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Breast cancers in humans belong to one of several intrinsic molecular subtypes each with different tumor biology and different clinical impact. Mammary gland tumors in dogs are proposed as a relevant comparative model for human breast cancer; however, it is still unclear whether the intrinsic molecular subtypes have the same significance in dogs and humans. Using publicly available data, we analyzed gene expression and whole-exome sequencing data from 158 canine mammary gland tumors. We performed molecular subtyping using the PAM50 method followed by subtype-specific comparisons of gene expression characteristics, mutation patterns and copy number profiles between canine tumors and human breast tumors from The Cancer Genome Atlas (TCGA) breast cancer cohort (n = 1097). We found that luminal A canine tumors greatly resemble luminal A human tumors both in gene expression characteristics, mutations and copy number profiles. Also, the basal-like canine and human tumors were relatively similar, with low expression of luminal epithelial markers and high expression of genes involved in cell proliferation. There were, however, distinct differences in immune-related gene expression patterns in basal-like tumors between the two species. Characteristic HER2-enriched and luminal B subtypes were not present in the canine cohort, and we found no tumors with high-level ERBB2 amplifications. Benign and malignant canine tumors displayed similar PAM50 subtype characteristics. Our findings indicate that deeper understanding of the different molecular subtypes in canine mammary gland tumors will further improve the value of canines as comparative models for human breast cancer.

Systematically investigating the scores of genes mutated in cancer and discerning disease drivers from inconsequential bystanders is a prerequisite for precision medicine but remains challenging. Here, we developed a somatic CRISPR/Cas9 mutagenesis screen to study 215 recurrent “long-tail” breast cancer genes, which revealed epigenetic regulation as a major tumor-suppressive mechanism. We report that components of the BAP1 and COMPASS-like complexes, including KMT2C/D, KDM6A, BAP1, and ASXL1/2 (“EpiDrivers”), cooperate with PIK3CAH1047R to transform mouse and human breast epithelial cells. Mechanistically, we find that activation of PIK3CAH1047R and concomitant EpiDriver loss triggered an alveolar-like lineage conversion of basal mammary epithelial cells and accelerated formation of luminal-like tumors, suggesting a basal origin for luminal tumors. EpiDriver mutations are found in ∼39% of human breast cancers, and ∼50% of ductal carcinoma in situ express casein, suggesting that lineage infidelity and alveogenic mimicry may significantly contribute to early steps of breast cancer etiology.Significance:Infrequently mutated genes comprise most of the mutational burden in breast tumors but are poorly understood. In vivo CRISPR screening identified functional tumor suppressors that converged on epigenetic regulation. Loss of epigenetic regulators accelerated tumorigenesis and revealed lineage infidelity and aberrant expression of alveogenesis genes as potential early events in tumorigenesis.This article is highlighted in the In This Issue feature, p. 2711

Supplementary Data from Loss of Epigenetic Regulation Disrupts Lineage Integrity, Induces Aberrant Alveogenesis, and Promotes Breast Cancer

Supplementary Table 1: Distribution of clinico-pathological parameters among 112 patients included in the validation set. Supplementary Table 2: Assays and primers used for testing gene profile. Supplementary Table 3: Distribution of clinico-pathological parameters among 146 patients of the training set. Supplementary Table 4: Characteristics of patients included in and excluded from the technical transfer of the DBCG-RT profile to RT-qPCR and formalin fixed, paraffin embedded tissue (FFPE). Supplementary Table 5: Distribution of patients with "High LRR risk" and "Low LRR risk" within subgroups of clinical relevance for administration of PMRT.

