Multi-omics Analysis Reveals Immune Features Associated with Immunotherapy Benefit in Patients with Squamous Cell Lung Cancer from Phase III Lung-MAP S1400I Trial

PURPOSE

Identifying molecular and immune features to guide immune checkpoint inhibitor (ICI)-based regimens remains an unmet clinical need.

EXPERIMENTAL DESIGN

Tissue and longitudinal blood specimens from phase III trial S1400I in patients with metastatic squamous non-small cell carcinoma (SqNSCLC) treated with nivolumab monotherapy (nivo) or nivolumab plus ipilimumab (nivo+ipi) were subjected to multi-omics analyses including multiplex immunofluorescence (mIF), nCounter PanCancer Immune Profiling Panel, whole-exome sequencing, and Olink.

RESULTS

Higher immune scores from immune gene expression profiling or immune cell infiltration by mIF were associated with response to ICIs and improved survival, except regulatory T cells, which were associated with worse overall survival (OS) for patients receiving nivo+ipi. Immune cell density and closer proximity of CD8+GZB+ T cells to malignant cells were associated with superior progression-free survival and OS. The cold immune landscape of NSCLC was associated with a higher level of chromosomal copy-number variation (CNV) burden. Patients with LRP1B-mutant tumors had a shorter survival than patients with LRP1B-wild-type tumors. Olink assays revealed soluble proteins such as LAMP3 increased in responders while IL6 and CXCL13 increased in nonresponders. Upregulation of serum CXCL13, MMP12, CSF-1, and IL8 were associated with worse survival before radiologic progression.

CONCLUSIONS

The frequency, distribution, and clustering of immune cells relative to malignant ones can impact ICI efficacy in patients with SqNSCLC. High CNV burden may contribute to the cold immune microenvironment. Soluble inflammation/immune-related proteins in the blood have the potential to monitor therapeutic benefit from ICI treatment in patients with SqNSCLC.

Predicting patient outcomes after treatment with immune checkpoint blockade: A review of biomarkers derived from diverse data modalities

Immune checkpoint blockade (ICB) therapy targeting cytotoxic T-lymphocyte-associated protein 4, programmed death 1, and programmed death ligand 1 has shown durable remission and clinical success across different cancer types. However, patient outcomes vary among disease indications. Studies have identified prognostic biomarkers associated with immunotherapy response and patient outcomes derived from diverse data types, including next-generation bulk and single-cell DNA, RNA, T cell and B cell receptor sequencing data, liquid biopsies, and clinical imaging. Owing to inter- and intra-tumor heterogeneity and the immune system's complexity, these biomarkers have diverse efficacy in clinical trials of ICB. Here, we review the genetic and genomic signatures and image features of ICB studies for pan-cancer applications and specific indications. We discuss the advantages and disadvantages of computational approaches for predicting immunotherapy effectiveness and patient outcomes. We also elucidate the challenges of immunotherapy prognostication and the discovery of novel immunotherapy targets.

Immune determinants of CAR-T cell expansion in solid tumor patients receiving GD2 CAR-T cell therapy

Chimeric antigen receptor T cells (CAR-Ts) have remarkable efficacy in liquid tumors, but limited responses in solid tumors. We conducted a Phase I trial (NCT02107963) of GD2 CAR-Ts (GD2-CAR.OX40.28.z.iC9), demonstrating feasibility and safety of administration in children and young adults with osteosarcoma and neuroblastoma. Since CAR-T efficacy requires adequate CAR-T expansion, patients were grouped into good or poor expanders across dose levels. Patient samples were evaluated by multi-dimensional proteomic, transcriptomic, and epigenetic analyses. T cell assessments identified naive T cells in pre-treatment apheresis associated with good expansion, and exhausted T cells in CAR-T products with poor expansion. Myeloid cell assessment identified CXCR3+ monocytes in pre-treatment apheresis associated with good expansion. Longitudinal analysis of post-treatment samples identified increased CXCR3- classical monocytes in all groups as CAR-T numbers waned. Together, our data uncover mediators of CAR-T biology and correlates of expansion that could be utilized to advance immunotherapies for solid tumor patients.

Heterogeneity and transcriptional drivers of triple-negative breast cancer

Triple-negative breast cancer (TNBC) is a heterogeneous disease with limited treatment options. To characterize TNBC heterogeneity, we defined transcriptional, epigenetic, and metabolic subtypes and subtype-driving super-enhancers and transcription factors by combining functional and molecular profiling with computational analyses. Single-cell RNA sequencing revealed relative homogeneity of the major transcriptional subtypes (luminal, basal, and mesenchymal) within samples. We found that mesenchymal TNBCs share features with mesenchymal neuroblastoma and rhabdoid tumors and that the PRRX1 transcription factor is a key driver of these tumors. PRRX1 is sufficient for inducing mesenchymal features in basal but not in luminal TNBC cells via reprogramming super-enhancer landscapes, but it is not required for mesenchymal state maintenance or for cellular viability. Our comprehensive, large-scale, multiplatform, multiomics study of both experimental and clinical TNBC is an important resource for the scientific and clinical research communities and opens venues for future investigation.

What approaches are needed to understand human development and disease?

Researchers are leveraging what we have learned from model organisms to understand if the same principles arise in human physiology, development, and disease. In this collection of Voices, we asked researchers from different fields to discuss what tools and insights they are using to answer fundamental questions in human biology.

Peripheral blood TCR clonotype diversity as an age-associated marker of breast cancer progression

Immune escape is a prerequisite for tumor growth. We previously described a decline in intratumor activated cytotoxic T cells and T cell receptor (TCR) clonotype diversity in invasive breast carcinomas compared to ductal carcinoma in situ (DCIS), implying a central role of decreasing T cell responses in tumor progression. To determine potential associations between peripheral immunity and breast tumor progression, here, we assessed the peripheral blood TCR clonotype of 485 breast cancer patients diagnosed with either DCIS or de novo stage IV disease at younger (<45) or older (≥45) age. TCR clonotype diversity was significantly lower in older compared to younger breast cancer patients regardless of tumor stage at diagnosis. In the younger age group, TCR-α clonotype diversity was lower in patients diagnosed with de novo stage IV breast cancer compared to those diagnosed with DCIS. In the older age group, DCIS patients with higher TCR-α clonotype diversity were more likely to have a recurrence compared to those with lower diversity. Whole blood transcriptome profiles were distinct depending on the TCR-α Chao1 diversity score. There were more CD8+ T cells and a more active immune environment in DCIS tumors of young patients with higher peripheral blood TCR-α Chao1 diversity than in those with lower diversity. These results provide insights into the role that host immunity plays in breast cancer development across different age groups.

Mathematical Modeling Identifies Optimum Palbociclib-fulvestrant Dose Administration Schedules for the Treatment of Patients with Estrogen Receptor-positive Breast Cancer

Cyclin-dependent kinases 4/6 (CDK4/6) inhibitors such as palbociclib are approved for the treatment of metastatic estrogen receptor-positive (ER+) breast cancer in combination with endocrine therapies and significantly improve outcomes in patients with this disease. However, given the large number of possible pairwise drug combinations and administration schedules, it remains unclear which clinical strategy would lead to best survival. Here, we developed a computational, cell cycle-explicit model to characterize the pharmacodynamic response to palbociclib-fulvestrant combination therapy. This pharmacodynamic model was parameterized, in a Bayesian statistical inference approach, using in vitro data from cells with wild-type estrogen receptor (WT-ER) and cells expressing the activating missense ER mutation, Y537S, which confers resistance to fulvestrant. We then incorporated pharmacokinetic models derived from clinical data into our computational modeling platform. To systematically compare dose administration schedules, we performed in silico clinical trials based on integrating our pharmacodynamic and pharmacokinetic models as well as considering clinical toxicity constraints. We found that continuous dosing of palbociclib is more effective for lowering overall tumor burden than the standard, pulsed-dose palbociclib treatment. Importantly, our mathematical modeling and statistical analysis platform provides a rational method for comparing treatment strategies in search of optimal combination dosing strategies of other cell-cycle inhibitors in ER+ breast cancer.

SIGNIFICANCE

We created a computational modeling platform to predict the effects of fulvestrant/palbocilib treatment on WT-ER and Y537S-mutant breast cancer cells, and found that continuous treatment schedules are more effective than the standard, pulsed-dose palbociclib treatment schedule.

