Pooling breast cancer datasets has a synergetic effect on classification performance and improves signature stability

Background: Michiels et al. (Lancet 2005; 365: 488-92) employed a resampling strategy to show that the genes identified as predictors of prognosis from resamplings of a single gene expression dataset are highly variable. The genes most frequently identified in the separate resamplings were put forward as a 'gold standard'. On a higher level, breast cancer datasets collected by different institutions can be considered as resamplings from the underlying breast cancer population. The limited overlap between published prognostic signatures confirms the trend of signature instability identified by the resampling strategy. Six breast cancer datasets, totaling 947 samples, all measured on the Affymetrix platform, are currently available. This provides a unique opportunity to employ a substantial dataset to investigate the effects of pooling datasets on classifier accuracy, signature stability and enrichment of functional categories. Results: We show that the resampling strategy produces a suboptimal ranking of genes, which can not be considered to be a 'gold standard'. When pooling breast cancer datasets, we observed a synergetic effect on the classification performance in 73% of the cases. We also observe a significant positive correlation between the number of datasets that is pooled, the validation performance, the number of genes selected, and the enrichment of specific functional categories. In addition, we have evaluated the support for five explanations that have been postulated for the limited overlap of signatures. Conclusion: The limited overlap of current signature genes can be attributed to small sample size. Pooling datasets results in more accurate classification and a convergence of signature genes. We therefore advocate the analysis of new data within the context of a compendium, rather than analysis in isolatio

Gene List significance at-a-glance with GeneValorization

Motivation: High-throughput technologies provide fundamental informations concerning thousands of genes. Many of the current research laboratories daily use one or more of these technologies and end-up with lists of genes. Assessing the originality of the results obtained includes being aware of the number of publications available concerning individual or multiple genes and accessing information about these publications. Faced with the exponential growth of publications avaliable and number of genes involved in a study, this task is becoming particularly difficult to achieve

Clinical spectrum and evolution of immune-checkpoint inhibitors toxicities over a decade-a worldwide perspective.

BACKGROUND: Immune-checkpoint inhibitors (ICI) have revolutionized cancer treatment by harnessing the immune system but ICI can induce life-threatening immune-related adverse events (irAE) affecting every organ. METHODS: We extracted irAE from VigiBase, the international pharmacovigilance database, first reported in 2008 until 01/2023 to characterize irAE reporting trends, clinical features, risk factors and outcomes. FINDINGS: We distinguished 25 types of irAE (n = 50,347cases, single irAE/case in 84.9%). Cases mainly involved anti-PD1 (programmed-death-1) monotherapy (62.4%) in male (61.7%) aged 64.3 ± 12.6 years. After 2020 vs. prior to 2016, proportion of anti-CTLA4 (Cytotoxic-T-Lymphocyte-Antigen-4) monotherapy prescription almost vanished (1.6% vs. 47%, respectively) contrasting with increased use of anti-PDL1 (PD1-ligand) monotherapy (18% vs. 0.9%) and anti-CTLA4+anti-PD(L)1 combination (20% vs. 8.9%). Anti-LAG3 (Lymphocyte-Activation-Gene-3) prescription was limited (<1%) in the studied timeframe. After 2020, over 14 different cancer types were treated vs. almost exclusively melanoma and lung cancers before 2016. Overall, the most reported irAE were skin reactions (22.9%), pneumonitis (18.5%), enterocolitis (14.4%) and thyroiditis (12.1%). ICI-myotoxicities (6.6%) included myositis, myocarditis and myasthenia-gravis like syndrome and were the most overlapping irAE (up to 30% overlap, vs. <3% in general for other inter-irAE overlap). The top factors associated with specific irAE (odds-ratio>5) were presence of thymic cancer for ICI-myotoxicities or hepatitis; presence of melanoma for vitiligo, uveitis or sarcoidosis; specific types of ICI regimen (anti-LAG3 for meningitis, anti-CTLA4 for hypophysitis); and specific reporting regions (eastern Asia for cholangitis). Median time-to-onset ranged from 31 to 273 days, being shortest for myotoxicities and most delayed for skin-bullous auto-immune reactions. Overall fatality was highest for myocarditis = 27.6%, myasthenia = 23.1%, severe cutaneous adverse reactions (SCAR) = 22.1%, myositis = 21.9%, pneumonitis = 21%, and encephalomyelitis = 18%; generally decreasing after 2020, except for myasthenia and SCAR. When reported, irAE recurrence rate after rechallenge was 28.9% (n = 275/951). INTERPRETATION: This up-to-date comprehensive worldwide pharmacovigilance study defines the spectrum, characteristics, and evolution of irAE reporting summarizing over a decade of use. Multiple risk factors and clinical peculiarities for specific irAE have been identified as signals to guide clinical practice and future research. FUNDING: Paul Gougis was supported by the academic program: Contrats ED: Programme blanc Institut Curie PSL for the conduct of his PhD. Baptiste Abbar was supported by the Fondation ARC Pour le Rechercher Sur le Cancer. The RT2L research group (Institut Curie) was supported by the academic program SHS INCa, Sanofi iTech award, and by Monoprix∗

A comprehensive analysis of prognostic signatures reveals the high predictive capacity of the proliferation, immune response and RNA splicing modules in breast cancer.

