Treatment results and prognostic factors in primary thyroid lymphoma patients: a rare cancer network study.

Background: This study analyzed prognostic factors and treatment outcomes of primary thyroid lymphoma. Patients and Methods: Data were retrospectively collected for 87 patients (53 stage I and 34 stage II) with median age 65 years. Fifty-two patients were treated with single modality (31 with chemotherapy alone and 21 with radiotherapy alone) and 35 with combined modality treatment. Median follow-up was 51 months. Results: Sixty patients had aggressive lymphoma and 27 had indolent lymphoma. The 5- and 10-year overall survival (OS) rates were 74% and 71%, respectively, and the disease-free survival (DFS) rates were 68% and 64%. Univariate analysis revealed that age, tumor size, stage, lymph node involvement, B symptoms, and treatment modality were prognostic factors for OS, DFS, and local control (LC). Patients with thyroiditis had significantly better LC rates. In multivariate analysis, OS was influenced by age, B symptoms, lymph node involvement, and tumor size, whereas DFS and LC were influenced by B symptoms and tumor size. Compared with single modality treatment, patients treated with combined modality had better 5-year OS, DFS, and LC. Conclusions: Combined modality leads to an excellent prognosis for patients with aggressive lymphoma but does not improve OS and LC in patients with indolent lymphoma.

Early Stage Primary Bone Lymphoma: A Retrospective, Multicenter Rare Cancer Network Study

PURPOSE/OBJECTIVE(S): Primary bone lymphoma (PBL) represents less than 1% of all malignant lymphomas, and 4-5% of all extranodal lymphomas. In this study, we assessed the disease profile, outcome, and prognostic factors in patients with stage I and II PBL. MATERIALS/METHODS: Between 1987 and 2008, 116 consecutive patients with PBL treated in 13 RCNinstitutions were included in this study. Inclusion criteriawere: age.17 yrs, PBLin stage I and II, andminimum6months follow-up. The median agewas 51 yrs (range: 17-93).Diagnosticwork-up included plain boneXray (74%of patients), scintigraphy (62%), CT-scan (65%),MRI (58%), PET (18%), and bone-marrow biopsy (84%).All patients had biopsy-proven confirmation of non-Hodgkin's lymphoma (NHL). The histopathological type was predominantly diffuse large B-cell lymphoma (78%) and follicular lymphoma (6%), according to theWHOclassification. One hundred patients had a high-grade, 7 intermediate and 9 low-gradeNHL. Ninety-three patients had anAnn-Arbor stage I, and 23 had a stage II. Seventy-seven patients underwent chemoradiotherapy (CXRT), 12 radiotherapy (RT) alone, 10 chemotherapy alone (CXT), 9 surgery followed by CXRT, 5 surgery followed by CXT, and 2 surgery followed by RT. One patient died before treatment.Median RT dosewas 40Gy (range: 4-60).Themedian number ofCXTcycleswas 6 (range, : 2-8).Median follow-upwas 41months (range: 6-242). RESULTS: Following treatment, the overall response rate was 91% (CR 74%, PR 17%). Local recurrence was observed in 12 (10%) patients, and systemic recurrence in 17 (15%) patients. Causes of death included disease progression in 16, unrelated disease in 6, CXT-related toxicity in 1, and secondary cancer in 2 patients. The 5-yr overall survival (OS), disease-free survival (DFS), lymphoma- specific survival (LSS), and local control (LC) were 76%, 69%, 78%, and 92%, respectively. In univariate analyses (log-rank test), favorable prognostic factors for survival were: age\50 years (p = 0.008), IPI score #1 (p = 0.009), complete response (p\0.001), CXT (p = 0.008), number of CXT cycles $6 (p = 0.007), and RT dose . 40 Gy (p = 0.005). In multivariate analysis age, RT dose, complete response, and absence of B symptoms were independent factors influencing the outcome. There were 3 patients developing grade 3 or more (CTCAE.V3.0) toxicities. CONCLUSIONS: This large multicenter study, confirms the relatively good prognosis of early stage PBL, treated with combined CXRT. Local control was excellent, and systemic failure occurred infrequently. A sufficient dose of RT (. 40 Gy) and complete CXT regime (. 6 cycles) were associated with a better outcome. Combined modality appears to be the treatment of choice.

