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The goal of this study was to identify a novel target for antibody-drug conjugate (ADC) development in triple negative breast cancer (TNBC), which has limited treatment options, using gene expression datasets and in vitro siRNA/CRISPR and in vivo functional assays. We analyzed 4467 breast cancers and identified GABRP as top expressed gene in TNBC with low expression in most normal tissues. GABRP protein was localized to cell membrane with broad range of receptors/cell (815–53,714) and expressed by nearly half of breast cancers tissues. GABRP gene knockdown inhibited TNBC cell growth and colony formation in vitro and growth of MDA-MB-468 xenografts in nude mice. Commercially available anti-GABRP antibody (5–100 μg/ml) or de novo generated Fabs (20 μg/ml) inhibited TNBC cell growth in vitro. The same antibody conjugated to mertansine (DM1) also showed significant anticancer activity at nanomolar concentrations. Our results indicate that GABRP is a potential novel therapeutic target for ADC development.
Background: Remodeling of extracellular matrix through collagen degradation is a crucial step in the metastatic cascade. The aim of this study was to evaluate the potential clinical relevance of the serum collagen degradation markers (CDM) C3M and C4M during neoadjuvant chemotherapy for breast cancer.
Methods: Patients from the GeparQuinto phase 3 trial with untreated HER2-positive operable or locally advanced breast cancer were enrolled between 7 November 2007, and 9 July 2010, and randomly assigned to receive neoadjuvant treatment with EC/docetaxel with either trastuzumab or lapatinib. Blood samples were collected at baseline, after four cycles of chemotherapy and at surgery. Cutoff values were determined using validated cutoff finder software (C3M: Low ≤9.00 ng/mL, high >9.00 ng/mL, C4M: Low ≤40.91 ng/mL, high >40.91 ng/mL).
Results: 157 patients were included in this analysis. At baseline, 11.7% and 14.8% of patients had high C3M and C4M serum levels, respectively. No correlation was observed between CDM and classical clinical-pathological factors. Patients with high levels of CDM were significantly more likely to achieve a pathological complete response (pCR, defined as ypT0 ypN0) than patients with low levels (C3M: 66.7% vs. 25.7%, p = 0.002; C4M: 52.7% vs. 26.6%, p = 0.031). Median levels of both markers were lower at the time of surgery than at baseline. In the multivariate analysis including clinical-pathological factors and C3M levels at baseline and changes in C3M levels between baseline and after four cycles of therapy, only C3M levels at baseline (p = 0.035, OR 4.469, 95%-CI 1.115–17.919) independently predicted pCR. In a similar model including clinical-pathological factors and C4M, only C4M levels at baseline (p = 0.028, OR 6.203, 95%-CI 1.220–31.546) and tumor size (p = 0.035, OR 4.900, 95%-CI 1.122–21.393) were independent predictors of pCR. High C3M levels at baseline did not correlate with survival in the entire cohort but were associated with worse disease-free survival (DFS; p = 0.029, 5-year DFS 40.0% vs. 74.9%) and overall survival (OS; p = 0.020, 5-year OS 60.0% vs. 88.3%) in the subgroup of patients randomized to lapatinib. In the trastuzumab arm, C3M did not correlate with survival. In the entire patient cohort, high levels of C4M at baseline were significantly associated with shorter DFS (p = 0.001, 5-year DFS 53.1% vs. 81.6%) but not with OS. When treatment arms were considered separately, the association with DFS was still significant (p = 0.014, 5-year DFS 44.4% vs. 77.0% in the lapatinib arm; p = 0.023, 5-year DFS 62.5% vs. 86.2% in the trastuzumab arm).
Conclusions: Collagen degradation markers are associated with response to neoadjuvant therapy and seem to play a role in breast cancer.
Background: The focus of this study is to identify particular microRNA (miRNA) signatures in exosomes derived from plasma of 435 human epidermal growth factor receptor 2 (HER2)-positive and triple-negative (TN) subtypes of breast cancer (BC).
