Spanish National Cancer Research Center Research Articles

2nd Annual Conference on Health and Food Science Technology (ACHOST) 2021

We are glad to introduce you the proceedings of the first Annual Conference on Health and Food Science Technology (ACHOST) 2021. The 2nd ACHOST 2021 addresses challenges and innovations the field of Food Science and Health, Environmental Science and Issue, Earth Science and Technology. It also provides a premier interdisciplinary platform for researchers, educators and practitioners to present and discuss the most recent innovations, trends, and concerns as well as practical challenges encountered and solutions adopted in the fields of of applied science, technology, and engineering.As we may aware, the World Health Organization officially declared the novel coronavirus COVID-19 a pandemic. Governments around the world are now issuing restrictions on travel, gatherings, and meetings in an effort to limit and slow the spread of the virus. The health and safety of the author and reseacher community is our first priority and we are supporting these efforts. Therefore, the ACHOST conference was held virtually on 20 November 2021.The ACHOST conference is hosted by PT. Kresna Acitya Nusantara Mediatama and co-hosted by Universitas Muhammadiyah Sidoarjo, Relawan Jurnal Indonesia. This year, we held this flexible online conference to gather experts and scholars around the globe with the aim to continue disseminating the latest advanced research in the field of Food Science and Health, Environmental Science and Issue, Earth Science and Technology. The conference was held from Yogyakarta as the host of the event. The ACHOST 2021 event is virtually implemented with a model that all invited speakers are given time to present their material for about 30-45 minutes each. It then followed by a question and answer by the participants with a direct questioning system, through chat forums and Q&A forums provided by the zoom application. Overall, the conference took 6 hours.The number of participants who joined the zoom room was recorded around 341 participants. The authors or participants are came from 5 countries, namely Indonesia, Malaysia, Brunei Darussalam, Philippine and India. Indonesian Participants are come from 19 Provinces of 33 Provinces.The committee of the conference are honored to have invited following renowned experts as our keynote speakers. ASSOC. PROF. IR. TS. DR. MUZAMMIL BIN JUSOH (C.ENG), PhD from Universiti Malaysia Perlis; DR. YUDHI NUGRAHA from Spanish National Cancer Research Center (CNIO).We are glad to share with you that around 89 pre-registered authors are submitted their work in the conferences. However, its about 54 papers are selected and accepted for the conferences. All the papers have been through rigorous review by a panel of reviewers who provide critical comments and corrections, and have contributed subtantially to the improvement of the quality of the papers to meet the requirements of International publication standard and IOP EES Scope.We would like to express our sincere gratitude to the Chairman, the distinguished keynote speakers, as well as all the participants. We also want to thank the publisher for publishing the proceedings. May the readers could enjoy the gain some valuable knowledge from it. We are expecting more and more experts and scholars from all over the world to join this international event next year.List of Chair of the Organizing Committee, Editors, Host Organizer, Committee are available in this Pdf.

Multidisciplinary practice guidelines for the diagnosis, genetic counseling and treatment of pheochromocytomas and paragangliomas

Pheochromocytomas and paragangliomas (PPGLs) are rare neuroendocrine tumors that arise from chromaffin cells of the adrenal medulla and the sympathetic/parasympathetic neural ganglia, respectively. The heterogeneity in its etiology makes PPGL diagnosis and treatment very complex. The aim of this article was to provide practical clinical guidelines for the diagnosis and treatment of PPGLs from a multidisciplinary perspective, with the involvement of the Spanish Societies of Endocrinology and Nutrition (SEEN), Medical Oncology (SEOM), Medical Radiology (SERAM), Nuclear Medicine and Molecular Imaging (SEMNIM), Otorhinolaryngology (SEORL), Pathology (SEAP), Radiation Oncology (SEOR), Surgery (AEC) and the Spanish National Cancer Research Center (CNIO). We will review the following topics: epidemiology; anatomy, pathology and molecular pathways; clinical presentation; hereditary predisposition syndromes and genetic counseling and testing; diagnostic procedures, including biochemical testing and imaging studies; treatment including catecholamine blockade, surgery, radiotherapy and radiometabolic therapy, systemic therapy, local ablative therapy and supportive care. Finally, we will provide follow-up recommendations.

