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Ingenuity Pathway Analysis of Inflammation and Immunity Transcriptome panel.

Heat map of RNA expression showing all polyps including those with < 50% tumor purity.

Power calculations for experimental design of RNASeq analysis.

Supplemental Figure Legend

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Supplementary Figures S1-S8, Supplementary Materials and Methods, and Supplementary Tables S1-S2.

Log hazard smoothing spline plot.

Supplemental Figures 1-7 include a graphical outline of the study, graphs depicting probe performance, correlations between MHCII and TIL scores, ROC statistics, and additional Kaplan Meier curves.

PDF file, 68KB, Supplemental Table 1: Intrinsic subtype definitions by immunohistochemistry. Supplemental Table 2: C-Index for Risk-of-Relapse (ROR) Scores.

To investigate whether the impact of postdiagnosis exercise on breast cancer outcomes in women diagnosed with early-stage breast cancer differs on the basis of tumor clinicopathologic and molecular features. Using a prospective design, 6,211 patients with early-stage breast cancer from two large population-based cohort studies were studied. Age-adjusted and multivariable Cox regression models were performed to determine the relationship between exercise exposure (total MET-hours/week) and recurrence and breast cancer–related death for: (i) all patients (“unselected” cohort), and on the basis of (ii) classic clinicopathologic features, (iii) clinical subtypes, (iv) PAM50-based molecular intrinsic subtypes, and (v) individual PAM50 target genes. After a median follow-up of 7.2 years, in the unselected cohort (n = 6,211) increasing exercise exposure was not associated with a reduction in the risk of recurrence (adjusted Ptrend = 0.60) or breast cancer–related death (adjusted Ptrend = 0.39). On the basis of clinicopathologic features, an exercise-associated reduction in breast cancer–related death was apparent for tumors +/PR+/HER2−/low-grade clinical subtype was preferentially responsive to exercise (recurrence: adjusted HR, 0.63; 95% CI, 0.45–0.88; breast cancer–related death: adjusted HR, 0.57; 95% CI, 0.37–0.86). The impact of exercise on cancer outcomes appears to differ as a function of pathologic and molecular features in early-stage breast cancer. Cancer Res; 76(18); 5415–22. ©2016 AACR.

Supplemental Figure: Description of sample sets for the DNAseq and RNAseq experiments.

Purpose: Lung squamous cell carcinoma (SCC) is clinically and genetically heterogeneous, and current diagnostic practices do not adequately substratify this heterogeneity. A robust, biologically based SCC subclassification may describe this variability and lead to more precise patient prognosis and management. We sought to determine if SCC mRNA expression subtypes exist, are reproducible across multiple patient cohorts, and are clinically relevant.Experimental Design: Subtypes were detected by unsupervised consensus clustering in five published discovery cohorts of mRNA microarrays, totaling 382 SCC patients. An independent validation cohort of 56 SCC patients was collected and assayed by microarrays. A nearest-centroid subtype predictor was built using discovery cohorts. Validation cohort subtypes were predicted and evaluated for confirmation. Subtype survival outcome, clinical covariates, and biological processes were compared by statistical and bioinformatic methods.Results: Four lung SCC mRNA expression subtypes, named primitive, classical, secretory, and basal, were detected and independently validated (P < 0.001). The primitive subtype had the worst survival outcome (P < 0.05) and is an independent predictor of survival (P < 0.05). Tumor differentiation and patient sex were associated with subtype. The expression profiles of the subtypes contained distinct biological processes (primitive: proliferation; classical: xenobiotic metabolism; secretory: immune response; basal: cell adhesion) and suggested distinct pharmacologic interventions. Comparison with lung model systems revealed distinct subtype to cell type correspondence.Conclusions: Lung SCC consists of four mRNA expression subtypes that have different survival outcomes, patient populations, and biological processes. The subtypes stratify patients for more precise prognosis and targeted research. Clin Cancer Res; 16(19); 4864–75. ©2010 AACR.

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PDF file, 125KB, Supplemental Figure 1: REMARK Diagram for MA.12 Trial and Biospecimens Supplemental Figure 2: Forest plot for Disease free Survival across various Classifiers.

Purpose: Gene expression profiling classifies breast cancer into intrinsic subtypes based on the biology of the underlying disease pathways. We have used material from a prospective randomized trial of tamoxifen versus placebo in premenopausal women with primary breast cancer (NCIC CTG MA.12) to evaluate the prognostic and predictive significance of intrinsic subtypes identified by both the PAM50 gene set and by immunohistochemistry.Experimental Design: Total RNA from 398 of 672 (59%) patients was available for intrinsic subtyping with a quantitative reverse transcriptase PCR (qRT-PCR) 50-gene predictor (PAM50) for luminal A, luminal B, HER-2–enriched, and basal-like subtypes. A tissue microarray was also constructed from 492 of 672 (73%) of the study population to assess a panel of six immunohistochemical IHC antibodies to define the same intrinsic subtypes.Results: Classification into intrinsic subtypes by the PAM50 assay was prognostic for both disease-free survival (DFS; P = 0.0003) and overall survival (OS; P = 0.0002), whereas classification by the IHC panel was not. Luminal subtype by PAM50 was predictive of tamoxifen benefit [DFS: HR, 0.52; 95% confidence interval (CI), 0.32–0.86 vs. HR, 0.80; 95% CI, 0.50–1.29 for nonluminal subtypes], although the interaction test was not significant (P = 0.24), whereas neither subtyping by central immunohistochemistry nor by local estrogen receptor (ER) or progesterone receptor (PR) status were predictive. Risk of relapse (ROR) modeling with the PAM50 assay produced a continuous risk score in both node-negative and node-positive disease.Conclusions: In the MA.12 study, intrinsic subtype classification by qRT-PCR with the PAM50 assay was superior to IHC profiling for both prognosis and prediction of benefit from adjuvant tamoxifen. Clin Cancer Res; 18(16); 4465–72. ©2012 AACR.

