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http://www.bccrc.ca/dept/ttr

A provincial biobank resource to support translational cancer research at the BC Cancer Agency, across Canada and internationally. This biobank collects biospecimens (tissues and blood), and clinical information and processes these to create anonymous cases that can be studied by cancer researchers to understand how cancer develops, how it grows, how it spreads, and how it responds to treatment. These tissues and data are obtained from patients who undergo surgery to treat a tumor and who have generously provided their consent for the TTR to collect tissues that are unused after diagnosis has been completed. The TTR is a provincial program that currently comprises a core biobank at the Vancouver Island Center, Victoria, that offers participation in the program to patients in Victoria and Nanaimo. The TTR works with other banks and expert translational research groups in BC, to create expanded capacity for collection and opportunities for research access to tissue resources. The TTR operates under the management and oversight of the director, a scientific advisory board, and the UBC BCCA Research Ethics Board. The TTR operates within organizational policies and a commitment to protection of donor privacy that is embodied in all standard operating procedures and aspects of the repository. The TTR is also a founding member and contributor to the development of provincial (BC BioLibrary) and national (CTRNet) initiatives to promote biobanking.

Proper citation: British Columbia Tumour Tissue Repository (RRID:SCR_004597) Copy   

•   Source: SciCrunch Registry

https://moffitt.org/research-science/shared-resources/tissue/

A central tissue repository at Moffitt specializing in protocol-driven human tissue collection, storage, processing and dissemination. Tissue Core provides investigators with access to high quality, well-annotated human specimens obtained from representative of the patient populations. The advent of powerful molecular technologies has opened the door to developing more effective treatments of patients with cancer. Access to high quality specimens with associated clinical, treatment, recurrence outcome data will be critical to developing and validating the tests needed for diagnosis and prediction of response to therapy. Since its commencement in 1993, the Tissue Core has collected more than 8,000 cases of human liquid cancers and solid primary and metastatic tumors both malignant and benign with adjacent normal, from variety of sites and diagnoses. Collected samples are mostly remnant tissues obtained from patients undergoing therapeutic surgical procedures at the Center. The core also ensures tissue release compliance with USF-IRB and Privacy Board recommendations. * Protocol driven sample collection, processing and distribution * Collection of sample and patient demographic information. * Nucleic acid extractions from tissue sections, FNA, core biopsies blood and bone marrow. * Histology services: H&E slides, staining, sectioning, paraffin blocks, OCT blocks, sample microdissection * WBC, plasma and serum isolation. * Project development and support: Facility staff provides advice and guidance to researchers.

Proper citation: Moffitt Cancer Center Tissue Core (RRID:SCR_004406) Copy   

•   Source: SciCrunch Registry

http://www.cnio.es/ES/grupos/plantillas/presentacion.asp?grupo=50004308

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 29, 2016. The need to use human neoplastic tissue under ideal conditions is currently of particular importance due to the development molecular pathology techniques that allow large-scale studies of genetic expression that are also of clinical significance. The Tumour Bank Network (TBN), instigated and coordinated by the Molecular Pathology Programme (MMP) aims to respond to this need by the promoting of Tumour Banks in Spanish hospitals. This will be achieved through the application of homogeneous procedures for the collection, processing and storage of neoplastic and normal tissue samples in such a way as to make molecular studies possible, avoiding that avoid the intrinsic bias of multi-centre studies possible. These Hospital Tumour Banks are based within the Pathology Departments of the collaborating Hospitals, that are interconnected through a computer-based network. In this way, each Centre''s tissue remains in the Hospital itself, thereby playing a key role in the development of the welfare, teaching and research activities within the Hospital. At the same time, it represents a tool to encourage of multi-hospital cancer research and of cooperation between basic and clinical researchers, constituting important collaboration between biomedical disciplines. The design does not correspond to a Central Tumour Bank, but that of a cooperative and coordinated Network of Hospital Banks, based on simple, homogeneous and optimal tissue treatment protocols. This Network is promoted by the Centro Nacional de Investigaciones Oncologicas (CNIO), which thereby undertakes the work of coordinating the network, using and maintaining the database, adhering to quality control. The aim of the CNIO's TBN is to acquire neoplastic and control non-neoplastic material of all types of malignant neoplasias, in the form of tissue fixed in formalin and paraffin embedded, of samples that are unfixed or frozen according to conventional methods as set out in Annexe 1 and even, exceptionally as fresh tissue. When other types of samples are required to carry out a specific project, the central office of the TBN will draw up a protocol with the group leading the project for the collection and maintenance of the tissue and clinicopathological data required for the proposed research. These protocols will be disseminated among the Associated Hospitals in order to gather the previously agreed number cases. Basic data surrounding the processing and preservation conditions for each case will be sent to the central office of the Bank, which under no circumstances will reveal the identity of the patient. Any Spanish cancer research team will be able to request tissue from the Tissue Bank Network. Absolute priority will be afforded to projects whose principal researcher belongs to one of the Associated Centres of the TNB, to other institutions with special agreements concerning the exchange of samples, and to the CNIO's researchers.

