Establishment and Comprehensive Characterization of a Novel Preclinical Platform of Metastatic Retinoblastoma for Therapeutic Developments.

Purpose: Although there have been improvements in the management of metastatic retinoblastoma, most patients do not survive, and all patients suffer from multiple short- and long-term treatment toxicities. Reliable and informative models to assist clinicians are needed. Thus we developed and comprehensively characterized a novel preclinical platform of primary cell cultures and xenograft models of metastatic retinoblastoma to provide insights into the molecular biology underlying metastases and to perform drug screening for the identification of hit candidates with the highest potential for clinical translation. Methods: Orbital tumor, bone marrow, cerebrospinal fluid, and lymph node tumor infiltration specimens were obtained from seven patients with metastatic retinoblastoma at diagnosis, disease progression, or relapse. Tumor specimens were engrafted in immunodeficient animals, and primary cell lines were established. Genomic, immunohistochemical/immunocytochemical, and pharmacological analysis were performed. Results: We successfully established five primary cell lines: two derived from leptomeningeal, two from orbital, and one from lymph node tumor dissemination. After the intravitreal or intraventricular inoculation of these cells, we established cell-derived xenograft models. Both primary cell lines and xenografts accurately retained the histological and genomic features of the tumors from which they were derived and faithfully recapitulated the dissemination patterns and pharmacological sensitivity observed in the matched patients. Conclusions: Ours is an innovative and thoroughly characterized preclinical platform of metastatic retinoblastoma developed for the understanding of tumor biology of this highly aggressive tumor and has the potential to identify drug candidates to treat patients who currently lack effective treatment options.

Novel evaluation approach for molecular signature-based deconvolution methods.

The tumoral immune microenvironment (TIME) plays a key role in prognosis, therapeutic approach and pathophysiological understanding over oncological processes. Several computational immune cell-type deconvolution methods (DM), supported by diverse molecular signatures (MS), have been developed to uncover such TIME interplay from RNA-seq tumor biopsies. MS-DM pairs were benchmarked against each other by means of different metrics, such as Pearson's correlation, R2 and RMSE, but these only evaluate the linear association of the estimated proportion related to the expected one, missing the analysis of prediction-dependent bias trends and cell identification accuracy. We present a novel protocol composed of four tests allowing appropriate evaluation of the cell type identification performance and proportion prediction accuracy of molecular signature-deconvolution method pair by means of certainty and confidence cell-type identification scores (F1-score, distance to the optimal point and error rates) as well the Bland-Altman method for error-trend analysis. Our protocol was used to benchmark six state-of-the-art DMs (CIBERSORTx, DCQ, DeconRNASeq, EPIC, MIXTURE and quanTIseq) paired to five murine tissue-specific MSs, revealing a systematic overestimation of the number of different cell types across almost all methods.

Socioeconomic, Clinical, and Molecular Features of Breast Cancer Influence Overall Survival of Latin American Women.

Molecular profile of breast cancer in Latin-American women was studied in five countries: Argentina, Brazil, Chile, Mexico, and Uruguay. Data about socioeconomic characteristics, risk factors, prognostic factors, and molecular subtypes were described, and the 60-month overall cumulative survival probabilities (OS) were estimated. From 2011 to 2013, 1,300 eligible Latin-American women 18 years or older, with a diagnosis of breast cancer in clinical stage II or III, and performance status ≦̸1 were invited to participate in a prospective cohort study. Face-to-face interviews were conducted, and clinical and outcome data, including death, were extracted from medical records. Unadjusted associations were evaluated by Chi-squared and Fisher's exact tests and the OS by Kaplan-Meier method. Log-rank test was used to determine differences between cumulative probability curves. Multivariable adjustment was carried out by entering potential confounders in the Cox regression model. The OS at 60 months was 83.9%. Multivariable-adjusted death hazard differences were found for women living in Argentina (2.27), Chile (1.95), and Uruguay (2.42) compared with Mexican women, for older (≥60 years) (1.84) compared with younger (≤40 years) women, for basal-like subtype (5.8), luminal B (2.43), and HER2-enriched (2.52) compared with luminal A subtype, and for tumor clinical stages IIB (1.91), IIIA (3.54), and IIIB (3.94) compared with stage IIA women. OS was associated with country of residence, PAM50 intrinsic subtype, age, and tumor stage at diagnosis. While the latter is known to be influenced by access to care, including cancer screening, timely diagnosis and treatment, including access to more effective treatment protocols, it may also influence epigenetic changes that, potentially, impact molecular subtypes. Data derived from heretofore understudied populations with unique geographic ancestry and sociocultural experiences are critical to furthering our understanding of this complexity.