Brain Connectivity Analysis in Children. Effects of Prematurity. and Prenatal Growth Restriction

Introduction: Survival of children born prematurely or with very low birth weight has increased dramatically, but the long term developmental outcome remains unknown. Many children have deficits in cognitive capacities, in particular involving executive domains and those disabilities are likely to involve a central nervous system deficit. To understand their neurostructural origin, we use DTI. Structurally segregated and functionally regions of the cerebral cortex are interconnected by a dense network of axonal pathways. We noninvasively map these pathways across cortical hemispheres and construct normalized structural connection matrices derived from DTI MR tractography. Group comparisons of brain connectivity reveal significant changes in fiber density in case of children with poor intrauterine grown and extremely premature children (gestational age<28 weeks at birth) compared to control subjects. This changes suggest a link between cortico-axonal pathways and the central nervous system deficit. Methods: Sixty premature born infants (5-6 years old) were scanned on clinical 3T scanner (Magnetom Trio, Siemens Medical Solutions, Erlangen, Germany) at two hospitals (HUG, Geneva and CHUV, Lausanne). For each subject, T1-weighted MPRAGE images (TR/TE=2500/2.91,TI=1100, resolution=1x1x1mm, matrix=256x154) and DTI images (30 directions, TR/TE=10200/107, in-plane resolution=1.8x1.8x2mm, 64 axial, matrix=112x112) were acquired. Parent(s) provided written consent on prior ethical board approval. The extraction of the Whole Brain Structural Connectivity Matrix was performed following (Cammoun, 2009 and Hagmann, 2008). The MPARGE images were registered using an affine registration to the non-weighted-DTI and WM-GM segmentation performed on it. In order to have equal anatomical localization among subjects, 66 cortical regions with anatomical landmarks were created using the curvature information, i.e. sulcus and gyrus (Cammoun et al, 2007; Fischl et al, 2004; Desikan et al, 2006) with freesurfer software (http://surfer.nmr.mgh.harvard.edu/). Tractography was performed in WM using an algorithm especially designed for DTI/DSI data (Hagmann et al., 2007) and both information were then combined in a matrix. Each row and column of the matrix corresponds to a particular ROI. Each cell of index (i,j) represents the fiber density of the bundle connecting the ROIs i and j. Subdividing each cortical region, we obtained 4 Connectivity Matrices of different resolution (33, 66, 125 and 250 ROI/hemisphere) for each subject . Subjects were sorted in 3 different groups, namely (1) control, (2) Intrauterine Growth Restriction (IUGR), (3) Extreme Prematurity (EP), depending on their gestational age, weight and percentile-weight score at birth. Group-to-group comparisons were performed between groups (1)-(2) and (1)-(3). The mean age at examination of the three groups were similar. Results: Quantitative analysis were performed between groups to determine fibers density differences. For each group, a mean connectivity matrix with 33ROI/hemisphere resolution was computed. On the other hand, for all matrix resolutions (33,66,125,250 ROI/hemisphere), the number of bundles were computed and averaged. As seen in figure 1, EP and IUGR subjects present an overall reduction of fibers density in both interhemispherical and intrahemispherical connections. This is given quantitatively in table 1. IUGR subjects presents a higher percentage of missing fiber bundles than EP when compared to control subjects (~16% against 11%). When comparing both groups to control subjects, for the EP subjects, the occipito-parietal regions seem less interhemispherically connected whilst the intrahemispherical networks present lack of fiber density in the lymbic system. Children born with IUGR, have similar reductions in interhemispherical connections than the EP. However, the cuneus and precuneus connections with the precentral and paracentral lobe are even lower than in the case of the EP. For the intrahemispherical connections the IUGR group preset a loss of fiber density between the deep gray matter structures (striatum) and the frontal and middlefrontal poles, connections typically involved in the control of executive functions. For the qualitative analysis, a t-test comparing number of bundles (p-value<0.05) gave some preliminary significant results (figure 2). Again, even if both IUGR and EP appear to have significantly less connections comparing to the control subjects, the IUGR cohort seems to present a higher lack of fiber density specially relying the cuneus, precuneus and parietal areas. In terms of fiber density, preliminary Wilcoxon tests seem to validate the hypothesis set by the previous analysis. Conclusions: The goal of this study was to determine the effect of extreme prematurity and poor intrauterine growth on neurostructural development at the age of 6 years-old. This data indicates that differences in connectivity may well be the basis for the neurostructural and neuropsychological deficit described in these populations in the absence of overt brain lesions (Inder TE, 2005; Borradori-Tolsa, 2004; Dubois, 2008). Indeed, we suggest that IUGR and prematurity leads to alteration of connectivity between brain structures, especially in occipito-parietal and frontal lobes for EP and frontal and middletemporal poles for IUGR. Overall, IUGR children have a higher loss of connectivity in the overall connectivity matrix than EP children. In both cases, the localized alteration of connectivity suggests a direct link between cortico-axonal pathways and the central nervous system deficit. Our next step is to link these connectivity alterations to the performance in executive function tests.