A paracrine circuit of IL-1β/IL-1R1 between myeloid and tumor cells drives genotype-dependent glioblastoma progression

Monocytes and monocyte-derived macrophages (MDMs) from blood circulation infiltrate glioblastoma (GBM) and promote growth. Here, we show that PDGFB-driven GBM cells induce the expression of the potent proinflammatory cytokine IL-1β in MDM, which engages IL-1R1 in tumor cells, activates the NF-κB pathway, and subsequently leads to induction of monocyte chemoattractant proteins (MCPs). Thus, a feedforward paracrine circuit of IL-1β/IL-1R1 between tumors and MDM creates an interdependence driving PDGFB-driven GBM progression. Genetic loss or locally antagonizing IL-1β/IL-1R1 leads to reduced MDM infiltration, diminished tumor growth, and reduced exhausted CD8+ T cells and thereby extends the survival of tumor-bearing mice. In contrast to IL-1β, IL-1α exhibits antitumor effects. Genetic deletion of Il1a/b is associated with decreased recruitment of lymphoid cells and loss-of-interferon signaling in various immune populations and subsets of malignant cells and is associated with decreased survival time of PDGFB-driven tumor-bearing mice. In contrast to PDGFB-driven GBM, Nf1-silenced tumors have a constitutively active NF-κB pathway, which drives the expression of MCPs to recruit monocytes into tumors. These results indicate local antagonism of IL-1β could be considered as an effective therapy specifically for proneural GBM.

H3K36 methylation maintains cell identity by regulating opposing lineage programmes

The epigenetic mechanisms that maintain differentiated cell states remain incompletely understood. Here we employed histone mutants to uncover a crucial role for H3K36 methylation in the maintenance of cell identities across diverse developmental contexts. Focusing on the experimental induction of pluripotency, we show that H3K36M-mediated depletion of H3K36 methylation endows fibroblasts with a plastic state poised to acquire pluripotency in nearly all cells. At a cellular level, H3K36M facilitates epithelial plasticity by rendering fibroblasts insensitive to TGFβ signals. At a molecular level, H3K36M enables the decommissioning of mesenchymal enhancers and the parallel activation of epithelial/stem cell enhancers. This enhancer rewiring is Tet dependent and redirects Sox2 from promiscuous somatic to pluripotency targets. Our findings reveal a previously unappreciated dual role for H3K36 methylation in the maintenance of cell identity by integrating a crucial developmental pathway into sustained expression of cell-type-specific programmes, and by opposing the expression of alternative lineage programmes through enhancer methylation.

Tutorial: integrative computational analysis of bulk RNA-sequencing data to characterize tumor immunity using RIMA

RNA-sequencing (RNA-seq) has become an increasingly cost-effective technique for molecular profiling and immune characterization of tumors. In the past decade, many computational tools have been developed to characterize tumor immunity from gene expression data. However, the analysis of large-scale RNA-seq data requires bioinformatics proficiency, large computational resources and cancer genomics and immunology knowledge. In this tutorial, we provide an overview of computational analysis of bulk RNA-seq data for immune characterization of tumors and introduce commonly used computational tools with relevance to cancer immunology and immunotherapy. These tools have diverse functions such as evaluation of expression signatures, estimation of immune infiltration, inference of the immune repertoire, prediction of immunotherapy response, neoantigen detection and microbiome quantification. We describe the RNA-seq IMmune Analysis (RIMA) pipeline integrating many of these tools to streamline RNA-seq analysis. We also developed a comprehensive and user-friendly guide in the form of a GitBook with text and video demos to assist users in analyzing bulk RNA-seq data for immune characterization at both individual sample and cohort levels by using RIMA.

Phase I study of a novel glioblastoma radiation therapy schedule exploiting cell-state plasticity

BACKGROUND

Glioblastomas comprise heterogeneous cell populations with dynamic, bidirectional plasticity between treatment-resistant stem-like and treatment-sensitive differentiated states, with treatment influencing this process. However, current treatment protocols do not account for this plasticity. Previously, we generated a mathematical model based on preclinical experiments to describe this process and optimize a radiation therapy fractionation schedule that substantially increased survival relative to standard fractionation in a murine glioblastoma model.

METHODS

We developed statistical models to predict the survival benefit of interventions to glioblastoma patients based on the corresponding survival benefit in the mouse model used in our preclinical study. We applied our mathematical model of glioblastoma radiation response to optimize a radiation therapy fractionation schedule for patients undergoing re-irradiation for glioblastoma and developed a first-in-human trial (NCT03557372) to assess the feasibility and safety of administering our schedule.

RESULTS

Our statistical modeling predicted that the hazard ratio when comparing our novel radiation schedule with a standard schedule would be 0.74. Our mathematical modeling suggested that a practical, near-optimal schedule for re-irradiation of recurrent glioblastoma patients was 3.96 Gy × 7 (1 fraction/day) followed by 1.0 Gy × 9 (3 fractions/day). Our optimized schedule was successfully administered to 14/14 (100%) patients.

CONCLUSIONS

A novel radiation therapy schedule based on mathematical modeling of cell-state plasticity is feasible and safe to administer to glioblastoma patients.

Brief Report: Combination of Osimertinib and Dacomitinib to Mitigate Primary and Acquired Resistance in EGFR-Mutant Lung Adenocarcinomas

PURPOSE

Primary and acquired resistance to osimertinib remain significant challenges for patients with EGFR-mutant lung cancers. Acquired EGFR alterations such as EGFR T790M or C797S mediate resistance to EGFR tyrosine kinase inhibitors (TKI) and combination therapy with dual EGFR TKIs may prevent or reverse on-target resistance.

PATIENTS AND METHODS

We conducted two prospective, phase I/II trials assessing combination osimertinib and dacomitinib to address on-target resistance in the primary and acquired resistance settings. In the initial therapy study, patients received dacomitinib and osimertinib in combination as initial therapy. In the acquired resistance trial, dacomitinib with or without osimertinib was administered to patients with EGFR-mutant lung cancers with disease progression on osimertinib alone and evidence of an acquired EGFR second-site mutation.

RESULTS

Cutaneous toxicities occurred in 93% (any grade) of patients and diarrhea in 72% (any grade) with the combination. As initial therapy, the overall response to the combination was 73% [95% confidence interval (CI), 50%-88%]. No acquired secondary alterations in EGFR were observed in any patients at progression. In the acquired resistance setting, the overall response was 14% (95% CI, 1%-58%).

CONCLUSIONS

We observed no acquired secondary EGFR alterations with dual inhibition of EGFR as up-front treatment, but this regimen was associated with greater toxicity. The combination was not effective in reversing acquired resistance after development of a second-site acquired EGFR alteration. Our study highlights the need to develop better strategies to address on-target resistance in patients with EGFR-mutant lung cancers.

Mechanisms of response and resistance to combined decitabine and ipilimumab for advanced myeloid disease

The challenge of eradicating leukemia in patients with acute myelogenous leukemia (AML) after initial cytoreduction has motivated modern efforts to combine synergistic active modalities including immunotherapy. Recently, the ETCTN/CTEP 10026 study tested the combination of the DNA methyltransferase inhibitor decitabine together with the immune checkpoint inhibitor ipilimumab for AML/myelodysplastic syndrome (MDS) either after allogeneic hematopoietic stem cell transplantation (HSCT) or in the HSCT-naïve setting. Integrative transcriptome-based analysis of 304 961 individual marrow-infiltrating cells for 18 of 48 subjects treated on study revealed the strong association of response with a high baseline ratio of T to AML cells. Clinical responses were predominantly driven by decitabine-induced cytoreduction. Evidence of immune activation was only apparent after ipilimumab exposure, which altered CD4+ T-cell gene expression, in line with ongoing T-cell differentiation and increased frequency of marrow-infiltrating regulatory T cells. For post-HSCT samples, relapse could be attributed to insufficient clearing of malignant clones in progenitor cell populations. In contrast to AML/MDS bone marrow, the transcriptomes of leukemia cutis samples from patients with durable remission after ipilimumab monotherapy showed evidence of increased infiltration with antigen-experienced resident memory T cells and higher expression of CTLA-4 and FOXP3. Altogether, activity of combined decitabine and ipilimumab is impacted by cellular expression states within the microenvironmental niche of leukemic cells. The inadequate elimination of leukemic progenitors mandates urgent development of novel approaches for targeting these cell populations to generate long-lasting responses. This trial was registered at www.clinicaltrials.gov as #NCT02890329.

