Topographic analysis of pancreatic cancer by TMA and digital spatial profiling reveals biological complexity with potential therapeutic implications.

Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal human malignancies. Tissue microarrays (TMA) are an established method of high throughput biomarker interrogation in tissues but may not capture histological features of cancer with potential biological relevance. Topographic TMAs (T-TMAs) representing pathophysiological hallmarks of cancer were constructed from representative, retrospective PDAC diagnostic material, including 72 individual core tissue samples. The T-TMA was interrogated with tissue hybridization-based experiments to confirm the accuracy of the topographic sampling, expression of pro-tumourigenic and immune mediators of cancer, totalling more than 750 individual biomarker analyses. A custom designed Next Generation Sequencing (NGS) panel and a spatial distribution-specific transcriptomic evaluation were also employed. The morphological choice of the pathophysiological hallmarks of cancer was confirmed by protein-specific expression. Quantitative analysis identified topography-specific patterns of expression in the IDO/TGF-ß axis; with a heterogeneous relationship of inflammation and desmoplasia across hallmark areas and a general but variable protein and gene expression of c-MET. NGS results highlighted underlying genetic heterogeneity within samples, which may have a confounding influence on the expression of a particular biomarker. T-TMAs, integrated with quantitative biomarker digital scoring, are useful tools to identify hallmark specific expression of biomarkers in pancreatic cancer.

Emergence of nutrigenomics and dietary components as a complementary therapy in cancer prevention.

Cancer is an illness characterized by abnormal cell development and the capability to infiltrate or spread to rest of the body. A tumor is the term for this abnormal growth that develops in solid tissues like an organ, muscle, or bone and can spread to other parts of the body through the blood and lymphatic systems. Nutrition is a critical and immortal environmental component in the development of all living organisms encoding the relationship between a person's nutrition and their genes. Nutrients have the ability to modify gene expression and persuade alterations in DNA and protein molecules which is researched scientifically in nutrigenomics. These interactions have a significant impact on the pharmacokinetic properties of bioactive dietary components as well as their site of action/molecular targets. Nutrigenomics encompasses nutrigenetics, epigenetics, and transcriptomics as well as other "omic" disciplines like proteomics and metabolomics to explain the vast disparities in cancer risk among people with roughly similar life style. Clinical trials and researches have evidenced that alternation of dietary habits is potentially one of the key approaches for reducing cancer risk in an individual. In this article, we will target how nutrigenomics and functional food work as preventive therapy in reducing the risk of cancer.

Immunoglobulin/T Cell Receptor Capture Strategy for Comprehensive Immunogenetics.

In the era of genomic medicine, targeted next generation sequencing strategies (NGS) are becoming increasingly adopted by clinical molecular diagnostic laboratories to identify genetic diagnostic and prognostic biomarkers in hemato-oncology. We describe the EuroClonality-NGS DNA Capture (EuroClonality-NDC) assay, which is designed to simultaneously detect B and T cell clonal rearrangements, translocations, copy number alterations, and sequence variants. The accompanying validated bioinformatics pipeline enables production of an integrated report. The combination of the laboratory protocol and bioinformatics pipeline in the EuroClonality-NDC minimizes the potential for human error, reduces economic costs compared to current molecular testing strategies, and should improve diagnostic outcomes.

Validation of the EuroClonality-NGS DNA capture panel as an integrated genomic tool for lymphoproliferative disorders.

Current diagnostic standards for lymphoproliferative disorders include multiple tests for detection of clonal immunoglobulin (IG) and/or T-cell receptor (TCR) rearrangements, translocations, copy-number alterations (CNAs), and somatic mutations. The EuroClonality-NGS DNA Capture (EuroClonality-NDC) assay was designed as an integrated tool to characterize these alterations by capturing IGH switch regions along with variable, diversity, and joining genes of all IG and TCR loci in addition to clinically relevant genes for CNA and mutation analysis. Diagnostic performance against standard-of-care clinical testing was assessed in a cohort of 280 B- and T-cell malignancies from 10 European laboratories, including 88 formalin-fixed paraffin-embedded samples and 21 reactive lesions. DNA samples were subjected to the EuroClonality-NDC protocol in 7 EuroClonality-NGS laboratories and analyzed using a bespoke bioinformatic pipeline. The EuroClonality-NDC assay detected B-cell clonality in 191 (97%) of 197 B-cell malignancies and T-cell clonality in 71 (97%) of 73 T-cell malignancies. Limit of detection (LOD) for IG/TCR rearrangements was established at 5% using cell line blends. Chromosomal translocations were detected in 145 (95%) of 152 cases known to be positive. CNAs were validated for immunogenetic and oncogenetic regions, highlighting their novel role in confirming clonality in somatically hypermutated cases. Single-nucleotide variant LOD was determined as 4% allele frequency, and an orthogonal validation using 32 samples resulted in 98% concordance. The EuroClonality-NDC assay is a robust tool providing a single end-to-end workflow for simultaneous detection of B- and T-cell clonality, translocations, CNAs, and sequence variants.