Exome and Tissue-Associated Microbiota as Predictive Markers of Response to Neoadjuvant Treatment in Locally Advanced Rectal Cancer.

The clinical and pathological responses to multimodal neoadjuvant therapy in locally advanced rectal cancers (LARCs) remain unpredictable, and robust biomarkers are still lacking. Recent studies have shown that tumors present somatic molecular alterations related to better treatment response, and it is also clear that tumor-associated bacteria are modulators of chemotherapy and immunotherapy efficacy, therefore having implications for long-term survivorship and a good potential as the biomarkers of outcome. Here, we performed whole exome sequencing and 16S ribosomal RNA (rRNA) amplicon sequencing from 44 pre-treatment LARC biopsies from Argentinian and Brazilian patients, treated with neoadjuvant chemoradiotherapy or total neoadjuvant treatment, searching for predictive biomarkers of response (responders, n = 17; non-responders, n = 27). In general, the somatic landscape of LARC was not capable to predict a response; however, a significant enrichment in mutational signature SBS5 was observed in non-responders (p = 0.0021), as well as the co-occurrence of APC and FAT4 mutations (p < 0.05). Microbiota studies revealed a similar alpha and beta diversity of bacteria between response groups. Yet, the linear discriminant analysis (LDA) of effect size indicated an enrichment of Hungatella, Flavonifractor, and Methanosphaera (LDA score ≥3) in the pre-treatment biopsies of responders, while non-responders had a higher abundance of Enhydrobacter, Paraprevotella (LDA score ≥3) and Finegoldia (LDA score ≥4). Altogether, the evaluation of these biomarkers in pre-treatment biopsies could eventually predict a neoadjuvant treatment response, while in post-treatment samples, it could help in guiding non-operative treatment strategies.

A Single Dose of a Hybrid hAdV5-Based Anti-COVID-19 Vaccine Induces a Long-Lasting Immune Response and Broad Coverage against VOC.

Most approved vaccines against COVID-19 have to be administered in a prime/boost regimen. We engineered a novel vaccine based on a chimeric human adenovirus 5 (hAdV5) vector. The vaccine (named CoroVaxG.3) is based on three pillars: (i) high expression of Spike to enhance its immunodominance by using a potent promoter and an mRNA stabilizer; (ii) enhanced infection of muscle and dendritic cells by replacing the fiber knob domain of hAdV5 by hAdV3; (iii) use of Spike stabilized in a prefusion conformation. The transduction with CoroVaxG.3-expressing Spike (D614G) dramatically enhanced the Spike expression in human muscle cells, monocytes and dendritic cells compared to CoroVaxG.5 that expressed the native fiber knob domain. A single dose of CoroVaxG.3 induced a potent humoral immunity with a balanced Th1/Th2 ratio and potent T-cell immunity, both lasting for at least 5 months. Sera from CoroVaxG.3-vaccinated mice was able to neutralize pseudoviruses expressing B.1 (wild type D614G), B.1.117 (alpha), P.1 (gamma) and B.1.617.2 (delta) Spikes, as well as an authentic P.1 SARS-CoV-2 isolate. Neutralizing antibodies did not wane even after 5 months, making this kind of vaccine a likely candidate to enter clinical trials.

Clinical and Genetic Spectrum of Stargardt Disease in Argentinean Patients.