A combination of urinary biomarker panel and PancRISK score for earlier detection of pancreatic cancer: A case-control study.

BackgroundPancreatic ductal adenocarcinoma (PDAC) is one of the deadliest cancers, with around 9% of patients surviving >5 years. Asymptomatic in its initial stages, PDAC is mostly diagnosed late, when already a locally advanced or metastatic disease, as there are no useful biomarkers for detection in its early stages, when surgery can be curative. We have previously described a promising biomarker panel (LYVE1, REG1A, and TFF1) for earlier detection of PDAC in urine. Here, we aimed to establish the accuracy of an improved panel, including REG1B instead of REG1A, and an algorithm for data interpretation, the PancRISK score, in additional retrospectively collected urine specimens. We also assessed the complementarity of this panel with CA19-9 and explored the daily variation and stability of the biomarkers and their performance in common urinary tract cancers.Methods and findingsClinical specimens were obtained from multiple centres: Barts Pancreas Tissue Bank, University College London, University of Liverpool, Spanish National Cancer Research Center, Cambridge University Hospital, and University of Belgrade. The biomarker panel was assayed on 590 urine specimens: 183 control samples, 208 benign hepatobiliary disease samples (of which 119 were chronic pancreatitis), and 199 PDAC samples (102 stage I–II and 97 stage III–IV); 50.7% were from female individuals. PDAC samples were collected from patients before treatment. The samples were assayed using commercially available ELISAs. Statistical analyses were performed using non-parametric Kruskal–Wallis tests adjusted for multiple comparisons, and multiple logistic regression. Training and validation datasets for controls and PDAC samples were obtained after random division of the whole available dataset in a 1:1 ratio. The substitution of REG1A with REG1B enhanced the performance of the panel to detect resectable PDAC. In a comparison of controls and PDAC stage I–II samples, the areas under the receiver operating characteristic curve (AUCs) increased from 0.900 (95% CI 0.843–0.957) and 0.926 (95% CI 0.843–1.000) in the training (50% of the dataset) and validation sets, respectively, to 0.936 in both the training (95% CI 0.903–0.969) and the validation (95% CI 0.888–0.984) datasets for the new panel including REG1B. This improved panel showed both sensitivity (SN) and specificity (SP) to be >85%. Plasma CA19-9 enhanced the performance of this panel in discriminating PDAC I–II patients from controls, with AUC = 0.992 (95% CI 0.983–1.000), SN = 0.963 (95% CI 0.913–1.000), and SP = 0.967 (95% CI 0.924–1.000). We demonstrate that the biomarkers do not show significant daily variation, and that they are stable for up to 5 days at room temperature. The main limitation of our study is the low number of stage I–IIA PDAC samples (n = 27) and lack of samples from individuals with hereditary predisposition to PDAC, for which specimens collected from control individuals were used as a proxy.ConclusionsWe have successfully validated our urinary biomarker panel, which was improved by substituting REG1A with REG1B. At a pre-selected cutoff of >80% SN and SP for the affiliated PancRISK score, we demonstrate a clinically applicable risk stratification tool with a binary output for risk of developing PDAC (‘elevated’ or ‘normal’). PancRISK provides a step towards precision surveillance for PDAC patients, which we will test in a prospective clinical study, UroPanc.

Centre for Genomic Regulation - a hub for Integrative Biology in Barcelona.

Centre for Genomic Regulation - a hub for Integrative Biology in Barcelona.