Supplementary Table S1 from Gene expression profiles do not consistently predict the clinical treatment response in locally advanced breast cancer

Purpose: To identify genes predicting benefit of radiotherapy in patients with high-risk breast cancer treated with systemic therapy and randomized to receive or not receive postmastectomy radiotherapy (PMRT).Experimental Design: The study was based on the Danish Breast Cancer Cooperative Group (DBCG82bc) cohort. Gene-expression analysis was performed in a training set of frozen tumor tissue from 191 patients. Genes were identified through the Lasso method with the endpoint being locoregional recurrence (LRR). A weighted gene-expression index (DBCG-RT profile) was calculated and transferred to quantitative real-time PCR (qRT-PCR) in corresponding formalin-fixed, paraffin-embedded (FFPE) samples, before validation in FFPE from 112 additional patients.Results: Seven genes were identified, and the derived DBCG-RT profile divided the 191 patients into “high LRR risk” and “low LRR risk” groups. PMRT significantly reduced risk of LRR in “high LRR risk” patients, whereas “low LRR risk” patients showed no additional reduction in LRR rate. Technical transfer of the DBCG-RT profile to FFPE/qRT-PCR was successful, and the predictive impact was successfully validated in another 112 patients.Conclusions: A DBCG-RT gene profile was identified and validated, identifying patients with very low risk of LRR and no benefit from PMRT. The profile may provide a method to individualize treatment with PMRT. Clin Cancer Res; 20(20); 5272–80. ©2014 AACR.

Supplementary Information from Gene expression profiles do not consistently predict the clinical treatment response in locally advanced breast cancer

Development of the DBCG-RT profile including description of Lasso method, selection of genes, and definition of index cut-off.

Cumulative incidence plots showing "High LRR risk" patients of the training set stratified according to PMRT and tumorsize (A), lymph node positive status (B), ER status (C) and combinations of tumorsize and nodal status (D), respectively.

Transfer of DBCG-RT profile to RT-qPCR on formalin-fixed, paraffin-embedded material.

Flowchart of patients included in the training set.

Neoadjuvant treatment offers an opportunity to correlate molecular variables to treatment response and to explore mechanisms of drug resistance in vivo. Here, we present a statistical analysis of large-scale gene expression patterns and their relationship to response following neoadjuvant chemotherapy in locally advanced breast cancers. We analyzed cDNA expression data from 81 tumors from two patient series, one treated with doxorubicin alone (51) and the other treated with 5-fluorouracil and mitomycin (30), and both were previously studied for correlations between TP53 status and response to therapy. We observed a low frequency of progressive disease within the luminal A subtype from both series (2 of 36 versus 13 of 45 patients; P = 0.0089) and a high frequency of progressive disease among patients with luminal B type tumors treated with doxorubicin (5 of 8 patients; P = 0.0078); however, aside from these two observations, no other consistent associations between response to chemotherapy and tumor subtype were observed. These specific associations could possibly be explained by covariance with TP53 mutation status, which also correlated with tumor subtype. Using supervised analysis, we could not uncover a gene profile that could reliably (>70% accuracy and specificity) predict response to either treatment regimen. [Mol Cancer Ther 2006;5(11):2914–8]

Recent microarray studies have identified distinct subtypes of breast tumors that arise from different cell types and that show statistically significant differences in patient outcome. To gain insight into these differences, we identified in vitro and in vivo changes in gene expression induced by chemotherapeutics. We treated two cell lines derived from basal epithelium (immortalized human mammary epithelial cells) and two lines derived from luminal epithelium (MCF-7 and ZR-75–1) with chemotherapeutics used in the treatment of breast cancer and assayed for changes in gene expression using DNA microarrays. Treatment doses for doxorubicin and 5-fluorouracil were selected to cause comparable cytotoxicity across all four cell lines. The dominant expression response in each of the cell lines was a general stress response; however, distinct expression patterns were observed. Both cell types induced DNA damage-response genes such as p21waf1, but the response in the luminal cells showed higher fold changes and included more p53-regulated genes. Luminal cell lines repressed a large number of cell cycle-regulated genes and other genes involved in cellular proliferation, whereas the basal cell lines did not. Instead, the basal cell lines repressed genes that were involved in differentiation. These in vitro responses were compared with expression responses in breast tumors sampled before and after treatment with doxorubicin or 5-fluorouracil/mitomycin C. The in vivo data corroborated the cell-type-specific responses to chemotherapeutics observed in vitro, including the induction of p21waf1. Similarities between in vivo and in vitro responses help to identify important response mechanisms to chemotherapeutics.