PURPOSE: To describe the clinical and molecular spectrum of Stargardt disease (STGD) in a cohort of Argentinean patients. METHODS: This retrospective study included 132 subjects comprising 95 probands clinically diagnosed with STGD and relatives from 16 of them. Targeted next-generation sequencing of the coding and splicing regions of ABCA4 and other phenocopying genes (ELOVL4, PROM1, and CNGB3) was performed in 97 STGD patients. RESULTS: We found two or more disease-causing variants in the ABCA4 gene in 69/95 (73%) probands, a single ABCA4 variant in 9/95 (9.5%) probands, and no ABCA4 variants in 17/95 (18%) probands. The final analysis identified 173 variants in ABCA4. Seventy-nine ABCA4 variants were unique, of which nine were novel. No significant findings were seen in the other evaluated genes. CONCLUSION: This study describes the phenotypic and genetic features of STGD1 in an Argentinean cohort. The mutations p.(Gly1961Glu) and p.(Arg1129Leu) were the most frequent, representing almost 20% of the mutated alleles. We also expanded the ABCA4 mutational spectrum with nine novel disease-causing variants, of which eight might be associated with South American natives.

Recurrent Somatic Chromosomal Abnormalities in Relapsed Extraocular Retinoblastoma.

Most reports about copy number alterations (CNA) in retinoblastoma relate to patients with intraocular disease and features of children with extraocular relapse remain unknown, so we aimed to describe the CNA in this population. We evaluated 23 patients and 27 specimens from 4 centers. Seventeen cases had extraocular relapse after initial enucleation and six cases after an initial preservation attempt. We performed an analysis of CNA and BCOR gene alteration by SNP array (Single Nucleotide Polymorfism array), whole-exome sequencing, IMPACT panel and CGH array (Array-based comparative genomic hybridization). All cases presented CNA at a higher prevalence than those reported in previously published studies for intraocular cases. CNA previously reported for intraocular retinoblastoma were found at a high frequency in our cohort: gains in 1q (69.5%), 2p (60.9%) and 6p (86.9%), and 16q loss (78.2%). Other, previously less-recognized, CNA were found including loss of 11q (34.8%), gain of 17q (56.5%), loss of 19q (30.4%) and BCOR alterations were present in 72.7% of our cases. A high number of CNA including 11q deletions, 17q gains, 19q loss, and BCOR alterations, are more common in extraocular retinoblastoma. Identification of these features may be correlated with a more aggressive tumor warranting consideration for patient management.

Prognostic Impact of An Integrative Landscape of Clinical, Immune, and Molecular Features in Non-Metastatic Rectal Cancer.

Rectal Cancer (RC) is a complex disease that involves highly variable treatment responses. Currently, there is a lack of reliable markers beyond TNM to deliver a personalized treatment in a cancer setting where the goal is a curative treatment. Here, we performed an integrated characterization of the predictive and prognostic role of clinical features, mismatch-repair deficiency markers, HER2, CDX2, PD-L1 expression, and CD3-CD8+ tumor-infiltrating lymphocytes (TILs) coupled with targeted DNA sequencing of 76 non-metastatic RC patients assigned to total mesorectal excision upfront (TME; n = 15) or neoadjuvant chemo-radiotherapy treatment (nCRT; n = 61) followed by TME. Eighty-two percent of RC cases displayed mutations affecting cancer driver genes such as TP53, APC, KRAS, ATM, and PIK3CA. Good response to nCRT treatment was observed in approximately 40% of the RC cases, and poor pathological tumor regression was significantly associated with worse disease-free survival (DFS, HR = 3.45; 95%CI = 1.14-10.4; p = 0.028). High neutrophils-platelets score (NPS) (OR = 10.52; 95%CI=1.34-82.6; p = 0.025) and KRAS mutated cases (OR = 5.49; 95%CI = 1.06-28.4; p = 0.042) were identified as independent predictive factors of poor response to nCRT treatment in a multivariate analysis. Furthermore, a Cox proportional-hazard model showed that the KRAS mutational status was an independent prognostic factor associated with higher risk of local recurrence (HR = 9.68; 95%CI = 1.01-93.2; p <0.05) and shorter DFS (HR = 2.55; 95%CI = 1.05-6.21; p <0.05), while high CEA serum levels were associated with poor DFS (HR = 2.63; 95%CI = 1.01-6.85; p <0.05). Integrated clinical and molecular-based unsupervised analysis allowed us to identify two RC prognostic groups (cluster 1 and cluster 2) associated with disease-specific OS (HR = 20.64; 95%CI = 2.63-162.2; p <0.0001), metastasis-free survival (HR = 3.67; 95%CI = 1.22-11; p = 0.012), local recurrence-free survival (HR = 3.34; 95%CI = 0.96-11.6; p = 0.043) and worse DFS (HR = 2.68; 95%CI = 1.18-6.06; p = 0.012). The worst prognosis cluster 2 was enriched by stage III high-risk clinical tumors, poor responders to nCRT, with low TILs density and high frequency of KRAS and TP53 mutated cases compared with the best prognosis cluster 1 (p <0.05). Overall, this study provides a comprehensive and integrated characterization of non-metastatic RC cases as a new insight to deliver a personalized therapeutic approach.