1674P - Exploratory study of CK-M30 and pHH3 expression in Circulating Tumor Cells (CTCs) as biomarkers of docetaxel (DOC) efficacy in metastatic castration resistant prostate cancer (mCRPC)

Background: A drop in CTCs counts as early as 4 weeks following treatment initiation have been suggested as an indicator of overall survival (OS) benefit. DOC remains a pivotal treatment in mCRPC for which there are no early pharmacodynamic (PD) markers of its activity in patients (pts). CTCs may be used as surrogate tumor tissue to study PD markers of apoptosis (CK-M30) or mitosis arrest (pHH3) in mCRPC pts receiving DOC. Methods: We conducted a prospective 2-cohort multicenter exploratory study in mCRPC pts progressing by PCWG2 criteria who were eligible for DOC 75 mg/m^2. Pts were prescreened using the CellSearch system and selected if CTCs≥5/7.5mLs of blood (Basal 1). A 2nd blood sample (Basal 2) was drawn in eligible pts within 0-7 days prior to C1D1 of DOC and further samples were collected at 8h, 24h, 7d and 21d. Directly conjugated mAb against pHH3 and CK-M30 were used in combination with CellSearch. Statistical analyses were performed to evaluate the baseline and post-treatment variability. Increases in % of biomarker CTC+ greater than the median baseline variability were correlated with achieving a 50% PSA response (PSA50) and OS from DOC start using chi-square and long-rank test, respectively. Results: 60 mCRPC pts (CK-M30 = 30; pHH3 = 30), 95% ECOG 0-1, 95% and 17% have bone and visceral metastases respectively, received a median of 7 cycles (range 2-10) of DOC. Biomarker results are summarised in Table.Table1674P VariabilityBasal 1 (N = 60) Median (Range)Basal 2 (N = 57) Median (Range)%marker Corr. CoeffPost-24h (n = 59) median (Range)P-value Basal vs post-24hCohort CK-M30CTC/7.5mL9 (5-1266)8 (3-863)0.54 p = 0.7639 (4-1129)NSCK-M30+48% (0-76%)35% (0-100%)51% (0-100%)Cohort pHH3CTC/7.5mL10 (5-567)12 (4-623)0.98 p < 0.0019 (3-584)<0.001pHH3+0% (0-10%)0% (0-8%)7% (0-67%)ResponseNPSA50p-valueOS median (CI95%)p-valueCK-M30+ change 24hCKM30 + >50%52NS24 m (–)NSCKM30 + <50%251121 m (12-30)pHH3+ change 24hpHH3 + >10%1380.04717 m (12-22)NSpHH3 + <10%16412 m (6-18) Open table in a new tab Conclusions: pHH3 in CTC+ may be a potential PD biomarker of a favourable response to DOC treatment. Legal entity responsible for the study: Spanish National Cancer Research Centre Funding: None Disclosure: All authors have declared no conflicts of interest.

A comparison of conditional random fields and structured support vector machines for chemical entity recognition in biomedical literature.

BackgroundChemical compounds and drugs (together called chemical entities) embedded in scientific articles are crucial for many information extraction tasks in the biomedical domain. However, only a very limited number of chemical entity recognition systems are publically available, probably due to the lack of large manually annotated corpora. To accelerate the development of chemical entity recognition systems, the Spanish National Cancer Research Center (CNIO) and The University of Navarra organized a challenge on Chemical and Drug Named Entity Recognition (CHEMDNER). The CHEMDNER challenge contains two individual subtasks: 1) Chemical Entity Mention recognition (CEM); and 2) Chemical Document Indexing (CDI). Our study proposes machine learning-based systems for the CEM task.MethodsThe 2013 CHEMDNER challenge organizers provided a manually annotated 10,000 UTF8-encoded PubMed abstracts according to a predefined annotation guideline: a training set of 3,500 abstracts, a development set of 3,500 abstracts and a test set of 3,000 abstracts. We developed machine learning-based systems, based on conditional random fields (CRF) and structured support vector machines (SSVM) respectively, for the CEM task for this data set. The effects of three types of word representation (WR) features, generated by Brown clustering, random indexing and skip-gram, on both two machine learning-based systems were also investigated. The performance of our system was evaluated on the test set using scripts provided by the CHEMDNER challenge organizers. Primary evaluation measures were micro Precision, Recall, and F-measure.ResultsOur best system was among the top ranked systems with an official micro F-measure of 85.05%. Fixing a bug caused by inconsistent features marginally improved the performance (micro F-measure of 85.20%) of the system.ConclusionsThe SSVM-based CEM systems outperformed the CRF-based CEM systems when using the same features. Each type of the WR feature was beneficial to the CEM task. Both the CRF-based and SSVM-based systems using the all three types of WR features showed better performance than the systems using only one type of the WR feature.

