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Background: Robust molecular subtyping of triple-negative breast cancer (TNBC) is a prerequisite for the success of precision medicine. Today, there is a clear consensus on three TNBC molecular subtypes: luminal androgen receptor (LAR), basal-like immune-activated (BLIA), and basal-like immune-suppressed (BLIS). However, the debate about the robustness of other subtypes is still open., Methods: An unprecedented number (n = 1942) of TNBC patient data was collected. Microarray- and RNAseq-based cohorts were independently investigated. Unsupervised analyses were conducted using k-means consensus clustering. Clusters of patients were then functionally annotated using different approaches. Prediction of response to chemotherapy and targeted therapies, immune checkpoint blockade, and radiotherapy were also screened for each TNBC subtype., Results: Four TNBC subtypes were identified in the cohort: LAR (19.36%); mesenchymal stem-like (MSL/MES) (17.35%); BLIA (31.06%); and BLIS (32.23%). Regarding the MSL/MES subtype, we suggest renaming it to mesenchymal-like immune-altered (MLIA) to emphasize its specific histological background and nature of immune response. Treatment response prediction results show, among other things, that despite immune activation, immune checkpoint blockade is probably less or completely ineffective in MLIA, possibly caused by mesenchymal background and/or an enrichment in dysfunctional cytotoxic T lymphocytes. TNBC subtyping results were included in the bc-GenExMiner v5.0 webtool ( http://bcgenex.ico.unicancer.fr )., Conclusion: The mesenchymal TNBC subtype is characterized by an exhausted and altered immune response, and resistance to immune checkpoint inhibitors. Consensus for molecular classification of TNBC subtyping and prediction of cancer treatment responses helps usher in the era of precision medicine for TNBC patients., (© 2024. The Author(s), under exclusive licence to The Japanese Breast Cancer Society.)

Background: Copy number alterations (CNA) are acquired during the evolution of cancers from their early stage to metastatic stage. This study aims at analysing the clinical value of the identified metastasis-associated CNAs both in metastatic breast cancers (mBCs) and early breast cancers (eBCs)., Methods: Single-nucleotide polymorphism (SNP)-array was performed on 926 biopsies from mBC patients, enrolled in SAFIR02-BREAST prospective trial. CNA profiles of eBCs from The Cancer Genome Atlas Breast Invasive Carcinoma (n = 770), Molecular Taxonomy of Breast Cancer International Consortium (n = 1620) and PACS04 trial (n = 243) cohorts were used as references for comparing mBCs and eBCs CNA profiles. Overall survival was the considered survival endpoint., Results: Among the twenty-one genes frequently altered in ER + /HER2- mBCs: focal amplification of TERT was associated with poor outcome in the ER + /HER2- mBC population. Among the ER + /HER2- mBCs patients for whom CDK4/6 inhibitors information before biopsies collection was available: we identified seven genes on post-treatment biopsies, including the cyclin-dependent kinase 4 (CDK4), which was amplified in 9.8% of the ER + /HER2- mBCs pretreated population, as compared to 1.5% in the ER + /HER2- mBCs unpretreated population (P = 2.82E-04) as well as the 3 eBC populations. CDK4 amplification was associated with poor outcome in the ER + /HER2- eBCs., Conclusions: This study provides insights into the biology of mBCs and identifies clinically useful genomic features for future improvement of breast cancer patient management., (© 2024. The Author(s).)

Proteomics has been little used for the identification of novel prognostic and/or therapeutic markers in isocitrate dehydrogenase (IDH)-wildtype glioblastoma (GB). In this study, we analyzed 50 tumor and 30 serum samples from short- and long-term survivors of IDH-wildtype GB (STS and LTS, respectively) by data-independent acquisition mass spectrometry (DIA-MS)-based proteomics, with the aim of identifying such markers. DIA-MS identified 5422 and 826 normalized proteins in tumor and serum samples, respectively, with only three tumor proteins and 26 serum proteins displaying significant differential expression between the STS and LTS groups. These dysregulated proteins were principally associated with the detoxification of reactive oxygen species (ROS). In particular, GB patients in the STS group had high serum levels of malate dehydrogenase 1 (MDH1) and ribonuclease inhibitor 1 (RNH1) and low tumor levels of fatty acid-binding protein 7 (FABP7), which may have enabled them to maintain low ROS levels, counteracting the effects of the first-line treatment with radiotherapy plus concomitant and adjuvant temozolomide. A blood score built on the levels of MDH1 and RNH1 expression was found to be an independent prognostic factor for survival based on the serum proteome data for a cohort of 96 IDH-wildtype GB patients. This study highlights the utility of circulating MDH1 and RNH1 biomarkers for determining the prognosis of patients with IDH-wildtype GB. Furthermore, the pathways driven by these biomarkers, and the tumor FABP7 pathway, may constitute promising therapeutic targets for blocking ROS detoxification to overcome resistance to chemoradiotherapy in potential GB STS., (© 2024 The Author(s). Molecular Oncology published by John Wiley & Sons Ltd on behalf of Federation of European Biochemical Societies.)

Heterogeneity of the tumor microenvironment (TME) is one of the major causes of treatment resistance in breast cancer. Among TME components, nervous system role in clinical outcome has been underestimated. Identifying neuronal signatures associated with treatment response will help to characterize neuronal influence on tumor progression and identify new treatment targets. The search for hormonotherapy-predictive biomarkers was implemented by supervised machine learning (ML) analysis on merged transcriptomics datasets from public databases. ML-derived genes were investigated by pathway enrichment analysis, and potential gene signatures were curated by removing the variables that were not strictly nervous system specific. The predictive and prognostic abilities of the generated signatures were examined by Cox models, in the initial cohort and seven external cohorts. Generated signature performances were compared with 14 other published signatures, in both the initial and external cohorts. Underlying biological mechanisms were explored using deconvolution tools (CIBERSORTx and xCell). Our pipeline generated two nervous system-related signatures of 24 genes and 97 genes (NervSign24 and NervSign97). These signatures were prognostic and hormonotherapy-predictive, but not chemotherapy-predictive. When comparing their predictive performance with 14 published risk signatures in six hormonotherapy-treated cohorts, NervSign97 and NervSign24 were the two best performers. Pathway enrichment score and deconvolution analysis identified brain neural progenitor presence and perineural invasion as nervous system-related mechanisms positively associated with NervSign97 and poor clinical prognosis in hormonotherapy-treated patients. Transcriptomic profiling has identified two nervous system-related signatures that were validated in clinical samples as hormonotherapy-predictive signatures, meriting further exploration of neuronal component involvement in tumor progression., Significance: The development of personalized and precision medicine is the future of cancer therapy. With only two gene expression signatures approved by FDA for breast cancer, we are in need of new ones that can reliably stratify patients for optimal treatment. This study provides two hormonotherapy-predictive and prognostic signatures that are related to nervous system in TME. It highlights tumor neuronal components as potential new targets for breast cancer therapy., Competing Interests: A. Basseville reports grants from European Commission during the conduct of the study. C. Cordier reports grants from la Ligue Nationale Contre le Cancer during the conduct of the study. M. Campone reports grants from AstraZeneca, Novartis, Abbvie, Sanofi, Lilly, Pfizer, Sandoz, Accord, G1 Therapeutics, Seagen, Gilead, Daiichi-Sankyo, Servier, Pet-Therapy, and Roche outside the submitted work. No disclosures were reported by the other authors., (© 2022 The Authors; Published by the American Association for Cancer Research.)

