Finding genes that are differentially expressed between conditions is an integral part of understanding the molecular basis of phenotypic variation. In the past decades, DNA microarrays have been ...used extensively to quantify the abundance of mRNA corresponding to different genes, and more recently high-throughput sequencing of cDNA (RNA-seq) has emerged as a powerful competitor. As the cost of sequencing decreases, it is conceivable that the use of RNA-seq for differential expression analysis will increase rapidly. To exploit the possibilities and address the challenges posed by this relatively new type of data, a number of software packages have been developed especially for differential expression analysis of RNA-seq data.
We conducted an extensive comparison of eleven methods for differential expression analysis of RNA-seq data. All methods are freely available within the R framework and take as input a matrix of counts, i.e. the number of reads mapping to each genomic feature of interest in each of a number of samples. We evaluate the methods based on both simulated data and real RNA-seq data.
Very small sample sizes, which are still common in RNA-seq experiments, impose problems for all evaluated methods and any results obtained under such conditions should be interpreted with caution. For larger sample sizes, the methods combining a variance-stabilizing transformation with the 'limma' method for differential expression analysis perform well under many different conditions, as does the nonparametric SAMseq method.
The methylation status of the O6 -methylguanine-DNA methyltransferase ( MGMT ) gene is an important predictive biomarker for benefit from alkylating agent therapy in glioblastoma. Our model ...MGMT-STP27 allows prediction of the methylation status of the MGMT promoter using data from the Illumina's Human Methylation BeadChips (HM-27K and HM-450K) that is publically available for many cancer data sets. Here, we investigate the impact of the context of genetic and epigenetic alterations and tumor type on the classification and report on technical aspects, such as robustness of cutoff definition and preprocessing of the data. The association between gene copy number variation, predicted MGMT methylation, and MGMT expression revealed a gene dosage effect on MGMT expression in lower grade glioma (World Health Organization grade II/III) that in contrast to glioblastoma usually carry two copies of chromosome 10 on which MGMT resides (10q26.3). This implies some MGMT expression, potentially conferring residual repair function blunting the therapeutic effect of alkylating agents. A sensitivity analyses corroborated the performance of the original cutoff for various optimization criteria and for most data preprocessing methods. Finally, we propose an R package mgmtstp27 that allows prediction of the methylation status of the MGMT promoter and calculation of appropriate confidence and/or prediction intervals. Overall, MGMT-STP27 is a robust model for MGMT classification that is independent of tumor type and is adapted for single sample prediction.
With the large amount of biological data that is currently publicly available, many investigators combine multiple data sets to increase the sample size and potentially also the power of their ...analyses. However, technical differences ("batch effects") as well as differences in sample composition between the data sets may significantly affect the ability to draw generalizable conclusions from such studies.
The current study focuses on the construction of classifiers, and the use of cross-validation to estimate their performance. In particular, we investigate the impact of batch effects and differences in sample composition between batches on the accuracy of the classification performance estimate obtained via cross-validation. The focus on estimation bias is a main difference compared to previous studies, which have mostly focused on the predictive performance and how it relates to the presence of batch effects.
We work on simulated data sets. To have realistic intensity distributions, we use real gene expression data as the basis for our simulation. Random samples from this expression matrix are selected and assigned to group 1 (e.g., 'control') or group 2 (e.g., 'treated'). We introduce batch effects and select some features to be differentially expressed between the two groups. We consider several scenarios for our study, most importantly different levels of confounding between groups and batch effects.
We focus on well-known classifiers: logistic regression, Support Vector Machines (SVM), k-nearest neighbors (kNN) and Random Forests (RF). Feature selection is performed with the Wilcoxon test or the lasso. Parameter tuning and feature selection, as well as the estimation of the prediction performance of each classifier, is performed within a nested cross-validation scheme. The estimated classification performance is then compared to what is obtained when applying the classifier to independent data.
Recently, several prognostic gene expression signatures have been identified; however, their performance has never been evaluated according to the previously described molecular subtypes based on the ...estrogen receptor (ER) and human epidermal growth factor receptor 2 (HER2), and their biological meaning has remained unclear. Here we aimed to perform a comprehensive meta-analysis integrating both clinicopathologic and gene expression data, focusing on the main molecular subtypes.
We developed gene expression modules related to key biological processes in breast cancer such as tumor invasion, immune response, angiogenesis, apoptosis, proliferation, and ER and HER2 signaling, and then analyzed these modules together with clinical variables and several prognostic signatures on publicly available microarray studies (>2,100 patients).
Multivariate analysis showed that in the ER+/HER2- subgroup, only the proliferation module and the histologic grade were significantly associated with clinical outcome. In the ER-/HER2- subgroup, only the immune response module was associated with prognosis, whereas in the HER2+ tumors, the tumor invasion and immune response modules displayed significant association with survival. Proliferation was identified as the most important component of several prognostic signatures, and their performance was limited to the ER+/HER2- subgroup.
