Overexpression of TSPAN8 in consensus molecular subtype 3 colorectal cancer.

BACKGROUND: Recently, consensus molecular subtypes (CMSs) have been proposed as a robust transcriptome-based classification system for colorectal cancer (CRC). Tetraspanins (TSPANs) are transmembrane proteins. They have been associated with the development of numerous malignancies, including CRC, through their role as "master organizers" for multi-molecular membrane complexes. No previous study has investigated the correlation between TSPANs and CMS classification. Herein, we investigated the expression of TSPANs in patient-derived primary CRC tissues and their CMS classifications. METHODS: RNA samples were derived from primary CRC tissues (n = 100 patients diagnosed with colorectal adenocarcinoma) and subjected to RNA sequencing for transcriptome-based CMS classification and TSPAN-relevant analyses. Immunohistochemistry (IHC) and immunofluorescence (IF) stains were conducted to observe the protein expression level. To evaluate the relative biological pathways, gene-set enrichment analysis was performed. RESULTS: Of the highly expressed TSPAN genes in CRC tissues (TSPAN8, TSPAN29, and TSPAN30), TSPAN8 was notably overexpressed in CMS3-classified primary tissues. The overexpression of TSPAN8 protein in CMS3 CRC was also observed by IHC and IF staining. As a result of gene-set enrichment analysis, TSPAN8 may potentially play a role in organizing signaling complexes for kinase-based metabolic deregulation in CMS3 CRC. CONCLUSIONS: The present study reports the overexpression of TSPAN8 in CMS3 CRC. This study proposes TSPAN8 as a subtype-specific biomarker for CMS3 CRC. This finding provides a foundation for future CMS-based studies of CRC, a complex disease and the second leading cause of cancer mortality worldwide.

Comparison of mutation landscapes of pretreatment versus recurrent squamous cell carcinoma of the oral cavity: The possible mechanism of resistance to standard treatment.

BACKGROUND: A high recurrent rate of oral squamous cell carcinoma (OSCC) is a major concern in head and neck cancer treatment. The study of the genetic mutation landscape in recurrent OSCC may provide information on certain mutations associated with the pathobiology and treatment response of the OSCC. AIM: We investigated the mutation landscape of matched pretreatment and recurrent tumors to understand the influence of genetic mutations on the pathobiology and clinical outcomes in OSCC. METHODS AND RESULTS: We sequenced 33 formalin-fixed paraffin-embedded (FFPE) recurrent tumors, primary tumors, and primary tumors before recurrence that matched the recurrent tumors collected from Rajavithi Hospital during 2019-2021. We identified recurrent mutations from these samples by the Oncomine Ion Torrent-based next-generation sequencing on the 517 cancer-associated gene panel. From the results, we found that the most commonly mutated gene in the cohort is a histone methyltransferase KMT2D (54.55%), implicating that aberrance in epigenetic regulation may play a role in oral cancer tumorigenesis. Functional protein association network analysis of the gene frequently mutated in the recurrent tumors showed enrichment of genes that regulate the cancer cell cycle, that is, MRE11A, CDKN2A, and CYLD. This finding was confirmed in the primary-recurring matched pair. We found that recurrent tumors possess a small but recurring group of genes, with presumably the subclonal mutations driving the recurrence of the tumor, suggesting that the recurrent disease originated from a small fraction of the cancer cell that survives standard treatment. These genes were absent in the primary tumor with a good response to the standard treatment. On the other hand, we found an enrichment of DNA repair genes, namely ATR, BRCA1, BRCA2, RAD50, and MUTYH, in nonrecurrent tumors suggesting that the mutations in the DNA repair pathway may at least partially explain the different response to the standard treatment. CONCLUSIONS: Our pilot study identified pathways of carcinogenesis in oral cancer and specific gene sets that indicate treatment responses and prognoses in this group of patients.

Exploring extracellular matrix and prostaglandin pathway alterations across varying resection margin distances of right-sided colonic adenocarcinoma.