Monitoring network optimisation for spatial data classification using support vector machines

The paper presents a novel method for monitoring network optimisation, based on a recent machine learning technique known as support vector machine. It is problem-oriented in the sense that it directly answers the question of whether the advised spatial location is important for the classification model. The method can be used to increase the accuracy of classification models by taking a small number of additional measurements. Traditionally, network optimisation is performed by means of the analysis of the kriging variances. The comparison of the method with the traditional approach is presented on a real case study with climate data.

Multiple Kernel Learning of Environmental Data. Case study: Analysis and Mapping of Wind Fields

The paper presents the Multiple Kernel Learning (MKL) approach as a modelling and data exploratory tool and applies it to the problem of wind speed mapping. Support Vector Regression (SVR) is used to predict spatial variations of the mean wind speed from terrain features (slopes, terrain curvature, directional derivatives) generated at different spatial scales. Multiple Kernel Learning is applied to learn kernels for individual features and thematic feature subsets, both in the context of feature selection and optimal parameters determination. An empirical study on real-life data confirms the usefulness of MKL as a tool that enhances the interpretability of data-driven models.

An interaction network of the mammalian COP9 signalosome identifies Dda1 as a core subunit of multiple Cul4-based E3 ligases.

The COP9 signalosome (CSN) is an evolutionarily conserved macromolecular complex that interacts with cullin-RING E3 ligases (CRLs) and regulates their activity by hydrolyzing cullin-Nedd8 conjugates. The CSN sequesters inactive CRL4(Ddb2), which rapidly dissociates from the CSN upon DNA damage. Here we systematically define the protein interaction network of the mammalian CSN through mass spectrometric interrogation of the CSN subunits Csn1, Csn3, Csn4, Csn5, Csn6 and Csn7a. Notably, we identified a subset of CRL complexes that stably interact with the CSN and thus might similarly be activated by dissociation from the CSN in response to specific cues. In addition, we detected several new proteins in the CRL-CSN interactome, including Dda1, which we characterized as a chromatin-associated core subunit of multiple CRL4 proteins. Cells depleted of Dda1 spontaneously accumulated double-stranded DNA breaks in a similar way to Cul4A-, Cul4B- or Wdr23-depleted cells, indicating that Dda1 interacts physically and functionally with CRL4 complexes. This analysis identifies new components of the CRL family of E3 ligases and elaborates new connections between the CRL and CSN complexes.

Individual prediction of cognitive decline in mild cognitive impairment using support vector machine-based analysis of diffusion tensor imaging data.

Although cross-sectional diffusion tensor imaging (DTI) studies revealed significant white matter changes in mild cognitive impairment (MCI), the utility of this technique in predicting further cognitive decline is debated. Thirty-five healthy controls (HC) and 67 MCI subjects with DTI baseline data were neuropsychologically assessed at one year. Among them, there were 40 stable (sMCI; 9 single domain amnestic, 7 single domain frontal, 24 multiple domain) and 27 were progressive (pMCI; 7 single domain amnestic, 4 single domain frontal, 16 multiple domain). Fractional anisotropy (FA) and longitudinal, radial, and mean diffusivity were measured using Tract-Based Spatial Statistics. Statistics included group comparisons and individual classification of MCI cases using support vector machines (SVM). FA was significantly higher in HC compared to MCI in a distributed network including the ventral part of the corpus callosum, right temporal and frontal pathways. There were no significant group-level differences between sMCI versus pMCI or between MCI subtypes after correction for multiple comparisons. However, SVM analysis allowed for an individual classification with accuracies up to 91.4% (HC versus MCI) and 98.4% (sMCI versus pMCI). When considering the MCI subgroups separately, the minimum SVM classification accuracy for stable versus progressive cognitive decline was 97.5% in the multiple domain MCI group. SVM analysis of DTI data provided highly accurate individual classification of stable versus progressive MCI regardless of MCI subtype, indicating that this method may become an easily applicable tool for early individual detection of MCI subjects evolving to dementia.

