Tissue banking, bioinformatics, and electronic medical records: the front-end requirements for personalized medicine

Integrative multi-omics and systems bioinformatics in translational neuroscience: A data mining perspective

Bioinformatic analysis of large and complex omics datasets has become increasingly useful in modern day biology by providing a great depth of information, with its application to neuroscience termed neuroinformatics. Data mining of omics datasets has enabled the generation of new hypotheses based on differentially regulated biological molecules associated with disease mechanisms, which can be tested experimentally for improved diagnostic and therapeutic targeting of neurodegenerative diseases. Importantly, integrating multi-omics data using a systems bioinformatics approach will advance the understanding of the layered and interactive network of biological regulation that exchanges systemic knowledge to facilitate the development of a comprehensive human brain profile. In this review, we first summarize data mining studies utilizing datasets from the individual type of omics analysis, including epigenetics/epigenomics, transcriptomics, proteomics, metabolomics, lipidomics, and spatial omics, pertaining to Alzheimer's disease, Parkinson's disease, and multiple sclerosis. We then discuss multi-omics integration approaches, including independent biological integration and unsupervised integration methods, for more intuitive and informative interpretation of the biological data obtained across different omics layers. We further assess studies that integrate multi-omics in data mining which provide convoluted biological insights and offer proof-of-concept proposition towards systems bioinformatics in the reconstruction of brain networks. Finally, we recommend a combination of high dimensional bioinformatics analysis with experimental validation to achieve translational neuroscience applications including biomarker discovery, therapeutic development, and elucidation of disease mechanisms. We conclude by providing future perspectives and opportunities in applying integrative multi-omics and systems bioinformatics to achieve precision phenotyping of neurodegenerative diseases and towards personalized medicine.

Biobanking: How Oncology Nurses Can Contribute to Its Use

Biobanking is one of the most valuable tools in precision medicine. The ability of scientists to sequence tumors, blood, and normal tissue obtained from biorepositories has defined efficacious tumor targeting and a much better understanding of cancer pathology pathways. However, these biorepositories require a great deal of effort to establish and maintain. Oncology nurses are key in helping to bank tissue during routine procedures as well as complex surgeries. Nurses can obtain informed consent from patients and coordinate the banking of samples in a timely manner to ensure sample quality. Oncology nurses play an important role in informing patients of their biobanking options and connecting patients with the appropriate team for their biobanking needs.

Role of Biobanks for Cancer Research and Precision Medicine in Hepatocellular Carcinoma

INTRODUCTION

Hepatocellular carcinoma (HCC) is a highly complex and deadly cancer. There is an urgent need for new and effective treatment modalities. Since the primary goal in the management of cancer is to cure and improve survival, personalized therapy can increase survival, reduce mortality rates, and improve quality of life. Biobanks hold potential in leading to breakthroughs in biomedical research and precision medicine (PM). They serve as a biorepository, collecting, processing, storing, and supplying specimens and relevant data for basic, translational, and clinical research.

OBJECTIVE

We aimed to highlight the fundamental role of biobanks, harboring high quality, sustainable collections of patient samples in adequate size and variability, for developing diagnostic, prognostic, and predictive biomarkers to develop and PM approaches in the management of HCC.

METHOD

We obtained information from previously published articles and BBMRI directory.

RESULTS AND CONCLUSION

Biobanking of high-quality biospecimens along with patient clinical information provides a fundamental scientific infrastructure for basic, translational, and clinical research. Biobanks that control and eliminate pre-analytical variability of biospecimens, provide a platform to identify reliable biomarkers for the application of PM. We believe, establishing HCC biobanks will empower to underpin molecular mechanisms of HCC and generate strategies for PM. Thus, first, we will review current therapy approaches in HCC care. Then, we will summarize challenges in HCC management. Lastly, we will focus on the best practices for establishing HCC biobanking to support research, translational medicine in the light of new experimental research conducted with the aim of delivering PM for HCC patients.