Abstract 2142: Immune determinants of CAR-T expansion in solid tumor patients receiving GD2 CAR-T cell therapy

Chimeric antigen receptor T cells (CAR-Ts) have demonstrated remarkable efficacy in leukemia and lymphomas but limited responses in solid tumors. We conducted a phase I trial (NCT02107963) of GD2 CAR-Ts (GD2-CAR.OX40.28.z.ICD9), demonstrating feasibility and safety of administering GD2 CAR-Ts in children and young adults with neuroblastoma and, for the first time, osteosarcoma. 15 patients aged 8-28 years were enrolled on four dose levels, of which 13 patients were infused. No dose-limiting toxicities were observed, and administration of up to 1x107 GD2-CAR-T/kg was feasible and safe for children and young adults with neuroblastoma and osteosarcoma. At Day 28 following GD2 CAR-T infusion, 23.1% (3/13) of evaluable patients had progressive disease and 76.9% (10/13) had stable disease (SD). 3/10 SD patients remained stable at 60 days post-infusion of GD2 CAR-T, but all patients eventually progressed. Since a major barrier to CAR-T efficacy is inadequate CAR-T expansion, we evaluated CAR-T levels and found that patients stratified into good and poor expander groups, observed across dose levels and associated with pro-inflammatory cytokine signatures in patients. To understand the immune cell contributors to CAR-T expansion, patient pre-treatment apheresis, CAR-T product, and post-infusion samples were evaluated by high-dimensional proteomic (CyTOF), transcriptomic (RNAseq), and epigenetic (ATACseq) analyses. In patient apheresis, good CAR-T expansion associated with more open chromatin and with both proteomic and transcriptomic enrichment of naïve T cells, while poor CAR-T expansion associated with increased levels of T effector memory (TEMRA) cells and enrichment of myeloid derived suppressor cell (MDSC) transcriptomic signatures. CAR-T products across patients, regardless of CAR-T expansion, demonstrated increased T cell activation proteomic signatures, with enhanced exhaustion transcriptomic signatures in poor expanders compared to good. The most robust cellular correlate to good CAR-T expansion was a population of CXCR3-expressing monocytes in pre-treatment apheresis. Interestingly, this CXCR3+ monocyte population reduced in post-infusion timepoints of good expanders, resembling levels found in poor expanders. Our findings were validated in TARGET-OS patient data in The Cancer Genome Atlas, where high CXCR3 expression was found to be associated with survival benefit in osteosarcoma patients. CXCR3 has been extensively studied on T cells, but its function on myeloid populations is yet to be fully explored. These results are the first to demonstrate that the peripheral immune environment prior to CAR-T administration may effectively predict and modulate CAR-T expansion in patients.

Citation Format: Tara Murty, Sabina Kaczanowska, Ahmad Alimadadi, Cristina Contreras, Caroline Duault, Priyanka Balasubrahmanyan, Warren Reynolds, Norma Gutierrez, Reema Baskar, Catherine Wu, Franziska Michor, Jennifer Altreuter, Yang Liu, Aashna Jhaveri, Vandon Duong, Hima Anbunathan, Radim Moravec, Joyce Hong, Roshni Biswas, Stephen Van Nostrand, James Lindsay, Mina Pichavant, Elena Sotillo, Bita Sahaf, Sean Bendall, Holden Maecker, Steven Highfill, David Stroncek, Melinda Merchant, John Glod, Catherine Hedrick, Crystal Mackall, Sneha Ramakrishna, Rosandra Kaplan. Immune determinants of CAR-T expansion in solid tumor patients receiving GD2 CAR-T cell therapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2142.

Single-cell heterogeneity of EGFR and CDK4 co-amplification is linked to immune infiltration in glioblastoma

Glioblastoma (GBM) is the most aggressive brain tumor, with a median survival of ∼15 months. Targeted approaches have not been successful in this tumor type due to the large extent of intratumor heterogeneity. Mosaic amplification of oncogenes suggests that multiple genetically distinct clones are present in each tumor. To uncover the relationships between genetically diverse subpopulations of GBM cells and their native tumor microenvironment, we employ highly multiplexed spatial protein profiling coupled with single-cell spatial mapping of fluorescence in situ hybridization (FISH) for EGFR, CDK4, and PDGFRA. Single-cell FISH analysis of a total of 35,843 single nuclei reveals that tumors in which amplifications of EGFR and CDK4 more frequently co-occur in the same cell exhibit higher infiltration of CD163⁺ immunosuppressive macrophages. Our results suggest that high-throughput assessment of genomic alterations at the single-cell level could provide a measure for predicting the immune state of GBM.

Abstract GS3-07: GS3-07 Clonal evolution and mechanisms of acquired resistance to CDK4/6 inhibitors in ER-wild type and ER-mutant breast cancer

Background Despite the remarkable activity of CDK4/6 inhibitors (CDK4/6i) in the treatment of estrogen receptor positive (ER+) metastatic breast cancer (BC), most patients eventually develop resistance to these drugs. The ctDNA analysis of the PALOMA-3 trial showed that the estrogen receptor (ER) mutation Y537S is a potential mechanism of acquired resistance to the combination of endocrine therapy (ET) with CDK4/6i. To date, the role of the ER mutations in the clonal evolution and the mechanisms of acquired resistance to CDK4/6i is unknown. Moreover, it is not known if the development of resistance to CDK4/6i in the presence or absence of ER mutations is due to the expansion of pre-existing resistant clones or to the de novo acquisition of resistance mechanisms. Methods To explore the clonal evolution and the mechanisms of resistance to CDK4/6i in ER-wild type (ER-WT) and ER-mutant (ER-Mut) BC, we transduced doxycycline (DOX)-inducible Y537S ER-Mut MCF7 cells with the ClonTracer library, a high-complexity DNA barcode library, and cultured the barcoded cells without DOX (MCF7), or with DOX to induce the expression of the Y537S ER mutation (MCF7-YS). To develop Palbociclib (Palbo)-resistant (PDR) and Abemaciclib (Abema)-resistant (ABR) cell models, the barcoded MCF7 and MCF7-YS cells were passaged in culture with increasing concentrations of Palbo and Abema until the acquisition of resistance. The clonal dynamics and the molecular characteristics of the PDR and ABR models were investigated by barcode sequencing, whole-exome sequencing (WES), bulk and single cell RNA sequencing (RNAseq) and protein analyses. Finally, using an ER-Mut barcoded mice model, we compared the in vitro clonal evolution of ER-Mut CDK4/6i-resistant cells with the in vivo clonal evolution of ER-Mut metastases. Results The analysis of the barcodes revealed that during the acquisition of resistance to either Palbo or Abema there is a strong clonal selection of pre-existing resistant clones. The PDR clones were different in the presence of the Y537S mutation versus WT-ER. In contrast, the clones enriched in the ABR cells were comparable between WT and mutant ER. Furthermore, the ER mutations led to decreased diversity of the enriched clones in the PDR but not in the ABR cells. Interestingly, the barcodes enriched in the PDR and ABR models did not overlap. Unsupervised analyses showed that the samples clustering based on the barcodes fractions and the mutations were similar, suggesting that the clonal selection was driven by cellular populations with specific mutational landscapes. All the ER-WT and ER-Mut resistant models had different transcriptional profiles and by single-cell RNAseq showed various degrees of intra-sample heterogeneity. At the protein level, the PDR and the ABR cells displayed downregulation of ER, Rb and p27 and upregulation of p21. In the ER-Mut conditions Cyclin D1 was upregulated in the PDR cells, while Cyclin E was upregulated in the ABR cells. Finally, the barcode sequencing of the mice metastases revealed that the clonal selection in ER-Mut metastases and in ER-Mut CDK4/6i-resistant cells is different. Conclusion Our study suggests that the development of resistance to CDK4/6i is due to the selection of pre-existing resistant clones. We also demonstrate that the expression of the Y537S ER mutation impacts the clonal evolution and the mechanisms of acquired resistance to Palbo but not to Abema. Finally, we show that the clonal evolution and mechanisms are disparate in Palbo and Abema resistance. These results support the addition of a third drug to CDK4/6i and ET, early in treatment, to delay the selection of pre-existing resistant clones and prolong the response to treatment and highlight differences between Palbo and Abema.