Equations to calculate sample size in a homozygous discordant design. Supplemental Table: Sample size requirements (n in each group)

Supplementary Data from A Comparison of PAM50 Intrinsic Subtyping with Immunohistochemistry and Clinical Prognostic Factors in Tamoxifen-Treated Estrogen Receptor–Positive Breast Cancer

The findings from genome-wide association studies hold enormous potential for novel insight into disease mechanisms. A major challenge in the field is to map these low-risk association signals to their underlying functional sequence variants (FSV). Simple sequence study designs are insufficient, as the vast numbers of statistically comparable variants and a limited knowledge of noncoding regulatory elements complicate prioritization. Furthermore, large sample sizes are typically required for adequate power to identify the initial association signals. One important question is whether similar sample sizes need to be sequenced to identify the FSVs. Here, we present a proof-of-principle example of an extreme discordant design to map FSVs within the 2q33 low-risk breast cancer locus. Our approach employed DNA sequencing of a small number of discordant haplotypes to efficiently identify candidate FSVs. Our results were consistent with those from a 2,000-fold larger, traditional imputation-based fine-mapping study. To prioritize further, we used expression-quantitative trait locus analysis of RNA sequencing from breast tissues, gene regulation annotations from the ENCODE consortium, and functional assays for differential enhancer activities. Notably, we implicate three regulatory variants at 2q33 that target CASP8 (rs3769823, rs3769821 in CASP8, and rs10197246 in ALS2CR12) as functionally relevant. We conclude that nested discordant haplotype sequencing is a promising approach to aid mapping of low-risk association loci. The ability to include more efficient sequencing designs into mapping efforts presents an opportunity for the field to capitalize on the potential of association loci and accelerate translation of association signals to their underlying FSVs. Cancer Res; 76(7); 1916–25. ©2016 AACR.

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Approximately 40% of patients with stage I–III triple-negative breast cancer (TNBC) recur after standard treatment, whereas the remaining 60% experience long-term disease-free survival (DFS). There are currently no clinical tests to assess the risk of recurrence in TNBC patients. We previously determined that TNBC patients with MHC class II (MHCII) pathway expression in their tumors experienced significantly longer DFS. To translate this discovery into a clinical test, we developed an MHCII Immune Activation assay, which measures expression of 36 genes using NanoString technology. Preanalytical testing confirmed that the assay is accurate and reproducible in formalin-fixed paraffin-embedded (FFPE) tumor specimens. The assay measurements were concordant with RNA-seq, MHCII protein expression, and tumor-infiltrating lymphocyte counts. In a training set of 44 primary TNBC tumors, the MHCII Immune Activation Score was significantly associated with longer DFS (HR = 0.17; P = 0.015). In an independent validation cohort of 56 primary FFPE TNBC tumors, the Immune Activation Score was significantly associated with longer DFS (HR = 0.19; P = 0.011) independent of clinical stage. An Immune Activation Score threshold for identifying patients with very low risk of relapse in the training set provided 100% specificity in the validation cohort. The assay format enables adoption as a standardized clinical prognostic test for identifying TNBC patients with a low risk of recurrence. Correlative data support future studies to determine if the assay can identify patients in whom chemotherapy can be safely deescalated and patients likely to respond to immunotherapy.Significance:The MHCII Immune Activation assay identifies TNBC patients with a low risk of recurrence, addressing a critical need for prognostic biomarker tests that enable precision medicine for TNBC patients.

Purpose: Recent studies suggest that intrinsic breast cancer subtypes may differ in their responsiveness to specific chemotherapy regimens. We examined this hypothesis on NCIC.CTG MA.5, a clinical trial randomizing premenopausal women with node-positive breast cancer to adjuvant CMF (cyclophosphamide-methotrexate-fluorouracil) versus CEF (cyclophosphamide-epirubicin-fluorouracil) chemotherapy.Experimental Design: Intrinsic subtype was determined for 476 tumors using the quantitative reverse transcriptase PCR PAM50 gene expression test. Luminal A, luminal B, HER2-enriched (HER2-E), and basal-like subtypes were correlated with relapse-free survival (RFS) and overall survival (OS), estimated using Kaplan–Meier plots and log-rank testing. Multivariable Cox regression analyses determined significance of interaction between treatment and intrinsic subtypes.Results: Intrinsic subtypes were associated with RFS (P = 0.0005) and OS (P < 0.0001) on the combined cohort. The HER2-E showed the greatest benefit from CEF versus CMF, with absolute 5-year RFS and OS differences exceeding 20%, whereas there was a less than 2% difference for non–HER2-E tumors (interaction test P = 0.03 for RFS and 0.03 for OS). Within clinically defined Her2+ tumors, 79% (72 of 91) were classified as the HER2-E subtype by gene expression and this subset was strongly associated with better response to CEF versus CMF (62% vs. 22%, P = 0.0006). There was no significant difference in benefit between CEF and CMF in basal-like tumors [n = 94; HR, 1.1; 95% confidence interval (CI), 0.6–2.1 for RFS and HR, 1.3; 95% CI, 0.7–2.5 for OS].Conclusion: HER2-E strongly predicted anthracycline sensitivity. The chemotherapy-sensitive basal-like tumors showed no added benefit for CEF over CMF, suggesting that nonanthracycline regimens may be adequate in this subtype although further investigation is required. Clin Cancer Res; 18(8); 2402–12. ©2012 AACR.

Purpose: To compare clinical, immunohistochemical (IHC), and gene expression models of prognosis applicable to formalin-fixed, paraffin-embedded blocks in a large series of estrogen receptor (ER)–positive breast cancers from patients uniformly treated with adjuvant tamoxifen.Experimental Design: Quantitative real-time reverse transcription-PCR (qRT-PCR) assays for 50 genes identifying intrinsic breast cancer subtypes were completed on 786 specimens linked to clinical (median follow-up, 11.7 years) and IHC [ER, progesterone receptor (PR), HER2, and Ki67] data. Performance of predefined intrinsic subtype and risk-of-relapse scores was assessed using multivariable Cox models and Kaplan-Meier analysis. Harrell's C-index was used to compare fixed models trained in independent data sets, including proliferation signatures.Results: Despite clinical ER positivity, 10% of cases were assigned to nonluminal subtypes. qRT-PCR signatures for proliferation genes gave more prognostic information than clinical assays for hormone receptors or Ki67. In Cox models incorporating standard prognostic variables, hazard ratios for breast cancer disease-specific survival over the first 5 years of follow-up, relative to the most common luminal A subtype, are 1.99 [95% confidence interval (CI), 1.09-3.64] for luminal B, 3.65 (95% CI, 1.64-8.16) for HER2-enriched subtype, and 17.71 (95% CI, 1.71-183.33) for the basal-like subtype. For node-negative disease, PAM50 qRT-PCR–based risk assignment weighted for tumor size and proliferation identifies a group with >95% 10-year survival without chemotherapy. In node-positive disease, PAM50-based prognostic models were also superior.Conclusion: The PAM50 gene expression test for intrinsic biological subtype can be applied to large series of formalin-fixed, paraffin-embedded breast cancers, and gives more prognostic information than clinical factors and IHC using standard cut points. Clin Cancer Res; 16(21); 5222–32. ©2010 AACR.