Supplementary Figures 2 from Cell-Type-Specific Responses to Chemotherapeutics in Breast Cancer

Supplementary Figures 1 from Cell-Type-Specific Responses to Chemotherapeutics in Breast Cancer

Supplementary Legends/Tables from Cell-Type-Specific Responses to Chemotherapeutics in Breast Cancer

How mixtures of immune cells associate with cancer cell phenotype and affect pathogenesis is still unclear. In 15 breast cancer gene expression datasets, we invariably identify three clusters of patients with gradual levels of immune infiltration. The intermediate immune infiltration cluster (Cluster B) is associated with a worse prognosis independently of known clinicopathological features. Furthermore, immune clusters are associated with response to neoadjuvant chemotherapy. In silico dissection of the immune contexture of the clusters identified Cluster A as immune cold, Cluster C as immune hot while Cluster B has a pro-tumorigenic immune infiltration. Through phenotypical analysis, we find epithelial mesenchymal transition and proliferation associated with the immune clusters and mutually exclusive in breast cancers. Here, we describe immune clusters which improve the prognostic accuracy of immune contexture in breast cancer. Our discovery of a novel independent prognostic factor in breast cancer highlights a correlation between tumor phenotype and immune contexture., In breast cancer, the immune infiltration of the tumour associates with clinical outcome. Here, the authors infer immune context based on gene expression data and identify a new independent subtype linked to pro-tumorigenic immune infiltration.

The large heterogeneity of DCIS complicates the identification of markers for risk of progression to invasive breast cancer. Molecular and cellular heterogeneity is observed across DCIS, between multiple foci of DCIS within a lesion and within mixed lesions of invasive tumors with DCIS foci. The intrinsic breast cancer subtypes represent fundamental biological properties of the disease and are also found at the DCIS stage. However, their frequency and relevance as prognostic markers in pre-invasive stage is still not clear. Novel technologies for spatial characterization of tumors allow detailed mapping of DCIS and the microenvironment and may give us clues to which DCIS have the propensity to invade surrounding stroma. In the presentation, we will discuss results from our ongoing genomic characterization of DCIS and invasive breast carcinomas that illustrate the need for stratification when searching for prognostic markers. We have found disproportionate distribution and characteristics of the intrinsic subtypes in DCIS compared with invasive breast cancer and the dominance of Luminal A and HER2 subtypes. Bona-fide basal-like tumors may rarely be found at the DCIS stage and HER2-enriched DCIS are associated with specific immune cell profiles. Citation Format: Therese Sørlie. Molecular subtypes and spatial heterogeneity in DCIS [abstract]. In: Proceedings of the AACR Special Conference on Rethinking DCIS: An Opportunity for Prevention?; 2022 Sep 8-11; Philadelphia, PA. Philadelphia (PA): AACR; Can Prev Res 2022;15(12 Suppl_1): Abstract nr IA030.

Aberrant DNA methylation is an early event in breast carcinogenesis and plays a critical role in regulating gene expression. Here, we perform genome-wide expression-methylation Quantitative Trait Loci (emQTL) analysis through the integration of DNA methylation and gene expression to identify disease-driving pathways under epigenetic control. By grouping the emQTLs using biclustering we identify associations representing important biological processes associated with breast cancer pathogenesis including regulation of proliferation and tumor-infiltrating fibroblasts. We report genome-wide loss of enhancer methylation at binding sites of proliferation-driving transcription factors including CEBP-β, FOSL1, and FOSL2 with concomitant high expression of proliferation-related genes in aggressive breast tumors as we confirm with scRNA-seq. The identified emQTL-CpGs and genes were found connected through chromatin loops, indicating that proliferation in breast tumors is under epigenetic regulation by DNA methylation. Interestingly, the associations between enhancer methylation and proliferation-related gene expression were also observed within known subtypes of breast cancer, suggesting a common role of epigenetic regulation of proliferation. Taken together, we show that proliferation in breast cancer is linked to loss of methylation at specific enhancers and transcription factor binding and gene activation through chromatin looping.