Firm's network capability and innovation performance: evidences from China hi-tech industry

ABSTRACT : A firm's competitive advantage can arise from internal resources as well as from an interfirm network. -This dissertation investigates the competitive advantage of a firm involved in an innovation network by integrating strategic management theory and social network theory. It develops theory and provides empirical evidence that illustrates how a networked firm enables the network value and appropriates this value in an optimal way according to its strategic purpose. The four inter-related essays in this dissertation provide a framework that sheds light on the extraction of value from an innovation network by managing and designing the network in a proactive manner. The first essay reviews research in social network theory and knowledge transfer management, and identifies the crucial factors of innovation network configuration for a firm's learning performance or innovation output. The findings suggest that network structure, network relationship, and network position all impact on a firm's performance. Although the previous literature indicates that there are disagreements about the impact of dense or spare structure, as well as strong or weak ties, case evidence from Chinese software companies reveals that dense and strong connections with partners are positively associated with firms' performance. The second essay is a theoretical essay that illustrates the limitations of social network theory for explaining the source of network value and offers a new theoretical model that applies resource-based view to network environments. It suggests that network configurations, such as network structure, network relationship and network position, can be considered important network resources. In addition, this essay introduces the concept of network capability, and suggests that four types of network capabilities play an important role in unlocking the potential value of network resources and determining the distribution of network rents between partners. This essay also highlights the contingent effects of network capability on a firm's innovation output, and explains how the different impacts of network capability depend on a firm's strategic choices. This new theoretical model has been pre-tested with a case study of China software industry, which enhances the internal validity of this theory. The third essay addresses the questions of what impact network capability has on firm innovation performance and what are the antecedent factors of network capability. This essay employs a structural equation modelling methodology that uses a sample of 211 Chinese Hi-tech firms. It develops a measurement of network capability and reveals that networked firms deal with cooperation between, and coordination with partners on different levels according to their levels of network capability. The empirical results also suggests that IT maturity, the openness of culture, management system involved, and experience with network activities are antecedents of network capabilities. Furthermore, the two-group analysis of the role of international partner(s) shows that when there is a culture and norm gap between foreign partners, a firm must mobilize more resources and effort to improve its performance with respect to its innovation network. The fourth essay addresses the way in which network capabilities influence firm innovation performance. By using hierarchical multiple regression with data from Chinese Hi-tech firms, the findings suggest that there is a significant partial mediating effect of knowledge transfer on the relationships between network capabilities and innovation performance. The findings also reveal that the impacts of network capabilities divert with the environment and strategic decision the firm has made: exploration or exploitation. Network constructing capability provides a greater positive impact on and yields more contributions to innovation performance than does network operating capability in an exploration network. Network operating capability is more important than network constructing capability for innovative firms in an exploitation network. Therefore, these findings highlight that the firm can shape the innovation network proactively for better benefits, but when it does so, it should adjust its focus and change its efforts in accordance with its innovation purposes or strategic orientation.

Management of adenoid cystic carcinoma of the breast: a Rare Cancer Network study.

BACKGROUND: Mammary adenoid cystic carcinoma (ACC) is a rare breast cancer. The aim of this retrospective study was to assess prognostic factors and patterns of failure, as well as the role of radiation therapy (RT), in ACC.¦METHODS: Between January 1980 and December 2007, 61 women with breast ACC were treated at participating centers of the Rare Cancer Network. Surgery consisted of lumpectomy in 41 patients and mastectomy in 20 patients. There were 51(84%) stage pN0 and 10 stage cN0 (16%) patients. Postoperative RT was administered to 40 patients (35 after lumpectomy, 5 after mastectomy).¦RESULTS: With a median follow-up of 79 months (range, 6-285), 5-year overall and disease-free survival rates were 94% (95% confidence interval [CI], 88%-100%) and 82% (95% CI, 71%-93%), respectively. The 5-year locoregional control (LRC) rate was 95% (95% CI, 89%-100%). Axillary lymph node dissection or sentinel node biopsy was performed in 84% of cases. All patients had stage pN0 disease. In univariate analysis, survival was not influenced by the type of surgery or the use of postoperative RT. The 5-year LRC rate was 100% in the mastectomy group versus 93% (95% CI, 83%-100%) in the breast-conserving surgery group, respectively (p = 0.16). For the breast-conserving surgery group, the use of RT significantly correlated with LRC (p = 0.03); the 5-year LRC rates were 95% (95% CI, 86%-100%) for the RT group versus 83% (95% CI, 54%-100%) for the group receiving no RT. No local failures occurred in patients with positive margins, all of whom received postoperative RT.¦CONCLUSION: Breast-conserving surgery is the treatment of choice for patients with ACC breast cancer. Axillary lymph node dissection or sentinel node biopsy might not be recommended. Postoperative RT should be proposed in the case of breast-conserving surgery.