Citation Format: Cristina Guarducci, Simona Cristea, Avery Feit, Sergey Naumenko, Agostina Nardone, Wen Ma, Douglas Russo, Gabriella Cohen Feit, Ariel Feiglin, Francisco Hermida-Prado, Shira Sherman, Myles Brown, Franziska Michor, Rinath Jeselsohn. GS3-07 Clonal evolution and mechanisms of acquired resistance to CDK4/6 inhibitors in ER-wild type and ER-mutant breast cancer [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr GS3-07.

T-REX17 is a transiently expressed non-coding RNA essential for human endoderm formation

Long non-coding RNAs (lncRNAs) have emerged as fundamental regulators in various biological processes, including embryonic development and cellular differentiation. Despite much progress over the past decade, the genome-wide annotation of lncRNAs remains incomplete and many known non-coding loci are still poorly characterized. Here, we report the discovery of a previously unannotated lncRNA that is transcribed 230 kb upstream of the SOX17 gene and located within the same topologically associating domain. We termed it T-REX17 (Transcript Regulating Endoderm and activated by soX17) and show that it is induced following SOX17 activation but its expression is more tightly restricted to early definitive endoderm. Loss of T-REX17 affects crucial functions independent of SOX17 and leads to an aberrant endodermal transcriptome, signaling pathway deregulation and epithelial to mesenchymal transition defects. Consequently, cells lacking the lncRNA cannot further differentiate into more mature endodermal cell types. Taken together, our study identified and characterized T-REX17 as a transiently expressed and essential non-coding regulator in early human endoderm differentiation.

JAK-STAT Signaling in Inflammatory Breast Cancer Enables Chemotherapy-Resistant Cell States

Inflammatory breast cancer (IBC) is a difficult-to-treat disease with poor clinical outcomes due to high risk of metastasis and resistance to treatment. In breast cancer, CD44+CD24- cells possess stem cell-like features and contribute to disease progression, and we previously described a CD44+CD24-pSTAT3+ breast cancer cell subpopulation that is dependent on JAK2/STAT3 signaling. Here we report that CD44+CD24- cells are the most frequent cell type in IBC and are commonly pSTAT3+. Combination of JAK2/STAT3 inhibition with paclitaxel decreased IBC xenograft growth more than either agent alone. IBC cell lines resistant to paclitaxel and doxorubicin were developed and characterized to mimic therapeutic resistance in patients. Multi-omic profiling of parental and resistant cells revealed enrichment of genes associated with lineage identity and inflammation in chemotherapy-resistant derivatives. Integrated pSTAT3 chromatin immunoprecipitation sequencing and RNA sequencing (RNA-seq) analyses showed pSTAT3 regulates genes related to inflammation and epithelial-to-mesenchymal transition (EMT) in resistant cells, as well as PDE4A, a cAMP-specific phosphodiesterase. Metabolomic characterization identified elevated cAMP signaling and CREB as a candidate therapeutic target in IBC. Investigation of cellular dynamics and heterogeneity at the single cell level during chemotherapy and acquired resistance by CyTOF and single cell RNA-seq identified mechanisms of resistance including a shift from luminal to basal/mesenchymal cell states through selection for rare preexisting subpopulations or an acquired change. Finally, combination treatment with paclitaxel and JAK2/STAT3 inhibition prevented the emergence of the mesenchymal chemo-resistant subpopulation. These results provide mechanistic rational for combination of chemotherapy with inhibition of JAK2/STAT3 signaling as a more effective therapeutic strategy in IBC.

SIGNIFICANCE

Chemotherapy resistance in inflammatory breast cancer is driven by the JAK2/STAT3 pathway, in part via cAMP/PKA signaling and a cell state switch, which can be overcome using paclitaxel combined with JAK2 inhibitors.

Genomic analysis of early-stage lung cancer reveals a role for TP53 mutations in distant metastasis

Patients with non-small cell lung cancer (NSCLC) who have distant metastases have a poor prognosis. To determine which genomic factors of the primary tumor are associated with metastasis, we analyzed data from 759 patients originally diagnosed with stage I-III NSCLC as part of the AACR Project GENIE Biopharma Collaborative consortium. We found that TP53 mutations were significantly associated with the development of new distant metastases. TP53 mutations were also more prevalent in patients with a history of smoking, suggesting that these patients may be at increased risk for distant metastasis. Our results suggest that additional investigation of the optimal management of patients with early-stage NSCLC harboring TP53 mutations at diagnosis is warranted in light of their higher likelihood of developing new distant metastases.

Abstract A38: Cd70 genetic perturbation limits the development of an effective CD8+ T-cell immune response to Bcl6-driven diffuse large B-cell lymphoma

Multiple immunomodulatory pathways shape the development of anti-tumor immune responses to lymphoid malignancies. We previously defined the recurrent genetic alterations in diffuse large B-cell lymphoma (DLBCL) and identified associated substructure and additional potential genetic bases for immune escape. CD70 was the most commonly perturbed immune response pathway component in our cohort of primary DLBCLs; alterations included inactivating mutations and copy loss. CD70 co-stimulation of CD27+ T cells induces antigen-dependent T-cell expansion and immune surveillance of normal and malignant B cells. Given the frequent co-association of CD70 alterations and BCL6 translocations in our DLBCL patient series, we assessed the consequences of Cd70 deficiency on Bcl6-driven lymphomagenesis in a murine model. We crossed previously generated Cd70 −/- and Bcl6 tg/+ mice to obtain Cd70 −/−; Bcl6 tg/+ animals. In our aging cohorts, Cd70− / −; Bcl6tg/+ mice developed significantly increased numbers of histopathologically confirmed DLBCLs at earlier timepoints, compared to Bcl6 tg/+ animals. Both the Cd70 −/−; Bcl6 tg/+ and Bcl6 tg/+ mice that were euthanized for symptoms exhibited massive splenomegaly and lymphomatous splenic infiltration. None of the wild-type (WT) and Cd70 −/- animals developed lymphoma. To characterize potential differences in anti-tumor responses in Cd70 −/−; Bcl6 tg/+ versus Bcl6 tg/+ mice, we harvested spleens from asymptomatic animals in each cohort at 6, 14 and 18 months (mo). Cd70 −/−; Bcl6 tg/+ mice exhibited significantly earlier onset splenomegaly than Bcl6 tg/+ animals (both in comparison with WT mice). We performed single cell RNA sequencing of splenic cell suspensions from each murine cohort at the above-mentioned predetermined timepoints (6, 14 and 18 mo) and describe genotype-related changes in splenic CD8+ T-cell infiltration in this abstract. Our study revealed an age-related decline in the percentages of naive CD8+ T cells in all genotypes, with more striking and earlier changes in Cd70 −/−; Bcl6 tg/+ animals. Cd70 −/−; Bcl6 tg/+ and Bcl6 tg/+ mice exhibited a selective and significant expansion of CD8+ cytotoxic T cells (CTLs), which expressed Gzmb and Prf1 and the exhaustion markers, Pdcd1, Lag3, Tigit, Tox and Tim3, and exhibited clonal expansion. At 6 mo, prior to splenic enlargement and the development of symptoms, CD8+ CTLs in Cd70 −/−; Bcl6 tg/+ animals expressed significantly higher levels of exhaustion markers than those in Bcl6 tg/+ mice. Consistent with this finding, there was a more limited expansion and a subsequent contraction of these splenic CD8+ CTLs in Cd70 −/−; Bcl6 tg/+ mice, in comparison to Bcl6 tg/+ animals. Taken together, these findings suggest that initial anti-tumor immune responses are less effective in Cd70 −/−; Bcl6 tg/+ mice than in Bcl6 tg/+ animals and highlight the likely importance of CD70/CD27 co-stimulation in CD8+ T-cell response to Bcl6-driven DLBCL.

