PROACTING: predicting pathological complete response to neoadjuvant chemotherapy in breast cancer from routine diagnostic histopathology biopsies with deep learning.

BACKGROUND: Invasive breast cancer patients are increasingly being treated with neoadjuvant chemotherapy; however, only a fraction of the patients respond to it completely. To prevent overtreatment, there is an urgent need for biomarkers to predict treatment response before administering the therapy. METHODS: In this retrospective study, we developed hypothesis-driven interpretable biomarkers based on deep learning, to predict the pathological complete response (pCR, i.e., the absence of tumor cells in the surgical resection specimens) to neoadjuvant chemotherapy solely using digital pathology H&E images of pre-treatment breast biopsies. Our approach consists of two steps: First, we use deep learning to characterize aspects of the tumor micro-environment by detecting mitoses and segmenting tissue into several morphology compartments including tumor, lymphocytes and stroma. Second, we derive computational biomarkers from the segmentation and detection output to encode slide-level relationships of components of the tumor microenvironment, such as tumor and mitoses, stroma, and tumor infiltrating lymphocytes (TILs). RESULTS: We developed and evaluated our method on slides from n = 721 patients from three European medical centers with triple-negative and Luminal B breast cancers and performed external independent validation on n = 126 patients from a public dataset. We report the predictive value of the investigated biomarkers for predicting pCR with areas under the receiver operating characteristic curve between 0.66 and 0.88 across the tested cohorts. CONCLUSION: The proposed computational biomarkers predict pCR, but will require more evaluation and finetuning for clinical application. Our results further corroborate the potential role of deep learning to automate TILs quantification, and their predictive value in breast cancer neoadjuvant treatment planning, along with automated mitoses quantification. We made our method publicly available to extract segmentation-based biomarkers for research purposes.

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.

Prognostic value of histopathological DCIS features in a large-scale international interrater reliability study.

PURPOSE: For optimal management of ductal carcinoma in situ (DCIS), reproducible histopathological assessment is essential to distinguish low-risk from high-risk DCIS. Therefore, we analyzed interrater reliability of histopathological DCIS features and assessed their associations with subsequent ipsilateral invasive breast cancer (iIBC) risk. METHODS: Using a case-cohort design, reliability was assessed in a population-based, nationwide cohort of 2767 women with screen-detected DCIS diagnosed between 1993 and 2004, treated by breast-conserving surgery with/without radiotherapy (BCS ± RT) using Krippendorff's alpha (KA) and Gwet's AC2 (GAC2). Thirty-eight raters scored histopathological DCIS features including grade (2-tiered and 3-tiered), growth pattern, mitotic activity, periductal fibrosis, and lymphocytic infiltrate in 342 women. Using majority opinion-based scores for each feature, their association with subsequent iIBC risk was assessed using Cox regression. RESULTS: Interrater reliability of grade using various classifications was fair to moderate, and only substantial for grade 1 versus 2 + 3 when using GAC2 (0.78). Reliability for growth pattern (KA 0.44, GAC2 0.78), calcifications (KA 0.49, GAC2 0.70) and necrosis (KA 0.47, GAC2 0.70) was moderate using KA and substantial using GAC2; for (type of) periductal fibrosis and lymphocytic infiltrate fair to moderate estimates were found and for mitotic activity reliability was substantial using GAC2 (0.70). Only in patients treated with BCS-RT, high mitotic activity was associated with a higher iIBC risk in univariable analysis (Hazard Ratio (HR) 2.53, 95% Confidence Interval (95% CI) 1.05-6.11); grade 3 versus 1 + 2 (HR 2.64, 95% CI 1.35-5.14) and a cribriform/solid versus flat epithelial atypia/clinging/(micro)papillary growth pattern (HR 3.70, 95% CI 1.34-10.23) were independently associated with a higher iIBC risk. CONCLUSIONS: Using majority opinion-based scores, DCIS grade, growth pattern, and mitotic activity are associated with iIBC risk in patients treated with BCS-RT, but interrater variability is substantial. Semi-quantitative grading, incorporating and separately evaluating nuclear pleomorphism, growth pattern, and mitotic activity, may improve the reliability and prognostic value of these features.

