Search

Recently it has been shown that the genome organizer SATB1 plays an important role in breast cancer progression and predicts a poor prognosis. However its prognostic value compared to markers as the estrogen receptor is currently unclear. The expression levels of SATB1 mRNA from Affymetrix microarray in a cohort of 2058 breast cancer samples and its prognostic impact were analyzed. There was no significant difference in disease-free survival among ER negative cancers but instead a benefit for high SATB1 expression among ER positive tumors (p = 0.042). However, even in ER positive cancer no independent prognostic value in multivariate analysis with standard parameters was observed. Thus the use of SATB1 as target or prognostic marker for breast cancer should be viewed with caution and a possible confounding effect of the estrogen receptor status of the tumor should be taken into account when analysing new markers as SATB1., (Copyright © 2010 Elsevier Ltd. All rights reserved.)

Objectives: Ceramide and sphingosine mediate response to cancer therapy, inhibit cell growth and induce apoptosis in vitro. Only a few clinical data about the impact of ceramide and sphingosine iny vivo are available. We investigated the relevance of ceramide- and sphingosine-generating enzymes in breast cancer (acid ceramidase 1 (ASAH1), ceramide synthases 4 (LASS4) and 6 (LASS6)) by means of gene expression analysis., Methods: We analyzed differences in ASAH1, LASS4 and LASS6 on mRNA level between breast cancer subgroups using microarray data from 1581 tumor samples., Results: High ASAH1, LASS4 and LASS6 expression correlates with pathohistological grading (p < 0.001) and estrogen receptor (ER) status (p < 0.001). High ASAH1 expression was associated with a larger tumor size >2 cm (p = 0.003), while high LASS6 expression was correlated with ErbB2 negativity (p < 0.001). In survival analysis, we detected a significant better prognosis of patients with higher ASAH1 expression (p = 0.002) in the ER-positive subgroup. In contrast, expression of LASS4 or LASS6 did not show any prognostic impact. In the multivariate analysis, only ASAH1 expression (p = 0.002), tumor size (p < 0.0001) and ErbB2 positivity (p = 0.041) remained significant., Conclusion: ASAH1 is an estrogen-dependent member of the sphingolipid metabolism, which might provide further prognostic information in ER-positive breast cancers.

Reprogramming of human somatic cells into pluripotent cell types gives insight in the pathophysiology of diseases. We analysed genes recently shown to be differentially expressed in induced pluripotent stem cells (iPS) in 95 breast cancer samples. This analysis reveals two breast cancer subgroups with stem cell-like features, differing in ER-status and proliferation as well as in their clinical course of disease.

Summary: Gene expression profiling using Affymetrix HG-U133 Arrays (22,500 genes) was performed on fresh frozen pretherapeutic core biopsies from 50 patients undergoing neoadjuvant chemotherapy (NAC) with docetaxel, adriamycin, cyclophosphamide (TAC) within the GEPARTRIO trial. The Sorlie classification based on the “intrinsic gene set” revealed four different subgroups in our cohort (normal-like: 14%, basal-like: 20%, erbB2+: 22% and luminal: 44%), which is in line with the original description. High genomic grade but not histopathological grading was statistically different within the four subgroups (P<0.001). About 45.5% of tumors classified according to erbB2+ cluster showed a pathological complete response compared to 0% in the normal-like, 10.0% in the basal-like and 9.1% in the luminal subgroup (P=0.024). There was a trend to less tumor relapses in the erbB2+ subgroup (0%) compared to the normal-like (28.6%), basal-like (30.0%) and luminal (13.6%) cluster (P=0.215). Our data suggest that the molecular tumor subtypes based on the “intrinsic gene set” can be used to predict tumor response according to NAC. [Copyright &y& Elsevier]

Summary: Gene expression analysis in breast cancer patients undergoing neoadjuvant chemotherapy is an interesting tool for identification of gene signatures and new markers to predict tumor response. However, the detection of predictive markers strongly depends on the drugs used in the specific therapeutic setting. There is growing evidence that topoisomerase II-alpha (TOPO IIα) is a marker for anthracycline-, and microtubule-associated protein tau (MAPT) for taxane sensitivity. HER-2 has been described as a marker of both anthracycline and taxane sensitivity. We performed gene expression profiling of 50 patients within the GEPARTRIO study, an anthracycline and taxane neoadjuvant chemotherapy trial. Here we investigate the predictive value of TOPO IIα, MAPT and HER-2 mRNA expression for pathological complete response (pCR) in this setting. Interestingly, HER-2 gene expression was strongly predictive of pCR (P=0.017) as well as overall response (P=0.037) and clinical complete response (cCR, P=0.050). In contrast, for both TOPO IIα and MAPT no correlation with pCR was observed in our sample group. [Copyright &y& Elsevier]

