Cell-free DNA concentration as a biomarker of response and recurrence in HER2-negative breast cancer receiving neoadjuvant chemotherapy

PURPOSE

We previously demonstrated the clinical significance of circulating tumor DNA (ctDNA) in patients with HER2-negative breast cancer receiving neoadjuvant chemotherapy (NAC). Here, we compared its predictive and prognostic value with cell-free DNA (cfDNA) concentration measured in the same samples from the same patients.

EXPERIMENTAL DESIGN

145 hormone receptor (HR)-positive/HER2-negative and 138 triple-negative breast cancer (TNBC) patients with ctDNA data from a previous study were included in the analysis. Associations of serial cfDNA concentration with residual cancer burden (RCB) and distant recurrence-free survival (DRFS) were examined.

RESULTS

In TNBC, we observed a modest negative correlation between cfDNA concentration 3 weeks after treatment initiation and RCB, but none of the other timepoints showed significant correlation. In contrast, ctDNA was significantly positively correlated with RCB at all timepoints (all R>0.3 and p<0.05). In the HR-positive/HER2-negative group, cfDNA concentration did not associate with response to NAC, but survival analysis showed that high cfDNA-shedders at pretreatment had a significantly worse DRFS than low shedders (hazard ratio 2.12, p=0.037). In TNBC, the difference in survival between high vs. low cfDNA-shedders at all timepoints was not statistically significant. In contrast, as previously reported, ctDNA at all timepoints was significantly correlated with DRFS in both subtypes.

CONCLUSIONS

In TNBC, cfDNA concentrations during therapy were not strongly correlated with response or prognosis. In the HR-positive/HER2-negative group, pretreatment cfDNA concentration was prognostic for DRFS. Overall, the predictive and prognostic value of cfDNA concentration was more limited than that of ctDNA.

Loss of epigenetic suppression of retrotransposons with oncogenic potential in aging mammary luminal epithelial cells

A primary function of DNA methylation in mammalian genomes is to repress transposable elements (TEs). The widespread methylation loss that is commonly observed in cancer cells results in the loss of epigenetic repression of TEs. The aging process is similarly characterized by changes to the methylome. However, the impact of these epigenomic alterations on TE silencing and the functional consequences of this have remained unclear. To assess the epigenetic regulation of TEs in aging, we profiled DNA methylation in human mammary luminal epithelial cells (LEps)-a key cell lineage implicated in age-related breast cancers-from younger and older women. We report here that several TE subfamilies function as regulatory elements in normal LEps, and a subset of these display consistent methylation changes with age. Methylation changes at these TEs occurred at lineage-specific transcription factor binding sites, consistent with loss of lineage specificity. Whereas TEs mainly showed methylation loss, CpG islands (CGIs) that are targets of the Polycomb repressive complex 2 (PRC2) show a gain of methylation in aging cells. Many TEs with methylation loss in aging LEps have evidence of regulatory activity in breast cancer samples. We furthermore show that methylation changes at TEs impact the regulation of genes associated with luminal breast cancers. These results indicate that aging leads to DNA methylation changes at TEs that undermine the maintenance of lineage specificity, potentially increasing susceptibility to breast cancer.

Clinical significance and biology of circulating tumor DNA in high-risk early-stage HER2-negative breast cancer receiving neoadjuvant chemotherapy

Circulating tumor DNA (ctDNA) analysis may improve early-stage breast cancer treatment via non-invasive tumor burden assessment. To investigate subtype-specific differences in the clinical significance and biology of ctDNA shedding, we perform serial personalized ctDNA analysis in hormone receptor (HR)-positive/HER2-negative breast cancer and triple-negative breast cancer (TNBC) patients receiving neoadjuvant chemotherapy (NAC) in the I-SPY2 trial. ctDNA positivity rates before, during, and after NAC are higher in TNBC than in HR-positive/HER2-negative breast cancer patients. Early clearance of ctDNA 3 weeks after treatment initiation predicts a favorable response to NAC in TNBC only. Whereas ctDNA positivity associates with reduced distant recurrence-free survival in both subtypes. Conversely, ctDNA negativity after NAC correlates with improved outcomes, even in patients with extensive residual cancer. Pretreatment tumor mRNA profiling reveals associations between ctDNA shedding and cell cycle and immune-associated signaling. On the basis of these findings, the I-SPY2 trial will prospectively test ctDNA for utility in redirecting therapy to improve response and prognosis.

