Neoadjuvant nivolumab or nivolumab plus ipilimumab in early-stage triple-negative breast cancer: a phase 2 adaptive trial.

Immune checkpoint inhibition (ICI) with chemotherapy is now the standard of care for stage II-III triple-negative breast cancer; however, it is largely unknown for which patients ICI without chemotherapy could be an option and what the benefit of combination ICI could be. The adaptive BELLINI trial explored whether short combination ICI induces immune activation (primary end point, twofold increase in CD8+ T cells or IFNG), providing a rationale for neoadjuvant ICI without chemotherapy. Here, in window-of-opportunity cohorts A (4 weeks of anti-PD-1) and B (4 weeks of anti-PD-1 + anti-CTLA4), we observed immune activation in 53% (8 of 15) and 60% (9 of 15) of patients, respectively. High levels of tumor-infiltrating lymphocytes correlated with response. Single-cell RNA sequencing revealed that higher pretreatment tumor-reactive CD8+ T cells, follicular helper T cells and shorter distances between tumor and CD8+ T cells correlated with response. Higher levels of regulatory T cells after treatment were associated with nonresponse. Based on these data, we opened cohort C for patients with high levels of tumor-infiltrating lymphocytes (≥50%) who received 6 weeks of neoadjuvant anti-PD-1 + anti-CTLA4 followed by surgery (primary end point, pathological complete response). Overall, 53% (8 of 15) of patients had a major pathological response (<10% viable tumor) at resection, with 33% (5 of 15) having a pathological complete response. All cohorts met Simon's two-stage threshold for expansion to stage II. We observed grade ≥3 adverse events for 17% of patients and a high rate (57%) of immune-mediated endocrinopathies. In conclusion, neoadjuvant immunotherapy without chemotherapy demonstrates potential efficacy and warrants further investigation in patients with early triple-negative breast cancer. ClinicalTrials.gov registration: NCT03815890 .

A pan-cancer screen identifies drug combination benefit in cancer cell lines at the individual and population level.

Combining drugs can enhance their clinical efficacy, but the number of possible combinations and inter-tumor heterogeneity make identifying effective combinations challenging, while existing approaches often overlook clinically relevant activity. We screen one of the largest cell line panels (N = 757) with 51 clinically relevant combinations and identify responses at the level of individual cell lines and tissue populations. We establish three response classes to model cellular effects beyond monotherapy: synergy, Bliss additivity, and independent drug action (IDA). Synergy is rare (11% of responses) and frequently efficacious (>50% viability reduction), whereas Bliss and IDA are more frequent but less frequently efficacious. We introduce "efficacious combination benefit" (ECB) to describe high-efficacy responses classified as either synergy, Bliss, or IDA. We identify ECB biomarkers in vitro and show that ECB predicts response in patient-derived xenografts better than synergy alone. Our work here provides a valuable resource and framework for preclinical evaluation and the development of combination treatments.

Predictive gene expression profile for adjuvant taxane benefit in breast cancer in the MATADOR trial.

The primary objective of the prospective, randomized, multicenter, phase 3 biomarker Microarray Analysis in breast cancer to Taylor Adjuvant Drugs Or Regimens trial (MATADOR: ISRCTN61893718) is to generate a gene expression profile that can predict benefit from either docetaxel, doxorubicin, and cyclophosphamide (TAC) or dose-dense scheduled doxorubicin and cyclophosphamide (ddAC). Patients with a pT1-3, pN0-3 tumor were randomized 1:1 between ddAC and TAC. The primary endpoint was a gene profile-treatment interaction for recurrence-free survival (RFS). We observed 117 RFS events in 664 patients with a median follow-up of 7 years. Hallmark gene set analyses showed significant association between enrichment in immune-related gene expression and favorable outcome after TAC in hormone receptor-negative, human epidermal growth factor receptor 2 (HER2)-negative breast cancer (BC) (triple-negative breast cancer [TNBC]). We validated this association in TNBC patients treated with TAC on H&E slides; stromal tumor-infiltrating lymphocytes (sTILs) ≥20% was associated with longer RFS (hazard ratio 0.18, p = 0.01), while in patients treated with ddAC no difference in RFS was seen (hazard ratio 0.92, p = 0.86, p interaction = 0.02).

The innate immune landscape of dMMR/MSI cancers predicts outcome of nivolumab treatment: results from the Drug Rediscovery Protocol.