BACKGROUND: Surgical resection followed by indicated adjuvant therapy offers potential curative treatment in colonic adenocarcinoma. Beyond the well-established seed and soil theory of colon cancer progression, the 'normal-appearing' tissues near the tumor are not genuinely normal and remain as remnants in patients following surgery. Our objective was to elucidate the alteration of gene expression and pathways across various distances of resection margins in right-sided colonic adenocarcinoma. METHODS: Twenty-seven fresh samples of primary cancer and 56 matched non-tumor tissues adjacent to the tumor (NAT) were collected from patients with resectable right-sided colon cancer. NAT were systematically obtained at varying distances (1, 5, and 10 cm) on both proximal and distal sides. Comprehensive gene expression analysis was performed using 770-gene PanCancer Progression Panel, delineating distinctive pathways and functional predictions for each region. RESULTS: Distinctive gene signatures and pathways exhibited by normal-appearing tissues were discovered at varying distances from cancer. Notably, SFRP2, PTGDS, COL1A1, IL1B, THBS2, PTGIS, COL1A2, NPR1, and BGN were upregulated, while ENPEP, MMP1, and NRCAM were downregulated significantly in 1-cm tissue compared to farther distances. Substantial alterations in the extracellular matrix (ECM) and prostaglandin/thromboxane synthesis were significantly evident at the 1-cm distance. Functional analysis indicated enhanced cell viability and survival, alongside reduced cellular death and apoptosis. CONCLUSIONS: Different distances exerted a significant impact on gene alteration within the normal-looking mucosa surrounding primary cancer, influenced by various mechanisms. These findings may highlight potential therapeutic targets related to the ECM and prostaglandin/thromboxane pathways for treatment strategies.

Retrospective study of transcriptomic profiling identifies Thai triple-negative breast cancer patients who may benefit from immune checkpoint and PARP inhibitors.

Background: Triple-negative breast cancer (TNBC) is a rare and aggressive breast cancer subtype. Unlike the estrogen receptor-positive subtype, whose recurrence risk can be predicted by gene expression-based signature, TNBC is more heterogeneous, with diverse drug sensitivity levels to standard regimens. This study explored the benefit of gene expression-based profiling for classifying the molecular subtypes of Thai TNBC patients. Methods: The nCounter-based Breast 360 gene expression was used to classify Thai TNBC retrospective cohort subgroups. Their expression profiles were then compared against the previously established TNBC classification system. The differential characteristics of the tumor microenvironment and DNA damage repair signatures across subgroups were also explored. Results: Thai TNBC cohort could be classified into four main subgroups, corresponding to the LAR, BL-2, and M subtypes based on Lehmann's TNBC classification. The PAM50 gene set classified most samples as basal-like subtypes except for Group 1. Group 1 exhibited similar enrichment of the metabolic and hormone response pathways to the LAR subtype. Group 2 shared pathway activation with the BL-2 subtype. Group 3 showed an increase in the EMT pathway, similar to the M subtype. Group 4 showed no correlation with Lehmann's TNBC. The tumor microenvironment (TME) analysis showed high TME cell abundance with increased expression of immune blockade genes in Group 2. Group 4 exhibited low TME cell abundance and reduced immune blockade gene expressions. We also observed distinct signatures of the DNA double-strand break repair genes in Group 1. Conclusions: Our study reported unique characteristics between the four TNBC subgroups and showed the potential use of immune checkpoint and PARP inhibitors in subsets of Thai TNBC patients. Our findings warrant further clinical investigation to validate TNBC's sensitivity to these regimens.

The KRAS-Mutant Consensus Molecular Subtype 3 Reveals an Immunosuppressive Tumor Microenvironment in Colorectal Cancer.

Colorectal cancers (CRC) with KRAS mutations (KRASmut) are frequently included in consensus molecular subtype 3 (CMS3) with profound metabolic deregulation. We explored the transcriptomic impact of KRASmut, focusing on the tumor microenvironment (TME) and pathways beyond metabolic deregulation. The status of KRASmut in patients with CRC was investigated and overall survival (OS) was compared with wild-type KRAS (KRASwt). Next, we identified CMS, and further investigated differentially expressed genes (DEG) of KRASmut and distinctive pathways. Lastly, we used spatially resolved gene expression profiling to define the effect of KRASmut in the TME regions of CMS3-classified CRC tissues. CRC patients with KRASmut were mainly enriched in CMS3. Their specific enrichments of immune gene signatures in immunosuppressive TME were associated with worse OS. Activation of TGFß signaling by KRASmut was related to reduced pro-inflammatory and cytokine gene signatures, leading to suppression of immune infiltration. Digital spatial profiling in TME regions of KRASmut CMS3-classified tissues suggested up-regulated genes, CD40, CTLA4, ARG1, STAT3, IDO, and CD274, that could be characteristic of immune suppression in TME. This study may help to depict the complex transcriptomic profile of KRASmut in immunosuppressive TME. Future studies and clinical trials in CRC patients with KRASmut should consider these transcriptional landscapes.