An integrated tumor, immune and microbiome atlas of colon cancer

The lack of multi-omics cancer datasets with extensive follow-up information hinders the identification of accurate biomarkers of clinical outcome. In this cohort study, we performed comprehensive genomic analyses on fresh-frozen samples from 348 patients affected by primary colon cancer, encompassing RNA, whole-exome, deep T cell receptor and 16S bacterial rRNA gene sequencing on tumor and matched healthy colon tissue, complemented with tumor whole-genome sequencing for further microbiome characterization. A type 1 helper T cell, cytotoxic, gene expression signature, called Immunologic Constant of Rejection, captured the presence of clonally expanded, tumor-enriched T cell clones and outperformed conventional prognostic molecular biomarkers, such as the consensus molecular subtype and the microsatellite instability classifications. Quantification of genetic immunoediting, defined as a lower number of neoantigens than expected, further refined its prognostic value. We identified a microbiome signature, driven by Ruminococcus bromii, associated with a favorable outcome. By combining microbiome signature and Immunologic Constant of Rejection, we developed and validated a composite score (mICRoScore), which identifies a group of patients with excellent survival probability. The publicly available multi-omics dataset provides a resource for better understanding colon cancer biology that could facilitate the discovery of personalized therapeutic approaches.

Abstract A003: Integrating noise into a signal: Luminal epithelial cells integrate variable responses to aging into stereotypical changes that underlie breast cancer susceptibility

This abstract is being presented as a short talk in the scientific program. A full abstract is available in the Short Talks from Proffered Abstracts section (PR006) of the Conference Proceedings.

Citation Format: Masaru Miyano, Rosalyn W. Sayaman, Parijat Senapati, Stefan Hinz, Victoria E. Seewaldt, Dustin Schones, Mark A. LaBarge. Integrating noise into a signal: Luminal epithelial cells integrate variable responses to aging into stereotypical changes that underlie breast cancer susceptibility [abstract]. In: Proceedings of the AACR Special Conference: Aging and Cancer; 2022 Nov 17-20; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2022;83(2 Suppl_1):Abstract nr A003.

Abstract A016: Aging-dependent emergent mechanical properties of single epithelial cells exploited for detection of breast cancer susceptibility

Age is the major risk factor in most carcinomas, yet, little is known about the specific reasons aging increases cancer susceptibility. In the mammary gland, luminal epithelial cells rank high as the putative breast cancer cell of origin. Dysregulation of keratin intermediate filament proteins exemplifies a hallmark age-dependent change in luminal cells, which implicates mechanical states unique to cancer susceptible cells. We implemented mechano-node-pore sensing (mechano-NPS), a multi-parametric single-cell analysis that simultaneously measures cell diameter, resistance to compressive deformation, transverse deformation under constant strain, and recovery time after deformation. We demonstrated that the epithelial lineages, chronological ages, and stages of cancer progression of primary human mammary epithelial cells (HMEC) exhibited discrete mechanical phenotypes. We trained a machine learning model that accurately predicted the chronological age of average risk HMEC cells based exclusively on mechanical properties. Application of the model to cells from women who are germline carriers of high-risk cancer-causing mutations showed that they are mechanically old irrespective of their chronological age, suggesting that mechanical states could be a window into detection and prevention of cancer susceptible states. Indeed, this mechano-age model detected high-risk women with &gt;90% accuracy. Mass spectrometry and cell-based functional assays in mammary epithelia revealed that cytoskeleton related proteins keratin 14 (KRT14) and pseudopodium enriched atypical kinase 1 (PEAK1) were key drivers of age-dependent mechanical signatures. Pharmacological and gene silencing approaches that targeted KRT14 and PEAK1 modulated the mechanical age of HMEC and, in the case of PEAK1 modulation, ablated luminal epithelial cells in an age- and lineage- dependent manner. We define an intersection between mechanical phenotypes and novel age-dependent changes in cytoskeleton-related proteins that we hypothesize can be exploited to assess an individual’s breast cancer susceptibility and provide new targets for cancer-prevention strategies.

Citation Format: Stefan Hinz, Masaru Miyano, Antigoni Manousopoulou, Rosalyn W. Sayaman, Kristina Y. Aguilera, Michael E. Todhunter, Jennifer C. Lopez, Leo D. Wang, Lydia L. Sohn, Mark A. LaBarge. Aging-dependent emergent mechanical properties of single epithelial cells exploited for detection of breast cancer susceptibility [abstract]. In: Proceedings of the AACR Special Conference: Aging and Cancer; 2022 Nov 17-20; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2022;83(2 Suppl_1):Abstract nr A016.