PURPOSE: Treatment efficacy of nivolumab was evaluated in patients with advanced, treatment-refractory solid dMMR/MSI tumors and in-depth biomarker analyses were performed to inform precision immunotherapy approaches. PATIENTS AND METHODS: Patients with dMMR/MSI tumors who exhausted standard-of-care treatment options were enrolled in the Drug Rediscovery Protocol (DRUP), a pan-cancer clinical trial that treats patients with cancer based on their tumor molecular profile with off-label anticancer drugs (NCT02925234). Patients received nivolumab (four cycles of 240 mg every 2 weeks, thereafter 480 mg every 4 weeks). The primary endpoint was clinical benefit (CB: objective response (OR) or stable disease ≥ 16 weeks). Whole-genome sequencing and RNA-sequencing were performed on pre-treatment tumor biopsies. RESULTS: 130 evaluable patients were enrolled with 16 different cancer types. CB was observed in 62% (95% CI: 53 - 70) with an OR in 45% (95% CI: 36 - 54). After a median follow-up of 14.5 months (95% CI: 13 - 19), median progression-free survival was 18 months (95% CI 9 - not reached) and median overall survival was not reached. While CB was not or only weakly associated with markers of adaptive immune cell infiltration, CB was strongly associated with expression of a broad set of innate immune receptors/ligands. This clearly contrasted findings in melanoma, where markers of adaptive immunity dominated the biomarker landscape. CONCLUSIONS: Nivolumab proved highly effective in advanced dMMR/MSI tumors. Expression of key innate immune receptors/ligands was the main predictor of good treatment outcome, contrasting findings in melanoma and strengthening the rationale for tumor-type specific biomarkers for guiding immunotherapy.

Platinum-Based Chemotherapy Induces Opposing Effects on Immunotherapy Response-Related Spatial and Stromal Biomarkers in the Bladder Cancer Microenvironment.

PURPOSE: Platinum-based chemotherapy and immune checkpoint inhibitors are key components of systemic treatment for muscle-invasive and advanced urothelial cancer. The ideal integration of these two treatment modalities remains unclear as clinical trials have led to inconsistent results. Modulation of the tumor-immune microenvironment by chemotherapy is poorly characterized. We aimed to investigate this modulation, focusing on potential clinical implications for immune checkpoint inhibitor response. EXPERIMENTAL DESIGN: We assessed immune cell densities, spatial relations, and tumor/stromal components from 116 patients with urothelial bladder cancer (paired data for 95 patients) before and after platinum-based chemotherapy. RESULTS: Several published biomarkers for immunotherapy response changed upon chemotherapy treatment. The intratumoral CD8+ T-cell percentage increased after treatment and was associated with increased TNFα-via-NF-κB signaling. The percentage of PDL1+ immune cells was higher after chemotherapy. An increase in chemo-induced changes that potentially inhibit an antitumor immune response was also observed, including increased fibroblast-based TGFß signaling and distances from immune cells to the nearest cancer cell. The latter two parameters correlated significantly in posttreatment samples, suggesting that TGFß signaling in fibroblasts may play a role in spatially separating immune cells from cancer cells. We examined specific chemotherapy regimens and found that treatment with methotrexate, vinblastine, doxorubicin, and cisplatin was associated with an increase in the macrophage cell percentage. Gemcitabine-containing chemotherapy was associated with upregulation of fibroblast TGFß signaling. CONCLUSIONS: The opposing effects of platinum-based chemotherapy on the immune cell composition and stromal context of the tumor-immune microenvironment may explain the inconsistent results of clinical trials investigating chemotherapy and immune checkpoint inhibitor combinations in bladder cancer.

DNA damage induces p53-independent apoptosis through ribosome stalling.

In response to excessive DNA damage, human cells can activate p53 to induce apoptosis. Cells lacking p53 can still undergo apoptosis upon DNA damage, yet the responsible pathways are unknown. We observed that p53-independent apoptosis in response to DNA damage coincided with translation inhibition, which was characterized by ribosome stalling on rare leucine-encoding UUA codons and globally curtailed translation initiation. A genetic screen identified the transfer RNAse SLFN11 and the kinase GCN2 as factors required for UUA stalling and global translation inhibition, respectively. Stalled ribosomes activated a ribotoxic stress signal conveyed by the ribosome sensor ZAKα to the apoptosis machinery. These results provide an explanation for the frequent inactivation of SLFN11 in chemotherapy-unresponsive tumors and highlight ribosome stalling as a signaling event affecting cell fate in response to DNA damage.