Objective. This paper proposes a novel approach for the longitudinal registration of PET imaging acquired for the monitoring of patients with metastatic breast cancer. Unlike with other image analysis tasks, the use of deep learning (DL) has not significantly improved the performance of image registration. With this work, we propose a new registration approach to bridge the performance gap between conventional and DL-based methods: medical image registration method regularized by architecture (MIRRBA). Approach. MIRRBAis a subject-specific deformable registration method which relies on a deep pyramidal architecture to parametrize the deformation field. Diverging from the usual deep-learning paradigms,MIRRBAdoes not require a learning database, but only a pair of images to be registered that is used to optimize the network's parameters. We appliedMIRRBAon a private dataset of 110 whole-body PET images of patients with metastatic breast cancer. We used different architecture configurations to produce the deformation field and studied the results obtained. We also compared our method to several standard registration approaches: two conventional iterative registration methods (ANTs and Elastix) and two supervised DL-based models (LapIRN and Voxelmorph). Registration accuracy was evaluated using the Dice score, the target registration error, the average Hausdorff distance and the detection rate, while the realism of the registration obtained was evaluated using Jacobian's determinant. The ability of the different methods to shrink disappearing lesions was also computed with the disappearing rate. Main results. MIRRBA significantly improved all metrics when compared to DL-based approaches. The organ and lesion Dice scores of Voxelmorph improved by 6% and 52% respectively, while the ones of LapIRN increased by 5% and 65%. Regarding conventional approaches, MIRRBA presented comparable results showing the feasibility of our method. Significance. In this paper, we also demonstrate the regularizing power of deep architectures and present new elements to understand the role of the architecture in DL methods used for registration., (© 2022 Institute of Physics and Engineering in Medicine.)

Purpose: Investigates the link between HER2 status and histological response after neoadjuvant chemotherapy in patients with early TNBC., Methods: We retrieved clinical and anatomopathological data retrospectively from 449 patients treated for the first time with standard neoadjuvant chemotherapy for early unilateral BC between 2005 and 2020. The primary endpoint was pathological complete response (pCR, i.e., ypT0 ypN0), according to HER2 status. Secondary endpoints included invasive disease-free survival (I-DFS) and overall survival (OS)., Results: 437 patients were included, and 121 (27.7%) patients had HER2-low tumours. The pCR rate was not significantly different between the HER2-low group vs. the HER2-0 group (35.7% versus 41.8%, p = 0.284) in either univariate analysis or multivariate analysis adjusted for TNM classification and grade (odds ratio [OR] = 0.70, confidence interval [CI] 95% 0.45-1.08). With a median follow-up of 72.9 months, no significant survival differences were observed between patients with HER2-low tumours vs. patients with HER2-0 tumours in terms of I-DFS ( p = 0.487) and OS ( p = 0.329)., Conclusions: In our cohort, HER2 status was not significantly associated with pCR in a manner consistent with data published recently on TNBC. However, the prognostic impact of HER2-low expression among TNBC patients warrants further evaluation.

(1) Background: triple-negative breast cancer (TNBC) remains a clinical and therapeutic challenge primarily affecting young women with poor prognosis. TNBC is currently treated as a single entity but presents a very diverse profile in terms of prognosis and response to treatment. Positron emission tomography/computed tomography (PET/CT) with 18 F-fluorodeoxyglucose ([ 18 F]FDG) is gaining importance for the staging of breast cancers. TNBCs often show high [ 18 F]FDG uptake and some studies have suggested a prognostic value for metabolic and volumetric parameters, but no study to our knowledge has examined textural features in TNBC. The objective of this study was to evaluate the association between metabolic, volumetric and textural parameters measured at the initial [ 18 F]FDG PET/CT and disease-free survival (DFS) and overall survival (OS) in patients with nonmetastatic TBNC. (2) Methods: all consecutive nonmetastatic TNBC patients who underwent a [ 18 F]FDG PET/CT examination upon diagnosis between 2012 and 2018 were retrospectively included. The metabolic and volumetric parameters (SUV max , SUV mean , SUV peak , MTV, and TLG) and the textural features (entropy, homogeneity, SRE, LRE, LGZE, and HGZE) of the primary tumor were collected. (3) Results: 111 patients were enrolled (median follow-up: 53.6 months). In the univariate analysis, high TLG, MTV and entropy values of the primary tumor were associated with lower DFS ( p = 0.008, p = 0.006 and p = 0.025, respectively) and lower OS ( p = 0.002, p = 0.001 and p = 0.046, respectively). The discriminating thresholds for two-year DFS were calculated as 7.5 for MTV, 55.8 for TLG and 2.6 for entropy. The discriminating thresholds for two-year OS were calculated as 9.3 for MTV, 57.4 for TLG and 2.67 for entropy. In the multivariate analysis, lymph node involvement in PET/CT was associated with lower DFS ( p = 0.036), and the high MTV of the primary tumor was correlated with lower OS ( p = 0.014). (4) Conclusions: textural features associated with metabolic and volumetric parameters of baseline [ 18 F]FDG PET/CT have a prognostic value for identifying high-relapse-risk groups in early TNBC patients.

Metastatic breast cancer patients receive lifelong medication and are regularly monitored for disease progression. The aim of this work was to (1) propose networks to segment breast cancer metastatic lesions on longitudinal whole-body PET/CT and (2) extract imaging biomarkers from the segmentations and evaluate their potential to determine treatment response. Baseline and follow-up PET/CT images of 60 patients from the EPICUREseinmeta study were used to train two deep-learning models to segment breast cancer metastatic lesions: One for baseline images and one for follow-up images. From the automatic segmentations, four imaging biomarkers were computed and evaluated: SULpeak, Total Lesion Glycolysis (TLG), PET Bone Index (PBI) and PET Liver Index (PLI). The first network obtained a mean Dice score of 0.66 on baseline acquisitions. The second network obtained a mean Dice score of 0.58 on follow-up acquisitions. SULpeak, with a 32% decrease between baseline and follow-up, was the biomarker best able to assess patients' response (sensitivity 87%, specificity 87%), followed by TLG (43% decrease, sensitivity 73%, specificity 81%) and PBI (8% decrease, sensitivity 69%, specificity 69%). Our networks constitute promising tools for the automatic segmentation of lesions in patients with metastatic breast cancer allowing treatment response assessment with several biomarkers.