Citation Format: Elisa Mandato, Eleonora Calabretta, Gali Bai, Li Song, Yanbo Sun, Vignesh Shanmugam, Julia Paczkowska, Il-Kyu Choi, Robert Redd, Ming Tang, Lee N Lawton, Donna Neuberg, Scott Rodig, Franziska Michor, Baochun Zhang, Margaret A Shipp. Cd70 genetic perturbation limits the development of an effective CD8+ T-cell immune response to Bcl6-driven diffuse large B-cell lymphoma [abstract]. In: Proceedings of the Third AACR International Meeting: Advances in Malignant Lymphoma: Maximizing the Basic-Translational Interface for Clinical Application; 2022 Jun 23-26; Boston, MA. Philadelphia (PA): AACR; Blood Cancer Discov 2022;3(5_Suppl):Abstract nr A38.

Spatial intra-tumor heterogeneity is associated with survival of lung adenocarcinoma patients

Intra-tumor heterogeneity (ITH) of human tumors is important for tumor progression, treatment response, and drug resistance. However, the spatial distribution of ITH remains incompletely understood. Here, we present spatial analysis of ITH in lung adenocarcinomas from 147 patients using multi-region mass spectrometry of >5,000 regions, single-cell copy number sequencing of ~2,000 single cells, and cyclic immunofluorescence of >10 million cells. We identified two distinct spatial patterns among tumors, termed clustered and random geographic diversification (GD). These patterns were observed in the same samples using both proteomic and genomic data. The random proteomic GD pattern, which is characterized by decreased cell adhesion and lower levels of tumor-interacting endothelial cells, was significantly associated with increased risk of recurrence or death in two independent patient cohorts. Our study presents comprehensive spatial mapping of ITH in lung adenocarcinoma and provides insights into the mechanisms and clinical consequences of GD.

Designing optimal allocations for cancer screening using queuing network models

Cancer is one of the leading causes of death, but mortality can be reduced by detecting tumors earlier so that treatment is initiated at a less aggressive stage. The tradeoff between costs associated with screening and its benefit makes the decision of whom to screen and when a challenge. To enable comparisons across screening strategies for any cancer type, we demonstrate a mathematical modeling platform based on the theory of queuing networks designed for quantifying the benefits of screening strategies. Our methodology can be used to design optimal screening protocols and to estimate their benefits for specific patient populations. Our method is amenable to exact analysis, thus circumventing the need for simulations, and is capable of exactly quantifying outcomes given variability in the age of diagnosis, rate of progression, and screening sensitivity and intervention outcomes. We demonstrate the power of this methodology by applying it to data from the Surveillance, Epidemiology and End Results (SEER) program. Our approach estimates the benefits that various novel screening programs would confer to different patient populations, thus enabling us to formulate an optimal screening allocation and quantify its potential effects for any cancer type and intervention.

We describe a mathematical modeling methodology that offers quantitative insights into the potential benefits of screening and other interventions on cancer mortality. Our queuing-theoretic approach represents a potentially useful alternative to more traditional modeling approaches, in that it can provide more detailed results and entirely circumvents the need for simulations. Our methodology can be widely applied to estimate costs and benefits of screening strategies. By providing a detailed example of our method applied to epidemiological data, we hope to encourage greater uptake of this methodology in the community.

Abstract IA013: Genetic heterogeneity and tumor microenvironment in glioblastoma

Glioblastoma (GBM), the most aggressive brain tumor, remains an unmet medical need. Despite aggressive chemotherapy, radiation and surgery, only 5.6% of patients survive beyond 5 years post-diagnosis. Targeted approaches have not been successful in this tumor type due to the extreme heterogeneity of GBM. Mosaic amplification of oncogenes suggests that multiple genetically distinct clones are present in each tumor. However, little is known about how different subpopulations of GBM cells interact with each other or with the surrounding tumor microenvironment (TME). To address this, we employed spatial protein profiling coupled with single-cell spatial maps of fluorescence in situ hybridization (FISH) for key oncogenes frequently amplified in GBM. Our analysis spanned 3-4 areas from 17 formalin-fixed paraffin-embedded (FFPE) GBM cases, 96 sub-regions of interest and total of 35,843 single nuclei. Digital spatial profiling for 79 protein markers associated with GBM biology, TME and neurobiology revealed high intra-tumor variability of vasculature, between distinct regions of the same tumor biopsy. The single-cell FISH signal quantification allowed us to classify tumors based on the relative frequency of cells harboring co-occurring of EGFR and CDK4 amplifications. Tumors with low odds ratio for EGFR and CDK4 co-amplification in a cell had a significantly higher EGFR copy number in cells harboring this amplification. Cell-to-cell variation in EGFR copy number was also much higher in these tumors, suggesting a possibility for extrachromosomal origin of this amplification. Interestingly, the tumors with high frequency of cells harboring co-amplification of EGFR and CDK4 exhibit higher infiltration by CD163+ immunosuppressive macrophages. Our results suggest that high throughput assessment of genomic alterations at the single cell level could provide a measure for predicting the immune state of GBM.

Citation Format: Kacper A. Walentynowicz, Dalit Engelhardt, Shreya Yadav, Ugoma Onubogu, Roberto Salatino, Cristina Vincentelli, Thomas O. McDonald, Franziska Michor, Michalina Janiszewska. Genetic heterogeneity and tumor microenvironment in glioblastoma [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 IA013.

Barcoded Bulk QTL mapping reveals highly polygenic and epistatic architecture of complex traits in yeast

Mapping the genetic basis of complex traits is critical to uncovering the biological mechanisms that underlie disease and other phenotypes. Genome-wide association studies (GWAS) in humans and quantitative trait locus (QTL) mapping in model organisms can now explain much of the observed heritability in many traits, allowing us to predict phenotype from genotype. However, constraints on power due to statistical confounders in large GWAS and smaller sample sizes in QTL studies still limit our ability to resolve numerous small-effect variants, map them to causal genes, identify pleiotropic effects across multiple traits, and infer non-additive interactions between loci (epistasis). Here, we introduce barcoded bulk quantitative trait locus (BB-QTL) mapping, which allows us to construct, genotype, and phenotype 100,000 offspring of a budding yeast cross, two orders of magnitude larger than the previous state of the art. We use this panel to map the genetic basis of eighteen complex traits, finding that the genetic architecture of these traits involves hundreds of small-effect loci densely spaced throughout the genome, many with widespread pleiotropic effects across multiple traits. Epistasis plays a central role, with thousands of interactions that provide insight into genetic networks. By dramatically increasing sample size, BB-QTL mapping demonstrates the potential of natural variants in high-powered QTL studies to reveal the highly polygenic, pleiotropic, and epistatic architecture of complex traits.

PATH-29. GLIOBLASTOMA TUMOR CLASSIFICATION BASED ON SPATIAL ANALYSIS OF ONCOGENIC AMPLIFICATIONS AND PROTEIN EXPRESSION

Heterogeneity of glioblastoma (GBM) has been extensively studied in recent years with identification of oncogenic drivers of GBM cellular subtypes. However, little is known about how these cells interact with each other or with the surrounding tumor microenvironment (TME). We employed spatial protein profiling targeting immune and neuronal markers (79 proteins) coupled with single-cell spatial maps of fluorescence in situ hybridization (FISH) for EGFR, CDK4, and PDGFRA on human GBM tissue sections. Several cores from 20 GBM samples were collected to create a tissue microarray, and 96 regions of interests were profiled with 37,844 nuclei for oncogenic amplification screen. Spatial protein profiling identified strong correlation of certain immune markers, TAU-associated proteins, and oligodendrocyte-enriched protein groups and overall high intratumor heterogeneity of TME. Our single-cell quantification of FISH signals showed differences among tumors based on the prevalence of dual amplification of EGFR and CDK4 within a cell relative to single oncogene amplified cells. High relative frequency of dual amplification was associated with increased expression of immune-related markers and decreased expression of EGFR protein. Moreover, this protein expression signature was associated with survival in another GBM dataset. Here, we present spatial genetic analysis at the single cell level coupled with protein expression profiles associated with tumor microenvironment. Our results suggest that assessment of genetic heterogeneity in GBM could potentially drive improved patient stratification and treatment.

Response to comment on "Genomic epidemiology of superspreading events in Austria reveals mutational dynamics and transmission properties of SARS-CoV-2"

Further analysis of SARS-CoV-2 genome sequencing data identifies several highly recurrent genetic variants with low allele frequencies, which, if filtered out, provide estimates consistent with tighter transmission bottlenecks.