INTRODUCTION: Several gene expression signatures have been proposed and demonstrated to be predictive of outcome in breast cancer. In the present article we address the following issues: Do these signatures perform similarly? Are there (common) molecular processes reported by these signatures? Can better prognostic predictors be constructed based on these identified molecular processes? METHODS: We performed a comprehensive analysis of the performance of nine gene expression signatures on seven different breast cancer datasets. To better characterize the functional processes associated with these signatures, we enlarged each signature by including all probes with a significant correlation to at least one of the genes in the original signature. The enrichment of functional groups was assessed using four ontology databases. RESULTS: The classification performance of the nine gene expression signatures is very similar in terms of assigning a sample to either a poor outcome group or a good outcome group. Nevertheless the concordance in classification at the sample level is low, with only 50% of the breast cancer samples classified in the same outcome group by all classifiers. The predictive accuracy decreases with the number of poor outcome assignments given to a sample. The best classification performance was obtained for the group of patients with only good outcome assignments. Enrichment analysis of the enlarged signatures revealed 11 functional modules with prognostic ability. The combination of the RNA-splicing and immune modules resulted in a classifier with high prognostic performance on an independent validation set. CONCLUSIONS: The study revealed that the nine signatures perform similarly but exhibit a large degree of discordance in prognostic group assignment. Functional analyses indicate that proliferation is a common cellular process, but that other functional categories are also enriched and show independent prognostic ability. We provide new evidence of the potentially promising prognostic impact of immunity and RNA-splicing processes in breast cancer.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

8p22 MTUS1 Gene Product ATIP3 Is a Novel Anti-Mitotic Protein Underexpressed in Invasive Breast Carcinoma of Poor Prognosis

BACKGROUND: Breast cancer is a heterogeneous disease that is not totally eradicated by current therapies. The classification of breast tumors into distinct molecular subtypes by gene profiling and immunodetection of surrogate markers has proven useful for tumor prognosis and prediction of effective targeted treatments. The challenge now is to identify molecular biomarkers that may be of functional relevance for personalized therapy of breast tumors with poor outcome that do not respond to available treatments. The Mitochondrial Tumor Suppressor (MTUS1) gene is an interesting candidate whose expression is reduced in colon, pancreas, ovary and oral cancers. The present study investigates the expression and functional effects of MTUS1 gene products in breast cancer. METHODS AND FINDINGS: By means of gene array analysis, real-time RT-PCR and immunohistochemistry, we show here that MTUS1/ATIP3 is significantly down-regulated in a series of 151 infiltrating breast cancer carcinomas as compared to normal breast tissue. Low levels of ATIP3 correlate with high grade of the tumor and the occurrence of distant metastasis. ATIP3 levels are also significantly reduced in triple negative (ER- PR- HER2-) breast carcinomas, a subgroup of highly proliferative tumors with poor outcome and no available targeted therapy. Functional studies indicate that silencing ATIP3 expression by siRNA increases breast cancer cell proliferation. Conversely, restoring endogenous levels of ATIP3 expression leads to reduced cancer cell proliferation, clonogenicity, anchorage-independent growth, and reduces the incidence and size of xenografts grown in vivo. We provide evidence that ATIP3 associates with the microtubule cytoskeleton and localizes at the centrosomes, mitotic spindle and intercellular bridge during cell division. Accordingly, live cell imaging indicates that ATIP3 expression alters the progression of cell division by promoting prolonged metaphase, thereby leading to a reduced number of cells ungergoing active mitosis. CONCLUSIONS: Our results identify for the first time ATIP3 as a novel microtubule-associated protein whose expression is significantly reduced in highly proliferative breast carcinomas of poor clinical outcome. ATIP3 re-expression limits tumor cell proliferation in vitro and in vivo, suggesting that this protein may represent a novel useful biomarker and an interesting candidate for future targeted therapies of aggressive breast cancer

Respective Prognostic Value of Genomic Grade and Histological Proliferation Markers in Early Stage (pN0) Breast Carcinoma

Genomic grade (GG) is a 97-gene signature which improves the accuracy and prognostic value of histological grade (HG) in invasive breast carcinoma. Since most of the genes included in the GG are involved in cell proliferation, we performed a retrospective study to compare the prognostic value of GG, Mitotic Index and Ki67 score.A series of 163 consecutive breast cancers was retained (pT1-2, pN0, pM0, 10-yr follow-up). GG was computed using MapQuant Dx(R).GG was low (GG-1) in 48%, high (GG-3) in 31% and equivocal in 21% of cases. For HG-2 tumors, 50% were classified as GG-1, 18% as GG-3 whereas 31% remained equivocal. In a subgroup of 132 ER+/HER2- tumors GG was the most significant prognostic factor in multivariate Cox regression analysis adjusted for age and tumor size (HR = 5.23, p = 0.02).In a reference comprehensive cancer center setting, compared to histological grade, GG added significant information on cell proliferation in breast cancers. In patients with HG-2 carcinoma, applying the GG to guide the treatment scheme could lead to a reduction in adjuvant therapy prescription. However, based on the results observed and considering (i) the relatively close prognostic values of GG and Ki67, (ii) the reclassification of about 30% of HG-2 tumors as Equivocal GG and (iii) the economical and technical requirements of the MapQuant micro-array GG test, the availability in the near future of a PCR-based Genomic Grade test with improved performances may lead to an introduction in clinical routine of this test for histological grade 2, ER positive, HER2 negative breast carcinoma

Analyse du profil d'expression par la technique des puces à ADN (Application à la caractérisation moléculaire et à la détermination du pronostic des cancers canalaires infiltrants du sein)

LE KREMLIN-B.- PARIS 11-BU Méd (940432101) / SudocSudocFranceF