Background: Breast cancer may present genomic alterations leading to homologous recombination deficiency (HRD). PARP inhibitors have proven their efficacy in patients with HER2-negative (HER2-) metastatic breast cancer (mBC) harbouring germline (g) BRCA1/2 mutations in 3 phases III trials. The single-arm phase II RUBY trial included 42 patients, 40 of whom received at least one dose of rucaparib. RUBY study assessed the efficacy of rucaparib in HER2-mBC with either high genomic loss of heterozygosity (LOH) score or non-germline BRCA1/2 mutation., Patients and Methods: The primary objective was the clinical benefit rate (CBR), and the study was powered to see 20% CBR using a 2-stage Simon design., Results: The primary-end point was not reached with a CBR of 13.5%. Two LOH-high patients, without somatic BRCA1/2 mutation, presented a complete and durable response (12 and 28.5 months). Whole-genome analysis was performed on 24 samples, including 5 patients who presented a clinical benefit from rucaparib. HRDetect tended to be associated with response to rucaparib, without reaching statistical significance (median HRDetect responders versus non-responders: 0.465 versus 0.040; p = 0.2135). Finally, 220 of 711 patients with mBC screened for LOH upstream from RUBY presented a high LOH score associated with a higher likelihood of death (hazard ratio = 1.39; 95% CI: 1.11-1.75; p = 0.005)., Conclusion: Our data suggest that a small subset of patients with high LOH scores without germline BRCA1/2 mutation could derive benefit from PARP inhibitors. However, the RUBY study underlines the need to develop additional biomarkers to identify selectively potential responders., (Copyright © 2021 The Authors. Published by Elsevier Ltd.. All rights reserved.)

We are taking advantage of the launch of the latest version (v4.6) of our web-based data mining tool "breast cancer gene-expression miner" (bc-GenExMiner) to take stock of its position within the oncology research landscape and to present an activity report ten years after its establishment (http://bcgenex.ico.unicancer.fr). bc-GenExMiner is an open-access, user-friendly tool for statistical mining on breast tumor transcriptomes, annotated with more than 20 clinicopathologic and molecular characteristics. The database comprises more than 16,000 patients from 64 cohorts - including TCGA, METABRIC and SCAN-B - for whom several thousands of genes have been quantified by microarrays or RNA-seq. Correlation, expression and prognostic analyses are available for targeted, exhaustive or customized explorations of queried genes. bc-GenExMiner facilitates the validation, investigation, and prioritization of discoveries and hypotheses on genes of interest. It allows users to analyse large databases, create data visualizations, and obtain robust statistical analysis, thereby accelerating biomarker discovery. Ten years after its launch, judging by the number of visits, analyses, and scientific citations of bc-GenExMiner, we conclude that this web resource serves its purpose in the international scientific community working in breast cancer research, with a never-ending rise in its use., (Copyright © 2021 Société Française du Cancer. Published by Elsevier Masson SAS. All rights reserved.)

Motivation: The principle of Breiman's random forest (RF) is to build and assemble complementary classification trees in a way that maximizes their variability. We propose a new type of random forest that disobeys Breiman's principles and involves building trees with no classification errors in very large quantities. We used a new type of decision tree that uses a neuron at each node as well as an in-innovative half Christmas tree structure. With these new RFs, we developed a score, based on a family of ten new statistical information criteria, called Nguyen information criteria (NICs), to evaluate the predictive qualities of features in three dimensions., Results: The first NIC allowed the Akaike information criterion to be minimized more quickly than data obtained with the Gini index when the features were introduced in a logistic regression model. The selected features based on the NICScore showed a slight advantage compared to the support vector machines-recursive feature elimination (SVM-RFE) method. We demonstrate that the inclusion of artificial neurons in tree nodes allows a large number of classifiers in the same node to be taken into account simultaneously and results in perfect trees without classification errors., Availability and Implementation: The methods used to build the perfect trees in this article were implemented in the 'ROP' R package, archived at https://cran.r-project.org/web/packages/ROP/index.html., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author(s) 2021. Published by Oxford University Press.)

Background: Breast cancer is the most common cancer in women and the first cancer concerning mortality. Metastatic breast cancer remains a disease with a poor prognosis and about 30% of women diagnosed with an early stage will have a secondary progression. Metastatic breast cancer is an incurable disease despite significant therapeutic advances in both supportive cares and targeted specific therapies. In the management of a metastatic patient, each clinician follows a highly complex and strictly personal decision making process. It is based on a number of objective and subjective parameters which guides therapeutic choice in the most individualized or adapted manner., Methods/design: The main objective is to integrate massive and heterogeneous data concerning the patient's environment, personal and familial history, clinical and biological data, imaging, histological results (with multi-omics data), and microbiota analysis. These characteristics are multiple and in dynamic interaction overtime. With the help of mathematical units with biological competences and scientific collaborations, our project is to improve the comprehension of treatment response, based on health clinical and molecular heterogeneous big data investigation., Discussion: Our project is to prove feasibility of creation of a clinico-biological database prospectively by collecting epidemiological, socio-economic, clinical, biological, pathological, multi-omic data and to identify characteristics related to the overall survival status before treatment and within 15 years after treatment start from a cohort of 300 patients with a metastatic breast cancer treated in the institution., Trial Registration: ClinicalTrials.gov identifier (NCT number): NCT03958136 . Registration 21st of May, 2019; retrospectively registered.

'Breast cancer gene-expression miner' (bc-GenExMiner) is a breast cancer-associated web portal (http://bcgenex.ico.unicancer.fr). Here, we describe the development of a new statistical mining module, which permits several differential gene expression analyses, i.e. 'Expression' module. Sixty-two breast cancer cohorts and one healthy breast cohort with their corresponding clinicopathological information are included in bc-GenExMiner v4.5 version. Analyses are based on microarray or RNAseq transcriptomic data. Thirty-nine differential gene expression analyses, grouped into 13 categories, according to clinicopathological and molecular characteristics ('Targeted' and 'Exhaustive') and gene expression ('Customized'), have been developed. Output results are visualized in four forms of plots. This new statistical mining module offers, among other things, the possibility to compare gene expression in healthy (cancer-free), tumour-adjacent and tumour tissues at once and in three triple-negative breast cancer subtypes (i.e. C1: molecular apocrine tumours; C2: basal-like tumours infiltrated by immune suppressive cells and C3: basal-like tumours triggering an ineffective immune response). Several validation tests showed that bioinformatics process did not alter the pathobiological information contained in the source data. In this work, we developed and demonstrated that bc-GenExMiner 'Expression' module can be used for exploratory and validation purposes. Database URL: http://bcgenex.ico.unicancer.fr., (© The Author(s) 2021. Published by Oxford University Press.)

Triple-negative breast cancer (TNBC) heterogeneity represents one of the main obstacles to precision medicine for this disease. Recent concordant transcriptomics studies have shown that TNBC could be divided into at least three subtypes with potential therapeutic implications. Although a few studies have been conducted to predict TNBC subtype using transcriptomics data, the subtyping was partially sensitive and limited by batch effect and dependence on a given dataset, which may penalize the switch to routine diagnostic testing. Therefore, we sought to build an absolute predictor (i.e., intra-patient diagnosis) based on machine learning algorithms with a limited number of probes. To that end, we started by introducing probe binary comparison for each patient (indicators). We based the predictive analysis on this transformed data. Probe selection was first involved combining both filter and wrapper methods for variable selection using cross-validation. We tested three prediction models (random forest, gradient boosting [GB], and extreme gradient boosting) using this optimal subset of indicators as inputs. Nested cross-validation consistently allowed us to choose the best model. The results showed that the fifty selected indicators highlighted the biological characteristics associated with each TNBC subtype. The GB based on this subset of indicators performs better than other models., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

A fascinating but uncharacterized action of antimitotic chemotherapy is to collectively prime cancer cells to apoptotic mitochondrial outer membrane permeabilization (MOMP), while impacting only on cycling cell subsets. Here, we show that a proapoptotic secretory phenotype is induced by activation of cGAS/STING in cancer cells that are hit by antimitotic treatment, accumulate micronuclei and maintain mitochondrial integrity despite intrinsic apoptotic pressure. Organotypic cultures of primary human breast tumors and patient-derived xenografts sensitive to paclitaxel exhibit gene expression signatures typical of type I IFN and TNFα exposure. These cytokines induced by cGAS/STING activation trigger NOXA expression in neighboring cells and render them acutely sensitive to BCL-xL inhibition. cGAS/STING-dependent apoptotic effects are required for paclitaxel response in vivo, and they are amplified by sequential, but not synchronous, administration of BH3 mimetics. Thus anti-mitotic agents propagate apoptotic priming across heterogeneously sensitive cancer cells through cytosolic DNA sensing pathway-dependent extracellular signals, exploitable by delayed MOMP targeting.