Impact of HER2 Heterogeneity on Treatment Response of Early-Stage HER2-Positive Breast Cancer: Phase II Neoadjuvant Clinical Trial of T-DM1 Combined with Pertuzumab

Intratumor heterogeneity is postulated to cause therapeutic resistance. To prospectively assess the impact of HER2 (ERBB2) heterogeneity on response to HER2-targeted therapy, we treated 164 patients with centrally confirmed HER2-positive early-stage breast cancer with neoadjuvant trastuzumab emtansine plus pertuzumab. HER2 heterogeneity was assessed on pretreatment biopsies from two locations of each tumor. HER2 heterogeneity, defined as an area with ERBB2 amplification in >5% but <50% of tumor cells, or a HER2-negative area by FISH, was detected in 10% (16/157) of evaluable cases. The pathologic complete response rate was 55% in the nonheterogeneous subgroup and 0% in the heterogeneous group (P < 0.0001, adjusted for hormone receptor status). Single-cell ERBB2 FISH analysis of cellular heterogeneity identified the fraction of ERBB2 nonamplified cells as a driver of therapeutic resistance. These data suggest HER2 heterogeneity is associated with resistance to HER2-targeted therapy and should be considered in efforts to optimize treatment strategies. SIGNIFICANCE: HER2-targeted therapies improve cure rates in HER2-positive breast cancer, suggesting chemotherapy can be avoided in a subset of patients. We show that HER2 heterogeneity, particularly the fraction of ERBB2 nonamplified cancer cells, is a strong predictor of resistance to HER2 therapies and could potentially be used to optimize treatment selection.See related commentary by Okines and Turner, p. 2369.This article is highlighted in the In This Issue feature, p. 2355.

Systematic tissue collection during clinical breast biopsy is feasible, safe and enables high-content translational analyses

Systematic collection of fresh tissues for research at the time of diagnostic image-guided breast biopsy has the potential to fuel a wide variety of innovative studies. Here we report the initial experience, including safety, feasibility, and laboratory proof-of-principle, with the collection and analysis of research specimens obtained via breast core needle biopsy immediately following routine clinical biopsy at a single institution over a 14-month period. Patients underwent one or two additional core biopsies following collection of all necessary clinical specimens. In total, 395 patients were approached and 270 consented to the research study, yielding a 68.4% consent rate. Among consenting patients, 238 lesions were biopsied for research, resulting in 446 research specimens collected. No immediate complications were observed. Representative research core specimens showed high diagnostic concordance with clinical core biopsies. Flow cytometry demonstrated consistent recovery of hundreds to thousands of viable cells per research core. Among a group of HER2 + tumor research specimens, HER2 assessment by flow cytometry correlated highly with immunohistochemistry (IHC) staining, and in addition revealed extensive inter- and intra-tumoral variation in HER2 levels of potential clinical relevance. Suitability for single-cell transcriptomic analysis was demonstrated for a triple-negative tumor core biopsy, revealing substantial cellular diversity in the tumor immune microenvironment, including a prognostically relevant T cell subpopulation. Thus, collection of fresh tissues for research purposes at the time of diagnostic breast biopsy is safe, feasible and efficient, and may provide a high-yield mechanism to generate a rich tissue repository for a wide variety of cross-disciplinary research.

Dissecting dual roles of MyoD during lineage conversion to mature myocytes and myogenic stem cells

The generation of myotubes from fibroblasts upon forced MyoD expression is a classic example of transcription factor-induced reprogramming. We recently discovered that additional modulation of signaling pathways with small molecules facilitates reprogramming to more primitive induced myogenic progenitor cells (iMPCs). Here, we dissected the transcriptional and epigenetic dynamics of mouse fibroblasts undergoing reprogramming to either myotubes or iMPCs using a MyoD-inducible transgenic model. Induction of MyoD in fibroblasts combined with small molecules generated Pax7⁺ iMPCs with high similarity to primary muscle stem cells. Analysis of intermediate stages of iMPC induction revealed that extinction of the fibroblast program preceded induction of the stem cell program. Moreover, key stem cell genes gained chromatin accessibility prior to their transcriptional activation, and these regions exhibited a marked loss of DNA methylation dependent on the Tet enzymes. In contrast, myotube generation was associated with few methylation changes, incomplete and unstable reprogramming, and an insensitivity to Tet depletion. Finally, we showed that MyoD's ability to bind to unique bHLH targets was crucial for generating iMPCs but dispensable for generating myotubes. Collectively, our analyses elucidate the role of MyoD in myogenic reprogramming and derive general principles by which transcription factors and signaling pathways cooperate to rewire cell identity.

Combined epigenetic and metabolic treatments overcome differentiation blockade in acute myeloid leukemia

A hallmark of acute myeloid leukemia (AML) is the inability of self-renewing malignant cells to mature into a non-dividing terminally differentiated state. This differentiation block has been linked to dysregulation of multiple cellular processes, including transcriptional, chromatin, and metabolic regulation. The transcription factor HOXA9 and the histone demethylase LSD1 are examples of such regulators that promote differentiation blockade in AML. To identify metabolic targets that interact with LSD1 inhibition to promote myeloid maturation, we screened a small molecule library to identify druggable substrates. We found that differentiation caused by LSD1 inhibition is enhanced by combined perturbation of purine nucleotide salvage and de novo lipogenesis pathways, and identified multiple lines of evidence to support the specificity of these pathways and suggest a potential basis of how perturbation of these pathways may interact synergistically to promote myeloid differentiation. In sum, these findings suggest potential drug combination strategies in the treatment of AML.

The impact of tumor epithelial and microenvironmental heterogeneity on treatment responses in HER2+ breast cancer

Despite the availability of multiple human epidermal growth factor receptor 2-targeted (HER2-targeted) treatments, therapeutic resistance in HER2+ breast cancer remains a clinical challenge. Intratumor heterogeneity for HER2 and resistance-conferring mutations in the PIK3CA gene (encoding PI3K catalytic subunit α) have been investigated in response and resistance to HER2-targeting agents, while the role of divergent cellular phenotypes and tumor epithelial-stromal cell interactions is less well understood. Here, we assessed the effect of intratumor cellular genetic heterogeneity for ERBB2 (encoding HER2) copy number and PIK3CA mutation on different types of neoadjuvant HER2-targeting therapies and clinical outcome in HER2+ breast cancer. We found that the frequency of cells lacking HER2 was a better predictor of response to HER2-targeted treatment than intratumor heterogeneity. We also compared the efficacy of different therapies in the same tumor using patient-derived xenograft models of heterogeneous HER2+ breast cancer and single-cell approaches. Stromal determinants were better predictors of response than tumor epithelial cells, and we identified alveolar epithelial and fibroblastic reticular cells as well as lymphatic vessel endothelial hyaluronan receptor 1-positive (Lyve1+) macrophages as putative drivers of therapeutic resistance. Our results demonstrate that both preexisting and acquired resistance to HER2-targeting agents involve multiple mechanisms including the tumor microenvironment. Furthermore, our data suggest that intratumor heterogeneity for HER2 should be incorporated into treatment design.

Progression signature underlies clonal evolution and dissemination of multiple myeloma

Clonal evolution drives tumor progression, dissemination, and relapse in multiple myeloma (MM), with most patients dying of relapsed disease. This multistage process requires tumor cells to enter the circulation, extravasate, and colonize distant bone marrow (BM) sites. Here, we developed a fluorescent or DNA-barcode clone-tracking system on MM PrEDiCT (progression through evolution and dissemination of clonal tumor cells) xenograft mouse model to study clonal behavior within the BM microenvironment. We showed that only the few clones that successfully adapt to the BM microenvironment can enter the circulation and colonize distant BM sites. RNA sequencing of primary and distant-site MM tumor cells revealed a progression signature sequentially activated along human MM progression and significantly associated with overall survival when evaluated against patient data sets. A total of 28 genes were then computationally predicted to be master regulators (MRs) of MM progression. HMGA1 and PA2G4 were validated in vivo using CRISPR-Cas9 in the PrEDiCT model and were shown to be significantly depleted in distant BM sites, indicating their role in MM progression and dissemination. Loss of HMGA1 and PA2G4 also compromised the proliferation, migration, and adhesion abilities of MM cells in vitro. Overall, our model successfully recapitulates key characteristics of human MM disease progression and identified potential new therapeutic targets for MM.