Although proliferation is the strongest parameter predicting clinical outcome in the ER+/HER2- subtype and the common denominator of most prognostic gene signatures, immune response and tumor invasion seem to be the main molecular processes associated with prognosis in the ER-/HER2- and HER2+ subgroups, respectively. These findings may help to define new clinicogenomic models and to identify new therapeutic strategies in the specific molecular subgroups.
High T‐cell infiltration in colorectal cancer (CRC) correlates with a favorable disease outcome and immunotherapy response. This, however, is only observed in a small subset of CRC patients. A better ...understanding of the factors influencing tumor T‐cell responses in CRC could inspire novel therapeutic approaches to achieve broader immunotherapy responsiveness. Here, we investigated T cell‐suppressive properties of different myeloid cell types in an inducible colon tumor mouse model. The most potent inhibitors of T‐cell activity were tumor‐infiltrating neutrophils. Gene expression analysis and combined in vitro and in vivo tests indicated that T‐cell suppression is mediated by neutrophil‐secreted metalloproteinase activation of latent TGFβ. CRC patient neutrophils similarly suppressed T cells via TGFβ in vitro, and public gene expression datasets suggested that T‐cell activity is lowest in CRCs with combined neutrophil infiltration and TGFβ activation. Thus, the interaction of neutrophils with a TGFβ‐rich tumor microenvironment may represent a conserved immunosuppressive mechanism in CRC.
Synopsis
Neutrophil infiltration is a conserved characteristic in human and mouse colon tumors, and is initiated during the formation of early adenomas. Neutrophils contribute to an immune‐suppressive tumor microenvironment through the secretion of MMPs, which activate latent TGFβ stored in the tumor stroma.
Inflammatory T cells counteracted mouse colon adenoma formation at the earliest stage, but were excluded during disease progression.
In contrast, neutrophils infiltrated early‐stage as well as established mouse colon adenomas, where they suppressed inflammatory T cells through matrix metalloproteinase‐mediated activation of latent TGFβ stored in the tumor microenvironment.
In mice, targeting neutrophils or neutrophil‐mediated TGFβ activation counteracted colon adenoma formation and promoted tumor T cell activity.
Similar to mouse tumors, human colon carcinomas were frequently infiltrated with neutrophils.
Human colon carcinomas with high neutrophil infiltration and TGFβ activation had the lowest T cell infiltration.
Neutrophil infiltration is a conserved characteristic in human and mouse colon tumors, and is initiated during the formation of early adenomas. Neutrophils contribute to an immune‐suppressive tumor microenvironment through the secretion of MMPs, which activate latent TGFβ stored in the tumor stroma.
Summary Background Following the discovery that mutant KRAS is associated with resistance to anti-epidermal growth factor receptor (EGFR) antibodies, the tumours of patients with metastatic ...colorectal cancer are now profiled for seven KRAS mutations before receiving cetuximab or panitumumab. However, most patients with KRAS wild-type tumours still do not respond. We studied the effect of other downstream mutations on the efficacy of cetuximab in, to our knowledge, the largest cohort to date of patients with chemotherapy-refractory metastatic colorectal cancer treated with cetuximab plus chemotherapy in the pre- KRAS selection era. Methods 1022 tumour DNA samples (73 from fresh-frozen and 949 from formalin-fixed, paraffin-embedded tissue) from patients treated with cetuximab between 2001 and 2008 were gathered from 11 centres in seven European countries. 773 primary tumour samples had sufficient quality DNA and were included in mutation frequency analyses; mass spectrometry genotyping of tumour samples for KRAS, BRAF, NRAS , and PIK3CA was done centrally. We analysed objective response, progression-free survival (PFS), and overall survival in molecularly defined subgroups of the 649 chemotherapy-refractory patients treated with cetuximab plus chemotherapy. Findings 40·0% (299/747) of the tumours harboured a KRAS mutation, 14·5% (108/743) harboured a PIK3CA mutation (of which 68·5% 74/108 were located in exon 9 and 20·4% 22/108 in exon 20), 4·7% (36/761) harboured a BRAF mutation, and 2·6% (17/644) harboured an NRAS mutation. KRAS mutants did not derive benefit compared with wild types, with a response rate of 6·7% (17/253) versus 35·8% (126/352; odds ratio OR 0·13, 95% CI 0·07–0·22; p<0·0001), a median PFS of 12 weeks versus 24 weeks (hazard ratio HR 1·98, 1·66–2·36; p<0·0001), and a median overall survival of 32 weeks versus 50 weeks (1·75, 1·47–2·09; p<0·0001). In KRAS wild types, carriers of BRAF and NRAS mutations had a significantly lower response rate than did BRAF and NRAS wild types, with a response rate of 8·3% (2/24) in carriers of BRAF mutations versus 38·0% in BRAF wild types (124/326; OR 0·15, 95% CI 0·02–0·51; p=0·0012); and 7·7% (1/13) in carriers of NRAS mutations versus 38·1% in NRAS wild types (110/289; OR 0·14, 0·007–0·70; p=0·013). PIK3CA exon 9 mutations had no effect, whereas exon 20 mutations were associated with a worse outcome compared with wild types, with a response rate of 0·0% (0/9) versus 36·8% (121/329; OR 0·00, 0·00–0·89; p=0·029), a median PFS of 11·5 weeks versus 24 weeks (HR 2·52, 1·33–4·78; p=0·013), and a median overall survival of 34 weeks versus 51 weeks (3·29, 1·60–6·74; p=0·0057). Multivariate analysis and conditional inference trees confirmed that, if KRAS is not mutated, assessing BRAF, NRAS , and PIK3CA exon 20 mutations (in that order) gives additional information about outcome. Objective response rates in our series were 24·4% in the unselected population, 36·3% in the KRAS wild-type selected population, and 41·2% in the KRAS, BRAF, NRAS , and PIK3CA exon 20 wild-type population. Interpretation While confirming the negative effect of KRAS mutations on outcome after cetuximab, we show that BRAF, NRAS , and PIK3CA exon 20 mutations are significantly associated with a low response rate. Objective response rates could be improved by additional genotyping of BRAF, NRAS , and PIK3CA exon 20 mutations in a KRAS wild-type population. Funding Belgian Federation against Cancer (Stichting tegen Kanker).