Heterogeneity and lack of targeted therapies represent the two main impediments to precision treatment of triple-negative breast cancer (TNBC). Therefore, molecular subtyping and identification of therapeutic pathways are required to optimize medical care. The aim of the present study is to define robust TNBC subtypes with clinical relevance by means of proteomics and transcriptomics. As a first step, unsupervised analyses are conducted in parallel on proteomics and transcriptomics data of 83 TNBC tumors. Proteomics data unsupervised analysis did not permit separation of TNBC into different subtypes, whereas transcriptomics data are able to clearly and robustly identify three subtypes: molecular apocrine (C1), basal-like immune-suppressed (C2), and basal-like immune response (C3). Supervised analysis of proteomics data are then conducted based on transcriptomics subtyping. Thirty out of 62 proteins differentially expressed between C1, C2, and C3 belonged to biological categories which characterized these TNBC clusters: luminal and androgen-regulated proteins (C1), basal, invasion, and extracellular matrix (C2), and basal and immune response (interferon pathway and immunoglobulins) (C3). Although proteomics unsupervised analysis of TNBC tumors is unsuccessful at identifying clusters, the integrated approach is promising. Identification and measurement of 30 proteins strengthen subtyping of TNBC based on robust transcriptomics unsupervised analysis., (© 2019 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Human olfactomedin-4 (OLFM4) is a secreted protein involved in a variety of cellular functions including proliferation, differentiation, apoptosis, and cell adhesion. OLFM4 expression has been studied in several tumor types including gastric, colorectal, lung, and endometrioid cancers where it has been suggested to be an independent favorable or unfavorable prognostic marker. For breast cancer, the clinical significance of OLFM4 is still unclear. In the present study, SWATH-MS is used as a tool for the robust identification and quantification of breast tissue proteins. SWATH-MS data show that OLFM4 expression is higher in DCIS than in invasive breast cancer. In-depth analysis of the breast tumor proteome show that OLFM4 is a favorable pronostic marker. Serum OLFM4 levels in peripheral blood are also analyzed by ELISA in 825 cases, including 94 cases of healthy individuals, 61 cases of non-invasive breast tumor (DCIS) and 670 cases of breast cancer (BC). It is found that serum OLFM4 levels are significantly higher in the DCIS cohort and in the breast cancer cohort compared with the healthy controls. This result suggests that circulating OLFM4 could be an interesting biomarker of early breast cancer. Data are available via ProteomeXchange with identifier PXD014194., (© 2019 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Background: Heterogeneity and lack of targeted therapies represent the two main impediments to precision treatment of triple-negative breast cancer (TNBC), and therefore, molecular subtyping and identification of therapeutic pathways are required to optimize medical care. The aim of the present study was to define robust TNBC subtypes with clinical relevance., Methods: Gene expression profiling by means of DNA chips was conducted in an internal TNBC cohort composed of 238 patients. In addition, external data (n = 257), obtained by using the same DNA chip, were used for validation. Fuzzy clustering was followed by functional annotation of the clusters. Immunohistochemistry was used to confirm transcriptomics results: CD138 and CD20 were used to test for plasma cell and B lymphocyte infiltrations, respectively; MECA79 and CD31 for tertiary lymphoid structures; and UCHL1/PGP9.5 and S100 for neurogenesis., Results: We identified three molecular clusters within TNBC: one molecular apocrine (C1) and two basal-like-enriched (C2 and C3). C2 presented pro-tumorigenic immune response (immune suppressive), high neurogenesis (nerve infiltration), and high biological aggressiveness. In contrast, C3 exhibited adaptive immune response associated with complete B cell differentiation that occurs in tertiary lymphoid structures, and immune checkpoint upregulation. External cohort subtyping by means of the same approach proved the robustness of these results. Furthermore, plasma cell and B lymphocyte infiltrates, tertiary lymphoid structures, and neurogenesis were validated at the protein levels by means of histological evaluation and immunohistochemistry., Conclusion: Our work showed that TNBC can be subcategorized in three different subtypes characterized by marked biological features, some of which could be targeted by specific therapies.

Background: ADAM8 (a disintegrin and metalloproteinase 8) protein promotes the invasive and metastatic phenotype of triple-negative breast cancer (TNBC) cells. High ADAM8 expression in breast cancer patients is an independent predictor of poor prognosis. Here, we investigated whether ADAM8 regulates specific miRNAs, their roles in aggressive phenotype, and potential use as biomarkers of disease., Methods: Microarray analysis was performed on RNA from MDA-MB-231 cells after transient ADAM8 knockdown using TaqMan miRNA cards. Changes in miRNA levels were confirmed using two ADAM8 siRNAs in TNBC cell lines. Kinase inhibitors, β1-integrin antagonist antibody, and different forms of ADAM8 were employed to elucidate the signaling pathway required for miR-720 expression. miR-720 levels were modulated using a specific antagomiR or a mimic, and effects on aggressive phenotype of TNBC cells were determined using Boyden chamber and 3D-Matrigel outgrowth assays. Plasma was isolated from mice before and after implantation of MDA-MB-231 cells and analyzed for miR-720 levels. Serum samples of TNBC patients were evaluated for their ADAM8 and miR-720 levels., Results: We identified 68 miRNAs differentially regulated upon ADAM8 knockdown, including decreased levels of secreted miR-720. Ectopic overexpression of wild-type ADAM8 or forms that lack metalloproteinase activity similarly induced miR-720 levels. The disintegrin and cysteine-rich domains of ADAM8 were shown to induce miR-720 via activation of a β1-integrin to ERK signaling cascade. Knockdown of miR-720 led to a significant decrease in migratory and invasive abilities of TNBC cells. Conversely, miR-720 overexpression rescued these properties. A profound increase in plasma levels of miR-720 was detected 7 days after TNBC cell inoculation into mouse mammary fat pads when tumors were barely palpable. Concordantly, miR-720 levels were found to be significantly higher in serum samples of TNBC patients with high ADAM8 expression., Conclusions: We have shown for the first time that miR-720 is induced by ADAM8 signaling via ERK and plays an essential role in promoting the aggressive phenotype of TNBCs. miR-720 is elevated in serum of patients with ADAM8-high TNBC and, in a group with other miRNAs downstream of ADAM8, holds promise as a biomarker for early detection of or treatment response of ADAM8-positive TNBCs.