Detection of Structural Variants in Circulating Cell-Free DNA from Sarcoma Patients Using Next Generation Sequencing.

Circulating tumour DNA (ctDNA) analysis using next generation sequencing (NGS) is being implemented in clinical practice for treatment stratification and disease monitoring. However, using ctDNA to detect structural variants, a common occurrence in sarcoma, can be challenging. Here, we use a sarcoma-specific targeted NGS panel to identify translocations and copy number variants in a cohort of 12 tissue specimens and matched circulating cell-free DNA (cfDNA) from soft tissue sarcoma patients, including alveolar rhabdomyosarcoma (n = 2), Ewing's Sarcoma (n = 2), synovial sarcoma (n = 2), extraskeletal myxoid chondrosarcoma (n = 1), clear cell sarcoma (n = 1), undifferentiated round cell sarcoma (n = 1), myxoid liposarcoma (n = 1), alveolar soft part cell sarcoma (n = 1) and dedifferentiated liposarcoma (n = 1). Structural variants were detected in 11/12 (91.6%) and 6/12 (50%) of tissue and plasma samples, respectively. Structural variants were detected in cfDNA at variant allele frequencies >0.2% with an average sequencing depth of 1026×. The results from this cohort show clinical potential for using NGS in ctDNA to aid in the diagnosis and clinical monitoring of sarcomas and warrant additional studies in larger cohorts.

Prostate cancer heterogeneity assessment with multi-regional sampling and alignment-free methods.

Combining alignment-free methods for phylogenetic analysis with multi-regional sampling using next-generation sequencing can provide an assessment of intra-patient tumour heterogeneity. From multi-regional sampling divergent branching, we validated two different lesions within a patient's prostate. Where multi-regional sampling has not been used, a single sample from one of these areas could misguide as to which drugs or therapies would best benefit this patient, due to the fact these tumours appear to be genetically different. This application has the power to render, in a fraction of the time used by other approaches, intra-patient heterogeneity and decipher aberrant biomarkers. Another alignment-free method for calling single-nucleotide variants from raw next-generation sequencing samples has determined possible variants and genomic locations that may be able to characterize the differences between the two main branching patterns. Alignment-free approaches have been applied to relevant clinical multi-regional samples and may be considered as a valuable option for comparing and determining heterogeneity to help deliver personalized medicine through more robust efforts in identifying targetable pathways and therapeutic strategies. Our study highlights the application these tools could have on patient-aligned treatment indications.

Inulin as a Delivery Vehicle for Targeting Colon-Specific Cancer.

Natural polysaccharides, as well as biopolymers, are now days widely developed for targeting colon cancer using various drug delivery systems. Currently, healing conformations are being explored that can efficiently play a multipurpose role. Owing to the capability of extravagance colonic diseases with the least adverse effects, biopolymers for site specific colon delivery have developed an increased curiosity over the past decades. Inulin (INU) was explored for its probable application as an entrapment material concerning its degradation by enzymes in the colonic microflora and its drug release behavior in a sustained and controlled manner. INU is a polysaccharide and it consists of 2 to 1 linkage having an extensive array of beneficial uses such as a carrier for delivery of therapeutic agents as an indicative/investigative utensil or as a dietary fiber with added well-being aids. In the main, limited research, as well as information, is available on the delivery of therapeutic agents using inulin specifically for colon cancer because of its capability to subsist in the stomach's acidic medium. This exceptional steadiness and robustness properties are exploited in numerous patterns to target drugs securely for the management of colonic cancer, where they effectively act and kills colonic tumor cells easily. In this review article, recent efforts and inulin-based nano-technological approaches for colon cancer targeting are presented and discussed.

A novel next generation sequencing approach to improve sarcoma diagnosis.