Methods: First, miRNA expression profiles were determined in exosomes derived from the plasma of 15 TNBC patients before neoadjuvant therapy using a quantitative TaqMan real-time PCR-based microRNA array card containing 384 different miRNAs. Forty-five miRNAs associated with different clinical parameters were then selected and mounted on microRNA array cards that served for the quantification of exosomal miRNAs in 435 BC patients before therapy and 20 healthy women. Confocal microscopy, Western blot, and ELISA were used for exosome characterization.
Results: Quantification of 45 exosomal miRNAs showed that compared with healthy women, 10 miRNAs in the entire cohort of BC patients, 13 in the subgroup of 211 HER2-positive BC, and 17 in the subgroup of 224 TNBC were significantly deregulated. Plasma levels of 18 exosomal miRNAs differed between HER2-positive and TNBC subtypes, and 9 miRNAs of them also differed from healthy women. Exosomal miRNAs were significantly associated with the clinicopathological and risk factors. In uni- and multivariate models, miR-155 (p = 0.002, p = 0.003, respectively) and miR-301 (p = 0.002, p = 0.001, respectively) best predicted pathological complete response (pCR).
Conclusion: Our findings show a network of deregulated exosomal miRNAs with specific expression patterns in exosomes of HER2-positive and TNBC patients that are also associated with clinicopathological parameters and pCR within each BC subtype.
Brustkrebs ist die häufigste Krebserkrankung und Todesursache bei Frauen. Die Forschung der letzten Jahrzehnte hat gezeigt, dass es sich dabei nicht um eine einzelne, immer gleich verlaufende Erkrankung handelt. Vielmehr geht man heute davon aus, dass Brustkrebs eine heterogene Erkrankung mit verschiedenen Subtypen darstellt. Sie lassen sich klinisch und molekular deutlich von einander unterscheiden. Wichtiges Ziel der modernen Forschung und ihrer Methoden ist daher die Entwicklung einer individuellen Therapie für jede einzelne Patientin.
Introduction: We examined if a combination of proliferation markers and estrogen receptor (ER) activity could predict early versus late relapses in ER-positive breast cancer and inform the choice and length of adjuvant endocrine therapy.
Methods: Baseline affymetrix gene-expression profiles from ER-positive patients who received no systemic therapy (n = 559), adjuvant tamoxifen for 5 years (cohort-1: n = 683, cohort-2: n = 282) and from 58 patients treated with neoadjuvant letrozole for 3 months (gene-expression available at baseline, 14 and 90 days) were analyzed. A proliferation score based on the expression of mitotic kinases (MKS) and an ER-related score (ERS) adopted from Oncotype DX® were calculated. The same analysis was performed using the Genomic Grade Index as proliferation marker and the luminal gene score from the PAM50 classifier as measure of estrogen-related genes. Median values were used to define low and high marker groups and four combinations were created. Relapses were grouped into time cohorts of 0-2.5, 0-5, 5-10 years.
Results: In the overall 10 years period, the proportional hazards assumption was violated for several biomarker groups indicating time-dependent effects. In tamoxifen-treated patients Low-MKS/Low-ERS cancers had continuously increasing risk of relapse that was higher after 5 years than Low-MKS/High-ERS cancers [0 to 10 year, HR 3.36; p = 0.013]. High-MKS/High-ERS cancers had low risk of early relapse [0-2.5 years HR 0.13; p = 0.0006], but high risk of late relapse which was higher than in the High-MKS/Low-ERS group [after 5 years HR 3.86; p = 0.007]. The High-MKS/Low-ERS subset had most of the early relapses [0 to 2.5 years, HR 6.53; p < 0.0001] especially in node negative tumors and showed minimal response to neoadjuvant letrozole. These findings were qualitatively confirmed in a smaller independent cohort of tamoxifen-treated patients. Using different biomarkers provided similar results.