Abstract: The identification of new biological markers for breast cancer has adopted a new dimension by the use of novel techniques such as global gene expression profiling. While important results have been achieved by these methods not all hopes for a more precise assessment of patients’ prognosis have yet been accomplished and validation of prognostic or predictive gene signatures is still often difficult. Several recent approaches suggest that comparisons of differential gene expression could be more instructive if prior classifications of tumors based on molecular or biological characteristics were applied. We previously reported a subtype of breast cancer by using a cluster of coordinately expressed genes many of which has been associated with the mammary epithelial stem cells. While a stringent inverse link of ER status and proliferation of the tumor was observed among those “stem cell like” (SCL) tumors, this link was “uncoupled” in about half of the Non-“stem cell like” (Non-SCL) tumors. This subgroup of SCL tumors can be used as a reference system to analyze changes in the ER pathway by comparing the expression of genes dependent on the ER status. By using this strategy we identified Plexin B1, a cell-surface receptor for the semaphorin Sema4D, whose expression is reduced in the group of “uncoupled” tumors. Loss of Plexin B1 is associated with a poor prognosis in both univariate (all patients: p =0.0062; ER positive: p =0.0107) and multivariate analyses (all patients: p =0.032; ER positive: p =0.022). In conclusion those strategies of gene expression analysis in a context of biological meaningful classifications could be helpful to reveal new prognostic/predictive markers. [Copyright &y& Elsevier]

The predictive value of tumor mutational burden (TMB), alone or in combination with an immune gene expression profile (GEP), for response to neoadjuvant therapy in early triple negative breast cancer (TNBC) is currently not known, either for immune checkpoint blockade (ICB) or conventional chemotherapy. We obtained both whole exome sequencing and RNA-Seq data from pretreatment samples of 149 TNBC of the recent neoadjuvant ICB trial, GeparNuevo. In a predefined analysis, we assessed the predictive value of TMB and a previously developed immune GEP for pathological complete remission (pCR). Median TMB was 1.52 mut/Mb (range 0.02–7.65) and was significantly higher in patients with pCR (median 1.87 versus 1.39; P = 0.005). In multivariate analysis, odds ratios for pCR per mut/Mb were 2.06 [95% confidence intervals (CI) 1.33–3.20, P = 0.001] among all patients, 1.77 (95% CI 1.00–3.13, P = 0.049) in the durvalumab treatment arm, and 2.82 (95% CI 1.21–6.54, P = 0.016) in the placebo treatment arm, respectively. We also found that both continuous TMB and immune GEP (or tumor infiltrating lymphocytes) independently predicted pCR. When we stratified patients in groups based on the upper tertile of TMB and median GEP, we observed a pCR rate of 82% (95% CI 60% to 95%) in the group with both high TMB and GEP in contrast to only 28% (95% CI 16% to 43%) in the group with both low TMB and GEP. TMB and immune GEP add independent value for pCR prediction. Our results recommend further analysis of TMB in combination with immune parameters to individually tailor therapies in breast cancer. • Tumor mutational burden (TMB) predicts pCR after neoadjuvant treatment in early triple negative breast cancer. • The predictive value of TMB was found both for immune checkpoint inhibition with chemotherapy and for chemotherapy alone. • Both TMB and an immune gene expression profile add independent value for pCR prediction in multivariate analysis. [ABSTRACT FROM AUTHOR]

Background: A genomic index for sensitivity to endocrine therapy (SET) was previously derived from genes strongly positively and negatively coexpressed with estrogen receptor (Symmans et al. 2010, JCO 28:4111). This SET index has been reported to predict survival benefit from adjuvant endocrine therapy independently of prognosis. Materials and Methods: Affymetrix gene expression profiling was performed on 307 ER positive primary breast cancers from a retrospective cohort treated solely with endocrine therapy. In a blinded study the SET index' ability to predict survival was analyzed in this previously unpublished dataset. Affymetrix profiles (CEL files) were anonymized and provided to the developers of SET index (Nuvera Biosciences) without any clinical information. The 261 profiles that passed QC were categorized into SET classes based on the published prespecified cutoffs. Samples categorized as ER negative based on gene expression were excluded. Subsequently classifications were unblinded and clinical associations analyzed according to a predefined protocol. Exploratory analyses were performed on the relationship of SET index to other genomic signatures. We also assessed a potential pure prognostic value of SET index in an additional dataset of 164 node negative ER positive patients that did not receive any adjuvant treatment. Results: A lower SET index significantly correlated with higher grade (p = 0.009) and negative PgR status (p = 0.016). We detected no significant differences for age, tumor size, lymph node status, and HER2 status between patients with high, intermediate, and low SET index. In the lymph node negative (LNN) cohort (n = 120) we observed a significant difference in DFS (5yr DFS 77.1±10.2% vs 94.4±2.2%; HR 4.20, 95% CI 1.72--10.2; p = 0.002) and DMFS (HR 3.18, 95% CI 1.20--8.47; p = 0.020) for patients with low SET index. In contrast, we found no prognostic value of SET index in lymph node positive patients (n = 95). In multivariate analyses of LNN patients including SET, age, tumor size, histological grade, and PgR status, only SET was significantly associated with DFS (HR 3.37, 95% CI 1.25--9.01; p = 0.016) and DMFS (HR 3.03, 95% CI 1.08--8.55; p = 0.036). In exploratory analyses SET index was not correlated to other genomic signatures related to proliferation (as Recurrence Score, GGI, and NKI70) or immune response (e.g. 7IGS, SDPP). When we included all these genomic signatures as continous scores in a multivariate stepwise Cox regression model in the LNN endocrine treated cohort, only SET remained as significant (p = 0.025) while Recurrence Score displayed a strong trend (p = 0.054). We also verified that SET had no pure prognostic value in an additional dataset of 164 ER positive patients that did not receive any adjuvant treatment. Conclusions: In a blinded analysis the predictive ability of SET index was prospectively validated in an independent cohort of node-negative patients. Our exploratory analysis demonstrates that SET index is unrelated to other genomic signatures and delivers independent information on the response of patients to endocrine therapy rather than prognosis. [ABSTRACT FROM AUTHOR]