Next generation sequencing of triple negative breast cancer to find predictors for chemotherapy response.

INTRODUCTION: In triple negative breast cancers (TNBC) the initial response to chemotherapy is often favorable, but relapse and chemotherapy resistance frequently occur in advanced disease. Hence there is an urgent need for targeted treatments in this breast cancer subtype. In the current study we deep sequenced DNA of tumors prior to chemotherapy to search for predictors of response or resistance. METHODS: Next generation sequencing (NGS) was performed for 1,977 genes involved in tumorigenesis. DNA from 56 pre-treatment TNBC-biopsies was sequenced, as well as matched normal DNA. Following their tumor biopsy, patients started neoadjuvant chemotherapy with doxorubicin and cyclophosphamide. We studied associations between genetic alterations and three clinical variables: chemotherapy response, relapse-free survival and BRCA proficiency. RESULTS: The mutations observed were diverse and few recurrent mutations were detected. Most mutations were in TP53, TTN, and PIK3CA (55 %, 14 %, and 9 %, respectively). The mutation rates were similar between responders and non-responders (average mutation rate 9 vs 8 mutations). No recurrent mutations were associated with chemotherapy response or relapse. Interestingly, PIK3CA mutations were exclusively observed in patients proficient for BRCA1. Samples with a relapse had a higher copy number alteration rate, and amplifications of TTK and TP53BP2 were associated with a poor chemotherapy response. CONCLUSIONS: In this homogenous cohort of TNBCs few recurrent mutations were found. However, PIK3CA mutations were associated with BRCA proficiency, which can have clinical consequences in the near future.

SERPINA6, BEX1, AGTR1, SLC26A3, and LAPTM4B are markers of resistance to neoadjuvant chemotherapy in HER2-negative breast cancer.

Response rates to chemotherapy remain highly variable in breast cancer patients. We set out to identify genes associated with chemotherapy resistance. We analyzed what is currently the largest single-institute set of gene expression profiles derived from breast cancers prior to a single neoadjuvant chemotherapy regimen (dose-dense doxorubicin and cyclophosphamide). We collected, gene expression-profiled, and analyzed 178 HER2-negative breast tumor biopsies ("NKI dataset"). We employed a recently developed approach for detecting imbalanced differential signal (DIDS) to identify markers of resistance to treatment. In contrast to traditional methods, DIDS is able to identify markers that show aberrant expression in only a small subgroup of the non-responder samples. We found a number of markers of resistance to anthracycline-based chemotherapy. We validated our findings in three external datasets, totaling 456 HER2-negative samples. Since these external sets included patients who received differing treatment regimens, the validated markers represent markers of general chemotherapy resistance. There was a highly significant overlap in the markers identified in the NKI dataset and the other three datasets. Five resistance markers, SERPINA6, BEX1, AGTR1, SLC26A3, and LAPTM4B, were identified in three of the four datasets (p value overlap < 1 × 10(-6)). These five genes identified resistant tumors that could not have been identified by merely taking ER status or proliferation into account. The identification of these genes might lead to a better understanding of the mechanisms involved in (clinically) observed chemotherapy resistance and could possibly assist in the recognition of breast cancers in which chemotherapy does not contribute to response or survival.

Platform comparisons for identification of breast cancers with a BRCA-like copy number profile.