INSIDE INDUSTRY

AMSilk founder Professor Thomas Scheibel receives DECHEMA award. ProJect Pharmaceutics and TUM-Spin-off ImevaX collaborate on development of pharmaceutical formulation for IMX101. DSM and Tunitas Therapeutics to develop lead allergy therapeutic. RCSI led EU Consortium receives major funding to develop materials to regenerate cardiac tissue following heart attacks. Teva and Takeda to research multiple sclerosis treatment in Japan. AB SCIEX helps accelerate food safety testing in Southeast Asia's largest food producer. Merck enters into license agreement with the Spanish National Cancer Research Centre. Agilent Technologies and Nanyang Technological University collaborate on wastewater treatment research. IBC Life Sciences and ISPE Singapore Affiliate to partner on ISPE Singapore Conference &amp; Exhibition 2014. Novogen enters global collaboration to drive the development of drugs to treat brain cancer.

International Society for Computational Biology Honors David Eisenberg with 2013 Accomplishment by a Senior Scientist Award

International Society for Computational Biology Honors David Eisenberg with 2013 Accomplishment by a Senior Scientist Award

Endoscopic ultrasound procedures on panceatic fluid

Endoscopic ultrasound procedures on panceatic fluid

International Society for Computational Biology Honours Gunnar von Heijne and Ziv Bar-Joseph with Top Bioinformatics/Computational Biology Awards for 2012

Each year, the International Society for Computational Biology (ISCB; http://www.iscb.org) makes awards for exceptional achievement to two scientists. The ISCB Accomplishment by a Senior Scientist Award honours career achievement in recognition of distinguished contributions over many years in research, teaching, service, or any combination of the three. In 2012 this award is going to Gunnar von Heijne of the Stockholm University in Sweden. The Overton Prize recognizes a young scientist in the early to mid-stage of his or her career who has already achieved a significant and lasting impact in the field of computational biology. In 2012, the Overton Prize is being awarded to Ziv Bar-Joseph of Carnegie Mellon University in Pittsburgh, Pennsylvania, United States. The recipients were chosen by the ISCB's awards committee chaired by Alfonso Valencia at the CNIO (Spanish National Cancer Research Centre) in Madrid. The winners will receive their awards at the ISCB's annual Intelligent Systems for Molecular Biology (ISMB) meeting, where they will deliver keynote talks. ISMB 2012 (http://www.iscb.org/ismb2012) marks the 20th anniversary of the conference, and will take place July 15–17 in Long Beach, California, United States.

Spanish national hereditary pancreatic cancer registry (PanFAM).

