T cells, compared to other distinct T cell phenotypes, and was evident in BCC and SCC patients. These results, enabled by single-cell multi-omic profiling of clinical samples, demonstrate that pre-existing tumor-specific T cells may be limited in their capacity for re-invigoration, and that the T cell response to checkpoint blockade relies on the expansion of a distinct repertoire of T cell clones that may have just recently entered the tumor.

Immunotherapies that block inhibitory checkpoint receptors on T cells have transformed the clinical care of patients with cancer

Mutations in ARID1A, encoding a subunit of the BAF chromatin remodeling complex, rank amongst the most common molecular aberrations in human cancer. However, oncogenic consequences of ARID1A mutation in human cells remain poorly defined due to lack of forward human genetic model systems. Here, CRISPR/Cas9 knockout of ARID1A in primary TP53-/- human gastric organoids induced morphologic dysplasia, tumorigenicity and mucinous differentiation but impaired Wnt/β-catenin signaling. Genetic Wnt pathway activation rescued mucinous differentiation, but not hyperproliferation, suggesting alternative essential pathways of ARID1A-mediated transformation. ARID1A loss induced transcriptional regulatory modules characteristic of MSI and EBV subtype human gastric cancer, including FOXM1 regulation of multiple mitotic regulatory genes and BIRC5/survivin. Convergently, high-throughput compound screening indicated selective vulnerability of ARID1A-deficient organoids to BIRC5/survivin inhibition, functionally implicating BIRC5/survivin as an essential mediator of proliferation following initial ARID1A loss. However, CRISPR inactivation of ARID1A in established gastric cancer cell lines did not elicit sensitivity to BIRC5/survivin inhibitors, suggesting that this pathway may be selectively required during the early establishment of tumorigenesis. Overall, we define distinct pathways downstream of oncogenic ARID1A mutation, with non-essential Wnt-inhibited mucinous differentiation in parallel with essential transcriptional FOXM1/BIRC5-stimulated proliferation, indicating the general utility of organoid-based forward genetic cancer analysis in human cells. Citation Format: Yuan-Hung Lo, Kevin S. Kolahi, Yuhong Du, Chiung-Ying Chang, Andrey Krokhotin, Ajay Nair, Walter D. Sobba, Kasper Karlsson, Sunny J. Jones, Teri A. Longacre, Amanda T. Mah, Alexandra Sockell, Jose A. Seoane, Jin Chen, Jonathan S. Weissman, Christina Curtis, Andrea Califano, Haian Fu, Gerald R. Crabtree, Calvin J. Kuo. A CRISPR/Cas9-engineered ARID1A-deficient human gastric cancer organoid model reveals essential and non-essential modes of oncogenic transformation [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 123.

Introduction: Chromatin accessibility and cell-free DNA fragmentation patterns can be used to identify epigenomic mechanisms (Sharma et al. 2010) and infer cell-types contributing to cfDNA in pathological states such as cancer (Snyder et al. 2016; Ulz et al. 2017). We describe results from a novel blood-based cell-free DNA (cfDNA) assay using epigenomic signatures that have high sensitivity for detecting early stages of breast cancer, a cancer type that is characterized by low tumor burden (Phallen et al. 2017). We present the results from a prospective, case-control study demonstrating improved sensitivity to the screening mammogram and other published blood-based assays. Methods: Assay performance was evaluated using a case-control study design enrolling 123 total subjects (58% Healthy, 18% Stage I, 13% Stage II, 11% Stage III). Cases were defined as subjects with a confirmatory diagnosis of invasive breast cancer, at any stage, by tissue biopsy. Controls were composed of subjects with either a negative finding by mammography (BI-RADS 1 or 2) or self-declared cancer-free. Whole blood samples were collected in Streck BCT tubes and shipped to a central laboratory for processing. Total cell-free DNA was extracted from plasma and prepped for next-generation sequencing. Sequencing libraries were enriched using a custom panel targeting genomic regions with distinct epigenomic activity in breast cancer. We trained a neural net to predict regulatory events in each of these regions, and then identified those events that were predictive of the presence of breast cancer. Final classification was performed by logistic regression over the predicted regulatory events. Results: Performance was tested using a held-out test set and achieved an overall sensitivity of 92.5% (95% CI: 88.1%, 97%) at specificity of 88.9% with an overall AUC of 95.8%. Performance of screening mammography is reported to be 86.9% (95% CI: 86.3%, 87.6%) sensitive at 88.9% specificity on data obtained from six Breast Cancer Surveillance Consortium (BCSC) registries on 792808 women (Lehman et al. 2017). Conclusion: These results support the utility for detecting epigenomic signals from cell-free DNA to enhance early detection of breast cancer. A prospective breast cancer screening study in a larger cohort is needed to further validate performance. Citation Format: Erik Gafni, Adam Harvey, Artur Jaroszewicz, Omid Shams Solari, Jane Landolin, Mouadh Barbirou, Amanda Miller, Peter J. Tonellato, Anshul Kundaje, Stefanie S. Jeffrey, Christina Curtis, George W. Sledge, Paul Giresi, Nathan Boley. Cell-free DNA fragments inform epigenomic mechanisms for early detection of breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2105.

Although TP53 is the most commonly mutated gene in human cancers, the p53-dependent transcriptional programs mediating tumor suppression remain incompletely understood. Here, to uncover critical components downstream of p53 in tumor suppression, we perform unbiased RNAi and CRISPR-Cas9-based genetic screens invivo. These screens converge upon the p53-inducible gene Zmat3, encoding an RNA-binding protein, and we demonstrate that ZMAT3 is an important tumor suppressor downstream of p53 in mouse KrasG12D-driven lung and liver cancers and human carcinomas. Integrative analysis of the ZMAT3 RNA-binding landscape and transcriptomic profiling reveals that ZMAT3 directly modulates exon inclusion in transcripts encoding proteins of diverse functions, including the p53 inhibitors MDM4 and MDM2, splicing regulators, and components of varied cellular processes. Interestingly, these exons are enriched in NMD signals, and, accordingly, ZMAT3 broadly affects target transcript stability. Collectively, these studies reveal ZMAT3 as a novel RNA-splicing and homeostasis regulator and a key component of p53-mediated tumor suppression.