Computational modelling of perivascular-niche dynamics for the optimization of treatment schedules for glioblastoma

Glioblastoma stem-like cells dynamically transition between a chemoradiation-resistant state and a chemoradiation-sensitive state. However, physical barriers in the tumour microenvironment restrict the delivery of chemotherapy to tumour compartments that are distant from blood vessels. Here, we show that a massively parallel computational model of the spatiotemporal dynamics of the perivascular niche that incorporates glioblastoma stem-like cells and differentiated tumour cells as well as relevant tissue-level phenomena can be used to optimize the administration schedules of concurrent radiation and temozolomide-the standard-of-care treatment for glioblastoma. In mice with platelet-derived growth factor (PDGF)-driven glioblastoma, the model-optimized treatment schedule increased the survival of the animals. For standard radiation fractionation in patients, the model predicts that chemotherapy may be optimally administered about one hour before radiation treatment. Computational models of the spatiotemporal dynamics of the tumour microenvironment could be used to predict tumour responses to a broader range of treatments and to optimize treatment regimens.

Breast tumours maintain a reservoir of subclonal diversity during expansion

Our knowledge of copy number evolution during the expansion of primary breast tumours is limited^1,2. Here, to investigate this process, we developed a single-cell, single-molecule DNA-sequencing method and performed copy number analysis of 16,178 single cells from 8 human triple-negative breast cancers and 4 cell lines. The results show that breast tumours and cell lines comprise a large milieu of subclones (7-22) that are organized into a few (3-5) major superclones. Evolutionary analysis suggests that after clonal TP53 mutations, multiple loss-of-heterozygosity events and genome doubling, there was a period of transient genomic instability followed by ongoing copy number evolution during the primary tumour expansion. By subcloning single daughter cells in culture, we show that tumour cells rediversify their genomes and do not retain isogenic properties. These data show that triple-negative breast cancers continue to evolve chromosome aberrations and maintain a reservoir of subclonal diversity during primary tumour growth.

Reconstructing the Lineage Histories and Differentiation Trajectories of Individual Cancer Cells in Myeloproliferative Neoplasms

Some cancers originate from a single mutation event in a single cell. Blood cancers known as myeloproliferative neoplasms (MPNs) are thought to originate when a driver mutation is acquired by a hematopoietic stem cell (HSC). However, when the mutation first occurs in individuals and how it affects the behavior of HSCs in their native context is not known. Here we quantified the effect of the JAK2-V617F mutation on the self-renewal and differentiation dynamics of HSCs in treatment-naive individuals with MPNs and reconstructed lineage histories of individual HSCs using somatic mutation patterns. We found that JAK2-V617F mutations occurred in a single HSC several decades before MPN diagnosis-at age 9 ± 2 years in a 34-year-old individual and at age 19 ± 3 years in a 63-year-old individual-and found that mutant HSCs have a selective advantage in both individuals. These results highlight the potential of harnessing somatic mutations to reconstruct cancer lineages.

ESTIpop: a computational tool to simulate and estimate parameters for continuous-time Markov branching processes

SUMMARY

ESTIpop is an R package designed to simulate and estimate parameters for continuous-time Markov branching processes with constant or time-dependent rates, a common model for asexually reproducing cell populations. Analytical approaches to parameter estimation quickly become intractable in complex branching processes. In ESTIpop, parameter estimation is based on a likelihood function with respect to a time series of cell counts, approximated by the Central Limit Theorem for multitype branching processes. Additionally, simulation in ESTIpop via approximation can be performed many times faster than exact simulation methods with similar results.

AVAILABILITY AND IMPLEMENTATION

ESTIpop is available as an R package on Github (https://github.com/michorlab/estipop).

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Genomic epidemiology of superspreading events in Austria reveals mutational dynamics and transmission properties of SARS-CoV-2

Superspreading events shaped the coronavirus disease 2019 (COVID-19) pandemic, and their rapid identification and containment are essential for disease control. Here, we provide a national-scale analysis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) superspreading during the first wave of infections in Austria, a country that played a major role in initial virus transmissions in Europe. Capitalizing on Austria's well-developed epidemiological surveillance system, we identified major SARS-CoV-2 clusters during the first wave of infections and performed deep whole-genome sequencing of more than 500 virus samples. Phylogenetic-epidemiological analysis enabled the reconstruction of superspreading events and charts a map of tourism-related viral spread originating from Austria in spring 2020. Moreover, we exploited epidemiologically well-defined clusters to quantify SARS-CoV-2 mutational dynamics, including the observation of low-frequency mutations that progressed to fixation within the infection chain. Time-resolved virus sequencing unveiled viral mutation dynamics within individuals with COVID-19, and epidemiologically validated infector-infectee pairs enabled us to determine an average transmission bottleneck size of 103 SARS-CoV-2 particles. In conclusion, this study illustrates the power of combining epidemiological analysis with deep viral genome sequencing to unravel the spread of SARS-CoV-2 and to gain fundamental insights into mutational dynamics and transmission properties.

Abstract PO-133: Breast tumors maintain a reservoir of subclonal diversity during primary expansion

Our knowledge of copy number evolution during the expansion of primary breast tumors is limited. To investigate this process, we developed a single-cell, single-molecule DNA sequencing method and performed copy number analysis of 13,808 single cells from six triple-negative breast cancers (TNBCs) and two breast cancer cell lines. Our data shows that breast tumors and cell lines are comprised of a large milieu (17-26) of subclones that are organized into a few (4-8) major superclones. Phylogenetic analysis and mathematical modeling show that copy number evolution was ongoing during the expansion of the primary tumor, after the initial punctuated burst of genomic instability. By expanding single daughter cells in culture, we show that cancer cells re-diversify their genomes and do not retain isogenic properties. These data elucidate modes of evolution and show that TNBCs maintain a vast reservoir of subclonal copy number diversity during the expansion of the primary tumor mass.

Citation Format: Darlan Conterno Minussi, Michael Nicholson, Hanghui Ye, Alexander Davis, Kaile Wang, Emi Sei, Haowei Du, Mashiat Rabbani, Cheng Peng, Min Hu, Shanshan Bai, Thomas McDonald, Aislyn Schalck, Anna Casasent, Angelica Barrera, Hui Chen, Bora Lim, Banu Arun, Funda Meric-Bernstam, Franziska Michor, Nicholas Navin. Breast tumors maintain a reservoir of subclonal diversity during primary expansion [abstract]. In: Proceedings of the AACR Virtual Special Conference on Tumor Heterogeneity: From Single Cells to Clinical Impact; 2020 Sep 17-18. Philadelphia (PA): AACR; Cancer Res 2020;80(21 Suppl):Abstract nr PO-133.

Pharmacokinetic Profiles Determine Optimal Combination Treatment Schedules in Computational Models of Drug Resistance

Identification of optimal schedules for combination drug administration relies on accurately estimating the correct pharmacokinetics, pharmacodynamics, and drug interaction effects. Misspecification of pharmacokinetics can lead to wrongly predicted timing or order of treatments, leading to schedules recommended on the basis of incorrect assumptions about absorption and elimination of a drug and its effect on tumor growth. Here, we developed a computational modeling platform and software package for combination treatment strategies with flexible pharmacokinetic profiles and multidrug interaction curves that are estimated from data. The software can be used to compare prespecified schedules on the basis of the number of resistant cells where drug interactions and pharmacokinetic curves can be estimated from user-provided data or models. We applied our approach to publicly available in vitro data of treatment with different tyrosine kinase inhibitors of BT-20 triple-negative breast cancer cells and of treatment with erlotinib of PC-9 non-small cell lung cancer cells. Our approach is publicly available in the form of an R package called ACESO (https://github.com/Michorlab/aceso) and can be used to investigate optimum dosing for any combination treatment. SIGNIFICANCE: These findings introduce a computational modeling platform and software package for combination treatment strategies with flexible pharmacokinetic profiles and multidrug interaction curves that are estimated from data.

Circadian clock effects on cellular proliferation: Insights from theory and experiments

Oscillations of the cellular circadian clock have emerged as an important regulator of many physiological processes, both in health and in disease. One such process, cellular proliferation, is being increasingly recognized to be affected by the circadian clock. Here, we review how a combination of experimental and theoretical work has furthered our understanding of the way circadian clocks couple to the cell cycle and play a role in tissue homeostasis and cancer. Finally, we discuss recently introduced methods for modeling coupling of clocks based on techniques from survival analysis and machine learning and highlight their potential importance for future studies.