Simple Summary In breast cancer, there is a high degree of variability in tumors and the surrounding tissue called the tumor microenvironment (TME). To better understand tumor biology and metastasis, as well as to predict response to cancer treatments or the course of the disease, it is important to characterize molecular diversity in the breast TME. The GeoMx Digital Spatial Profiler (DSP) enables researchers to spatially analyze proteins and RNA transcripts in tumors and surrounding tissues from patients or preclinical models. Using the GeoMx DSP, protein expression and RNA transcripts in the distinct regions of a tumor can be quantified up to and including the whole transcriptome level. Herein, the GeoMx Breast Cancer Consortium presents best practices for GeoMx spatial profiling of tumors to promote the collection of high-quality data, optimization of data analysis and integration of datasets to accelerate biomarker discovery. These best practices can also be applied to any tumor type to provide information about the tumor and the TME. Abstract Breast cancer is a heterogenous disease with variability in tumor cells and in the surrounding tumor microenvironment (TME). Understanding the molecular diversity in breast cancer is critical for improving prediction of therapeutic response and prognostication. High-plex spatial profiling of tumors enables characterization of heterogeneity in the breast TME, which can holistically illuminate the biology of tumor growth, dissemination and, ultimately, response to therapy. The GeoMx Digital Spatial Profiler (DSP) enables researchers to spatially resolve and quantify proteins and RNA transcripts from tissue sections. The platform is compatible with both formalin-fixed paraffin-embedded and frozen tissues. RNA profiling was developed at the whole transcriptome level for human and mouse samples and protein profiling of 100-plex for human samples. Tissue can be optically segmented for analysis of regions of interest or cell populations to study biology-directed tissue characterization. The GeoMx Breast Cancer Consortium (GBCC) is composed of breast cancer researchers who are developing innovative approaches for spatial profiling to accelerate biomarker discovery. Here, the GBCC presents best practices for GeoMx profiling to promote the collection of high-quality data, optimization of data analysis and integration of datasets to advance collaboration and meta-analyses. Although the capabilities of the platform are presented in the context of breast cancer research, they can be generalized to a variety of other tumor types that are characterized by high heterogeneity.

Long non-coding RNAs (lncRNAs) are involved in breast cancer pathogenesis through chromatin remodeling, transcriptional and post-transcriptional gene regulation. We report robust associations between lncRNA expression and breast cancer clinicopathological features in two population-based cohorts: SCAN-B and TCGA. Using co-expression analysis of lncRNAs with protein coding genes, we discovered three distinct clusters of lncRNAs. In silico cell type deconvolution coupled with single-cell RNA-seq analyses revealed that these three clusters were driven by cell type specific expression of lncRNAs. In one cluster lncRNAs were expressed by cancer cells and were mostly associated with the estrogen signaling pathways. In the two other clusters, lncRNAs were expressed either by immune cells or fibroblasts of the tumor microenvironment. To further investigate the cis-regulatory regions driving lncRNA expression in breast cancer, we identified subtype-specific transcription factor (TF) occupancy at lncRNA promoters. We also integrated lncRNA expression with DNA methylation data to identify long-range regulatory regions for lncRNA which were validated using ChiA-Pet-Pol2 loops. lncRNAs play an important role in shaping the gene regulatory landscape in breast cancer. We provide a detailed subtype and cell type-specific expression of lncRNA, which improves the understanding of underlying transcriptional regulation in breast cancer.