Combining the SMAC mimetic LCL161 with Gemcitabine plus Cisplatin therapy inhibits and prevents the emergence of multidrug resistance in cholangiocarcinoma.

Cholangiocarcinoma (CCA) is a highly lethal gastrointestinal malignancy that has one of the worst prognoses among solid tumors. The combination of Gemcitabine + Cisplatin (GEM/CIS) remains the standard first-line treatment for advanced stage CCA. However, this drug combination yields only a modest objective response rate, and in cases that initially respond to this treatment, drug resistance commonly rapidly develops. To improve the efficiency of GEM/CIS therapy for CCA, a thorough understanding of the mechanism of GEM/CIS resistance in CCA is required. To that end - in this study, we developed several acquired GEM/CIS-resistant CCA cell lines and we screened those cell lines for acquired vulnerability. The screening process revealed that subset of CCA with GEM/CIS resistance acquired vulnerability to the small-molecule second mitochondrial-derived activator of caspases (SMAC) mimetics LCL161 and Birinapant. The observed acquired vulnerability was found to be associated with upregulation of an inhibitor of apoptosis protein 2 (cIAP2), a known target of SMAC mimetics. LCL161 or cIAP2-shRNA downregulated cIAP2 and restored the sensitivity to GEM/CIS in GEM/CIS-resistant CCA cell lines and in in vivo GEM/CIS-resistant xenograft models. A strong synergic effect was observed when LCL161 was added to GEM/CIS. Interestingly, this synergism was also observed in drug-naïve CCA cell lines, xenografts, and patient-derived organoids. This triplet therapy also prevented the emergence of multidrug-resistant CCA in in vitro and in vivo models. Our findings suggest that activation of cIAP2 allows CCA to escape GEM/CIS, and that suppression of cIAP2 reestablishes the apoptotic profile of CCA, thus restoring its vulnerability to GEM/CIS. The results of this study indicate that combining the SMAC mimetic LCL161 with GEM/CIS inhibits and prevents the emergence of multidrug resistance in CCA.

Molecular Mechanisms behind Safranal's Toxicity to HepG2 Cells from Dual Omics.

The spice saffron (Crocus sativus) has anticancer activity in several human tissues, but the molecular mechanisms underlying its potential therapeutic effects are poorly understood. We investigated the impact of safranal, a small molecule secondary metabolite from saffron, on the HCC cell line HepG2 using untargeted metabolomics (HPLC-MS) and transcriptomics (RNAseq). Increases in glutathione disulfide and other biomarkers for oxidative damage contrasted with lower levels of the antioxidants biliverdin IX (139-fold decrease, p = 5.3 × 105), the ubiquinol precursor 3-4-dihydroxy-5-all-trans-decaprenylbenzoate (3-fold decrease, p = 1.9 × 10-5), and resolvin E1 (-3282-fold decrease, p = 45), which indicates sensitization to reactive oxygen species. We observed a significant increase in intracellular hypoxanthine (538-fold increase, p = 7.7 × 10-6) that may be primarily responsible for oxidative damage in HCC after safranal treatment. The accumulation of free fatty acids and other biomarkers, such as S-methyl-5'-thioadenosine, are consistent with safranal-induced mitochondrial de-uncoupling and explains the sharp increase in hypoxanthine we observed. Overall, the dual omics datasets describe routes to widespread protein destabilization and DNA damage from safranal-induced oxidative stress in HCC cells.

Corrigendum: Combining the SMAC mimetic LCL161 with Gemcitabine plus Cisplatin therapy inhibits and prevents the emergence of multidrug resistance in cholangiocarcinoma.

[This corrects the article DOI: 10.3389/fonc.2022.1021632.].

High-Throughput Metabolic Profiling for Model Refinements of Microalgae.