Results of the Seventh Scientific Workshop of ECCO: Precision Medicine in IBD-What, Why, and How

Many diseases that affect modern humans fall in the category of complex diseases, thus called because they result from a combination of multiple aetiological and pathogenic factors. Regardless of the organ or system affected, complex diseases present major challenges in diagnosis, classification, and management. Current forms of therapy are usually applied in an indiscriminate fashion based on clinical information, but even the most advanced drugs only benefit a limited number of patients and to a variable and unpredictable degree. This 'one measure does not fit all' situation has spurred the notion that therapy for complex disease should be tailored to individual patients or groups of patients, giving rise to the notion of 'precision medicine' [PM]. Inflammatory bowel disease [IBD] is a prototypical complex disease where the need for PM has become increasingly clear. This prompted the European Crohn's and Colitis Organisation to focus the Seventh Scientific Workshop on this emerging theme. The articles in this special issue of the Journal address the various complementary aspects of PM in IBD, including what PM is; why it is needed and how it can be used; how PM can contribute to prediction and prevention of IBD; how IBD PM can aid in prognosis and improve response to therapy; and the challenges and future directions of PM in IBD. This first article of this series is structured on three simple concepts [what, why, and how] and addresses the definition of PM, discusses the rationale for the need of PM in IBD, and outlines the methodology required to implement PM in IBD in a correct and clinically meaningful way.

Identification of PLA2G7 as a novel biomarker of diffuse large B cell lymphoma

BACKGROUND

Diffuse large B-cell lymphoma is the most common form of non-Hodgkin lymphoma globally, and patients with relapsed or refractory DLBCL typically experience poor long-term outcomes.

METHODS

Differentially expressed genes associated with DLBCL were identified using two GEO datasets in an effort to detect novel diagnostic or prognostic biomarkers of this cancer type, after which receiver operating characteristic curve analyses were conducted. Genes associated with DLBCL patient prognosis were additionally identified via WCGNA analyses of the TCGA database. The expression of PLA2G7 in DLBCL patient clinical samples was further assessed, and the functional role of this gene in DLBCL was assessed through in vitro and bioinformatics analyses.

RESULTS

DLBCL-related DEGs were found to be most closely associated with immune responses, cell proliferation, and angiogenesis. WCGNA analyses revealed that PLA2G7 exhibited prognostic value in DLBCL patients, and the upregulation of this gene in DLBCL patient samples was subsequently validated. PLA2G7 was also found to be closely linked to tumor microenvironmental composition such that DLBCL patients expressing higher levels of this gene exhibited high local monocyte and gamma delta T cell levels. In vitro experiments also revealed that knocking down PLA2G7 expression was sufficient to impair the migration and proliferation of DLBCL cells while promoting their apoptotic death. Furthmore, the specific inhibitor of PLA2G7, darapladib, could noticeably restrained the DLBCL cell viability and induced apoptosis.

CONCLUSIONS

PLA2G7 may represent an important diagnostic, prognostic, or therapeutic biomarker in patients with DLBCL.

Informatics Management of Tumor Specimens in the Era of Big Data: Challenges and Solutions

Biomedical data bear the potential to facilitate personalized diagnosis and precision treatment. In the era of Big Data, high-quality annotation of human specimens has become the primary mission of biobankers, especially for tumor biobanks with large amounts of "omics" and clinical data. However, the lack of agreed-upon standardization and the gap among heterogeneous databases make information application and communication a major challenge. International efforts are underway to develop national projects on informatics management. The aim of this review is to provide references in specimen annotation to regulate and take full advantage of biological and biomedical information. First, critical data categories that are vital for specimen applications, including sample attributes, clinical data, preanalytical variations, and analytical records, are systematically listed for subsequent data mining. Second, current standards and guidelines related to biospecimen information are reviewed, and proper standards for tumor biobanks are recommended. In particular, commonly-used approaches and functionalities of data management are summarized and discussed. This review highlights the importance of informatics management of tumor specimens, defines critical data types, recommends data standards, and presents the methodologies of data harmonization for biobankers to reach high quality annotation of biospecimens.