Systematically investigating the scores of genes mutated in cancer and discerning disease drivers from inconsequential bystanders is a prerequisite for precision medicine but remains challenging. Here, we developed a somatic CRISPR/Cas9 mutagenesis screen to study 215 recurrent “long-tail” breast cancer genes, which revealed epigenetic regulation as a major tumor-suppressive mechanism. We report that components of the BAP1 and COMPASS-like complexes, including KMT2C/D, KDM6A, BAP1, and ASXL1/2 (“EpiDrivers”), cooperate with PIK3CAH1047R to transform mouse and human breast epithelial cells. Mechanistically, we find that activation of PIK3CAH1047R and concomitant EpiDriver loss triggered an alveolar-like lineage conversion of basal mammary epithelial cells and accelerated formation of luminal-like tumors, suggesting a basal origin for luminal tumors. EpiDriver mutations are found in ∼39% of human breast cancers, and ∼50% of ductal carcinoma in situ express casein, suggesting that lineage infidelity and alveogenic mimicry may significantly contribute to early steps of breast cancer etiology. Significance: Infrequently mutated genes comprise most of the mutational burden in breast tumors but are poorly understood. In vivo CRISPR screening identified functional tumor suppressors that converged on epigenetic regulation. Loss of epigenetic regulators accelerated tumorigenesis and revealed lineage infidelity and aberrant expression of alveogenesis genes as potential early events in tumorigenesis. This article is highlighted in the In This Issue feature, p. 2711

Physical inactivity, high postmenopausal body mass index, alcohol consumption and use of menopausal hormone therapy are established risk factors for breast cancer. Less is known about whether these factors influence the risk of progression of benign and premalignant breast lesions to invasive breast cancer. This registry-based cohort study was based on women with a precancerous lesion who were followed for breast cancer. The cohort consisted of 11 270 women with a benign lesion, 972 women with hyperplasia with atypia and 2379 women with carcinoma in situ diagnosed and treated after participation in BreastScreen Norway, 2006-2016. Information on breast cancer risk factors was collected by a questionnaire administered with the invitation letter. Cox regression analysis was used to estimate the association between breast cancer and physical activity, body mass index, alcohol consumption, tobacco smoking and menopausal hormone therapy, adjusted for age. During follow-up, 274 women with a benign lesion, 34 women with hyperplasia with atypia and 118 women with carcinoma in situ were diagnosed with invasive breast cancer. We observed an increased risk of breast cancer associated with use of menopausal hormone therapy for women with a benign or premalignant lesion. Alcohol consumption and tobacco smoking showed suggestive increased risk of breast cancer among women with a benign lesion. We were only to a limited degree able to identify associations between modifiable risk factors of breast cancer and the disease among women with a precancerous lesion, and a larger study is needed to confirm or refute associations. The work was funded by The Norwegian Cancer Society (grant no. 5746604).

Background Ductal carcinoma in situ (DCIS) comprises a diverse group of preinvasive lesions in the breast and poses a considerable clinical challenge due to lack of markers of progression. Genomic alterations are to a large extent similar in DCIS and invasive carcinomas, although differences in copy number aberrations, gene expression patterns, and mutations exist. In mixed tumors with synchronous invasive breast cancer (IBC) and DCIS, it is still unclear to what extent invasive tumor cells are directly derived from the DCIS cells. Aim Our aim was to compare cancer‐relevant mutation profiles of different cellular compartments in mixed DCIS/IBC and pure DCIS tumors. Methods and results We performed targeted sequencing of 50 oncogenes in microdissected tissue from three different epithelial cell compartments (in situ, invasive, and normal adjacent epithelium) from 26 mixed breast carcinomas. In total, 44 tissue samples (19 invasive, 16 in situ, 9 normal) were subjected to sequencing using the Ion Torrent platform and the AmpliSeq Cancer Hotspot Panel v2. For comparison, 10 additional, pure DCIS lesions were sequenced. Across all mixed samples, we detected 23 variants previously described in cancer. The most commonly affected genes were TP53, PIK3CA, and ERBB2. The PIK3CA:p.H1047R variant was found in nine samples from six patients. Most variants detected in invasive compartments were also found in the corresponding in situ cell compartment indicating a clonal relationship between the tumor stages. A lower frequency of variants were observed in pure DCIS lesions. Conclusion Similar mutation profiles between in situ and invasive cell compartments indicate a similar origin of the two tumor stages in mixed breast tumors. The lower number of potential driver variants found in pure DCIS compared with the in situ cell compartments of mixed tumors may imply that pure DCIS is captured earlier in the path of progression to invasive disease.