e12033 Background: Inherited predisposition to Pancreatic Cancer (PC) corresponds 10% of all cases and includes members of families affected with hereditary cancer syndromes as Familial Pancreatic Cancer (FPC), Peutz-Jeghers, familial melanoma, hereditary breast and ovarian cancer, hereditary pancreatitis. An inherited predisposition in early onset PC (≤ 50 years) has also been suggested. We report preliminary data on PanFAM patients and screening of high risk individuals. Methods: PamFAM is a part of the European PANGEN PC case/control study of hereditary PC, co-ordinated by the Ramón y Cajal (RC) hospital and the Spanish National Cancer Research Center, with 16 participating hospitals. All families with clinical evidence of an inherited PC syndrome were recruited and multi-generational pedigrees were constructed. Cancer diagnoses were confirmed, when possible, by review of medical records. Blood samples and epidemiological data were collected for all participating family members. A screening program for early detection of PC, based on endoscopic ultrasound (EUS), CT and circulating tumour cells (CTCs) was offered to high risk individuals. Results: Of 505 Spanish PCs collected by PANGEN, 31 (~6%) were FPC cases; 18 (58%) revealed only PC and the remaining showed clustering with other tumor types, gastric cancer was the most common (13%). Among FPC families, 3 had 3 cases of PC and the remaining had 2 cases. The mean age of diagnosis was 67 years (range 47-85), 20 male and 11 female. Four FPCs were previously diagnosed with cancer (Hodgkin lymphoma, breast and prostate cancer) and 3 with acute pancreatitis. 37 PCs with no family history of cancer were diagnosed at the age of 50 years or earlier (mean 45, range 30-50), 18 male and 19 female. Other 27 eligible families were recruited by RyC hospital, 8 (30%) with FPC and 3 (11%) with PC ≤ 50 years. A cohort of 61 high risk individuals participes in the screening study: 3 had abnormal EUS, 1 a benign pancreatic node and 1 a renal angiolipoma; one young man had 2 CTCs. Conclusions: PanFAM is the first registry in Spain collecting hereditary PC cases and it represents an important resource to identify underlying gene defects and to the development of screening methods precursor lesions detection in high risk individuals.

Cohesin-SA1 deficiency drives aneuploidy and tumourigenesis in mice due to impaired replication of telomeres

Cohesin is a protein complex originally identified for its role in sister chromatid cohesion, although increasing evidence portrays it also as a major organizer of interphase chromatin. Vertebrate cohesin consists of Smc1, Smc3, Rad21/Scc1 and either stromal antigen 1 (SA1) or SA2. To explore the functional specificity of these two versions of cohesin and their relevance for embryonic development and cancer, we generated a mouse model deficient for SA1. Complete ablation of SA1 results in embryonic lethality, while heterozygous animals have shorter lifespan and earlier onset of tumourigenesis. SA1-null mouse embryonic fibroblasts show decreased proliferation and increased aneuploidy as a result of chromosome segregation defects. These defects are not caused by impaired centromeric cohesion, which depends on cohesin-SA2. Instead, they arise from defective telomere replication, which requires cohesion mediated specifically by cohesin-SA1. We propose a novel mechanism for aneuploidy generation that involves impaired telomere replication upon loss of cohesin-SA1, with clear implications in tumourigenesis.

Lack of Major Histocompatibility Class II (MHCII) Protein and Decreased Immunosurveillance in Plasmablastic Lymphoma (PBL)