Conclusions: Early relapses are highest in highly proliferative/low-ERS cancers, in particular in node negative tumors. Relapses occurring after 5 years of adjuvant tamoxifen are highest among the highly-proliferative/high-ERS tumors although their risk of recurrence is modest in the first 5 years on tamoxifen. These tumors could be the best candidates for extended endocrine therapy.
Heterogenous subtypes of breast cancer need to be analyzed separately. Pooling of datasets can provide reasonable sample sizes but dataset bias is an important concern. We assembled a combined dataset of 579 Affymetrix microarrays from triple negative breast cancer (TNBC) in Gene Expression Omnibus (GEO) series GSE31519. We developed a method for selecting comparable datasets and to control for the amount of dataset bias of individual probesets.
Introduction: Current prognostic gene expression profiles for breast cancer mainly reflect proliferation status and are most useful in ER-positive cancers. Triple negative breast cancers (TNBC) are clinically heterogeneous and prognostic markers and biology-based therapies are needed to better treat this disease.
Methods: We assembled Affymetrix gene expression data for 579 TNBC and performed unsupervised analysis to define metagenes that distinguish molecular subsets within TNBC. We used n = 394 cases for discovery and n = 185 cases for validation. Sixteen metagenes emerged that identified basal-like, apocrine and claudin-low molecular subtypes, or reflected various non-neoplastic cell populations, including immune cells, blood, adipocytes, stroma, angiogenesis and inflammation within the cancer. The expressions of these metagenes were correlated with survival and multivariate analysis was performed, including routine clinical and pathological variables.
Results: Seventy-three percent of TNBC displayed basal-like molecular subtype that correlated with high histological grade and younger age. Survival of basal-like TNBC was not different from non basal-like TNBC. High expression of immune cell metagenes was associated with good and high expression of inflammation and angiogenesis-related metagenes were associated with poor prognosis. A ratio of high B-cell and low IL-8 metagenes identified 32% of TNBC with good prognosis (hazard ratio (HR) 0.37, 95% CI 0.22 to 0.61; P < 0.001) and was the only significant predictor in multivariate analysis including routine clinicopathological variables.
Conclusions: We describe a ratio of high B-cell presence and low IL-8 activity as a powerful new prognostic marker for TNBC. Inhibition of the IL-8 pathway also represents an attractive novel therapeutic target for this disease.
Introduction: Lymphocyte infiltration (LI) is often seen in breast cancer but its importance remains controversial. A positive correlation of human epidermal growth factor receptor 2 (HER2) amplification and LI has been described, which was associated with a more favorable outcome. However, specific lymphocytes might also promote tumor progression by shifting the cytokine milieu in the tumor.
Methods: Affymetrix HG-U133A microarray data of 1,781 primary breast cancer samples from 12 datasets were included. The correlation of immune system-related metagenes with different immune cells, clinical parameters, and survival was analyzed.
Results: A large cluster of nearly 600 genes with functions in immune cells was consistently obtained in all datasets. Seven robust metagenes from this cluster can act as surrogate markers for the amount of different immune cell types in the breast cancer sample. An IgG metagene as a marker for B cells had no significant prognostic value. In contrast, a strong positive prognostic value for the T-cell surrogate marker (lymphocyte-specific kinase (LCK) metagene) was observed among all estrogen receptor (ER)-negative tumors and those ER-positive tumors with a HER2 overexpression. Moreover ER-negative tumors with high expression of both IgG and LCK metagenes seem to respond better to neoadjuvant chemotherapy.
Conclusions: Precise definitions of the specific subtypes of immune cells in the tumor can be accomplished from microarray data. These surrogate markers define subgroups of tumors with different prognosis. Importantly, all known prognostic gene signatures uniformly assign poor prognosis to all ER-negative tumors. In contrast, the LCK metagene actually separates the ER-negative group into better or worse prognosis.