Previously, we employed bacterial artificial chromosome (BAC) array comparative genomic hybridization (aCGH) profiles from BRCA1 and -2 mutation carriers and sporadic tumours to construct classifiers that identify tumour samples most likely to harbour BRCA1 and -2 mutations, designated 'BRCA1 and -2-like' tumours, respectively. The classifiers are used in clinical genetics to evaluate unclassified variants, and patients for which no good quality germline DNA is available. Furthermore, we have shown that breast cancer patients with BRCA-like tumour aCGH profiles benefit substantially from platinum-based chemotherapy, potentially due to their inability to repair DNA double strand breaks (DSB), providing a further important clinical application for the classifiers. The BAC array technology has been replaced with oligonucleotide arrays. To continue clinical use of existing classifiers, we mapped oligonucleotide aCGH data to the BAC domain, such that the oligonucleotide profiles can be employed as in the BAC classifier. We demonstrate that segmented profiles derived from oligonucleotide aCGH show high correlation with BAC aCGH profiles. Furthermore, we trained a support vector machine score to objectify aCGH profile quality. Using the mapped oligonucleotide aCGH data, we show equivalence in classification of biologically relevant cases between BAC and oligonucleotide data. Furthermore, the predicted benefit of DSB inducing chemotherapy due to a homologous recombination defect is retained. We conclude that oligonucleotide aCGH data can be mapped to and used in the previously developed and validated BAC aCGH classifiers. Our findings suggest that it is possible to map copy number data from any other technology in a similar way.

High-dose alkylating chemotherapy in BRCA-altered triple-negative breast cancer: the randomized phase III NeoTN trial.

Exploratory analyses of high-dose alkylating chemotherapy trials have suggested that BRCA1 or BRCA2-pathway altered (BRCA-altered) breast cancer might be particularly sensitive to this type of treatment. In this study, patients with BRCA-altered tumors who had received three initial courses of dose-dense doxorubicin and cyclophosphamide (ddAC), were randomized between a fourth ddAC course followed by high-dose carboplatin-thiotepa-cyclophosphamide or conventional chemotherapy (initially ddAC only or ddAC-capecitabine/decetaxel [CD] depending on MRI response, after amendment ddAC-carboplatin/paclitaxel [CP] for everyone). The primary endpoint was the neoadjuvant response index (NRI). Secondary endpoints included recurrence-free survival (RFS) and overall survival (OS). In total, 122 patients were randomized. No difference in NRI-score distribution (p = 0.41) was found. A statistically non-significant RFS difference was found (HR 0.54; 95% CI 0.23-1.25; p = 0.15). Exploratory RFS analyses showed benefit in stage III (n = 35; HR 0.16; 95% CI 0.03-0.75), but not stage II (n = 86; HR 1.00; 95% CI 0.30-3.30) patients. For stage III, 4-year RFS was 46% (95% CI 24-87%), 71% (95% CI 48-100%) and 88% (95% CI 74-100%), for ddAC/ddAC-CD, ddAC-CP and high-dose chemotherapy, respectively. No significant differences were found between high-dose and conventional chemotherapy in stage II-III, triple-negative, BRCA-altered breast cancer patients. Further research is needed to establish if there are patients with stage III, triple negative BRCA-altered breast cancer for whom outcomes can be improved with high-dose alkylating chemotherapy or whether the current standard neoadjuvant therapy including carboplatin and an immune checkpoint inhibitor is sufficient. Trial Registration: NCT01057069.

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.

Genomic signature of BRCA1 deficiency in sporadic basal-like breast tumors.

About 10-20% of all breast carcinomas show a basal-like phenotype, while ∼ 90% of breast tumors from BRCA1-mutation carriers are of this subtype. There is growing evidence that BRCA1-mutated tumors are not just a specific subset of the basal-like tumors, but that (the majority of) basal-like tumors show a dysfunctional BRCA1 pathway. This has major treatment implications, because emerging regimens specifically targeting DNA repair mechanisms would then be most effective against these tumors. To further understand the involvement of BRCA1 deficiency in sporadic basal-like tumors, we investigated 41 basal-like tumors for BRCA1 mRNA expression by quantitative real-time polymerase chain reaction, BRCA1 promoter methylation, their genomic profile by array-CGH, and gene expression levels by whole genome expression arrays. Array-CGH results were compared to those of 34 proven BRCA1-mutated tumors. Basal-like tumors were subdivided into two equal groups: deficient and proficient in BRCA1 gene expression. The chromosomal makeup of BRCA1 deficient sporadic basal-like tumors was similar to that of BRCA1-mutated tumors. BRCA1 proficient sporadic basal-like tumors were more similar to nonbasal-like tumors. Only half of the basal-like breast tumors are actually deficient in BRCA1 expression. Gain of chromosome arm 3q is a marker for BRCA1 deficiency in hereditary and sporadic breast tumors.

