An introduction to low-level analysis methods of DNA microarray data

This article gives an overview over the methods used in the low--level analysis of gene expression data generated using DNA microarrays. This type of experiment allows to determine relative levels of nucleic acid abundance in a set of tissues or cell populations for thousands of transcripts or loci simultaneously. Careful statistical design and analysis are essential to improve the efficiency and reliability of microarray experiments throughout the data acquisition and analysis process. This includes the design of probes, the experimental design, the image analysis of microarray scanned images, the normalization of fluorescence intensities, the assessment of the quality of microarray data and incorporation of quality information in subsequent analyses, the combination of information across arrays and across sets of experiments, the discovery and recognition of patterns in expression at the single gene and multiple gene levels, and the assessment of significance of these findings, considering the fact that there is a lot of noise and thus random features in the data. For all of these components, access to a flexible and efficient statistical computing environment is an essential aspect

Origin and pathogenesis of nodular lymphocyte–predominant Hodgkin lymphoma as revealed by global gene expression analysis

The pathogenesis of nodular lymphocyte–predominant Hodgkin lymphoma (NLPHL) and its relationship to other lymphomas are largely unknown. This is partly because of the technical challenge of analyzing its rare neoplastic lymphocytic and histiocytic (L&H) cells, which are dispersed in an abundant nonneoplastic cellular microenvironment. We performed a genome-wide expression study of microdissected L&H lymphoma cells in comparison to normal and other malignant B cells that indicated a relationship of L&H cells to and/or that they originate from germinal center B cells at the transition to memory B cells. L&H cells show a surprisingly high similarity to the tumor cells of T cell–rich B cell lymphoma and classical Hodgkin lymphoma, a partial loss of their B cell phenotype, and deregulation of many apoptosis regulators and putative oncogenes. Importantly, L&H cells are characterized by constitutive nuclear factor {kappa}B activity and aberrant extracellular signal-regulated kinase signaling. Thus, these findings shed new light on the nature of L&H cells, reveal several novel pathogenetic mechanisms in NLPHL, and may help in differential diagnosis and lead to novel therapeutic strategies

Origin and pathogenesis of nodular lymphocyte–predominant Hodgkin lymphoma as revealed by global gene expression analysis

The pathogenesis of nodular lymphocyte–predominant Hodgkin lymphoma (NLPHL) and its relationship to other lymphomas are largely unknown. This is partly because of the technical challenge of analyzing its rare neoplastic lymphocytic and histiocytic (L&H) cells, which are dispersed in an abundant nonneoplastic cellular microenvironment. We performed a genome-wide expression study of microdissected L&H lymphoma cells in comparison to normal and other malignant B cells that indicated a relationship of L&H cells to and/or that they originate from germinal center B cells at the transition to memory B cells. L&H cells show a surprisingly high similarity to the tumor cells of T cell–rich B cell lymphoma and classical Hodgkin lymphoma, a partial loss of their B cell phenotype, and deregulation of many apoptosis regulators and putative oncogenes. Importantly, L&H cells are characterized by constitutive nuclear factor κB activity and aberrant extracellular signal-regulated kinase signaling. Thus, these findings shed new light on the nature of L&H cells, reveal several novel pathogenetic mechanisms in NLPHL, and may help in differential diagnosis and lead to novel therapeutic strategies

Устройство автоматического регулирования жидкости

Although the significance of tumour site for estimating malignant potential in gastrointestinal stromal tumours (GISTs) has recently been recognized, site-specific genetic patterns have not to date been defined. This study examined 52 c-kit-positive primary GISTs (with a mean follow-up of 42.3 months in 51 cases) from three different locations (35 gastric, 12 small intestinal, and five colorectal) using comparative genomic hybridization (CGH). In general, tumour site correlated with key prognostic factors, including tumour size, mitotic rate, proliferative activity, and probable malignant potential. Furthermore, several DNA copy number changes showed a site-dependent pattern. These included losses at 14q (gastric 83%, intestinal 35%; p = 0.001), losses at 22q (gastric 46%, intestinal 82%; p = 0.02), losses at 1p (gastric 23%, intestinal 88%; p = 1 × 10-5), losses at 15q (gastric 14%, intestinal 59%; p = 0.002), losses at 9q (gastric 14%, intestinal 53%; p = 0.006), and gains at 5p (gastric 11%, intestinal 53%; p = 0.002). These data demonstrate strong site-dependent genetic heterogeneity in GISTs that may form a basis for subclassification. Prognostic evaluation of DNA copy number changes identified losses at 9q as a site-independent prognostic marker associated with shorter disease-free survival (p = 0.03) and overall survival (p = 0.002). Furthermore, 9q loss also appeared to carry prognostic value in predicting overall survival for patients with advanced or progressive GISTs (p = 0.003). Copyright © 2004 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd

Avelumab in patients with previously treated metastatic melanoma: phase 1b results from the JAVELIN Solid Tumor trial