Survivin overexpression, frequently found in breast cancers and others, is associated with poor prognosis. Its dual regulation of cell division and apoptosis makes it an attractive therapeutic target but its exact functions that are required for tumor maintenance are still elusive. Survivin protects cancer cells from genotoxic agents and this ability is generally assigned to a universal anti-apoptotic function. However, a specific role in cancer cell protection from DNA damage has been overlooked so far. We assessed DNA damage occurrence in Survivin-depleted breast cancer cells using γH2AX staining and comete assay. QPCR data and a gene conversion assay indicated that homologous recombination (HR) was impaired upon Survivin depletion. We conducted the analysis of Survivin and HR genes' expression in breast tumors. We revealed BRCAness phenotype of Survivin-depleted cells using cell death assays combined to PARP targeting. Survivin silencing leads to DNA double-strand breaks in breast cancer cells and functionally reduces HR. Survivin depletion decreases the transcription of a set of genes involved in HR, decreases RAD51 protein expression and impairs the endonuclease complex MUS81/EME1 involved in the resolution of Holliday junctions. Clinically, EME1, RAD51, EXO1, BLM expressions correlate with that of BIRC5 (coding for Survivin) and are of prognostic value. Functionally, Survivin depletion triggers p53 activation and sensitizes cancer cells to of PARP inhibition. We defined Survivin as a constitutive actor of HR in breast cancers, and implies that its inhibition would enhance cell vulnerability upon PARP inhibition.

Background: Breast cancer biological characteristics change as age advances. Today, there is a lack of knowledge regarding age-specific molecular alterations that characterize breast tumours, notably in elderly patients. The vast majority of studies that aimed at exploring breast cancer in function of age are based on clinico-pathological data. Gene-expression signatures (GES), which in some ways capture biological information in a non-reductionist manner, represent powerful tools able to explore tumour heterogeneity., Methods: Twenty-five GES were used for functional annotation of breast tumours in function of age: five for molecular subtyping, seven for immune response, three for metabolism, seven for critical pathways in cancer and three for prognosis. Affymetrix® genomics datasets were exclusively used to avoid cross-platform normalization issues. Available corresponding clinico-pathological data were also retrieved and analysed., Results: Fifteen publicly available datasets were pooled for a total of 2378 breast cancer patients (whole cohort), out of whom 1413 were of Caucasian origin. Three age groups were defined: ≤ 40 years (AG1), > 40 to < 70 years (AG2) and ≥ 70 years (AG3). We confirmed that age influenced the incidence of molecular subtypes. We found a significant growing incidence of luminal B and a decreasing kinetics for basal-like in function of age. We showed that AG3 luminal B tumours were less aggressive than AG1 luminal B tumours based on different GES (iron metabolism, mitochondrial oxidative phosphorylation and reactive stroma), recurrence score prognostic GES and histological grade (SBR). Contrary to tumours of young patients, tumours of elderly patients concentrated favourable GES scores: high oestrogen receptor and mitochondrial oxidative phosphorylation, low proliferation, basal-like, glycolysis, chromosomal instability and iron metabolism, and low GES prognostic scores (van't Veer 70-GES, genomic grade index and recurrence score)., Conclusions: Functional annotation of breast tumours by means of 25 GES demonstrated a decreasing aggressiveness of breast tumours in function of age. This strategy, which can be strengthened by increasing the number of representative GES to gain more insight into biological systems involved in this disease, provides a framework to develop rational therapeutic strategies in function of age.

To date, there is no available targeted therapy for patients who are diagnosed with triple-negative breast cancers (TNBC). The aim of this study was to identify a new specific target for specific treatments. Frozen primary tumors were collected from 83 adjuvant therapy-naive TNBC patients. These samples were used for global proteome profiling by iTRAQ-OFFGEL-LC-MS/MS approach in two series: a training cohort (n = 42) and a test set (n = 41). Patients who remains free of local or distant metastasis for a minimum of 5 years after surgery were classified in the no-relapse group; the others were in the relapse group. OPLS and Kaplan-Meier analyses were performed to select candidate markers, which were validated by immunohistochemistry. Three proteins were identified in the training set and validated in the test set by Kaplan-Meier method and immunohistochemistry (IHC): TrpRS as a good prognostic markers and DP and TSP1 as bad prognostic markers. We propose the establishment of an IHC test to calculate the score of TrpRS, DP, and TSP1 in TNBC tumors to evaluate the degree of aggressiveness of the tumors. Finally, we propose that DP and TSP1 could provide therapeutic targets for specific treatments., (© 2015 by The American Society for Biochemistry and Molecular Biology, Inc.)

Introduction: Triple-negative breast cancers need to be refined in order to identify therapeutic subgroups of patients., Methods: We conducted an unsupervised analysis of microarray gene-expression profiles of 107 triple-negative breast cancer patients and undertook robust functional annotation of the molecular entities found by means of numerous approaches including immunohistochemistry and gene-expression signatures. A triple-negative external cohort (n=87) was used for validation., Results: Fuzzy clustering separated triple-negative tumours into three clusters: C1 (22.4%), C2 (44.9%) and C3 (32.7%). C1 patients were older (mean=64.6 years) than C2 (mean=56.8 years; P=0.03) and C3 patients (mean=51.9 years; P=0.0004). Histological grade and Nottingham prognostic index were higher in C2 and C3 than in C1 (P<0.0001 for both comparisons). Significant event-free survival (P=0.03) was found according to cluster membership: patients belonging to C3 had a better outcome than patients in C1 (P=0.01) and C2 (P=0.02). Event-free survival analysis results were confirmed when our cohort was pooled with the external cohort (n=194; P=0.01). Functional annotation showed that 22% of triple-negative patients were not basal-like (C1). C1 was enriched in luminal subtypes and positive androgen receptor (luminal androgen receptor). C2 could be considered as an almost pure basal-like cluster. C3, enriched in basal-like subtypes but to a lesser extent, included 26% of claudin-low subtypes. Dissection of immune response showed that high immune response and low M2-like macrophages were a hallmark of C3, and that these patients had a better event-free survival than C2 patients, characterized by low immune response and high M2-like macrophages: P=0.02 for our cohort, and P=0.03 for pooled cohorts., Conclusions: We identified three subtypes of triple-negative patients: luminal androgen receptor (22%), basal-like with low immune response and high M2-like macrophages (45%), and basal-enriched with high immune response and low M2-like macrophages (33%). We noted out that macrophages and other immune effectors offer a variety of therapeutic targets in breast cancer, and particularly in triple-negative basal-like tumours. Furthermore, we showed that CK5 antibody was better suited than CK5/6 antibody to subtype triple-negative patients.

Background: The standard therapy regimen of conventional osteosarcoma includes neoadjuvant chemotherapy followed by surgical resection and postoperative chemotherapy. The percentage of necrotic tissue following induction chemotherapy is assessed by using the Huvos grading system, which classifies patients as "poor responders" (PR) and "good responders" (GR). The aim of this study was to identify molecular markers expressed differentially between good and poor responders to neoadjuvant chemotherapy in order to predict the response to chemotherapy in conventional osteosarcomas before beginning treatment., Methods: Suppression Substractive Hybridization (SSH) was performed by using cDNA from frozen biopsy specimens. Expression of selected relevant genes identified by SSH was validated by using QRT-PCR. Immunohistochemistry (IHC) on tissue microarray (TMA) sections of 52 biopsies was performed to investigate protein expression in an independent cohort., Results: ERK1 and STAT3 mRNA level were significantly different between PR and GR in an independent cohort. Phosphorylated STAT3 and ERK1 expressions by IHC on TMA were correlated with poor response to chemotherapy., Conclusions: Our results suggest that ERK1 and STAT3 expression are good predictive markers for chemotherapy response and that inhibitors might be used in combination with common chemotherapeutic drugs in conventional osteosarcomas.