Man's best friend in life and death: scientific perspectives and challenges of dog brain banking

Biobanking refers to the systematic collection, storage, and distribution of pre- or post-mortem biological samples derived from volunteer donors. The demand for high-quality human specimens is clearly demonstrated by the number of newly emerging biobanking facilities and large international collaborative networks. Several animal species are relevant today in medical research; therefore, similar initiatives in comparative physiology could be fruitful. Dogs, in particular, are gaining increasing attention in translational research on complex phenomena, like aging, cancer, and neurodegenerative diseases. Therefore, biobanks gathering and storing dog biological materials together with related data could play a vital role in translational and veterinary research projects. To achieve these aims, a canine biobank should meet the same standards in sample quality and data management as human biobanks and should rely on well-designed collaborative networks between different professionals and dog owners. While efforts to create dog biobanks could face similar financial and technical challenges as their human counterparts, they can widen the spectrum of successful collaborative initiatives towards a better picture of dogs’ physiology, disease, evolution, and translational potential. In this review, we provide an overview about the current state of dog biobanking and introduce the “Canine Brain and Tissue Bank” (CBTB)—a new, large-scale collaborative endeavor in the field.

The OncoLifeS data-biobank for oncology: a comprehensive repository of clinical data, biological samples, and the patient's perspective

Background

Understanding cancer heterogeneity, its temporal evolution over time, and the outcomes of guided treatment depend on accurate data collection in a context of routine clinical care. We have developed a hospital-based data-biobank for oncology, entitled OncoLifeS (Oncological Life Study: Living well as a cancer survivor), that links routine clinical data with preserved biological specimens and quality of life assessments. The aim of this study is to describe the organization and development of a data-biobank for cancer research.

Results

We have enrolled 3704 patients aged ≥ 18 years diagnosed with cancer, of which 45 with hereditary breast-ovarian cancer (70% participation rate) as of October 24th, 2019. The average age is 63.6 ± 14.2 years and 1892 (51.1%) are female. The following data are collected: clinical and treatment details, comorbidities, lifestyle, radiological and pathological findings, and long-term outcomes. We also collect and store various biomaterials of patients as well as information from quality of life assessments.

Conclusion

Embedding a data-biobank in clinical care can ensure the collection of high-quality data. Moreover, the inclusion of longitudinal quality of life data allows us to incorporate patients’ perspectives and inclusion of imaging data provides an opportunity for analyzing raw imaging data using artificial intelligence (AI) methods, thus adding new dimensions to the collected data.

Biomarkers for detection, prognosis and therapeutic assessment of neurological disorders

Neurological disorders have aroused a significant concern among the health scientists globally, as diseases such as Parkinson's, Alzheimer's and dementia lead to disability and people have to live with them throughout the life. Recent evidence suggests that a number of environmental chemicals such as pesticides (paraquat) and metals (lead and aluminum) are also the cause of these diseases and other neurological disorders. Biomarkers can help in detecting the disorder at the preclinical stage, progression of the disease and key metabolomic alterations permitting identification of potential targets for intervention. A number of biomarkers have been proposed for some neurological disorders based on laboratory and clinical studies. In silico approaches have also been used by some investigators. Yet the ideal biomarker, which can help in early detection and follow-up on treatment and identifying the susceptible populations, is not available. An attempt has therefore been made to review the recent advancements of in silico approaches for discovery of biomarkers and their validation. In silico techniques implemented with multi-omics approaches have potential to provide a fast and accurate approach to identify novel biomarkers.

Single-Nucleotide Polymorphism to Associate Cancer Risk

Genetic heterogeneity explains variation in predisposition for cancer. Whole-genome analysis allows risk to be quantified, giving better targeted screening and quantification of the personalized risk posed by environmental factors. Array-based approaches to whole-genome analysis are rapidly being overtaken by next-generation sequencing (NGS). In this review the different platforms currently available for NGS are compared and the opportunities and risks of this approach are discussed: including the informatics packages required and the ethical issues. Methods applicable to the personal genome machine (PGM) are given as an example of workflows.