Synthetic Lethal and Resistance Interactions with BET Bromodomain Inhibitors in Triple-Negative Breast Cancer

BET bromodomain inhibitors (BBDIs) are candidate therapeutic agents for triple-negative breast cancer (TNBC) and other cancer types, but inherent and acquired resistance to BBDIs limits their potential clinical use. Using CRISPR and small-molecule inhibitor screens combined with comprehensive molecular profiling of BBDI response and resistance, we identified synthetic lethal interactions with BBDIs and genes that, when deleted, confer resistance. We observed synergy with regulators of cell cycle progression, YAP, AXL, and SRC signaling, and chemotherapeutic agents. We also uncovered functional similarities and differences among BRD2, BRD4, and BRD7. Although deletion of BRD2 enhances sensitivity to BBDIs, BRD7 loss leads to gain of TEAD-YAP chromatin binding and luminal features associated with BBDI resistance. Single-cell RNA-seq, ATAC-seq, and cellular barcoding analysis of BBDI responses in sensitive and resistant cell lines highlight significant heterogeneity among samples and demonstrate that BBDI resistance can be pre-existing or acquired.

Stochastic Evolution of Pancreatic Cancer Metastases During Logistic Clonal Expansion

Despite recent progress in diagnostic and multimodal treatment approaches, most cancer deaths are still caused by metastatic spread and the subsequent growth of tumor cells in sites distant from the primary organ. So far, few quantitative studies are available that allow for the estimation of metastatic parameters and the evaluation of alternative treatment strategies. Most computational studies have focused on situations in which the tumor cell population expands exponentially over time; however, tumors may eventually be subject to resource and space limitations so that their growth patterns deviate from exponential growth to adhere to density-dependent growth models. In this study, we developed a stochastic evolutionary model of cancer progression that considers alterations in metastasis-related genes and intercellular growth competition leading to density effects described by logistic growth. Using this stochastic model, we derived analytical approximations for the time between the initiation of tumorigenesis and diagnosis, the expected number of metastatic sites, the total number of metastatic cells, the size of the primary tumor, and survival. Furthermore, we investigated the effects of drug administration and surgical resection on these quantities and predicted outcomes for different treatment regimens. Parameter values used in the analysis were estimated from data obtained from a pancreatic cancer rapid autopsy program. Our theoretical approach allows for flexible modeling of metastatic progression dynamics.

Abstract B16: Mathematical modeling identifies optimum palbociclib dosing schedules for the treatment of estrogen receptor-positive (ER+) breast cancer patients

Fulvestrant and other endocrine therapies are widely used to treat estrogen receptor-positive (ER+) breast cancer, although most patients eventually develop treatment resistance. Endocrine therapy-resistant tumors have been shown to be sensitive to cyclin-dependent kinases 4/6 (CDK4/6) inhibitors, including palbociclib, abemaciclib, and ribociclib, which have recently been approved to be used in combination with endocrine therapies to treat ER+ breast cancers. Given the large number of possible pairwise drug combinations, systematically comparing different combinations and administration schedules experimentally is difficult, though it has been shown that altering therapy administration schedules can substantially improve treatment outcomes. Here, we develop a novel mathematical model to characterize the pharmacodynamic response to fulvestrant-palbociclib combination therapy in fulvestrant-sensitive and -resistant MCF7 cells. We use a cell cycle explicit model to describe changes in the G1/S transition rates in response to the combination therapy, and a Bayesian statistical inference approach to estimate model parameters from the in vitro data. We then combine the results from our pharmacodynamic model with published pharmacokinetic data to systematically compare dose administration schedules computationally. We use in silico clinical trials to identify treatment schedules within the clinical toxicity limits that are predicted to be more effective than the current standard of care. Our results suggest that continuous dosing of 75mg of palbociclib with no treatment holiday is more effective for slowing down tumor growth and lowering overall tumor burden than the current palbociclib treatment standard (125mg of palbociclib per day, three weeks on, followed by a one-week holiday). We predict that both palbociclib treatment strategies are most effective when combined with the current standard fulvestrant administration schedule, even when considering various levels of fulvestrant resistance. Thus, we plan to compare the two palbocilib schedules described above in combination with the current standard fulvestrant therapy in an investigator-led clinical trial at Dana-Farber Cancer Institute. Our mathematical modeling and statistical analysis platform provides a rational method for comparing treatment strategies in search of optimal combination dosing strategies for ER+ breast cancer.

Citation Format: Shayna Stein, Agostina Nardone, Weihan Liu, Gabriella Cohen, Cristina Guarducci, Myles Brown, Rinath Jeselsohn, Franziska Michor. Mathematical modeling identifies optimum palbociclib dosing schedules for the treatment of estrogen receptor-positive (ER+) breast cancer patients [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 B16.

Acquired resistance to combined BET and CDK4/6 inhibition in triple-negative breast cancer

BET inhibitors are promising therapeutic agents for the treatment of triple-negative breast cancer (TNBC), but the rapid emergence of resistance necessitates investigation of combination therapies and their effects on tumor evolution. Here, we show that palbociclib, a CDK4/6 inhibitor, and paclitaxel, a microtubule inhibitor, synergize with the BET inhibitor JQ1 in TNBC lines. High-complexity DNA barcoding and mathematical modeling indicate a high rate of de novo acquired resistance to these drugs relative to pre-existing resistance. We demonstrate that the combination of JQ1 and palbociclib induces cell division errors, which can increase the chance of developing aneuploidy. Characterizing acquired resistance to combination treatment at a single cell level shows heterogeneous mechanisms including activation of G1-S and senescence pathways. Our results establish a rationale for further investigation of combined BET and CDK4/6 inhibition in TNBC and suggest novel mechanisms of action for these drugs and new vulnerabilities in cells after emergence of resistance.

Drug Sensitivity and Allele Specificity of First-Line Osimertinib Resistance EGFR Mutations

Osimertinib, a mutant-specific third-generation EGFR tyrosine kinase inhibitor, is emerging as the preferred first-line therapy for EGFR-mutant lung cancer, yet resistance inevitably develops in patients. We modeled acquired resistance to osimertinib in transgenic mouse models of EGFR^L858R -induced lung adenocarcinoma and found that it is mediated largely through secondary mutations in EGFR-either C797S or L718V/Q. Analysis of circulating free DNA data from patients revealed that L718Q/V mutations almost always occur in the context of an L858R driver mutation. Therapeutic testing in mice revealed that both erlotinib and afatinib caused regression of osimertinib-resistant C797S-containing tumors, whereas only afatinib was effective on L718Q mutant tumors. Combination first-line osimertinib plus erlotinib treatment prevented the emergence of secondary mutations in EGFR. These findings highlight how knowledge of the specific characteristics of resistance mutations is important for determining potential subsequent treatment approaches and suggest strategies to overcome or prevent osimertinib resistance in vivo. SIGNIFICANCE: This study provides insight into the biological and molecular properties of osimertinib resistance EGFR mutations and evaluates therapeutic strategies to overcome resistance. GRAPHICAL ABSTRACT: http://cancerres.aacrjournals.org/content/canres/80/10/2017/F1.large.jpg.

Ascl2-Dependent Cell Dedifferentiation Drives Regeneration of Ablated Intestinal Stem Cells

Ablation of LGR5⁺ intestinal stem cells (ISCs) is associated with rapid restoration of the ISC compartment. Different intestinal crypt populations dedifferentiate to provide new ISCs, but the transcriptional and signaling trajectories that guide this process are unclear, and a large body of work suggests that quiescent "reserve" ISCs contribute to regeneration. By timing the interval between LGR5⁺ lineage tracing and lethal injury, we show that ISC regeneration is explained nearly completely by dedifferentiation, with contributions from absorptive and secretory progenitors. The ISC-restricted transcription factor ASCL2 confers measurable competitive advantage to resting ISCs and is essential to restore the ISC compartment. Regenerating cells re-express Ascl2 days before Lgr5, and single-cell RNA sequencing (scRNA-seq) analyses reveal transcriptional paths underlying dedifferentiation. ASCL2 target genes include the interleukin-11 (IL-11) receptor Il11ra1, and recombinant IL-11 enhances crypt cell regenerative potential. These findings reveal cell dedifferentiation as the principal means for ISC restoration and highlight an ASCL2-regulated signal that enables this adaptive response.