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Background: Previously, family-based designs and high-risk pedigrees have illustrated value for the discovery of high- and intermediate-risk germline breast cancer susceptibility genes. However, genetic heterogeneity is a major obstacle hindering progress. New strategies and analytic approaches will be necessary to make further advances. One opportunity with the potential to address heterogeneity via improved characterization of disease is the growing availability of multisource databases. Specific to advances involving family-based designs are resources that include family structure, such as the Utah Population Database (UPDB). To illustrate the broad utility and potential power of multisource databases, we describe two different novel family-based approaches to reduce heterogeneity in the UPDB. Methods: Our first approach focuses on using pedigree-informed breast tumor phenotypes in gene mapping. Our second approach focuses on the identification of families with similar pleiotropies. We use a novel network-inspired clustering technique to explore multi-cancer signatures for high-risk breast cancer families. Results: Our first approach identifies a genome-wide significant breast cancer locus at 2q13 [P = 1.6 × 10−8, logarithm of the odds (LOD) equivalent 6.64]. In the region, IL1A and IL1B are of particular interest, key cytokine genes involved in inflammation. Our second approach identifies five multi-cancer risk patterns. These clusters include expected coaggregations (such as breast cancer with prostate cancer, ovarian cancer, and melanoma), and also identify novel patterns, including coaggregation with uterine, thyroid, and bladder cancers. Conclusions: Our results suggest pedigree-informed tumor phenotypes can map genes for breast cancer, and that various different cancer pleiotropies exist for high-risk breast cancer pedigrees. Impact: Both methods illustrate the potential for decreasing etiologic heterogeneity that large, population-based multisource databases can provide. See all articles in this CEBP Focus section, “Modernizing Population Science.”

Background: Approximately 40% of patients with stage I-III triple-negative breast cancer (TNBC) recur after standard treatment, while the remaining 60% experience long-term disease-free survival (DFS). There are currently no clinical tests to assess the risk of recurrence in TNBC patients. We previously developed and validated an MHCII Immune Activation assay, which measures a gene expression signature that includes the major histocompatibility complex class II (MHCII) pathway genes and markers of activated tumor infiltrating lymphocytes. The MHCII Immune Activation assay was recently shown to accurately assess the risk of recurrence in Basal-like TNBC patients using FFPE tissues from an institutional cohort. A limitation of the previous study is that the patients’ treatment regimens in the institutional cohort were heterogeneous. The goal of this study was to determine if the MHCII Immune Activation assay can accurately assess the DFS in Basal-like TNBC patients who received uniform chemotherapy regimens in the context of a randomized clinical trial. Methods: The MHCII Immune Activation assay was applied to RNA isolated from 60 Basal-like TNBC FFPE specimens from the GEICAM/9906 clinical trial, a multicenter randomized phase III study evaluating adjuvant chemotherapy in node-positive operable BC patients. Thirty nine (65%) of the patients were treated with fluorouracil, epirubicin, and cyclophosphamide (FEC), and 21 (35%) patients received FEC followed by paclitaxel (FEC-P) (median follow-up 9.7 years). The MHCII Immune Activation Score was calculated from the assay using methods described previously, and patients were categorized into a High Risk of Recurrence (High ROR) group using pre-specified thresholds. The association between the MHCII Immune Activation Score and DFS was assessed using Kaplan-Meier analysis and cox proportional hazards models. Results: Across both arms, 32/60 (53.3%) patients were classified into the High ROR group based on their Low MHCII Immune Activation Scores. Patients in the High ROR group had significantly shorter DFS (Hazard Ratio (HR)=2.9 (CI95%:1.27-6.66), p-value=0.0081). Cox proportional hazard regression of the log10 transformed MHCII Immune Activation Score confirmed that MHCII Immune Activation Score is significantly associated with DFS (Wald Test p=0.0127). In the FEC arm, there were 22/39 (56.41%) patients classified into the High ROR group (Low MHCII Immune Activation Score). Patients in the High ROR group in the FEC arm showed a trend toward shorter DFS (HR=1.99 (CI95%:0.74-5.31)), but it was not significant (p-value=0.1595). In the FEC-P arm, there were 10/21 (47.62%) patients classified into the High ROR group (Low MHCII Immune Activation Score). Patients in the High ROR group in the FEC-P arm had significantly shorter DFS (HR=6.28 (CI95%:1.28-30.73), p-value=0.0111). Larger cohorts will be needed to confirm if the association between DFS and MHCII Immune Activation Score is stronger when patients are treated with chemotherapy regimens that include paclitaxel. Conclusions: The MHCII Immune Activation assay can be applied to RNA from FFPE tumor specimens to assess risk of recurrence in TNBC patients. The MHCII Immune Activation Score is associated with risk of recurrence in TNBC patients treated with uniform adjuvant chemotherapy regimens. Citation Format: Miguel Martín, Katherine L Updike, Alvaro Rodríguez-Lescure, Lourdes Calvo, Jesús Herranz, Nuria Martín, Philip S Bernard, Katherine E Varley. The MHCII immune activation assay is prognostic for disease free survival in basal-like TNBC breast cancer patients in the GEICAM/9906 clinical 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 P1-10-09.