Introducing Biospecimen Science to Communities: Tools from Two Cities

BACKGROUND

This article describes community-engaged processes employed by two Community Network Program Center (CNPC) sites located in Tampa, Florida, and Buffalo, New York, toward the development of Spanish/English educational products about biobanking and biospecimen research.

METHODS

Each CNPC carried out a community-based participatory research (CBPR) approach that underscored six essential components that moved concepts to a final educational product in a highly participatory fashion. The similar CBPR processes at the two locations focused on the same topic, resulted in different engagement approaches and tools for their respective communities: 1) DVD and brochure toolkit and 2) PowerPoint, group program with audience response system (ARS).

RESULTS

We detail a comparison of methods and applications for using these tools among diverse community groups to advance understandings about genetic and biomedical research technologies.

CONCLUSION

Ultimately, these tools and associated educational efforts emphasize the critical value of co-learning among academic and community members in biobanking and biospecimen research.

Banking Brain Tumor Specimens Using a University Core Facility

Within the past three decades, the significance of banking human cancer tissue for the advancement of cancer research has grown exponentially. The purpose of this article is to detail our experience in collecting brain tumor specimens in collaboration with the University of Miami/Sylvester Tissue Bank Core Facility (UM-TBCF), to ensure the availability of high-quality samples of central nervous system tumor tissue for research. Successful tissue collection begins with obtaining informed consent from patients following institutional IRB and federal HIPAA guidelines, and it needs a well-trained professional staff and continued maintenance of high ethical standards and record keeping. Since starting in 2011, we have successfully banked 225 brain tumor specimens for research. Thus far, the most common tumor histology identified among those specimens has been glioblastoma (22.1%), followed by meningioma (18.1%). The majority of patients were White, non-Hispanics accounting for 45.1% of the patient population; Hispanic/Latinos accounted for 23%, and Black/African Americans accounted for 14%, which represent the particular population of the State of Florida according to the 2010 census data. The most common tumors found in each subgroup were as follows: Black/African American, glioblastoma and meningioma; Hispanic, metastasis and glioblastoma; White, glioblastoma and meningioma. The UM-TBCF is a valuable repository, offering high-quality tumor samples from a unique patient population.

From Molecules to Patients: The Clinical Applications of Translational Bioinformatics

OBJECTIVE

In order to realize the promise of personalized medicine, Translational Bioinformatics (TBI) research will need to continue to address implementation issues across the clinical spectrum. In this review, we aim to evaluate the expanding field of TBI towards clinical applications, and define common themes and current gaps in order to motivate future research.

METHODS

Here we present the state-of-the-art of clinical implementation of TBI-based tools and resources. Our thematic analyses of a targeted literature search of recent TBI-related articles ranged across topics in genomics, data management, hypothesis generation, molecular epidemiology, diagnostics, therapeutics and personalized medicine.

RESULTS

Open areas of clinically-relevant TBI research identified in this review include developing data standards and best practices, publicly available resources, integrative systemslevel approaches, user-friendly tools for clinical support, cloud computing solutions, emerging technologies and means to address pressing legal, ethical and social issues.

CONCLUSIONS

There is a need for further research bridging the gap from foundational TBI-based theories and methodologies to clinical implementation. We have organized the topic themes presented in this review into four conceptual foci - domain analyses, knowledge engineering, computational architectures and computation methods alongside three stages of knowledge development in order to orient future TBI efforts to accelerate the goals of personalized medicine.

Introducing Biospecimen Science to Communities: Tools from Two Cities

BACKGROUND

This article describes community-engaged processes employed by two Community Network Program Center (CNPC) sites located in Tampa, Florida, and Buffalo, New York, toward the development of Spanish/English educational products about biobanking and biospecimen research.

METHODS

Each CNPC carried out a community-based participatory research (CBPR) approach that underscored six essential components that moved concepts to a final educational product in a highly participatory fashion. The similar CBPR processes at the two locations focused on the same topic, resulted in different engagement approaches and tools for their respective communities: 1) DVD and brochure toolkit and 2) PowerPoint, group program with audience response system (ARS).