Clinical, Genomic, and Pharmacological Study of MYCN-Amplified RB1 Wild-Type Metastatic Retinoblastoma.

An uncommon subgroup of unilateral retinoblastomas with highly aggressive histological features, lacking aberrations in RB1 gene with high-level amplification of MYCN (MCYNamplRB1+/+) has only been described as intra-ocular cases treated with initial enucleation. Here, we present a comprehensive clinical, genomic, and pharmacological analysis of two cases of MCYNamplRB1+/+ with orbital and cervical lymph node involvement, but no central nervous system spread, rapidly progressing to fatal disease due to chemoresistance. Both patients showed in common MYCN high amplification and chromosome 16q and 17p loss. A somatic mutation in TP53, in homozygosis by LOH, and high chromosomal instability leading to aneuploidy was identified in the primary ocular tumor and sites of dissemination of one patient. High-throughput pharmacological screening was performed in a primary cell line derived from the lymph node dissemination of one case. This cell line showed resistance to broad spectrum chemotherapy consistent with the patient's poor response but sensitivity to the synergistic effects of panobinostat-bortezomib and carboplatin-panobinostat associations. From these cells we established a cell line derived xenograft model that closely recapitulated the tumor dissemination pattern of the patient and served to evaluate whether triple chemotherapy significantly prolonged survival of the animals. We report novel genomic alterations in two cases of metastatic MCYNamplRB1+/+ that may be associated with chemotherapy resistance and in vitro/in vivo models that serve as basis for tailoring therapy in these cases.

Pre-Existing Tumoral B Cell Infiltration and Impaired Genome Maintenance Correlate with Response to Chemoradiotherapy in Locally Advanced Rectal Cancer.

Locally advanced rectal cancer (LARC) remains a medical challenge. Reliable biomarkers to predict which patients will significantly respond to neoadjuvant chemoradiotherapy (nCRT) have not been identified. We evaluated baseline genomic and transcriptomic features to detect differences that may help predict response to nCRT. Eligible LARC patients received nCRT (3D-LCRT 50.4 Gy plus capecitabine 825 mg/m2/bid), preceded by three cycles of CAPOX in high systemic-relapse risk tumors, and subsequent surgery. Frozen tumor biopsies at diagnosis were sequenced using a colorectal cancer panel. Transcriptomic data was used for pathway and cell deconvolution inferential algorithms, coupled with immunohistochemical validation. Clinical and molecular data were analyzed according to nCRT outcome. Pathways related to DNA repair and proliferation (p < 0.005), and co-occurrence of RAS and TP53 mutations (p = 0.001) were associated with poor response. Enrichment of expression signatures related to enhanced immune response, particularly B cells and interferon signaling (p < 0.005), was detected in good responders. Immunohistochemical analysis of CD20+ cells validated the association of good response with B cell infiltration (p = 0.047). Findings indicate that the presence of B cells is associated with successful tumor regression following nCRT in LARC. The prevalence of simultaneous RAS and TP53 mutations along with a proficient DNA repair system that may counteract chemoradio-induced DNA damage was associated with poor response.