Background We recently showed PAM50 gene expression data can be represented by five quantitative, orthogonal, multi-gene breast tumor traits. These novel tumor ‘dimensions’ were superior to categorical intrinsic subtypes for clustering in high-risk breast cancer pedigrees, indicating potential to represent underlying genetic susceptibilities and biological pathways. Here we explore the prognostic and predictive utility of these dimensions in a sub-study of GEICAM/9906, a Phase III randomized prospective clinical trial of paclitaxel in breast cancer. Methods Tumor dimensions, PC1–PC5, were calculated using pre-defined coefficients. Univariable and multivariable Cox proportional hazards (PH) models for disease-free survival (DFS) were used to identify associations between quantitative dimensions and prognosis or response to the addition of paclitaxel. Results were illustrated using Kaplan–Meier curves. Results Dimensions PC1 and PC5 were associated with DFS (Cox PH p = 6.7 \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\times$$\end{document}× 10−7 and p = 0.036), remaining significant after correction for standard clinical–pathological prognostic characteristics. Both dimensions were selected in the optimal multivariable model, together with nodal status and tumor size (Cox PH p = 1.4 \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\times$$\end{document}× 10−12). Interactions with treatment were identified for PC3 and PC4. Response to paclitaxel was restricted to tumors with low PC3 and PC4 (log-rank p = 0.0021). Women with tumors high for PC3 or PC4 showed no survival advantage. Conclusions Our proof-of-concept application of quantitative dimensions illustrated novel findings and clinical utility beyond standard clinical–pathological characteristics and categorical intrinsic subtypes for prognosis and predicting chemotherapy response. Consideration of expression data as quantitative tumor dimensions offers new potential to identify clinically important patient subsets in clinical trials and advance precision medicine. Electronic supplementary material The online version of this article (10.1007/s10549-018-05097-5) contains supplementary material, which is available to authorized users.

Simple Summary Breast cancer outcomes are variable due to differences in tumor biology, patient biology, and treatment. The likelihood of developing cancer and other diseases increases with age. Thus, many patients with breast cancer have multiple co-morbidities requiring medical management, which increases the probability of polypharmacy and the risk of adverse drug events. Pharmacogenetics is the study of how inherited genetic variants influence drug response. Depending on the genes that a patient inherits, some respond to drugs as expected, some experience debilitating side effects, and others have minimal to no response. In this paper, we discuss the theoretical clinical utility of pharmacogenetics for 225 patients with breast cancer relative to anti-cancer drugs and non-cancer drugs. For this population, 38 drug–gene associations with high levels of evidence for clinical actionability were identified, supporting the concept of pharmacogenetics integration into the routine care of future patients with breast cancer. Abstract Patients with breast cancer often receive many drugs to manage the cancer, side effects associated with cancer treatment, and co-morbidities (i.e., polypharmacy). Drug–drug and drug–gene interactions contribute to the risk of adverse events (AEs), which could lead to non-adherence and reduced efficacy. Here we investigated several well-characterized inherited (germline) pharmacogenetic (PGx) targets in 225 patients with breast cancer. All relevant clinical, pharmaceutical, and PGx diplotype data were aggregated into a single unifying informatics platform to enable an exploratory analysis of the cohort and to evaluate pharmacy ordering patterns. Of the drugs recorded, there were 38 for which high levels of evidence for clinical actionability with PGx was available from the US FDA and/or the Clinical Pharmacogenetics Implementation Consortium (CPIC). These data were associated with 10 pharmacogenes: DPYD, CYP2C9, CYP2C19, CYP2D6, CYP3A5, CYP4F2, G6PD, MT-RNR1, SLCO1B1, and VKORC1. All patients were taking at least one of the 38 drugs and had inherited at least one actionable PGx variant that would have informed prescribing decisions if this information had been available pre-emptively. The non-cancer drugs with PGx implications that were common (prescribed to at least one-third of patients) included anti-depressants, anti-infectives, non-steroidal anti-inflammatory drugs, opioids, and proton pump inhibitors. Based on these results, we conclude that pre-emptive PGx testing may benefit patients with breast cancer by informing drug and dose selection to maximize efficacy and minimize AEs.

BACKGROUND Although the proportion of triple-negative breast cancers (TNBCs) diagnosed among older women is low, the number of TNBC cases is substantial because of the high incidence of breast cancer after the age of 65 years. The molecular features of TNBC in this age group have not been well described. METHODS This study examined a population-based cohort of women with stage I to III TNBC diagnosed between the ages of 25 and 91 years with the PAM50 gene expression subtyping assay. The concordance between the TNBC classification by immunohistochemistry and the gene expression classification by PAM50, the expression of individual genes, and 5-year recurrence and breast cancer mortality in older women (≥65 years old) and younger women (

Background: Breast tumor subtyping has failed to provide impact in susceptibility genetics. The PAM50 assay categorizes breast tumors into: Luminal A, Luminal B, HER2-enriched and Basal-like. However, tumors are often more complex than simple categorization can describe. The identification of heritable tumor characteristics has potential to decrease heterogeneity and increase power for gene finding. Methods: We used 911 sporadic breast tumors with PAM50 expression data to derive tumor dimensions using principal components (PC). Dimensions in 238 tumors from high-risk pedigrees were compared with the sporadic tumors. Proof-of-concept gene mapping, informed by tumor dimension, was performed using Shared Genomic Segment (SGS) analysis. Results: Five dimensions (PC1-5) explained the majority of the PAM50 expression variance: three captured intrinsic subtype, two were novel (PC3, PC5). All five replicated in 745 TCGA tumors. Both novel dimensions were significantly enriched in the high-risk pedigrees (intrinsic subtypes were not). SGS gene-mapping in a pedigree identified a 0.5 Mb genome-wide significant region at 12q15. This region segregated through 32 meioses to 8 breast cancer cases with extreme PC3 tumors (P = 2.6 × 10−8). Conclusions: PC analysis of PAM50 gene expression revealed multiple independent, quantitative measures of tumor diversity. These tumor dimensions show evidence for heritability and potential as powerful traits for gene mapping. Impact: Our study suggests a new approach to describe tumor expression diversity, provides new avenues for germline studies, and proposes a new breast cancer locus. Similar reparameterization of expression patterns may inform other studies attempting to model the effects of tumor heterogeneity. Cancer Epidemiol Biomarkers Prev; 27(6); 644–52. ©2018 AACR.