Analytic pipelines to assess the relationship between immune response and germline genetics in human tumors

Germline genetic variants modulate human immune response. We present analytical pipelines for assessing the contribution of hosts' genetic background to the immune landscape of solid tumors using harmonized data from more than 9,000 patients in The Cancer Genome Atlas (TCGA). These include protocols for heritability, genome-wide association studies (GWAS), colocalization, and rare variant analyses. These workflows are developed around the structure of TCGA but can be adapted to explore other repositories or in the context of cancer immunotherapy. For complete details on the use and execution of this protocol, please refer to Sayaman et al. (2021).

Analysis of germline-driven ancestry-associated gene expression in cancers

Differential mRNA expression between ancestry groups can be explained by both genetic and environmental factors. We outline a computational workflow to determine the extent to which germline genetic variation explains cancer-specific molecular differences across ancestry groups. Using multi-omics datasets from The Cancer Genome Atlas (TCGA), we enumerate ancestry-informative markers colocalized with cancer-type-specific expression quantitative trait loci (e-QTLs) at ancestry-associated genes. This approach is generalizable to other settings with paired germline genotyping and mRNA expression data for a multi-ethnic cohort.

For complete details on the use and execution of this protocol, please refer to Carrot-Zhang et al. (2020), Robertson et al. (2021), and Sayaman et al. (2021).

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Protocol for obtaining controlled access TCGA datasets

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Protocols for quality control analysis and genotype imputation of TCGA germline data

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Statistical analysis for determining ancestry-associated SNPs

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Determination of ancestry-associated germline genetic variation driving mRNA expression

Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

Abstract 5682: Accelerated biological age is a driver of cancer susceptibility in genetic high risk breast tissue

During aging in the human mammary gland, luminal epithelial cells lose lineage fidelity by expressing markers normally expressed in myoepithelial cells. We hypothesize that loss of lineage fidelity is a general manifestation of epithelia that are susceptible to cancer initiation. We show that histologically normal breast tissue from younger women who are susceptible to breast cancer because they harbor a germline mutation in BRCA1, BRCA2, or PALB2 genes, exhibit hallmarks of accelerated aging. These include proportionately increased luminal epithelial cells that acquired myoepithelial markers, decreased proportions of myoepithelial cells, and a basal differentiation bias or failure of differentiation of cKit+ progenitors. High-risk luminal and myoepithelial cells are transcriptionally enriched for genes of the opposite lineage, inflammatory, and cancer-related pathways. Genetically high risk luminal epithelial cells also show evidence of accelerated age, by as much as four decades compared to their chronological age, using a breast specific biological clock comprised of measurements of methylation and expression of the luminal-specific ELF5 transcription factor. We have identified breast aging hallmarks that reflect a convergent biology of cancer susceptibility, regardless of the specific underlying genetic or age-dependent risk, or the associated breast cancer subtype.

Citation Format: Masaru Miyano, Sundus Shalabi, Rosalyn W. Sayaman, Martha Stampfer, Victoria E. Seewaldt, Mark A. LaBarge. Accelerated biological age is a driver of cancer susceptibility in genetic high risk breast tissue [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5682.

Abstract P2-01-03: Elucidating the biology of circulating tumor DNA (ctDNA) shedding across receptor subtypes in high-risk early-stage breast cancer