Triple-negative breast cancers (TNBC) lacking estrogen and progesterone receptors and HER2 amplification have a relatively high risk of metastatic dissemination, but the mechanistic basis for this risk is not understood. Here, we report that serum levels of CD95 ligand (CD95L) are higher in patients with TNBC than in other patients with breast cancer. Metalloprotease-mediated cleavage of CD95L expressed by endothelial cells surrounding tumors generates a gradient that promotes cell motility due to the formation of an unconventional CD95-containing receptosome called the motility-inducing signaling complex. The formation of this complex was instrumental for Nox3-driven reactive oxygen species generation. Mechanistic investigations revealed a Yes-Orai1-EGFR-PI3K pathway that triggered migration of TNBC cells exposed to CD95L. Our findings establish a prometastatic function for metalloprotease-cleaved CD95L in TNBCs, revisiting its role in carcinogenesis., (©2013 AACR)

We recently developed a user-friendly web-based application called bc-GenExMiner (http://bcgenex.centregauducheau.fr), which offered the possibility to evaluate prognostic informativity of genes in breast cancer by means of a 'prognostic module'. In this study, we develop a new module called 'correlation module', which includes three kinds of gene expression correlation analyses. The first one computes correlation coefficient between 2 or more (up to 10) chosen genes. The second one produces two lists of genes that are most correlated (positively and negatively) to a 'tested' gene. A gene ontology (GO) mining function is also proposed to explore GO 'biological process', 'molecular function' and 'cellular component' terms enrichment for the output lists of most correlated genes. The third one explores gene expression correlation between the 15 telomeric and 15 centromeric genes surrounding a 'tested' gene. These correlation analyses can be performed in different groups of patients: all patients (without any subtyping), in molecular subtypes (basal-like, HER2+, luminal A and luminal B) and according to oestrogen receptor status. Validation tests based on published data showed that these automatized analyses lead to results consistent with studies' conclusions. In brief, this new module has been developed to help basic researchers explore molecular mechanisms of breast cancer. DATABASE URL: http://bcgenex.centregauducheau.fr

Induction of epithelial-to-mesenchymal transition (EMT) by TGF-β1 requires Ras signaling. We recently identified the transcriptional repressor Blimp-1 (PRDM1) as a downstream effector of the NF-κB, RelB/Bcl-2/Ras-driven pathway that promotes breast cancer cell migration. As the RelB/Blimp-1 pathway similarly required Ras signaling activation, we tested whether Blimp-1 plays a role in TGF-β1-mediated EMT. Here, TGF-β1 treatment of untransformed NMuMG mammary epithelial and MDA-MB-231 breast cancer cells was shown to induce Blimp-1 expression, which promoted an EMT signature and cell migration. TGFB1 and BLIMP1 RNA levels were correlated in patient breast tumors. BLIMP1 gene transcription was activated by TGF-β1 via a c-Raf (RAF1) to AP-1 pathway. Blimp-1 induced expression of the EMT master regulator Snail (SNAI1) via repressing BMP-5, which inhibited Snail expression upon TGF-β1 treatment. Interestingly, a similar cascade was observed during postnatal mouse mammary gland development. RelB expression was detected early in pregnancy followed progressively by Blimp-1 and then Snail; whereas, BMP-5 levels were high in nulliparous and regressing glands. Finally, lower BMP5 RNA levels were detected in patient breast tumors versus normal tissues, and correlated with cancer recurrence. Thus, the Ras effector Blimp-1 plays an essential role in TGF-β1-induced EMT via repression of BMP-5 in breast cancer.

Novel prognostic biomarkers are imperatively needed to help direct treatment decisions by typing subgroups of node-negative breast cancer patients. Large screening of different biological compartments, such as the proteome, by means of high throughput techniques may greatly help scientists to find such markers. The present retrospective multicentric study included 268 node-negative breast cancer patients. We used a proteomic approach of SELDI-TOF-MS screening to identify differentially expressed cytosolic proteins with prognostic impact. The screening cohort was composed of 198 patients. Seventy supplementary patients were included for validation. Immunohistochemistry (IHC) and immunoassay (IA) were run to confirm the prognostic role of the marker identified by SELDI-TOF-MS screening. IHC was also used to explore links between selected marker and epithelial-mesenchymal transition (EMT)-like, proliferation and macrophage markers. Ferritin light chain (FTL) was identified as an independent prognostic marker (HR = 1.30-95% CI: 1.10-1.50, p = 0.001). Validation step by means of IHC and IA confirmed the prognostic value of FTL level. CD68 IHC showed that FTL was stored in tumor-associated macrophages (TAM), which exhibit an M2-like phenotype. We report here, first, the validation of FTL as a breast tumor prognostic biomarker in node-negative patients, and second, the fact that FTL is stored in TAM., (Copyright © 2011 UICC.)

We used a 2D-electrophoresis (2-DE) proteomic approach to identify novel biomarkers in node-negative breast cancers. This retrospective study focused on a population of patients with ductal pN0M0 tumours. A subset of patients who developed metastases and in whose tumours were found high levels of uPA and PAI-1 (metastatic relapse, MR: n=20) were compared to another subset in whom no metastatic relapse occurred and whose tumours were found to have low levels of uPA and PAI-1 (no relapse, NR: n=21). We used a 2-DE coupled with MS approach to screen cytosol fractions using two pH-gradient scales, a broad scale (3.0-11.0) and a narrower scale focussing in on a protein rich region (5.0-8.0). This study was conducted on 41 cytosol specimens analyzed in duplicate on two platforms. The differential analysis of more than 2,000 spots in 2-DE gels, obtained on the two platforms, allowed the identification of 13 proteins which were confirmed by western blotting. Two proteins, GPDA and FABP4 were down-regulated in the MR subset whereas all the others were up-regulated. An in silico analysis revealed that GMPS (GUAA), GAPDH (G3P), CFL1 (COF1) and FTL (FRIL), the most informative genes, displayed a proliferation profile (high expression in basal-like, HER2+ and luminal B molecular subtypes). Inversely, similar to FABP4, GPD1 [GPDA] displayed a high expression in luminal A subtype, a profile characteristic of tumour suppressor genes. Despite the small size of our cohort, the 2-DE analysis gave interesting results which were confirmed by the in silico analysis showing that some of the corresponding genes had a strong prognostic impact in breast cancer, mostly because of their link with proliferation: GMPS, GAPDH, FTL and GPD1. A validation phase on a larger cohort is now needed before these biomarkers could be considered for use in clinical practice.