Introduction: The ability for oncologists to predict a cancer's response to therapy is limited to a few biomarkers used for histologic diagnosis and targeted therapy. Often, in advanced and metastatic disease these biomarkers provide no alternative options for next step systemic treatments. There is a need in oncology for functional assays that can determine a tumor's response to a drug, regardless of its tissue of origin, previous treatments, or mutation status. Quantitative phase imaging (QPI) can measure changes in single cell mass in response to drug treatment in vitro and ex vivo. This platform offers advantages over other functional/metabolic assays in that it monitors changes in real-time and on a single cell basis, revealing heterogeneity in drug response. Methods: Here, we describe the validation of QPI for the measurement of breast cancer cell response to therapy versus CellTiterGlo (CTG), an endpoint ATP assay. We ran a series of 3-day drug response assays using QPI alongside CTG. We used a 96 well plate with a 6-point dose response between 1.6 nM and 20 μM for multiple cell lines spanning a range of receptor statuses (MCF7, MDA-MB-231, BT-474) with two controls in triplicate. We analyzed single-cell data to measure the heterogeneity of response and assessed how cell-to-cell heterogeneity is affected by dose. Our response data were fitted to a four-parameter Hill equation to compute the IC50 and depth of response. Results: We found that QPI can determine IC50s for effective treatments as validated by concordance to CTG. As measured by QPI, doxorubicin has a substantial depth of response, indicating cytotoxic effects. Doxorubicin data also show a tighter range of growth rates at high concentration than control, which implies low heterogeneity of response. As expected, ER positive MCF7 cells responded to hydroxy-tamoxifen. This response shows a similar reduction in heterogeneity to doxorubicin but with a reduced depth of response indicating a cytostatic effect. MDA-MB-231 response to palbociclib exhibits a wide range of growth rates, indicating an increase in heterogeneity as measured by QPI. Fluorouracil response shows no significant difference in heterogeneity from control. Conclusion: In summary, QPI is a useful tool for functional assays that can capture IC50, depth of response, and single-cell heterogeneity of response. In particular, this additional information about single-cell behavior and heterogeneity cannot be measured using a typical endpoint assay. Future work is needed to prove the clinical utility of functional assays from QPI. Citation Format: Tarek E. Moustafa, Edward R. Polanco, Andrew Butterfield, Sandra D. Scherer, Bryan E. Welm, Philip S. Bernard, Thomas A. Zangle. Real-time single-cell drug response assay in metastatic breast cancer cell lines using quantitative phase imaging [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 1301.

BACKGROUND Studies of obesity and survival among patients with breast cancer produce conflicting results, possibly because of heterogeneity by molecular subtype. METHODS This study examined whether the association of body mass index (BMI) at diagnosis with breast cancer recurrence and survival varied across subtypes defined by PAM50 (Prediction Analysis of Microarray 50) gene expression. Included were 1559 Kaiser Permanente Northern California members ages 18 to 79 years who had PAM50 assays and were diagnosed with American Joint Committee on Cancer stage I through III breast cancer from 1996 to 2013. Patients reported weight and height. Cox regression models were adjusted for age, menopause, race/ethnicity, stage, and chemotherapy. RESULTS Over a median of 9 years (maximum, 19 years), 378 women developed recurrent disease, and 312 died from breast cancer. Overall, BMI was not associated with breast cancer recurrence or survival when controlling for subtype (eg, the hazard ratio per 5 kg/m2 of BMI was 1.05 [95% confidence interval, 0.95-1.15] for breast cancer-specific death). However, associations varied by subtype. Among women with luminal A cancers, those who had class II/III obesity, but not class I obesity or overweight, had worse outcomes. When women who had a BMI ≥35 kg/m2 were compared with those who had a BMI from 18.5 to

Objectives Sessile serrated adenoma/polyps (SSA/Ps) contribute up to 30% of all colon cancers. There is considerable histological overlap between SSA/Ps and hyperplastic polyps. Inadequate consensus exists among pathologists, and no molecular biomarkers exist to differentiate these lesions with high accuracy. Lack of reliable diagnosis adversely affects clinical care. We previously defined a novel 7-gene panel by RNA sequencing that differentiates SSA/Ps from hyperplastic polyps. Here, we use the 7-gene panel as a molecular approach to differentiate SSA/Ps and HPs with higher sensitivity and specificity in a large sample set from a tertiary health care center. Methods Reverse transcription quantitative polymerase chain reaction of the 7-gene panel was performed on 223 formalin-fixed, paraffin-embedded serrated polyp and normal colon samples. We compare the sensitivity and specificity of the 7-gene panel with the BRAF and KRAS mutation incidence in differentiating SSA/Ps and HPs. We also evaluate the clinical data of patients with SSA/Ps showing high and low expression of the gene panel. Results The 7-gene RNA expression panel differentiates SSA/Ps and HPs with 89.2% sensitivity and 88.4% specificity. The gene panel outperforms BRAF mutation in identification of SSA/Ps. Clinical data suggest that expression of the 7-gene panel correlates with the development of SSA/Ps in the future. Discussion This study describes a novel 7-gene panel that identifies SSA/Ps with improved accuracy. Our data show that RNA markers of SSA/Ps advance the distinction of serrated lesions and contribute to the study of the serrated pathway to colon cancer.

To investigate whether the impact of postdiagnosis exercise on breast cancer outcomes in women diagnosed with early-stage breast cancer differs on the basis of tumor clinicopathologic and molecular features. Using a prospective design, 6,211 patients with early-stage breast cancer from two large population-based cohort studies were studied. Age-adjusted and multivariable Cox regression models were performed to determine the relationship between exercise exposure (total MET-hours/week) and recurrence and breast cancer–related death for: (i) all patients (“unselected” cohort), and on the basis of (ii) classic clinicopathologic features, (iii) clinical subtypes, (iv) PAM50-based molecular intrinsic subtypes, and (v) individual PAM50 target genes. After a median follow-up of 7.2 years, in the unselected cohort (n = 6,211) increasing exercise exposure was not associated with a reduction in the risk of recurrence (adjusted Ptrend = 0.60) or breast cancer–related death (adjusted Ptrend = 0.39). On the basis of clinicopathologic features, an exercise-associated reduction in breast cancer–related death was apparent for tumors

Approximately 40% of patients with stage I–III triple-negative breast cancer (TNBC) recur after standard treatment, whereas the remaining 60% experience long-term disease-free survival (DFS). There are currently no clinical tests to assess the risk of recurrence in TNBC patients. We previously determined that TNBC patients with MHC class II (MHCII) pathway expression in their tumors experienced significantly longer DFS. To translate this discovery into a clinical test, we developed an MHCII Immune Activation assay, which measures expression of 36 genes using NanoString technology. Preanalytical testing confirmed that the assay is accurate and reproducible in formalin-fixed paraffin-embedded (FFPE) tumor specimens. The assay measurements were concordant with RNA-seq, MHCII protein expression, and tumor-infiltrating lymphocyte counts. In a training set of 44 primary TNBC tumors, the MHCII Immune Activation Score was significantly associated with longer DFS (HR = 0.17; P = 0.015). In an independent validation cohort of 56 primary FFPE TNBC tumors, the Immune Activation Score was significantly associated with longer DFS (HR = 0.19; P = 0.011) independent of clinical stage. An Immune Activation Score threshold for identifying patients with very low risk of relapse in the training set provided 100% specificity in the validation cohort. The assay format enables adoption as a standardized clinical prognostic test for identifying TNBC patients with a low risk of recurrence. Correlative data support future studies to determine if the assay can identify patients in whom chemotherapy can be safely deescalated and patients likely to respond to immunotherapy. Significance: The MHCII Immune Activation assay identifies TNBC patients with a low risk of recurrence, addressing a critical need for prognostic biomarker tests that enable precision medicine for TNBC patients.