Pericytes regulate the development of organ-specific characteristics of the brain vasculature such as the blood-brain barrier (BBB) and astrocytic end-feet. Whether pericytes are involved in the ...control of leukocyte trafficking in the adult central nervous system (CNS), a process tightly regulated by CNS vasculature, remains elusive. Using adult pericyte-deficient mice (
), we show that pericytes limit leukocyte infiltration into the CNS during homeostasis and autoimmune neuroinflammation. The permissiveness of the vasculature toward leukocyte trafficking in
mice inversely correlates with vessel pericyte coverage. Upon induction of experimental autoimmune encephalomyelitis (EAE), pericyte-deficient mice die of severe atypical EAE, which can be reversed with fingolimod, indicating that the mortality is due to the massive influx of immune cells into the brain. Additionally, administration of anti-VCAM-1 and anti-ICAM-1 antibodies reduces leukocyte infiltration and diminishes the severity of atypical EAE symptoms of
mice, indicating that the proinflammatory endothelium due to absence of pericytes facilitates exaggerated neuroinflammation. Furthermore, we show that the presence of myelin peptide-specific peripheral T cells in
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mice leads to the development of spontaneous neurological symptoms paralleled by the massive influx of leukocytes into the brain. These findings indicate that intrinsic changes within brain vasculature can promote the development of a neuroinflammatory disorder.
Metabolic alterations, related to cerebral glucose metabolism, brain insulin resistance, and age-induced mitochondrial dysfunction, play an important role in Alzheimer's disease (AD) on both the ...systemic and central nervous system level. To study the extent and significance of these alterations in AD, quantitative metabolomics was applied to plasma and cerebrospinal fluid (CSF) from clinically well-characterized AD patients and cognitively healthy control subjects. The observed metabolic alterations were associated with core pathological processes of AD to investigate their relation with amyloid pathology and tau-related neurodegeneration.
In a case-control study of clinical and biomarker-confirmed AD patients (n = 40) and cognitively healthy controls without cerebral AD pathology (n = 34) with paired plasma and CSF samples, we performed metabolic profiling, i.e., untargeted metabolomics and targeted quantification. Targeted quantification focused on identified deregulated pathways highlighted in the untargeted assay, i.e. the TCA cycle, and its anaplerotic pathways, as well as the neuroactive tryptophan and kynurenine pathway.
Concentrations of several TCA cycle and beta-oxidation intermediates were higher in plasma of AD patients, whilst amino acid concentrations were significantly lower. Similar alterations in these energy metabolism intermediates were observed in CSF, together with higher concentrations of creatinine, which were strongly correlated with blood-brain barrier permeability. Alterations of several amino acids were associated with CSF Amyloidβ1-42. The tryptophan catabolites, kynurenic acid and quinolinic acid, showed significantly higher concentrations in CSF of AD patients, which, together with other tryptophan pathway intermediates, were correlated with either CSF Amyloidβ1-42, or tau and phosphorylated Tau-181.
This study revealed AD-associated systemic dysregulation of nutrient sensing and oxidation and CNS-specific alterations in the neuroactive tryptophan pathway and (phospho)creatine degradation. The specific association of amino acids and tryptophan catabolites with AD CSF biomarkers suggests a close relationship with core AD pathology. Our findings warrant validation in independent, larger cohort studies as well as further investigation of factors such as gender and APOE genotype, as well as of other groups, such as preclinical AD, to identify metabolic alterations as potential intervention targets.
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