Gene prognostic meta-analyses should benefit from breast tumour genomic data obtained during the last decade. The aim was to develop a user-friendly, web-based application, based on DNA microarrays results, called "breast cancer Gene-Expression Miner" (bc-GenExMiner) to improve gene prognostic analysis performance by using the same bioinformatics process. bc-GenExMiner was developed as a web-based tool including a MySQL relational database. Survival analyses are performed with R statistical software and packages. Molecular subtyping was performed by means of three single sample predictors (SSPs) and three subtype clustering models (SCMs). Twenty-one public data sets have been included. Among the 3,414 recovered breast cancer patients, 1,209 experienced a pejorative event. Molecular subtyping by means of three SSPs and three SCMs was performed for 3,063 patients. Furthermore, three robust lists of stable subtyped patients were built to maximize reliability of molecular assignment. Gene prognostic analyses are done by means of univariate Cox proportional hazards model and may be conducted on cohorts split by nodal (N), oestrogen receptor (ER), or molecular subtype status. To evaluate independent prognostic impact of genes relative to Nottingham Prognostic Index and Adjuvant! Online, adjusted Cox proportional hazards models are performed. bc-GenExMiner allows researchers without specific computation skills to easily and quickly evaluate the in vivo prognostic role of genes in breast cancer by means of Cox proportional hazards model on large pooled cohorts, which may be split according to different prognostic parameters: N, ER, and molecular subtype. Prognostic analyses by molecular subtype may also be performed in three robust molecular subtype classifications.

Background: Anti-apoptotic signals induced downstream of HER2 are known to contribute to the resistance to current treatments of breast cancer cells that overexpress this member of the EGFR family. Whether or not some of these signals are also involved in tumor maintenance by counteracting constitutive death signals is much less understood. To address this, we investigated what role anti- and pro-apoptotic Bcl-2 family members, key regulators of cancer cell survival, might play in the viability of HER2 overexpressing breast cancer cells., Methods: We used cell lines as an in vitro model of HER2-overexpressing cells in order to evaluate how anti-apoptotic Bcl-2, Bcl-xL and Mcl-1, and pro-apoptotic Puma and Bim impact on their survival, and to investigate how the constitutive expression of these proteins is regulated. Expression of the proteins of interest was confirmed using lysates from HER2-overexpressing tumors and through analysis of publicly available RNA expression data., Results: We show that the depletion of Mcl-1 is sufficient to induce apoptosis in HER2-overexpressing breast cancer cells. This Mcl-1 dependence is due to Bim expression and it directly results from oncogenic signaling, as depletion of the oncoprotein c-Myc, which occupies regions of the Bim promoter as evaluated in ChIP assays, decreases Bim levels and mitigates Mcl-1 dependence. Consistently, a reduction of c-Myc expression by inhibition of mTORC1 activity abrogates occupancy of the Bim promoter by c-Myc, decreases Bim expression and promotes tolerance to Mcl-1 depletion. Western blot analysis confirms that naïve HER2-overexpressing tumors constitutively express detectable levels of Mcl-1 and Bim, while expression data hint on enrichment for Mcl-1 transcripts in these tumors., Conclusions: This work establishes that, in HER2-overexpressing tumors, it is necessary, and maybe sufficient, to therapeutically impact on the Mcl-1/Bim balance for efficient induction of cancer cell death.

Fibroblast growth factor receptor 4 (FGFR4) contains a Gly388Arg functional polymorphism (rs351855) that has shown contrasting results in association studies. In this study, we assessed the association between the FGFR4 Gly388Arg polymorphism and cancer prognosis. Meta-analysis and pooled analysis of 6817 and 2537 cancer cases, respectively, were carried out by nodal status and overall survival. The study included the following types of cancer: brain, breast, colorectal, head and neck, larynx, lung, melanoma, prostate, sarcomas. A statistically significant association between the Arg388Arg genotype and nodal involvement was found in the meta-analysis (odds ratio=1.33, 95% confidence interval 1.01-1.74). In the pooled analysis, the Arg388 allele carriers showed an increased hazard of poor overall survival compared with homozygous carriers of the common Gly388 allele, even after adjusting for nodal status (hazard ratio=1.21, 95% confidence interval 1.05-1.40). These results provide evidence of a role for the FGFR4 Gly388Arg polymorphism in modulating patients' outcome in different types of cancer, thus offering to clinicians a new marker to predict predisposition to poor survival in cancer patients.

The highly immunogenic human tumor antigen NY-ESO-1 (ESO) is a target of choice for anti-cancer immune therapy. In this study, we assessed spontaneous antibody (Ab) responses to ESO in a large cohort of patients with primary breast cancer (BC) and addressed the correlation between the presence of anti-ESO Ab, the expression of ESO in the tumors and their characteristics. We found detectable Ab responses to ESO in 1% of the patients. Tumors from patients with circulating Ab to ESO exhibited common characteristics, being mainly hormone receptor (HR)⁻ invasive ductal carcinomas of high grade, including both HER2⁻ and HER2⁺ tumors. In line with these results, we detected ESO expression in 20% of primary HR⁻ BC, including both ESO Ab⁺ and Ab⁻ patients, but not in HR⁺ BC. Interestingly, whereas expression levels in ESO⁺ BC were not significantly different between ESO Ab⁺ and Ab⁻ patients, the former had, in average, significantly higher numbers of tumor-infiltrated lymph nodes, indicating that lymph node invasion may be required for the development of spontaneous anti-tumor immune responses. Thus, the presence of ESO Ab identifies a tumor subtype of HR⁻ (HER2⁻ or HER2⁺) primary BC with frequent ESO expression and, together with the assessment of antigen expression in the tumor, may be instrumental for the selection of patients for whom ESO-based immunotherapy may complement standard therapy.

Interleukin-6 (IL-6) is a cytokine involved in different physiologic and pathophysiologic processes including carcinogenesis. In 2003, a single nucleotide polymorphism (-174G/C) of the IL-6 gene promoter has been linked to breast cancer prognosis in node-positive (N+) breast cancer patients. Since, different studies have led to conflicting conclusions about its role as a prognostic and/or diagnostic marker. The primary aim of our study was to investigate the link between -174G/C polymorphism and breast cancer risk on the one hand, and -174G/C polymorphism and prognosis in different groups of patients: sporadic N+breast cancers (n=138), sporadic N- breast cancers (n=95) and familial breast cancer (n=60) on the other hand. The variables of interest were disease-free survival and overall survival. The secondary aim of the study was to screen IL-6 gene promoter using direct sequencing to identify new polymorphisms in our French Caucasian breast cancer population. No association or trend of association between -174G/C polymorphism of IL-6 gene promoter gene and breast cancer diagnosis or prognosis was shown, even in meta-analyses. Furthermore, we have identified four novel polymorphic sites in the IL-6 gene promoter region: -764G-->A, -757C-->T, -233T-->A, 15C-->A.