181 Background: In “window of opportunity” (WOO) clinical trials, people with newly diagnosed early-stage cancer are exposed to an experimental drug during the period of time between diagnosis and definitive anti-cancer treatment. These trials allow investigators to study drug efficacy in untreated disease, which can expedite drug development. However, for trial participants, the WOO approach requires them to decide about an altruistic clinical trial during an intense time immediately after cancer diagnosis. This qualitative study aimed to understand patient perspectives on WOO clinical trials. Methods: We recruited adults newly diagnosed with early-stage breast cancer who were awaiting definitive therapy at a single academic medical center. We developed an interview guide grounded in the theoretical framework, the Theory of Planned Behavior (TPB). TBP is a well-validated decision-making model with three domains that guide behavior: (1) attitudes (2) normative factors and (3) perceived difficulty of a behavior. We conducted one-on-one semi-structured interviews that were audio-recorded and transcribed. Transcripts were analyzed to ensure interrater reliability and content analysis was performed to assess themes that emerged. Results: We interviewed 15 women (age 32-72) with early-stage breast cancer, and the majority were White (n = 12, 80%) and at least college educated (n = 12, 80%). Key themes that emerged included favorable attitudes towards participating in a WOO trial that were altruistic, including the desire to contribute to science (n = 10, 67%) and to help future breast cancer patients (n = 5, 33%). Several individuals also identified a potential benefit to themselves (n = 10, 67%), including access to a targeted drug (n = 4, 27%) and adding meaning to their diagnosis (n = 3, 20%). However, most interviewees reported concerns about drug side effects (n = 12, 80%) and whether side effects would impact other planned treatments (n = 10, 67%). Interviewees also expressed family would be an important normative factor in decision-making (n = 8, 53%). A key theme that emerged as a difficulty was the potential delay in standard treatment (n = 14, 93%). Despite this concern, at the end of the interviews, most interviewees stated they would participate in a WOO trial if offered (n = 10, 67%). Conclusions: WOO trials are becoming increasingly common in oncology research. In this qualitative study, interviewees weighed altruism against the possibility delaying or impacting other treatments. Our results may inform trial design and communication approaches in future WOO efforts.

Metastasis is the primary cause of cancer-related deaths, but the natural history, clonal evolution and patterns of systemic spread are poorly understood. We analyzed exome sequencing data from 458 paired primary tumors (P) or metastasis (M) samples from 136 breast, colorectal and lung cancer patients, including both untreated (n=98) and treated (n=101) metastases. We find that treated metastases often harbored private driver gene mutations whereas untreated metastases did not, suggesting the acquisition and selection of additional mutations is not required for untreated metastases and treatment promotes clonal evolution. Additionally, the ratio of nonsynonymous versus synonymous mutations (dN/dS) showed decreased selection pressures in the metastasis relative to primary tumors. Polyclonal seeding was common in lymph node metastases (n=19/35, 54%; mostly untreated) and untreated distant metastases (n=20/70, 29%), but less frequent in treated metastases (n=9/90, 10%). Mathematical modeling shows that the low number of metastasis-private clonal mutations is consistent with early metastatic seeding, which commonly occurred several years prior to diagnosis in breast (2.4 years, range 0-3.3), lung (3.6 years, range 2.8-3.7) and colorectal (4.1 years, range 3.1-4.6) cancers. Thus, this pan-cancer analysis reveals early systemic spread in three common cancer types. Further, these data suggest that the natural course of metastasis is selectively relaxed relative to early tumor development and that metastasis-private mutations are not drivers of cancer spread but are instead associated with drug resistance. Citation Format: Zheng Hu, Zan Li, Zhicheng Ma, Christina Curtis. Pan-cancer analysis of clonality and the timing of systemic spread in paired primary tumors and metastases [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2688.

The causes and consequences of metabolic reprogramming during human breast cancer metastasis remain largely unknown. We performed metabolomics in the human triple-negative breast cancer cell line MDA-MB-231 (231-Parental) and its metastatic subclones that display tissue-tropism towards the brain (831-BrM), the bone (1833-BoM), and the lung (4175-LM). Using molecular and metabolic flux analysis, we uncovered that the mitochondrial serine and one-carbon (1C) unit pathway is upregulated in the metastatic subclones. Inhibition of the first rate-limiting enzyme of the pathway, serine hydroxymethyltransferase (SHMT2), potently suppresses proliferation of metastatic subclones in culture and impairs growth of lung metastatic subclones at both primary and metastatic sites in mice. In addition to breast cancer, a few other cancer types, such as adrenocortical carcinoma (ACC) and kidney chromophobe cell carcinoma (KICH), also display increased SHMT2 expression during disease progression. Moreover, we found that metastatic cells are exquisitely adapted to low serine conditions by synthesizing serine de novo from glucose to generate 1C units, and blocking serine catabolism abrogates metastatic growth under serine deprivation. How do metastatic breast cancer cells acquire new metabolic properties such as de novo serine synthesis? We observed that 231-Parental cells grown in media lacking serine for up to ten passages exhibited metastatic cell-like metabolic properties. Subsequent RNA-sequencing revealed dramatic global gene expression changes during serine starvation in more primary tumor-like cells. Several pathways involved in metastasis such as TNFα signaling, mTOR1 signaling, and Ras signaling were modulated upon serine starvation. These data suggest that the availability of the nonessential amino acid serine may play a key regulatory role in breast cancer progression and metastasis, and highlight the potential for metabolite supplementation to block or halt these transformations. Citation Format: Albert Mao Li, Gregory S. Ducker, Yang Li, Jose A. Seoane, Yiren Xiao, Stavros Melemenidis, Yiren Zhou, Ling Liu, Sakari Vanharanta, Edward E. Graves, Erinn B. Rankin, Christina Curtis, Joan Massague, Joshua D. Rabinowitz, Craig B. Thompson, Jiangbin Ye. Reprogramming of serine metabolism during breast cancer progression [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 5713.