Background: Current prognostic gene signatures for breast cancer mainly reflect proliferation status and have limited value in triple-negative (TNBC) cancers. The identification of prognostic signatures from TNBC cohorts was limited in the past due to small sample sizes.
Methodology/Principal Findings: We assembled all currently publically available TNBC gene expression datasets generated on Affymetrix gene chips. Inter-laboratory variation was minimized by filtering methods for both samples and genes. Supervised analysis was performed to identify prognostic signatures from 394 cases which were subsequently tested on an independent validation cohort (n = 261 cases).
Conclusions/Significance: Using two distinct false discovery rate thresholds, 25% and <3.5%, a larger (n = 264 probesets) and a smaller (n = 26 probesets) prognostic gene sets were identified and used as prognostic predictors. Most of these genes were positively associated with poor prognosis and correlated to metagenes for inflammation and angiogenesis. No correlation to other previously published prognostic signatures (recurrence score, genomic grade index, 70-gene signature, wound response signature, 7-gene immune response module, stroma derived prognostic predictor, and a medullary like signature) was observed. In multivariate analyses in the validation cohort the two signatures showed hazard ratios of 4.03 (95% confidence interval [CI] 1.71–9.48; P = 0.001) and 4.08 (95% CI 1.79–9.28; P = 0.001), respectively. The 10-year event-free survival was 70% for the good risk and 20% for the high risk group. The 26-gene signatures had modest predictive value (AUC = 0.588) to predict response to neoadjuvant chemotherapy, however, the combination of a B-cell metagene with the prognostic signatures increased its response predictive value. We identified a 264-gene prognostic signature for TNBC which is unrelated to previously known prognostic signatures.
Background: Breast cancer (BC) is the most frequent female cancer and preferentially metastasizes to bone. The transcription factor TGFB-induced factor homeobox 1 (TGIF) is involved in bone metabolism. However, it is not yet known whether TGIF is associated with BC bone metastasis or patient outcome and thus of potential interest. Methods: TGIF expression was analyzed by immunohistochemistry in 1197 formalin-fixed, paraffin-embedded tissue samples from BC patients treated in the GAIN (German Adjuvant Intergroup Node-Positive) study with two adjuvant dose-dense schedules of chemotherapy with or without bisphosphonate ibandronate. TGIF expression was categorized into negative/low and moderate/strong staining. Endpoints were disease-free survival (DFS), overall survival (OS) and time to primary bone metastasis as first site of relapse (TTPBM). Results: We found associations of higher TGIF protein expression with smaller tumor size (p= 0.015), well differentiated phenotype (p< 0.001) and estrogen receptor (ER)-positive BC (p< 0.001). Patients with higher TGIF expression levels showed a significantly longer disease-free (DFS: HR 0.75 [95%CI 0.59–0.95], log-rank p=0.019) and overall survival (OS: HR 0.69 [95%CI 0.50–0.94], log-rank p= 0.019), but no association with TTPBM (HR 0.77 [95%CI 0.51–1.16]; p= 0.213). Univariate analysis in molecular subgroups emphasized that elevated TGIF expression was prognostic for both DFS and OS in ER-positive BC patients (DFS: HR 0.68 [95%CI 0.51–0.91]; log-rank p= 0.009, interaction p= 0.130; OS: HR 0.60 [95%CI 0.41–0.88], log-rank p= 0.008, interaction p= 0.107) and in the HER2-negative subgroup (DFS:HR 0.67 [95%CI 0.50–0.88], log-rank p= 0.004, interaction p= 0.034; OS: HR 0.57 [95%CI 0.40–0.81], log-rank p= 0.002, interaction p= 0.015). Conclusions: Our results suggest that moderate to high TGIF expression is a common feature of breast cancer cells and that this is not associated with bone metastases as first site of relapse. However, a reduced expression is linked to tumor progression, especially in HER2-negative breast cancer.