Exosomes are membrane nanovesicles implicated in cell-to-cell signaling in which they transfer their molecular cargo from the parent to the recipient cells. This role essentially depends on the exosomes' small size, which is the prerequisite for their rapid migration through the crowded extracellular matrix and into and out of circulation. Here we report much lower exosome mobility than expected from the size of their vesicles, implicate membrane proteins in a substantially impeded rate of migration, and suggest an approach to quantifying the impact. The broadly distributed excess hydrodynamic resistance provided by surface proteins produces a highly heterogeneous and microenvironment-dependent hindrance to exosome mobility. The implications of the findings on exosome-mediated signaling are discussed.

Purpose. To determine intrinsic breast cancer subtypes represented within categories defined by quantitative hormone receptor (HR) and HER2 expression. Methods. We merged 1,557 cases from three randomized phase III trials into a single data set. These breast tumors were centrally reviewed in each trial for quantitative ER, PR, and HER2 expression by immunohistochemistry (IHC) stain and by reverse transcription-quantitative polymerase chain reaction (RT-qPCR), with intrinsic subtyping by research-based PAM50 RT-qPCR assay. Results. Among 283 HER2-negative tumors with 10%) expression, only 69 (54%) were HER2-enriched and 55 (43%) were luminal (39 luminal B, 16 luminal A). Quantitative HR expression by RT-qPCR gave similar results. Regardless of methodology, basal-like cases seldom expressed ER/ESR1 or PR/PGR and were associated with the lowest expression level of HER2/ERBB2 relative to other subtypes. Conclusion. Significant discordance remains between clinical assay-defined subsets and intrinsic subtype. For identifying basal-like breast cancer, the optimal HR IHC cut point was

Exosomes are membrane nanovesicles that intermediate cell-to-cell signaling through the transfer of their molecular cargo. The exosomes’ small size facilitates rapid migration through the extracellular matrix and into and out of circulation. Here we report that the mobility of the exosomes is much lower than would be expected from the size of their membrane vesicles. The difference is broadly distributed and caused by surface proteins, which significantly impede exosome migration. The observed wide range in the mobility implies that a subpopulation of hydrodynamically small exosomes is more likely to participate in signaling. The extracellular environment amplifies the size-dependent hindrance to the exosomes migration. The significant contribution of surface proteins to the transport resistance make the exosome mobility a dynamic property that changes with the extracellular environment which affects the membrane protein conformation, glycosylation, specific, and non-specific surface adsorption.

BACKGROUND: Breast tumor subtyping has failed to provide impact in susceptibility genetics. The PAM50 assay categorizes breast tumors into: Luminal A, Luminal B, HER2-enriched and Basal-like. However, tumors are often more complex than simple categorization can describe. The identification of heritable tumor characteristics has potential to decrease heterogeneity and increase power for gene-finding. METHODS: We used 911 sporadic breast tumors with PAM50 expression data to derive tumor dimensions using principal components (PC). Dimensions in 238 tumors from high-risk pedigrees were compared to the sporadic tumors. Proof-of-concept gene mapping, informed by tumor dimension, was performed using Shared Genomic Segment (SGS) analysis. RESULTS: Five dimensions (PC1-5) explained the majority of the PAM50 expression variance: three captured intrinsic subtype, two were novel (PC3, PC5). All five replicated in 745 TCGA tumors. Both novel dimensions were significantly enriched in the high-risk pedigrees (intrinsic subtypes were not). SGS gene-mapping in a pedigree identified a 0.5 Mb genomewide significant region at 12q15. This region segregated through 32 meioses to 8 breast cancer cases with extreme PC3 tumors (p=2.6×10(−8)). CONCLUSIONS: Principal component analysis of PAM50 gene expression revealed multiple independent, quantitative measures of tumor diversity. These tumor dimensions show evidence for heritability and potential as powerful traits for gene-mapping. IMPACT: Our study suggests a new approach to describe tumor expression diversity, provides new avenues for germline studies, and proposes a new breast cancer locus. Similar reparameterization of expression patterns may inform other studies attempting to model the effects of tumor heterogeneity.

PAM50 intrinsic breast cancer subtypes are prognostic independent of standard clinicopathologic factors. CALGB 9741 demonstrated improved recurrence-free (RFS) and overall survival (OS) with 2-weekly dose-dense (DD) versus 3-weekly therapy. A significant interaction between intrinsic subtypes and DD-therapy benefit was hypothesized. Suitable tumor samples were available from 1,471 (73%) of 2,005 subjects. Multiplexed gene-expression profiling generated the PAM50 subtype call, proliferation score, and risk of recurrence score (ROR-PT) for the evaluable subset of 1,311 treated patients. The interaction between DD-therapy benefit and intrinsic subtype was tested in a Cox proportional hazards model using two-sided alpha=0.05. Additional multivariable Cox models evaluated the proliferation and ROR-PT scores as continuous measures with selected clinical covariates. Improved outcomes for DD therapy in the evaluable subset mirrored results from the complete data set (RFS; hazard ratio=1.20; 95% confidence interval=0.99–1.44) with 12.3-year median follow-up. Intrinsic subtypes were prognostic of RFS (PP=0.44). Proliferation and ROR-PT scores were prognostic for RFS (both PP=0.14 and 0.59, respectively). Results were similar for OS. The prognostic value of PAM50 intrinsic subtype was greater than estrogen receptor/HER2 immunohistochemistry classification. PAM50 gene signatures were highly prognostic but did not predict for improved outcomes with DD anthracycline- and taxane-based therapy. Clinical validation studies will assess the ability of PAM50 and other gene signatures to stratify patients and individualize treatment based on expected risks of distant recurrence.