The TP53 gene, which encodes the p53 transcription factor, is mutated in ~75% of human pancreatic ductal adenocarcinomas (PDACs), underscoring the fundamental role of p53 as a barrier to PDAC development. Despite this critical function, however, the cellular and molecular programs through which p53 acts in pancreatic cancer suppression remain poorly understood. To gain a better understanding of the pathways through which p53 acts to suppress PDAC development, which will provide key insight into how the disease develops, we have taken combined mouse genetic and genomic approaches. First, we have sought to determine whether p53 acts in acinar and/or ductal cells to restrain PDAC development. Importantly, for these experiments we have used adult mice to more accurately mimic the development of PDAC in humans. Second, we have sought to systematically deconstruct the role of p53 deletion and p53 missense mutations in driving cancer from these different cells of origin. This comprehensive analysis of large adult mouse cohorts has helped to define the cell of origin for PDAC and the effects of different p53 mutations on spontaneous PDAC development. To gain additional insight into the programs that become dysregulated during pancreatic cancer development, we have performed RNA-sequencing analysis on tumors arising from different compartments and driven by different genetic lesions. These studies have revealed the molecular profiles of tumors arising from acinar versus ductal cells as well those driven by different types of p53 mutations. Through comparison to human pancreatic cancer data, our studies are helping us to better understand the paths to PDAC development in humans and the underlying origins of different subtypes of this disease. Citation Format: Brittany Flowers, Hang Xu, Kathryn Hanson, Christina Curtis, Hannes Vogel, Laura Wood, Laura D. Attardi. Deconstructing the origins of PDAC development [abstract]. In: Proceedings of the AACR Special Conference on the Evolving Landscape of Cancer Modeling; 2020 Mar 2-5; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2020;80(11 Suppl):Abstract nr IA14.

Both the timing and molecular determinants of metastasis are unknown, hindering treatment and prevention efforts. Here we characterize the evolutionary dynamics of this lethal process by analyzing exome sequencing data from 118 biopsies from 23 colorectal cancer (CRC) patients with metastases to the liver or brain. The data show low primary tumor-metastasis genomic divergence, where canonical driver genes were acquired early. Analysis within a spatial tumor growth model and statistical inference framework indicates that early disseminated cells commonly (81%, 17/21 evaluable patients) seed metastases while the carcinoma is clinically undetectable (typically, Editorial summary: Analysis of evolutionary dynamics of colorectal cancers and paired distant brain or liver metastases provides evidence that early disseminated cancer cells seed metastases before the carcinoma is clinically undetectable.

INTRODUCTION Cancer is one of the leading causes of death worldwide. Although the 2% of the human genome that encodes proteins has been extensively studied, much remains to be learned about the noncoding genome and gene regulation in cancer. Genes are turned on and off in the proper cell types and cell states by transcription factor (TF) proteins acting on DNA regulatory elements that are scattered over the vast noncoding genome and exert long-range influences. The Cancer Genome Atlas (TCGA) is a global consortium that aims to accelerate the understanding of the molecular basis of cancer. TCGA has systematically collected DNA mutation, methylation, RNA expression, and other comprehensive datasets from primary human cancer tissue. TCGA has served as an invaluable resource for the identification of genomic aberrations, altered transcriptional networks, and cancer subtypes. Nonetheless, the gene regulatory landscapes of these tumors have largely been inferred through indirect means. RATIONALE A hallmark of active DNA regulatory elements is chromatin accessibility. Eukaryotic genomes are compacted in chromatin, a complex of DNA and proteins, and only the active regulatory elements are accessible by the cell’s machinery such as TFs. The assay for transposase-accessible chromatin using sequencing (ATAC-seq) quantifies DNA accessibility through the use of transposase enzymes that insert sequencing adapters at these accessible chromatin sites. ATAC-seq enables the genome-wide profiling of TF binding events that orchestrate gene expression programs and give a cell its identity. RESULTS We generated high-quality ATAC-seq data in 410 tumor samples from TCGA, identifying diverse regulatory landscapes across 23 cancer types. These chromatin accessibility profiles identify cancer- and tissue-specific DNA regulatory elements that enable classification of tumor subtypes with newly recognized prognostic importance. We identify distinct TF activities in cancer based on differences in the inferred patterns of TF-DNA interaction and gene expression. Genome-wide correlation of gene expression and chromatin accessibility predicts tens of thousands of putative interactions between distal regulatory elements and gene promoters, including key oncogenes and targets in cancer immunotherapy, such as MYC , SRC , BCL2 , and PDL1 . Moreover, these regulatory interactions inform known genetic risk loci linked to cancer predisposition, nominating biochemical mechanisms and target genes for many cancer-linked genetic variants. Lastly, integration with mutation profiling by whole-genome sequencing identifies cancer-relevant noncoding mutations that are associated with altered gene expression. A single-base mutation located 12 kilobases upstream of the FGD4 gene, a regulator of the actin cytoskeleton, generates a putative de novo binding site for an NKX TF and is associated with an increase in chromatin accessibility and a concomitant increase in FGD4 gene expression. CONCLUSION The accessible genome of primary human cancers provides a wealth of information on the susceptibility, mechanisms, prognosis, and potential therapeutic strategies of diverse cancer types. Prediction of interactions between DNA regulatory elements and gene promoters sets the stage for future integrative gene regulatory network analyses. The discovery of hundreds of noncoding somatic mutations that exhibit allele-specific regulatory effects suggests a pervasive mechanism for cancer cells to manipulate gene expression and increase cellular fitness. These data may serve as a foundational resource for the cancer research community.