Genomic and Transcriptomic Tumor Heterogeneity in Bilateral Retinoblastoma.

Importance: Comprehensive understanding of the genomic and gene-expression differences between retinoblastoma tumors from patients with bilateral disease may help to characterize risk and optimize treatment according to individual tumor characteristics. Objective: To compare the genomic features between each eye and a specimen from an orbital relapse in patients with bilateral retinoblastoma. Design, Setting, and Participants: In this case, 2 patients with retinoblastoma underwent upfront bilateral enucleation. Tumor samples were subjected to genomic and gene-expression analysis. Primary cell cultures were established from both of the tumors of 1 patient and were used for gene-expression studies. Main Outcomes and Measures: Whole-exome sequencing was performed on an Illumina platform for fresh tumor samples and DNA arrays (CytoScan or OncoScan) were used for paraffin-embedded samples and cell lines. Gene-expression analysis was performed using Agilent microarrays. Germinal and somatic alterations, copy number alterations, and differential gene expression were assessed. Results: After initial bilateral enucleation, patient 1 showed massive choroidal and laminar optic nerve infiltration, while patient 2 showed choroidal and laminar optic nerve invasion. Patient 1 developed left-eye orbital recurrence and bone marrow metastasis less than 1 year after enucleation. Both ocular tumors showed gains on 1q and 6p but presented other distinct genomic alterations, including an additional gain in 2p harboring the N-myc proto-oncogene (MYCN) in the left tumor and orbital recurrence. Similar copy number alterations between the orbital recurrence and the left eye supported the origin of the relapse, with an additional 11q loss only detected in the orbital relapse. Specimens from patient 2 showed common copy number gains and losses, but further evolution rendered a 2p gain spanning MYCN in the left tumor. For this patient, microarray expression analysis showed differential expression of the MYCN and the forkhead box protein G1 (FOXG1) gene pathways between the left and right tumors. Conclusions and Relevance: Differential genomic and gene expression features were observed between tumors in 2 patients with bilateral disease, confirming intereye heterogeneity that might be considered if targeted therapies are used in such patients. Chromosomal alteration profile supported the origin of the orbital recurrence from the homolateral eye in 1 patient. Loss in chromosome 11q may have been associated with extraocular relapse in this patient.

Massive integrative gene set analysis enables functional characterization of breast cancer subtypes.

The availability of large-scale repositories and integrated cancer genome efforts have created unprecedented opportunities to study and describe cancer biology. In this sense, the aim of translational researchers is the integration of multiple omics data to achieve a better identification of homogeneous subgroups of patients in order to develop adequate diagnostic and treatment strategies from the personalized medicine perspective. So far, existing integrative methods have grouped together omics data information, leaving out individual omics data phenotypic interpretation. Here, we present the Massive and Integrative Gene Set Analysis (MIGSA) R package. This tool can analyze several high throughput experiments in a comprehensive way through a functional analysis strategy, relating a phenotype to its biological function counterpart defined by means of gene sets. By simultaneously querying different multiple omics data from the same or different groups of patients, common and specific functional patterns for each studied phenotype can be obtained. The usefulness of MIGSA was demonstrated by applying the package to functionally characterize the intrinsic breast cancer PAM50 subtypes. For each subtype, specific functional transcriptomic profiles and gene sets enriched by transcriptomic and proteomic data were identified. To achieve this, transcriptomic and proteomic data from 28 datasets were analyzed using MIGSA. As a result, enriched gene sets and important genes were consistently found as related to a specific subtype across experiments or data types and thus can be used as molecular signature biomarkers.

TarSeqQC: Quality control on targeted sequencing experiments in R.