Comprehensive characterization of pre- and post-treatment samples of breast cancer reveal potential mechanisms of chemotherapy resistance.

When locally advanced breast cancer is treated with neoadjuvant chemotherapy, the recurrence risk is significantly higher if no complete pathologic response is achieved. Identification of the underlying resistance mechanisms is essential to select treatments with maximal efficacy and minimal toxicity. Here we employed gene expression profiles derived from 317 HER2-negative treatment-naïve breast cancer biopsies of patients who underwent neoadjuvant chemotherapy, deep whole exome, and RNA-sequencing profiles of 22 matched pre- and post-treatment tumors, and treatment outcome data to identify biomarkers of response and resistance mechanisms. Molecular profiling of treatment-naïve breast cancer samples revealed that expression levels of proliferation, immune response, and extracellular matrix (ECM) organization combined predict response to chemotherapy. Triple negative patients with high proliferation, high immune response and low ECM expression had a significantly better treatment response and survival benefit (HR 0.29, 95% CI 0.10-0.85; p = 0.02), while in ER+ patients the opposite was seen (HR 4.73, 95% CI 1.51-14.8; p = 0.008). The characterization of paired pre-and post-treatment samples revealed that aberrations of known cancer genes were either only present in the pre-treatment sample (CDKN1B) or in the post-treatment sample (TP53, APC, CTNNB1). Proliferation-associated genes were frequently down-regulated in post-treatment ER+ tumors, but not in triple negative tumors. Genes involved in ECM were upregulated in the majority of post-chemotherapy samples. Genomic and transcriptomic differences between pre- and post-chemotherapy samples are common and may reveal potential mechanisms of therapy resistance. Our results show a wide range of distinct, but related mechanisms, with a prominent role for proliferation- and ECM-related genes.

Genomic analysis defines clonal relationships of ductal carcinoma in situ and recurrent invasive breast cancer.

Ductal carcinoma in situ (DCIS) is the most common form of preinvasive breast cancer and, despite treatment, a small fraction (5-10%) of DCIS patients develop subsequent invasive disease. A fundamental biologic question is whether the invasive disease arises from tumor cells in the initial DCIS or represents new unrelated disease. To address this question, we performed genomic analyses on the initial DCIS lesion and paired invasive recurrent tumors in 95 patients together with single-cell DNA sequencing in a subset of cases. Our data show that in 75% of cases the invasive recurrence was clonally related to the initial DCIS, suggesting that tumor cells were not eliminated during the initial treatment. Surprisingly, however, 18% were clonally unrelated to the DCIS, representing new independent lineages and 7% of cases were ambiguous. This knowledge is essential for accurate risk evaluation of DCIS, treatment de-escalation strategies and the identification of predictive biomarkers.

Concordance of clinical and molecular breast cancer subtyping in the context of preoperative chemotherapy response.

ER, PR and HER2 status in breast cancer are important markers for the selection of drug therapy. By immunohistochemistry (IHC), three major breast cancer subtypes can be distinguished: Triple negative (TN(IHC)), HER2+(IHC) and Luminal(IHC) (ER+(IHC)/HER2-(IHC)). By using the intrinsic gene set defined by Hu et al. five molecular subtypes (Basal(mRNA), HER2+(mRNA), Luminal A(mRNA), Luminal B(mRNA) and Normal-like(mRNA)) can be defined. We studied the concordance between analogous subtypes and their prediction of response to neoadjuvant chemotherapy. We classified 195 breast tumors by both IHC and mRNA expression analysis of patients who received neoadjuvant treatment at the Netherlands Cancer institute for Stage II-III breast cancer between 2000 and 2007. The pathological complete remission (pCR) rate was used to assess chemotherapy response. The IHC and molecular subtypes showed high concordance with the exception of the HER2+(IHC) group. 60% of the HER2+(IHC) tumors were not classified as HER2+(mRNA). The HER2+(IHC)/Luminal A or B(mRNA) group had a low response rate to a trastuzumab-chemotherapy combination with a pCR rate of 8%, while the HER2+(mRNA) group had a pCR rate of 54%. The Luminal A(mRNA) and Luminal B(mRNA) groups showed similar degrees of response to chemotherapy. Neither the PR status nor the endocrine responsiveness index subdivided the ER+(IHC) tumors accurately into Luminal A(mRNA) and Luminal B(mRNA) groups. Molecular subtyping suggests the existence of a HER2+(IHC)/Luminal(mRNA) group that responds poorly to trastuzumab-based chemotherapy. For Luminal(IHC) and triple negative(IHC) tumors, further subdivision into molecular subgroups does not offer a clear advantage in treatment selection.