Efficacy of Pembrolizumab and Biomarker Analysis in Patients with WGS-Based Intermediate to High Tumor Mutational Load: Results from the Drug Rediscovery Protocol.

PURPOSE: To evaluate the efficacy of pembrolizumab across multiple cancer types harboring different levels of whole-genome sequencing-based tumor mutational load (TML; total of nonsynonymous mutations across the genome) in patients included in the Drug Rediscovery Protocol (NCT02925234). PATIENTS AND METHODS: Patients with solid, treatment-refractory, microsatellite-stable tumors were enrolled in cohort A: breast cancer cohort harboring a TML of 140 to 290, cohort B: tumor-agnostic cohort harboring a TML of 140 to 290, and cohort C: tumor-agnostic cohort harboring a TML >290. Patients received pembrolizumab 200 mg every 3 weeks. The primary endpoint was clinical benefit [CB; objective response or stable disease (SD) ≥16 weeks]. Pretreatment tumor biopsies were obtained for whole-genome sequencing and RNA sequencing. RESULTS: Seventy-two evaluable patients with 26 different histotypes were enrolled. The CB rate was 13% in cohort A [3/24 with partial response (PR)], 21% in cohort B (3/24 with SD; 2/24 with PR), and 42% in cohort C (4/24 with SD; 6/24 with PR). In cohort C, neoantigen burden estimates and expression of inflammation and innate immune biomarkers were significantly associated with CB. Similar associations were not identified in cohorts A and B. In cohort A, CB was significantly associated with mutations in the chromatin remodeling gene PBRM1, whereas in cohort B, CB was significantly associated with expression of MICA/MICB and butyrophilins. CB and clonal TML were not significantly associated. CONCLUSIONS: Although pembrolizumab lacked activity in cohort A, cohorts B and C met the study's primary endpoint. Further research is warranted to refine the selection of patients with tumors harboring lower TMLs and may benefit from a focus on innate immunity. See related commentary by Hsu and Yen, p. 3652.

Spatial relationships in the urothelial and head and neck tumor microenvironment predict response to combination immune checkpoint inhibitors.

Immune checkpoint inhibitors (ICI) can achieve remarkable responses in urothelial cancer (UC), which may depend on tumor microenvironment (TME) characteristics. However, the relationship between the TME, usually characterized by immune cell density, and response to ICI is unclear. Here, we quantify the TME immune cell densities and spatial relationships (SRs) of 24 baseline UC samples, obtained before pre-operative combination ICI treatment, using multiplex immunofluorescence. We describe SRs by approximating the first nearest-neighbor distance distribution with a Weibull distribution and evaluate the association between TME metrics and ipilimumab+nivolumab response. Immune cell density does not discriminate between response groups. However, the Weibull SR metrics of CD8+ T cells or macrophages to their closest cancer cell positively associate with response. CD8+ T cells close to B cells are characteristic of non-response. We validate our SR response associations in a combination ICI cohort of head and neck tumors. Our data confirm that SRs, in contrast to density metrics, are strong biomarkers of response to pre-operative combination ICIs.

Evaluating the effectiveness of pre-operative diagnosis of ovarian cancer using minimally invasive liquid biopsies by combining serum human epididymis protein 4 and cell-free DNA in patients with an ovarian mass.

OBJECTIVE: To assess the feasibility of scalable, objective, and minimally invasive liquid biopsy-derived biomarkers such as cell-free DNA copy number profiles, human epididymis protein 4 (HE4), and cancer antigen 125 (CA125) for pre-operative risk assessment of early-stage ovarian cancer in a clinically representative and diagnostically challenging population and to compare the performance of these biomarkers with the Risk of Malignancy Index (RMI). METHODS: In this case-control study, we included 100 patients with an ovarian mass clinically suspected to be early-stage ovarian cancer. Of these 100 patients, 50 were confirmed to have a malignant mass (cases) and 50 had a benign mass (controls). Using WisecondorX, an algorithm used extensively in non-invasive prenatal testing, we calculated the benign-calibrated copy number profile abnormality score. This score represents how different a sample is from benign controls based on copy number profiles. We combined this score with HE4 serum concentration to separate cases and controls. RESULTS: Combining the benign-calibrated copy number profile abnormality score with HE4, we obtained a model with a significantly higher sensitivity (42% vs 0%; p<0.002) at 99% specificity as compared with the RMI that is currently employed in clinical practice. Investigating performance in subgroups, we observed especially large differences in the advanced stage and non-high-grade serous ovarian cancer groups. CONCLUSION: This study demonstrates that cell-free DNA can be successfully employed to perform pre-operative risk of malignancy assessment for ovarian masses; however, results warrant validation in a more extensive clinical study.