RESULTS

We detail a comparison of methods and applications for using these tools among diverse community groups to advance understandings about genetic and biomedical research technologies.

CONCLUSION

Ultimately, these tools and associated educational efforts emphasize the critical value of co-learning among academic and community members in biobanking and biospecimen research.

Genetic Testing and Tissue Banking for Personalized Oncology: Analytical and Institutional Factors

Personalized oncology, or more aptly precision oncogenomics, refers to the identification and implementation of clinically actionable targets tailored to an individual patient's cancer genomic information. Banking of human tissue and other biospecimens establishes a framework to extract and collect the data essential to our understanding of disease pathogenesis and treatment. Cancer cooperative groups in the United States have led the way in establishing robust biospecimen collection mechanisms to facilitate translational research, and combined with technological advances in molecular testing, tissue banking has expanded from its traditional base in academic research and is assuming an increasingly pivotal role in directing the clinical care of cancer patients. Comprehensive screening of tumors by DNA sequencing and the ability to mine and interpret these large data sets from well-organized tissue banks have defined molecular subtypes of cancer. Such stratification by genomic criteria has revolutionized our perspectives on cancer diagnosis and treatment, offering insight into prognosis, progression, and susceptibility or resistance to known therapeutic agents. In turn, this has enabled clinicians to offer treatments tailored to patients that can greatly improve their chances of survival. Unique challenges and opportunities accompany the rapidly evolving interplay between tissue banking and genomic sequencing, and are the driving forces underlying the revolution in precision medicine. Molecular testing and precision medicine clinical trials are now becoming the major thrust behind the cooperative groups' clinical research efforts.

Clinical decision support systems for improving diagnostic accuracy and achieving precision medicine

As research laboratories and clinics collaborate to achieve precision medicine, both communities are required to understand mandated electronic health/medical record (EHR/EMR) initiatives that will be fully implemented in all clinics in the United States by 2015. Stakeholders will need to evaluate current record keeping practices and optimize and standardize methodologies to capture nearly all information in digital format. Collaborative efforts from academic and industry sectors are crucial to achieving higher efficacy in patient care while minimizing costs. Currently existing digitized data and information are present in multiple formats and are largely unstructured. In the absence of a universally accepted management system, departments and institutions continue to generate silos of information. As a result, invaluable and newly discovered knowledge is difficult to access. To accelerate biomedical research and reduce healthcare costs, clinical and bioinformatics systems must employ common data elements to create structured annotation forms enabling laboratories and clinics to capture sharable data in real time. Conversion of these datasets to knowable information should be a routine institutionalized process. New scientific knowledge and clinical discoveries can be shared via integrated knowledge environments defined by flexible data models and extensive use of standards, ontologies, vocabularies, and thesauri. In the clinical setting, aggregated knowledge must be displayed in user-friendly formats so that physicians, non-technical laboratory personnel, nurses, data/research coordinators, and end-users can enter data, access information, and understand the output. The effort to connect astronomical numbers of data points, including ‘-omics’-based molecular data, individual genome sequences, experimental data, patient clinical phenotypes, and follow-up data is a monumental task. Roadblocks to this vision of integration and interoperability include ethical, legal, and logistical concerns. Ensuring data security and protection of patient rights while simultaneously facilitating standardization is paramount to maintaining public support. The capabilities of supercomputing need to be applied strategically. A standardized, methodological implementation must be applied to developed artificial intelligence systems with the ability to integrate data and information into clinically relevant knowledge. Ultimately, the integration of bioinformatics and clinical data in a clinical decision support system promises precision medicine and cost effective and personalized patient care.