It is well-known that breast tumors exhibit different expression patterns that can be used to assign intrinsic subtypes – the PAM50 assay, for example, categorizes tumors into: Luminal A, Luminal B, HER2-enriched and Basal-like – yet tumors are often more complex than categorization can describe. We used 911 sporadic breast tumors to reparameterize expression from the PAM50 genes to five orthogonal tumor dimensions using principal components (PC). Three dimensions captured intrinsic subtype, two dimensions were novel, and all replicated in 945 TCGA tumors. By definition dimensions are independent, an important attribute for inclusion in downstream studies exploring effects of tumor diversity. One application where tumor subtyping has failed to provide impact is susceptibility genetics. Germline genetic heterogeneity reduces power for gene-finding. The identification of heritable tumor characteristics has potential to increase homogeneity. We compared 238 breast tumors from high-risk pedigrees not attributable to BRCA1 or BRCA2 to 911 sporadic breast tumors. Two PC dimensions were significantly enriched in the pedigrees (intrinsic subtypes were not). We performed proof-of-concept gene-mapping in one enriched pedigree and identified a 0.5 Mb genomewide significant region at 12q15 that segregated to the 8 breast cancer cases with the most extreme PC tumors through 32 meioses (p=2.6×10−8). In conclusion, our study: suggests a new approach to describe tumor diversity; supports the hypothesis that tumor characteristics are heritable providing new avenues for germline studies; and proposes a new breast cancer locus. Reparameterization of expression patterns may similarly inform other studies attempting to model the effects of tumor heterogeneity.

To identify gene expression biomarkers and pathways targeted by sulindac and erlotinib given in a chemoprevention trial with a significant decrease in duodenal polyp burden at 6 months (P < 0.001) in familial adenomatous polyposis (FAP) patients, we biopsied normal and polyp duodenal tissues from patients on drug versus placebo and analyzed the RNA expression. RNA sequencing was performed on biopsies from the duodenum of FAP patients obtained at baseline and 6-month endpoint endoscopy. Ten FAP patients on placebo and 10 on sulindac and erlotinib were selected for analysis. Purity of biopsied polyp tissue was calculated from RNA expression data. RNAs differentially expressed between endpoint polyp and paired baseline normal were determined for each group and mapped to biological pathways. Key genes in candidate pathways were further validated by quantitative RT-PCR. RNA expression analyses of endpoint polyp compared with paired baseline normal for patients on placebo and drug show that pathways activated in polyp growth and proliferation are blocked by this drug combination. Directly comparing polyp gene expression between patients on drug and placebo also identified innate immune response genes (IL12 and IFNγ) preferentially expressed in patients on drug. Gene expression analyses from tissue obtained at endpoint of the trial demonstrated inhibition of the cancer pathways COX2/PGE2, EGFR, and WNT. These findings provide molecular evidence that the drug combination of sulindac and erlotinib reached the intended tissue and was on target for the predicted pathways. Furthermore, activation of innate immune pathways from patients on drug may have contributed to polyp regression. Cancer Prev Res; 11(1); 4–15. ©2017 AACR. See related editorial by Shureiqi, p. 1

Background: The PAM50, a gene expression assay to categorize breast tumors into intrinsic subtypes, has not been previously used to examine short- and long-term prognostication in a population-based cohort where treatment patterns and time of initial follow-up vary. Methods: In a stratified case–cohort design of 1,691 women from the LACE and Pathways breast cancer survivor cohorts, we used PAM50 to categorize tumors into Luminal A (LumA), Luminal B (LumB), HER2-enriched (HER2-E), Basal-like and Normal-like, and to examine risk of early and late recurrence and mortality by Cox proportional hazards regression. Results: Compared with LumA, cumulative risk of recurrence and breast cancer death was higher for LumB, HER2-E, and Basal-like tumors at 2, 5, and 10 years. However, HR of breast cancer death varied over time [ 5 years (late)] for both Basal-like (HR, 6.23 early vs. HR, 0.63 late) and HER2-E tumors (HR, 2.97 early vs. HR, 0.73 late) but not for LumB tumors where risk was elevated consistently (HR, 2.67 early vs. HR, 1.47 late). The contrast between LumB, HER2-E, and Basal-like compared with LumA on early recurrence was stronger when subtype was defined by PAM50 than by immunohistochemistry (IHC) markers. Conclusions: The PAM50 categorized intrinsic subtypes in a manner that more accurately predicts recurrence and survival, especially for luminal tumors, compared with commonly used methods that rely on traditional IHC clinical markers. Impact: The PAM50 is robust for use in epidemiologic studies and should be considered when archived tumor tissues are available. Cancer Epidemiol Biomarkers Prev; 23(5); 725–34. ©2014 AACR.

Lung cancer histologic diagnosis is clinically relevant because there are histology-specific treatment indications and contraindications. Histologic diagnosis can be challenging owing to tumor characteristics, and it has been shown to have less-than-ideal agreement among pathologists reviewing the same specimens. Microarray profiling studies using frozen specimens have shown that histologies exhibit different gene expression trends; however, frozen specimens are not amenable to routine clinical application. Herein, we developed a gene expression–based predictor of lung cancer histology for FFPE specimens, which are routinely available in clinical settings. Genes predictive of lung cancer histologies were derived from published cohorts that had been profiled by microarrays. Expression of these genes was measured by quantitative RT-PCR (RT-qPCR) in a cohort of patients with FFPE lung cancer. A histology expression predictor (HEP) was developed using RT-qPCR expression data for adenocarcinoma, carcinoid, small cell carcinoma, and squamous cell carcinoma. In cross-validation, the HEP exhibited mean accuracy of 84% and κ = 0.77. In separate independent validation sets, the HEP was compared with pathologist diagnoses on the same tumor block specimens, and the HEP yielded similar accuracy and precision as the pathologists. The HEP also exhibited good performance in specimens with low tumor cellularity. Therefore, RT-qPCR gene expression from FFPE specimens can be effectively used to predict lung cancer histology.