Anthracyclines are a highly effective component of curative breast cancer chemotherapy but are associated with substantial morbidity1,2. Because anthracyclines work in part by inhibiting topoisomerase-II (TOP2) on accessible DNA3,4, we hypothesized that chromatin regulatory genes (CRGs) that mediate DNA accessibility might predict anthracycline response. We studied the role of CRGs in anthracycline sensitivity in breast cancer through integrative analysis of patient and cell line data. We identified a consensus set of 38 CRGs associated with anthracycline response across ten cell line datasets. By evaluating the interaction between expression and treatment in predicting survival in a metacohort of 1006 patients with early-stage breast cancer, we identified 54 CRGs whose expression levels dictate anthracycline benefit across the clinical subgroups; of these CRGs, 12 overlapped with those identified in vitro. CRGs that promote DNA accessibility, including Trithorax complex members, were associated with anthracycline sensitivity when highly expressed, whereas CRGs that reduce accessibility, such as Polycomb complex proteins, were associated with decreased anthracycline sensitivity. We show that KDM4B modulates TOP2 accessibility to chromatin, elucidating a mechanism of TOP2 inhibitor sensitivity. These findings indicate that CRGs mediate anthracycline benefit by altering DNA accessibility, with implications for the stratification of patients with breast cancer and treatment decision making.

The degree of intrinsic and interpatient phenotypic heterogeneity and its role in tumour evolution is poorly understood. Phenotypic drifts can be transmitted via inheritable transcriptional programs. Cell-type specific transcription is maintained through the activation of epigenetically-defined regulatory regions including promoters and enhancers. Here we annotated the epigenome of 47 primary and metastatic oestrogen-receptor (ERα)-positive breast cancer clinical specimens and inferred phenotypic heterogeneity from the regulatory landscape, identifying key regulatory elements commonly shared across patients. Shared regions contain a unique set of regulatory information including the motif for the transcription factor YY1. We identify YY1 as a critical determinant of ERα transcriptional activity promoting tumour growth in most luminal patients. YY1 also contributes to the expression of genes mediating resistance to endocrine treatment. Finally, we used H3K27ac levels at active enhancer elements as a surrogate of intra-tumour phenotypic heterogeneity to track the expansion and contraction of phenotypic subpopulations throughout breast cancer progression. By tracking the clonality of SLC9A3R1-positive cells, a bona fide YY1-ERα-regulated gene, we show that endocrine therapies select for phenotypic clones underrepresented at diagnosis. Collectively, our data show that epigenetic mechanisms significantly contribute to phenotypic heterogeneity and evolution in systemically treated breast cancer patients.

Subclonal architectures are prevalent across cancer types. However, the temporal evolutionary dynamics that produce tumour subclones remain unknown. Here we measure clone dynamics in human cancers using computational modelling of subclonal selection and theoretical population genetics applied to high throughput sequencing data. Our method determines the detectable subclonal architecture of tumour samples, and simultaneously measures the selective advantage and time of appearance of each subclone. We demonstrate the accuracy of our approach and the extent to which evolutionary dynamics are recorded in the genome. Application of our method to high-depth sequencing data from breast, gastric, blood, colon and lung cancers, as well as metastatic deposits, showed that detectable subclones under selection, when present, consistently emerged early during tumour growth and had a large fitness advantage (>20%). Our quantitative framework provides new insight into the evolutionary trajectories of human cancers, facilitating predictive measurements in individual tumours from widely available sequencing data.

The Annual Advances in Genome Biology and Technology (AGBT) General Meeting was held in Orlando, Florida, USA, on the 12–15 February 2018. Professors Ami S. Bhatt and Christina Curtis from Stanford University, USA, report advances and applications in the field that were discussed at the meeting.

Single-cell analyses in cancer are limited by the small biomass of individual cells. In vitro production of 3D organoid structures from single tumour-derived cells generates sufficient biomass for in-depth analyses. Single-cell analyses in cancer are limited by the small biomass of individual cells. In vitro production of 3D organoid structures from single tumour-derived cells generates sufficient biomass for in-depth analyses.