Background: Identifying mechanisms that govern the shedding of ctDNA in blood could inform the use of liquid biopsy in individual patients. Previous studies in the I-SPY2 neoadjuvant trial involving high-risk breast cancer showed that the detection of ctDNA before treatment was associated with aggressive clinical characteristics and residual ctDNA after treatment was associated with poor outcomes. Moreover, ctDNA positivity rates significantly varied across breast cancer subtypes suggesting that ctDNA shedding may in part be driven by subtype-specific etiology. We performed genome-wide transcriptomic analysis to identify genes and biological processes associated with increased ctDNA shedding within and across receptor subtypes. Methods: Our study involved 227 patients in I-SPY2 with tumor gene expression and ctDNA data at pretreatment. All patients were at high risk for recurrence (MammaPrint high). Each subtype: HR+HER2- (n=109), HER2+ (n=19), and triple negative breast cancer (TNBC, n=99) was evaluated independently. We performed differential expression (DE) analysis on the global transcriptome (m=19,134 genes) and curated gene signature (cGS, m=31 signatures developed in I-SPY2) data between ctDNA+ and ctDNA- patients at baseline. Gene-set enrichment analysis (GSEA) was also performed across hallmark (H, m=50), canonical pathway (CP, m=5,501), gene ontology (GO, m=9,996) and immunologic (IM, m=4,872) gene sets. Features were associated with ctDNA shedding if Benjamini-Hochberg adjusted p &lt; 0.05. For subtypes with smaller sample size and unbalanced groups, we also report features with nominally significant p &lt; 0.05. Results: ctDNA positivity rate was significantly higher in TNBC (91%) than in HR+HER2- and HER2+ (65% and 74% respectively, Fisher p &lt;0.001). The HR+HER2- subtype had the most significant hits for DE analysis between ctDNA+ and ctDNA- patients, with 0.2% of genes and 3.2% of cGS. No genes or cGS were differentially expressed in TNBC and HER2+, likely due to imbalance or small size of these groups. For GSEA, we observed the most significant number of enrichments in HR+HER2- subtype, with 58%, 21.8%, 4.4% and 40.3% of H, CP, GO, and IM gene sets enriched, respectively. In the HER2+ subtype, 40% H, 15.7% CP and 36.4% IM gene sets were significantly enriched, while no gene sets were enriched in TNBC. To identify common mechanistic themes across subtypes, we also considered nominally significant features in DE and GSEA. Processes associated with infection and innate immune responses were enriched in ctDNA+ patients, while adaptive immune response and antigen presentation—e.g., T-cell, TCR and MHC II protein complex, and downregulation of MYC targets were enriched in ctDNA- patients. HR+HER2- and HER2+ subtypes shared the most common modulated features with 134 genes and 2,165 gene sets, including up-regulation of cell cycle and proliferation in ctDNA+ patients, as well as up- or down-regulation of specific immunologic and metabolic processes. In contrast, TNBC gene set enrichment was associated with more distinct biologic processes, sharing common enrichment of 113 and 27 gene sets with HR+HER2- and HER2+ subtype, respectively. Conclusions: Findings from our exploratory analysis suggest a key role of immune response pathways in the control of ctDNA release. Additionally, tumor cell proliferation was associated with increased shedding in HR+HER2- and HER2+ subtypes, while down regulation of MYC targets was associated with ctDNA- patients across all subtypes. These suggest an important role of cell cycle in ctDNA shedding. Overall, our analysis revealed common and unique mechanisms potentially associated with ctDNA shedding across and within subtypes. However, due to the unbalanced groups and limited sample sizes, validation in a larger cohort is warranted.

Citation Format: Rosalyn W. Sayaman, Denise M. Wolf, Christina Yau, Lamorna Brown Swigart, Gillian L. Hirst, Laura Sit, Nicholas O'Grady, Amy L. Delson, I-SPY2 Investigators, Laura Esserman, Laura J. van 't Veer, Mark Jesus M. Magbanua. Elucidating the biology of circulating tumor DNA (ctDNA) shedding across receptor subtypes in high-risk early-stage breast cancer [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P2-01-03.

Deep proteome profiling of human mammary epithelia at lineage and age resolution

Age is the major risk factor in most carcinomas, yet little is known about how proteomes change with age in any human epithelium. We present comprehensive proteomes comprised of >9,000 total proteins and >15,000 phosphopeptides from normal primary human mammary epithelia at lineage resolution from ten women ranging in age from 19 to 68 years. Data were quality controlled and results were biologically validated with cell-based assays. Age-dependent protein signatures were identified using differential expression analyses and weighted protein co-expression network analyses. Upregulation of basal markers in luminal cells, including KRT14 and AXL, were a prominent consequence of aging. PEAK1 was identified as an age-dependent signaling kinase in luminal cells, which revealed a potential age-dependent vulnerability for targeted ablation. Correlation analyses between transcriptome and proteome revealed age-associated loss of proteostasis regulation. Age-dependent proteome changes in the breast epithelium identified heretofore unknown potential therapeutic targets for reducing breast cancer susceptibility.

Changes in Immune Cell Types with Age in Breast are Consistent with a Decline in Immune Surveillance and Increased Immunosuppression