Cancer transcriptomes are shaped by genetic and epigenetic features, such as DNA methylation and copy number aberrations. Knowledge of the relationships between gene expression and such features is fundamental to understanding the basis of tumor phenotypes. Here, we present a pan-cancer atlas of transcriptional dependence on DNA methylation and copy number aberrations (PANORAMA). Our analyses suggest that copy number alterations are a central driver of inter-tumor heterogeneity, while the majority of expression-methylation associations found in cancer are a reflection of cell-of-origin and normal cell admixture. The atlas is made available through an online tool at https://pancancer.app.

Summary The receptor tyrosine kinase AXL is associated with epithelial plasticity in several solid tumors including breast cancer and AXL-targeting agents are currently in clinical trials. We hypothesized that AXL is a driver of stemness traits in cancer by co-option of a regulatory function normally reserved for stem cells. AXL-expressing cells in human mammary epithelial ducts co-expressed markers associated with multipotency, and AXL inhibition abolished colony formation and self-maintenance activities while promoting terminal differentiation in vitro. Axl-null mice did not exhibit a strong developmental phenotype, but enrichment of Axl+ cells was required for mouse mammary gland reconstitution upon transplantation, and Axl-null mice had reduced incidence of Wnt1-driven mammary tumors. An AXL-dependent gene signature is a feature of transcriptomes in basal breast cancers and reduced patient survival irrespective of subtype. Our interpretation is that AXL regulates access to epithelial plasticity programs in MaSCs and, when co-opted, maintains acquired stemness in breast cancer cells., Graphical Abstract, Highlights • AXL + mammary epithelial cells have multipotent activity conserved in women and mice • AXL allows accesses to epithelial-to-mesenchymal transition genes and prevents differentiation into luminal cells • Deletion of Axl reduced incidence of Wnt1-driven tumors in mice • Provides a rationale explaining the advantage to cancer cells that co-opt AXL signaling, Cell Biology; Stem Cells Research; Cancer

The long non-coding RNA NEAT1 locus is transcribed into two overlapping isoforms, NEAT1_1 and NEAT1_2, of which the latter is essential for the assembly of nuclear paraspeckles. NEAT1 is abnormally expressed in a wide variety of human cancers. Emerging evidence suggests that the two isoforms have distinct functions in gene expression regulation, and recently it was shown that NEAT1_2, but not NEAT1_1, expression predicts poor clinical outcome in cancer. Here, we report that NEAT1_2 expression correlates with HER2-positive breast cancers and high-grade disease. We provide evidence that NEAT1_1 and NEAT1_2 have distinct expression pattern among different intrinsic breast cancer subtypes. Finally, we show that NEAT1_2 expression and paraspeckle formation increase upon lactation in humans, confirming what has previously been demonstrated in mice. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

Ductal carcinoma in situ (DCIS) is a non-invasive type of breast cancer with highly variable potential of becoming invasive and affecting mortality. Currently, many patients with DCIS are overtreated due to the lack of specific biomarkers that distinguish low risk lesions from those with a higher risk of progression. In this study, we analyzed 57 pure DCIS and 313 invasive breast cancers (IBC) from different patients. Three levels of genomic data were obtained; gene expression, DNA methylation, and DNA copy number. We performed subtype stratified analyses and identified key differences between DCIS and IBC that suggest subtype specific progression. Prominent differences were found in tumors of the basal-like subtype: Basal-like DCIS were less proliferative and showed a higher degree of differentiation than basal-like IBC. Also, core basal tumors (characterized by high correlation to the basal-like centroid) were not identified amongst DCIS as opposed to IBC. At the copy number level, basal-like DCIS exhibited fewer copy number aberrations compared with basal-like IBC. An intriguing finding through analysis of the methylome was hypermethylation of multiple protocadherin genes in basal-like IBC compared with basal-like DCIS and normal tissue, possibly caused by long range epigenetic silencing. This points to silencing of cell adhesion-related genes specifically in IBC of the basal-like subtype. Our work confirms that subtype stratification is essential when studying progression from DCIS to IBC, and we provide evidence that basal-like DCIS show less aggressive characteristics and question the assumption that basal-like DCIS is a direct precursor of basal-like invasive breast cancer.