Abstract 5186PBL is a distinct clinicopathological entity classified separately from diffuse large B-cell lymphoma (DLBCL). A recent immunohistochemical (IHC) study described the plasmablastic phenotype of PBL including co-expression of PRDM1/BLIMP1 and XBP1 with lack of the B cell markers PAX5 and CD20. This protein expression profile is unusual for DLBCL and therefore helps to differentiate PBL tumors from conventional DLBCL. In a minority of DLBCL cases, the acquisition of a partial plasmablastic phenotype (Blimp1 positive) is associated with a worse outcome. Given that Blimp1 and MHCII expression are inversely related as normal B cells enter the terminal differentiation program towards plasma cells, and that loss of MHCII mRNA and protein expression correlates with poor outcome DLBCL (likely due to a loss of immunosurveillance), we hypothesized that PBL cases would also lack HLA-DR and have correspondingly low numbers of tumor infiltrating T cells.Twenty-three cases of PBL, which were part of a previously published case series (S. Montes-Moreno et al, Haematologica 2010) from the Spanish National Cancer Research Center were studied with approval of the Carlos III Institutional Review Board. Cases were stained with antibodies specific to HLA-DR and CD8. Three consecutive 60x fields with a minimum of 950 cells were counted per case. As previously (L.M. Rimsza et al, Blood 2004) described, the area of tumor with the lowest frequency of CD8(+) cells was chosen for counting. The IHC results were quantified by counting the number of HLA-DR(+) cells and CD8(+) cells in the total number of malignant cells or lymphoid-appearing cells respectively (obvious stromal and histiocytic cells excluded). HLA-DR staining intensity was also scored as followed: 0 = no staining; 1+ = faint partial staining; 2+ = complete or partial moderate staining; 3+ = complete strong staining. Additionally, HLA-DR staining was characterized as surface membrane, cytoplasmic, or negative.Only three PBL cases (13%) showed the typical B-cell pattern of HLA-DR cell surface membrane expression in a few (2% ± 2) of tumor cells with a faint to partial expression (median intensity of 1.8 ± 0.7), and average of 14% (±10) CD8(+) cells. Cytoplasmic HLA-DR expression in the absence of membrane expression was observed in 10 cases (43.5%) in a minority of cells (9% ±18) with a median intensity of 1.9+ (±0.6), and an average of 10.3% (±6) CD8(+) cells. Ten cases (43.5%) were completely negative for HLA-DR and showed only 7% (± 6) CD8(+) cells.In summary, this study demonstrates the lack of MHCII protein expression on the surface membrane of most cases of PBL, which is associated with a decrease in CD8(+) tumor infiltrating T-cells cells, likely indicative of decreased immunosurveillance. These results are in agreement with our previous studies, in which DLBCL cases showed an average of 11% CD8(+) T-cells in the presence of MHCII cell surface expression, but only 2.8% CD8(+) T-cells in the absence of MHCII protein cell surface expression. The significance of the cytoplasmic localization is not clear, however may represent a stage of partial expression, which is associated with an intermediate level of T cells. Decreased immunosurveillance has long been correlated with deficient host response and tumor containment. The absence of MHCII protein expression may provide a reason for the poor outcome in PBL patients as well as serve as additional tool for diagnosis. Disclosures:No relevant conflicts of interest to declare.

Straight talk with... María Blasco

On 22 June, María Blasco, best known for her research on the enzymes that maintain telomeres, became the new director of the Spanish National Cancer Research Centre (CNIO). Elie Dolgin spoke with her about her plans for the 13-year-old agency. Life hasn't been easy at the Spanish National Cancer Research Centre (CNIO) since the founding director Mariano Barbacid announced his intention to step down in 2009. Two campaigns to find a successor had to be halted—the first for lack of international candidates, and the second because nominees' names were leaked to the press. The leaks occurred amidst a high-profile dispute over Barbacid's controversial plan to use private funds to develop cancer drugs—a move that the country's Ministry of Science and Innovation said contradicted state financing rules for a public foundation. But things seem to have settled down since CNIO insider María Blasco was unanimously chosen to lead the 13-year-old center. Blasco, best known for her research on the enzymes that maintain telomeres, had directed the center's molecular oncology program since 2003, and had been vice director for basic research at the center since 2005. She became the CNIO's new director on 22 June. Elie Dolgin spoke to the new cancer capitán about her plans for the agency.

Centralizing Discovery Information: From Logistics to Knowledge at a Public Organization

Due to the huge amount of data generated in drug discovery programs, their success strongly depends on both the workflows and platforms to manage and, more importantly, to integrate different chemical and biological data sources. At Experimental Therapeutics Program in the Spanish National Cancer Research Center (CNIO), we have addressed our efforts in the design and optimal implementation of those key processes that enable dynamic workflows and interfaces between the different information blocks. Our approach focuses on the development of a common chemical and biological repository (CCBR) that gathers all data that pass quality control criteria. An integral web application (WACBIP) was designed to query against CCBR while providing decision making tools. Currently, our CCBR contains more than 43,000 unique structures as well as experimental data from more than 350 different biological assays. As input sources of the CCBR, we federated a series of Laboratory Information Management Systems (LIMS) which cover sections as follows: chemical synthesis, analytical department, compound logistics, biochemical and cellular data (including high-throughput and high-content screenings; HTS and HCS), computational chemistry (in-silico chemogenomics and physico-chemical profiling) and in-vivo pharmacology. With regard to the last section, an integral In-Vivo Management e-Biobook (IVMB) that handles the entire workflow of in-vivo labs was designed and implemented. Herein we describe the processes and tools that we have developed and implemented, balancing purchase and development, for centralizing discovery information as well as providing decision-making and project management tools - a clear unmet need in public organizations and networks.