The recent integration of both genomic and transcriptomic datasets have added a further dimension to the landscape of breast cancer (BrCa) subtyping, defining novel functional subgroups with distinctive oncogenic drivers that carry important implications for therapy. This integrative clustering has unveiled a novel subtype of hormone receptor positive (HR+) BrCa associated with high proliferation and very poor survival characterised by copy number amplification and overexpression of a cluster of candidate oncogenic drivers at the 11q13.5-14 locus (1). At the heart of this amplicon we have demonstrated the selective overexpression of C11orf67/AAMDC (Adipogenesis associated Mth938 domain containing) which encodes a hypothetical protein of 122 aa with unknown function. In a pilot tissue microarray of 75 BrCa cases C11orf67 amplification and expression were significantly correlated with hormone receptor positivity. These positive cases also demonstrated high risk features with 75% demonstrating lymph node involvement. In functional elucidation studies knockdown of C11orf67 in the highly expressing T47D cell line lead to decreased cell proliferation, cell migration, anchorage independent cell growth and induction of senescence. T47D xenografts with stable shRNA-induced C11orf67 knockdowns introduced into BALB/c mice showed significantly lower tumour volumes relative to T47D with empty vector. A genome wide analysis of these T47D-C11orf67 shRNA cells compared to T47D-empty vector cells using the Illumina HumanHT-12 platform demonstrated 40 differentially expressed genes. Network analysis revealed a proliferation node, enriched in cell cycle proteins, and a metabolic node comprising several biosynthetic enzymes such as MTHFD1L involved in one-carbon folate metabolism. Supporting this link and pointing to potential utility in chemotherapy selection, induction of ectopic C11orf67 expression in MCF7 cells increased sensitivity to fluorouracil and methotrexate but not to paclitaxel. Investigating potential novel binding partners and effectors, in yeast two hybrid screening C11orf67 was a found to associate strongly with RABGAP1L, a protein involved in controlling GTPase signalling, protein trafficking, and autophagy. Exploring the molecular cues that control C11orf67 expression, our data suggest the locus is regulated by transcription factors associated with high proliferation and metabolic control, notably Myc and NFkB, as well as HRs. E2 lead to a significant down-regulation of C11orf67 in T47D cells, which was reversed by the antiestrogen drug tamoxifen, whereas PG significantly increased C11orf67 levels. In keeping with this MCF7 cells ectopically expressing C11orf67 were resistant to the anti-proliferative effects of tamoxifen compared to the parent cell line. These observations endorse C11orf67 as a novel oncogenic driver with exciting therapeutic potential, which could serve to distinguish the HR+ tumours at high risk of relapse and guide both the selection of current chemotherapeutical and endocrine treatments as well as the design of future precision therapeutics, notably anti-folate/one carbon drugs and novel endocrine agents. References 1. Curtis et al. Nature. 2012 Jun 21;486 (7403):346-52. Citation Format: Redfern A, Rashwan R, Sorolla A, Ratajska M, Kardas I, Kuzniacka A, Parry J, Curtis C, Woo A, Sgro A, Biernat W. Characterisation of C11orf67, an oncogenic driver in a new subtype of aggressive endocrine receptor positive breast cancer. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P2-06-01.

What happens in the early and still undetectable human malignancy is unknown because direct observations are impractical. Here we present a “Big Bang” model, whereby a tumor grows predominantly as a single expansion producing numerous intermixed sub-clones, which are not subject to stringent clonal selection. In this model, both public and most detectable private mutations arise during the earliest phase of tumor growth. Multi-scale genomic profiling of 349 individual glands sampled from 15 colorectal tumors revealed the absence of selective sweeps, uniformly high intra-tumor heterogeneity, and sub-clone mixing in distant tumor regions, as postulated by the Big Bang. By integrating the data in a spatial model of tumor growth and statistical inference framework we also verified the most striking prediction of our model, namely that most detectable intra-tumor heterogeneity originates from private alterations acquired early during growth, and not from the later expansion of selected sub-clones. Hence, early sub-clones define the genomic profile of colorectal carcinomas and advanced adenomas, whereas potentially dangerous late-arising sub-clones will go undetected. Moreover, our results suggest that sub-clone mixing may be a biomarker of malignant potential. This new model provides a quantitative framework that explains the origins of intra-tumor heterogeneity and tumor growth dynamics with significant clinical implications. Citation Format: Andrea Sottoriva, Haeyoun Kang, Zhicheng Ma, Trevor A. Graham, Matthew Salomon, Junsong Zhao, Paul Marjoram, Kim Siegmund, Michael F. Press, Darryl Shibata, Christina Curtis. A Big Bang model of human colorectal tumor growth. [abstract]. In: Proceedings of the AACR Special Conference on Computational and Systems Biology of Cancer; Feb 8-11 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 2):Abstract nr B2-23.

Intratumoural mutational heterogeneity (ITH) or the presence of different private mutations in different parts of the same tumour is commonly observed in human tumours. The mechanisms generating such ITH are uncertain. Here we find that ITH can be remarkably well structured by measuring point mutations, chromosome copy numbers, and DNA passenger methylation from opposite sides and individual glands of a 6cm human colorectal adenoma. ITH was present between tumour sides and individual glands, but the private mutations were side-specific and subdivided the adenoma into two major subclones. Furthermore, ITH disappeared within individual glands because the glands were clonal populations composed of cells with identical mutant genotypes. Despite mutation clonality, the glands were relatively old, diverse populations when their individual cells were compared for passenger methylation and by FISH. These observations can be organized into an expanding star-like ancestral tree with co-clonal expansion, where many private mutations and multiple related clones arise during the first few divisions. As a consequence, most detectable mutational ITH in the final tumour originates from the first few divisions. Much of the early history of a tumour, especially the first few divisions, may be embedded within the detectable ITH of tumour genomes. Copyright (c) 2015 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

A new computational method illuminates the heterogeneity and evolutionary histories of cells within a tumor.

Purpose: Tumor-infiltrating lymphocytes (TIL) in pretreatment biopsies are associated with improved survival in triple-negative breast cancer (TNBC). We investigated whether higher peripheral lymphocyte counts are associated with lower breast cancer–specific mortality (BCM) and overall mortality (OM) in TNBC. Experimental Design: Data on treatments and diagnostic tests from electronic medical records of two health care systems were linked with demographic, clinical, pathologic, and mortality data from the California Cancer Registry. Multivariable regression models adjusted for age, race/ethnicity, socioeconomic status, cancer stage, grade, neoadjuvant/adjuvant chemotherapy use, radiotherapy use, and germline BRCA1/2 mutations were used to evaluate associations between absolute lymphocyte count (ALC), BCM, and OM. For a subgroup with TIL data available, we explored the relationship between TILs and peripheral lymphocyte counts. Results: A total of 1,463 stage I–III TNBC patients were diagnosed from 2000 to 2014; 1,113 (76%) received neoadjuvant/adjuvant chemotherapy within 1 year of diagnosis. Of 759 patients with available ALC data, 481 (63.4%) were ever lymphopenic (minimum ALC Conclusions: Higher peripheral lymphocyte counts predicted lower mortality from early-stage, potentially curable TNBC, suggesting that immune function may enhance the effectiveness of early TNBC treatment. Clin Cancer Res; 24(12); 2851–8. ©2018 AACR.