Combining Genomic Biomarkers to Guide Immunotherapy in Non-Small Cell Lung Cancer.

PURPOSE: The clinical value of STK11, KEAP1, and EGFR alterations for guiding immune checkpoint blockade (ICB) therapy in non-small cell lung cancer (NSCLC) remains controversial, as some patients with these proposed resistance biomarkers show durable ICB responses. More specific combinatorial biomarker approaches are urgently needed for this disease. EXPERIMENTAL DESIGN: To develop a combinatorial biomarker strategy with increased specificity for ICB unresponsiveness in NSCLC, we performed a comprehensive analysis of 254 patients with NSCLC treated with ligand programmed death-ligand 1 (PD-L1) blockade monotherapy, including a discovery cohort of 75 patients subjected to whole-genome sequencing (WGS), and an independent validation cohort of 169 patients subjected to tumor-normal large panel sequencing. The specificity of STK11/KEAP1/EGFR alterations for ICB unresponsiveness was assessed in the contexts of a low (<10 muts/Mb) or high (≥10 muts/Mb) tumor mutational burden (TMB). RESULTS: In low TMB cases, STK11/KEAP1/EGFR alterations were highly specific biomarkers for ICB resistance, with 0/15 (0.0%) and 1/34 (2.9%) biomarker-positive patients showing treatment benefit in the discovery and validation cohorts, respectively. This contrasted with high TMB cases, where 11/13 (85%) and 15/34 (44%) patients with at least one STK11/KEAP1/EGFR alteration showed durable treatment benefit in the discovery and validation cohorts, respectively. These findings were supported by analyses of progression-free survival and overall survival. CONCLUSIONS: The unexpected ICB responses in patients carrying resistance biomarkers in STK11, KEAP1, and EGFR were almost exclusively observed in patients with a high TMB. Considering these alterations in context, the TMB offered a highly specific combinatorial biomarker strategy for limiting overtreatment in NSCLC.

Distinct spatiotemporal dynamics of CD8+ T cell-derived cytokines in the tumor microenvironment.

Cells in the tumor microenvironment (TME) influence each other through secretion and sensing of soluble mediators, such as cytokines and chemokines. While signaling of interferon γ (IFNγ) and tumor necrosis factor α (TNFα) is integral to anti-tumor immune responses, our understanding of the spatiotemporal behavior of these cytokines is limited. Here, we describe a single cell transcriptome-based approach to infer which signal(s) an individual cell has received. We demonstrate that, contrary to expectations, CD8+ T cell-derived IFNγ is the dominant modifier of the TME relative to TNFα. Furthermore, we demonstrate that cell pools that show abundant IFNγ sensing are characterized by decreased expression of transforming growth factor ß (TGFß)-induced genes, consistent with IFNγ-mediated TME remodeling. Collectively, these data provide evidence that CD8+ T cell-secreted cytokines should be categorized into local and global tissue modifiers, and describe a broadly applicable approach to dissect cytokine and chemokine modulation of the TME.

MYC is a clinically significant driver of mTOR inhibitor resistance in breast cancer.

Targeting the PI3K-AKT-mTOR pathway is a promising therapeutic strategy for breast cancer treatment. However, low response rates and development of resistance to PI3K-AKT-mTOR inhibitors remain major clinical challenges. Here, we show that MYC activation drives resistance to mTOR inhibitors (mTORi) in breast cancer. Multiomic profiling of mouse invasive lobular carcinoma (ILC) tumors revealed recurrent Myc amplifications in tumors that acquired resistance to the mTORi AZD8055. MYC activation was associated with biological processes linked to mTORi response and counteracted mTORi-induced translation inhibition by promoting translation of ribosomal proteins. In vitro and in vivo induction of MYC conferred mTORi resistance in mouse and human breast cancer models. Conversely, AZD8055-resistant ILC cells depended on MYC, as demonstrated by the synergistic effects of mTORi and MYCi combination treatment. Notably, MYC status was significantly associated with poor response to everolimus therapy in metastatic breast cancer patients. Thus, MYC is a clinically relevant driver of mTORi resistance that may stratify breast cancer patients for mTOR-targeted therapies.