Simple Summary The PAM50 risk of recurrence (ROR) score is predictive of the risk of distant recurrence and the benefits of adjuvant therapy in early breast cancer. The Prosigna assay utilizes RNA from tumor cells selected via macrodissection of formalin-fixed, paraffin-embedded (FFPE) tissue sections to measure the activity of the PAM50 genes. An alternative and widely used extraction method is RNA purification from fresh-frozen (FF) bulk tissue without enriching the tumor cellularity. However, the impact of the RNA preparation approach on ROR scores and subsequent treatment selection has not been systematically evaluated. We compared the different approaches and found high correlation between risk of recurrence scores estimated from macrodissected FFPE tissue and scores estimated from bulk FF tumor tissue. However, important discrepancies were revealed for luminal tumors, which may have consequences for treatment recommendations for these patients. Abstract The PAM50 gene expression subtypes and the associated risk of recurrence (ROR) score are used to predict the risk of recurrence and the benefits of adjuvant therapy in early-stage breast cancer. The Prosigna assay includes the PAM50 subtypes along with their clinicopathological features, and is approved for treatment recommendations for adjuvant hormonal therapy and chemotherapy in hormone-receptor-positive early breast cancer. The Prosigna test utilizes RNA extracted from macrodissected tumor cells obtained from formalin-fixed, paraffin-embedded (FFPE) tissue sections. However, RNA extracted from fresh-frozen (FF) bulk tissue without macrodissection is widely used for research purposes, and yields high-quality RNA for downstream analyses. To investigate the impact of the sample preparation approach on ROR scores, we analyzed 94 breast carcinomas included in an observational study that had available gene expression data from macrodissected FFPE tissue and FF bulk tumor tissue, along with the clinically approved Prosigna scores for the node-negative, hormone-receptor-positive, HER2-negative cases (n = 54). ROR scores were calculated in R; the resulting two sets of scores from FFPE and FF samples were compared, and treatment recommendations were evaluated. Overall, ROR scores calculated based on the macrodissected FFPE tissue were consistent with the Prosigna scores. However, analyses from bulk tissue yielded a higher proportion of cases classified as normal-like; these were samples with relatively low tumor cellularity, leading to lower ROR scores. When comparing ROR scores (low, intermediate, and high), discordant cases between the two preparation approaches were revealed among the luminal tumors; the recommended treatment would have changed in a minority of cases.

To investigate immune escape during breast tumor progression, we analyzed the composition of leukocytes in normal breast tissues, ductal carcinoma in situ (DCIS), and invasive ductal carcinomas (IDC). We found significant tissue and tumor subtype-specific differences in multiple cell types including T cells and neutrophils. Gene expression profiling of CD45+CD3+ T cells demonstrated a decrease in CD8+ signatures in IDCs. Immunofluorescence analysis showed fewer activated GZMB+CD8+ T cells in IDC than in DCIS, including in matched DCIS and recurrent IDC. T-cell receptor clonotype diversity was significantly higher in DCIS than in IDCs. Immune checkpoint protein TIGIT-expressing T cells were more frequent in DCIS, whereas high PD-L1 expression and amplification of CD274 (encoding PD-L1) was only detected in triple-negative IDCs. Coamplification of a 17q12 chemokine cluster with ERBB2 subdivided HER2+ breast tumors into immunologically and clinically distinct subtypes. Our results show coevolution of cancer cells and the immune microenvironment during tumor progression. Significance: The design of effective cancer immunotherapies requires the understanding of mechanisms underlying immune escape during tumor progression. Here we demonstrate a switch to a less active tumor immune environment during the in situ to invasive breast carcinoma transition, and identify immune regulators and genomic alterations that shape tumor evolution. Cancer Discov; 7(10); 1098–115. ©2017 AACR. See related commentary by Speiser and Verdeil, p. 1062. This article is highlighted in the In This Issue feature, p. 1047