High-throughput sequencing can be used to measure changes in tumor composition across space and time. Specifically, comparisons of pre- and post-treatment samples can reveal the underlying clonal dynamics and resistance mechanisms. Here, we discuss evidence for distinct modes of tumor evolution and their implications for therapeutic strategies. Additionally, we consider the utility of spatial tissue sampling schemes, single cell analysis, and circulating tumor DNA to track tumor evolution and the emergence of resistance, as well as approaches that seek to forestall resistance by targeting tumor evolution. Ultimately, characterization of the (epi)genomic, transcriptomic, and phenotypic changes that occur during tumor progression, coupled with computational and mathematical modeling of tumor evolutionary dynamics may inform personalized treatment strategies.

To describe recent advances in the application of advanced genomic technologies towards the identification of biomarkers of prognosis and treatment response in breast cancer.Advances in high-throughput genomic profiling such as massively parallel sequencing have enabled researchers to catalogue the spectrum of somatic alterations in breast cancers. These tools also hold promise for precision medicine through accurate patient prognostication, stratification, and the dynamic monitoring of treatment response. For example, recent efforts have defined robust molecular subgroups of breast cancer and novel subtype-specific oncogenes. In addition, previously unappreciated activating mutations in human epidermal growth factor receptor 2 have been reported, suggesting new therapeutic opportunities. Genomic profiling of cell-free tumor DNA and circulating tumor cells has been used to monitor disease burden and the emergence of resistance, and such 'liquid biopsy' approaches may facilitate the early, noninvasive detection of aggressive disease. Finally, single-cell genomics is coming of age and will contribute to an understanding of breast cancer evolutionary dynamics.Here, we highlight recent studies that employ high-throughput genomic technologies in an effort to elucidate breast cancer biology, discover new therapeutic targets, improve prognostication and stratification, and discuss the implications for precision cancer medicine.

Glioblastoma, the most common and aggressive adult brain tumor, is characterized by extreme phenotypic diversity and treatment failure. Through fluorescence-guided resection, we identified fluorescent tissue in the sub-ependymal zone (SEZ) of patients with glioblastoma. Histologic analysis and genomic characterization revealed that the SEZ harbors malignant cells with tumor-initiating capacity, analogous to cells isolated from the fluorescent tumor mass (T). We observed resistance to supramaximal chemotherapy doses along with differential patterns of drug response between T and SEZ in the same tumor. Our results reveal novel insights into glioblastoma growth dynamics, with implications for understanding and limiting treatment resistance. Cancer Res; 75(1); 194–202. ©2014 AACR.

The p53 transcription factor is a critical barrier to pancreatic cancer progression. To unravel mechanisms of p53-mediated tumor suppression, which have remained elusive, we analyzed pancreatic cancer development in mice expressing p53 transcriptional activation domain (TAD) mutants. Surprisingly, the p5353,54 TAD2 mutant behaves as a "super-tumor suppressor," with an enhanced capacity to both suppress pancreatic cancer and transactivate select p53 target genes, including Ptpn14. Ptpn14 encodes a negative regulator of the Yap oncoprotein and is necessary and sufficient for pancreatic cancer suppression, like p53. We show that p53 deficiency promotes Yap signaling and that PTPN14 and TP53 mutations are mutually exclusive in human cancers. These studies uncover a p53-Ptpn14-Yap pathway that is integral to p53-mediated tumor suppression.

Molecular networks governing responses to targeted therapies in cancer cells are complex dynamic systems that demonstrate nonintuitive behaviors. We applied a novel computational strategy to infer probabilistic causal relationships between network components based on gene expression. We constructed a model comprised of an ensemble of networks using multidimensional data from cell line models of cell-cycle arrest caused by inhibition of MEK1/2. Through simulation of a reverse-engineered Bayesian network model, we generated predictions of G1–S transition. The model identified known components of the cell-cycle machinery, such as CCND1, CCNE2, and CDC25A, as well as revealed novel regulators of G1–S transition, IER2, TRIB1, TRIM27. Experimental validation of model predictions confirmed 10 of 12 predicted genes to have a role in G1–S progression. Further analysis showed that TRIB1 regulated the cyclin D1 promoter via NFκB and AP-1 sites and sensitized cells to TRAIL-induced apoptosis. In clinical specimens of breast cancer, TRIB1 levels correlated with expression of NFκB and its target genes (IL8, CSF2), and TRIB1 copy number and expression were predictive of clinical outcome. Together, our results establish a critical role of TRIB1 in cell cycle and survival that is mediated via the modulation of NFκB signaling. Cancer Res; 77(7); 1575–85. ©2017 AACR.