Multi-omics analysis reveals distinct non-reversion mechanisms of PARPi resistance in BRCA1- versus BRCA2-deficient mammary tumors.

BRCA1 and BRCA2 both function in DNA double-strand break repair by homologous recombination (HR). Due to their HR defect, BRCA1/2-deficient cancers are sensitive to poly(ADP-ribose) polymerase inhibitors (PARPis), but they eventually acquire resistance. Preclinical studies yielded several PARPi resistance mechanisms that do not involve BRCA1/2 reactivation, but their relevance in the clinic remains elusive. To investigate which BRCA1/2-independent mechanisms drive spontaneous resistance in vivo, we combine molecular profiling with functional analysis of HR of matched PARPi-naive and PARPi-resistant mouse mammary tumors harboring large intragenic deletions that prevent reactivation of BRCA1/2. We observe restoration of HR in 62% of PARPi-resistant BRCA1-deficient tumors but none in the PARPi-resistant BRCA2-deficient tumors. Moreover, we find that 53BP1 loss is the prevalent resistance mechanism in HR-proficient BRCA1-deficient tumors, whereas resistance in BRCA2-deficient tumors is mainly induced by PARG loss. Furthermore, combined multi-omics analysis identifies additional genes and pathways potentially involved in modulating PARPi response.

PD-L1 blockade in combination with carboplatin as immune induction in metastatic lobular breast cancer: the GELATO trial.

Invasive lobular breast cancer (ILC) is the second most common histological breast cancer subtype, but ILC-specific trials are lacking. Translational research revealed an immune-related ILC subset, and in mouse ILC models, synergy between immune checkpoint blockade and platinum was observed. In the phase II GELATO trial ( NCT03147040 ), patients with metastatic ILC were treated with weekly carboplatin (area under the curve 1.5 mg ml-1 min-1) as immune induction for 12 weeks and atezolizumab (PD-L1 blockade; triweekly) from the third week until progression. Four of 23 evaluable patients had a partial response (17%), and 2 had stable disease, resulting in a clinical benefit rate of 26%. From these six patients, four had triple-negative ILC (TN-ILC). We observed higher CD8+ T cell infiltration, immune checkpoint expression and exhausted T cells after treatment. With this GELATO trial, we show that ILC-specific clinical trials are feasible and demonstrate promising antitumor activity of atezolizumab with carboplatin, particularly for TN-ILC, and provide insights for the design of highly needed ILC-specific trials.

A living biobank of patient-derived ductal carcinoma in situ mouse-intraductal xenografts identifies risk factors for invasive progression.

Ductal carcinoma in situ (DCIS) is a non-obligate precursor of invasive breast cancer (IBC). Due to a lack of biomarkers able to distinguish high- from low-risk cases, DCIS is treated similar to early IBC even though the minority of untreated cases eventually become invasive. Here, we characterized 115 patient-derived mouse-intraductal (MIND) DCIS models reflecting the full spectrum of DCIS observed in patients. Utilizing the possibility to follow the natural progression of DCIS combined with omics and imaging data, we reveal multiple prognostic factors for high-risk DCIS including high grade, HER2 amplification, expansive 3D growth, and high burden of copy number aberrations. In addition, sequential transplantation of xenografts showed minimal phenotypic and genotypic changes over time, indicating that invasive behavior is an intrinsic phenotype of DCIS and supporting a multiclonal evolution model. Moreover, this study provides a collection of 19 distributable DCIS-MIND models spanning all molecular subtypes.

ecpc: an R-package for generic co-data models for high-dimensional prediction.