Targeted sequencing (TS) is growing as a screening methodology used in research and medical genetics to identify genomic alterations causing human diseases. In general, a list of possible genomic variants is derived from mapped reads through a variant calling step. This processing step is usually based on variant coverage, although it may be affected by several factors. Therefore, undercovered relevant clinical variants may not be reported, affecting pathology diagnosis or treatment. Thus, a prior quality control of the experiment is critical to determine variant detection accuracy and to avoid erroneous medical conclusions. There are several quality control tools, but they are focused on issues related to whole-genome sequencing. However, in TS, quality control should assess experiment, gene, and genomic region performances based on achieved coverages. Here, we propose TarSeqQC R package for quality control in TS experiments. The tool is freely available at Bioconductor repository. TarSeqQC was used to analyze two datasets; low-performance primer pools and features were detected, enhancing the quality of experiment results. Read count profiles were also explored, showing TarSeqQC's effectiveness as an exploration tool. Our proposal may be a valuable bioinformatic tool for routinely TS experiments in both research and medical genetics.

Predictive Outcomes for HER2-enriched Cancer Using Growth and Metastasis Signatures Driven By SPARC.

Understanding the mechanism of metastatic dissemination is crucial for the rational design of novel therapeutics. The secreted protein acidic and rich in cysteine (SPARC) is a matricellular glycoprotein which has been extensively associated with human breast cancer aggressiveness although the underlying mechanisms are still unclear. Here, shRNA-mediated SPARC knockdown greatly reduced primary tumor growth and completely abolished lung colonization of murine 4T1 and LM3 breast malignant cells implanted in syngeneic BALB/c mice. A comprehensive study including global transcriptomic analysis followed by biological validations confirmed that SPARC induces primary tumor growth by enhancing cell cycle and by promoting a COX-2-mediated expansion of myeloid-derived suppressor cells (MDSC). The role of SPARC in metastasis involved a COX-2-independent enhancement of cell disengagement from the primary tumor and adherence to the lungs that fostered metastasis implantation. Interestingly, SPARC-driven gene expression signatures obtained from these murine models predicted the clinical outcome of patients with HER2-enriched breast cancer subtypes. In total, the results reveal that SPARC and its downstream effectors are attractive targets for antimetastatic therapies in breast cancer.Implications: These findings shed light on the prometastatic role of SPARC, a key protein expressed by breast cancer cells and surrounding stroma, with important consequences for disease outcome. Mol Cancer Res; 15(3); 304-16. ©2016 AACR.

Improving information retrieval in functional analysis.

Transcriptome analysis is essential to understand the mechanisms regulating key biological processes and functions. The first step usually consists of identifying candidate genes; to find out which pathways are affected by those genes, however, functional analysis (FA) is mandatory. The most frequently used strategies for this purpose are Gene Set and Singular Enrichment Analysis (GSEA and SEA) over Gene Ontology. Several statistical methods have been developed and compared in terms of computational efficiency and/or statistical appropriateness. However, whether their results are similar or complementary, the sensitivity to parameter settings, or possible bias in the analyzed terms has not been addressed so far. Here, two GSEA and four SEA methods and their parameter combinations were evaluated in six datasets by comparing two breast cancer subtypes with well-known differences in genetic background and patient outcomes. We show that GSEA and SEA lead to different results depending on the chosen statistic, model and/or parameters. Both approaches provide complementary results from a biological perspective. Hence, an Integrative Functional Analysis (IFA) tool is proposed to improve information retrieval in FA. It provides a common gene expression analytic framework that grants a comprehensive and coherent analysis. Only a minimal user parameter setting is required, since the best SEA/GSEA alternatives are integrated. IFA utility was demonstrated by evaluating four prostate cancer and the TCGA breast cancer microarray datasets, which showed its biological generalization capabilities.

The multi-reference contrast method: facilitating set enrichment analysis.

Set enrichment analysis (SEA) is used to identify enriched biological categories/terms within high-throughput differential expression experiments. This is done by evaluating the proportion of differentially expressed genes against a background reference (BR). However, the choice of the "appropriate" BR is a perplexing problem and results will depend on it. Here, a visualization procedure that integrates results from several BRs and a stability analysis of enriched terms is presented as a tool to aid SEA. The multi-reference contrast method (MRCM) combines results from multiple BRs in a unique picture. The application of the proposed method was illustrated in one proteomic and three microarray experiments. The MRCM facilitates the exploration task involved in ontology analysis on proteomic/genomic experiments, where consensus terms were found to validate main experimental hypothesis. The use of more than one reference may provide new biological insights. The tool automatically highlights non-consensus terms assisting SEA.