Metabolic models are reconstructed based on an organism's available genome annotation and provide predictive tools to study metabolic processes at a systems-level. Genome-scale metabolic models may include gaps as well as reactions that are unverified experimentally. Reconstructed models of newly isolated microalgal species will result in weaknesses due to these gaps, as there is usually sparse biochemical evidence available for the metabolism of such isolates. The phenotype microarray (PM) technology is an effective, high-throughput method that functionally determines cellular metabolic activities in response to a wide array of entry metabolites. Combining the high throughput phenotypic assays with metabolic modeling can allow existing metabolic network models to be rapidly reconstructed or optimized by providing biochemical evidence to support and expand genomic evidence. This work will show the use of PM assays for the study of microalgae by using the green microalgal model species Chlamydomonas reinhardtii as an example. Experimental evidence for over 254 reactions obtained by PM was used in this study to expand and refine a genome-scale C. reinhardtii metabolic network model, iRC1080, by approximately 25 percent. The protocol created here can be used as a basis for functionally profiling the metabolism of other microalgae, including known microalgae mutants and new isolates.

Metabolic reprogramming of terminally exhausted CD8+ T cells by IL-10 enhances anti-tumor immunity.

T cell exhaustion presents one of the major hurdles to cancer immunotherapy. Among exhausted CD8+ tumor-infiltrating lymphocytes, the terminally exhausted subset contributes directly to tumor cell killing owing to its cytotoxic effector function. However, this subset does not respond to immune checkpoint blockades and is difficult to be reinvigorated with restored proliferative capacity. Here, we show that a half-life-extended interleukin-10-Fc fusion protein directly and potently enhanced expansion and effector function of terminally exhausted CD8+ tumor-infiltrating lymphocytes by promoting oxidative phosphorylation, a process that was independent of the progenitor exhausted T cells. Interleukin-10-Fc was a safe and highly efficient metabolic intervention that synergized with adoptive T cell transfer immunotherapy, leading to eradication of established solid tumors and durable cures in the majority of treated mice. These findings show that metabolic reprogramming by upregulating mitochondrial pyruvate carrier-dependent oxidative phosphorylation can revitalize terminally exhausted T cells and enhance the response to cancer immunotherapy.

Large-scale genome sequencing reveals the driving forces of viruses in microalgal evolution.

Being integral primary producers in diverse ecosystems, microalgal genomes could be mined for ecological insights, but representative genome sequences are lacking for many phyla. We cultured and sequenced 107 microalgae species from 11 different phyla indigenous to varied geographies and climates. This collection was used to resolve genomic differences between saltwater and freshwater microalgae. Freshwater species showed domain-centric ontology enrichment for nuclear and nuclear membrane functions, while saltwater species were enriched in organellar and cellular membrane functions. Further, marine species contained significantly more viral families in their genomes (p = 8e-4). Sequences from Chlorovirus, Coccolithovirus, Pandoravirus, Marseillevirus, Tupanvirus, and other viruses were found integrated into the genomes of algal from marine environments. These viral-origin sequences were found to be expressed and code for a wide variety of functions. Together, this study comprehensively defines the expanse of protein-coding and viral elements in microalgal genomes and posits a unified adaptive strategy for algal halotolerance.

GPCR Genes as Activators of Surface Colonization Pathways in a Model Marine Diatom.

Surface colonization allows diatoms, a dominant group of phytoplankton in oceans, to adapt to harsh marine environments while mediating biofoulings to human-made underwater facilities. The regulatory pathways underlying diatom surface colonization, which involves morphotype switching in some species, remain mostly unknown. Here, we describe the identification of 61 signaling genes, including G-protein-coupled receptors (GPCRs) and protein kinases, which are differentially regulated during surface colonization in the model diatom species, Phaeodactylum tricornutum. We show that the transformation of P. tricornutum with constructs expressing individual GPCR genes induces cells to adopt the surface colonization morphology. P. tricornutum cells transformed to express GPCR1A display 30% more resistance to UV light exposure than their non-biofouling wild-type counterparts, consistent with increased silicification of cell walls associated with the oval biofouling morphotype. Our results provide a mechanistic definition of morphological shifts during surface colonization and identify candidate target proteins for the screening of eco-friendly, anti-biofouling molecules.

Potential for Heightened Sulfur-Metabolic Capacity in Coastal Subtropical Microalgae.