Optimization of HS-SPME/GC-MS analysis and its use in the profiling of illicit ecstasy tablets (Part 1)

A headspace solid-phase microextraction procedure (HS-SPME) was developed for the profiling of traces present in 3,4-methylenedioxymethylampethamine (MDMA). Traces were first extracted using HS-SPME and then analyzed by gas chromatography-mass spectroscopy (GC-MS). The HS-SPME conditions were optimized using varying conditions. Optimal results were obtained when 40 mg of crushed MDMA sample was heated at 80 °C for 15 min, followed by extraction at 80 °C for 15 min with a polydimethylsiloxane/divinylbenzene coated fibre. A total of 31 compounds were identified as traces related to MDMA synthesis, namely precursors, intermediates or by-products. In addition some fatty acids used as tabletting materials and caffeine used as adulterant, were also detected. The use of a restricted set of 10 target compounds was also proposed for developing a screening tool for clustering samples having close profile. 114 seizures were analyzed using an SPME auto-sampler (MultiPurpose Samples MPS2), purchased from Gerstel GMBH & Co. (Germany), and coupled to GC-MS. The data was handled using various pre-treatment methods, followed by the study of similarities between sample pairs based on the Pearson correlation. The results show that HS-SPME, coupled with the suitable statistical method is a powerful tool for distinguishing specimens coming from the same seizure and specimens coming from different seizures. This information can be used by law enforcement personnel to visualize the ecstasy distribution network as well as the clandestine tablet manufacturing.

A system-level, molecular evolutionary analysis of mammalian phototransduction

Visual perception is initiated in the photoreceptor cells of the retina via the phototransduction system.This system has shown marked evolution during mammalian divergence in such complex attributes as activation time and recovery time. We have performed a molecular evolutionary analysis of proteins involved in mammalianphototransduction in order to unravel how the action of natural selection has been distributed throughout thesystem to evolve such traits. We found selective pressures to be non-randomly distributed according to both a simple protein classification scheme and a protein-interaction network representation of the signaling pathway. Proteins which are topologically central in the signaling pathway, such as the G proteins, as well as retinoid cycle chaperones and proteins involved in photoreceptor cell-type determination, were found to be more constrained in their evolution. Proteins peripheral to the pathway, such as ion channels and exchangers, as well as the retinoid cycle enzymes, have experienced a relaxation of selective pressures. Furthermore, signals of positive selection were detected in two genes: the short-wave (blue) opsin (OPN1SW) in hominids and the rod-specific Na+/Ca2+,K+ ion exchanger (SLC24A1) in rodents. The functions of the proteins involved in phototransduction and the topology of the interactions between them have imposed non-random constraints on their evolution. Thus, in shaping or conserving system-level phototransduction traits, natural selection has targeted the underlying proteins in a concerted manner.

Meta-analysis identifies multiple loci associated with kidney function-related traits in east Asian populations.

Chronic kidney disease (CKD), impairment of kidney function, is a serious public health problem, and the assessment of genetic factors influencing kidney function has substantial clinical relevance. Here, we report a meta-analysis of genome-wide association studies for kidney function-related traits, including 71,149 east Asian individuals from 18 studies in 11 population-, hospital- or family-based cohorts, conducted as part of the Asian Genetic Epidemiology Network (AGEN). Our meta-analysis identified 17 loci newly associated with kidney function-related traits, including the concentrations of blood urea nitrogen, uric acid and serum creatinine and estimated glomerular filtration rate based on serum creatinine levels (eGFRcrea) (P < 5.0 × 10(-8)). We further examined these loci with in silico replication in individuals of European ancestry from the KidneyGen, CKDGen and GUGC consortia, including a combined total of ∼110,347 individuals. We identify pleiotropic associations among these loci with kidney function-related traits and risk of CKD. These findings provide new insights into the genetics of kidney function.