A majority of breast cancers (BC) are age-related and we seek to determine what cellular and molecular changes occur in breast tissue with age that make women more susceptible to cancer initiation. Immune-epithelial cell interactions are important during mammary gland development and the immune system plays an important role in BC progression. The composition of human immune cell populations is known to change in peripheral blood with age and in breast tissue during BC progression. Less is known about changes in immune populations in normal breast tissue and how their interactions with mammary epithelia change with age. We quantified densities of T cells, B cells, and macrophage subsets in pathologically normal breast tissue from 122 different women who ranged in age from 24 to 74 years old. Donor-matched peripheral blood from a subset of 20 donors was analyzed by flow cytometry. Tissue immune cell densities and localizations relative to the epithelium were quantified in situ with machine learning-based image analyses of multiplex immunohistochemistry-stained tissue sections. In situ results were corroborated with flow cytometry analyses of peri-epithelial immune cells from primary breast tissue preparations and transcriptome analyses of public data from bulk tissue reduction mammoplasties. Proportions of immune cell subsets in breast tissue and donor-matched peripheral blood were not correlated. Density (cells/mm²) of T and B lymphocytes in situ decreased with age. T cells and macrophages preferentially localized near or within epithelial bilayers, rather than the intralobular stroma. M2 macrophage density was higher than M1 macrophage density and this difference was due to higher density of M2 in the intralobular stroma. Transcriptional signature analyses suggested age-dependent decline in adaptive immune cell populations and functions and increased innate immune cell activity. T cells and macrophages are so intimately associated with the epithelia that they are embedded within the bilayer, suggesting an important role for immune-epithelial cell interactions. Age-associated decreased T cell density in peri-epithelial regions, and increased M2 macrophage density in intralobular stroma suggests the emergence of a tissue microenvironment that is simultaneously immune-senescent and immunosuppressive with age.

Evidence for accelerated aging in mammary epithelia of women carrying germline BRCA1 or BRCA2 mutations

During aging in the human mammary gland, luminal epithelial cells lose lineage fidelity by expressing markers normally expressed in myoepithelial cells. We hypothesize that loss of lineage fidelity is a general manifestation of epithelia that are susceptible to cancer initiation. In the present study, we show that histologically normal breast tissue from younger women who are susceptible to breast cancer, as a result of harboring a germline mutation in BRCA1, BRCA2 or PALB2 genes, exhibits hallmarks of accelerated aging. These include proportionately increased luminal epithelial cells that acquired myoepithelial markers, decreased proportions of myoepithelial cells and a basal differentiation bias or failure of differentiation of cKit⁺ progenitors. High-risk luminal and myoepithelial cells are transcriptionally enriched for genes of the opposite lineage, inflammatory- and cancer-related pathways. We have identified breast-aging hallmarks that reflect a convergent biology of cancer susceptibility, regardless of the specific underlying genetic or age-dependent risk or the associated breast cancer subtype.

Breast-Specific Molecular Clocks Comprised of ELF5 Expression and Promoter Methylation Identify Individuals Susceptible to Cancer Initiation

A robust breast cancer prevention strategy requires risk assessment biomarkers for early detection. We show that expression of ELF5, a transcription factor critical for normal mammary development, is downregulated in mammary luminal epithelia with age. DNA methylation of the ELF5 promoter is negatively correlated with expression in an age-dependent manner. Both ELF5 methylation and gene expression were used to build biological clocks to estimate chronological ages of mammary epithelia. ELF5 clock-based estimates of biological age in luminal epithelia from average-risk women were within three years of chronological age. Biological ages of breast epithelia from BRCA1 or BRCA2 mutation carriers, who were high risk for developing breast cancer, suggested they were accelerated by two decades relative to chronological age. The ELF5 DNA methylation clock had better performance at predicting biological age in luminal epithelial cells as compared with two other epigenetic clocks based on whole tissues. We propose that the changes in ELF5 expression or ELF5-proximal DNA methylation in luminal epithelia are emergent properties of at-risk breast tissue and constitute breast-specific biological clocks. PREVENTION RELEVANCE: ELF5 expression or DNA methylation level at the ELF5 promoter region can be used as breast-specific biological clocks to identify women at higher than average risk of breast cancer.

Volume-constrained microcontainers enable myoepithelial functional differentiation in highly parallel mammary organoid culture

A long-standing constraint on organoid culture is the need to add exogenous substances to provide hydrogel matrix, which limits the study of fully human or fully native organoids. This paper introduces an approach to culture reconstituted mammary organoids without the impediment of exogenous matrix. We enclose organoids in nanoliter-scale, topologically enclosed, fluid compartments surrounded by agar. Organoids cultured in these “microcontainers” appear to secrete enough extracellular matrix to yield a self-sufficient microenvironment without exogenous supplements. In microcontainers, mammary organoids exhibit contractility and a high-level, physiological, myoepithelial (MEP) behavior that has not been previously reported in reconstituted organoids. The presence of contractility suggests that microcontainers elicit MEP functional differentiation, an important milestone. Microcontainers yield thousands of substantially identical and individually trackable organoids within a single culture vessel, enabling longitudinal studies and statistically powerful experiments, such as the evaluation of small effect sizes. Microcontainers open new doors for researchers who rely on organoid models.