BRCA1-Mutated Estrogen Receptor-Positive Breast Cancer Shows BRCAness, Suggesting Sensitivity to Drugs Targeting Homologous Recombination Deficiency.

Purpose: As estrogen receptor-positive (ER+) breast cancer in BRCA1 mutation carriers arises at an older age with less aggressive tumor characteristics than ER-negative (ER-) BRCA1-mutated breast cancer, it has been suggested that these tumors are "sporadic" and not BRCA1 driven. With the introduction of targeted treatments specific for tumors with a nonfunctioning BRCA1 or BRCA2 gene, the question whether the BRCA genes are impaired in the tumor is highly relevant. Therefore, we performed genomic profiling of BRCA1-mutated ER+ tumors.Experimental Design: Genomic profiling, BRCA1 promoter methylation assessment, and loss of heterozygosity analysis were done on 16 BRCA1-mutated ER+ tumors. Results were compared with 57 BRCA1-mutated ER- tumors, 36 BRCA2-mutated ER+-associated tumors, and 182 sporadic ER+ tumors.Results: The genomic profile of BRCA1-mutated ER+ tumors was different from BRCA1-mutated ER- breast tumors, but highly similar to BRCA2-mutated ER+ tumors. In 83% of the BRCA1-mutated ER+ tumors, loss of the wild-type BRCA1 allele was observed. In addition, clinicopathologic variables in BRCA1-mutated ER+ cancer were also more similar to BRCA2-mutated ER+ and sporadic ER+ breast cancer than to BRCA1-mutated ER- cancers.Conclusions: As BRCA1-mutated ER+ tumors show a BRCAness copy number profile and LOH, it is likely that the loss of a functional BRCA1 protein plays a role in tumorigenesis in BRCA1-mutated ER+ tumors. Therefore, we hypothesize that these tumors are sensitive to drugs targeting the BRCA1 gene defect, providing new targeted treatment modalities for advanced BRCA-deficient, ER+ breast cancer. Clin Cancer Res; 23(5); 1236-41. ©2016 AACR.

Evaluation of the EGFR polymorphism R497K in two cohorts of neoadjuvantly treated breast cancer patients.

Pathological response of breast cancer to neoadjuvant chemotherapy (NAC) presents great variability, and new prognostic biomarkers are needed. Our aim was to evaluate the association of the epidermal growth factor receptor gene (EGFR) polymorphism R497K (rs2227983) with prognostic features and clinical outcomes of breast cancer, including the pathological response to NAC and the recurrence-free survival (RFS). Tumoral complete response (tCR) was defined by no remaining invasive cancer in the excised breast, whereas pathological complete response (pCR) was defined by no remaining invasive cancer both in the excised breast and lymph nodes. Two independent cohorts were analyzed: one from Brazil (INCA, n = 288) and one from The Netherlands (NKI-AVL, n = 255). In the INCA cohort, the variant (Lys-containing) genotypes were significantly associated with lower proportion of tCR (ORadj = 0.92; 95%CI = 0.85-0.99), whereas in the NKI-AVL cohort they were associated with tumor grade 3 (p = 0.035) and with triple-negative subtype (p = 0.032), but not with clinical outcomes. Such distinct prognostic associations may have arisen due to different neoadjuvant protocols (p < 0.001), or to lower age at diagnosis (p < 0.001) and higher proportion of tumor grade 3 (p = 0.018) at the NKI-AVL cohort. Moreover, NKI-AVL patients achieved better proportion of pCR (21.2% vs 8.3%, p < 0.001) and better RFS (HRadj = 0.48; 95% adjCI = 0.26-0.86) than patients from INCA. In conclusion, large scale studies comprehending different populations are needed to evaluate the impact of genome variants on breast cancer outcomes.