Predicting response to BCG

Methylation status of a select panel of genes can predict failure of bacillus Calmette–Guerin (BCG) immunotherapy, according to research carried out by Marta Sanchez-Carbayo and colleagues at the Spanish National Cancer Research Centre in Madrid. Intravesical BCG is the treatment of choice for patients with non-muscle-invasive bladder cancer who are considered to be at high risk of recurrence and progression to muscle-invasive disease. However, about a third of recipients do not respond to BCG, and the ability to identify which patients might require more-aggressive management is a major goal of bladder cancer research today.

International Society for Computational Biology Honors Michael Ashburner and Olga Troyanskaya with Top Bioinformatics/Computational Biology Awards for 2011

Each year, the International Society for Computational Biology (ISCB; http://www.iscb.org/) makes awards for exceptional achievement to two scientists. The first is presented to a scientist who has made distinguished contributions over many years in research, teaching, service, or any combination of the three. This year, the ISCB Accomplishment by a Senior Scientist Award goes to Michael Ashburner in the department of genetics at the University of Cambridge. The second, known as the Overton Prize, honours a young scientist in the early to mid-stage of his or her career who has already achieved significant and lasting impact in the field of computational biology. In 2011, the Overton Prize is awarded to Olga Troyanskaya of Princeton University in New Jersey. The recipients were chosen by the ISCB's awards committee chaired by Alfonso Valencia at the CNIO (Spanish National Cancer Research Centre) in Madrid. The winners will receive their awards at the ISCB's annual meeting, where they will also deliver keynote talks. This meeting, ISMB/ECCB 2011 http://www.iscb.org/ismbeccb2011, will take place in Vienna, Austria, 17–19 July 2011.

A Framework for BioCuration Workflows (part II)

AbstractThis is the second part of the talk ‘A Framework for BioCuration Workflows’, given by Martin Krallinger from the Spanish National Cancer Research Centre at the 'Text Mining for the BioCuration Workflow' workshop. The first part was held by Gully APC Burns (USC Information Sciences Institute, USA). This presentation covered some of the main general tasks often shared by existing literature biocuration workflows: Identification of relevant articles, identification and normalization of the actual bio-entities, the extraction of the annotation event and the identification of some evidential support (e.g. experimental evidence). Some of the important aspects, bottlenecks and potential text mining approaches were briefly introduced for each general workflow task. This talk provided a short overview of some of the important aspects to integrate text mining systems into a given biocuration workflow and showed how heterogeneous workflows can be even for a relatively straight forward task such as the identification of curation relevant literature. A more detailed example of the biocuration of protein-protein interactions through the workflow followed by the BioGRID database was presented.

Protein co-evolution, co-adaptation and interactions

Co-evolution has an important function in the evolution of species and it is clearly manifested in certain scenarios such as host–parasite and predator–prey interactions, symbiosis and mutualism. The extrapolation of the concepts and methodologies developed for the study of species co-evolution at the molecular level has prompted the development of a variety of computational methods able to predict protein interactions through the characteristics of co-evolution. Particularly successful have been those methods that predict interactions at the genomic level based on the detection of pairs of protein families with similar evolutionary histories (similarity of phylogenetic trees: mirrortree). Future advances in this field will require a better understanding of the molecular basis of the co-evolution of protein families. Thus, it will be important to decipher the molecular mechanisms underlying the similarity observed in phylogenetic trees of interacting proteins, distinguishing direct specific molecular interactions from other general functional constraints. In particular, it will be important to separate the effects of physical interactions within protein complexes (‘co-adaptation') from other forces that, in a less specific way, can also create general patterns of co-evolution.

An account of the Seventh Meeting of the Worldwide Critical Assessment of Techniques for Protein Structure Prediction

An account of the Seventh Meeting of the Worldwide Critical Assessment of Techniques for Protein Structure Prediction