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Microcontainers are volume-constrained microwells with hydrogel lids

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Microcontainers enable statistically robust experimental design with organoids

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Organoids produce their own extracellular matrix within microcontainers

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Myoepithelial cells in mammary organoids achieve fully functional differentiation

Ancestry-associated transcriptomic profiles of breast cancer in patients of African, Arab, and European ancestry

Breast cancer largely dominates the global cancer burden statistics; however, there are striking disparities in mortality rates across countries. While socioeconomic factors contribute to population-based differences in mortality, they do not fully explain disparity among women of African ancestry (AA) and Arab ancestry (ArA) compared to women of European ancestry (EA). In this study, we sought to identify molecular differences that could provide insight into the biology of ancestry-associated disparities in clinical outcomes. We applied a unique approach that combines the use of curated survival data from The Cancer Genome Atlas (TCGA) Pan-Cancer clinical data resource, improved single-nucleotide polymorphism-based inferred ancestry assignment, and a novel breast cancer subtype classification to interrogate the TCGA and a local Arab breast cancer dataset. We observed an enrichment of BasalMyo tumors in AA patients (38 vs 16.5% in EA, p = 1.30E - 10), associated with a significant worse overall (hazard ratio (HR) = 2.39, p = 0.02) and disease-specific survival (HR = 2.57, p = 0.03). Gene set enrichment analysis of BasalMyo AA and EA samples revealed differences in the abundance of T-regulatory and T-helper type 2 cells, and enrichment of cancer-related pathways with prognostic implications (AA: PI3K-Akt-mTOR and ErbB signaling; EA: EGF, estrogen-dependent and DNA repair signaling). Strikingly, AMPK signaling was associated with opposing prognostic connotation (AA: 10-year HR = 2.79, EA: 10-year HR = 0.34). Analysis of ArA patients suggests enrichment of BasalMyo tumors with a trend for differential enrichment of T-regulatory cells and AMPK signaling. Together, our findings suggest that the disparity in the clinical outcome of AA breast cancer patients is likely related to differences in cancer-related and microenvironmental features.

Germline genetic contribution to the immune landscape of cancer

Understanding the contribution of the host's genetic background to cancer immunity may lead to improved stratification for immunotherapy and to the identification of novel therapeutic targets. We investigated the effect of common and rare germline variants on 139 well-defined immune traits in ∼9000 cancer patients enrolled in TCGA. High heritability was observed for estimates of NK cell and T cell subset infiltration and for interferon signaling. Common variants of IFIH1, TMEM173 (STING1), and TMEM108 were associated with differential interferon signaling and variants mapping to RBL1 correlated with T cell subset abundance. Pathogenic or likely pathogenic variants in BRCA1 and in genes involved in telomere stabilization and Wnt-β-catenin also acted as immune modulators. Our findings provide evidence for the impact of germline genetics on the composition and functional orientation of the tumor immune microenvironment. The curated datasets, variants, and genes identified provide a resource toward further understanding of tumor-immune interactions.

Comprehensive Analysis of Genetic Ancestry and Its Molecular Correlates in Cancer

We evaluated ancestry effects on mutation rates, DNA methylation, and mRNA and miRNA expression among 10,678 patients across 33 cancer types from The Cancer Genome Atlas. We demonstrated that cancer subtypes and ancestry-related technical artifacts are important confounders that have been insufficiently accounted for. Once accounted for, ancestry-associated differences spanned all molecular features and hundreds of genes. Biologically significant differences were usually tissue specific but not specific to cancer. However, admixture and pathway analyses suggested some of these differences are causally related to cancer. Specific findings included increased FBXW7 mutations in patients of African origin, decreased VHL and PBRM1 mutations in renal cancer patients of African origin, and decreased immune activity in bladder cancer patients of East Asian origin.

Abstract P1-21-08: Application of machine learning to elucidate the biology predicting response in the I-SPY 2 neoadjuvant breast cancer trial

Background: Machine learning relies on algorithms that learn patterns in large, complex datasets to predict outcomes. The adaptive, neoadjuvant I-SPY 2 TRIAL evaluates novel agents added to standard therapy, and identifies their most responsive subtype. While previously proposed genes/signatures reflecting an agent’s mechanism of action predicted pathologic complete response (pCR) in some treatment arms/subtypes, not all arms had strong predictive biomarkers. We leverage machine learning to explore the limitations of using only known mechanisms of action in predicting pCR, and the extent to which biology outside known drug action improves response prediction in the first 10 arms of the trial.