The therapy regimen of high-grade osteosarcoma includes chemotherapy followed by surgical resection and postoperative chemotherapy. The degree of necrosis following definitive surgery remains the only reliable prognostic factor and is used to guide the choice of postoperative chemotherapy. The aim of this study was to find molecular markers able to classify patients with an osteosarcoma as good or poor responders to chemotherapy before beginning treatment. Gene expression screening of 20 nonmetastatic high-grade osteosarcoma patients was performed using cDNA microarray. Expression of selected relevant genes was validated using QRT-PCR. Immunohistochemistry on tissue microarrays sections of 73 biopsies was performed to investigate protein expression. Fluorescent in situ hybridization was performed for RPL8 gene. We have found that HSD17B10 gene expression was up-regulated in poor responders and that immunohistochemistry expression of HSD17B10 on biopsy before treatment was correlated to response to chemotherapy. Other results include correlation of IFITM2, IFITM3, and RPL8 gene expression to chemotherapy response. A statistical correlation was found between polysomy 8 or gain of RPL8 and good response to chemotherapy. These data suggest that HSD17B10, RPL8, IFITM2, and IFITM3 genes are involved in the response to the chemotherapy and that HSD17B10 may be a therapeutic target. RPL8 and IFITM2 may be useful in the assessment at diagnosis and for stratifying patients taking part in randomized trials.

Currently, no prognostic gene-expression signature (GES) established from node-positive breast cancer cohorts, able to predict evolution after systemic adjuvant chemotherapy, exists. Gene-expression profiles of 252 node-positive breast cancer patients (median follow-up: 7.7 years), mostly included in a randomized clinical trial (PACS01), receiving systemic adjuvant regimen, were determined by means of cDNA custom array. In the training cohort, we established a GES composed of 38 genes (38-GES) for the purpose of predicting metastasis-free survival. The 38-GES yielded unadjusted hazard ratio (HR) of 4.86 (95% confidence interval = 2.76-8.56). Even when adjusted with the best two clinicopathological prognostic indexes: Nottingham prognostic index (NPI) and Adjuvant!, 38-GES HRs were 3.30 (1.81-5.99) and 3.40 (1.85-6.24), respectively. Furthermore, 38-GES improved NPI and Adjuvant! classification. In particular, NPI intermediate-risk patients were divided into 2/3 close to low-risk group and 1/3 close to high-risk group (HR = 6.97 [2.51-19.36]). Similarly, Adjuvant! intermediate-risk patients were divided into 2/3 close to low-risk group and 1/3 close to high-risk group (HR = 4.34 [1.64-11.48]). The 38-GES was validated on gene-expression datasets from three external node-positive breast cancer subcohorts (n = 224) generated from different microarray platforms, with HR = 2.95 (1.74-5.01). Moreover, 38-GES showed prognostic performance in supplementary cohorts with different lymph-node status and endpoints (1,040 new patients). The 38-GES represents a robust tool able to type systemic adjuvant treated node-positive patients at high risk of metastatic relapse, and is especially powerful to refine NPI and Adjuvant! classification for those patients.

Purpose: Survival of patients with multiple myeloma is highly heterogeneous, from periods of a few weeks to more than 10 years. We used gene expression profiles of myeloma cells obtained at diagnosis to identify broadly applicable prognostic markers., Patients and Methods: In a training set of 182 patients, we used supervised methods to identify individual genes associated with length of survival. A survival model was built from these genes. The validity of our model was assessed in our test set of 68 patients and in three independent cohorts comprising 853 patients with multiple myeloma., Results: The 15 strongest genes associated with the length of survival were used to calculate a risk score and to stratify patients into low-risk and high-risk groups. The survival-predictor score was significantly associated with survival in both the training and test sets and in the external validation cohorts. The Kaplan-Meier estimates of rates of survival at 3 years were 90.5% (95% CI, 85.6% to 95.3%) and 47.4% (95% CI, 33.5% to 60.1%), respectively, in our patients having a low risk or high risk independently of traditional prognostic factors. High-risk patients constituted a homogeneous biologic entity characterized by the overexpression of genes involved in cell cycle progression and its surveillance, whereas low-risk patients were heterogeneous and displayed hyperdiploid signatures., Conclusion: Gene expression-based survival prediction and molecular features associated with high-risk patients may be useful for developing prognostic markers and may provide basis to treat these patients with new targeted antimitotics.

Breast cancer is a very heterogeneous disease, and markers for disease subtypes and therapy response remain poorly defined. For that reason, we employed a retrospective study in node-positive breast cancer to identify molecular signatures of gene expression correlating with metastatic free survival. Patients were primarily included in FEC100 (5-fluorouracil 500 mg/m(2), epirubicin 100 mg/m(2) and cyclophosphamide 500 mg/m(2)) arms of two multicentric prospective adjuvant clinical trials (PACS01 and PEGASE01-FNCLCC cooperative group). Data from nylon microarrays containing 8,032 cDNA unique sequences, representing 5,776 distinct genes, have been used to develop a predictive model for treatment outcome. We obtained the gene expression profiles for 150 of these patients, and used stringent univariate selection techniques based on Cox regression combined with principal component analysis to identify a genomic signature of metastatic relapse after adjuvant FEC100 regimen. Most of the 14 selected genes have a clear role in breast cancer, carcinogenesis or chemotherapy resistance. Six genes have been previously described in other genomic studies (UBE2C, CENPF, C16orf61 [DC13], STMN1, CCT5 and BCL2A1). Furthermore, we showed the interest of combining transcriptomic data with clinical data into a clinicogenomic model for patients subtyping. The described model adds predictive accuracy to that provided by the well-established Nottingham prognostic index or by our genomic signature alone.

Novel prognostic biomarkers are imperatively needed to help direct treatment decisions by typing subgroups of node-negative breast cancer patients. The current study has used a proteomic approach of SELDI-TOF-MS screening to identify differentially cytosolic expressed proteins with a prognostic impact in 30 node-negative breast cancer patients with no relapse versus 30 patients with metastatic relapse. The data analysis took into account 73 peaks, among which 2 proved, by means of univariate Cox regression, to have a good cumulative prognostic-informative power. Repeated random sampling (n = 500) was performed to ensure the reliability of the peaks. Optimized thresholds were then computed to use both peaks as risk factors and, adding them to the St. Gallen ones, improve the prognostic classification of node-negative breast cancer patients. Identification of ubiquitin and ferritin light chain (FLC), corresponding to the two peaks of interest, was obtained using ProteinChip LDI-Qq-TOF-MS. Differential expression of the two proteins was further confirmed by Western blotting analyses and immunohistochemistry. SELDI-TOF-MS protein profiling clearly showed that a high level of cytosolic ubiquitin and/or a low level of FLC were associated with a good prognosis in breast cancer.

Background: In breast cancer treatment, FEC100 (fluorouracil, epirubicin and cyclophosphamide) chemotherapy delivered in a neoadjuvant setting is still applied empirically to all patients. The aim of this study was to establish a multigene classifier of sensitivity to neoadjuvant FEC100., Materials and Methods: cDNA nylon microarrays, containing 15,000 genes, were used to analyze the gene expression profiles of tumour biopsies collected before chemotherapy: 8 were typed as pathological complete responders and 8 as non-responders according to their histological and clinical responses., Results: A classifier was generated by means of Linear Discriminant Analysis and was evaluated by leave-one-out cross-validation. The difference of expression of the NDUFB5 gene (NADH dehydrogenase 1 beta subcomplex, 5), the best discriminating gene, was verified using RT-PCR., Conclusion: This preliminary work requires further investigations, especially in terms of larger cohorts, before the results can be transferred to clinical practice., (Copyright© 2006 International Institute of Anticaner Research (Dr. John G. Delinassios), All rights reserved.)