Biobanking for Personalized Medicine

A biobank is an entity that collects, processes, stores, and distributes biospecimens and relevant data for use in basic, translational, and clinical research. Biobanking of high-quality human biospecimens such as tissue, blood and other bodily fluids along with associated patient clinical information provides a fundamental scientific infrastructure for personalized medicine. Identification of biomarkers that are specifically associated with particular medical conditions such as cancer, cardiovascular disease and neurological disorders are useful for early detection, prevention, and treatment of the diseases. The ability to determine individual tumor biomarkers and to use those biomarkers for disease diagnosis, prognosis and prediction of response to therapy is having a very significant impact on personalized medicine and is rapidly changing the way clinical care is conducted. As a critical requirement for personalized medicine is the availability of a large collection of patient samples with well annotated patient clinical and pathological data, biobanks thus play an important role in personalized medicine advancement. The goal of this chapter is to explore the role of biobanks in personalized medicine and discuss specific needs regarding biobank development for translational and clinical research, especially for personalized medicine advancement.

Engaging diverse populations about biospecimen donation for cancer research

Clinical research increasingly relies upon the availability of appropriate genetic materials; however, the proportion of biospecimens from racial/ethnic minority patients and healthy controls are underrepresented, which preclude equitable research across all patient groups for cancer treatment. National Cancer Institute-funded Community Network Program Centers in California, Florida, and New York collaborated with local community partners to conduct three independent formative research studies with diverse (African American, Asian American, Hispanic, and White) participants to explore their knowledge, attitudes, and beliefs about biobanking, and their experiences with the donation of biospecimens. Our findings demonstrated similarities in overall low knowledge and understanding about the use of biospecimens for research. This was exacerbated for non-English speakers. Racial and ethnic groups differed with regard to a number of factors that are obstacles for participation, e.g., continuing medical mistrust (African Americans), lack of benefit (Hispanics), apprehension about the physical toll of donating (Vietnamese), usage of biospecimen for research (Hmong and Chinese), and suspicion of exploitation by corporate entities (Whites). However, participants uniformly reported general interest and willingness to participate in biobanking for altruistic purposes, particularly to benefit future generations. This interest was framed with a strong admonition that donations should be accompanied by transparency about study sponsorship and ownership, distribution and use of biospecimens, and study information that fit participants' backgrounds and experiences. This cross-cultural regional analysis offers significant insights into the similarities and variations in opinions and perceptions about biobanking and the collection of biospecimens for use in cancer research.

Polymalic acid-based nano biopolymers for targeting of multiple tumor markers: an opportunity for personalized medicine?

Tumors with similar grade and morphology often respond differently to the same treatment because of variations in molecular profiling. To account for this diversity, personalized medicine is developed for silencing malignancy associated genes. Nano drugs fit these needs by targeting tumor and delivering antisense oligonucleotides for silencing of genes. As drugs for the treatment are often administered repeatedly, absence of toxicity and negligible immune response are desirable. In the example presented here, a nano medicine is synthesized from the biodegradable, non-toxic and non-immunogenic platform polymalic acid by controlled chemical ligation of antisense oligonucleotides and tumor targeting molecules. The synthesis and treatment is exemplified for human Her2-positive breast cancer using an experimental mouse model. The case can be translated towards synthesis and treatment of other tumors.

Bioinformatics for precision medicine in oncology: principles and application to the SHIVA clinical trial

Precision medicine (PM) requires the delivery of individually adapted medical care based on the genetic characteristics of each patient and his/her tumor. The last decade witnessed the development of high-throughput technologies such as microarrays and next-generation sequencing which paved the way to PM in the field of oncology. While the cost of these technologies decreases, we are facing an exponential increase in the amount of data produced. Our ability to use this information in daily practice relies strongly on the availability of an efficient bioinformatics system that assists in the translation of knowledge from the bench towards molecular targeting and diagnosis. Clinical trials and routine diagnoses constitute different approaches, both requiring a strong bioinformatics environment capable of (i) warranting the integration and the traceability of data, (ii) ensuring the correct processing and analyses of genomic data, and (iii) applying well-defined and reproducible procedures for workflow management and decision-making. To address the issues, a seamless information system was developed at Institut Curie which facilitates the data integration and tracks in real-time the processing of individual samples. Moreover, computational pipelines were developed to identify reliably genomic alterations and mutations from the molecular profiles of each patient. After a rigorous quality control, a meaningful report is delivered to the clinicians and biologists for the therapeutic decision. The complete bioinformatics environment and the key points of its implementation are presented in the context of the SHIVA clinical trial, a multicentric randomized phase II trial comparing targeted therapy based on tumor molecular profiling versus conventional therapy in patients with refractory cancer. The numerous challenges faced in practice during the setting up and the conduct of this trial are discussed as an illustration of PM application.