Methods: Our study involves 986 patients with pre-treatment gene expression and pCR data across 10 treatment arms including inhibitors of HER2: neratinib (N), pertuzumab (P), TDM1/P; AKT (MK-2206; M); IGF1R (ganitumab); HSP90 (ganetespib); PARP/DNA repair (veliparib/carboplatin; VC); ANG1/2 (AMG386); immune checkpoints (pembrolizumab; Pembro); and a shared control arm (Ctr). Each arm/receptor subtype group was evaluated independently for groups with at least 20 patients (n=19), with 25% of data held out as independent test sets. We implemented a 3-fold cross validation technique with 10 repeats using Random Forest ensemble algorithm with recursive feature elimination. In combination with clinical data, a three-pronged feature-selection approach was employed: (1) restricted to mechanism of action genes: AKT/PI3K/HER (m=10 genes), IGF1 (m=11), HSP90 (m=88), DNA repair (m=79), TIE1/2 (m=11), and immune (m=61), as well as HER2 amplicon genes; (2) expanded to include targeted pathways for all 10 agents/combinations plus ESR1 and proliferation genes (m=339); (3) an unbiased whole genome approach (m=17,990). Models were considered predictive if AUROC ≥ 0.75, Sensitivity ≥ 0.6 and Specificity ≥ 0.6 in cross validation and independent test sets.

Results: Table 1 summarizes the results of our analysis (Yes=predictive; NA=no/insufficient data). Prediction of pCR using only genes reflecting the known mechanism of the drug succeeded in 5 subgroups, with DNA repair genes predicting VC response and immune genes predicting Pembro response in HR+HER2- and HR-HER2- subsets, and AKT/PI3K/HER + HER2 amplicon genes predicting (P) response in HR+HER2+ patients. Expansion of the feature set to include genes associated with all mechanisms of action of all drugs proved sufficient to produce good predictive models in 8 of 19 subgroups. Examples include DNA repair + immune genes predicting response to ganitumab in HR+HER2- and to (N) in HR+HER2+. An unbiased approach using all data yielded predictive power in 8 of 19 subgroups, including 5 with no predictive models from the first two approaches. Examples include HR-HER2- (N) predictors enriched for metabolic, cell division and membrane protein proteolytic processes; HR+HER2+ TDM1/P enriched for metabolic, stress response and cell cycle processes; and HR-HER2- MK-2206 predictors containing Ser/Thr kinases. In total, we identify predictive biomarkers in 14 of 19 subgroups across the three feature selection approaches.

Conclusion: Our results suggests that hypothesis driven analysis restricted to assumed mechanisms of action of the experimental agents may be insufficient, and that exploration of possible off target effects may be needed to understand the underlying biology of response or resistance.

Table 1. Model results across feature selection approachesHR+HER2-HR-HER2-HR+HER2+HR-HER2+Number of PatientsMechanism of ActionAll Mechanisms of ActionUnbiasedNumber of PatientsMechanism of ActionAll Mechanisms of ActionUnbiasedNumber of PatientsMechanism of ActionAll Mechanisms of ActionUnbiasedNumber of PatientsMechanism of ActionAll Mechanisms of ActionUnbiasedneratinib (pan anti-HER)NA32NoNoYes42NoYesYes23NoNoYespertuzumab (anti-HER2)NANA29YesYesNoNATDM1/Pertuzumab (anti-HER2)NANA35NoNoYesNAMK−2206 (AKT inhibitor)28NoNoNo32NoNoYesNANAganitumab (IGFR inhibitor)58NoYesNo48NoNoNoNANAganetespib (HSP90 inhibitor)48NoYesYes45NoNoNoNANAvelirapib/carboplatin (PARP inhibitor/DNA damage)33YesYesNo39YesYesNoNANAAMG386 (ANG1/2 inhibitor)62NoYesYes53NoNoNoNANApembrolizumab (immune checkpoint inhibitor)38YesYesNo29YesNoNoNANAHER2+ controlNANANANAHER2- control94NoNoYes84NoNoNoNANA

Citation Format: Rosalyn W. Sayaman, Denise M. Wolf, Christina Yau, Julie Wulfkuhle, Emanuel Petricoin, Lamorna Brown-Swigart, Smita M. Asare, Gillian L. Hirst, Laura Sit, Nicholas O'Grady, Diane Hedistian, I-SPY 2 TRIAL Consortium, Laura J. Esserman, Mark A. LaBarge, Laura J van 't Veer. Application of machine learning to elucidate the biology predicting response in the I-SPY 2 neoadjuvant breast cancer trial [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P1-21-08.