The TP53 gene, encoding the p53 transcription factor, is mutated in the majority of human pancreatic cancers, underscoring its critical role as a barrier to PDAC development. Despite this essential function, however, the cellular and molecular pathways through which p53 acts in pancreatic cancer suppression have remained elusive. To gain a better understanding of the programs through which p53 suppresses PDAC development, which will provide key insight into how the disease develops, we have taken combined mouse genetic and genomic approaches. First, we have sought to understand whether p53 acts in acinar and/or ductal cells to restrain PDAC development. For these studies we have used adult mice to more accurately mimic the development of PDAC in humans. Second, we have sought to systematically deconstruct the role of p53 loss-of-function and gain-of-function mutations in driving cancer from these different cells of origin. In addition, we have characterized the trajectory of cancer development in these models through histologic analysis of lesions at different time points and through lineage tracing. This comprehensive analysis of large adult mouse cohorts has helped to define the role for p53 in restraining spontaneous PDAC development, an essential first step for understanding p53 programs involved in tumor suppression. To gain insight into the programs that become dysregulated during pancreatic cancer development, we have performed transcriptomic analysis on tumors arising from different compartments and driven by different genetic lesions. These studies have revealed the molecular profiles of tumors arising from acinar versus ductal cells as well those driven by different types of p53 mutations. Through comparison to human pancreatic cancer data, our studies will reveal the paths to PDAC development in humans and the underlying origins of different subtypes of this disease. Citation Format: Brittany Flowers, Hang Xu, Kathryn Hanson, Christina Curtis, Hannes Vogel, Laura D. Wood, Laura D. Attardi. Deciphering the origins of PDAC development [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer: Advances in Science and Clinical Care; 2019 Sept 6-9; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2019;79(24 Suppl):Abstract nr I15.

The tumor suppressor gene TP53 encodes a transcriptional activator critical for suppressing pancreatic ductal adenocarcinoma (PDAC). TP53 mutations, which are most frequently missense mutations in the DNA binding domain, result in both loss of wild-type p53 function and gain of novel, oncogenic functions. Mouse models of PDAC relying on oncogenic Kras and p53 mutation have suggested that either pancreatic acinar or ductal cells, the two major epithelial cell types in the pancreas, may be the cell of origin for PDAC, although there is very limited understanding of the molecular pathways through which p53 mutations contribute to PDAC driven by oncogenic Kras. Moreover, the cellular functions of p53 involved in tumor suppression remain enigmatic. To set up a platform for deconstructing p53 loss-of-function (LOF) and gain-of-function (GOF) pathways, we have generated mouse models to study p53 function in adult mice, mimicking the context of human cancer, using tamoxifen-inducible Cre recombinases to activate Kras (KrasLSL-G12D) in adult mouse pancreatic acinar (Ptf1aCreER) and ductal (Sox9CreER) compartments, in the backdrop of different p53 alleles. To investigate p53 LOF, we generated mouse cohorts with wild-type p53 expression or conditional p53 knockout (p53fl/fl). To examine p53 GOF, we generated mouse cohorts with conditional expression of structural mutant p53R172H (p53LSL-R172H/fl), contact mutant p53R270H (p53LSL-R270H/fl) and conditional p53 knockout (p53null/fl) for comparison in a uniform p53 heterozygous genetic background of stromal tissues. Our tumor studies have demonstrated that oncogenic Kras expression and p53 knockout or mutation in acinar cells of adult mice leads to metastatic PDAC development with complete penetrance. This suggests a novel role for p53 in tumor suppression by blocking cellular reprogramming of acinar cells to ductal-like cells. In contrast, these mutations drive PDAC from ductal cells less efficiently. To understand the origins of human PDAC, we are investigating the molecular pathways altered in mouse acinar and ductal cell-derived tumors. Through comparison with human pancreatic cancer data, our studies will elucidate the cellular origins of different molecular subtypes of human PDAC. Elucidating the mechanisms of PDAC development is critical to improving detection and therapy in PDAC patients. Citation Format: Brittany M. Flowers, Hang Xu, Kathryn Hanson, Christina Curtis, Hannes Vogel, Laura D. Wood, Laura D. Attardi. Elucidating the role of p53 in the cellular origins of pancreatic cancer development [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer: Advances in Science and Clinical Care; 2019 Sept 6-9; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2019;79(24 Suppl):Abstract nr A15.

The aim of this study is to determine the effect of chromatin regulators on anthracycline response in breast cancer. Anthracyclines are a highly effective component of curative breast cancer chemotherapy, but can be associated with substantial side effects. Because anthracyclines work in part via inhibition of topoisomerase II (TOP2) on accessible DNA, we hypothesized that expression levels of chromatin regulatory proteins that mediate DNA accessibility might predict anthracycline response. We used RNA-sequencing data from the TCGA breast cancer cohort to infer a breast cancer chromatin regulatory network using the ARACNE algorithm. A panel of 45 breast cancer cell lines with accompanying gene expression and growth inhibitory (GI50) data was used to build a genome-wide signature of anthracycline response. Based on the GI50, cell lines were classified as sensitive or resistant. The VIPER algorithm was then used to identify chromatin regulatory genes (CRGs) from the ARACNE network whose targets were significantly enriched in the anthracycline resistance signature. We further compiled a metacohort of 1006 clinically annotated early-stage breast cancer patients with gene expression data, allowing us to identify CRGs whose expression levels were associated with outcome after adjuvant treatment with anthracyclines. 24 CRGs associated (P Citation Format: Jose A. Seoane, Jacob G. Kirkland, Jennifer L. Caswell-Jin, Gerald R. Crabtree, Christina Curtis. Chromatin state as a mechanism of anthracycline response in breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 2108.