Translational informatics in personalized medicine: an update for 2014

Many things have changed but much has remained the same as we have seen a dramatic increase in the generation of genetics, genomics and a variety of clinical data leading to increased data density and continued challenges in organizing and managing that data in pursuit of personalized medicine. Simultaneously, we have seen an increase in commercial and open-source solutions, and marked movement toward open sharing of tools and data in public–private partnerships, yet still few examples of traditional companion diagnostics for personalized medicine products. Most encouraging are examples of focused public and private efforts that have resulted in knowledge leading to critical assessment of existing therapies and the development of new therapies. These examples lay highly emulatable informatics foundations for rapid advances in personalized medicine.

Engaging diverse populations about biospecimen donation for cancer research

Clinical research increasingly relies upon the availability of appropriate genetic materials; however, the proportion of biospecimens from racial/ethnic minority patients and healthy controls are underrepresented, which preclude equitable research across all patient groups for cancer treatment. National Cancer Institute-funded Community Network Program Centers in California, Florida, and New York collaborated with local community partners to conduct three independent formative research studies with diverse (African American, Asian American, Hispanic, and White) participants to explore their knowledge, attitudes, and beliefs about biobanking, and their experiences with the donation of biospecimens. Our findings demonstrated similarities in overall low knowledge and understanding about the use of biospecimens for research. This was exacerbated for non-English speakers. Racial and ethnic groups differed with regard to a number of factors that are obstacles for participation, e.g., continuing medical mistrust (African Americans), lack of benefit (Hispanics), apprehension about the physical toll of donating (Vietnamese), usage of biospecimen for research (Hmong and Chinese), and suspicion of exploitation by corporate entities (Whites). However, participants uniformly reported general interest and willingness to participate in biobanking for altruistic purposes, particularly to benefit future generations. This interest was framed with a strong admonition that donations should be accompanied by transparency about study sponsorship and ownership, distribution and use of biospecimens, and study information that fit participants' backgrounds and experiences. This cross-cultural regional analysis offers significant insights into the similarities and variations in opinions and perceptions about biobanking and the collection of biospecimens for use in cancer research.

Intravital biobank and personalized cancer therapy: the correlation with omics

Biobanks have played a decisive role in all aspects of the field of cancer, including pathogenesis, diagnosis, prognosis and treatment. The significance of cancer biobanks is epitomized through the appropriate application of various "-omic" techniques (omics). The mutually motivated relationship between biobanks and omics has intensified the development of cancer research. Human cancer tissues that are maintained in intravital biobanks (or living tissue banks) retain native tumor microenvironment, tissue architecture, hormone responsiveness and cell-to-cell signalling properties. Intravital biobanks replicate the structural complexity and heterogeneity of human cancers, making them an ideal platform for preclinical studies. The application of omics with intravital biobanks renders them more active, which makes it possible for the cancer-related evaluations to be dynamically monitored on a real-time basis. Integrating intravital biobank and modern omics will provide a useful tool for the discovery and development of new drugs or novel therapeutic strategies. More importantly, intravital biobanks may play an essential role in the creation of meaningful patient-tailored therapies as for personalized medicine.

Colorectal Cancer: Basic and Translational Research

BACKGROUND

Colorectal cancer (CRC) still accounts for high mortality and morbidity of cancer patients worldwide. Early detection screening and therapeutic management of CRC are still traditional, with some important progress including cetuximab, microsatellite instability and the concept of CRC intrinsic subtypes.

SUMMARY

Most achievements are derived from translational cancer research. Translational cancer research attempts to better understand the heterogeneity of human cancer and further turn discoveries into benefits for cancer patients. The four basic strategies of translational research can be depicted as (a) biomarker discovery, (b) identification in xenografts, (c) population-based verification and (d) clinical validation.