Proper citation: Spanish National Tumour Bank Network (RRID:SCR_008707) Copy   

•   Source: SciCrunch Registry

http://www.rbta.es/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 16, 2013. Located in Spain, the Andalusian Regional Tumour Bank is a regional tumor bank. In the last decades cancer knowledge is growing exponentially due human genome knowledge and technological advantages. However, this disease is the biggest problem of health in Europe, with more than 2,5 million new cases per year. The diagnosis and treatment of cancer is now allowing to identify the characteristics that the disease has on each person. The next step is meant to be a great revolution in the treatment of cancer. This scientific development is dependent on the availability of human tumour samples preserved in demanding conditions. Current technology requires the availability of tissue morphological and molecular conditions similar to those that had the sample before being removed. Tumor banks are responsible for these new quality requirements to foster the development of research and health care of patients.

Proper citation: Andalusian Regional Tumour Bank (RRID:SCR_004885) Copy   

•   Source: SciCrunch Registry

http://www.bumc.bu.edu/busm-pathology/pathology-core-services/biospecimen-archive-research-core-barc/

Biospecimen repository of normal and diseased human material from a variety of tissues and conditions along with clinical annotation. Both frozen aliquots and paraffin embedded tissue are available. Biospecimens are available to qualified researchers with IRB approval. * Preliminary inquires please contact Cheryl Spencer at cheryl.spencer (at) bmc.org

Proper citation: Boston University Biospecimen Archive Research Core (RRID:SCR_005363) Copy   

•   Source: SciCrunch Registry

http://www.einstein.yu.edu/centers/ictr/

Patient-derived specimens are essential to research in genomics, proteomics, and biomarkers. We provide banking for biological fluid and tissue specimens as well as human DNA and RNA. We provide secure archival sample storage as well as clinically-annotated specimen biobanks for defined research projects. The core serves the human research blood and tissue banking needs of clinical and translational researchers. Samples can be banked by an individual PI or by a consortium of investigators. All samples are tracked and archived using a secure tracking database, the Einstein-Montefiore Bio-Repository Databank (EM-BRED), http://informatics30.aecom.yu.edu/em-bred/default.aspx. EM-BRED provides qualified investigators with a solution to securely link patient specimens to clinical and pathological data. It consists of a user-friendly query engine that allows for comprehensive specimen search, and ultimately to build clinical annotations of relevance. The facility works under the best practices set out by NCI and ISBER (2006) for collection, storage, and retrieval of human biological materials for research.

Proper citation: Einstein-Montefiore Institute for Clinical and Translational Research Biorepository (RRID:SCR_005297) Copy   

•   Source: SciCrunch Registry

http://pstiing.icr.ac.uk/

A publicly accessible knowledgebase about protein-protein, protein-lipid, protein-small molecules, ligand-receptor interactions, receptor-cell type information, transcriptional regulatory and signal transduction modules relevant to inflammation, cell migration and tumourigenesis. It integrates in-house curated information from the literature, biochemical experiments, functional assays and in vivo studies, with publicly available information from multiple and diverse sources across human, rat, mouse, fly, worm and yeast. The knowledgebase allowing users to search and to dynamically generate visual representations of protein-protein interactions and transcriptional regulatory networks. Signalling and transcriptional modules can also be displayed singly or in combination. This allow users to identify important "cross-talks" between signalling modules via connections with key components or "hubs". The knowledgebase will facilitate a "systems-wide" understanding across many protein, signalling and transcriptional regulatory networks triggered by multiple environmental cues, and also serve as a platform for future efforts to computationally and mathematically model the system behavior of inflammatory processes and tumourigenesis.