The activities of microalgae support nutrient cycling that helps to sustain aquatic and terrestrial ecosystems. Most microalgal species, especially those from the subtropics, are genomically uncharacterized. Here we report the isolation and genomic characterization of 22 microalgal species from subtropical coastal regions belonging to multiple clades and three from temperate areas. Halotolerant strains including Halamphora, Dunaliella, Nannochloris, and Chloroidium comprised the majority of these isolates. The subtropical-based microalgae contained arrays of methyltransferase, pyridine nucleotide-disulfide oxidoreductase, abhydrolase, cystathionine synthase, and small-molecule transporter domains present at high relative abundance. We found that genes for sulfate transport, sulfotransferase, and glutathione S-transferase activities were especially abundant in subtropical, coastal microalgal species and halophytic species in general. Our metabolomics analyses indicate lineage- and habitat-specific sets of biomolecules implicated in niche-specific biological processes. This work effectively expands the collection of available microalgal genomes by ∼50%, and the generated resources provide perspectives for studying halophyte adaptive traits.

Safranal induces DNA double-strand breakage and ER-stress-mediated cell death in hepatocellular carcinoma cells.

Poor prognoses remain the most challenging aspect of hepatocellular carcinoma (HCC) therapy. Consequently, alternative therapeutics are essential to control HCC. This study investigated the anticancer effects of safranal against HCC using in vitro, in silico, and network analyses. Cell cycle and immunoblot analyses of key regulators of cell cycle, DNA damage repair and apoptosis demonstrated unique safranal-mediated cell cycle arrest at G2/M phase at 6 and 12 h, and at S-phase at 24 h, and a pronounced effect on DNA damage machinery. Safranal also showed pro-apoptotic effect through activation of both intrinsic and extrinsic initiator caspases; indicating ER stress-mediated apoptosis. Gene set enrichment analysis provided consistent findings where UPR is among the top terms of up-regulated genes in response to safranal treatment. Thus, proteins involved in ER stress were regulated through safranal treatment to induce UPR in HepG2 cells.

A computational framework for complex disease stratification from multiple large-scale datasets.

BACKGROUND: Multilevel data integration is becoming a major area of research in systems biology. Within this area, multi-'omics datasets on complex diseases are becoming more readily available and there is a need to set standards and good practices for integrated analysis of biological, clinical and environmental data. We present a framework to plan and generate single and multi-'omics signatures of disease states. METHODS: The framework is divided into four major steps: dataset subsetting, feature filtering, 'omics-based clustering and biomarker identification. RESULTS: We illustrate the usefulness of this framework by identifying potential patient clusters based on integrated multi-'omics signatures in a publicly available ovarian cystadenocarcinoma dataset. The analysis generated a higher number of stable and clinically relevant clusters than previously reported, and enabled the generation of predictive models of patient outcomes. CONCLUSIONS: This framework will help health researchers plan and perform multi-'omics big data analyses to generate hypotheses and make sense of their rich, diverse and ever growing datasets, to enable implementation of translational P4 medicine.

Intracellular spectral recompositioning of light enhances algal photosynthetic efficiency.

Diatoms, considered as one of the most diverse and largest groups of algae, can provide the means to reach a sustainable production of petrochemical substitutes and bioactive compounds. However, a prerequisite to achieving this goal is to increase the solar-to-biomass conversion efficiency of photosynthesis, which generally remains less than 5% for most photosynthetic organisms. We have developed and implemented a rapid and effective approach, herein referred to as intracellular spectral recompositioning (ISR) of light, which, through absorption of excess blue light and its intracellular emission in the green spectral band, can improve light utilization. We demonstrate that ISR can be used chemogenically, by using lipophilic fluorophores, or biogenically, through the expression of an enhanced green fluorescent protein (eGFP) in the model diatom Phaeodactylum tricornutum. Engineered P. tricornutum cells expressing eGFP achieved 28% higher efficiency in photosynthesis than the parental strain, along with an increased effective quantum yield and reduced nonphotochemical quenching (NPQ) induction levels under high-light conditions. Further, pond simulator experiments demonstrated that eGFP transformants could outperform their wild-type parental strain by 50% in biomass production rate under simulated outdoor sunlight conditions. Transcriptome analysis identified up-regulation of major photosynthesis genes in the engineered strain in comparison with the wild type, along with down-regulation of NPQ genes involved in light stress response. Our findings provide a proof of concept for a strategy of developing more efficient photosynthetic cell factories to produce algae-based biofuels and bioactive products.

The genome and phenome of the green alga Chloroidium sp. UTEX 3007 reveal adaptive traits for desert acclimatization.