Mutations in TP53 lead to a defective G1 checkpoint and the dependence on checkpoint kinase 1 (Chk1) for G2 or S phase arrest in response to DNA damage. In preclinical studies, Chk1 inhibition resulted in enhanced cytotoxicity of several chemotherapeutic agents. The high frequency of TP53 mutations in triple negative breast cancer (TNBC: negative for estrogen receptor, progesterone receptor, and HER2) make Chk1 an attractive therapeutic target. UCN-01, a non-selective Chk1 inhibitor, combined with irinotecan demonstrated activity in advanced TNBC in our Phase I study. The goal of this trial was to further evaluate this treatment in women with TNBC. Patients with metastatic TNBC previously treated with anthracyclines and taxanes received irinotecan (100-125 mg/m(2) IV days 1, 8, 15, 22) and UCN-01 (70 mg/m(2) IV day 2, 35 mg/m(2) day 23 and subsequent doses) every 42-day cycle. Peripheral blood mononuclear cells (PBMC) and tumor specimens were collected. Twenty five patients were enrolled. The overall response (complete response (CR) + partial response (PR)) rate was 4 %. The clinical benefit rate (CR + PR + stable disease ≥6 months) was 12 %. Since UCN-01 inhibits PDK1, phosphorylated ribosomal protein S6 (pS6) in PBMC was assessed. Although reduced 24 h post UCN-01, pS6 levels rose to baseline by day 8, indicating loss of UCN-01 bioavailability. Immunostains of γH2AX and pChk1(S296) on serial tumor biopsies from four patients demonstrated an induction of DNA damage and Chk1 activation following irinotecan. However, Chk1 inhibition by UCN-01 was not observed in all tumors. Most tumors were basal-like (69 %), and carried mutations in TP53 (53 %). Median overall survival in patients with TP53 mutant tumors was poor compared to wild type (5.5 vs. 20.3 months, p = 0.004). This regimen had limited activity in TNBC. Inconsistent Chk1 inhibition was likely due to the pharmacokinetics of UCN-01. TP53 mutations were associated with a poor prognosis in metastatic TNBC.

Objectives A decrease in Ki67 during neoadjuvant therapy predicts response to tamoxifen. Previous trials have shown a decreased Ki67 in breast tumors with as little as two or more weeks of preoperative tamoxifen. Shortening the preoperative treatment time in window of opportunity clinical trials makes these trials more attractive to women. POWERPIINC examined the effect of 7 days of preoperative tamoxifen on breast tumor proliferation and patient symptoms. Methods Women with untreated stage I/II, ER-positive, invasive breast cancer with no contraindications to tamoxifen were enrolled. Women received 20 mg of tamoxifen for 7 days up to the day of surgery. Proliferation was assessed by Ki67 immunohistochemistry before and after 7 days of tamoxifen. Symptoms and QOL were assessed by the FACT-ES and MENQOL. Adherence was measured by pill counts. Results 52 women were enrolled, and 44 were evaluable for Ki67. The median age was 58.5 years, and the median tumor diameter was 1.2 cm. Most women (73%) were post-menopausal. Most tumors were PR positive (88%) and HER2-negative (92%). The Ki67 decreased by a geometric mean of 40% (95% CI 29%–63%), and 73% (95% CI 57%–85%) of women had tumors with decreased proliferation (p = 0.0001 by paired t-test). Adherence to taking tamoxifen during the preoperative period was 100%. Women reported minimal bother from psychosocial or physical symptoms at baseline or on the day of surgery. Conclusion Seven days of tamoxifen showed a similar relative decrease in Ki67 as that reported for longer courses, was acceptable to women, and could be considered for window of opportunity studies.

The findings from genome-wide association studies hold enormous potential for novel insight into disease mechanisms. A major challenge in the field is to map these low-risk association signals to their underlying functional sequence variants (FSV). Simple sequence study designs are insufficient, as the vast numbers of statistically comparable variants and a limited knowledge of noncoding regulatory elements complicate prioritization. Furthermore, large sample sizes are typically required for adequate power to identify the initial association signals. One important question is whether similar sample sizes need to be sequenced to identify the FSVs. Here, we present a proof-of-principle example of an extreme discordant design to map FSVs within the 2q33 low-risk breast cancer locus. Our approach employed DNA sequencing of a small number of discordant haplotypes to efficiently identify candidate FSVs. Our results were consistent with those from a 2,000-fold larger, traditional imputation-based fine-mapping study. To prioritize further, we used expression-quantitative trait locus analysis of RNA sequencing from breast tissues, gene regulation annotations from the ENCODE consortium, and functional assays for differential enhancer activities. Notably, we implicate three regulatory variants at 2q33 that target CASP8 (rs3769823, rs3769821 in CASP8, and rs10197246 in ALS2CR12) as functionally relevant. We conclude that nested discordant haplotype sequencing is a promising approach to aid mapping of low-risk association loci. The ability to include more efficient sequencing designs into mapping efforts presents an opportunity for the field to capitalize on the potential of association loci and accelerate translation of association signals to their underlying FSVs. Cancer Res; 76(7); 1916–25. ©2016 AACR.

Long non-coding RNAs (lncRNAs) are emerging as crucial regulators of cellular processes and diseases such as cancer; however, their functions remain poorly characterised. Several studies have demonstrated that lncRNAs are typically disease and tumour subtype specific, particularly in breast cancer where lncRNA expression alone is sufficient to discriminate samples based on hormone status and molecular intrinsic subtype. However, little attempt has been made to assess the reproducibility of lncRNA signatures across more than one dataset. In this work, we derive consensus lncRNA signatures indicative of breast cancer subtype based on two clinical RNA-Seq datasets: the Utah Breast Cancer Study and The Cancer Genome Atlas, through integration of differential expression and hypothesis-free clustering analyses. The most consistent signature is associated with breast cancers of the basal-like subtype, leading us to generate a putative set of six lncRNA basal-like breast cancer markers, at least two of which may have a role in cis-regulation of known poor prognosis markers. Through in silico functional characterization of individual signatures and integration of expression data from pre-clinical cancer models, we discover that discordance between signatures derived from different clinical cohorts can arise from the strong influence of non-cancerous cells in tumour samples. As a consequence, we identify nine lncRNAs putatively associated with breast cancer associated fibroblasts, or the immune response. Overall, our study establishes the confounding effects of tumour purity on lncRNA signature derivation, and generates several novel hypotheses on the role of lncRNAs in basal-like breast cancers and the tumour microenvironment.