SPARC promotes cathepsin B-mediated melanoma invasiveness through a collagen I/α2ß1 integrin axis.

In melanoma, the extracellular protein SPARC (secreted protein acidic and rich in cysteine) is related to tumor progression. Some of the evidence that links SPARC to melanoma progression indicates that SPARC may be involved in the acquisition of mesenchymal traits that favor metastatic dissemination. However, no molecular pathways that link extracellular SPARC to a mesenchymal phenotype have been described. In this study, global protein expression analysis of the melanoma secretome following enforced downregulation of SPARC expression led us to elucidate a new molecular mechanism by which SPARC promotes cathepsin B-mediated melanoma invasiveness using collagen I and α2ß1 integrins as mediators. Interestingly, we also found that the transforming growth factor (TGF)-ß1 contribution to cathepsin B-mediated invasion is highly SPARC dependent. In addition, induction of the E-cadherin to N-cadherin switch by SPARC enabled melanoma cells to transmigrate across an endothelial layer through a mechanism independent to that of enhancing invasion. Finally, SPARC also enhanced the extracellular expression of other proteins involved in epithelial-mesenchymal transformation, such as family with sequence similarity 3, member C/interleukin-like EMT-inducer. Our findings demonstrate a previously unreported molecular pathway for SPARC activity on invasion and support an active role of SPARC in the mesenchymal transformation that contributes to melanoma dissemination.

Improving 2D-DIGE protein expression analysis by two-stage linear mixed models: assessing experimental effects in a melanoma cell study.

MOTIVATION: Difference in-gel electrophoresis (DIGE)-based protein expression analysis allows assessing the relative expression of proteins in two biological samples differently labeled (Cy5, Cy3 CyDyes). In the same gel, a reference sample is also used (Cy2 CyDye) for spot matching during image analysis and volume normalization. The standard statistical techniques to identify differentially expressed (DE) proteins are the calculation of fold-changes and the comparison of treatment means by the t-test. The analyses rarely accounts for other experimental effects, such as CyDye and gel effects, which could be important sources of noise while detecting treatment effects. RESULTS: We propose to identify DIGE DE proteins using a two-stage linear mixed model. The proposal consists of splitting the overall model for the measured intensity into two interconnected models. First, we fit a normalization model that accounts for the general experimental effects, such as gel and CyDye effects as well as for the features of the associated random term distributions. Second, we fit a model that uses the residuals from the first step to account for differences between treatments in protein-by-protein basis. The modeling strategy was evaluated using data from a melanoma cell study. We found that a heteroskedastic model in the first stage, which also account for CyDye and gel effects, best normalized the data, while allowing for an efficient estimation of the treatment effects. The Cy2 reference channel was used as a covariate in the normalization model to avoid skewness of the residual distribution. Its inclusion improved the detection of DE proteins in the second stage.

The role of the matricellular protein SPARC in the dynamic interaction between the tumor and the host.

Tumor growth is essentially the result of an evolving cross-talk between malignant and surrounding stromal cells (fibroblasts, endothelial cells and inflammatory cells). This heterogeneous mass of extracellular matrix and intermingled cells interact through cell-cell and cell-matrix contacts. Malignant cells also secrete soluble proteins that reach neighbor stromal cells, forcing them to provide the soil on which they will grow and metastasize. Different studies including expression array analysis identified the matricellular protein SPARC as a marker of poor prognosis in different cancer types. Further evidence demonstrated that high SPARC levels are often associated with the most aggressive and highly metastatic tumors. Here we describe the most recent evidence that links SPARC with human cancer progression, the controversy regarding its role in certain human cancers and the physiological processes in which SPARC is involved: epithelial-mesenchymal transition, immune surveillance and angiogenesis. Its relevance as a potential target in cancer therapy is also discussed.