Mechanisms of Therapy Resistance in Patient-Derived Xenograft Models of BRCA1-Deficient Breast Cancer.

BACKGROUND: Although BRCA1-deficient tumors are extremely sensitive to DNA-damaging drugs and poly(ADP-ribose) polymerase (PARP) inhibitors, recurrences do occur and, consequently, resistance to therapy remains a serious clinical problem. To study the underlying mechanisms, we induced therapy resistance in patient-derived xenograft (PDX) models of BRCA1-mutated and BRCA1-methylated triple-negative breast cancer. METHODS: A cohort of 75 mice carrying BRCA1-deficient breast PDX tumors was treated with cisplatin, melphalan, nimustine, or olaparib, and treatment sensitivity was determined. In tumors that acquired therapy resistance, BRCA1 expression was investigated using quantitative real-time polymerase chain reaction and immunoblotting. Next-generation sequencing, methylation-specific multiplex ligation-dependent probe amplification (MLPA) and Target Locus Amplification (TLA)-based sequencing were used to determine mechanisms of BRCA1 re-expression in therapy-resistant tumors. RESULTS: BRCA1 protein was not detected in therapy-sensitive tumors but was found in 31 out of 42 resistant cases. Apart from previously described mechanisms involving BRCA1-intragenic deletions and loss of BRCA1 promoter hypermethylation, a novel resistance mechanism was identified in four out of seven BRCA1-methylated PDX tumors that re-expressed BRCA1 but retained BRCA1 promoter hypermethylation. In these tumors, we found de novo gene fusions that placed BRCA1 under the transcriptional control of a heterologous promoter, resulting in re-expression of BRCA1 and acquisition of therapy resistance. CONCLUSIONS: In addition to previously described clinically relevant resistance mechanisms in BRCA1-deficient tumors, we describe a novel resistance mechanism in BRCA1-methylated PDX tumors involving de novo rearrangements at the BRCA1 locus, demonstrating that BRCA1-methylated breast cancers may acquire therapy resistance via both epigenetic and genetic mechanisms.

BRCA1 loss preexisting in small subpopulations of prostate cancer is associated with advanced disease and metastatic spread to lymph nodes and peripheral blood.

PURPOSE: A preliminary study performed on a small cohort of multifocal prostate cancer (PCa) detected BRCA1 allelic imbalances among circulating tumor cells (CTC). The present analysis was aimed to elucidate the biological and clinical roles of BRCA1 losses in metastatic spread and tumor progression in PCa patients. EXPERIMENTAL DESIGN: To map molecular progression in PCa outgrowth, we used fluorescence in situ hybridization analysis of primary tumors and lymph node sections, and CTCs from peripheral blood. RESULTS: We found that 14% of 133 tested patients carried monoallelic BRCA1 loss in at least one tumor focus. Extended molecular analysis of chr17q revealed that this aberration was often a part of larger cytogenetic rearrangement involving chr17q21 accompanied by allelic imbalance of the tumor suppressor gene PTEN and lack of BRCA1 promoter methylation. The BRCA1 losses correlated with advanced T stage (P < 0.05), invasion to pelvic lymph nodes (P < 0.05), as well as biochemical recurrence (P < 0.01). Their prevalence was twice as high within 62 lymph node metastases (LNM) as in primary tumors (27%, P < 0.01). The analysis of 11 matched primary PCa-LNM pairs confirmed the suspected transmission of genetic abnormalities between these two sites. In four of seven patients with metastatic disease, BRCA1 losses appeared in a minute fraction of cytokeratin- and vimentin-positive CTCs. CONCLUSIONS: Small subpopulations of PCa cells bearing BRCA1 losses might be one confounding factor initiating tumor dissemination and might provide an early indicator of shortened disease-free survival.