To investigate the phenomic and genomic traits that allow green algae to survive in deserts, we characterized a ubiquitous species, Chloroidium sp. UTEX 3007, which we isolated from multiple locations in the United Arab Emirates (UAE). Metabolomic analyses of Chloroidium sp. UTEX 3007 indicated that the alga accumulates a broad range of carbon sources, including several desiccation tolerance-promoting sugars and unusually large stores of palmitate. Growth assays revealed capacities to grow in salinities from zero to 60 g/L and to grow heterotrophically on >40 distinct carbon sources. Assembly and annotation of genomic reads yielded a 52.5 Mbp genome with 8153 functionally annotated genes. Comparison with other sequenced green algae revealed unique protein families involved in osmotic stress tolerance and saccharide metabolism that support phenomic studies. Our results reveal the robust and flexible biology utilized by a green alga to successfully inhabit a desert coastline.

Algal Cell Factories: Approaches, Applications, and Potentials.

With the advent of modern biotechnology, microorganisms from diverse lineages have been used to produce bio-based feedstocks and bioactive compounds. Many of these compounds are currently commodities of interest, in a variety of markets and their utility warrants investigation into improving their production through strain development. In this review, we address the issue of strain improvement in a group of organisms with strong potential to be productive "cell factories": the photosynthetic microalgae. Microalgae are a diverse group of phytoplankton, involving polyphyletic lineage such as green algae and diatoms that are commonly used in the industry. The photosynthetic microalgae have been under intense investigation recently for their ability to produce commercial compounds using only light, CO2, and basic nutrients. However, their strain improvement is still a relatively recent area of work that is under development. Importantly, it is only through appropriate engineering methods that we may see the full biotechnological potential of microalgae come to fruition. Thus, in this review, we address past and present endeavors towards the aim of creating productive algal cell factories and describe possible advantageous future directions for the field.

Systems level analysis of the Chlamydomonas reinhardtii metabolic network reveals variability in evolutionary co-conservation.

Metabolic networks, which are mathematical representations of organismal metabolism, are reconstructed to provide computational platforms to guide metabolic engineering experiments and explore fundamental questions on metabolism. Systems level analyses, such as interrogation of phylogenetic relationships within the network, can provide further guidance on the modification of metabolic circuitries. Chlamydomonas reinhardtii, a biofuel relevant green alga that has retained key genes with plant, animal, and protist affinities, serves as an ideal model organism to investigate the interplay between gene function and phylogenetic affinities at multiple organizational levels. Here, using detailed topological and functional analyses, coupled with transcriptomics studies on a metabolic network that we have reconstructed for C. reinhardtii, we show that network connectivity has a significant concordance with the co-conservation of genes; however, a distinction between topological and functional relationships is observable within the network. Dynamic and static modes of co-conservation were defined and observed in a subset of gene-pairs across the network topologically. In contrast, genes with predicted synthetic interactions, or genes involved in coupled reactions, show significant enrichment for both shorter and longer phylogenetic distances. Based on our results, we propose that the metabolic network of C. reinhardtii is assembled with an architecture to minimize phylogenetic profile distances topologically, while it includes an expansion of such distances for functionally interacting genes. This arrangement may increase the robustness of C. reinhardtii's network in dealing with varied environmental challenges that the species may face. The defined evolutionary constraints within the network, which identify important pairings of genes in metabolism, may offer guidance on synthetic biology approaches to optimize the production of desirable metabolites.

The in vitro selection world.

Through iterative cycles of selection, amplification, and mutagenesis, in vitro selection provides the ability to isolate molecules of desired properties and function from large pools (libraries) of random molecules with as many as 10(16) distinct species. This review, in recognition of a quarter of century of scientific discoveries made through in vitro selection, starts with a brief overview of the method and its history. It further covers recent developments in in vitro selection with a focus on tools that enhance the capabilities of in vitro selection and its expansion from being purely a nucleic acids selection to that of polypeptides and proteins. In addition, we cover how next generation sequencing and modern biological computational tools are being used to complement in vitro selection experiments. On the very least, sequencing and computational tools can translate the large volume of information associated with in vitro selection experiments to manageable, analyzable, and exploitable information. Finally, in vivo selection is briefly compared and contrasted to in vitro selection to highlight the unique capabilities of each method.