Genetic Variation in CCL5 Signaling Genes and Triple Negative Breast Cancer: Susceptibility and Prognosis Implications

Triple-negative breast cancer (TNBC) accounts for ~15–20% of breast cancer (BC) and has a higher rate of early relapse and mortality compared to other subtypes. The Chemokine (C-C motif) ligand 5 (CCL5) and its signaling pathway have been linked to TNBC. We aimed to investigate the susceptibility and prognostic implications of genetic variation in CCL5 signaling genes in TNBC in the present study. We characterized variants in CCL5 and that of six other CCL5 signaling genes (CCND1, ZMIZ1, CASP8, NOTCH2, MAP3K21, and HS6ST3) among 1,082 unrelated Tunisian subjects (544 BC patients, including 196 TNBC, and 538 healthy controls), assessed the association of the variants with BC-specific overall survival (OVS) and progression-free survival (PFS), and correlated CCL5 mRNA and serum levels with CCL5 genotypes. We found a highly significant association between the CCND1 rs614367-TT genotype (OR = 5.14; P = 0.004) and TNBC risk, and identified a significant association between the rs614367-T allele and decreased PFS in TNBC. A decreased risk of lymph node metastasis was associated with the MAP3K21 rs1294255-C allele, particularly in rs1294255-GC (OR = 0.47; P = 0.001). CCL5 variants (rs2107538 and rs2280789) were linked to CCL5 serum and mRNA levels. In the TCGA TNBC/Basal-like cohort the MAP3K21 rs1294255-G allele was associated with a decreased OVS. High expression of CCL5 in breast tumors was significantly associated with an increased OVS in all BC patients, but particularly in TNBC/Basal-like patients. In conclusion, genetic variation in CCL5 signaling genes may predict not only TNBC risk but also disease aggressiveness.

Tissue aging: the integration of collective and variant responses of cells to entropic forces over time

Aging is driven by unavoidable entropic forces, physicochemical in nature, that damage the raw materials that constitute biological systems. Single cells experience and respond to stochastic physicochemical insults that occur either to the cells themselves or to their microenvironment, in a dynamic and reciprocal manner, leading to increased age-related cell-to-cell variation. We will discuss the biological mechanisms that integrate cell-to-cell variation across tissues resulting in stereotypical phenotypes of age.

Abstract A54: A cellular and molecular atlas of the human breast for dissecting mechanisms of cell and tissue function

A fundamental question in biology, central to our understanding of cancer, is determining how cells coordinate and cooperate to form and maintain tissues. Developing systems-wide knowledge of the numerous cell interactions within a tissue requires robust identification of the cell types it comprises. It demands comprehensive information about each of these cell types, including the genes they express and proteins they make. Unfortunately, the cellular composition and arrangement of cells in many complex tissue systems has yet to be fully resolved, and this includes the breast. This has resulted in a crucial knowledge gap where we know very little about the elaborate biology of how different normal cell types interact, and the consequences these interactions have on each other and the tissue as a whole. Using immunofluorescence and advanced flow cytometry, we have recently developed methods to resolve and isolate every known cell type in the normal human breast. This includes several different luminal and epithelial fractions, myoepithelial cells, adipocytes, leukocytes, pericytes, erythrocytes, adipose-derived mesenchymal stem cells, vascular smooth muscle cells, and both lymphatic and vascular endothelial cells—12 different types in all. Successful modification of this multiparameter FACS procedure allowed purification of enough cells and RNA to perform next-generation sequencing (NGS) from even the rarest of populations at high depth. Here, we present global transcriptome analysis of these different cell types. These data have clarified cell-type differences and revealed new insights, including the identification of genes and gene families contributing to the unique phenotype of each cell type and the delineation of lineage-specific marker expression. Our analysis has also exposed how the cell types each contribute to their individual microenvironments through production of extracellular matrix proteins and other secreted factors. Moreover, identification of cognate ligand and receptor pairs expressed by these cells has unveiled an elaborate paracrine and autocrine signaling network that has implications towards interpreting the biologic interactome underlying tissue homeostasis. Future studies are aimed at establishing coculture models and determining the biochemical processes essential for cell-coordination and tissue maintenance, and developing knowledge of how these processes go awry in breast cancer.

Citation Format: Rosalyn W. Sayaman, Ambrose Carr, Kate Thi, Zhenmao Wan, Dana Pe’er, Mina J. Bissell, Curt Hines. A cellular and molecular atlas of the human breast for dissecting mechanisms of cell and tissue function [abstract]. In: Proceedings of the AACR Special Conference: Advances in Breast Cancer Research; 2017 Oct 7-10; Hollywood, CA. Philadelphia (PA): AACR; Mol Cancer Res 2018;16(8_Suppl):Abstract nr A54.