BACKGROUND: High-dimensional prediction considers data with more variables than samples. Generic research goals are to find the best predictor or to select variables. Results may be improved by exploiting prior information in the form of co-data, providing complementary data not on the samples, but on the variables. We consider adaptive ridge penalised generalised linear and Cox models, in which the variable-specific ridge penalties are adapted to the co-data to give a priori more weight to more important variables. The R-package ecpc originally accommodated various and possibly multiple co-data sources, including categorical co-data, i.e. groups of variables, and continuous co-data. Continuous co-data, however, were handled by adaptive discretisation, potentially inefficiently modelling and losing information. As continuous co-data such as external p values or correlations often arise in practice, more generic co-data models are needed. RESULTS: Here, we present an extension to the method and software for generic co-data models, particularly for continuous co-data. At the basis lies a classical linear regression model, regressing prior variance weights on the co-data. Co-data variables are then estimated with empirical Bayes moment estimation. After placing the estimation procedure in the classical regression framework, extension to generalised additive and shape constrained co-data models is straightforward. Besides, we show how ridge penalties may be transformed to elastic net penalties. In simulation studies we first compare various co-data models for continuous co-data from the extension to the original method. Secondly, we compare variable selection performance to other variable selection methods. The extension is faster than the original method and shows improved prediction and variable selection performance for non-linear co-data relations. Moreover, we demonstrate use of the package in several genomics examples throughout the paper. CONCLUSIONS: The R-package ecpc accommodates linear, generalised additive and shape constrained additive co-data models for the purpose of improved high-dimensional prediction and variable selection. The extended version of the package as presented here (version number 3.1.1 and higher) is available on ( https://cran.r-project.org/web/packages/ecpc/ ).

Codon-specific KRAS mutations predict survival benefit of trifluridine/tipiracil in metastatic colorectal cancer.

Genomics has greatly improved how patients with cancer are being treated; however, clinical-grade genomic biomarkers for chemotherapies are currently lacking. Using whole-genome analysis of 37 patients with metastatic colorectal cancer (mCRC) treated with the chemotherapy trifluridine/tipiracil (FTD/TPI), we identified KRAS codon G12 (KRASG12) mutations as a potential biomarker of resistance. Next, we collected real-world data of 960 patients with mCRC receiving FTD/TPI and validated that KRASG12 mutations were significantly associated with poor survival, also in analyses restricted to the RAS/RAF mutant subgroup. We next analyzed the data of the global, double-blind, placebo-controlled, phase 3 RECOURSE trial (n = 800 patients) and found that KRASG12 mutations (n = 279) were predictive biomarkers for reduced overall survival (OS) benefit of FTD/TPI versus placebo (unadjusted interaction P = 0.0031, adjusted interaction P = 0.015). For patients with KRASG12 mutations in the RECOURSE trial, OS was not prolonged with FTD/TPI versus placebo (n = 279; hazard ratio (HR) = 0.97; 95% confidence interval (CI) = 0.73-1.20; P = 0.85). In contrast, patients with KRASG13 mutant tumors showed significantly improved OS with FTD/TPI versus placebo (n = 60; HR = 0.29; 95% CI = 0.15-0.55; P < 0.001). In isogenic cell lines and patient-derived organoids, KRASG12 mutations were associated with increased resistance to FTD-based genotoxicity. In conclusion, these data show that KRASG12 mutations are biomarkers for reduced OS benefit of FTD/TPI treatment, with potential implications for approximately 28% of patients with mCRC under consideration for treatment with FTD/TPI. Furthermore, our data suggest that genomics-based precision medicine may be possible for a subset of chemotherapies.

Tumour-educated platelets for breast cancer detection: biological and technical insights.

BACKGROUND: Studies have shown that blood platelets contain tumour-specific mRNA profiles tumour-educated platelets (TEPs). Here, we aim to train a TEP-based breast cancer detection classifier. METHODS: Platelet mRNA was sequenced from 266 women with stage I-IV breast cancer and 212 female controls from 6 hospitals. A particle swarm optimised support vector machine (PSO-SVM) and an elastic net-based classifier (EN) were trained on 71% of the study population. Classifier performance was evaluated in the remainder (29%) of the population, followed by validation in an independent set (37 cases and 36 controls). Potential confounding was assessed in post hoc analyses. RESULTS: Both classifiers reached an area under the curve (AUC) of 0.85 upon internal validation. Reproducibility in the independent validation set was poor with an AUC of 0.55 and 0.54 for the PSO-SVM and EN classifier, respectively. Post hoc analyses indicated that 19% of the variance in gene expression was associated with hospital. Genes related to platelet activity were differentially expressed between hospitals. CONCLUSIONS: We could not validate two TEP-based breast cancer classifiers in an independent validation cohort. The TEP protocol is sensitive to within-protocol variation and revision might be necessary before TEPs can be reconsidered for breast cancer detection.