Background We report phase 1b data from patients enrolled in the JAVELIN Solid Tumor clinical trial (NCT01772004) with unresectable stage IIIC or IV melanoma that had progressed after ≥1 line of therapy for metastatic disease. Patients and methods Patients received avelumab (10 mg/kg)—a human anti–PD-L1 antibody. Assessments included objective response rate (ORR), progression-free survival (PFS), overall survival (OS), and safety. Results As of December 31, 2016, 51 patients were treated and followed for a median of 24.2 months (range, 16.1–31.5). Most patients had cutaneous (n = 28 [54.9%]) or ocular (n = 16 [31.4%]) melanoma and had received a median of 2 prior lines of therapy (range, 0–4), including ipilimumab (n = 26 [51.0%]). The confirmed ORR was 21.6% (95% CI, 11.3–35.3; complete response, 7.8%; partial response, 13.7%). The median duration of response was not estimable (95% CI, 2.6 months-not estimable). Median PFS and OS were 3.1 months (95% CI, 1.4–6.3) and 17.2 months (95% CI, 6.6-not estimable), respectively. Subgroup analyses suggested meaningful clinical activity (ORR [95% CI]) in patients with non-ocular melanoma (31.4% [16.9–49.3]), PD-L1–positive tumors (42.1% [20.3–66.5]), or prior ipilimumab therapy (30.8% [14.3–51.8]). Thirty-nine patients (76.5%) had a treatment-related adverse event (TRAE), most commonly infusion-related reaction (29.4%), fatigue (17.6%), and chills (11.8%); 4 patients (7.8%) had a grade 3 TRAE. Five patients (9.8%) had an immune-related TRAE (all were grade 1/2). No grade 4 TRAEs or treatment-related deaths were reported. Conclusion Avelumab showed durable responses, promising survival outcomes, and an acceptable safety profile in patients with previously treated metastatic melanoma. Trial registration ClinicalTrials.gov identifier: NCT01772004This trial was sponsored by Merck KGaA, Darmstadt, Germany, and is part of an alliance between Merck KGaA and Pfizer, Inc., New York, NY, USA. Medical writing support was provided by ClinicalThinking, Inc., Hamilton, NJ, USA, and funded by Merck KGaA, and Pfizer, Inc

Avelumab, an anti-PD-L1 antibody, in patients with locally advanced or metastatic breast cancer: a phase 1b JAVELIN Solid Tumor study

PURPOSE: Agents targeting programmed death receptor 1 (PD-1) or its ligand (PD-L1) have shown antitumor activity in the treatment of metastatic breast cancer (MBC). The aim of this study was to assess the activity of avelumab, a PD-L1 inhibitor, in patients with MBC. METHODS: In a phase 1 trial (JAVELIN Solid Tumor; NCT01772004), patients with MBC refractory to or progressing after standard-of-care therapy received avelumab intravenously 10 mg/kg every 2 weeks. Tumors were assessed every 6 weeks by RECIST v1.1. Adverse events (AEs) were graded by NCI-CTCAE v4.0. Membrane PD-L1 expression was assessed by immunohistochemistry (Dako PD-L1 IHC 73-10 pharmDx). RESULTS: A total of 168 patients with MBC, including 58 patients with triple-negative breast cancer (TNBC), were treated with avelumab for 2-50 weeks and followed for 6-15 months. Patients were heavily pretreated with a median of three prior therapies for metastatic or locally advanced disease. Grade >/= 3 treatment-related AEs occurred in 13.7% of patients, including two treatment-related deaths. The confirmed objective response rate (ORR) was 3.0% overall (one complete response and four partial responses) and 5.2% in patients with TNBC. A trend toward a higher ORR was seen in patients with PD-L1+ versus PD-L1- tumor-associated immune cells in the overall population (16.7% vs. 1.6%) and in the TNBC subgroup (22.2% vs. 2.6%). CONCLUSION: Avelumab showed an acceptable safety profile and clinical activity in a subset of patients with MBC. PD-L1 expression in tumor-associated immune cells may be associated with a higher probability of clinical response to avelumab in MBC

Maximum

likelihood estimation of oncogenetic tree model

Class Discovery in Gene Expression Data: Characterizing Splits by support vector machines

ISIS is a class discovery method for microarray data described by Heydebreck et al. (2001). The objective is to discover biologically relevant structures in the gene expression profiles of different tissue samples in an unsupervised fashion. We present a variation of the original ISIS-algorithm based on Support Vector Machines (SVM). The method searches for binary partitions in the set of samples that show clear separation. Mathematically, each class distinction is characterized according to the size of margin achieved by a SVM separating the two classes. ISIS produces not only one partition (like most commonly used clustering algorithms) but several mutually independent ones. In three data sets from cancer gene expression studies the SVM margin approach succeeds in detecting relationships between the tissue samples, for example cancer subtypes. The known biological classes exhibit an exceptionally large value of the svm-margin. The significance of the margin as a measure of class distinction is indicated by comparison to random partitions of the samples