Sarcoma is a rare disease affecting both bone and connective tissue and with over 100 pathologic entities, differential diagnosis can be difficult. Complementing immune-histological diagnosis with current ancillary diagnostic techniques, including FISH and RT-PCR, can lead to inconclusive results in a significant number of cases. We describe here the design and validation of a novel sequencing tool to improve sarcoma diagnosis. A NGS DNA capture panel containing probes for 87 fusion genes and 7 genes with frequent copy number changes was designed and optimized. A cohort of 113 DNA samples extracted from soft-tissue and bone sarcoma FFPE material with clinical FISH and/or RT-PCR results positive for either a translocation or gene amplification was used for validation of the NGS method. Sarcoma-specific translocations or gene amplifications were confirmed in 110 out of 113 cases using FISH and/or RT-PCR as gold-standard. MDM2/CDK4 amplification and a total of 25 distinct fusion genes were identified in this cohort of patients using the NGS approach. Overall, the sensitivity of the NGS panel is 97% with a specificity of 100 and 0% failure rate. Targeted NGS appears to be a feasible and cost-effective approach to improve sarcoma subtype diagnosis with the ability to screen for a wide range of genetic aberrations in one test.

Genomic Evaluation of Multiparametric Magnetic Resonance Imaging-visible and -nonvisible Lesions in Clinically Localised Prostate Cancer.

BACKGROUND: The prostate cancer (PCa) diagnostic pathway is undergoing a radical change with the introduction of multiparametric magnetic resonance imaging (mpMRI), genomic testing, and different prostate biopsy techniques. It has been proposed that these tests should be used in a sequential manner to optimise risk stratification. OBJECTIVE: To characterise the genomic, epigenomic, and transcriptomic features of mpMRI-visible and -nonvisible PCa in clinically localised disease. DESIGN, SETTING, AND PARTICIPANTS: Multicore analysis of fresh prostate tissue sampled immediately after radical prostatectomy was performed for intermediate- to high-risk PCa. INTERVENTION: Low-pass whole-genome, exome, methylation, and transcriptome profiling of patient tissue cores taken from microscopically benign and cancerous areas in the same prostate. Circulating free and germline DNA was assessed from the blood of five patients. OUTCOME MEASUREMENT AND STATISTICAL ANALYSIS: Correlations between preoperative mpMRI and genomic characteristics of tumour and benign prostate samples were assessed. Gene profiles for individual tumour cores were correlated with existing genomic classifiers currently used for prognostication. RESULTS AND LIMITATIONS: A total of 43 prostate cores (22 tumour and 21 benign) were profiled from six whole prostate glands. Of the 22 tumour cores, 16 were tumours visible and six were tumours nonvisible on mpMRI. Intratumour genomic, epigenomic, and transcriptomic heterogeneity was found within mpMRI-visible lesions. This could potentially lead to misclassification of patients using signatures based on copy number or RNA expression. Moreover, three of the six cores obtained from mpMRI-nonvisible tumours harboured one or more genetic alterations commonly observed in metastatic castration-resistant PCa. No circulating free DNA alterations were found. Limitations include the small cohort size and lack of follow-up. CONCLUSIONS: Our study supports the continued use of systematic prostate sampling in addition to mpMRI, as avoidance of systematic biopsies in patients with negative mpMRI may mean that clinically significant tumours harbouring genetic alterations commonly seen in metastatic PCa are missed. Furthermore, there is inconsistency in individual genomics when genomic classifiers are applied. PATIENT SUMMARY: Our study shows that tumour heterogeneity within prostate tumours visible on multiparametric magnetic resonance imaging (mpMRI) can lead to misclassification of patients if only one core is used for genomic analysis. In addition, some cancers that were missed by mpMRI had genomic aberrations that are commonly seen in advanced metastatic prostate cancer. Avoiding biopsies in mpMRI-negative cases may mean that such potentially lethal cancers are missed.

Do Brain Networks Evolve by Maximizing Their Information Flow Capacity?

We propose a working hypothesis supported by numerical simulations that brain networks evolve based on the principle of the maximization of their internal information flow capacity. We find that synchronous behavior and capacity of information flow of the evolved networks reproduce well the same behaviors observed in the brain dynamical networks of Caenorhabditis elegans and humans, networks of Hindmarsh-Rose neurons with graphs given by these brain networks. We make a strong case to verify our hypothesis by showing that the neural networks with the closest graph distance to the brain networks of Caenorhabditis elegans and humans are the Hindmarsh-Rose neural networks evolved with coupling strengths that maximize information flow capacity. Surprisingly, we find that global neural synchronization levels decrease during brain evolution, reflecting on an underlying global no Hebbian-like evolution process, which is driven by no Hebbian-like learning behaviors for some of the clusters during evolution, and Hebbian-like learning rules for clusters where neurons increase their synchronization.