Proper citation: pSTIING (RRID:SCR_002045) Copy   

•   Source: SciCrunch Registry

http://neurosurgery.ucsf.edu/index.php/research_tissue_bank.html

The Tissue Bank began collecting tissue from neurosurgical operations in 1978 and has established an organized repository of characterized tissues that have been collected and maintained in a manner useful for a wide range of studies. Copies of each patient''s consent to donate their tissue for research are maintained in a secure area of the Tissue Bank. Clinical data from each case are logged into a secured computer data base. Tissue received into the Tissue Bank is catalogued and referenced by a consecutive numbering system in order to maintain patients'' confidentiality. We have established a complete histology service including tissue processing, embedding, sectioning and H&E staining for fixed tissues, in addition to creating and staining frozen sections. This facility enables the Tissue Bank to support research needs for fixed samples from animal model experiments, to fulfill requests for paraffin sections from diagnostic samples and to provide frozen sections for histologic review.

Proper citation: UCSF Brain Tumor Tissue Bank (RRID:SCR_006439) Copy   

•   Source: SciCrunch Registry

http://compbio.bccrc.ca/software/mutationseq/

A software suite using feature-based classifiers for somatic mutation prediction from paired tumour/normal next-generation sequencing data. mutationSeq has the advantages of integrating different features (e.g., base qualities, mapping qualities, strand bias, and tailed distance features), and validated somatic mutations to make predictions. Given paired normal/tumour bam files, mutationSeq will output the probability of each candidate site being somatic.

Proper citation: mutationSeq (RRID:SCR_006815) Copy   

•   Source: SciCrunch Registry

https://github.com/Illumina/strelka/

Software for somatic single nucleotide variant (SNV) and small indel detection from sequencing data of matched tumor-normal samples. Strelka2 germline and somatic small variant caller.

Proper citation: Strelka2 (RRID:SCR_005109) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/ibsr

Data set of manually-guided expert segmentation results along with magnetic resonance brain image data. Its purpose is to encourage the development and evaluation of segmentation methods by providing raw test and image data, human expert segmentation results, and methods for comparing segmentation results. Please see the MediaWiki for more information. This repository is meant to contain standard test image data sets which will permit a standardized mechanism for evaluation of the sensitivity of a given analysis method to signal to noise ratio, contrast to noise ratio, shape complexity, degree of partial volume effect, etc. This capability is felt to be essential to further development in the field since many published algorithms tend to only operate successfully under a narrow range of conditions which may not extend to those experienced under the typical clinical imaging setting. This repository is also meant to describe and discuss methods for the comparison of results.

Proper citation: Internet Brain Segmentation Repository (RRID:SCR_001994) Copy   

•   Source: SciCrunch Registry

http://ranchobiosciences.com/gse4922/

Curated data set of a study that investigated the expression profiles of 347 primary invasive breast tumors on Affymetrix microarrays. Three separate breast cancer cohorts were analyzed: 1) Uppsala (n=249), 2) Stockholm (n=58), 3) Singapore (n=40). The Uppsala and Singapore data can be accessed in GSE4922. The Stockholm cohort data can be accessed at GEO Series GSE1456.

Proper citation: GSE4922 (RRID:SCR_003557) Copy   

•   Source: SciCrunch Registry

http://www.broadinstitute.org/science/programs/genome-biology/computational-rd/somaticcall-manual

Software program that finds single-base differences (substitutions) between sequence data from tumor and matched normal samples. It is designed to be highly stringent, so as to achieve a low false positive rate. It takes as input a BAM file for each sample, and produces as output a list of differences (somatic mutations). Note: This software package is no longer supported and information on this page is provided for archival purposes only.