MicroRNAs (miRNAs) show differential expression across breast cancer subtypes, and have both oncogenic and tumour-suppressive roles. Here we report the miRNA expression profiles of 1,302 breast tumours with matching detailed clinical annotation, long-term follow-up and genomic and messenger RNA expression data. This provides a comprehensive overview of the quantity, distribution and variation of the miRNA population and provides information on the extent to which genomic, transcriptional and post-transcriptional events contribute to miRNA expression architecture, suggesting an important role for post-transcriptional regulation. The key clinical parameters and cellular pathways related to the miRNA landscape are characterized, revealing context-dependent interactions, for example with regards to cell adhesion and Wnt signalling. Notably, only prognostic miRNA signatures derived from breast tumours devoid of somatic copy-number aberrations (CNA-devoid) are consistently prognostic across several other subtypes and can be validated in external cohorts. We then use a data-driven approach to seek the effects of miRNAs associated with differential co-expression of mRNAs, and find that miRNAs act as modulators of mRNA-mRNA interactions rather than as on-off molecular switches. We demonstrate such an important modulatory role for miRNAs in the biology of CNA-devoid breast cancers, a common subtype in which the immune response is prominent. These findings represent a new framework for studying the biology of miRNAs in human breast cancer.

Cancer results from the acquisition of somatic alterations in a microevolutionary process that typically occurs over many years, much of which is occult. Understanding the evolutionary dynamics that are operative at different stages of progression in individual tumors might inform the earlier detection, diagnosis, and treatment of cancer. Although these processes cannot be directly observed, the resultant spatiotemporal patterns of genetic variation amongst tumor cells encode their evolutionary histories. Such intra-tumor heterogeneity is pervasive not only at the genomic level, but also at the transcriptomic, phenotypic, and cellular levels. Given the implications for precision medicine, the accurate quantification of heterogeneity within and between tumors has become a major focus of current research. In this review, we provide a population genetics perspective on the determinants of intra-tumor heterogeneity and approaches to quantify genetic diversity. We summarize evidence for different modes of evolution based on recent cancer genome sequencing studies and discuss emerging evolutionary strategies to therapeutically exploit tumor heterogeneity. This article is part of a Special Issue entitled: Evolutionary principles - heterogeneity in cancer?, edited by Dr. Robert A. Gatenby.

Background High mitotic activity is associated with the genesis and progression of many cancers. Small molecule inhibitors of mitotic apparatus proteins are now being developed and evaluated clinically as anticancer agents. With clinical trials of several of these experimental compounds underway, it is important to understand the molecular mechanisms that determine high mitotic activity, identify tumor subtypes that carry molecular aberrations that confer high mitotic activity, and to develop molecular markers that distinguish which tumors will be most responsive to mitotic apparatus inhibitors. Methods We identified a coordinately regulated mitotic apparatus network by analyzing gene expression profiles for 53 malignant and non-malignant human breast cancer cell lines and two separate primary breast tumor datasets. We defined the mitotic network activity index (MNAI) as the sum of the transcriptional levels of the 54 coordinately regulated mitotic apparatus genes. The effect of those genes on cell growth was evaluated by small interfering RNA (siRNA). Results High MNAI was enriched in basal-like breast tumors and was associated with reduced survival duration and preferential sensitivity to inhibitors of the mitotic apparatus proteins, polo-like kinase, centromere associated protein E and aurora kinase designated GSK462364, GSK923295 and GSK1070916, respectively. Co-amplification of regions of chromosomes 8q24, 10p15-p12, 12p13, and 17q24-q25 was associated with the transcriptional upregulation of this network of 54 mitotic apparatus genes, and we identify transcription factors that localize to these regions and putatively regulate mitotic activity. Knockdown of the mitotic network by siRNA identified 22 genes that might be considered as additional therapeutic targets for this clinically relevant patient subgroup. Conclusions We define a molecular signature which may guide therapeutic approaches for tumors with high mitotic network activity. Electronic supplementary material The online version of this article (doi:10.1186/s13058-016-0728-y) contains supplementary material, which is available to authorized users.

Substantial evidence supports the concept that cancers are organized in a cellular hierarchy with cancer stem cells (CSC) at the apex. To date, the primary evidence for CSCs derives from transplantation assays, which have known limitations. In particular, they are unable to report on the fate of cells within the original human tumor. Because of the difficulty in measuring tumor characteristics in patients, cellular organization and other aspects of cancer dynamics have not been quantified directly, although they likely play a fundamental role in tumor progression and therapy response. As such, new approaches to study CSCs in patient-derived tumor specimens are needed. In this study, we exploited ultradeep single-molecule genomic data derived from multiple microdissected colorectal cancer glands per tumor, along with a novel quantitative approach to measure tumor characteristics, define patient-specific tumor profiles, and infer tumor ancestral trees. We show that each cancer is unique in terms of its cellular organization, molecular heterogeneity, time from malignant transformation, and rate of mutation and apoptosis. Importantly, we estimate CSC fractions between 0.5% and 4%, indicative of a hierarchical organization responsible for long-lived CSC lineages, with variable rates of symmetric cell division. We also observed extensive molecular heterogeneity, both between and within individual cancer glands, suggesting a complex hierarchy of mitotic clones. Our framework enables the measurement of clinically relevant patient-specific characteristics in vivo, providing insight into the cellular organization and dynamics of tumor growth, with implications for personalized patient care. Cancer Res; 73(1); 41–49. ©2012 AACR.

Recent studies have identified prevalent subclonal architectures within many cancer types. However, the temporal evolutionary dynamics that produce these subclonal architectures remain unknown. Here we measure evolutionary dynamics in primary human cancers using computational modelling of clonal selection applied to high throughput sequencing data. Our approach simultaneously determines the subclonal architecture of a tumour sample, and measures the mutation rate, the selective advantage, and the time of appearance of subclones. Simulations demonstrate the accuracy of the method, and revealed the degree to which evolutionary dynamics are recorded in the genome. Application of our method to high-depth sequencing data from gastric and lung cancers revealed that detectable subclones consistently emerged early during tumour growth and had considerably large fitness advantages (>20% growth advantage). Our quantitative platform provides new insight into the evolutionary history of cancers by facilitating the measurement of fundamental evolutionary parameters in individual patients.