On the tractability of the piecewise-linear approximation for general discrete-choice network revenue management

The choice network revenue management (RM) model incorporates customer purchase behavioras customers purchasing products with certain probabilities that are a function of the offeredassortment of products, and is the appropriate model for airline and hotel network revenuemanagement, dynamic sales of bundles, and dynamic assortment optimization. The underlyingstochastic dynamic program is intractable and even its certainty-equivalence approximation, inthe form of a linear program called Choice Deterministic Linear Program (CDLP) is difficultto solve in most cases. The separation problem for CDLP is NP-complete for MNL with justtwo segments when their consideration sets overlap; the affine approximation of the dynamicprogram is NP-complete for even a single-segment MNL. This is in contrast to the independentclass(perfect-segmentation) case where even the piecewise-linear approximation has been shownto be tractable. In this paper we investigate the piecewise-linear approximation for network RMunder a general discrete-choice model of demand. We show that the gap between the CDLP andthe piecewise-linear bounds is within a factor of at most 2. We then show that the piecewiselinearapproximation is polynomially-time solvable for a fixed consideration set size, bringing itinto the realm of tractability for small consideration sets; small consideration sets are a reasonablemodeling tradeoff in many practical applications. Our solution relies on showing that forany discrete-choice model the separation problem for the linear program of the piecewise-linearapproximation can be solved exactly by a Lagrangian relaxation. We give modeling extensionsand show by numerical experiments the improvements from using piecewise-linear approximationfunctions.

Early-Stage Primary Bone Lymphoma: A Retrospective, Multicenter Rare Cancer Network (RCN) Study.

PURPOSE: Primary bone lymphoma (PBL) represents less than 1% of all malignant lymphomas. In this study, we assessed the disease profile, outcome, and prognostic factors in patients with Stages I and II PBL.¦PATIENTS AND METHODS: Thirteen Rare Cancer Network (RCN) institutions enrolled 116 consecutive patients with PBL treated between 1987 and 2008 in this study. Eighty-seven patients underwent chemoradiotherapy (CXRT) without (78) or with (9) surgery, 15 radiotherapy (RT) without (13) or with (2) surgery, and 14 chemotherapy (CXT) without (9) or with (5) surgery. Median RT dose was 40 Gy (range, 4-60). The median number of CXT cycles was six (range, 2-8). Median follow-up was 41 months (range, 6-242).¦RESULTS: The overall response rate at the end of treatment was 91% (complete response [CR] 74%, partial response [PR] 17%). Local recurrence or progression was observed in 12 (10%) patients and systemic recurrence in 17 (15%). The 5-year overall survival (OS), lymphoma-specific survival (LSS), and local control (LC) were 76%, 78%, and 92%, respectively. In univariate analyses (log-rank test), favorable prognostic factors for OS and LSS were International Prognostic Index (IPI) score ≤1 (p = 0.009), high-grade histology (p = 0.04), CXRT (p = 0.05), CXT (p = 0.0004), CR (p < 0.0001), and RT dose >40 Gy (p = 0.005). For LC, only CR and Stage I were favorable factors. In multivariate analysis, IPI score, RT dose, CR, and CXT were independently influencing the outcome (OS and LSS). CR was the only predicting factor for LC.¦CONCLUSION: This large multicenter retrospective study confirms the good prognosis of early-stage PBL treated with combined CXRT. An adequate dose of RT and complete CXT regime were associated with better outcome.

Gene Promoter Evolution Targets the Center of the Human Protein Interaction Network

Assessing the contribution of promoters and coding sequences to gene evolution is an important step toward discovering the major genetic determinants of human evolution. Many specific examples have revealed the evolutionary importance of cis-regulatory regions. However, the relative contribution of regulatory and coding regions to the evolutionary process and whether systemic factors differentially influence their evolution remains unclear. To address these questions, we carried out an analysis at the genome scale to identify signatures of positive selection in human proximal promoters. Next, we examined whether genes with positively selected promoters (Prom+ genes) show systemic differences with respect to a set of genes with positively selected protein-coding regions (Cod+ genes). We found that the number of genes in each set was not significantly different (8.1% and 8.5%, respectively). Furthermore, a functional analysis showed that, in both cases, positive selection affects almost all biological processes and only a few genes of each group are located in enriched categories, indicating that promoters and coding regions are not evolutionarily specialized with respect to gene function. On the other hand, we show that the topology of the human protein network has a different influence on the molecular evolution of proximal promoters and coding regions. Notably, Prom+ genes have an unexpectedly high centrality when compared with a reference distribution (P = 0.008, for Eigenvalue centrality). Moreover, the frequency of Prom+ genes increases from the periphery to the center of the protein network (P = 0.02, for the logistic regression coefficient). This means that gene centrality does not constrain the evolution of proximal promoters, unlike the case with coding regions, and further indicates that the evolution of proximal promoters is more efficient in the center of the protein network than in the periphery. These results show that proximal promoters have had a systemic contribution to human evolution by increasing the participation of central genes in the evolutionary process.