Proper citation: SomaticCall (RRID:SCR_001196) Copy   

•   Source: SciCrunch Registry

http://patchwork.r-forge.r-project.org/

Software tool for analyzing and visualizing allele-specific copy numbers and loss-of-heterozygosity in cancer genomes. The data input is in the format of whole-genome sequencing data which enables characterization of genomic alterations ranging in size from point mutations to entire chromosomes. High quality results are obtained even if samples have low coverage, ~4x, low tumor cell content or are aneuploid. Patchwork takes BAM files as input whereas PatchworkCG takes input from CompleteGenomics files. TAPS performs the same analysis as Patchwork but for microarray data.

Proper citation: Patchwork (RRID:SCR_000072) Copy   

•   Source: SciCrunch Registry

http://www.oncotest.com/

A contract research organization (CRO) specializing in preclinical oncology services. As a pioneer in the field of patient derived tumor xenografts (PDX), they provide tailored solutions to the problems faced by preclinical oncology researchers. They assist with the identification of the best drug candidates and the validation of their targets and deliver in-depth bioinformatics analyses, laying the groundwork for the successful planning of clinical trials. Their diverse tumor model collection enables them to recommend the right assays and models to answer their customers' questions. Their AAALAC accredited facilities with IVC system, separate model development unit, large cage capacity of over 14,500 mice and proprietary electronic measurement system with an integrated database and by continuously maintaining important PDX models in mice, they are able to provide the highest standard of testing within a reasonable timeframe.

Proper citation: Oncotest (RRID:SCR_000489) Copy   

•   Source: SciCrunch Registry

http://sourceforge.net/projects/variantmaster/

Software program that extracts causative variants in familial and sporadic genetic diseases. The algorithm takes into account predicted variants (SNPs and indels) in affected individuals or tumor samples and utilizes the row (BAM) data to robustly estimate the conditional probability of segregation in a family, as well as the probability of it being de novo or somatic. In familial cases, various modes of inheritance are considered: X-linked, autosomal dominant, and recessive (homozygosity or compound heterozygosity). Moreover, it integrates phenotypes and genotypes, and employs Annovar to produce additional information as allelic frequencies in general population and damaging scores.

Proper citation: VariantMaster (RRID:SCR_000569) Copy   

•   Source: SciCrunch Registry

https://github.com/ding-lab/msisensor

A C++ software program for automatically detecting somatic and germline variants at microsatellite regions. It computes length distributions of microsatellites per site in paired tumor and normal sequence data, subsequently using these to statistically compare observed distributions in both samples.

Proper citation: MSIsensor (RRID:SCR_006418) Copy   

•   Source: SciCrunch Registry

http://bioinf.wehi.edu.au/socrates/

Software for detecting genomic rearrangements in tumors that utilizes only split-read data. It features single nucleotide resolution, high sensitivity, and high specificity in simulated data. It takes advantage of parallelism for efficient use of resources.

Proper citation: Socrates (RRID:SCR_006411) Copy   

•   Source: SciCrunch Registry

http://bioinformatics.oxfordjournals.org/content/early/2014/01/02/bioinformatics.btt759.abstract?sid=e62f3c2b-26dc-428b-ba24-99e92a277d77

Statistical software to estimate tumor purity, ploidy and absolute copy numbers from next generation sequencing data.

Proper citation: AbsCN-seq (RRID:SCR_006409) Copy   

•   Source: SciCrunch Registry

http://www.proteinatlas.org/

Open access resource for human proteins. Used to search for specific genes or proteins or explore different resources, each focusing on particular aspect of the genome-wide analysis of the human proteins: Tissue, Brain, Single Cell, Subcellular, Cancer, Blood, Cell line, Structure and Interaction. Swedish-based program to map all human proteins in cells, tissues, and organs using integration of various omics technologies, including antibody-based imaging, mass spectrometry-based proteomics, transcriptomics, and systems biology. All the data in the knowledge resource is open access to allow scientists both in academia and industry to freely access the data for exploration of the human proteome.

Proper citation: The Human Protein Atlas (RRID:SCR_006710) Copy   

•   Source: SciCrunch Registry