Background Molecular profiling has recently been included in recommendations for decisions on adjuvant treatment in breast cancer (BrCa). However, the use of molecular profiling has not yet been widely established in all countries. Additional studies may give important information about the clinical relevance of the tests. Aims The study aims to discover the long term prognostic impact of PAM50 and PAM50 ROR score on survival for early BrCa pts according to treatment, with comparison to the routine clinical and histopathological parameters. Patients and methods Unselected early BrCa pts (n=651) from the Oslo Micromet project (n=920) having available FFPE primary tumor tissue were included in the current study. The pts were enrolled from 1995-1998. Follow up status is available for distant disease (median FU 7 years) and BrCa death (16.0-19.7 years after study inclusion). Clinical and histopathological parameters have been collected from the hospital records. FFPE tissue sections were macrodissected, RNA isolated from the dissected tumor tissue, followed by analysis of the PAM50 gene list on the Nanostring Platform. The samples were run in research mode and the raw data was sent to Nanostring (Seattle) for determination of the PAM50 subtype and ROR score. Results Of the 651 included pts, 323 did not receive any adjuvant systemic treatment (pT1pN0 patients), 161 tamoxifen only, the rest chemotherapy+/-tamoxifen. Twelve preoperatively treated pts were excluded from the analyses. Of the 639 remaining pts, PAM50 molecular profiling defined 52.3% as LumA, 26.8% LumB, 10.6% HER2enriched and 10.3% Basal. Multivariate analysis showed that the PAM50 intrinsic subtypes yielded prognostic information in addition to the established clinicopathological variables (pT, Grade, pN, age HR/HER2 subgroups, systemic treatment)(BCSS: HazardR vs LumA: 2.7 (95% CI 1.7-4.1) for LumB, 3.5 (1.8-6.8) for HER2enriched, 1.8 (0.8-4.2) for Basal). For the HR+HER2- pts, the risk classification by ROR score was an independent prognostic factor (BCSS: HazardR vs low risk: 3.1 (1.2-8.1) for intermediate, 6.6 (2.5-17.1) for high risk). In univariate analysis, the PAM50 intrinsic subtype classification separated clinical outcome both for all pts, for no adjuvant treated pts (both p Conclusions PAM50 subtype classification and ROR score improves classification of BrCa pts into prognostic groups, allowing more precise identification of future recurrence risk and improved basis for adjuvant treatment decisions. Citation Format: Naume B, Borgen E, Falk RS, Ohnstad HO, Lien TG, Aaserud M, Sveli MAT, Kyte JA, Kristensen V, Geitvik G, Schlichting E, Wist E, Sørlie T, Russnes H. Establishment of molecular profiling for individual treatment decisions in early breast cancer – Clinical impact of PAM50 and PAM50 risk of recurrence score after more than 16 years follow up [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P2-05-16.

Increased expression of GLI1, the main Hedgehog signalling pathway effector, is related to unfavourable prognosis and progressive disease of certain breast cancer subtypes. We used conditional transgenic mice induced to overexpress GLI1 in the mammary epithelium either alone or in combination with deletion of one Trp53 allele to address the role of elevated GLI1 expression in breast tumour initiation and progression. Induced GLI1 expression facilitates mammary gland tumour formation and this was further increased upon heterozygous deletion of Trp53. The GLI1-induced primary tumours were of different murine molecular subtypes, including Normal-likeEx , Class8Ex , Claudin-LowEx and Erbb2-likeEx . The gene expression profiles of some of the tumours correlated well with the PAM50 subtypes for human breast cancer. Whole-exome sequencing revealed somatic mutation profiles with only little overlap between the primary tumours. Orthotopically serially transplanted GLI1-induced tumours maintained the main morphological characteristics of the primary tumours for ≥10 generations. Independent of Trp53 status and molecular subtype, the serially transplanted GLI1-induced tumours were able to grow both in the absence of transgenic GLI1 expression and in the presence of the GLI1 inhibitor GANT61. These data suggest that elevated GLI1 expression has a determinant role in tumour initiation; however, additional genetic events are required for tumour progression.